NEGAR NOORI
POLICY
TRANSPLANTATIONFOR
SMARTCITYINITIATIVES
ERASMUS UNIVERSITY OF ROTTERDAM
i
POLICY TRANSPLANTATION
FOR
S
MART CITY INITIATIVES
ii Contents
Contents iii
POLICY TRANSPLANTATION
FOR
SMART
CITY INITIATIVES
BELEIDSTRANSPLANTATIE
VOOR
SLIMME STADSINITIATIEVEN
Dissertation
Proefschrift
for the purpose of obtaining the degree of doctor
at Erasmus University of Rotterdam
by the authority of the Rector Magnificus Prof.dr. F.A. van der Duijn Schouten
and in accordance with the decision of the Doctorate Board.
The public defence shall be held on
March 19, 2021 at 10:30 hrs
by
Negar Noori
Born in Ahvaz, Iran
iv Contents
This dissertation has been approved by the promotors.
Composition of the doctoral committee:
Prof. dr. W. M de Jong
Promotor
Prof. dr. E. Stamhuis
Promotor
Other member:
Prof. dr. M. Janssen
Prof. dr. A. Meijer
Prof. dr. A. Arcuri
Co-promotor:
Dr. T. Hoppe
This research was funded by the Erasmus research initiative of ‘Dynamics of Inclusive
Prosperity’.
Copyright © 2021 by Negar Noori
Cover design by Negar Noori
Printed by: GildePrint
ISBN: 978-94-6419-174-5
Contents v
To
My family
vi Contents
CONTENTS
CONTENTS .......................................................................................................................... VI
SUMMARY ........................................................................................................................... XI
SAMENVATTING ................................................................................................................ XV
1 INTRODUCTION ................................................................................................................. 1
1.1. RESEARCH MOTIVATION .............................................................................................. 2
1.2. CONCEPTUAL REALM AND INTERDISCIPLINARY ........................................................ 3
1.2.1. Ecological modernization and urban policies ................................................... 3
1.2.2. Smart City policy as the dominant approach.................................................... 6
1.2.3. Provisioning a Successful Smart City development process .......................... 7
1.2.4. Cross city lesson drawing on Smart City development .................................. 8
1.2.5. Where to look for a lesson: good practices of Smart Cities ............................. 9
And Where to transplant policies: an example of Smart City initiatives ............ 9
1.3. RESEARCH AIMS AND RESEARCH QUESTIONS ........................................................... 10
1.4. RESEARCH METHODOLOGY ........................................................................................ 11
1.5. THE INNOVATIVE ASPECTS OF THE STUDY ............................................................... 13
1.6. RESEARCH STRUCTURE ............................................................................................... 14
2 TOWARDS CREDIBLE CITY BRANDING PRACTICES: HOW DO IRAN’S LARGEST CITIES
FACE ECOLOGICAL MODERNIZATION? ............................................................................ 17
2.1. INTRODUCTION ........................................................................................................... 18
2.2. THE CREDIBILITY OF CITY BRANDS: THEORY ........................................................... 19
2.3. THE CREDIBILITY OF CITY BRANDS: METHOD.......................................................... 22
2.4. THE MAIN FEATURES OF IRAN’S MEGACITIES IN BRIEF .......................................... 25
2.5. CITY BRANDING PRACTICES IN IRAN’S FIFTEEN MEGACITIES ................................ 30
Contents vii
2.6. CONCLUSION ............................................................................................................... 39
3 INPUT-OUTPUT MODELLING FOR SMART CITY DEVELOPMENT ................................. 41
3.1. INTRODUCTION ........................................................................................................... 42
3.2. POSITIONING AND PINPOINTING KEY FACETS OF THE SMART CITY ...................... 46
3.3. CONCEPTUAL MODEL ................................................................................................. 52
3.3.1. Input ..................................................................................................................... 53
3.3.1.1 Modern ICT Infrastructure: Internet of Things ........................................ 53
3.3.1.2 Data ................................................................................................................ 53
3.3.1.3 Human Resources and Entrepreneurship ................................................. 54
3.3.1.4 Financial Resources ...................................................................................... 54
3.3.2. Throughput .......................................................................................................... 55
3.3.3. Output .................................................................................................................. 57
3.3.3.1 Smart Applications ....................................................................................... 57
3.3.3.2 Externalities ................................................................................................... 58
3.4. ILLUSTRATIVE CASE STUDY: SMART DUBAI; THE HAPPIEST CITY ......................... 59
3.5. DISCUSSION AND CONCLUSION ................................................................................ 63
4 CLASSIFYING PATHWAYS FOR SMART CITY DEVELOPMENT: COMPARING DESIGN,
GOVERNANCE AND IMPLEMENTATION IN AMSTERDAM, BARCELONA, DUBAI, AND
ABU DHABI ......................................................................................................................... 67
4.1. INTRODUCTION ........................................................................................................... 68
4.2. RESEARCH BACKGROUND .......................................................................................... 69
4.2.1. Design Choices for the Resources of Smart City Development .................... 69
4.2.2. Design Choices for the Throughputs ............................................................... 71
4.2.3. Design Choices for the Applications of Smart City Development ............... 72
4.3. RESEARCH DESIGN AND METHODOLOGY ................................................................. 73
4.3.1. Case Selection ...................................................................................................... 76
4.3.2. Data Collection .................................................................................................... 76
4.3.3. Data Analysis and Operationalization ............................................................. 76
viii Contents
4.4. A BRIEF DESCRIPTION OF THE CASES ........................................................................ 78
4.4.1. Masdar City ......................................................................................................... 78
4.4.2. Amsterdam Smart City ...................................................................................... 79
4.4.3. Barcelona Digital (Smart) City .......................................................................... 79
4.4.4. Smart Dubai ......................................................................................................... 79
4.5. RESULTS ....................................................................................................................... 80
4.5.1. Design Input Choices ......................................................................................... 80
4.5.1.1 Masdar ........................................................................................................... 80
4.5.1.2 Amsterdam .................................................................................................... 80
4.5.1.3 Barcelona ....................................................................................................... 81
4.5.1.4 Dubai .............................................................................................................. 82
4.5.2. Design Throughput Choices.............................................................................. 83
4.5.2.1 Masdar ........................................................................................................... 83
4.5.2.2 Amsterdam .................................................................................................... 84
4.5.2.3 Barcelona ....................................................................................................... 86
4.5.2.4 Dubai .............................................................................................................. 87
4.5.3. Applications and Externalities .......................................................................... 88
4.5.3.1 Masdar ........................................................................................................... 88
4.5.3.2 Amsterdam .................................................................................................... 89
4.5.3.3 Barcelona ....................................................................................................... 90
4.5.3.4 Dubai .............................................................................................................. 90
4.6. TOWARDS A CLASSIFICATION OF SMART CITY DEVELOPMENT PATHWAYS.......... 92
4.7. CONCLUSION ............................................................................................................... 95
5 TOWARDS AN INTEGRATED FRAMEWORK TO MEASURE SMART CITY READINESS:
THE CASE OF IRANIAN CITIES ........................................................................................... 99
5.1. INTRODUCTION ......................................................................................................... 100
5.2. TRANSITION TOWARDS A SMART CITY AND READINESS FOR CHANGE .............. 102
5.2.1. Urban Transition ............................................................................................... 102
Contents ix
5.2.2. Technological Readiness .................................................................................. 103
5.2.3. Socio-economic Readiness ............................................................................... 105
5.2.4. Political Readiness ............................................................................................ 106
5.3. RESEARCH DESIGN AND METHODS ......................................................................... 108
5.3.1. Data Collection .................................................................................................. 108
5.3.2. Data Analysis and Theory of Change ............................................................ 109
5.4. IRANIAN SMART CITY DEVELOPMENT: SMART CITY READINESS......................... 110
5.4.1. Technological Readiness .................................................................................. 111
5.4.2. Socio-economical Readiness ............................................................................ 112
5.4.3. Political Readiness ............................................................................................ 114
5.5. IRANIAN SMART CITY DEVELOPMENT: VISION AND EXPECTATIONS .................. 116
5.6. CONCLUSION ............................................................................................................. 124
6 INTRODUCING A CONCEPTUAL FRAMEWORK TO ANALYZE SMART CITY POLICY
TRANSPLANTATION
.......................................................................................................... 127
6.1. INTRODUCTION ......................................................................................................... 128
6.2. THEORY AND PRACTICE ASSOCIATED WITH POLICY TRAVEL ................................. 130
6.3. A FRAMEWORK FOR THE SMART CITY POLICY TRANSPLANTATION ANALYSIS .... 134
6.4. THE SMART CITY POLICY TRANSPLANTATION MODEL ........................................... 135
6.4.1. Phase 1: Recipient preparation for Smart City transplantation .................. 138
6.4.2. Phase 2: Learning from good practice ............................................................ 138
6.4.3. Phase 3: Transferring policies from good practices to the recipient .......... 139
6.4.4. Phase 4: Adoption of Smart City policy by the recipient and transplanting
policies .......................................................................................................................... 140
6.5. CONCLUSION ............................................................................................................. 141
7 CONCLUSIONS & FUTURE PERSPECTIVES .................................................................... 143
7.1. CONCLUSIONS ........................................................................................................... 144
x Contents
7.1.1. Sub-question one: How do cities engage city branding practices when
facing ecological modernization? To what extent do they use ‘smart’ in their
brands and how? ......................................................................................................... 145
7.1.2. Sub-question two: What does a conceptual model representing different
domains of the Smart City look like? ....................................................................... 147
7.1.3. Sub-question three: How do Smart Cities differ from each other in terms of
their resources goals and developmeNt pathway? ................................................ 149
7.1.4. Sub-question four: How to determine whether cities are ready to transition
into Smart Cities? ........................................................................................................ 152
7.1.5. Sub-question five: How can Smart City policies be transplanted from cities
hosting good practices to cities where Smart City initiatives are to take place? 155
7.2. POLICY RECOMMENDATIONS ................................................................................... 158
7.3. SCIENTIFIC CONTRIBUTION ...................................................................................... 159
7.4. LIMITATIONS ............................................................................................................. 161
7.5. FUTURE PERSPECTIVES .............................................................................................. 161
A APPENDIX ...................................................................................................................... 163
A.1. A ............................................................................................................................ 163
REFERENCES ...................................................................................................................... 173
ACKNOWLEDGMENTS ...................................................................................................... 207
CURRICULUM VITAE ........................................................................................................ 209
LIST OF PUBLICATIONS .................................................................................................... 211
PHD TRAJECTORY ............................................................................................................ 212
WORK AND RESEARCH ACTIVITIES ............................................................................... 212
xi
SUMMARY
City branding is increasingly practiced in cities with a strong drive to engage
in urban (re)development in the post-oil era through enhancing ‘ecological modern-
ization’. One of the most popular brands among them is ‘Smart City’, however, some
of the adopted city branding strategies lack sophistication. The first challenge ahead
for those cities aiming to profile themselves as ‘Smart’ is to credibly brand them-
selves and let this brand become the cornerstone for a transition towards a future
city. Although there are an infinite number of city brands and at least thirty-five city
labels distinguished in the literature (Schraven et al. 2021), still there is no frame-
work to examine city brand credibility.
In the past decade, the popularity of using Smart City labels for sustainable
techno-driven urbanization has increased dramatically. Several generations of Smart
City constructs have emerged so far, and the concept has evolved and broadened in
meaning. Although this broader scope has allowed for proper response to many crit-
icisms of the Smart City, including the over-emphasis on technology, it has added
to the complexity of the concept. The most significant consequence of this vagueness
is that the policy implication underlying Smart City development have become puz-
zling for both policymakers and practitioners. Despite the fact that no model can
cover all different aspects of Smart City development, models can simplify reality
constructively and allow for better understanding of its various facets. Although
there are numerous analytical models of the Smart City in areas such as the engi-
neering and management of IoT platforms, no such model exists looking at Smart
City development as a process with viable policy design choices that can be used as
an intermediary tool between policymakers and practitioners.
Recently in numerous countries around the world, policy makers in urban areas
pay a lot of attention to the programs associated with the development of Smart
Cities. Many urban managers, however, are now just beginning to learn how to ‘do’
Smart City development. Nevertheless, building such an advanced techno-driven
city seems very expensive and cities that are just getting started can potentially make
it cost-effective through a learning process by technology, policy and experiences
transfer and avoid having to reinvent the wheel. In the quest for smart city develop-
ment, numerous examples of ‘best practices’ have been created and circulated in na-
tional and international arenas. Learning from good practices is a perennial aspect
of human development. It is adopted in the Smart City realm aligned with the wider
xii Summary
stream of political science and urban policy studies. There are abundant indices to
rank Smart City good practices, and extensive studies on lessons that can be learned
from them have been conducted. Nonetheless, a comprehensive framework for an-
alyzing lessons from Smart City good practices in a systematic way is missing.
Cities running Smart City programs seem to want a lot, but do not always
know how to do it, and intend to learn from leading Smart Cities running good prac-
tices projects. The assumption underlying this research is that they can do so, but
must realize that first, the readiness for becoming Smart is crucial and second, the
political, legal, institutional and cultural context in donor countries are different.
Context plays an important role and transferring lessons and policies is not some-
thing that occurs in a vacuum. First of all, transforming a city into a Smart City re-
quires consideration of the readiness of a city for the change. The existing studies on
Smart City readiness are mostly focused on technological readiness. Whereas the
evidence shows social and political readiness are just as crucial as technological
readiness, if not more so. Furthermore, taking steps in the complicated process of
travelling policies (from donor countries to the recipient) requires a comprehensive
framework to show pathways, and/or roadmaps.
To address these challenges and gaps the author first examines what indicators
can be used for evaluating the credibility of city brands and apply these to the ‘Smart
City’ brand. The proposed ‘brand credibility evaluation' framework applies to Ira-
nian large cities which are our candidate recipients for adopting Smart City policies
from good practices in this research. The results indicate that four large Iranian cities
have a credible ‘Smart City brand’ that justifies their use as illustrative examples for
Smart City policy transplantation. Then an Input-Output (IO) model of the Smart
City development process helping policy makers and analysts make informed de-
sign choices is developed. The IO model translates required key resources, the capa-
bilities of transforming resources to intended applications, and the desired applica-
tion of this development process into inputs, throughputs, and outputs. In the next
step the (IO) model is used to retrieve which design variables are at play and lead to
which output in the following Smart City projects: Smart Dubai, Masdar City, Bar-
celona Smart City, and Amsterdam Smart City. In fact, a Smart City design frame-
work is developed based on the (IO) model which is used as a tool to analyze Smart
City good practices. The results of analyzing the four cases (Amsterdam, Barcelona,
Masdar, and Dubai) indicate in which ways their Smart City development pathways
are different. In the next step, a framework for assessing Smart City readiness is pre-
sented to develop a Theory of Change for recipient cities to be ready for becoming
‘Smart’. The framework is applied to the examples of the recipient cities (four large
Iranian cities with a credible brand of ‘Smart’) to examine their readiness for becom-
ing Smart. Here, I find that political readiness is the main challenge for Iranian cities.
Summary xiii
And finally, all the conceptual and theoretical frameworks mentioned enabled the
author to propose a comprehensive framework to analyze ’travelling’ Smart City
policy from donor countries to recipients; i.e. the so-called ‘Smart City Policy Trans-
plantation’ framework. This framework is the first comprehensive one for Smart
City policy travelling that uses the term ‘Transplantation’ inspired by comparative
law (legal transplantation) and political science (institutional transplantation). The
main idea behind using this terminology is that ‘The Smart City Policy Transplanta-
tion’ framework is not only about the policy traveling but also accommodating of
the policy travel.
Chapter 1 (Introduction) introduces the reader to the general concepts, theories
and approaches associated with the Smart City development policy. It introduces
the theory of Ecological Modernization as the source of the emergence of the concept
of future cities’ brands and the most popular one among them; Smart City develop-
ment policy with the issue of vagueness in its implementation.
Chapter 2 (Towards credible city branding practices) examines the credibility
of cities’ brands facing ecological modernization. It also deals with recognizing the
credible brand of ‘Smart’ among those cities that profile themselves as ‘Smart’. Much
of the future-proof city policies have started from branding practices, and as such
represents an important chapter.
Chapter 3 (Input-output modeling of Smart City) deals especially with the
Smart City development process and applies a system thinking to map the process.
It first provides an overview of the Smart City's various definitions, classifications,
and domains. Then translates various facets of its development process into inputs,
throughputs, and outputs helping its implementation.
Chapter 4 (Classifying pathways for Smart City development) presents an inte-
grated framework for the Smart City design choices based on the IO model as a tool
to analyze and compare various Smart City good practices and their development
pathways.
Chapter 5 (Towards an integrated framework for Smart City readiness) classi-
fies indicators, factors, and practices for Smart City readiness into technological, so-
cio-economic, and political readiness parameters. It also deals with how to develop
a theory of change for cities to become ready to be ‘Smart’.
Chapter 6 (A conceptual framework for Smart City policy transplantation) de-
scribes the mechanism of policy transplantation from good practices to a Smart City
initiative that is the main ambition of the present study to help them initiate their
Smart City program.
Chapter 7 (Conclusion) covers the responses to the research questions and some
policy recommendations for the Smart City initiatives and those cities that are just
started their Smart City program.
xiv Summary
xv
SAMENVATTING
City branding wordt steeds meer toegepast in steden met een sterke drive om
deel te nemen aan stedelijke (her)ontwikkeling in het post-olietijdperk door het ver-
sterken van ‘ecologische modernisering’. Een van de meest populaire merken daar-
van is ‘Slim’(smart). Maar sommige van de gebruikte city branding-strategieën zijn
weinig verfijnd. De eerste uitdaging voor die steden die zich willen prositioneren
als ‘Smart’ is om zichzelf geloofwaardig te profileren en zo het fundament onder de
transitie naar een toekomstige stad te bouwen. Hoewel er meer dan twintig stads-
merken in de literatuur zijn, is er nog steeds geen raamwerk om de geloofwaar-
digheid van stadsmerken te onderzoeken en hoe een stad zichzelf geloofwaardig
kan etiketteren als ‘smart’.
In het afgelopen decennium is de populariteit van het gebruik van Slimme
steden-labels voor duurzame, technologie-gestuurde verstedelijking fors toege-
nomen. Er zijn tot nu toe verschillende generaties Smart City-constructies ontstaan
en het concept is geëvolueerd en breder geworden. Hoewel deze bredere reikwijdte
een reactie was op kritiek op de Smart City, waaronder de te grote nadruk op tech-
nologie, heeft het de complexiteit van het concept vergroot. Het belangrijkste gevolg
van deze vaagheid is dat de implementatie van het Smart City-ontwikkelingsbeleid
een raadsel wordt voor zowel beleidsmakers als praktijkmensen. Ondanks het feit
dat geen enkel model alle verschillende aspecten van de Smart City-ontwikkeling
kan dekken, kunnen modellen de realiteit vereenvoudigen om de verschillende fac-
etten ervan beter te begrijpen. Er zijn weliswaartalloze modellen in de hoofdcate-
gorieen van de Smart City, maarer ontbreekt een model dat kijkt naar het proces van
de Smart City-ontwikkeling. Zo een model kan met een pragmatische benadering
een rol spelen als intermediair tussen beleidsmakers en praktijkmensen.
Tegenwoordig besteden beleidsmakers in stedelijke gebieden in tal van landen
over de hele wereld veel aandacht aan de programma's rond de ontwikkeling van
zogenaamde ’slimme steden‘. Veel stedelijke managers en planologen beginnen
echter nu pas te leren hoe ze slimme stadsontwikkeling kunnen aanpakken en
uitvoeren’. Het bouwen van zo'n geavanceerde technologie gedreven stad lijkt erg
duur, om welke reden efficiency wenselijk is. Steden die past zijn begonnen, kunnen
effectief te werk gaan wanneer zij een leerproces doormaken, waarbij technologie,
beleid en ervaringsoverdracht centraal staan, en zo vermijden dat ze het wiel
xvi Samenvatting
opnieuw moeten uitvinden. In de zoektocht naar de ontwikkeling van slimme
steden zijn talloze voorbeelden van ‘best practices’ gecreëerd en verspreid in natio-
nale en internationale arena's. Leren van goede praktijken is altijd een element dat
in de menselijke ontwikkeling wordt aangetroffen, met verschillende betekenissen
en consequenties in de verschillende contexten. In lijn met de bredere stroom in de
politieke wetenschappen en stedelijk beleidsonderzoek wordt het leren van anderen
ook in Smart City beleidsontwikkeling aangenomen. Er zijn veel rangen en indexen
om de goede praktijken van Smart City te bepalen, en er zijn uitgebreide studies
uitgevoerd naar de lessen die eruit kunnen worden getrokken. Niettemin ontbreekt
een alomvattend kader om lessen uit de goede praktijken van Smart City op een
systematische manier te analyseren.
Het lijkt erop dat steden die net begonnen zijn met Slimme steden-programmas
wel veel willen, maar niet precies weten hoe ze het moeten doen en hoe te leren van
toonaangevende Slimme steden elders die voorbeeldprojecten uitvoeren. De aan-
name die aan dit onderzoek ten grondslag ligt, is dat ze dat kunnen, maar wel
moeten beseffen dat ten eerste de bereidheid om slim te worden cruciaal is en ten
tweede, dat de politieke, juridische, institutionele en culturele context in die donor-
landen anders is dan in de eigen stad. Ergo, context speelt een belangrijke rol en het
overdragen van lessen en beleid kan daarvan niet worden geïsoleerd. Allereerst ver-
eist het transformeren van een stad in een slimme stad dat rekening wordt gehouden
met de bereidheid van een stad voor de verandering. De bestaande onderzoeken
naar de gereedheid van Smart City zijn vooral gericht op technologische aspecten,
terwijl het bewijs aantoont dat sociale en politieke bereidheid net zo cruciaal is als
technologische gereedheid, zo niet meer. Bovendien vereist het zetten van stappen
vooruit in het gecompliceerde proces van ‘beleidtransfer’ (van steden in donor-
landen naar ontvangende steden) het gebruik van een alomvattend kader.
Om deze uitdagingen en hiaten aan te pakken begint de auteur met na te gaan
welke indicatoren kunnen worden gebruikt om de geloofwaardigheid van ‘stads-
merken’ te evalueren en deze toe te passen op het merk ‘Slim’. Het voorgestelde
kader voor de beoordeling van de geloofwaardigheid van het merk wordt toegepast
op Iraanse grote steden die kandidaten zijn om Smart City-beleid als ontvanger over
te nemen op basis van goede praktijken in dit onderzoek. De resultaten geven aan
dat vier grote Iraanse steden een geloofwaardige merk 'Smart' hebben, wat recht-
vaardigt dat zij illustratieve voorbeelden zijn als de ontvangers van het Smart City-
beleid. Vervolgens wordt een Input-Output (IO)-model geïntroduceerd dat
beleidsmakers en analisten kunnen gebruiken bij het maken van geïnformeerde on-
twerpkeuzes. Het (IO)-model wordt vervolgens gebruikt om te achterhalen welke
ontwerpvariabelen van belang zijn en tot welke output deze variabelen leiden in de
volgende Slimme steden-projecten: Smart Dubai, Masdar City, Barcelona Smart City
Samenvatting xvii
en Amsterdam Smart City. Dit model kan worden gebruikt als een hulpmiddel om
de goede praktijken van Smart City te analyseren. Het resultaat van de analyse van
de vier cases (Amsterdam, Barcelona, Masdar en Dubai) geeft aan hoe hun Smart
City-ontwikkelingstrajecten verschillen. In de volgende stap wordt een raamwerk
gepresenteerd voor het beoordelen van de gereedheid van een stad om zo een The-
ory of Change te ontwikkelen voor ontvangende steden die klaar willen zijn om
‘Smart’ te worden. Het raamwerk wordt toegepast op de voorbeelden van de
ontvangende steden (vier grote Iraanse steden met een geloofwaardig merk 'Smart')
om te onderzoeken of ze er klaar voor zijn om Smart te worden. Het resultaat is dat
politieke geschiktheid de grootste uitdaging is voor Iraanse steden. Tot slot hebben
al deze conceptuele en theoretische kaders de auteur in staat gesteld een alomvat-
tend raamwerk te ontwerpen voor transplantatie van smart city-beleid. Dit raam-
werk is het eerste alomvattende raamwerk voor Smart City-beleidstransities dat de
terminologie van ‘Transplantatie’ gebruikt, geïnspireerd door rechtsvergelijking (ju-
ridische transplantatie) en politieke wetenschappen (institutionele transplantatie).
Het belangrijkste idee achter het gebruik van deze terminologie is dat het raamwerk
van ‘The Smart City Policy Transplantation’ niet alleen gaat over het reizen van het
beleid in isolement, maar ook over de accommodatie van het reizen met het beleid
van de ene naar de andere context.
Hoofdstuk 1 (Inleiding) laat de lezer kennismaken met de algemene concepten,
theorieën en benaderingen die verband houden met het Smart City-ontwikkelings-
beleid. Het introduceert de theorie van ecologische modernisering als de bron van
de opkomst van het concept van de merken van toekomstige steden en de meest
populaire onder hen; Smart City-ontwikkelingsbeleid. Aan de kwestie van vaagheid
bij de uitvoering ervan wordt in dat hoofdstuk aandacht besteed.
Hoofdstuk 2 (Towards credible city branding practices) onderzoekt de geloof-
waardigheid van stedenmerken die worden geconfronteerd met ecologische mod-
ernisering. Het behandelt ook de erkenning van het geloofwaardige merk ‘Smart’ in
steden die zichzelf profileren als ‘Smart’. Veel van het toekomstbestendige
stadsbeleid is uitgegaan van merkpraktijken en daarom vormt hoofdstuk 2 als zo-
danig een belangrijk onderdeel van deze studie.
Hoofdstuk 3 (Input-output modellering van Smart City) behandelt in het bi-
jzonder het Smart City-ontwikkelingsproces waarbij een systeemdenken wordt
toegepast om het proces in kaart te brengen. Het geeft eerst een overzicht van de
verschillende definities, classificaties en domeinen van de Smart City. Vervolgens
worden verschillende facetten van het ontwikkelingsproces vertaald in inputs,
throughputs en outputs die de implementatie helpen.
Hoofdstuk 4 (Op weg naar een classificatie van Smart City-ontwikkelingstra-
ject) presenteert een geïntegreerd raamwerk voor de Smart City-ontwerpkeuzes op
xviii Samenvatting
basis van het IO-model als een hulpmiddel om verschillende Smart City-good prac-
tices en hun ontwikkelingstrajecten te analyseren en te vergelijken.
Hoofdstuk 5 (Naar een geïntegreerd raamwerk voor Smart City-gereedheid)
classificeert indicatoren, factoren en praktijken voor Smart City-gereedheid in tech-
nologische, sociaaleconomische en politieke gereedheidsparameters. Het behandelt
ook hoe een veranderingstheorie ontwikkeld kan worden zodat steden klaar
worden om ‘slim’ te zijn.
Hoofdstuk 6 (Een conceptueel raamwerk voor Smart City-beleidstrans-
plantatie) beschrijft het mechanisme van beleidstransplantatie van goede praktijken
naar een Smart City-initiatief, dat de belangrijkste ambitie is van de huidige studie
om de beleidspraktijk te helpen bij het opstarten van een Smart City-programma.
Hoofdstuk 7 (Conclusie) behandelt de antwoorden op de onderzoeksvragen en
geeft enkele beleidsaanbevelingen voor de Smart City-initiatieven, in het bijzonder
die steden die net begonnen zijn met hun Smart City-programma.
1
1
INTRODUCTION
2 Research Motivation
1
1.1. RESEARCH MOTIVATION
‘The Smart City concept is increasingly frequently used’; this is a statement in
which many authors express their motivation for researching and writing about the
Smart City. Nevertheless, why the concept of a Smart City has been as broad as an
umbrella? On the one hand, this inclusive incidence is due to the need to solve com-
plex urban problems, and the other side is affected by technology push and technoc-
racy (rules by technology companies). Therefore, from the standpoint of technolog-
ical forecasting, smart urbanism is not only an urban development option or diplo-
macy but also an inevitable future reality. The experience of the COVID-19 pan-
demic has shown us how technology can be used to serve humans in vulnerable
conditions. But is technology the core of designing our future cities? I started my
journey on Smart City with this early assumption that ‘technology is the core of our
future cities and more specifically the Smart City’. My primary motivation was
based on this assumption that I left my job as a Technology Manager in the ICT in-
dustry for new adventures on the fascinating and trendy subject of Smart Cities de-
velopment. However, from the early steps of investigating the Smart City concept, I
begun to change my assumption and my interest in the human factor grew for the
further steps of this journey. I started my adventure on the topic of Smart Cities as a
freelancer project coordinator to facilitate public-private partnership for the 'Smart
City and City Branding' projects. Then I realized that despite the growing demand
for creating Smart Cities, it seems the understanding of how put the policies in action
and implement them is still very limited for Smart City initiatives. The more the
concept of the Smart City becomes extensive and the higher its ambiguity, the more
difficult it will be to convince urban policymakers and managers to invest in Smart
City initiatives to transform their cities into a real Smart City rather than just brand-
ing it as smart (Hollands, 2008). Another challenge for the Smart City initiatives is
managing stakeholders from different disciplines with various approaches and ex-
pectations. Using a common language so that policymakers and practitioners can
understand each other’s expectations is crucial for implementing the Smart Cities
policies.
Those challenges in the real world of the Smart City development drove me to
research on the initiation phase when urban governments begin a new policy and
then it is mainly about governance. So, the main purpose of this research is to discuss
the governance of Smart Cities and how local and municipal government should run
the city to be smart. It will be centered around the policy behind such governance
and highlight the institutional and organizational features. Looking at the legal con-
Introduction 3
1
text, for instance, legality is more important in some countries than in others. Politi-
cally, the way government organization are structured, and the level of collaborative
governance based on interaction between public and private sectors, levels of hier-
archy lead to different approaches in initiating a Smart City. Since still there is no
best model or clear conceptual definition and defined domain of application for the
Smart City, learning from good practices helps initiators to develop better Smart
City policies based on their own objectives. On the other hand, it also helps those
leading Smart Cities to improve their policies over time and make them more trans-
parent. To clarify how we can learn from good practices, first an understanding of
the Smart City development process, its required resources, intended outputs and
expected outcomes is essential. Then applying it to the various Smart Cities cases
reveals different Smart Cities development pathways. The process to investigate
what lessons follower Smart Cities can learn from leading Smart Cities in terms of
governance approaches and how can these be transplanted is the core of this study.
1.2. CONCEPTUAL REALM AND INTERDISCIPLINARY
1.2.1. ECOLOGICAL MODERNIZATION AND URBAN POLICIES
Globalization, technological changes, urbanization, and climate change have
emerged as important challenges of the twenty-first century. Ecological moderniza-
tion (EM) Theory-originating from the early 1980s (Mol & Spaargaren, 2000) has
been developed in need of solutions for these challenges in the early 1990s (Mastran-
gelo & Aguiar, 2019). In response to the ‘Risk Society Theory’, which criticized sci-
ence and technology and promoted deindustrialization and de-modernization, EM
as an approach was developed (Mol & Spaargaren, 1993, p.433). The main discussion
of the theory concerns the connection between society and nature based on the evo-
lution of socio-political institutions (Campos-Medina, 2019). It is argued that mod-
ernization brings technology that consumes energy and leads to issues such as air
pollution and climate change. Ecological Modernization narratives basically are re-
lated to making the environmental improvements through the further advancement
of technology, industrialization, and urbanization (Fisher & Freudenburg, 2001). In
a simple word, EM seeks eco-efficient innovation and environmentally friendly tech-
nologies to increase resource productivity that means achieving higher outputs with
consuming less resource (Huber, 2000). From an economic point of view, EM claims
that a sustainable form of capitalism is possible by using modern and clean technol-
ogies (Fieldman, 2014). The common denominator of all these definitions is that eco-
nomic development and environmental protection can proceed hand-in-hand bene-
4 Conceptual Realm and Interdisciplinary
1
fiting from technological development (Dryzek, 1997). There are also two major ap-
proaches to ecological modernization as a theory of the social transformation-conti-
nuity and ecological modernization as the political program (Mol & Spaargaren,
2000). The wave of ecological modernization has led to many environmental laws
faced with the problem of climate change (Campos-Medina, 2019). Urban transfor-
mation and sustainable development using technological advances affect urban pol-
icies and governance (Midttun & Kamfjord, 1999; Smith & Kern, 2009; McGee &
Wenta, 2014). In another study, Hajer (1995) introduces two distinct approaches to
EM: the techno-corporatist version, and reflexive EM. The techno-corporatist form
pertains to the technological-administrative approach and the reflexive EM is asso-
ciated with social learning, democratic governance, institutional arrangement ap-
proaches democratic governance, institutional arrangement approaches (Hajer,
1995). In a follow-up study, Christoff (1996) divided all those approaches to EM up
into weak and strong types of EM. The weak form is associated with technological
solutions to environmental problems, technocratic style of policy making, exclusive
to developed nations to centralize their global economic advantages, and a closed
rigid framework on political and economic development. On the other hand, the
strong form is set side by side with socio-economic change incorporating environ-
mental concerns, democratic and participatory style of policy making, international
developments, and a more open and flexible framework on political and economic
development (Christoff, 1996). I will discuss the EM theory more in-depth in the next
chapter.
Introduction 5
1
The interest in EM is also inspired many urban theories (Langhelle, 2000; Pep-
per, 1998), urban branding practices (Goes, de Jong & Meijers, 2016), and modern
urbanization pathways (Szarka, 2012; Smink, Van Koppen & Spaargaren, 2003;
Toke, 2011; Coles & Peters, 2003). Both academia and practice have introduced a
myriad of terms and definitions related to face ecological modernization and build-
ing the cities of the future; smart, intelligent, ubiquitous, digital, knowledge, crea-
tive, innovative sustainable, eco, low carbon, and resilient (De Jong et al., 2015). In-
telligent, digital and ubiquitous cities are mainly based on technological infrastruc-
ture and the state-of-the-art information and communication technologies (ICTs) are
the core of these cities concept (Lee, 2009; Choi et al., 2005; Komninos, 2006).
Knowledge, creative and innovative cities are looking for economic growth through
creativity and knowledge-based society (Yigitcanlar, 2008). Eco, low carbon, and re-
silient cities are trying to (re)constructing cities in balance with nature with the aim
of presenting a lifestyle in harmony with nature (Wong & Yuen, 2011; Sengers, 2016).
Sustainable development balances ecological, socio-cultural, and economic values
for development. And Smart Sustainable development aims to leverage technologi-
cal developments for this balanced development (Tomor et al., 2019). Sustainable
and Smart Cities are broader concepts than other cities. They are affected by more
contextual aspects and also generate higher expectations than others. All of them are
Figure
1- Structural linkages between keywords in the EM literature (Scopus: Pub-
lications between 1996
– 2020, N= 789 articles).
6 Conceptual Realm and Interdisciplinary
1
introduced as answers to the set of issues related to urban agglomerations. There-
fore, urban modernization inspiring by the EM theory certainly builds our future,
But a question mark hangs over what kind of future city one can look forward to
and how we can position the Smart City (at the center of our debate) among the
various types? Are those cities that profile themselves really becoming Smart or they
just are branded as Smart? Thus, to trace the emergence of the Smart City concept,
this investigation takes EM theory as a point of departure and considers it the main
root from which different urban labels and branding practices have emerged. Brand-
ing a city as ‘Smart’ is the first step of moving towards a ‘Smart City’ as having a
policy in place to govern the city (De Jong et. al, 2015; De Jong et. al., 2018).
1.2.2. SMART CITY POLICY AS THE DOMINANT APPROACH
The use of the concept Smart City has grown tremendously over the past few
years facing ecological modernization and has dominated the Sustainable city in the
urban development stream (De Jong et. al, 2015; De Jong et. al., 2018; see also fig.2
in Chapter3). Nowadays it tends to be used like an umbrella concept and its meaning
has become increasingly broad and hazy over time (Yigitcanlar et. al., 2018; Appio
et. al., 2019; Chourabi et al., 2012; Hollands, 2008). Its rise can partly be explained by
the need to solve complex urban problems that cross sectorial and disciplinary
boundaries and partly by entrepreneurial technology push (Joss, 2016). Therefore,
from a technological forecasting point of view, the Smart City tends to be seen as not
just an urban development option or diplomatic tool for national or municipal self-
promotion, but also a likely scenario for future urban and infrastructure invest-
ments. Traffic, air pollution, livelihood, employment, education and social and legal
services are major concerns in metropolises in need of a solution. Apparently, now-
adays, one of the solutions which urban planners, engineers and social scientists
propose is Smart Cities, and the development of Smart Cities should be knowledge-
based, sustainable and above all convincing to policymakers (Sabatini-Marques, et.
al., 2020; Kumar et. al., 2020; Mora et. al., 2019; Yigitcanlar et. al., 2019; Yigitcanlar &
Kamruzzaman, 2018; Trindade et. al., 2017). Nonetheless, the concept of a Smart City
can seem elusive and vague, first of all because of the fact that there are many ways
to be smart; secondly, because there is a tendency to use the concept as a tool for
self-promotion, rather than a strategy for actually becoming smarter. Recently a geo-
twitter analysis of Smart City concepts and technologies in Australia revealed that
on Twitter the concepts perceived as the most trending are innovation, sustainabil-
ity, and governance in the Smart City discourse. The result marks that the top three
technologies in this discourse are Internet of Things (IoT), Artificial Intelligent (AI),
and Autonomous Vehicle (Yigitcanlar et al., 2020). this study indicates that 8241
tweets with the keywords of ‘Smart City’ and ‘Smart Cities’ were circulated in 2018.
Introduction 7
1
The result from searching scientific publications on Scopus with the same keyworks
and the year of publication is 5402 articles which demonstrate the popularity of the
Smart City discourse not only in the academic context but also on the social media.
Now that evidence shows (De Jong et. al., 2015; see also fig.2 in Chapter 3) that
the most popular type of future cities is ‘Smart’, the question is: how can cities initi-
ate (and later on evaluate) a Smart City development process?
1.2.3. PROVISIONING A SUCCESSFUL SMART CITY DEVELOPMENT PROCESS
The use of information and communication technology (ICT) and its new para-
digm; Internet of Things (IoT) in the Smart City development has been extensively
mentioned in the literature (Ahvenniemi et al., 2017). In this body of literature tech-
nology is considered as an enabler to improve the quality of life and bring prosperity
for citizens (Angelidou, 2014; Gonzales & Rossi, 2011; Washburn et al., 2010). In the
more sophisticated definitions, the role of technology as the key enabler is dimin-
ished and human capitals are given more attention (Neirotti et al., 2014; Giffinger et
al., 2007; Hollands, 2008; Nam & Pardo, 2011). In the literature several generations
of Smart City have emerged gradually along with the evolution of its concept. The
early generations resemble the intelligent city more, and in fact with the arrival of
new approaches such as ‘digitally inclusion’ (Deakin, 2007; Deakin, 2011) and ‘so-
cially inclusion’ (Paskaleva, 2009) the transition from digital and intelligent cities
toward the Smart City took shape (Deakin & Al Waer, 2011). Pascalova (2009) advo-
cates a human-centered approach to Smart Cities using digital technologies not only
to connect everything within the city, but also to use technology to strengthen good
governance and provide services capable of improving the quality of life (ibid). An-
other example of strong critique of the concept of Smart City and its technology-
centricity has been expressed by the governance center of University of Ottawa. It
offers a governance-oriented approach with an emphasis on social capital Smart Cit-
ies development (Albino et al., 2015). To characterize good governance of the Smart
City, several facets are expressed by various authors such as being collaborative,
accountable, responsive, communicative, and transparent (Johnston & Hansen,
2011; Mooij, 2003; Odendaal, 2003) all of which pleasant qualities governments need
to be capable of implementing the desired policies. However, the combination of
technology and human infrastructure can be a powerful driver for smart city devel-
opment but without government support for regulation, it will not be implemented
(Mora, 2018). Meijer and Bolıvar (2016), identified four ideal-typical conceptualiza-
tions of smart city governance: (i) government of a smart city, (ii) smart decision-
making, (iii) smart administration and (iv) smart urban collaboration (ibid). Accord-
ing to Joss (2016), Smart city innovation designates a transition from traditional
forms of urban governance, to modern control rooms and centralized urban service
8 Conceptual Realm and Interdisciplinary
1
hubs, in which technology and engineering firms play a direct and effective role
(ibid).
Looking at the Smart City as an urban development policy, needs to consider
Smart City development as a process. Since still there is no best model or clear con-
ceptual definition and defined domain of application for the Smart City, mapping
the Smart City development process and its facets helps initiators to make better
choices for Smart City policies and strategies implementation based on their own
pathway and intended outcomes. Also, it helps those leading Smart Cities to over-
view and improve their policies over time through mapping the development pro-
cess, its domains, outcomes and the way their policy works in practice more trans-
parent. Through characterizing the domains of the Smart City more precisely and
pinpointing structural factors and institutional and organizational features in the
development process, the concept of governing a smart city can be pragmatized. Be-
yond that, this understanding and conceptualization of the Smart City can be used
as a tool to analyze existing Smart City examples/practices to learn from them and
provisioning a successful Smart City development process based on the experiences
(both failures and successes). This is a common way in urban (re)development stud-
ies so-called ‘Lesson Drawing’.
1.2.4. CROSS CITY LESSON DRAWING ON SMART CITY DEVELOPMENT
Many cities, even in developing countries, have taken numerous steps to de-
velop in that direction. They have started to use IoT (Internet of things) solutions to
solve the problems of urban management (Zanella et al., 2014) through learning
from strategic and technical approaches to developing ‘Smart City’ from good prac-
tices (Gascó-Hernandez, 2018). For instance, the UAE and Singapore are joining
hands in develop the Smart City (Singapore, UAE embark on Smart City coopera-
tion, 2015). Looking at a few significant Smart Cities around the world such as Am-
sterdam, Barcelona, Malmo, Copenhagen, Vienna, Helsinki, and so on, leads us to
conclude that these cities have made great strides towards intelligent solutions, but
this valuable experience comes at considerable effort and budget (Joss et al., 2017;
Eden Strategy Institute and ONGandONG, 2019). It seems that cities that are just
getting started Smart City programs want a lot, but do not know how to do it and
intend to learn from mostly advanced countries (for instance the mayor of Tehran
stating that: ‘Our Smart City program is embarrassing’ when comparing the plans of
Iranian cities with those of cities in other countries to Iran that are successful in this
area and have provided a clear horizon). The assumption underlying this research
is that, they can do so, but must realize that the political, legal, institutional and cul-
tural context in those donor countries are different, so policy context plays an im-
portant role as well as technology in this case
Introduction 9
1
Nevertheless, building such an advanced techno-driven city seems very expen-
sive and cities that are just getting started can potentially make it cost-effective
through a learning process by technology, policy and experiences transfer and avoid
having to reinvent the wheel. They require policy and planning based on an analysis
of the effects information technologies have on urban structures.
In the quest for Smart Cities development, numerous examples of best practice
have been created and circulated in national and international arenas. But based on
the contextual differences it is argued that the differences – cultural, political, ideo-
logical – are so great that public policy for cities should rightly be nation specific.
However, I believe that notwithstanding the major differences between different so-
cieties there are significant possibilities for exchange. That is why I call this learning
process and policy travel (as the policy donation and adoption): policy transplanta-
tion. Yet despite the vast array of examples, demonstration projects, case studies,
and the like, little is known about the mechanism of policy transplantation, in which
best practices are produced and used, and the policies are adopted by recipients.
1.2.5. WHERE TO LOOK FOR A LESSON: GOOD PRACTICES OF SMART CITIES
A
ND WHERE TO TRANSPLANT POLICIES: AN EXAMPLE OF SMART CITY
INITIATIVES
I chose a list of European Smart Cities as the good practices looking for the les-
sons that illustrate us how the Smart City development process can be applied (Am-
sterdam, Barcelona, London, Paris, Malmo, Copenhagen, Oslo, Helsinki, Vienna,
etc.) and also two special cases in Asia (Dubai and Masdar city). I also used desk
research and content analysis that gave us an insight on the matter and provided us
the opportunity to observe and point out the best practices and smartest cities in the
world. In this case, the content analysis has been included the international rakings,
rewards and competitions related to Smart City development.
Based on these data I made a long list of Smart City projects as good practices,
and then a shorter list to visit and look for lessons considering their smart elements.
To select the final cases from this list I consider some criteria; cases should have:
• Smart City development policy and programs in place
• International positioning of Smart City(ranking)
• Different governance patterns
• And, should be accessible for interview and visit.
Finally, based on these criteria I chose four cases which have been repeatedly
considered among the top Smart City projects in the world, two European cases;
Amsterdam and Barcelona and two Asian cases; Dubai and Masdar based on their
10 Research aims and research questions
1
impact area to assess the policy they adopted, using a comprehensive framework
that includes different pathways of Smart City development.
As for the policy transplantation, I needed to grasp the real cases for studying
as the best practices for lesson drawing, I studied real life examples of cities that are
in the early stages of transformation into Smart Cities to which I can transplant the
policies. One of the countries where I find many adopting cities is Iran, which is
promising due to familiarity with the context and data accessibility. Considering
Iranian cities examples, I began this study by examining how they use ‘Smart’ label
facing ecological modernization in practice to make sense of what Smart City initia-
tives are aimed at. It is known that urban planning failures can be costly and have
serious consequences, so I examine of successful and failed cases to attain a clear
vision for successful development of Smart Cities.
1.3. RESEARCH AIMS AND RESEARCH QUESTIONS
The main purpose of this study is to investigate the adoption and decision-mak-
ing of Smart City policies through lesson-drawing from experiences obtained in
leading Smart Cities to cities that are just getting started. This research focuses on
the city level, and the initiation phase when urban governments begin a new policy
and then it is mainly about governance. In the initiation phase, branding is the first
sign that governments express their desire to become Smart and formulate their in-
tended goals to achieve that. A credible Smart City brand is the first indicator that
governments want to go beyond branding toward implementing their policies. In
the implementation phase, governing a Smart City first requires that the develop-
ment process and its various facets be well understood. To analyze the Smart City
development process, I develop a conceptual model that can also be used by policy
makers and practitioners in relevant decision-making processes. After understand-
ing what the Smart City development process looks like, looking at the existing ex-
periences and good practices can be a compass for newcomers to the pathway. To
clarify how we can learn from good practices, I apply the model to compare the four
cases (good practices) regarding their Smart City development process to investigate
what lessons follower Smart Cities can learn from them. I previously argued that the
lesson learnt from good practices cannot be copied and pasted into a new context.
Adopting the lessons requires the recipient to prepare thoroughly before transfer-
ring the lessons. To systematically measure the recipient readiness for becoming
Smart and being aware of what need to be done regarding that, I propose a readiness
measurement system and a Theory of Change to get ready to be Smart. After ensur-
ing readiness assessment, to theorize how these lessons can be transplanted I design
a mechanism for policy transplantation that is the core of this study. Accordingly,
Introduction 11
1
the main research question is: How to initiate and manage the process of transform-
ing a city into a Smart City?
Thus, to answer the main question I need to respond to the following sub-ques-
tions:
Q1: How do cities engage city branding practices when facing ecological mod-
ernization? To what extent do they use ‘smart’ in their brands and how?
Q2: What does a conceptual model representing different domains of the Smart
City development process look like?
Q3: How are Smart Cities different from each other by their resources and
goals? What lessons can we draw from the good practices in Smart City develop-
ment; how do their policy actors operate in governing a Smart City?
Q4: How to determine whether cities are ready to transition into Smart Cities?
What does an indicator system measure to determine whether a city is ready to be-
come smart? And to what extent do Iranian cities meet the minimum requirements
for becoming smart?
Q5: How Smart City policies can be transplanted from those good practices to
Smart City initiatives?
Finding the appropriate responses for these questions can offer us both positive
and negative lessons to formulate them as a roadmap or policy guidelines for Smart
City development at the initial phase.
1.4. RESEARCH METHODOLOGY
In order to answer the research questions, I conducted a systematic review of
the core literature. I started the systematic literature review from one the important
root of the Smart City debate as the ‘Ecological Modernization’ (EM) theory is. I
looked at the EM theory to understand the reason behind emerging the concept of
Smart City and I followed that root in the literature and through exploring different
aspects of the Smart City, I arrived at theories of Implementing Smart City develop-
ment policy. In this route, wherever the existing theories and models did not accu-
rately address my research questions, I began to develop my own theoretical frame-
work to fill the gaps in literature that I faced. For developing the theoretical frame-
work, I mainly relied on the concept mapping and system thinking approaches. Sys-
tem thinking approach assisted me to integrate different components of Smart City
and pinpoint them in a development process to reveal their interaction. Concept
12 Research Methodology
1
mapping helped me to organize and structure various phases, stages, and activities
regarding the Smart City policy transplantation mechanism in a comprehensive
framework.
Considering the complexity of the study, I choose to use case study as a main
method for data collection, which refers to the data that illustrate policies, institu-
tional and organizational features of Smart City projects. The empirical analysis is
based on desk research, site-visiting, interviews, and online survey pertaining to the
Iranian case study. As for the policy transplantation, I needed to grasp the real cases
for studying the best practices for lesson drawing as the Smart City policy donors.
For the recipient side, I studied real life examples of Smart City initiatives that are in
the early stages of transformation into Smart Cities to which I can transplant the
policies. The research framework is shown in the Fig.1.
Introduction 13
1
Figure 2-The research framework
1.5. THE INNOVATIVE ASPECTS OF THE STUDY
This study provides insights and useful guidelines for those cities and govern-
ments who desire to initiate a Smart City development policy and take it towards its
implementation. Therefore, the implementation aspect of the Smart City policy is an
Introduction
and Theories
Empirical
and Theo-
retical
analysis
Conclusions
Ecological modernization and city branding, Smart city develop-
ment, Smart city policies and lesson drawing
Towards Credible City Branding Practices: How Do Iran’s Largest
Cities Face Ecological Modernization?
Input-Output Modelling for Smart City Development
Classifying Pathways for Smart City Development: Comparing
Design, Governance and Implementation in Amsterdam, Barce-
lona, Dubai, and Abu Dhabi
Towards an Integrated Framework to Measure Smart City Readi-
ness: The Case of Iranian Cities
Policy transplantation for Smart City initiatives: An exploration of
mechanism and objectives
A roadmap and policy guidelines to initiate and manage the pro-
cess of transforming a city into a smart city
14 Research Structure
1
important part of this study which has received less attention in the literature. In this
study, I assume that one of the main challenges of involved governments is to find
out how and from where to start the Smart City development, and it provides a
comprehensive roadmap on a path to success. To do this, the present study starts
from an early stage of this development pathway which is branding practices. Cred-
ible branding of a city as a Smart city indicates the intention for implementing the
Smart City policy and a higher likelihood of achieving the goals of being Smart (Oha-
nian, 1990; Erdem & Swait, 2004). First, the study provides insights on how to cred-
ibly brand as ‘Smart’ to take its first step towards Smart City development. I develop
a methodology and criteria to map and evaluate the credible city branding practices.
Second, inspired by system theory (Checkland, 1999) and input-output per-
spectives, a conceptual model of the Smart City is developed. The added value of
using in-put-output (IO) model provides a realistic and dynamic analysis of various
domains of the smart city and adds transparency as to how to engage in a smart city
development process in practice. Thus, the second contribution is a novel pragmatic
model of smart city applying in different cases to develop a taxonomy of smart city
development pathways.
Third, a comprehensive framework of Smart City design choices is developed
that can be used as a tool to compare various Smart City practices and determine
how their development pathways are different from each other.
Fourth, a novel and comprehensive readiness assessment framework of Smart
City covering technological, socio-economic, and political aspects is developed.
Fifth, for the first time the term ‘policy transplantation’ inspired by comparative
law and public policy is applied to the Smart City context to develop a comprehen-
sive framework for traveling Smart City policy from the donor(s) to a recipient wish-
ing to adopt the policy.
1.6. RESEARCH STRUCTURE
The research is based on both a literature analysis and a large empirical survey
of four good Smart City practices with different governance structures, and four
Smart City initiatives. To achieve the ultimate goal of the research, several steps are
taken (figure.1): Chapter 2 specifies which cities in Iran have Smart City credible
brands to take them as the examples for Smart City initiatives for. Chapter3 con-
strues an integrated conceptual Input-Output (IO) model of Smart City based on the
system theory approach to apply in and analyze the good practices. Chapter 4 illus-
trates the lessons for beginners of a Smart City initiative, through comparing the
four good practices on the basis of the goals, resources, policies, procedures, and
design choices these cities have. Chapter 5 explains how the situation in Iranian
Introduction 15
1
Smart City initiatives is as candidates for transplantation. Chapter 6 deals with
policy transplantation theories to design a protocol for lesson drawing and shows
how can we learn from successful examples, and what steps should be taken. And
finally, Chapter 7 contains the conclusions of the study and policy guidelines for
Smart City initiatives.
17
2
TOWARDS CREDIBLE CITY
BRANDING PRACTICES: HOW DO
IRAN’S LARGEST CITIES FACE
ECOLOGICAL MODERNIZATION?
The contents of this chapter have been adapted from the following peer-reviewed article: Noori, N., & De
Jong, M. (2018). Towards credible city branding practices: How do Iran’s largest cities face ecological
modernization? Sustainability (Switzerland), 10(5), 1–16. https://doi.org/10.3390/su10051354
18 Introduction
2
2.1. INTRODUCTION
As noted at various places in the academic literature, city branding practices
have grown in importance among ambitious municipal governments in recent dec-
ades (Braun, 2012; Dinnie, 2011; Vanolo, 2008; Kavaratzis & Ashworth, 2005). They
are used as a tool to enhance a city’s image in the competitive global arena to lure
investors, corporations, a talented workforce, visitors, and residents into the city. In
many cases, using labels, such as sustainable, low carbon, eco, resilient, knowledge,
digital, or smart before ‘city’ aims to convey a particular impression among key
stakeholders and enhances attractiveness (Joss, 2011; De Jong et al., 2015). Nonethe-
less, empirical evidence suggests that the malleability of a city’s brand in the eyes of
stakeholders, clients, and observers is limited: it depends on subjective perceptions,
consists of multiple aspects that may not always point in the same direction, and is
associated with ideas lingering on from the past that are difficult to erase (Anholt,
2007). Much of the literature deals primarily with city branding strategies, practices,
and experiences collected in cities located in wealthy and developed nations, but
knowledge of how this works in non-Western countries is less widespread, espe-
cially in those where opening up to market influence and global capitalism is a re-
cent phenomenon. Nonetheless, there is a burgeoning literature and growing num-
ber of case studies on this topic (Morgan et al., 2012; Han et al., 2018; De Jong et al.,
2018). Awareness is growing that international and national positioning, profiling,
and imagineering of places is apparently also awakening in countries thus far rela-
tively secluded from international influence. One of them is Iran.
Since the rise to power of President Rohani and the signing of the international
treaty on nuclear power, economic sanctions have been lifted, curiosity for develop-
ment ‘out there’ has increased, and cities are getting increasingly connected to global
trends of which the need for credible self-branding is an important one. Iran is con-
sidered as being of strategic geopolitical importance due to its historical incorpora-
tion in the Silk Road, the presence of vast natural resources, the presence of a rela-
tively highly-educated population, and the availability of comparatively advanced
physical infrastructures (Iran Review). While the above suggests a very large fount
of future economic opportunities, mounting environmental problems, in fact, cause
a major headache. Implementing the construction of smart urban infrastructures and
transforming outdated industrial structures have become developmental impera-
tives. As a consequence, urban master plans for Iranian cities frequently express at-
tempts made by local governments to develop their urban environments into livable
and pleasant places for their citizens, as well as promising locations for high-quality
capital investments. Such efforts can be seen as dealing with the challenges of ‘eco-
logical modernization’ (De Jong et al., 2018; Hajer, 1995; Mol & Spaargaren, 2000;
Bayulken,& Huisingh, 2015): generating higher economic value-added with reduced
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 19
2
resource consumption and/or reduced emission of harmful substances. Often, a tran-
sition from manufacturing industries to services is involved, and/or the upgrading
of production processes by making them higher in quality and lower in resource
intensity. In the urban context, it is usually associated with the promotion of sustain-
able or Smart Cities.
The aim of this article is two-fold. It is first to distill from the academic literature
on city branding key insights allowing us to establish a set of criteria to assess the
credibility of city branding practices as developed by municipalities. This will allow
us to have a critical look at the practices of any given municipality. In Section 2,
therefore, I will examine what the state-of-the-art literature on city branding tells us
about the criteria for credible city branding practices.
The second aim is to map and evaluate the city branding practices as engaged
in by Iranian municipalities and obtain a valid impression of how they present them-
selves to the outside world, in terms of general positioning (city brand identities), as
well as in the specific debate on sustainable and/or Smart City development (use of
city labels). Section 3 will present the methodology as used in this contribution and
explain how data was collected in Iran’s 15 cities with over 500,000 inhabitants, na-
tionally known as its ‘megacities’. Section 4 will briefly introduce the main features
of these 15 cities to the extent that these are relevant for assessing the credibility of
their city branding choices. Section 5 presents the findings for the cities and a general
assessment of the credibility of these choices is given. Specific attention is paid to the
question of how issues of ecological modernization are addressed. Section 6 will
conclude with an overview of the main takeaways from this article and some hints
for future research on the Iranian cities with credible brand of ‘smart’.
2.2. THE CREDIBILITY OF CITY BRANDS: THEORY
This section will examine the existing literature on branding credibility and
place branding with as a specific aim to identify factors contributing to the credibil-
ity of city brands.
The literature on product branding in the private sector has generated a number
of insights on brand credibility with potential use for city branding. Ohanian (1990)
argues that branding is tantamount to successful communication. It is essentially the
manipulation of messages in such a way that these are received positively. Enhanc-
ing the credibility of both source and message can be helpful in reaching this goal.
Erdem et al. (2004) identify three elements which contribute to communicated mes-
sages being received in a positive manner and, thus, provide a higher likelihood of
being accepted: trustworthiness, expertise, and attractiveness. Trustworthiness is a
quality related to the reliability of the source of the information on the brand, exper-
20 The Credibility of City Brands: Theory
2
tise refers to the specific knowledge and skills of this source, and attractiveness in-
volves the ‘personality’ features of this source. Unfortunately, the literature on cred-
ibility of product branding has more to say about the credibility of the messenger
than about the credibility of the message or brand itself. Since, in this study, 15 mu-
nicipal governments are the messenger in all cases, this can barely be considered a
distinguishing factor.
As context for the credibility of city brands, their integration within the broader
provincial and national (country) context of which cities are a part matter a great
deal (Aitken & Campelo, 2011). In this sense, facilitating the national development
of an overarching branding strategy or policy and inserting the city brand in it may
eventually benefit both levels. A report commissioned by Heritage Counts (2016)
demonstrates that, in the United Kingdom, cultural heritage is emphasized at both
the national and local levels in place branding practices and that this combined ap-
proach promotes their credibility in terms of felt authenticity and distinctiveness.
Credible brands use a unique voice to tell the story about promotional promises, the
current situation, and the past heritage of the city. However relevant as a general
insight, all cities under study here are located in the same nation; a reason why I do
not include this factor in the analysis either.
Moving on to the literature on city branding (but without explicit attention paid
to credibility issues), at face value, place branding shows resemblance to city mar-
keting, a term much en vogue in the 1980 and 1990s. However, on closer inspection
it appears that marketing essentially refers to a heightened sense awareness of what
target groups or stakeholders wish, while branding has a strong aspect of loyalty
and overarching policy strategy to it (Baker, 2012). In contradistinction, however,
Lucarelli (2018) argues that place branding was driven by a more generic need in
public policy where public authorities needed to profile themselves more strongly
and, from there, place brands evolved into broader multi-dimensional socio-political
constructs generated through multi-level interaction among a variety of different
actors: this essentially makes city branding a co-development process of cities with
various relevant stakeholders. Having these stakeholders on board is crucial for its
translation into effective policy strategy and implementation. Vanolo (2008) has de-
fined city branding as a complete set of activities aimed at establishing and main-
taining a positive city image and conveying this information to different target
groups via materials and events at various scales, all of this to gain competitive ad-
vantage over other cities. In other words, while city marketing can, for instance, sup-
port Isfahan in knowing more about its various stakeholders in and around the city
and act on this knowledge, city branding can help it in letting these stakeholders
grow aware of Isfahan’s positive highlights that may be translated into a long-term
commitment to engage in, and collaborate with, it. Dinnie (2011), emphasizing other
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 21
2
aspects in his definition, sees a city brand as a unique, multi-dimensional blend of
elements, which provides the city with culturally-grounded differentiation and rel-
evance for its target audiences. This implies that a chosen brand should be clearly
distinct from others and, thus, the opposite of ‘a great place to live and work’ (Baker,
2012), while also able to attract a variety of audiences. Most authors in the field are
in agreement that place branding, of which city branding is a specific subspecies, is
more complex in nature than product branding, because cities are truly multi-di-
mensional entities evoking a great variety of impressions and associations depend-
ing on the people among whom, and circumstances under which, they are evoked
(Braun et al., 2014). One general message addressed at different groups of stakehold-
ers with potentially conflicting interests and expectations can lead to trouble, mak-
ing it necessary to convey partially different (but not contradictory) messages to
those various target groups (Kavaratzis& Kalandides, 2015; Merrilees et al., 2012;
Henninger et al., 2016). In that sense, city branding has more in common with the
corporate branding that large companies and holdings with many different product
lines engage in (Kavaratzis& Hatch, 2013). Tourists and visitors seek the availability
of exciting cultural centers and entertainment parks in a city, while wealthy resi-
dents, real estate companies, and project developers prefer quiet green neighbor-
hoods and high-quality public facilities, such as schools and hospitals. They may, in
fact, even be repelled by busy and noisy streets filled with hotels and exciting day-
trippers. This demonstrates the importance of distinguishing between various target
groups and stakeholders and addressing these in different ways; at their turn, they
hopefully communicate the brand message in the same way with their own partners,
a sign that they support it and act in accordance with it.
An additional aspect appearing in the literature on city branding relevant to
urban transformation is the aspect of dealing with the tension between a city’s cur-
rent social, economic, and geographic features, and its profile (its existing brand)
and self-image based on high-brow future ambitions (its desired brand). Generally
speaking, one can say that cities have (i) a historically-based cultural, social, and
economic inheritance or legacy which colors them; (ii) a present social and economic
profile with a specific composition of the population and collection of dominant in-
dustries; and (iii) a set of policy ambitions, goals, and chosen policy measures aimed
to realize these hopes for the future. If the present situation and future ambitions
deviate from each other too strongly without stakeholders able to grasp how this
gap can be closed, credibility of a brand severely suffers from this (perceived) incon-
sistency (Vanolo, 2008; Anholt, 2007; Kavaratzis, 2007; De Jong et al., 2018). On the
other hand, if the realization of future ambitions can be seen as a continuation and
enhancement of an evolving developmental path spiced up with a peculiar historical
and cultural background the brand will appear both attractive and credible. It is all
22 The Credibility of City Brands: Method
2
about the potential to connect past, present, and future in one logical narrative.
Therefore, local governments that are able to align their historical and current profile
with future wishes, follow up with necessary implementation steps, and manage to
convince relevant stakeholders to echo their brand in ways consistent with their own
are likely to bridge the gap between the existing and desired brand and have a
higher chance to realize their long-term goals for urban transition.
Based on the above reading of the literature, the list six factors that contribute
to the credibility of city brands are listed that can be taken on board for the rest of
the analysis. These are the potential to:
• Generate feelings of loyalty;
• Facilitate the development of an overarching strategy or policy;
• Evoke positive feelings;
• Demonstrate uniqueness or distinctness;
• Allow for different yet non-contradictory messages to various stakeholders;
and
• Logically connect past heritage, current profile, and future ambitions.
2.3. THE CREDIBILITY OF CITY BRANDS: METHOD
This section will explain how data was collected and processed and, following,
what procedures the credibility factors utilized to come to an assessment of the
branding practices of the 15 Iranian mega cities under study.
We have examined the city branding practices among the fifteen most promi-
nent cities in Iran, known as its 15 ‘megacities’, each having more than 500,000 in-
habitants. The question remains what city branding practices consist of and how
they can be measured. Kavaratzis and Ashworth (2005) have identified three ele-
ments in city brands: brand identity, brand position, and brand image. Mayes (2008:
125) argues that identities derive ‘from the intrinsic features and history of a given
place and a shared (personalized) relationship to these elements’. Govers and Go
(2009: 17) believe that ‘place identities are constructed through historical, political,
religious, and cultural discourses; through local knowledge, and influenced by
power struggles’. In short, given that a city brand identity constitutes the essential
actual or imagined core of a city’s self-perception, it should definitely be examined
here as an aspect that municipal governments deal with in their positioning and self-
promotion activities. A brand position, on the other hand, is that part of value prop-
osition communicated to a target group that demonstrates competitive advantages
in particular fields (Kavaratzis& Ashworth, 2005). In this sense, a city’s brand posi-
tion is related to a specific economic market, niche, or policy area for which its spe-
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 23
2
cific plans and visions express both the status quo and expectations for future devel-
opment based on future ambitions. I will also take this aspect into account in this
study since it addresses the desired infrastructural development and industrial
transformation of a city in the face of ecological modernization (De Jong et al., 2015;
Han et al., 2018; De Jong et al., 2018; Goess et al., 2016). Finally, a brand image refers
to how the brand is perceived by the outside world. In other words, identity is ‘how
we see ourselves’, whereas image represents its mirror image and can be described
as ‘how others see us’. Since the focus of this article is on how local government
practice city branding and not on how citizens, residents, and visitors perceive these
cities, this study mapped the city brand identities and city brand positions for each
city, but not the city images. The goal was to produce a table with the city brand
identities and positions for each of the 15 cities and then assess the credibility for
each cell in the table.
To compile this table, we collected the following data:
1. The city brand identity as shown in their most recent Urban Master Plan
(UMP);
2. The city brand identity as found on their municipal government website;
3. The dominant use of city labels as found in their UMPs reflecting their brand
position;
4. The dominant use of city labels on their internet websites reflecting their
brand position; and
5. A city’s adoption of and inclusion in national sustainable urban develop-
ment programs, such as on environmental protection or Smart City devel-
opment, but also the protection of cultural heritage and the preservation of
Iranian-Islamic identity or the identity of city and countryside characteris-
tics. These target ‘ecological modernization’ in Iran by promoting aspects of
social, economic, and/or environmental sustainability. This reflects their ef-
forts to flesh out the above brand position in terms of policy actions.
I assumed it to be more reliable to establish city brand identity on the basis of
two indicators (1 and 2) and city brand position on three indicators (3, 4, and 5).
While the brand identities were composed of essential self-descriptions and phrases
these cities give of themselves in the UMPs and on their websites, the city labels in
Table 5 had to be gathered in a more pre-structured manner. Inspired by earlier work
where 10–12 key city labels were distinguished in the academic literature (De Jong
et al., 2015), in the Randstad and Rhine-Ruhr areas (Goess et al., 2016), and in a va-
riety of Chinese regions (Han et al., 2018; De Jong et al., 2018), I also found a number
of recurrent city labels typical of the Iranian context. The labels were eventually used
were Smart City, digital city (including E-City, ICT-city, and virtual city), innovation
24 The Credibility of City Brands: Method
2
city, manufacturing city, service city, knowledge city (including education city), cre-
ative city, resilient city, liveable city (including green city, garden city, juicy city, and
smooth city), tourism city (including health city, natural eco city, religious city, and
beautiful city), and sustainable city. I simply made counts of the appearance of each
of these city labels in the UMPs and on official municipal websites and presented
these counts in a table (Table 5). However, since the format, density, and size of
UMPs and websites differed across cities, the numbers given in them cannot be eas-
ily be compared across cities. I decided to group similar variants under one label. As
with the brand identities I gathered them from the cities’ UMPs and websites, but I
also analyzed which cities had successfully applied for, and had been accepted, in
one of the national sustainable urbanization programs. This enables them to use the
label or reputation associated with that particular high-brow program and is, thus,
a valid third indicator of dominant use of city brand positions. Nevertheless, the
consistency of visible labels choice is debatable. Since we can measure internal com-
mitment to the labels mentioned in the website and UMPs, the assumption is that
consistency of choice is a sign of commitment.
The original goal of this study had been to systematically apply the six criteria
for credible city branding to the scores of the 15 cities as shown in Table 1:
Table 1- Criteria for credible city branding.
Credibility
As-
pect/City
Generating
Feelings of
Royalty
Facilitating
Overarching
Strategy
Evoking
Positive
Feelings
Demon-
strating
Unique-
Allowing
different,
Non-Con-
tradictory
Messages
Logically
Connect-
ing
Past,
Present
and Future
City A
City B
…
…
Etc.
However, when making the first tentative efforts to apply these credibility fac-
tors to the various data on the Iranian cities, it transpired that not all of them were
amenable to measurement and/or unambiguous outcomes. This was specifically the
case with ‘generating feelings of loyalty’ and ‘evoking positive feelings’ and mostly
strongly with issues of religion, which would typically lead to bipolar outcomes
(strongly positive or negative feelings about Iranian-Islamic identity). In this credi-
bility assessment I restricted the analysis to the other four factors and applied these
to the city branding practices of each city (an overall impression of the findings on
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 25
2
brand identity and use of city labels) with three possible scores: high, medium, and
low.
2.4. THE MAIN FEATURES OF IRAN’S MEGACITIES IN BRIEF
Before analyzing and interpreting the branding practices in Iran’s 15 megacities
with over 500,000 inhabitants, it is important to have a general impression of their
dominant demographic, economic, social, and cultural features. These features color
the position from which cities brand themselves and determine the developmental
options they have. The megacities are, in descending order of population numbers:
Tehran, Mashhad, Isfahan, Karaj, Tabriz, Shiraz, Ahvaz, Qom, Kermanshah, Ure-
mia, Rasht, Zahedan, Kerman, Arak, and Hamedan (see Figure 1 and Table 2). Fig-
ure 1 demonstrates the topographic position of the cities, Table 2 presents their pop-
ulation numbers and territorial size, while Table 3 at the end of the section summa-
rizes all other relevant geographic data of the cities.
Figure 1- Fifteen Iranian megacities
1
4
10
5
2
3
6
7
9
11
12
13
15
14
26 The Main Features of Iran’s Megacities in Brief
2
Table 2- Population and space of Iran’s megacities
City
Population (2011)
Space (km
2
)
1
Tehran
8,154,051
750
2
Mashhad
2,749,374
300
3
Isfahan
1,756,126
235
4
Karaj
1,614,626
165
5
Tabriz
1,494,988
190
6
Shiraz
1,460,665
225
7
Ahvaz
1,112,021
140
8
Qom
1,074,036
95
9
Kermanshah
851,405
90
10
Urmia
667,499
90
11
Rasht
639,951
60
12
Zahedan
560,725
75
13
Kerman
534,441
85
14
Arak
526,182
60
15
Hamedan
525,794
70
Tehran has been the nation’s capital for more than 200 years and currently
counts approximately 8 million regular inhabitants and an additional floating pop-
ulation of 4 million. It has 16.2% of Iran’s entire population. In addition to being its
political capital, Tehran is also an important administrative, economic, and cultural
metropolis. Three dominant industries in Tehran province in terms of investment
amount are food and beverages, rubber and plastics, and manufactured metal prod-
ucts (Statistical Center for Iran). Tehran is the focal point of Iran’s transportation
network and the area where more than 40% of the nation’s economic activities take
place. Tehran is a melting pot of ethnic groups, languages, and numerous Persian
dialects and accents. Having a wide range of high-ranked universities, innovative
businesses, and startups in comparison with others, their use of the term
‘knowledge-based’ is not far-fetched.
Mashhad (meaning ‘place of martyrdom’ in Arabic) is the capital of the central
Khurasan province and the greatest religious metropolis in the country. It is home
to about 8% of Iran’s population. It is the site of the very large Imam Reza (the Shia
imam murdered by Arabian Nights caliph Haroun al-Rashid) shrine that draws
more than 20 million Shia pilgrims a year. The city’s population numbers around 3
million in recent years and 55% of Iran’s hotels are located in Mashhad. Mashhad is
also the city of saffron. For this reason, agricultural and service sectors have an even
greater share in its added economic value than manufacturing and mining. The three
dominant industries in the central Khurasan province are; food and beverage, metal
products and textile (Statistical Center for Iran).
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 27
2
Isfahan is Iran’s third most populous city and the capital of Isfahan province. It
has historically been among the most important urban centers on the Iranian plateau
and counts a large number of historical monuments: bridges, caravanserais, mina-
rets, and mosques, attracting a major share of the tourists in Iran. Petroleum prod-
ucts and nuclear fuels, fabricated metal products, and textile production are three
dominant industries in Isfahan province (Statistical Center for Iran).
Located near Tehran, Karaj is one of the primary destinations for immigrants.
Many believe that if Karaj did not exist, Tehran would have no room to breathe with
all its immigrants, air pollution, and lack of green space. Karaj, due to massive im-
migration, is a microcosm of all cultures and ethnicities in Iran and has become one
of Iran’s economic and cultural pillars. Located near Tehran, it has accommodated
many industrial towns around the city causing considerable environmental prob-
lems. The opening of Tehran-Karaj metro has added to the flourishing of Karaj.
Food, equipment, and machine manufacturing and chemical products constitute the
industrial core of Alborz province in which Karaj is located.
Tabriz city, one of the ancient Turkic cities has the world’s largest historical
indoor bazar and is known as a UNESCO world heritage site, of which hand-woven
carpets are a key element. Ministers of tourism in Islamic countries selected Tabriz
as the capital of Islamic tourism in 2018. Petroleum products and nuclear fuels, food
and beverage products, and chemical products are the three dominant industries in
East Azerbaijan province (Statistical Center for Iran).
Shiraz; the capital of Fars province, has been the city of poetry and Persian lit-
erature, philosophy, and ethics for a long time. Until the Islamic revolution, Iran had
a tradition of wine-making which stretched back centuries. It centered on the ancient
city of Shiraz. Different people have lived in the Fars province, such as the Aryans,
the Samis, and the Turks, who worked together to form the Iranian culture (Iran
Chamber Society). Shiraz is also the birthplace and resting place of the great Persian
poets Hafez and Saadi. The most interesting buildings in Shiraz are located in the
old part of the town. The largest share of value added in Fars province is related to
agriculture; cultivation, and horticulture. With regard to industry, the three sectors
with the highest value-added are food, the production of petroleum, and chemical
products (Statistical Center for Iran).
Ahvaz is one of the key strategic metropolises of the country in that it contrib-
utes enormously to the nation’s GDP (gross domestic product) with its oil produc-
tion and refineries. Since much of its wealth is donated to the national coffers, while
it is left with severe environmental problems itself, it has seen a large number of
protests in recent years. It is said that ‘Ahvazies get only pollution, disease, and
death from the oil trade’ (Ahvaz Monitor). According to a recent air quality survey
by the World Health Organization, Ahvaz is one of the world’s most polluted cities
28 The Main Features of Iran’s Megacities in Brief
2
with the highest count of small airborne particles out of 1100 urban areas around the
world. As can be expected, the largest share of its the value added comes from pe-
troleum products and chemical products (Statistical Center for Iran).
Iran’s second pilgrimage center after Mashhad, Qom (Ghom), is home to the
magnificent Massoumeh shrine and shrines for various other Shiite scholars; stu-
dents come from around the world to study in its madrassas and browse in its fa-
mous religious bookshops. Receiving the pilgrims (providing accommodation, ser-
vices, and facilities) and being the center of religious learning have, along with its
proximity to Tehran, led to substantial population growth (Kiyani Haftlang, 2003).
Since Kermanshah is located in the middle of the Zagros Mountains, and be-
tween two cold and warm regions, it enjoys a moderate climate (Iran Chamber So-
ciety). Much of the industrial activity of the province is concentrated in its capital
city. An early modern industrial enterprise, established in 1962, is the Bisotun sugar-
refining factory. The most notable enterprise of all is Kermanshah’s oil refinery,
which was completed in 1971. There are also several operative factories of medium
size that manufacture textiles for local consumption. Other industries include food
processing, electrical and mechanical appliances, and cement and construction ma-
terials, as well as mining of marble and limestone throughout the province (Iran Re-
view).
Urmia, another ancient Turkic city and the capital of West Azarbaijan province
is located on vast green plains and surrounded by vineyards and apple orchards.
Recently, Urmia’s greatest challenge has been to preserve Lake Urmia. Lake Urmia
was twice as large as Luxembourg and the largest salt-water lake in the Middle East.
Since then it has shrunk substantially, and it was sliced in half in 2008, with conse-
quences uncertain to this day, by a 15-km causeway designed to shorten the travel
time between the cities of Urmia and Tabriz (Madani, 2016). The agricultural sector
adds the largest share of economic value-added in West Azarbaijan province. Food
production and non-metallic minerals manufacturing are the dominant industries
in this province.
Rasht is located by the Caspian Sea where it was one of the cities along the Silk
Road route. It joined the world’s creative cities network under UNESCO as a creative
city for gastronomy. Rasht and Hamedan are among the provincial centers of the
country considered as great agricultural centers of the country. Surrounded by the
fertile delta of the Sefīd-Rūd River, both the city and its gastronomy benefit from a
rich variety of natural resources, especially various species of fish and in-season
products. Above all, gastronomy in Rasht is synonymous with the protection and
promotion of cultural heritage (Creative Cities Network). Thus, the highest value-
added in industry is from food.
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 29
2
Zahedan is the capital of Baluchistan province in Iran. It is a border city con-
necting Iran with Pakistan. It is one of the largest regions in Iran, but it is less devel-
oped than much of the rest. Research carried out in this province and its cities indi-
cate that on all four economic, environmental, social, and health aspects, Baluchistan
ranks almost at the bottom of all Iranian provinces (Zahedan City Council).
Kerman is an ancient city located on the edge of the Lut Desert in the central
south of Iran and the capital city of Kerman province. It has been famous for cumin
and opium. Kerman and Zahedan are on the trade route opening Iran and Europe
to the opium trade from Afghanistan. A large share of the GDP in agriculture in
Kerman province is based on pistachios. Metal and steel manufacturing are the dom-
inant manufacturing industries in Kerman.
As a major industrial city, Arak hosts several industrial factories inside and
within a few kilometers outside of the city. As an industrial city in a developing
country Arak is subject to serious pollution. This city, only 200 years old, officially
became a megacity in 2014. The main agricultural products of the city are grain, bar-
ley, and fruits, including grape, apple, walnut, and almond. Arak also exports hand-
knotted carpets which are generally referred to as Sarouk rugs. After Khuzestan (in
which Ahvaz is located) and Tehran, Markazi province (with Arak in it) has the
highest GDP per capita among Iranian megacities. Petroleum products, chemical
products, and non-metallic minerals are the dominant industries (Iran Chamber So-
ciety).
Hamedan is a very historical city, since it was the capital of the empire of the
Medes until they forged a union with the Persians. It also served as the summer
capital of the Achaemenid Empire. Its modern version in Iran’s mountainous region
was designed by Karl Ferisch, a German engineer, as a city concentric in shape. Ha-
medan is famous for pottery and ceramics and it has an influential group of envi-
ronmental advocates who use the power of the media to preserve the environment
and the ancient city texture. Food production and the manufacturing of non-metallic
minerals add the lion’s share to its industrial value-added (Iran Chamber Society).
30 City Branding Practices in Iran’s Fifteen Megacities
2
Table 3-Key economic data of Iranian megacities (Statistical Centre of Iran, 2017)
Province
Capital
City
GDP
Value Added (%)
Value
(Billion
Rial)
Share
(%)
Per
Capita
Agri-
culture
Industry
and
Mining
Ser-
vices
Iran
6225.66
100
82.8
100
100
100
Tehran
Tehran
1436.432
23.1
117.9
3.9
11.8
36.4
Central
Khurasan
Mashhad 331.292 5.3 55.3 6.7 3.3 6.9
Isfahan
Isfahan
416.864
6.7
85.4
4.1
7.9
6.0
Alborz
Karaj
157.793
3.5
65.4
1.7
1.5
3.6
East Azer-
baijan
Tabriz 207.139 3.3 55.6 4.6 3.2 3.2
Fars
Shiraz
262.028
4.2
57
8.7
3.0
4.5
Khuzestan
Ahvaz
836.240
13.4
184.5
6.8
25.0
4.3
Qom
Qom
59.520
1.0
51.7
0.8
0.8
1.1
Kermanshah
Kerman-
shah
106.086 1.7 54.5 2.4 1.2 2.1
West Azer-
baijan
Urmia 125.717 2.0 40.8 4.6 1.0 2.5
Gilan
Rasht
126.891
2.0
51.1
3.0
1.3
2.6
Sistan
Zahedan
75.230
1.2
29.7
2.6
0.5
1.6
Kerman
Kerman
164.053
2.6
55.8
7.1
2.3
2.2
Markazi
Arak
125.424
2.0
88.7
2.2
2.3
1.7
Hamedan
Hame-
dan
88.882 1.4 50.6 3.5 0.8 1.7
2.5. CITY BRANDING PRACTICES IN IRAN’S FIFTEEN MEGACITIES
Table 4 presents the city brand identities of all 15 megacities as expressed in
their Urban Master Plans and as found on their official local government websites.
It is important to realize that there is no common format in either UMP or local web-
sites, so each city presents itself to the outside world in a different way. While some
cities incorporate strategic visions others, such as Kermanshah and Zahedan, mainly
display action plans.
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 31
2
Table 4- City brand identities in Urban Master Plan (UMP)s and on websites.
Brand
Identity
Indicator
/City
City Brand Identity as in UMP
City Brand Identity as on Of-
ficial Website
Tehran
Tehran is a world-class cultural,
knowledge-based city, with authentic Per-
sian and Islamic identity, beautiful, resili-
ent, a benchmark for the Islamic world.
Alive and prosperous, with a thriving
economy based on cultural industries and
higher education services. These features
will make our city an ‘educated city’.
Tehran, City of Hope, Part-
nership and Prosperity. Teh-
ran; Smart, Innovative and
Knowledge City.
Mashhad
Mashhad is a holy city with a unique reli-
gious-pilgrimage oriented identity on the
national and global scale; lead in sustaina-
ble urban development at the national level
with a global approach by relying on a
knowledge-based economy, advanced in-
dustries and superior services, especially
pilgrimage services, tourism and natural
tourism.
Mashhad; A Smart City; City of
Hope and Life
Isfahan
Isfahan Capital of Islamic Culture and Civ-
ilization; the cradle of elites, source of In-
spiration and Embodiment of Islamic Civi-
lization. A creative city with faithful, glad
and knowledgeable people. A beautiful,
green and Smart City with Iranian Islamic
architecture. Professionally run city with a
dynamic economy and a high quality of
life. A productive city based on science,
technology and tourism. An exciting city
with prominent culture, art and tourism
and the best city in Iran to live in.
Isfahan, the beautiful city of
God, with turquoise domes,
the Islamic Cultural Capital of
Iran and a creative city.
Karaj
Karaj; A Sustainable city ensuring quality
of life, providing superior services, with
the economic opportunities of a metropoli-
tan capital in terms of investment and em-
ployment, with relative self-sufficiency, fa-
vorable for tourism and leisure activities. A
resilient and environmentally friendly city.
Karaj; a miniature Iran. “A
city with an Iranian Islamic
Identity”, “A Sustainable City
with Public, Lively, Succulent
and Prosperous Spaces”, A
smart and Knowledge-based
City. “A Justice-Driven City
where Social and Economic
32 City Branding Practices in Iran’s Fifteen Megacities
2
Brand
Identity
Indicator
/City
City Brand Identity as in UMP
City Brand Identity as on Of-
ficial Website
Inequalities have been re-
moved”, “A creative and eco-
nomically robust city with
strong foun
dations to serve
Iran as a while”, A “sustaina-
ble city” residence, activity
and leisure are well- inte-
grated, “ A city with prosper-
ous, innovative, hopeful and
joyful citizens “. A resilient
city.
Tabriz
Tabriz, a city with a strong historical and
cultural background. Tabriz is one of the
most prominent faces of the Islamic city
and is one of the most important academic
centres of the country and the largest scien-
tific pole of Northwest Iran. Turkish lan-
guage symbolizes the local identity of the
city. “Tabriz City of the Firsts”; the first
printing house, the first school, the first
school for deaf, the first machine produced
coins, the first chamber of commerce, the
first municipality and the first township.
Tabriz is the fourth largest
city and one of the historical
capitals of Iran. “City without
beggars”, “Iran’s safest me-
tropolis”, “World of Carpet”
and the cleanest city in Iran.
The Capital of Tourism
among Islamic Countries in
2018.
Shiraz
Shiraz the Religious and Cultural Capital
of Islamic Iran. A smooth City for traffic,
green and safe. A capable city in urban
management and investment attraction. A
city for life, work and leisure. Shiraz is a
Centre for tourism (religion, sports, nature,
health, history and culture) at the national
and international levels. An ICT City for
services on the Persian Gulf coast. A beau-
tiful, coherent and shiny city.
Shiraz, the city of “Raz
[means mystery]”. The cul-
tural capital of Iran and the
second largest literary city in
the world, the third religious
city in Iran.
Ahwaz
Ahwaz is a clean, safe, commercial, indus-
trial and tourism city with high social well-
being based on continues cultural, social
and managerial growth in Southern Iran. A
tourism city in five years time.
Ahwaz has had many births
throughout history, and what
has been reminiscent of this
glorious millennial treasure is
a rich culture and small me-
morials left over from the last
century.
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 33
2
Brand
Identity
Indicator
/City
City Brand Identity as in UMP
City Brand Identity as on Of-
ficial Website
Qom
Qom is the capital for the production and
publication of religious thoughts and Shiite
teachings, a world-wide pilgrimage city, a
pattern of Islamic modernity. Qom is one
of the main poles of religious tourism.
Qom, pilot city for religious
diplomacy at the interna-
tional level, a large workshop
for construction projects, with
efficient urban transportation;
A Smart City. Qom is a desert
that becomes green.
Kerman-
shah
n.a
Only profiling actions mentioned
Kermanshah is a beautiful
face and stout chest of Islamic
Iran.
Urmia
Urmia is a cultural city, developed and cit-
izen-oriented. One of the oldest Iranian cit-
ies on a lush flood surrounded by apple
and grape gardens.
Urmia is the land of beauty;
Land of Understanding and
Peaceful Coexistence. The city
of apple and grapes. Urmia is
one of the oldest volleyball
cities in Iran.
Rasht
Rasht is the most important centre for lei-
sure and travel activities in terms of natural
attractions. The industrial area in Rasht is
one of the most important projects in the
Caspian Sea region.
The beautiful city of Rasht is
located in the most important
region in the province of Gi-
lan, no word can describe this
lush and beautiful area and it
should just be seen. Rasht is
named the “city of silver fre-
quent rains” due to rain and
thunderstorm.
Zahedan
n.a
Only profiling actions mentioned
Zahedan is the capital city of
the Province of Sistan and Ba-
luchestan and one of the
youngest provincial capital
cities in the country. Zahedan
is connected to both Pakistan
and Afghanistan via roads.
Kerman
Kerman; A city to live in with vitality and
sustainable city development. The gateway
to history and identity, the pole of tourism
in the East and South-east for the ancient
civilization of Islamic Iran. The historical
civilization in Kerman is perpetuated in the
academic and cultural activities.
Kerman has been usually one
of the most important cities in
tourism and every year has
been host for many internal
and external guests. It’s the
centre of Southeast and also
34 City Branding Practices in Iran’s Fifteen Megacities
2
Brand
Identity
Indicator
/City
City Brand Identity as in UMP
City Brand Identity as on Of-
ficial Website
its cultural economic, indus-
trial, social and political refer-
ence point in the Southeast.
Arak
Arak, a city near the Zagros Mountains,
Iran’s Industrial Pole. Iran’s central trans-
portation hub.
Arak, a city on the central
plateau of Iran, and its indus-
trial capital.
Hamedan Capital of Iranian History and Civilization.
Hamedan; an E-city and a
Cradle of History. Hamadan
is one of the most ancient cit-
ies in Iran and an emerald
jewel in the western region of
ancient Iran, One of the six
historical and cultural cities of
the country.
When comparing the style many of the above cities adopt in presenting them-
selves with those found in previous studies on Germany, the Netherlands (Goess et
al., 2016), and China (Han et al., 2018; De Jong et al., 2018) it stands out that religious,
cultural, and natural features are much more prominent in cities’ self-images and
that the focus on history is also stronger. This does not mean that a view of future
economic development is absent, but it essentially only appears among the subset of
cities that already economically do better. All taken together, a division can be made
into five types of Iranian megacities based on their brand identity choices:
1. Cities eager to adopt the complete package of religious, cultural, and mod-
ern technological amenities. This implies they are proud of their natural
and/or cultural treasures and Islamic significance, but they also want to
share in high-tech development boosting the future economic profile of their
city. This applies to Tehran, Mashhad, Isfahan, Shiraz, and Qom.
2. Cities adopting a modern, multi-cultural profile seeing themselves at the
confluence of various migration and ethnic streams and deriving character
and strength from diversity without leaning on tradition much. Karaj be-
longs to this category.
3. Cities with a strong industrial and manufacturing profile, based on petro-
leum and chemicals. Even though they may express a desire to diversify into
tourism, the credibility of realizing this is limited for the moment. Ahwaz
and Arak are in this industrial group.
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 35
2
4. Cities with abundant natural and agricultural treasures, and sometimes
quite poetic ways of describing themselves, but with a comparatively low
profile in industry and services. These cities are Tabriz, Urmia, Rasht, Ker-
man and Hamedan.
5. Cities with a weak economic profile and an essentially negative self-percep-
tion that mention only action points and features of transport accessibility
in their brand identity. Their self-image seems neither strongly rooted in
past heritage nor in future ambitions. Kermanshah and Zahedan are in this
group.
It becomes apparent that there is a strong correlation between economic
strength and professionalism in branding, with cities in groups 1 and 2 having both
city brand identities that generate emotional appeal, are amenable to the develop-
ment of an overarching strategy or policy, demonstrate a certain level of uniqueness
and allow for different yet non-contradictory messages to various stakeholders, and
connect past heritage, current profile, and future ambitions. Karaj is stronger in its
multi-cultural uniqueness and leans less on the past, Tehran is special in its global
ambitions, while the other cities in group 1 are strongest in connecting the past, pre-
sent, and future. While cities in group 3 are strong in their industrial profile, the
attractiveness of this profile as a city brand identity has obviously shrunk in the face
of severe environmental deterioration. Cities in the fourth group, on the other hand,
have attractive cultural identities in many ways: they demonstrate uniqueness and
lean strongly on natural or cultural treasures. However, their messages are not fu-
ture-oriented, allow for little economic variety, and cannot be seen as a strong start-
ing point for an overarching policy strategy. This severely restricts their practical
appeal for ecological modernization. The cities in the fifth group, finally, appear to
be so fully absorbed in getting by to pay any attention to branding at all.
Table 5 presents the dominant city labels of all 15 megacities as expressed in
their Urban Master Plans and as they are found on their official local government
websites. In the final column, it also demonstrates into which national city programs
each of them have been incorporated. Again, the website of Mashhad City proved
unavailable.
In line with our findings in Table 4, we see that the economically more powerful
cities also tend to adopt higher numbers and a greater variety of city labels; they are
also included in more city programs, helping them boost their urban structure and
profile. Tehran, for instance, is included in all of them, and so is Shiraz. It is also
intriguing that exactly all cities identified before in group 1 are included in the na-
tional Smart City program, and that just Urmia from the fourth group has been
added. Moreover, all cities in the first group with strong traditions in Islamic archi-
tecture (Mashhad, Isfahan, Shiraz, and Qom) also boost their tourist profile through
36 City Branding Practices in Iran’s Fifteen Megacities
2
the use of the city label ‘tourism city’. Karaj (group 2) is not a Smart City and also
does not promote itself as such, but it has firmly placed its focus on sustainability,
livability, and knowledge. Among the industrial cities (Ahvaz and Arak) choices of
city labels and adoption in national programs is comparatively weak, but to the ex-
tent that these exist, they reveal a wish for increases in tourism, livability, and sus-
tainability. Among the cities with weaker economic profiles, but potentially rich in
natural and cultural treasures (fourth group), and generally weak economic struc-
tures (fifth group), Hamedan stands as being by far the most ambitious by using
such terms as sustainable, tourism, digital, smart, livable, and resilient. Urmia is in-
triguing by focusing entirely on smart. Zahedan is significant at the very other ex-
treme by not mentioning any term at all. Most others are in between these outcomes.
More generally, however, consistency in the choices made in the various columns
are a sign of commitments and focus rather than name-dropping. In that sense, Teh-
ran, Isfahan, Karaj, Urmia, and Hamedan seem to stand mostly firmly behind the
branding and policy choices made and, in that sense, the credibility of their use of
labels and adoption of national city programs can be expected to be highest. Incor-
poration of their branding approach in an overarching policy strategy, therefore,
seems most likely, making its transformative capacity towards ecological moderni-
zation highest. In most other cases, the use of labels appears more as a haphazard
use of popular urban denominations than as actual reflected adoption and system-
atic application of city labels. A table offering a systematic assessment of the four
credibility factors applied to the city brand identities and use of city labels is pre-
sented in Table 6. The findings are in line with the general impressions obtained in
Tables 4 and 5 on city brand identities and the use of city labels, and can be used by
individual cities to evaluate and monitor ‘how well’ they do in their city branding
practices and what is open to improvement. We should add here that the factors
with emotional appeal (generating loyalty and conveying positive feelings) were
omitted from the analysis due to a lack of measurability (see Section 3).
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 37
2
Table 5-Use of city labels in UMPs and on websites, and the adoption in national
programs.
City Brand
Position/City
Dominant City La-
bels as in UMP
Dominant City La-
bel as on Website
Visible Engagement in Na-
tional City Programs
Tehran
Knowledge (8)
1
Global (7)
Smart (4)
Creative (3)
Innovation (1)
Smart (7)
Knowledge (3)
Innovation (2)
Knowledge-based develop-
ment
Smart City program
Preservation of Iranian-Is-
lamic identity
Identity of the city (global
metropolis)
Mashhad
Livable (6)
Global (6)
Tourism (5)
Sustainable (4)
Knowledge (3)
Digital (1)
Smart (8)
Tourism (6)
Livable (2) Sustain-
able (1)
Identity of the city (global
metropolis)
Smart City program
Isfahan
Tourism (6)
Livable (5)
Smart (4)
Creative (1)
Tourism (3)
Creative (1)
Iranian Islamic Culture
Preservation of Iranian-Is-
lamic identity
Smart City program
Karaj
Sustainable (5)
Resilient (3)
Livable (2)
Tourism (1)
Digital (1)
Manufacturing (1)
Sustainable (3)
Smart (1)
Knowledge (1)
Resilient (1)
Sustainable development
Tabriz Knowledge (1) Tourism (15)
Knowledge-based develop-
ment
Shiraz
Liveable (72)
Tourism (34)
Digital (15)
Smart (14)
Digital (6)
Preservation of Iranian-Is-
lamic identity
Smart City program
Sustainable development
The identity of the city
Ahwaz
Tourism (1)
n.a
Identity of the city
Qom Tourism (2)
Smart (3)
Tourism (1)
Digital (1)
Smart City program
Kermanshah
n.a
Livable (3)
n.a
Urmia
n.a
Smart (6)
Smart City program
Rasht n.a.
Creative (2)
Sustainable (1)
Sustainable development
38 City Branding Practices in Iran’s Fifteen Megacities
2
City Brand
Position/City
Dominant City La-
bels as in UMP
Dominant City La-
bel as on Website
Visible Engagement in Na-
tional City Programs
Zahedan
n.a
n.a
n.a
Kerman
Sustainable (3)
n.a
n.a
Arak
Sustainable (2)
Manufacturing (1)
Livable (1) Sustainable development
Hamedan
Sustainable (2)
Tourism (2)
Livable (1)
Sustainable (3)
Digital (2)
Smart (2)
Livable (1)
Resilient (1)
Sustainable development
1
Frequency count.
Table 6- Evaluating city brand credibility of Iranian megacities.
Credibility
Aspect/City
Facilitating
Overarching
Strategy
Demon-
strating
Uniqueness
Allowing Different,
Non-Contradictory
Messages
Logically Con-
necting Past, Pre-
sent, and Future
Tehran
high
high
high
high
Mashhad
medium
high
High
high
Isfahan
high
high
High
high
Karaj
high
high
High
medium
Tabriz
high
medium
Medium
high
Shiraz
high
high
High
high
Ahvaz
low
low
Medium
medium
Qom
high
medium
Medium
medium
Kermanshah
low
low
Medium
medium
Urmia
medium
medium
Medium
medium
Rasht
medium
high
Medium
medium
Zahedan
low
low
Low
low
Kerman
high
low
Medium
medium
Arak
medium
high
Medium
medium
Hamedan
medium
low
High
high
When applying the four credibility factors in a systematic way we consider
scoring each factor as below:
• facilitate the development of an overarching strategy or policy; high if align-
ment with a national program appears in both brand identity and position;
medium if it aligns with one of them; and low if seen in neither;
• demonstrate uniqueness or distinctness; high if the unique highlight ap-
pears in both brand identity and position; medium if it appears in only one
of them; and low if seen in neither;
Towards Credible City Branding Practices: How Do Iran’s Largest Cities Face Ecological
Modernization? 39
2
• allow for different yet non-contradictory messages to various stakeholders;
high if their profile covers all environmental, economic (technological and
industrial), and cultural aspects; medium if they cover one or two aspects;
and low if none is mentioned; and
• logically connect past heritage, current profile, and future ambitions; high if
their brand shows promotional promises and current situation as well as
past heritage; medium if two of them are seen; and low if only one or even
none is mentioned.
As it can be seen, in two heads of the assessment spectrum the cities of Tehran,
Isfahan, and Shiraz reflect top scores, and Zahedan has the lowest rank.
2.6. CONCLUSION
Like cities in other nations and regions around the world, Iranian cities have
also increasingly engaged in city branding practices that are potentially conducive
to industrial transformation and ecological modernization. The nuclear deal open-
ing their economy to stronger international influence has made them more amenable
to trends in global competition. Especially since it has become obvious that oil and
gas, as non-renewable natural resources, have a limited future timespan and gener-
ate considerable ecological damage as a result of their exploration and exploitation,
some of Iran’s megacities have begun to engage in city branding practices. Adopting
city brand identities and using various attractive city labels play crucial roles in their
attraction of alternative investors, corporations, and other stakeholders that can con-
tribute to the ecological modernization they aspire to. The question is, however, to
what extent their branding choices can be assessed as being credible. In order to
evaluate this, we identified six factors for credible city branding practices from the
academic literature on the topic. These were found to be the potential to (i) generate
feelings of loyalty; (ii) facilitate the development of an overarching strategy or pol-
icy; (iii) evoke positive feelings; (iv) demonstrate uniqueness or distinctness; (v) al-
low for different, yet non-contradictory, messages to various stakeholders; and (vi)
to logically connect past heritage, current profile, and future ambitions. Four of these
factors (2, 4, 5, and 6) proved fit for application to the branding practices in Iran’s 15
megacities and led to an assessment table offering an impression of how well each
city did on which factor.
This study has shown that compared to how city branding is deployed in the
face of ecological modernization, Iranian large cities pay ample attention to aspects
of past heritage and to cultural and religious identity, and (to a certain extent) natu-
ral beauty. It is obvious that all Iranian cities boasting religious shrines and monu-
ments cherish these cultural aspects in their identity. Religion is undoubtedly the
root aspect of their identity in Mashhad, Isfahan, Shiraz, and Qom and seen as an
40 Conclusion
2
important basis for tourism and pilgrimage. Science and technology also appear as
relevant among Iranian megacities, but only among the economically-leading cities.
The wish to transition from manufacturing to services is not nearly as prominent as
in Europe (Goess et al., 2016) and China (De Jong et al., 2018; Hans et al., 2018).
Among all fifteen cities under study (all with over 500,000 inhabitants), we de-
veloped a classification of five types: (i) cities eager to adopt the complete package
of religious, cultural, and modern technological amenities (Tehran, Mashhad, Isfa-
han, Shiraz and Qom); (ii) cities adopting a modern, multi-cultural profile, and de-
riving character and strength from diversity without leaning on tradition (Karaj);
(iii) cities with a strong industrial and manufacturing profile, based on petroleum
and chemicals; (iv) cities with abundant natural and agricultural treasures, and
sometimes quite poetic ways of describing themselves, but with a comparatively
weak profile in industry and services (Tabriz, Urmia, Rasht, Kerman, and Hame-
dan); and (v) cities with a weak economic profile and an essentially negative self-
perception that mention only action points and features of transport accessibility in
their brand identity (Kermanshah and Zahedan).
It appears that representatives in the first group tend to be sophisticated users
of city branding practices and they meet most of the criteria for credible city brand-
ing. The picture is far more mixed among the cities in the third, fourth, and fifth
groups. All the cities in the first group are adopted the national Smart City program
and among them Tehran, Isfahan, Shiraz, and Mashhad have the most credible
branding practices of ‘Smart’.
The picture sketched above is confirmed in Table 6, where the four measurable
factors influencing the credibility of city branding practices are systematically ap-
plied to all cities and from which individual cities can take clues as to which aspects
in their branding may be improved.
The findings in this study add a few significant insights to the existing academic
literature on the topic. They add knowledge on how cities in a nation that has re-
cently opened up to global competition and where religious considerations play a
vital role in information trends of economic development and urbanization, refract
the drive towards ecological modernization. Some trends, such as the emphasis on
sustainability and livability, tend to be generally shared, while others, such as
knowledge-orientation, smartness, and digitality, have been adopted among the
more developed cities. Chapter 5 will well introduce the four Iranian cities with the
credible brand of ‘smart’ and examines their readiness for bringing the branding
practices into action to become a Smart City. The follow-up researches in chapter 6
also indicate how these branding practices appear in the Smart City development
process to make quite sophisticated use of branding to promote their ecological
modernization.
41
3
INPUT-OUTPUT MODELLING FOR
SMART CITY DEVELOPMENT
The contents of this chapter have been adapted from the following peer-reviewed article: Noori, N.; De
Jong, M.; Janssen, M., Schraven, D.; and Hoppe, T. Input-Output Modelling for Smart City Development
Journal of Urban Technology 2020.
42 Introduction
3
3.1. INTRODUCTION
In the past decade, the popularity of using Smart City labels for sustainable
techno-driven urbanization has increased dramatically (de Jong, Joss, Schraven,
Changjie, and Weijnen, 2015; de Jong, et al., 2018). Smart City initiatives combine a
variety of ambitions reflected in the precepts for smart growth and ecological mod-
ernization, which suggest that continued economic growth is possible alongside de-
creased environmentally harmful output. This is achieved by steering production
and consumption more towards high-tech services. This list includes city concepts
like ‘sustainable cities,’ ‘eco cities,’ ‘low carbon cities,’ ‘knowledge cities,’ ‘infor-
mation cities,’ ‘innovation cities,’ ‘intelligent cities,’ ‘digital cities,’ and ‘Smart Cities.’
In particular, the popularity of the latter has skyrocketed in the past few years. The
bibliometric study by De Jong et al. (2015) into different types of future cities indi-
cated that the use of the Smart City label in the academic literature had already over-
taken the previous champion and umbrella term of ‘sustainable city’ by 2012. The
study counted the number of times that twelve city labels were mentioned (single
and plural) in the abstract, title, or keywords of academic articles or reviews until
2013 in Scopus
1
. Using the same procedure used by De Jong et al. (ibid.) in their
seminal work, I updated their study by including scientific articles and reviews that
were published afterwards (until the end of 2018). The results are presented in Fig-
ure 1. This figure indicates that the dominant position of the ‘Smart City’ has taken
on staggering proportions and has overtaken and completely eclipsed other terms.
This may reflect the importance attached to it in the world of planning and policy-
making.
Input-Output Modelling for Smart City Development 43
3
Figure 1- Frequency of appearance of different city labels over time in academic re-
search articles (Scopus, N = 6475 articles).
Equally significant is the shift of the ‘Smart City’ label in its relative position
vis-à-vis other future city labels in terms of its conceptual co-occurrence, as shown
in Figure 2. It clearly indicates that ‘Smart City’ has driven the ‘sustainable city’ out
of the center as a city label with the highest centrality score, and has taken over its
position, although smart and sustainable are still strongly interconnected.
44 Introduction
3
Publications between 1996 – 2013
(N=1666 articles)
Publications between 1996 – 2017
(N=6475 articles)
*(original figure obtained from De Jong et al.
2015).
*(updated figure following the methodology
procedure by De Jong et al. (2015), excluding
the results from that particular study).
Figure 2- Network diagrams depicting co-occurrence of twelve city labels in title,
abstract, and keywords in academic research articles (Scopus).
Although the ‘Smart City’ label has seen exponential growth in the number of
publications (Komninos and Mora, 2018), and its meaning has shifted, thus far there
are few indications that it has contributed in making cities ‘smarter’. Despite the fact
that the notion of Smart City development is increasingly popular
2
, one should also
notice that it has grown increasingly ambiguous for policy makers, city developers,
and practitioners who are in need of more systematic and fine-grained conceptual-
ization (Komninos and Mora, 2018). Various models (Chourabi, Nam, and Walker,
2012; Lee, Hancock, and Hu, 2013; Neirotti, Marco, Cagliano, Mangano, and Scor-
rano, 2014) have been developed to advance Smart City development, but all are
primarily descriptive in nature and offer few clues on how to flesh out Smart Cities
in practice.
The goal of the present chapter is, therefore, to map the various facets of the
Smart City, transform these into an Input-Output (IO) model, and provide an over-
view of design variables that can be handled when developing a (specific type of)
Smart City. The idea of IO modelling is to position and pinpoint key facets of the
Smart City and dynamics of Smart City development (Batey and Rose, 1990). Cov-
Input-Output Modelling for Smart City Development 45
3
ering all aspects of a Smart City is impossible and the aim is to develop a parsimo-
nious model that can help in making the main design decisions. The contribution of
the IO model is that it allows for conducting a dynamic analysis in various domains
represented within Smart Cities. The model makes facets of Smart Cities tangible
and transparent allowing decision-makers, city planners, developers, and engineers
to envisage what the relevant design variables are, which choices they can make,
and what their chosen type of Smart City may look like in practice. The main ques-
tion addressed in this paper is: How to develop a conceptual model to analyze Smart
City development that can also be used by policy makers and practitioners in rele-
vant decision-making processes? In order to answer the main research question, the
following sub-questions are used:
1. What are the key facets attributed to Smart City in the academic literature?
2. What are the key elements directly and indirectly related to Smart City de-
velopment? And how can they be used to develop and elaborate an IO
model on Smart City implementation?
3. How can this IO model for Smart City development be used?
To answer the first sub-question, I conducted a content analysis of the literature
and presented our main findings in a table. To conduct a systematic literature re-
view, first I started with identifying what has been written on the Smart City topic
in scientific journals and making decisions about the suitability of material to be
considered in the review (Cooper, 1988). Then I determined the relevant studies to
which specific research reveals domains and facets of the Smart City which provides
me a basis for including or excluding certain studies. And based on that, I extracted
the different determined domains of the Smart City addressing the first research
question (Cooper & Hedges, 2009). Besides, a bibliometric analysis was conducted
to map the structural linkages between the keywords in the Smart City literature. To
answer the second question, an IO modelling approach was used. This is presented
in the third section of this paper. IO is founded in systems theory (See Figure 3)
which translates sources (input) into policy deliverables (output) and identifies the
main decisions that can be made to transform inputs into outputs (Checkland, 1999).
46 Positioning and Pinpointing Key Facets of the Smart City
3
Figure 3- The IO model structure and its components (adapted from systems
theory, Checkland, 1999).
In order to answer the third question, I analyzed the grey literature on Smart
Cities and conducted interviews for the illustrative case of ‘Smart Dubai’ and trans-
lated these findings into terms that are used in the IO model. I thus examined how
the IO model could be applied and what type of Smart City ‘Smart Dubai’ can be
labeled as. In principle, I could have chosen any other case for our illustration pur-
poses, since I also had usable data for Amsterdam Smart City, Barcelona Smart City,
and Masdar City in Abu Dhabi, but Smart Dubai is less often described in the liter-
ature, yet it is highly innovative. Moreover, it involves comparatively high invest-
ments, shows progressive vision, recently appears in several international rankings
(i.e., the Global Smart City issued by Juniper Research, 2017; the Smart City Index
issued by Ernst and Young, 2017; or the global Smart City Discourse Network issued
by Joss et al., 2017; Top 50 Smart City Government rankings issued by Eden Strategy
Institute and ONGandONG, 2019), and has adopted an intriguing governance ap-
proach making it a good candidate of good practice and serving as an international
benchmark (Yigitcanlar, et al., 2018). The data collection for the Smart Dubai case
entailed conducting interviews, collecting text documents, and making site visits.
Several interviews
3
were conducted with smart Dubai officials and experts from
public and private organizations involved in the Smart Dubai program in 2018. I
participated in a research trip to Dubai. Interviews were recorded on a digital audio
recorder and transcribed using interpretative content analysis.
3.2. POSITIONING AND PINPOINTING KEY FACETS OF THE SMART
CITY
THROUGHPUT
APPROACH
PROCESS
FEEDBACK
LOOP
INPUTS
OUTPUTS
Input-Output Modelling for Smart City Development 47
3
Using the academic literature, key attributes of Smart Cities are identified in
order to answer the first research question. Currently, there are multiple and various
definitions of the Smart City concept (Chourabi, Nam, and Walker, 2012; Hollands,
2008; Caragliu, Bo, and Nijkamp, 2011; Yigitcalar, 2015). Table 1 shows that the va-
riety of definitions and aspects attributed to it have increased substantially over the
years. Moreover, the expectations that policymakers and analysts have of Smart Cit-
ies also vary, making the whereabouts of its implementation hazy.
As one can see, ICT infrastructure plays a key role in some of them, but the
meaning of ‘smart’ has broadened considerably and spread out to many urban in-
frastructures and services and aspects of livability and sustainability leading to a
great variety of ways in which ‘smart’ can be implemented.
Table 1- Smart City meanings and domains as used in the academic literature.
Source Meanings and Main Domains
Komninos (2008)
Use of networked infrastructures as a means to enable social, en-
vironmental, economic, and cultural development
Glaeser and Berry
(2006)
Role of human capital and education in urban development
Hollands (2008)
High capacity for learning and innovation, creativity, institu-
tions of knowledge production, and digital infrastructure for
communication
Caragliu and Nijkamp
(2011)
Considering the human and social capital, using ICT, sustainable
economic growth, role of management
Paskaleva and
Megliola (2011)
Better quality of life becoming a life-time outcome of urban func-
tioning
Kuk and Janssen
(2011)
Innovative information sharing technology, smart citizens, and
businesses
Schaffers et al. (2012)
Advanced infrastructures, sustainability, economic growth,
quality of life
Chourabi et al (2012)
Management and organization, technology, governance, policy,
people and communities, the economy, built infrastructure, the
natural environment
Anthopoulos (2015)
Resource, transportation, urban infrastructure, living, govern-
ment, economy, coherency
48 Positioning and Pinpointing Key Facets of the Smart City
3
Source Meanings and Main Domains
Lee et al. (2013)
Urban openness, service innovation, partnership formations, ur-
ban proactiveness, Smart City infrastructure integration, Smart
City governance
IBM
Planning and management services, infrastructure services, hu-
man services
ITU (2014)
Environmental sustainability, productivity, quality of life, eq-
uity, and social inclusion, infrastructure development
UN Habitat (2014)
Productivity and the prosperity of cities, urban infrastructure,
quality of life and urban prosperity, equity and the prosperity of
cities, environmental sustainability, and the prosperity of cities
ISO (2014)
Economy, education, energy, environment, finance, fire and
emergency response, governance, health, recreation, safety, shel-
ter, solid waste, telecommunication and innovation, transporta-
tion, urban planning, waste water, water, and sanitation
Neirotti et al. (2014)
Natural resources and energy, transport and mobility, buildings,
living, government, economy and people
Joss (2015)
Urban governance, technology infrastructure
Negro et al (2015)
People, information, knowledge, and ICT
Yigitcanlar (2015)
Joss et al (2019)
Sustainability; wellbeing and livability, economy, governance
Governance, infrastructure, international, digital technology, so-
ciety, economy, spatial planning, innovation, environment and
sustainability
Kitchin (2019)
Smart citizens, neoliberalism, technological solutionism
Figure 4 shows the results of the bibliometric analysis on key words around the
Smart City concept appearing in the academic literature. Internet of Things (IoT) is
clearly at the center of the whole graph and tightly connected with data related con-
cepts including big data, data analytics, security, and privacy. Yet, it is also linked
with a wide selection of concepts ranging from cloud computing, energy (i.e., re-
newable, smart meter, energy efficiency), and healthcare to, mobility, and even eth-
ics, trust, and social media. In the lower part of the graph, there are the governance
and sustainability related concepts.
49
Figure 4-Structural linkages between keywords in the Smart City literature, demonstrating the dominance of IoT (Publica-
tions between 1996 – 2018; N= 3573 articles).
1) The keyword ‘Smart city’ was removed from
this figure for readability.
2) Incidental linkages (i.e., one time co-occur-
rences) were removed from this figure for
50
Another extensive study (Anthopoulos, Janssen, and Weerakkody, 2015) con-
cludes that there is broad agreement among experts that essentially six dimensions
of the Smart City can be identified: people, governance, mobility, economy, environ-
ment, and quality of life. They propose these six dimensions as facets of the Smart
City which can be included in developing an integrated conceptual model. How-
ever, a missing crucial element is technology. Similarly, Chourabi et al. (2012) devel-
oped an integrative framework to identify crucial factors of Smart City initiatives
and examine how local governments imagine possible future Smart City initiatives.
This framework includes eight factors: management and organization, technology,
governance, policy context, people, economy infrastructure, and environment
(Chourabi, Nam, and Walker, 2012). Overall, the previous models are mainly fo-
cused on Smart City facets. Inspired by these previous modelling exercises, in this
study the goal is to determine where each facet is located in the Smart City develop-
ment process by classifying them as inputs, throughputs, and outputs. The only
model that adopted an input-process-output logic is Yigitcanlar’s multidimensional
Smart City framework (Yigitcanlar, et al., 2018). However, it still is too general for
practitioners and policymakers to pinpoint Smart City facets in inputs, throughputs,
and outputs.
More specifically, the proposed model in the present study consists of the fol-
lowing domains of the Smart City based on an extensive literature review:
• Modern ICT infrastructures and data (Hollands, 2008; Caragliu, Bo, and
Nijkamp, 2011; Kuk and Janssen, 2011; Steventon and Wright, 2006; Lee,
2009; Negre, Rosenthal-Sabroux, and Gasco, 2015; Cianci, Grieco, Boggia,
and Camarda, 2014; ISO, 2014; Joss, Sengers, Scheraven, Caprotti, and Da-
yot, 2019; Kitchin, 2014);
• Financial resources (ISO, 2014; Neirotti, De Marco, Cagliano, Mangano, and
Scorrano, 2014; Chourabi, Nam, and Walker, 2012; Florida, 2005; Lu, Zhu,
Li, and Wu, 2011; Yigitcanlar, 2014);
• Governance (Anthopoulos, 2015; (ISO), 2014; Neirotti, De Marco, Cagliano,
Mangano, and Scorrano, 2014; Lee, Hancock, and Hu, 2013; Chourabi, Nam,
and Walker, 2012; Hollands, 2008; Joss, 2015; Joss, Sengers, Scheraven,
Caprotti, and Dayot, 2019);
• Human infrastructure and entrepreneurial capital (Chourabi, Nam, and
Walker, 2012; Glaeser and Berry, 2006; Kuk and Janssen, 2011; Caragliu, Bo,
Input-Output Modelling for Smart City Development 51
3
and Nijkamp, 2011; Yigitcanlar, 2015; Yigitcalar, 2015; Munier, 2007;
Mortensen and Jonsbak Rohde, 2012);
• Smart citizens and applications (Neirotti, De Marco, Cagliano, Mangano,
and Scorrano, 2014; Kuk and Janssen, 2011; Chourabi, Nam, and Walker,
2012; Mortensen and Jonsbak Rohde, 2012; Streitz, 2011);
• Sustainability and high quality of life (Caragliu, Bo, and Nijkamp, 2011;
International Telecommunications Union, 2014; UN, 2014; Paskaleva and
Megliola, 2011; Schaffers, et al., 2012; Yigitcanlar, 2015; Cianci, Grieco, Bog-
gia, and Camarda, 2014; Munier, 2007; Yigitcanlar and Lee, 2014; Zhao,
2011).
The next step is to translate these into inputs and outputs to conceive of Smart
City facets for the conceptual model. When portraying the Smart City as an object of
urban development policy, I am convinced that it can be conceptualized as a process;
I group the eight domains of the Smart City mentioned above in two categories to
indicate how different facets are positioned vis-à-vis each other in the Smart City
development process:
1. Source-based (or need-oriented) domains refer to the needs and resources
for building a Smart City, such as modern ICT infrastructure, data, human
infra-structure and entrepreneurial capital, governance, and financial infra-
structure;
2. Target-based (or commitment-oriented) domains revolve around the re-
sults, the objects, and deliverables of Smart City promises. These include
smart applications and externalities.
In the following section we apply these categorized key facets to map our con-
ceptual model of the Smart City development process.
52 Conceptual Model
3
3.3. CONCEPTUAL MODEL
This section presents an IO model that has been developed for a city in an insti-
tutional environment in which a local government wishes to develop (itself into) a
Smart City, and policy makers draft and implement Smart City development plans.
The idea is that the various sorts of inputs of the Smart City vary and that there is
no such thing as ‘the’ Smart City, but there are various conceivable types of it. The
transformation from input to output and then back is determined by two arrows: (a)
a transformation process from input through throughput to output, and (b) an eval-
uation pathway (feedback loop) from output back to input. This flow is presented in
Figure 5.
Dynamic throughput:
• Data and infrastructure asset
management
• Knowledge and innovation
management
• Financial asset management
Governance and Leadership:
• Intergovernmental relations
• Coordination among actors
• Leadership capabilities
Smart city development process
Resources (input):
• Human resources and
entrepreneurship
• Data
• Modern ICT infrastruc-
ture
• Financial resources
Overarching policy, decisions, and attitudes
Applications (output):
• Mobility
• Energy
• Healthcare
• Smart government
• Smart citizens
Externalities (outcome):
• Environmental sustainability
• Economic sustainability
• Social sustainability/quality
of life
Figure 5
-Graphical conceptualization of the IO model for Smart City develop-
ment process (as compiled and drawn by the author).
Input-Output Modelling for Smart City Development 53
3
3.3.1. INPUT
Input refers to the domains of the Smart City for which goals are formulated
and re-sources made available. To characterize these resource-based domains, we
first define them, then pinpoint their application in Smart Cities, and finally sketch
what potential they offer for realizing the Smart City.
3.3.1.1 MODERN ICT INFRASTRUCTURE: INTERNET OF THINGS
From an engineering point of view, a Smart City is expected to deal with tech-
nology as well as the interconnection between technology and people (e.g., citizens,
governments, and companies). On the one hand, there is a need for smart urbanism
as an innovative solution for urban problems. On the other hand, the emergence of
the IoT through technology push gives it an increasingly important role in fulfilling
these expectations. As the Rothwell Innovation Model (1992) shows, the Smart City
can be viewed as an innovation resulting from the need to resolve urban issues and
the new technology push offered to deal with them (Rothwell, 1992). Accordingly,
the availability and quality of ICT infrastructures have become some of the main
resources for many cities aiding them to brand themselves as ‘smart’. ICT infrastruc-
tures can achieve: (1) ICT-enabled information and knowledge sharing; (2) ICT-
enabled forecasts; and (3) ICT-enabled integration (Gemma, 2014). State-of-the-art
ICT infrastructures, often referred to as Internet of Things (IoT), play a crucial role
in Smart City development since they act as a platform for the aggregation of infor-
mation and data and enable an improved understanding of how a city functions in
terms of resource consumption, services, and lifestyles. Janssen and Estevez (2013)
define the platform as a focal point where various type of actors interconnect in a
common area. There is a wide range of possibilities for Smart City development
based on this state-of-the-art technology and IoT platforms. The IoT infrastructure
for the Smart City refers to management of the city through connecting to physical
objects (through sensors, camera, RFIDs, etc.), using a large amount of real-time data
(energy and environment, transportation and traffic, healthcare, safety and. justice,
and business), transforming data into trustworthy and reliable information and de-
livering the right information to the right person at the right time in the most appro-
priate way.
3.3.1.2 DATA
In the present era, the competitive advantage is directly related to the level of
access to ‘data and information’. The higher the level of access to data, the greater
ability to control and enhance the future. But this is not valid for all data; data must
54 Conceptual Model
3
be processed, and made useful, reliable, and manageable. Provisioning aggregated
data through embedded sensors from traffic and transportation systems, buildings,
energy systems, and also people, products, and companies is crucial for developing
an integrated platform to communicate within the Smart City. IoT provides a plat-
form for sensors and actuator devices to communicate seamlessly within the Smart
City environment and enables increasingly convenient information sharing across
platforms. Furthermore, the physical infrastructure of the city must be integrated
into the digital and communicative infrastructure in order to increase the mobility
and effectiveness of the city and the administrative systems which connect its many
stakeholders. To do this, data is the linkage for making this connection. Big data,
sharing data, and open data platforms are required to have an IoT platform for real-
time data accessibility. For these reasons data as an asset is another key resource in
building a Smart City.
3.3.1.3 HUMAN RESOURCES AND ENTREPRENEURSHIP
Human resources and entrepreneurship refer to facilities honing human re-
sources and taking advantage of their expertise as well as the provision of facilities
for entrepreneurial initiatives. These should jointly promote the generation and im-
plementation of creative ideas driving innovation towards smart solutions.
There are three main reasons for considering human and entrepreneurial re-
sources as a source-oriented domain of the Smart City. First, although technology
and particularly modern ICT are the key enablers of Smart City initiatives (Chour-
abi, Nam, and Walker, 2012), a Smart City requires human involvement to become
effective. Second, entrepreneurship is one of the main drivers for a smart economy
to stimulate creativity and innovation. Finally, as Nam and Pardo (2011) stress, com-
munity commitment to the enactment and use of technology is crucial in initiating
Smart City initiatives (Nam and Pardo, 2011). Managerial and organizational factors
are also considered as important factors in Smart City development (Chourabi,
Nam, and Walker, 2012). Having research centers in place to foster creativity and
innovation related to the Smart City, building support structures for start-ups and
entrepreneurship, and establishing knowledge sharing programs are all potentially
fruitful ways to develop human and entrepreneurial infrastructures.
3.3.1.4 FINANCIAL RESOURCES
One of the important input facets for building such a techno-driven city is fi-
nancial resources which a Smart City requires to build modern IoT infrastructures.
Designing and equipping IoT platforms necessitates embedded sensors and actuator
devices to aggregate data and then having a connectivity layer which is responsible
Input-Output Modelling for Smart City Development 55
3
for transmitting aggregated data and an interface between embedded sensors and
the network server. Besides these, for security purposes, IoT platforms need invest-
ment in cyber security which is conducive to privacy and safety of all data within
the network through providing a secure and reliable substrate for data transmission
and big data storage. However, the Smart City is not necessarily just ICT-based, but
also deals with other aspects of innovation (Anthopoulos, Janssen, and Weerakkody,
2015). A Research and Development budget that is typically made available by local
government would also allow for fostering innovation and inventing smart solu-
tions (Hoppe, van der Vegt, and Stegmaier, 2016). In addition, some investment in
branding and training practices would enable the Smart City to attract more actors
(e.g., experts, citizens, investors, and business firms) to commit themselves. The pos-
sible funding sources for the Smart City can be funds provided exclusively by local,
regional, or state governments, but may also be obtained from public and private
co-funding arrangements, or even mainly private investment. Crowdfunding has
also become increasingly popular among start-ups, for it offers additional financial
resources (Carè, Trotta, Carè, and Rizzello, 2018).
3.3.2. THROUGHPUT
Throughput refers to managing and organizing of resources and assets and
making decisions about how to transform them into the output to achieve intended
goals and outcomes (Checkland, 1999). Throughput for Smart City development al-
lows for the modification and alignment of resources and processes within various
contexts (Gupta, Panagiotopoulos, and Bowen, 2015). Therefore, the process of
transforming input to output (which in system theory is known as throughput) re-
quires management, administration, and leadership skills and involves a variety of
actors. Dynamic throughput refers to the ability to manage the resources and de-
velop competencies in order to produce output (Teece, Pisano, and Shuen, 1997).
One of the most important Smart City capabilities is the ability to turn data into
value; providing reliable information in the context of Smart City (Gupta, Panag-
iotopoulos, and Bowen, 2015). The ability to use and maintain data and infrastruc-
ture assets has a significant impact on delivering sensed aggregated organized data
as smart applications and data visualization. Knowledge and innovation manage-
ment mainly address the question how benefits can be obtained from human in-
volvement, which essentially represent the capacity to generate knowledge, and in-
novate to generate output. Another resource that needs to be managed to align goals
with outcomes is financial assets. Since the IO model explains that one of the ulti-
mate goals of developing the Smart City is sustainability, providing funding for it
should also be sustainable. In this regard, there is a new approach for funding Smart
Cities in the literature known as ‘sustainable finance’ which states that funding
56 Conceptual Model
3
should not only consider financial aspects of return on investment and profit or loss,
but also non-financial aspects, such as responsibility for the future of the city, envi-
ronmental protection, issues of climate change, and social obligations (Janssen,
Charalabidis, and Zuiderwijk, 2012). Sustainable finance concerns long-term term
value creation which considers employees, customers, suppliers, the environment,
and society as a whole (Hauptmann, 2017).
Governance and leadership throughput refer to the question how the process
of transforming a city into a Smart City, consisting of different domains, can be gov-
erned: i.e., intergovernmental relations, coordination among actors, and leadership
capabilities (Hoppe, van der Vegt, and Stegmaier, 2016; Bressers, Bressers, Kuks, and
Larrue, 2016) (See Table 2).
Table 2- Smart City development process throughput
Throughput domains
Dynamic throughput
Data and infrastructure asset management
Knowledge and innovation management
Financial asset management
Governance and leadership
Intergovernmental relations
Coordination among actors
Leadership capabilities
Adapted from Gupta et al. (2015) and Bressers et al. (2016).
‘Intergovernmental relations’ refers to the interdependency of different organ-
izational layers involved in governing the process and the way these are handled
(Bress-ers, Bressers, Kuks, and Larrue, 2016). Since there are multiple actors, the in-
terests they bring to the game also vary and the shape these interactions take de-
pends on the political, legal, institutional, and cultural context in which they are em-
bedded (Joss, 2015; Yigitcalar, 2015). ‘Coordination among actors’ elaborates on the
question which actors are involved in the process, which interests and perspectives
they bring to the table, what responsibilities they have for specific tasks (for instance
data ownership), the legal authority granted to them and how key resources are ex-
changed among them (Bevir, 2012). Various leadership capabilities form the body of
decision-making in different ways, in terms of how the process of transformation
should be done and goals should be set. Different leadership styles form different
ways of processing resources and transforming them to outputs. For instance, in
participatory leadership styles leaders often make the final decision in alignment
Input-Output Modelling for Smart City Development 57
3
with other stakeholders, so the process of decision making tends to be slower. None-
theless in visionary leadership styles, leaders rely on their charisma and personality
to make the final decision, in this way decision making can be fast but the level of
acceptance by other stakeholders is based on the level of trust in the leader (Ibid.).
3.3.3. OUTPUT
Output refers to the deliverables of Smart City policies for which goals are formu-
lated and for which reason the input resources are made available. To characterize
these resource-based domains, we again first define them, then indicate how and
where they appear when they are applied in the Smart City, and finally sketch what
their potential is.
3.3.3.1 SMART APPLICATIONS
Giffinger et al. (2007) focus on the Smart City as a smart transportation system.
This is often a key element in smart mobility. However, in the present study I define
it in a broader sense as the innovative mobility capabilities in order to achieve more
flexible urban services and benefits. Mobility in fact increases the level of utilization
of facilities and services, and accessibility to them. Juniper Research on the top Smart
City performance by index (2017) indicates that mobility saves considerable time
and benefits Smart City inhabitants by allowing more time for family and friends,
decreasing the risk of depression, and improving earning potential (Juniper Re-
search, 2017). It includes all aspects of smart traffic systems, such as dynamic traffic
light phasing and smart parking to reduce time spent in traffic, and open data plat-
forms enabling citizens to choose the fastest option. The results also show that mo-
bility winners have their own smart solutions for urban transportation challenges
alongside long-term policies for new paradigms like autonomous vehicles. Some of
them, other than focusing on smart solutions, contain strong policies regarding car
ownership and reducing the number of vehicles on the road. So, there are different
approaches to smart mobility ranging from smart traffic solutions, smart public
transportation, and smart private transportation to smart mobile services like ship-
ping packages by drones.
An important feature of the Smart City which distinguishes it from other types
of techno-driven future cities is having ‘smart citizens’ in place (Cardullo and
Kitchin, 2019). In the present study I define ‘smart citizens’ as interactive and even
proactive citizens who are able to produce, share, and benefit from information
within the city to accelerate smart and sustainable solutions. One of the main strate-
gies to achieve the goal of Smart City development is its strategic use of innovative
ICT-based solutions to connect the citizens and technologies of the city on a common
58 Conceptual Model
3
platform. Borgia (2014) in an analytical survey states that what most authors have in
common is the focus on ICT as an enabler and as an opportunity to empower human
capital; education, aware-ness, and proficiency of citizens in the use of ICT. This
smart empowerment then becomes a primary goal of cities that brand themselves as
‘smart’. Therefore, Smart Cities, in addition to creating smart solutions based on
technology, are required to facilitate the communication between modern technolo-
gies and citizens through training and engaging them in the Smart City development
process through living labs, organizing related events and workshops, and building
spaces for idea sharing among citizens.
As Gil-Garcia, Pardo, and Burke (2010) argue, the use of ICT infrastructure and
the potential of bringing various information streams together is clearly affected by
acts of governance and institutional structures. They support the emergence and
persistence of stable and trusted social networks (players having confidence in each
other and collaborating) and facilitate information-sharing and the building of a
platform for smart governance. We make a distinction between ‘governing a city to
become smart’ (throughput) which includes making policies and regulatory regimes
for Smart City development, and ‘smart government’ (output) where basically the
application of ICT is basically utilized to transform traditional government and in-
crease efficiency, effectiveness, transparency, and accountability of governance
structures and operations through advanced use of information. This also promotes
open data to empower citizens by making information more publicly accessible.
Smart energy systems seek to reduce energy consumption through the applica-
tion of novel technological innovations while promoting energy conservation and
material reuse, and thus support the environmental aspect of sustainability. As a
result of the other achievements of the Smart City (smart mobility), Jeekel (2016) ar-
gues that, in response to the question ‘is smart mobility socially sustainable?’ new
mobility services are considered to have positive effects on sustainability.
High quality of life is one of the ultimate goals of all human advancement and
not exclusive to the Smart City. Access to high-quality healthcare services (including
e-health or remote healthcare monitoring), electronic health records management,
home automation, smart home and smart building services, and easier access—via
the internet— to social services of all kinds are evidence of Smart City commitments
for a high quality of life. Also, the smart use of new technologies by networks of
actors makes cities safer (Meijera and Thaens, 2018).
3.3.3.2 EXTERNALITIES
Multiple authors have argued that Smart City development is intertwined with
two aspects of externality: sustainability and high quality of life (Yigitcanlar, 2015;
Input-Output Modelling for Smart City Development 59
3
Mortensen and Jonsbak Rohde, 2012; Gemma, 2014; Zhao, 2011). For instance, Yig-
itcanlar’s definition of the Smart City focuses on sustainably to become an increas-
ingly better place to live, work, and play which essentially covers both aspects (Yig-
itcalar, 2015). Although the issue of sustainability was initially debated by econo-
mists, later it was later also picked up by scholars from different academic domains
like industrial ecology. The Smart City is believed to go hand in hand with sustain-
ability, as it looks committed to contribute to sustainable growth. However, the ef-
fects of Smart Cities can differ; amongst others they can have social, environmental,
and economic impact. According to McKenzie (2004), ‘social sustainability occurs
when the formal and informal processes and structures support the capacity of cur-
rent and future generations to create healthy, liveable communities’ (McKenzie,
2004). This largely coincides with quality of life. For Giessler (2005) in the social do-
main of sustainability, a more environmentally friendly way of life should be sup-
ported by Smart Cities. When economic sustainability is pursued, development is
seen as a form of qualitative rather than quantitative growth (Basiago, 1999). Here
social, economic, and potentially environmental sustainability coincide with quality
of life.
Finally, from an environmental perspective, the Smart City should be support-
ive of reaching ecological sustainability which promises a thriving physical environ-
ment as expressed in biodiversity or in minimizing the city’s ecological footprint.
Mobilized urban services and the smartness of citizens - the two indicators of safety
and livability - stand primarily for quality of life. Nonetheless, depending on the
context, policies, and attitudes, there are different interpretations of what quality of
life entails, and how it shows overlap with social and economic sustainability.
3.4. ILLUSTRATIVE CASE STUDY: SMART DUBAI; THE HAPPIEST CITY
This section presents the illustration of an iconic example of a well-branded in-
ternational Smart City and shows how different aspects of a Smart City development
process can be understood as input, throughput and output, and outcome in the
application of the IO-model presented previously in this chapter (See Table 3).
Different cities in the world that brand themselves as ‘smart’ differ remarkably
in the things they do. The history of the Smart City in Dubai returns to e-government
which has evolved into a smart government program and, then Smart City develop-
ment. In 2014 Sheikh Mohammad the Ruler of Dubai set up an executive office for
Smart City development that would respond to his innovative ideas: ‘Smart Dubai,
the happiest city’ (interview with Alazzawi, 2018). This is in line with his vision on
happiness and positivity which states that positivity is a way of thinking, and hap-
piness is a lifestyle (Al Maktoum, 2017). Smart Dubai is part of a transformational
60 Illustrative Case Study: Smart Dubai; The Happiest City
3
mind-set steered by the visionary leadership of the Emirates (interview with Ali Ra-
shid, 2018). Nonetheless the happiness policy influences all of the Emirates (Dubai
is part of the UAE) as an overarching policy, but the idea and its fundamental atti-
tude were created for Smart Dubai.
Table 3- Applying the IO model to the Smart Dubai case.
Elements/facets of the IO model
Application in the Smart Dubai case
Resources
(Input)
Modern ICT infrastructure
Dubai Pulse IoT platform
Human and entrepreneurial
infrastructure
Dubai Pulse PPP,
‘Happiness champion’
Free zones
Data
Presence of a shared data platform
Dubai Data Establishment
Financial infrastructures
Governmental funding,
foreign investment
Throughput
Dynamic capabilities
Dubai Smart City Accelerator
Expo 2020
Smart (AI) Lab
Sustainable financing
Governance
Administrative levels: The Ruler of Dubai,
Smart Dubai Office
Leadership
‘Visionary’ leadership by the Ruler of Dubai
Output
Mobility
Dubai-Abu Dhabi hyperloop, EV
Smart government and citi-
zens
‘Happiness champions’
‘Happiness meter’
DubaiNow App
Paper-free government
Smart energy and health
Shams Dubai
E-health program
Outcome
Sustainability
Increasing social, health economic, and environ-
mental performance indicators; but predomi-
nantly focused on improving energy efficiency
levels.
High quality of life
Happiness in terms of increased satisfaction on
public service delivery in a variety of policy ar-
eas
In 2015 Dubai and the International Telecommunication Union (ITU) signed an
agreement on Dubai becoming the first city using key performance indicators (KPIs)
Input-Output Modelling for Smart City Development 61
3
to assess smartness and sustainability of its urban services. To provide IoT infra-
structure, ‘Dubai Pulse’, which is the digital backbone powering the Smart City, was
made responsible for developing an IoT platform.
For data assets, there is a project called ‘Dubai Data Establishment’ (DDE),
which oversees the Dubai Data Law; it prescribes that all data the government gen-
erates belong to DDE which is a government entity that ensures the presence of a
shared data platform (interview with Alazzawi, 2018). The Dubai Pulse official web-
site shows that there are two different categories of Dubai data: (1) open data pub-
lished by the government or the private sector to be used or exchanged with indi-
viduals; and (2) shared data published under certain terms and conditions among
the entities. However, there is no information to clarify what type of data is shared
or made openly available. To manage data, disseminate information efficiently, and
to deliver public services for citizens, ‘DubaiNow’ is supposed to be a single com-
prehensive application established in 2015 to put all the services in one place. It en-
ables users through a single sign to access various kinds of public services. By the
time of writing the present paper, the application was still under development (in-
terview Alazzawi, 2018).
The supporting policy for entrepreneurship is to deploy free zones for attract-
ing businesses where foreign ownership is allowed and zero personal or corporate
income taxes are charged. Smart Dubai also has specific policies in place to support
start-ups, (Smart Dubai Office, 2018).
In terms of providing financial resources, the Dubai Smart City program is a
government program mainly funded by the Dubai government. Yet, private-sector
partners and start-ups have started a wave of sustainable and green fund-raising
activities supported by the Dubai Declaration on Sustainable Finance. On the other
hand, financing a clean-tech business is not always easy as Daniel Zywietz founder
and CEO of ‘Enerwhere’ states (a solar company with its headquarter located in Du-
bai). Crowdfunding is one of the solutions his company offers to counter financing
problems start-ups encounter.
Looking at Smart Dubai’s main governing body, the initiator is the Ruler of Du-
bai. The Dubai Smart City Office is the central implementation body which serves
as an independent initiative, and is responsible for the development and implemen-
tation of smart programs and solutions while cooperating with other governmental
and private-sector entities like the Dubai municipality, Du (a major integrated tele-
communications services provider in UAE), DEWA (Dubai Electricity and Water
Authority) RTA, (Road and Transport Authority), Dubai Pulse, and many other or-
ganizations. DEWA was launched in 2014 and started three smart initiatives to sup-
62 Illustrative Case Study: Smart Dubai; The Happiest City
3
port Dubai’s smart transformation including Shams Dubai (which pertains to a pro-
ject regarding photovoltaic solar panel installation on rooftops), smart meters and
grids, and the Green Charger for the construction of infrastructure and electric ve-
hicles. Dubai Smart City Accelerator is another initiative within the Dubai Smart
City office which also has joined the Dubai Future Accelerators (DFA) program to
support innovations and start-ups in IoT and connectivity, smart applications, and
sustainable living. Expo 2020 is one of the most extensive Dubai’s programs to foster
innovation for a sustainable future by engaging young people and promoting inter-
national cooperation. Branding aspects play a crucial role in generating worldwide
attention to such events in Dubai.
While the countries with the highest ranking in smart mobility—like Singa-
pore—are mainly focused on reducing the number of vehicles and car ownership,
the UAE—considering its cultural context to change consumer behavior—is more
focused on smart solutions like electric vehicles (EVs) and increasing the share of
electrical vehicles on the roads of Dubai. There is a target of reaching an overall 10
percent share of electrical vehicles for government entities, and a 10 percent share
for all vehicles of Dubai by 2030 (interview with Ali Rashid, 2018). In addition, Sy-
pron Solutions, an IoT company, and the first hyperloop company in the Middle
East, is to develop a project that constructs a hyperloop infrastructure from Dubai to
Abu Dhabi using smart mobility technology (ENGIN, 2018).
In terms of smart energy, DEWA is Smart Dubai’s main partner. It launched
Shams Dubai as an initiative responsible for making Dubai greener with the instal-
lation of solar panels. Green building regulation is a supportive strategy promoted
by Dubai’s Supreme Council of Energy to create healthy, eco-friendly, and efficient
buildings using smart applications.
Dubai Health Authority (DHA) is a public department that pursues the use of
smart applications to ensure all hospitals in the Emirate of Dubai eventually adopt
the electronic model which will facilitate the provision of better healthcare services
to the community (DHA official website, 2018). The six month roadmap of Dubai
Smart Health (2018-2019) contains four smart applications: (1) patient services: for
medication, appointments, and lab results, (2) Dammi: for blood donation, (3) Salem:
for medical fitness; and (4) live media and News: for health awareness (interview
with Almazami , 2018).
Another dimension in the applications within the realm of Smart Dubai (as a
form of Dubai smart government) is the ‘Government of the Future’ which operates
24/7 and 365 days a year. It considers any governmental body successful if it actively
engages the citizens and does not passively await them in providing government
services (Dubai Smart Office, 2018). There also is a paperless strategy used by the
Dubai government. Smart Dubai office has been instructed to oversee this policy and
Input-Output Modelling for Smart City Development 63
3
seeks to attain its goals by 2021 and enable this through three pillars: technology,
legislation, and creating a culture to support achieving sustainability goals (Dubai
Smart Office, 2018).
Sustainability has evolved into a key value of the Dubai Smart City Initiative.
There is also a sustainable city district in Dubai, deploying new technologies to
achieve social, economic, and environmental outcomes (SEE NEXUS Institute, 2018).
Awareness is a key means for realizing the energy efficiency policy and sustainabil-
ity goals in Dubai. Karim El-Jisr, the executive director of Dubai Sustainable City,
states, ‘What we offer here is not just sustainability, we create a lifestyle. So, if you appreciate
this lifestyle you will begin to appreciate sustainability’ (interview with El-Jisr and Rog-
man, 2018). In order to achieve high quality of life and having smart citizens, the
dominant concept is still related to happiness. Obviously, Smart Dubai operational-
izes quality of life in happiness indicators.
When it comes to smart citizens, there is a Smart Dubai ‘Happiness champion’
in order to communicate with citizens and stakeholders and to involve them in co-
ordinating, strategizing, and implementing programs and projects in line with the
Happiness system instead of using living labs. ‘Happiness champions’ are consid-
ered part of value creation that seeks to have a shared language and shared under-
standing and make the co-creation of policies possible (interview with Alazzawi,
2018). Alazzawi adds, ‘The main method to evaluate Smart Dubai’s performance is to
measure and monitor using the ‘happiness meter’ which demonstrates (increased) happiness
of Dubai’s citizens in terms of quality of life and satisfaction about the interaction with gov-
ernment bodies’ (i.e., appreciating public service delivery).
3.5. DISCUSSION AND CONCLUSION
This chapter set out with the question how to develop an IO model to support
decision-making for developing a Smart City based on a conceptual interpretation
of its key facets. The bibliometric analysis showed that the ‘Smart City’ has increas-
ingly become a focal point in urban policy and planning practices. Moreover, tech-
nological innovation has widened the scope of the Smart City. Although the litera-
ture is already replete with contributions about various aspects and dimensions of
the Smart City, thus far no attempt was made to synergize aspects and dimensions
of Smart Cities into a comprehensive conceptual model that can be applied as an IO
model to clarify how particular types of inputs and throughputs result in a given
output. Having developed such a model enables academics, analysts, and policy
makers to comprehend how design choices with regard to the Smart City develop-
ment and translate these into a particular Smart City types or profiles. The content
analysis based on the academic literature in the present study helped me to map the
64 Discussion and Conclusion
3
various attributes of the Smart City. The subsequent IO modelling exercise based on
system theory allowed me to position the key facets of the Smart City as found in
the literature survey within the framework of an Input-Throughput-Output model
and demonstrate the variety of design choices available to policy-makers and ana-
lysts when developing a Smart City. Finally, I applied the IO model to an illustrative
case to show how it can be used to analyze Smart City development.
The IO model explains what the essential input and throughput resources for
Smart City initiatives are, where and how they appear in making design choices
during the Smart City development process, and what possible outcomes of the pro-
cess are. Komninoa and Mora (2018) explored structural axes of the Smart City liter-
ature generated by a bibliometric analysis as technology-driven vs. human-driven
approach, top-down vs. bottom-up planning, and collective intelligence vs. data-
driven intelligence dichotomy. The results of applying the IO model to the illustra-
tive case of Smart Dubai shows a specific type of Smart City development process,
which can arguably be characterized as mainly a top-down process supported by
visionary leadership and active branding strategies and actions, a focus on promot-
ing happiness. This is very specifically defined as customer satisfaction about gov-
ernment services and the involvement of a variety of financial and technological ap-
plications to enhance the range of domains affected by Smart Dubai.
A look at the input to Smart Dubai's development process shows that the tech-
nology transfer strategy and the deployment of new technology-based smart solu-
tions are important resources. However, the importance of the startups and the pro-
motion of innovation was not overlooked. Creating an economic environment to at-
tract innovative companies and start-ups is a strategy Dubai has used to boost the
innovative atmosphere and strengthen the development of its human resources.
Among the through-puts, the main arm of potency for the Smart Dubai development
process is its visionary leadership style that determines the overarching policy. This
overarching policy is the ‘happiness’ policy. Although this sounds as a very positive
vision, the challenge is obviously to define and operationalize this elusive concept
making Smart Dubai truly inclusive under the umbrella of this policy, and include
all citizens including the migrant labor force. Smart Dubai, through designing a
‘happiness meter’ aims at operationalizing and measuring the happiness policy, has
narrowed its actual meaning down in particular ways that may seem odd to people
outside the region, but its approach has been embraced in other UAE members and
widely acclaimed in the broader Gulf Region. Data management as a dynamic
throughput is another aspect of Dubai's Smart City focus. Documentation, laws, and
guidelines related to data indicate that this issue is of interest in Smart Dubai. What
Smart Dubai is looking for as the output of this process, is covering different fields
of application ranging from a main focus on energy (which is a major challenge for
Input-Output Modelling for Smart City Development 65
3
countries in the region) to smart government and citizens, mobility, and health. Fol-
lowing the energy efficiency and carbon footprint challenges, the environmental
sustainability issue is highlighted in many Smart Dubai statements. But to what ex-
tent Smart Dubai can live up to that expectation, remains to be seen and should be
assessed in the future.
This raises the question how the Smart Dubai experience compares to those in
other Smart Cities, and what the application of the IO model would look like for
them? It also raises the question what crucially different design choices other cities
around the world make that seek to become Smart Cities? Other questions pertain
to how do other cities perform in terms of outputs and outcomes? And what can
they learn from Dubai and each other to enhance their respective performance? The
following chapter can throw light at these questions, further detail the use of this
model and help policymakers and analysts make well-reasoned design choices by
taking the various components and facets of a Smart City into account when devel-
oping one.
Notes
1
See for more details in the methodology section on occurrences per category in the
article by De Jong et al. (2015, p. 3).
2
However some discussions have addressed potential negatives associated with the
Smart City (Wiig, 2017; Attoh, Wells, and Cullen, 2019; Barns, 2016).
3
In-depth interviews were held (during 15
th
-25
th
May 2018) with 10 Smart City stake-
holders including: the City Experience advisor, the executive manager, the ideologist of Smart
Dubai Office, a professor from Zayed University, the executive director of Sustainable City in
Dubai, the executive director and the program manager of TAQATI, the executive director of
DEWA, The of Dubai Supreme Council of Energy, and the managing director of a magazine
called The Sustainabilist.
67
4
CLASSIFYING PATHWAYS FOR
SMART CITY DEVELOPMENT:
COMPARING DESIGN,
GOVERNANCE AND
IMPLEMENTATION IN
AMSTERDAM, BARCELONA,
DUBAI, AND ABU DHABI
The contents of this chapter have been adapted from the following peer-reviewed article: Noori, N.;
Hoppe, T.; de Jong, M. Classifying Pathways for Smart City Development: Comparing Design, Govern-
ance and Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi. Sustainability 2020, 12, 4030.
68 Introduction
4
4.1. INTRODUCTION
Studies on the concept of the ‘Smart City’ have become an essential aspect of
urban and environmental studies (Caprotti, 2019; Meijer & Thaens, 2018; Noori et
al., 2019; Yigitcanlar, Kamruzzaman, et al., 2019). Whilst some believe that this is
likely to be transient in terms of branding as a result of evolution (Cowley &
Caprotti, 2019), there is no unique definition for the Smart City yet (Caprotti, 2019).
This might be related to ‘smart’ having a strong connotation to (technological, or-
ganizational, and social) innovation (Anthopoulos et al., 2015; Giffinger, Rudolf; Lu,
2015; Meijer & Thaens, 2018).
Looking at cities that profile themselves as smart, one can conclude that not
only do they contribute a variety of meanings to the Smart City but also that they
deploy vastly different approaches to becoming a Smart City. For instance, the com-
parative studies of Amsterdam, Ningbo, and Hamburg by Raven et al. (2019), and
Glasgow, Bristol, Barcelona, and Bilbao by Calzada (2017) demonstrate how these
Smart Cities vary in their institutional arrangements.
The present chapter taps into these findings and seeks to systematically explore
what different approaches are used to establish Smart Cities and reveals commonal-
ities and differences in the patterns of coming into existence and the principles for
design and governance that are used. Looking at the recent dominant approach from
a perspective of social innovation (Calzada & Cobo, 2015; Giffinger, Rudolf; Lu,
2015), I consider this necessary given the complexity of Smart City planning and
development. Meijer et al. (2018) even call Smart City development a socio-techno-
logical system innovation process (Meijer & Thaens, 2018).
To reach the ambition level formulated above, first I developed a systematic,
conceptual Input-Output model (IO model) in pervious chapter to shed light on dif-
ferent facets of Smart City development, classifying them into the inputs, through-
puts, and outputs. The main idea addressed in the present chapter is to test key
propositions from the IO model, in general, and more specifically, to systematically
convey the design choices city planners and policy makers make in developing
Smart Cities. In fact, the IO model does not propose a prescriptive procedure but
rather the ideal type of a Smart City development process as a framework for think-
ing about, making sense of, and finding ways to improve aspects in the implemen-
tation of Smart City policies that are perceived as problematic. Weber’s definition of
an ideal type highlights that an ideal type is a conception derived from observable
reality and constructed in a particular way. It is not exactly similar to the reality and
not conforming to it in detail because of deliberate simplification, and it represents
the simplified reality in its highest perfection because of deliberate exaggeration (En-
cyclopaedia Britannica, 2002).
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 69
4
In this chapter, four Smart City planning and development projects will be sys-
tematically studied and compared, i.e., Amsterdam, Barcelona, Dubai, and Masdar.
Thus far, multiple studies have addressed these cases (also comparative studies),
e.g., (Margarita Angelidou, 2016; Badran, 2019; Baron et al., 2012; Breslow, 2020; Cal-
zada, 2017; Capra, 2016; Caprotti & Cowley, 2019; Confer & Madeira, 2014; Cowley
et al., 2018; Gascó et al., 2016; Griffiths & Sovacool, 2020; Mancebo, 2019; Mora et al.,
2019; Mora L., 2017; Niederer & Priester, 2016; Raven et al., 2019; Tok et al., 2015; van
Winden & van den Buuse, 2017; Virtudes et al., 2017; Yigitcanlar, Han, et al., 2019),
but none of them focuses on design choices made, or reveals and classifies develop-
mental pathways. The Smart City planning and development projects this study
seeks to analyze pertain to two different geographical regions in the world (Europe
and the Middle East), where it is expected that different institutions and different
attitudes exist, each of them influencing the style of policy making and Smart City
planning. Other relevant factors pertain to differences in cultural background and
political system (De Jong et al., 2019).
Consequently, this chapter seeks to compare these Smart City cases on the basis
of the goals, policies, procedures, and resources used in their Smart City develop-
ment process. A comparison across cities seen from this angle has not been made yet
in other studies. Whereas several studies were conducted to compare Smart City
practices (Caprotti & Cowley, 2019; Cowley et al., 2018; Joss et al., 2019; Raven et al.,
2019), the innovation in this contribution is the focus on design choices made, and
revealing and classifying developmental pathways. Therefore, the main research
question in the present study is: When comparing selected Smart City projects, how
can pathways for their implementation be classified?
The chapter is structured as follows. The next section introduces the key design
variables of the IO model classified under inputs, throughputs, and output variables.
Section 3 specifies the research design and methodology. Section 4 presents the four
Smart City cases. Section 5 provides the results of the comparative analysis of the
four cases. Section 6 then discusses the results and presents a classification of Smart
City development pathways. Finally, in Section 7, the conclusions and recommen-
dations are presented.
4.2. RESEARCH BACKGROUND
4.2.1. DESIGN CHOICES FOR THE RESOURCES OF SMART CITY DEVELOPMENT
An overview of different rankings for the Smart Cities around the world (Bay,
2018; Berrone & Ricart, 2018; Eden Strategy Institute, 2018; Juniper Research, 2017)
70 Research Background
4
that considers different criteria provides evidence for the existence of different ap-
proaches to Smart City development. Whereas Smart City development policy can
be considered as a dominant approach in urban policy formulation, the challenging
part of this dominant approach is in design and implementation. This section ex-
pands the IO model to a framework for Smart City design variables. As mentioned
in chapter 3, the IO model was constructed based on systems theory. General System
Theory is aimed at developing a language in which the problems of many disciplines
can be expressed and shared (Checkland & Haynes, 1994). In this sense, system the-
ory can be applied to many different fields and in many ways. Checkland and
Haynes (1994) classified these varieties. Based on their classification IO model uses
systems theory for ‘problem solving in a real-world situation’. This problem-solving
category used as decision-making support is divided into ‘hard’ systems and ‘soft’
systems sub-varieties. Since the goal is to model a human activity system (Smart City
development process), it can be located within the realm of the (largely qualitative)
soft systems approach. One could also claim that David Easton’s famous portrayal
of political systems (1957) was conceptual IO modeling ante datum (Easton, 1957).
There are still other IO models in existence for the analysis of Smart Cities, as,
for instance, the one developed by Yigitcanlar (2018). His model stresses the inter-
connection between ‘assets’ as the inputs or resources of a city, ‘drivers’ as processes
or opportunities for the Smart City formation, and ‘outcomes’ as the results that
transform a city into a Smart City (Yigitcanlar, Kamruzzaman, et al., 2019). The spe-
cial feature of the IO model is that it sheds light on those facets of the Smart City
development process where intervention becomes possible through design varia-
bles.
In optimization theory, design variables are defined as the entities that can
change the shape or properties of the model within a specified set of choices (Terlaky
& Curtis, 2012; Arora, 2004). An overview of relevant indicators for the design vari-
ables as they can be found in academic and grey literature was conducted. In order
to specify the Smart City design choices, first the determinant variables of each of
these key facets need to be identified and defined. For human facet as design choices,
Nam and Pardo (2011) highlight social learning, creativity, and education (which
simply means becoming knowledgeable). Social learning concerns creativity for
smart solutions and education to develop IT skills and knowledge-based human re-
sources (Nam & Pardo, 2011; Appio et al., 2018; Borri et al., 2011).
Another source of knowledge is data flows and information sharing (Negre et
al., 2015; Gil-Garcia et al., 2019). Data assets are becoming increasingly important
because of the emergence of the Internet of Things (IoT) (Appio et al., 2018). The
primary goal of the IoT is to connect to the ‘things’ to aggregate data (Abbate et al.,
2019), then to process data, and finally to analyze the aggregated data and provide
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 71
4
services, applications, and information (for decision-making). The real-time analysis
of city life can be used to model it, to predict and simulate urban processes, and/or
to monitor, regulate and manage cities (Kitchin, 2014) for better delivery of utility
services to citizens (Meijer,& Bolívar, 2016; Fistola & La Rocca, 2013).
For a high-tech driven urban development, financial requirements have a piv-
otal role in determining roadmaps. Collaboration between the public and private
sectors for investment in smart urban development projects is always supported as
a desirable fiscal mechanism (Pattberg & Widerberg, 2018). In practice, this collabo-
ration is complicated due to different interests and attitudes stakeholders have vis-
à-vis return on investment. Whereas private sector actors invest in urban commer-
cial projects with a decent fiscal return, public sector actors focus on social improve-
ments such as happiness, prosperity, and safety (Huston et al., 2015). Public sector
funding can be allocated by different governmental bodies, located in different lev-
els of government, for instance, via municipal outlay, via national investment or su-
pra-national budgets such as European (EU) funding (e.g., via EU framework pro-
grams like Horizon 2020, FP7, or Interreg) (Engelbert et al., 2019).
4.2.2. DESIGN CHOICES FOR THE THROUGHPUTS
Under the throughput category, three levels are discerned: leadership, govern-
ance, and management.
Government roles in Smart City governance pertain to ‘initiator’ (Alkandari et
al., 2019), ‘facilitator’ (Winters, 2011), ‘regulator’, or ‘funder’ (Gil-Garcia et al., 2015).
Considering how the government interacts with other actors, there are different
modes of governing Smart Cities, such as technocratic governance, citizen-centric
governance, socio-technical governance, or hierarchical governance (Zygiaris, 2013).
In order to determine governance structures, there is a need to specify the roles of
the government, the decision-making process of formulating Smart City policies, the
actors who are involved, and means for engaging actors (Dameri & Benevolo, 2016;
Meijer & Bolívar, 2016).
Knowledge and innovation management as a dynamic throughput refers to the
ways of adding value to the city by tangible and intangible sources of knowledge
(Polanyi, 1967; Fernandez-Anez et al., 2017). Fostering and managing innovation to-
wards propelling Smart Cities may involve establishing innovation centers and liv-
ing labs, and ‘champions’ available to share promising innovative ideas.
Big data management aims to ensure the quality of data and transform data
into knowledge (Watts et al., 2009) and to prevent the misuse of data. Issues like data
theft, data ownership, data accessibility, and privacy issues call for proper manage-
ment (Dijkers, 2019; Chierici et al., 2019).
72 Research Background
4
Meijer and Bolivar (2016) argue that a Smart City requires a focus on both eco-
nomic gains and other public values. Financial management as a dynamic through-
put is about increasing public and private fiscal viability to provide funding for
Smart City projects (Huston et al., 2015). In terms of public funding, as Floater et al.
(2014) argue, existing funding should be redirected away from inadequate and inef-
ficient urban infrastructure development. In terms of private finance, the main issue
is to provide a strong public–private alliance for raising private funds (Huston et al.,
2015). The former needs alignment of all the urban infrastructure development with
Smart City policies, whilst the latter requires a sound understanding of the complex-
ity that goes along with public–private collaboration.
Leadership explicitly addresses the offices that lead the public administration
of a Smart City (e.g., mayor, ruler of the city, Smart City office, city council, CTO
(Chief Technology Officer of the city)). Leadership capabilities strongly depend on
the leadership style of whoever is leading the Smart City program. Switching to an-
other type of leadership may change the shape or properties of the Smart City. The
ways leadership creates a vision, motivates and empowers people, collaborates with
stakeholders and influences them are the indicators that determine leadership style
(Samosudova, 2017).
4.2.3. DESIGN CHOICES FOR THE APPLICATIONS OF SMART CITY DEVELOPMENT
The IO model presents the application domains for mobility, energy, health,
governance, and citizens. Orlowskia and Romanowska (2019) developed an indica-
tor to measure smart mobility. It contains four dimensions: (i) technical infrastruc-
ture, (ii) information infrastructure, (iii) mobility methods and vehicles used for this
purpose, and (iv) legislation (Orlowski & Romanowska, 2019).
Walnuma et al. (2019) define ‘smart energy’ as the goal of achieving energy sys-
tems that are highly energy-efficient, increasingly powered by renewable and local
energy sources enabled by new technologies, and less dependent on fossil fuels
(Walnum et al., 2019). This vision of smart energy has spurred the development of
new approaches to future sustainable energy systems such as smart grids, green
buildings, smart meters, and solar photovoltaic panels (Lund et al., 2017; Koutitas,
2018).
Another domain to become smart in cities is healthcare. Here, ‘smart healthcare’
pertains to affordable and quality patient-centred health services enabled by
healthcare technologies (e.g., ICT supported, smart sensors, devices, and systems)
along with big data analytics (Hossain et al., 2017).
Taking advantage of these smart applications and solutions requires citizens to
share data (Bayar, 2017). From a participation perspective, it is one-way communi-
cation between citizens and the Smart City. In need of innovation, Smart Cities strive
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 73
4
to reach higher levels of citizen participation for sharing ideas (Appio et al., 2019).
Doody (2013) states that smart citizens need smart governance (Doody, 2013). Smart
governance then refers to the use data and ICT to produce effective, responsive, and
transparent modes of governance (Goldsmith & Crawford, 2014). Wilke (2007, p.
165) argues that smart governance needs the ‘redesigning’ of formal democratic gov-
ernance structures. Main areas of smart governance pertain to smart administration,
smart interaction with stakeholders, smart security and safety, and smart infrastruc-
tures (Scholl & Scholl, 2014).
4.3. RESEARCH DESIGN AND METHODOLOGY
In this research, I used a cross-case research design to which I applied the ana-
lytical framework (IO model) presented in the previous chapter. The cross-case com-
parison of the specific cases was made in four steps. First, applying systems theory
(and more specifically, the soft system variety) in order to tackle the research prob-
lem (implementation of Smart City development policy), I used the Input-through-
put-Output model to map the facets and relevant purposeful activities that I named
Smart City design variables. Then we applied the design variables framework (Table
1) to the different cases as a tool to describe their design choices in the real world.
The third step was to scale their design choices in order to verify their common and
unique choices. The next step was to analyze the design choice. For this purpose, I
adopted the qualitative techniques of pattern matching and explanation building to
generate descriptive analyses of the cases (Yigitcanlar, Kamruzzaman, et al., 2019).
In this regard, pattern matching refers to scanning for similarities, dissimilarities,
and patterns pertaining to design variables that influence Smart City development
pathways. This helped me realize the main goal, which is to classify different Smart
City pathways and generate insight regarding promising policy actions and inter-
ventions.
Table 1 provides an overview of Smart City design variables based on the IO
model presented in chapter 3 with available indicators for each of the facets men-
tioned.
74 Research Design and Methodology
4
Table1- The design variables and indicators of the Smart City development pro-
cess.
Smart City Attributes
Design Variables
Indicators (Presence of)
Inputs
HR and Entrepreneur-
ship
Educating and training
people
Supporting and strengthening uni-
versities and research centres (HR1)
Transferring (attracting)
educated and skilled
people
Launching knowledge transfer pro-
jects (e.g., scholarships, sabbaticals)
(HR2)
Nurturing the innovation
environment
Specific policy in place to promote
innovation (HR3)
Attracting innovative
companies
Supporting and encouraging pro-
grams for innovative companies (Sci-
ence and technology parks, free
zones) (HR4)
Information and Com-
munication Technology
(ICT) and Data
Data aggregation
Big data establishment (D1)
Data processing
Data science centres (D2)
Data real-time analysis
Data visualization (D3)
Financial resources
Supra
-national and na-
tional
investment
Supra-national and national Smart
City
development policy and budget
(F1)
Local government invest-
ment
Smart City profile and allocated
budget (F2)
Public–private invest-
ment
Collaboration with the private sector
(F3)
Foreign investment
International brand and investors
Throughputs
Governance
Governance structures;
technocratic, citizen
-cen-
tric, socio
-technical, hier-
archical, surveillance
Role of the government and deci-
sion-making process (G1)
Actors are involved and engaged
(G2)
Knowledge and Innova-
tion management
Open innovation
Living Labs, idea-sharing champions
(KI1)
In
-house R&D
Innovation Centres, Smart City R&D
department (KI2)
Data management
Establishing a data au-
thorization
Data Laws (DM1)
Open/closed/ or shared
data platform
Data accessibility (DM2)
Financial management
Redirecting funds away
from inadequate, ineffi-
cient urban infrastruc-
ture development
Alignment of the urban master plan
with
Smart City policies (FM1)
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 75
4
Raising
private funds
Having a collaboration platform
(FM2)
Leadership
Leadership styles
Vision creation and the bigger image
(L1)
Motivating and empowering people
(L2)
Collaborating with people and influ-
encing them (L3)
Outputs
Smart Mobility
Smart transportation in-
frastructures
Smart (sensor and actuator
equipped) roads and traffic lights,
smart parking, bicycle routes (SM1)
Smart public transporta-
tion
Interconnected public transporta-
tion, smart vehicles, information ap-
plication (SM2)
Smart private transporta-
tion
EVs (Electric Vehicles), autonomous
driving, car-sharing (SM3)
Smart energy
Renewable energy
Stationary energy use to be supplied
from renewable energy sources (SE1)
Energy-efficient build-
ings
Building regulations, energy certifi-
cates (SE2)
New technology for utili-
ties
Smart grids, smart meters (SE3)
Smart health
Smart health monitoring
systems
Remote health monitoring, mobile
health monitoring, or wearable
health monitoring (SH1)
Smart health manage-
ment and information
applications
Mobile applications for medication
information, weight management,
information regarding hospitals and
clinics (SH2)
Smart citizens
One
-
way communication
A participation platform for data
sharing (SC1)
Two-way communica-
tion
A participation platform for idea
sharing (SC2)
Co-creating and co-de-
signing
A participation platform for coopera-
tive policies (SC3)
Smart governance
Smart administration
Redesigning norms based on smart
solutions (technologies) (SG1)
Smart interaction
Participation and collaboration via
social media and social networking
(SG2)
Smart security and safety
Using smart devices and data analyt-
ics for surveillance (SG3)
76 Research Design and Methodology
4
4.3.1. CASE SELECTION
The present study used a small-N comparative analysis research approach.
Small-N case comparisons, also known as ‘case-oriented comparative methods’
(Ragin, 1987, pp. 34–52), are systematic comparative illustrations for insight-gener-
ating and in-depth studies of cases as a whole (Lor, 2019).
Four cases were compared: Amsterdam Smart City, Barcelona Smart City,
Smart Dubai, and Masdar City. All four were well-known, did well on international
rankings (e.g., the Global Smart City ranking issued by Juniper Research in 2016; the
Smart City Index issued by Ernst and Young, in 2017; the global Smart City Dis-
course Network issued by Joss et al. in 2017). These four may not necessarily have
been known as the four ‘best practices’ globally, but they were known for having
very different governance styles and Smart City discourses and showing various
types of Smart City applications in place, and were therefore intriguing to compare.
Joss et al. (2019) presented a list of 27 cities based on a systematic webometric inves-
tigation of the Smart City global discourse network (Joss et al., 2019). Their study
showed that Barcelona and Amsterdam are seen as pioneers (third and fourth place
after London and Singapore). These two cities are located in Europe, having demo-
cratically governed cities. In contrast, Dubai and Masdar City are located in the Mid-
dle East and are governed by sheikhs. Masdar City in Abu Dhabi and Dubai are
well-branded Smart Cities in the world (Yigitcanlar, 2019; Abdulla, 2019).
4.3.2. DATA COLLECTION
Data were collected between 2017 and 2019 by means of site visits and field-
work in all four cases, participatory observation in Smart City workshops and meet-
ings, including the Barcelona Smart City World Congress 2018 and 2019 editions,
and the Amsterdam Smart City Open House meetings in 2017 and 2019. Data collec-
tion also involved in-depth interviews with 32 stakeholders who were involved in
Smart City project development
1
. Finally, much information was collected from of-
ficial documents and websites.
4.3.3. DATA ANALYSIS AND OPERATIONALIZATION
Smart policies
Using big data analytics for decision-
making (SG4)
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 77
4
The cases were compared by descriptions of the current situations and their
design choices, using the operationalized indicators (See Table 2). In order to derive
a classification of Smart City development pathways, I used a multi-method ap-
proach to identify patterns in the data that would provide more insight into the
pathways, enable us to discern between them, and develop a classification. First, I
analysed the case narratives for the four different cases and reflected on key events
occurring that spurred smart policy development and implementation. Because this
was a complex task with rich data available for each case, I decided to treat these
mostly qualitative data in a way to make them apt for structured analysis. Toward
that end, (qualitative) scores were assigned for each case using a four-point scale
ranging from ‘0′ for absence, ‘+’ for having a plan without implementation, and ‘++’
for a plan that has begun, to ‘+++’ for implementation completed because ordinal
scales were used. For the throughput indicators, which used a nominal scale, I tried
to label the design choices and then compare them. In addition, the cases were com-
pared through the interpretation of the commonalities, differences, and the patterns
these revealed.
Table 2-The input and output indicators.
Indicators Absence (0)
Plan without Im-
plementation (+)
Plan has Begun (++)
Implementation
Completed (+++)
HR1
HR2
HR3
.
.
Etc.
This led me to measure the data and to create a data matrix that included these
data for each city measured against all indicators as presented in Table 1. I used this
table to analyse development more structurally, using two approaches. First, I con-
ducted an explorative statistical analysis focusing on bivariate correlations, focusing
foremost on assumed relations between input and output indicators (See Appendix,
Table A1). This would inform me about potential covariation but would offer too
little evidence to confirm any causal relationship. This led me to seek confirmation
using the rich qualitative data of the four cases, break them down into items pertain-
ing to input, throughput, and output of the cases, fill them out with qualitative in-
formation, and interpret and attach meaning to how the development pathways
played out for each of the four cases (See Supplementary Material). This also in-
cluded a comparison of commonalities and differences between the four cases.
78 A Brief Description of the Cases
4
Based on triangulation between the three types of data analysis used—i.e., (i) inter-
pretation of the four case narratives, (ii) statistical analysis, and (iii) qualitative com-
parative analysis of the qualitative comparative data matrix—we conceived devel-
opment pathways for Smart City project implementation of the four cases and cre-
ated insights on key commonalities and differences between them. Having more in-
formation available on case study storylines, narratives, and information on input,
throughput, and output, I was able to interpret and further understand the case
studies at a higher level of abstraction, which made it possible to discern key values
used by policy makers that support key decisions and the ways they play out in the
development pathways used in the four cases. Finally, following the next step of
interpretation of the four cases, I discerned fundamental values as drivers and clas-
sification of development pathways to emerge from the data.
4.4. A BRIEF DESCRIPTION OF THE CASES
This section presents the four cases and show how each of them can be under-
stood in terms of the concepts of the IO model. The origin of the Smart City concept
in the four cases is also explored.
4.4.1. MASDAR CITY
In 2006, the Masdar City project was launched in order to develop the world’s
most sustainable eco-city with the vision of making Abu Dhabi a reference for
knowledge and collaboration on the advancement of renewable energy, clean tech-
nologies, and sustainable development (Griffiths & Sovacool, 2020; Yigitcanlar et al.,
2019; Cugurullo, 2013). The mission of the project was not only to address the sus-
tainability challenges of the United Arab Emirates (UAE) but also to develop com-
mercially viable solutions in renewable energy and sustainable real estate. However,
after more than ten years, the number of residents is around 1300 (McArdle, 2018),
whilst it was initially planned to house 40,000 permanent residents with an addi-
tional 50,000 commuting to work and study in Masdar City (Abdulla, 2019). With
the emergence of Smart Cities as a trendy competitive urban policy, it was trans-
formed from an eco-centered project into a Smart City project. The Smart City project
was then based on four pillars: (i) research and academics; (ii) sustainable real estate;
(iii) clean energy deployment; and (iv) clean-tech innovation. Since Masdar City en-
tails the construction of an entirely new city, it can be seen as a living lab for devel-
oping and testing new technologies to evaluate how they can integrate into the uni-
fied platform for developing a Smart City (Solomon, 2017).
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 79
4
4.4.2. AMSTERDAM SMART CITY
Two years later, in Amsterdam, the Amsterdam Smart City program set out
with the primary goal of reducing CO2 emissions (Zygiaris, 2013). The program was
started with the focus on smart energy and smart grids by the City of Amsterdam
and Alliander through a three-year project funded by the EU (Mora, 2017). When
the project was finalized a discussion started on how the program could continue
and stand on its own feet. This was followed by the Amsterdam Economic Board,
which decided to take over the program as the coordinator and to govern and fund
it, using a collaborative platform. The first driver for moving toward implementing
a Smart City policy was based on the results of climate change discussions (Mora,
2017). More recently, the scope of the Smart City was broadened to include areas
that can improve the quality of life of citizens (Baron et al., 2012; Vermast, 2019).
Amsterdam also developed a circular economy and sustainable structural vision
that sketches an image of Amsterdam as a future-proof, innovative, data (evidence)
driven, and collaborative city by 2040.
4.4.3. BARCELONA DIGITAL (SMART) CITY
In 2011, Barcelona also launched a Smart City policy of its own aligned with the
European Union’s strategy to create a more sustainable, smart, and inclusive path
for development. Following that, a national plan for Smart Cities was launched in
Spain called the ‘Digital Agenda for Spain’, which allocated EUR 170 million for ac-
tions related to city objectives, 5G technology, interoperable virtual labs, smart tour-
ism, public services platforms, and rural territory. Currently, Barcelona’s approach
to becoming a Smart City derives from the digital city. Its profile pertains to ‘Barce-
lona Digital City: the right to the (smart) city’. The Mayor of Barcelona Colau (2018)
states, ‘Our goal is to exploit digitization and achieve a city that is more open, fair,
circular and democratic by putting technology at the service of people’ (Colau, 2018).
In this sense, Barcelona’s Smart City foundation is based on digital transformation,
digital innovation, and citizen empowerment.
4.4.4. SMART DUBAI
For Dubai, the Smart City journey developed from the concept of smart gov-
ernment. In 2014, an executive office for the Smart Dubai program was established
to expand the concept to different areas based on the vision of the Ruler of Dubai
[1,49]. The vision was to make Dubai the happiest city on the earth (Al-Azzawi,
2019). This is pursued by using smart technology innovation as one of the main tools
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contributing to creating happiness. Next to spurring technological innovation, a cor-
nerstone of the approach of the Smart Dubai strategy pertains to having all city
stakeholders on board (Smart Dubai Officie, 2018).
4.5. RESULTS
4.5.1. DESIGN INPUT CHOICES
4.5.1.1 M
ASDAR
To provide the human and entrepreneurship resource for the Masdar City de-
velopment, Abu Dhabi’s main funding project in research and education develop-
ment is allocated to the Masdar Institute of Science and Technology (MIST), which
is located within Masdar City. MIST, in collaboration with the Massachusetts Insti-
tute of Technology, aims to foster energy and sustainability innovations. In 2017, it
merged with Khalifa University (interview, 2018). When it comes to innovation pol-
icy, Abu Dhabi follows the national strategy for advanced innovation (2018), which
targets the establishment of an innovation platform and led to initiation of the ‘UAE
Innovation Month’ festival. In order to attract innovative companies, Abu Dhabi es-
tablished a policy for developing several free zones at a large scale per unit around
Masdar and provided companies with high-profile locations inside Masdar City (De
jong et al., 2019; Cugurullo, 2013). In terms of data and ICT infrastructure assets, the
Mubadala Company made substantial investments in building ICT infrastructures.
Mubadala, which is a regional government investment company, is responsible for
funding and provisioning infrastructure by either its institutions or outsourcing. It
also founded Khazna Data Centers (in Masdar City and Meydan Dubai) to deliver a
combined 18+ MegaWatt (MW) of IT load in 2012. Therefore, Masdar City is major-
ity-owned by the Mubadala Investment Company, which belongs to the Abu Dhabi
Government in collaboration with the International Renewable Energy Agency
(IRENA). The Mubadala Company announced that $20 million would be allocated
to the Masdar project, but after spending a few million, the remaining budget was
invested in other projects, mostly international projects.
4.5.1.2 AMSTERDAM
To make the potential human capital available for Amsterdam Smart City, the
Smart City Academy and Amsterdam Institute for Advanced Metropolitan Solu-
tions (AMS) were established as the knowledge-sharing programs for Smart City
development, aiming to support knowledge and build a human infrastructure (in-
terview, 2019). Amsterdam has a specific policy in place to promote innovation in
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 81
4
coordination with national and European policies, such as Innovation Union, Hori-
zon 2020, and the Digital Agenda (Policy framework: European Strategy for Amster-
dam, 2019). To support start-ups and emerging tech companies, Amsterdam Science
Park and the startup village inside it offer an ecosystem for innovation. Moreover,
in 2015, the City of Amsterdam initiated a public–private action program called
‘Startup Amsterdam’. It aims to assist startups and innovative companies so they
can accelerate their growth sustainably (Iamsterdam, 2019). Apart from the benefits
of an established start-up hub, a talented workforce, and the spirit of innovation,
Amsterdam offers skilled workers at start-ups and innovative companies a 30% per-
sonal income tax advantage (Iamsterdam, 2019).
Amsterdam has the second-largest Internet exchange point in the world and is
considered the second top city in the world in terms of technology readiness (PWC,
2014). As such, it benefits from modern technology infrastructures to make the city
smarter. There is a single portal for the data in Amsterdam (‘City Data’) established
by the City of Amsterdam in 2015. City Data uses big data collections and tries to
share as much data as possible, which is open to anyone who wants to use the data.
This includes the collected data from eight policy domains: traffic and infrastructure,
tourism, geography, population, public space and green, urban development, wel-
fare, and energy. At the time of writing this article, the portal was under develop-
ment. In terms of making the financial resources available, Amsterdam Smart City
initially used EU framework project funding (i.e., Horizon2020) (Söderström et al.,
2014). Later on, Amsterdam Smart City (ASC) established a public–private partner-
ship portal to provide a favorable platform for collecting co-funding from the private
sector (interview, 2018).
4.5.1.3 BARCELONA
For human resource development in Barcelona Smart City, the Institute for Ad-
vanced Architecture of Catalonia (IAAC) is one of the main research centers in col-
laboration with the city council of Barcelona. One of its departments, the so-called
‘Fab lab’, is currently developing projects in smart devices for data collection among
citizens in collaboration with the Smart City Expo and World Congress in Barcelona.
Barcelona’s innovation policy is mainly based on the real open innovation approach
(Gascó et al., 2016). It prefers to have open innovation centers for anyone to contrib-
ute rather than doing mere researches inside the universities. That is why the city
council’s cooperation with research centers and universities is generally carried out
through the research labs (interview, 2018). The director of Barcelona’s Smart City
Program stressed that the strength of Barcelona’s Smart City strategy relies on its
cyclic and cross-cutting innovation model (Ferrer, 2017). Apart from fostering inno-
vation in a collective collaborative way, the city council of Barcelona pays special
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4
attention to promoting entrepreneurship (interview, 2018). This process is sup-
ported by Barcelona Activa, which is a local development agency belonging to the
Barcelona City Council encouraging entrepreneurship and offering support to com-
panies and startups (interview, 2018).
The Barcelona City Council established the municipal data office for public data
sovereignty. Currently, it is promoting three projects: CityOS, Open Data Bcn, and
Monitoring Gentrification, to aggregate data from the various sensors distributed
throughout the city and numerous sources. CityOS is an advanced data analysis
platform that offers comprehensive and transversal connectivity to serve citizens
and the city. The platform is based on the main idea of using data to enable the fore-
sight and the ability to predict situations in order to make better decisions and reac-
tions. It is an open-code IoT platform that everybody can download and develop or
modify.
In both Amsterdam and Barcelona Smart City initiatives are linked to projects
that use EU framework funding (i.e., Horizon 2020). Apart from that, Barcelona City
Council is the responsible entity for the majority of funding (interview, 2018). In
terms of foreign investment, according to the Global Cities Investment Monitor 2019,
Barcelona is the seventh most popular global destination attracting international in-
vestments (KPMG, 2013).
4.5.1.4 DUBAI
The most significant supporting programs for universities and research centers
are focused on three districts: Dubai International Academic City (DIAC), Dubai
Knowledge Village, and Dubai Internet City. DIAC lists middle-of-the-road colleges,
schools, and universities from around the world (De Jong et al., 2019) established by
TECOM Group (a governmental entity) as a free zone dedicated to higher education
and the pursuit of intellectual growth. Apart from Dubai’s main higher education
project in DIAC, major training programs to develop human resources target civil
servants (Smart Dubai Officie, 2019).
However, skilled and educated workers have always been welcomed to work
in Dubai, and there is momentum in the Emirates to increase the number of highly
skilled and educated local workforces’ so-called ‘Emiratization’ (Ministry of Cabinet
Affairs and the Future, 2014). According to the Ministry of Education’s Strategic Plan
for 2017–2021, Dubai’s innovation policy was formulated to establish a culture of
innovation in the institutional and working environment. To encourage start-ups
and innovative companies to come, Dubai’s government established a significant
number of high-tech free zones and science parks. In parallel, the Smart Dubai
startup initiative was launched, having three programs in place to support emerging
technologies and entrepreneurs. These are: (i) the Global Blockchain Challenge; (ii)
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 83
4
the Dubai Smart City Accelerator; and (iii) the Dubai Future Accelerators. In terms
of ICT infrastructure assets, The Network Society Index indicates that Dubai is 26th
in performance in sustainable urban development and ICT maturity (interview,
2018).
For data assets as an essential resource for the Smart City, Dubai Data Estab-
lishment is the governing body with authority to push this strategy whilst seeking
to implement the roadmap for Dubai Data (interview, 2018). In order to process and
utilize data, ‘Dubai Pulse’ is the central platform that provides and computes, stores,
and analyses services for the categorical use of various entities (interview, 2018).
Currently, Smart Dubai office serves the analytical data as a single mobile applica-
tion, ‘Dubai Now’, which helps citizens to manage bills, track their visas, renew the
trade licenses, register cars, plan journeys by public transportations, and monitor
health (interview, 2018).
In both Dubai and Abu Dhabi, the Smart City program is considered to be part
of the National Happiness policy (interview, 2019). Therefore, the Smart Dubai ini-
tiative is established and funded by the ruler of Dubai. However, enjoying a positive
global image, Dubai has ample ability to attract foreign investment. An overview of
how the four Smart Cities perform against Smart City resources is presented in Table
3, which is constructed based on the scaling method defined in the data operation-
alization section (Table 2).
Table 3-Smart City development in Amsterdam, Barcelona, Dubai, and Masdar.
Design Choices/Cases
Amsterdam
Barcelona
Dubai
Masdar
Educating and training people
+++
+++
++
+
Transferring (attracting) educated and
skilled people
+++ +++ ++ +
Nurturing the innovation environment
+++
+++
+
+
Attracting innovative companies
+++
+++
+++
++
Data aggregation
++
++
+++
+++
Data processing
++
++
++
++
Data real-time analysis
+
++
++
++
Supra-national and national investment
+++
+++
++
++
Local government investment
++
++
+++
+++
Public–private investment
+++
++
++
++
Foreign investment
++
+++
+++
+
4.5.2. DESIGN THROUGHPUT CHOICES
4.5.2.1 M
ASDAR
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The governance structure of Masdar is mainly based on a holistic approach to
developing renewable energy and sustainability by creating a value chain from re-
search to investment. Dubai and Masdar City share common governance features,
such as the monarchical rule and central authority, that make their decision-making
process fast and flexible; the idea is initiated by the rulers, policies are formulated
and then adopted by citizens with high levels of trust. However, Abu Dhabi, having
abundant financial wealth because of its oil and gas resources, is much stronger than
Dubai. With a global approach, Masdar City launched the ‘sustainability week’ as a
platform for accelerating the world’s sustainable development. It brings together
policy makers, industry specialists, technology pioneers, and the young generation
of citizens for sharing knowledge, implementing strategies, and delivering solutions
for the world’s sustainable development (Masdar City, 2018). In terms of the Smart
City in-house R&D, Masdar recently established the Honeywell Masdar Innovation
Center of cutting-edge solutions for smart applications.
4.5.2.2 AMSTERDAM
Situated in a totally different political and government system from the Emir-
ates, in the case of Amsterdam the ASC platform is an innovative platform for con-
necting ideas and challenges between municipalities, partners, and companies to ac-
celerate doing/learning in order to strengthen smart solutions, market development,
business models and replication (Baron et al., 2012; Dameri, 2014). In 2011, the mu-
nicipality of Amsterdam governed ASC with more than 70 public and private part-
ners (Mora, 2017). Within the ASC platform, the city administration has different
roles apart from being the initiator, to a facilitator and from financer to customer
(van Windenet al., 2016). At present, the dominant approach to managing innova-
tion within the Smart City is to develop and test smart urban solutions in a real-life
context (urban living labs) (Zygiaris, 2013). For ASC, the living labs are mapped in
the middle of the stakeholder’s collaboration (Figure 1).
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 85
4
Figure1- Overview of the stakeholders involved in the Amsterdam Smart City
(ASC) living lab (Steen & Van Bueren, 2017).
The Amsterdam Institute for Advanced Metropolitan Solutions (AMS) is re-
sponsible for ASC living labs working on six different themes: i.e., circularity, food,
resilience, energy, mobility, and data. In addition, ASC uses open-house programs
and open meet-ups for communicating and empowering citizens (interview, 2019).
Within the Smart City context, knowledge and innovation management is closely
connected to data management driving innovative solutions. For data-related deci-
sion-making, the IO model focuses on two crucial aspects: data laws and data acces-
sibility (interview, 2019). Amsterdam and Barcelona are part of the European Un-
ion’s DECODE project aiming to return data sovereignty to the citizens. Currently,
four DECODE pilots are running in Amsterdam and Barcelona to test the technology
and approach. Amsterdam City Data is openly accessible through the Internet, and
data that are public can be freely used by anyone. However, some of the data are
available for authorized city employees only (interview, 2019).
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4.5.2.3 BARCELONA
To govern Barcelona Smart City, following the formulated smart policy in 2011,
Barcelona City Council launched the project ‘Barcelona Smart City Strategy, Plan-
ning and Implementation’ in collaboration with DOXA. DOXA is a consulting com-
pany that assisted and coordinated Barcelona’s Smart City strategy by supporting
planning, execution, and monitoring actions. In 2015, the project outcomes pertained
to the smart strategy development and implementation, the definition of a govern-
ance model (See Figure 3), storytelling and communication framework (Ferrer,
2017). The main governmental entities of Barcelona Smart City are the City Council,
the Barcelona Provincial Council, and Area Metropolitana de Barcelona (AMB) (in-
terview, 2018).
Figure 2-The Barcelona Smart City governance model (Ferrer, 2017).
One of the key points of Barcelona Smart City programs at the early stage was
the development of a community of citizens and developers, and installations for
Small to Medium Enterprises’ (SMEs) experimentation with the Living Labs. Barce-
lona’s 22@ innovation district was initiated by the City Council in need of an urban
renovation strategy for the transformation of the industrial area to the knowledge
economy area (Zygiaris, 2013). It brings universities, research centers, start-ups, and
emerging tech companies together to create synergies and foster innovation (inter-
view, 2018). The whole district operates as an urban lab that offers opportunities for
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 87
4
technology companies to move to the district, run pilot programs, and test new tech-
nologies (Ajuntament de Barcelona, 2012). There is a European Union (EU) General
Data Protection Regulation (GDPR) for European city authorities in digital ethics
and rights concerning citizens’ empowerment (Calzada, 2018). Barcelona’s Digital
Plan 2017–2020 is the main agenda for data policies and strategies aligned with
GDPR (Calzada, 2018). According to Calzada (2018), the three strategic initiatives
regarding data protection and regulation are: ‘Data Commons Barcelona’, ‘City Data
Analytics Office’, and ‘Decode’ (the EU’s scientific) project (Calzada, 2018). Data
Commons Barcelona offers an open-source policy toolkit regarding ethical digital
standards ‘for cities to develop digital policies that put citizens at the center and
make governments more open, transparent, and collaborative’ (Ajuntament de Bar-
celona). The city council of Barcelona also presented ‘Decidim Barcelona’, a partici-
patory democracy (digital) platform for communicating and empowering citizens.
Barcelona Municipal data office is currently working on the Open Data Bcn project
to develop a platform for sharing the information generated or stored by public bod-
ies with individuals and organizations (interview, 2018).
4.5.2.4 DUBAI
The Smart Dubai governance structure is based mainly on visionary leadership
and a positive approach to developing happiness. Setting up a ‘champion’ in line
with the overarching policy of developing the Smart City is Dubai’s unique pathway
to engage citizens for coordinating, strategizing, and implementing programs and
projects (interview, 2019). Smart Dubai points to the happiness champion as an es-
sential component of Dubai’s Smart City transformation where all the partners can
work in close collaboration with the Smart Dubai Office (Smart Dubai, 2019). Dubai
is also developing its first Artificial Intelligence (AI) Lab in partnership with IBM to
support Dubai’s AI roadmap (interview, 2018). The AI Lab’s first strategy is to trans-
form citizen engagement by infusing AI into services and operations, and disrupting
business processes (Lootah & Miailhe, 2017). In terms of the Smart City in-house
R&D, Dubai already has several innovation centers. Dubai has a set of comprehen-
sive documents on data authorization, including Dubai data law, Dubai data policy,
Dubai data manual, and the Dubai data model, which are all accessible online (in-
terview, 2018).
Last but not least, as a dynamic throughput, leadership style plays an important
role in the Emirati cases, where the initiators of the Smart City programs are the
rulers of Dubai and Abu Dhabi (interview, 2018). In European cases, the initiators
are institutions affiliated with either municipality or city council. So, the way of mo-
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tivating and empowering citizens in Dubai and Masdar is based on getting inspira-
tion from the vision of leader, whilst in Amsterdam and Barcelona Smart Cities are
based mainly on two-way communication.
4.5.3. APPLICATIONS AND EXTERNALITIES
All efforts to mobilize and manage resources are to provide solutions and then
transform them into smart applications. A common classification many studies
agree on pertains to five clusters, i.e., those of mobility, energy, health, governance,
and citizen contributions to the different aspects of sustainability (externalities) (An-
thopoulos et al., 2015; Neirotti et al., 2014; Chourabi et al., 2012).
4.5.3.1 MASDAR
Smart transportation policies in Masdar City are based on the elimination of car
use. They deploy cutting-edge technology solutions like the personal rapid transport
(PRT) system. This pertains to a driverless automated transport system that can
carry four passengers. Although it is mentioned on the official website of Masdar
City that the system was implemented, in practice, it only turns around the building
for a few minutes and it is clearly not as well-developed or functional as marketed
through its branding media.
Deploying clean energy worldwide is Masdar City’s core objective to make Abu
Dhabi a hub for sustainability and renewable energy. Green building prototypes
(Masdar Eco-villa), Solar PV Plant, and the Wind Tower are launched projects in
Masdar City (interview, 2018).
In early 2017, Masdar City and Huawei signed an agreement to use Huawei’s
IoT platform to develop applications for increased health, productivity, and sustain-
ability. The ultimate goal is to empower Masdar City residents in making better
health decisions. Citizen participation seems not to be at the core of the Masdar City
concept; in Masdar official documents and on the website (Masdar corporate bro-
chure), the words ‘citizens’, ‘residents’, and ‘people’ are mentioned only once to ad-
dress Abu Dhabi Sustainability Week. The Abu Dhabi Sustainability Week is a
knowledge platform for the global sustainability community and the largest sustain-
ability gathering in the Middle East to discuss viable and effective strategies to mit-
igate climate change.
Since automation through the cutting-edge technologies is the main facet of
Masdar City, there is a unified service desk called ‘one-stop shop’ where people and
companies can access a wide variety of government and business services, including
registration and licensing, visa and medical checks, ID card processing, document
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 89
4
authentication, and so on. It refers to the key facet of Masdar’s social attitude as ‘cus-
tomer satisfaction’ (Cugurullo, 2013).
4.5.3.2 AMSTERDAM
Amsterdam has been at the forefront of smart mobility for many years (Ver-
mast, 2019). What makes ASC different is that smart solutions and strategies are not
only based on modern technologies but also help to develop simple solutions that
are supported by cultural capacities. Amsterdam as ’the world capital of cycling‘
developed smart mobility solutions through smart bicycling, along with the electric
car (Wagner et al., 2014) and car sharing in terms of private transportation (Sengers,
2016). ASC also provides a network platform for public transport, which is easily
accessible to visitors and residents via smartphone applications (interview, 2018).
One of the crucial partners of ASC is the Chief Technology Officer (CTO), who
has many initiatives on innovative mobility (interview, 2019). ASC also uses the
smart traffic management system to optimize the traffic flow and works on a project
(Amsterdam Practical Trail), creating a future where cars, navigation systems, traffic
lights, and information signs are connected and working on an automated basis. The
urban energy transition was the starting point and primary goal of the ASC program
(Baron et al., 2012). City-Zen is an international consortium project on urban energy
transition in Grenoble and Amsterdam to integrate new energy solutions in existing
buildings and systems. A Virtual Power Plant (for storage and trade of surplus wind
or solar-PV energy), Smart grid, The District Heating and Comfort Cooling network,
Smart cooling, and Retrofitting homes are part of City-Zen project. ‘Healthcare has
less attention in our smart program so far, we just started to have strategic partners
to develop the smart healthcare theme,’ states Ger Baron, the chief technology officer
of Amsterdam (interview, 2019).
The main product that the ASC team developed is an online platform for people
to share their projects and initiatives and look for collaboration (interview, 2018).
Collaboration with citizens is a clear goal of Amsterdam Smart City to keep the city
livable, but currently it is more focused on collaboration with businesses and entre-
preneurs (Capra, 2016). Amsterdam Smart Citizens Lab is a bottom-up way to ex-
plore smart solutions from citizen-driven innovations as well as to help citizens to
become aware of smart lifestyles and ecosystems whilst it has early adopter citizens
receptive to new technologies and sustainable solutions (van Winden et al., 2016).
Considering the smart governance domain, administrative affairs in Amsterdam,
like registration, payment lay-out, and taxes, are mostly paper-based. Amsterdam,
however, is one of the first cities that has a Chief Technology Officer (CTO) in its
governance body contributing to e-health, circular economy, and mobility themes of
ASC.
90 Results
4
4.5.3.3 BARCELONA
Barcelona’s smart mobility policy began with raising public awareness through
a research and innovation project (‘Mobility Urban Value’) aiming to encourage be-
havioral change in mobility by using new technologies. Connected mobility, safe
and smart mobility for pedestrians and cyclists, clean, affordable, and efficient pub-
lic transport, and integrating electric vehicles (EVs) into the transport system are the
main aspects of Barcelona smart mobility that calls itself ‘the right to smart mobil-
ity’(interview, 2018).
Barcelona Energia’s (the public electricity distributor) energy transition model
incorporates smart energy with the mission of producing a 100% certified renewable
energy supply plan that began in July 2016 and is supported by the City Council
with a budget of EUR 130 million (Barcelona Self-sufficient Energy Plan 2014–2024).
For this purpose, Barcelona adopted encouraging plans like subsidies for the instal-
lation of photovoltaic panels and thermal solar panels, energy renovation, and en-
ergy improvements. Barcelona Energia (2018) also reported that 87 solar energy in-
stallations are already distributed around the city and the Program for Promoting
Solar-Energy Generation has been established, which includes 73 projects for in-
stalling more solar energy panels on rooftops, party walls, facades, and pergolas
(Ajuntament de Barcelona, 2018).
In the same way as ASC, Barcelona seeks two-way communication and co-cre-
ation of solutions and policies with citizens. For that purpose, there are several so-
called democratic Barcelona projects. One of them is ‘Decidim Barcelona’, which
aims to provide a portal for participation processes (interview, 2019). The ‘Smart
City Week’ program is also an initiative to bring citizens closer to the notion of Bar-
celona Smart City, which is ‘a city that uses its accumulated knowledge and technol-
ogies to achieve a more sustainable, fair, and inclusive urban setting’ (Ajuntament
de Barcelona, 2019).
As a collaborative governance platform, the ‘City Protocol’ project is another
common project between Amsterdam and Barcelona that offers an ‘Internet of Cities’
platform to communicate, share solutions across diverse cities, and learn from each
other (interview, 2018).
4.5.3.4 DUBAI
In Dubai, due to the Emirati preference for luxury and private transportation,
smart mobility projects are mostly related to smart lights, smart parking, traffic con-
trol management, and increasing the share of electric vehicles (a smart initiative by
Dubai Electricity and Water Authority) on the roads (Virtudes et al., 2017). Since the
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 91
4
UAE is always interested in using the title of ‘the first’, the Abu Dhabi–Dubai hyper-
loop is the world’s first commercial hyperloop set to open in 2020 for the Expo 2020
(De Jong et al., 2019).
Shams Dubai is the main smart energy initiative by Dubai Electricity and Water
Authority (DEWA), which is the key partner of Smart Dubai in this field. Shams is
focused on expanding the solar panel installations on buildings to generate electric-
ity and connect them to DEWA’s grid (interview, 2018). The program was started on
governmental buildings and aims to expand among household and private building
owners (Dubai Electricity and Water Authority, 2016). The Green Building Regula-
tions establishment is another major plan for energy efficiency launched by Dubai
Supreme Council of Energy and DEWA for all new buildings to ensure the efficient
use of electricity, water, and renewable energy (Virtudes et al., 2017).
In contrast to Amsterdam, Dubai pays a lot of attention to the health domain of
its smart program. Dubai Health Authority’s (DHA) smart applications are available
to use for different purposes such as Patient Services (for medications, appoint-
ments, and lab results), Dammi (for blood donation), Salem (for medical fitness and
occupational health screening), and Sheryan (for health licensing)(interview, 2018).
Smart Dubai tries to interact with citizens through different mobile applica-
tions. If the energy domain is the primary goal of Smart City development in Am-
sterdam, for Dubai it began in the governance domain (Badran, 2019). Paperless gov-
ernment policy is the goal for Dubai’s smart administration (interview, 2018).
Table 4 presents an overview of how the four Smart City cases perform against
Smart City output indicators.
Table 4- Applications of Smart City development in Amsterdam, Barcelona, Dubai
and Masdar.
Design Choices/Cases
Amsterdam
Barcelona
Dubai
Masdar
Smart transportation infrastructures
+++
+++
++
+
Smart public transportation
+++
+++
+
+
Smart private transportation
+++
++
++
+
Renewable energy
++
++
+
+
Building energy efficiency
++
++
+++
++
New technologies for utilities
+
++
+
++
Smart health monitoring systems
+
+
++
0
Smart health management and infor-
mation applications
+ + ++ +
One-way communication
++
++
++
+
Two-way communication
+++
++
+
+
Co-creating and co-designing
++
++
+
0
Smart administration
0
++
++
++
92 Towards a Classification of Smart City Development Pathways
4
Design Choices/Cases
Amsterdam
Barcelona
Dubai
Masdar
Smart interaction
++
+++
+++
+++
Smart security and safety
n/a
n/a
n/a
n/a
Smart policies
++
++
++
+
Even though one obvious case of using big data collected from the environment
is for surveillance objectives, in principle, governments do not publish information
on this issue.
4.6. TOWARDS A CLASSIFICATION OF SMART CITY DEVELOPMENT
PATHWAYS
In Sections 4 and 5 the results from the data collection and observations re-
vealed the design choices for inputs, throughputs, and outputs. This led to several
important analyses associated with Smart City development paths. The observed
data for input and output indicators are shown in Tables 4 and 5. Subsequently, the
qualitative and quantitative analyses of the observed data of the cases, through us-
ing pattern matching and explanation building techniques, led me to formulate their
fundamental values as drivers for Smart City development. The results are pre-
sented in Table 5.
Table 5-Smart City development pathways (Amsterdam, Barcelona, Dubai, and
Masdar).
Case
Main Driver
(Core Element)
Development
Path
Key Features
Amsterdam Innovation
Innocratic
(Startup and
business-driven)
Competition, entrepreneurial In-
novative, Bottom-up approach
Barcelona Inclusion
Sociocratic (Par-
ticipation-
driven)
Democracy, Citizen empower-
ment through technology and
citizens’ data sovereignty Partic-
ipatory, Co-creation
Dubai
Visionary-ambi-
tious leadership
Aristocratic
(State and ser-
vice-driven)
Being first, being best, Top-
down Happiness, government
services, branding
Masdar
Technological op-
timism
Technocratic
(Investment and
branding-
driven)
Visibility, lighthouse projects,
branding
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 93
4
Significant results of the statistical analysis were found between ‘nurturing of
the innovation environment’ and certain application domains such as smart trans-
portation infrastructure, renewable energies, or smart mobility. Nurturing the inno-
vation environment was also found to relate positively to investment from higher
tiers of government (like Barcelona and Amsterdam getting EU-funded projects). In
addition, nurturing the environment positively related to ways of bottom-up partic-
ipatory innovation and decision-making, i.e., ‘two-way communication’, ‘co-crea-
tion’, and ‘co-designing’. This, in turn, also showed a positive statistical relationship
to indicators of the smart citizen domain. Other significant correlations were found
between ‘two-way communication’ (of citizens and government) and ‘educating and
training of staff’. The ‘data aggregation’ and ‘data processing’ design variables
turned out to be related in particular to the application domain of smart health, but
also connected with ‘smart private transportation’ and ‘building energy efficiency’.
The analysis showed that there were remarkable interactions between ‘smart poli-
cies’, ‘data processing’, and ‘one-way communication’ (which points to sharing data
from citizens).
These results in combination with the qualitative data analysis table (See Ap-
pendix, Table A2), enabled me to identify the pathways (See Table 5). The main driv-
ers and the key values that were revealed from the process analysis (of Smart City
development) informed us about the pathways Smart City development has taken
in the four cases of the present study.
Looking at the origins of the Smart City program in each case showed that en-
vironmental issues, and eventually, the idea of making a city ‘sustainable and future
proof’, formed the main motivations to start undertaking actions that would result
in Smart City development plans, policies, and actions. However, the environmental
issue alone did not suffice, as it was local leadership taking ownership of the latter
to issue a vision and take the first steps in Smart City development, goal setting, and
policy. The visionary scenario of Amsterdam was structured around sustainability
(Gemeente Amsterdam, 2016). The ultimate goal of Amsterdam Smart City to in-
crease the quality of life was making it a future-proof city based on a circular econ-
omy. This implied a city for the future, ready to respond to all kinds of disruptions
and changes whilst remaining attractive and competitive in innovation, which is the
core element of the process. Mora (2017) believes that the key to the success of Am-
sterdam Smart City is ‘strategic planning’ that is based on three main rules: strategic
thinking, collaboration, and inclusion. In Masdar City, improving the quality of life
was interpreted as taking advantage of the technologies of the day to provide envi-
ronmental quality and better services to citizens (Han, et al., 2019; Masdar Mubadala
Company, 2018). But taking advantage of technology with only the focus on tech-
nology sounds like technological optimism (Pontin, 2009). It was high-risk gamble
94 Towards a Classification of Smart City Development Pathways
4
for Masdar, with a lot of confidence in technology and little space for the social as-
pect, that led Cugurullo (2013, p. 35) to end his study on the case of Masdar with the
statement of ‘We leave Masdar City hoping that Abu Dhabi’s example will not cross
the desert’ (Cugurullo, 2013). For Dubai, a Smart City is the happiest city and that
guarantees the quality of life, based on the vision and ambition of the Ruler of Dubai.
This vision sounds utopian due to the difficulty of defining happiness and the vari-
ety of opinions people have of it. Another challenge for Dubai is that more than 80%
of its population consists of migrant laborers (De Jong et al., 2019), for whom differ-
ent criteria apply when compared with locals. Nonetheless, putting a lot of effort
into the smart healthcare domain by Smart Dubai can be seen as a human-centric
approach (especially in times of the COVID-19 pandemic) that ensures a higher qual-
ity of life for its citizens. Barcelona Smart City is a digital (smart) city with techno-
logical sovereignty of citizens that puts technology at the service of people, as Cal-
zada (2018, p. 6) states: ‘Barcelona is currently explicitly branding itself as an inclu-
sive, democratic, and participative Smart City’. Barcelona is a leading Smart City in
terms of digital ethics and citizen data sovereignty; however, the challenge ahead
remains for citizens to become aware of their digital rights and duties (Calzada,
2018). Its experimental pathway in this regard can provide an answer to the question
‘is the open-data era, and citizen data ownership realistic or will remain as a
dream?’.
In sum, the results show that governance structures are a main determinant for
successfully developing a Smart City. It involves local government, other (higher
level) governments, private organizations, knowledge institutes, business enter-
prises, and citizens, and requires integrating technology (as the main enabler) with
creativity (for entrepreneurship) and viable business models (the financial-economic
driver). This leads to the emergence of smart applications (smart government, smart
citizens, smart mobility, energy and healthcare) and sustainability. In all cases, it also
requires outside investment to start Smart City initiatives and projects, not only from
the private sector but also from higher levels of government such as the EU or na-
tional government. Once having secured a financial basis the first projects are set up
to nurture the innovation environment and address how citizens can benefit or even
participate in bottom-up Smart City development (except for the case of Masdar
City). After the initial projects are set up, initiatives are taken to develop platforms
that are embedded in local policies and supported by local political and administra-
tive leadership, sometimes taking novel forms like in the Amsterdam Smart City
case.
In parallel, action is taken to set up living labs and data-driven experiments in
order to learn from e-innovations in practical, urban environments. Surrounding
these labs is involvement of stakeholders from different sectors like industry,
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 95
4
knowledge institutes, government, and citizens. Local and state governments also
use them as vehicles to attract more business investment. To support these innova-
tion zones, other—often low taxation—measures are implemented by public author-
ities. Finally, in all of the cases local authorities—but in particular Masdar and Du-
bai—strive to have lighthouse projects in places they can show at international
events (Yigitcanlar et al., 2019), like Expo Dubai 2020 or Barcelona hosting the Smart
City World Congress 2019, or brand themselves with, in order to attract future in-
vestment and prolong their development paths of Smart City development.
Nonetheless, Amsterdam, Barcelona, Masdar, and Dubai still have quite differ-
ent approaches to developing and governing a Smart City. Amsterdam and Barce-
lona are more focused on horizontal co-ordination with ample room for bottom-up
decision-making, using participatory platforms (Zygiaris, 2013). In contrast, Dubai
and Masdar use more vertically oriented, respectively aristocratic and technocratic
government approaches (Angelidou, 2017; Yigitcanlar et al., 2019). How cases play
out in terms of these dimensions and in which category they eventually end up in
the matrix determines in the end how the development pathways take shape and
differ from the more general pathway described earlier in this section.
4.7. CONCLUSION
This chapter examined different approaches to Smart City development that
reflect different ways in which cities are governed, and different pathways urban
governments take to become smart. The present study aimed to further understand
how urban governments formulate and use policies by systematically analyzing and
comparing four Smart City projects. The main research question was: When com-
paring a selection of Smart City projects, how can pathways for their implementa-
tion be classified? By using a comparative case study research design the present
study mapped how different design choices of Smart Cities play out in their imple-
mentation and governance. The four cases were: Smart Dubai, Masdar City, Barce-
lona Smart City, and Amsterdam Smart City. We selected two Emirati/Arab and two
EU cases (one in the North and the other in the South of Europe) to increase the
variation in geographic location, culture, type of city, and government, polity, public
leadership style, and institutions. To systematically analyze the four cases the Input-
Output model for Smart City development was used and elaborated, containing in-
dicators that are indicative for design choices and developmental pathways that in-
fluence their development.
The results of this study show that Smart City development in Amsterdam is
based on a business-driven approach, which puts innovation at its core; Masdar’s
choices reflect technological optimism; social inclusion is the focus of the Barcelona
Smart City pathway; and visionary-ambitious leadership is the main driver behind
96 Conclusion
4
Smart Dubai. This variety makes their Smart City development pathways different.
Comparing Smart City development in the four cities reveals that they also have
commonalities. In all cases, Smart City development took off in response to grand
environmental challenges and the need to make the city future-proof. In addition,
leadership is needed to adopt this vision and to start the process of initial policy
making and planning. Next, in order to support capacity development, outside in-
vestment is needed, which concerns collecting a budget not only through private
sector investment but also from higher levels of government. Once project budgets
are secured, the first activities are embarked on to nurture the innovation environ-
ment and address how citizens can benefit from or even participate in bottom-up
Smart City development. In parallel, initiatives are taken to develop platforms em-
bedded in local policies and supported by local political and administrative leader-
ship. Finally, local authorities strive to develop lighthouse projects that allow them
to brand themselves in order to attract future investment and extend their develop-
mental pathways for Smart City development. Although Amsterdam, Barcelona,
Masdar, and Dubai were compared analytically one should not forget that they are
located in contexts that vary a great deal.
The analysis of design choices made in the four cases also provides guidance
for the following research on how to transfer lessons from developmental-pathway-
supporting policies among various Smart City initiatives.
Finally, the concept and findings presented in this study for policy makers pro-
vide practical clues as well as policy lessons on how to develop a Smart City. Most
of the time, confusion and contradictions appear when a comprehensive team that
includes urban policy makers and planners, government officials, economists, envi-
ronmental engineers, technology companies, and sometimes even citizens starts
working on a Smart City development program. They have different expectations,
which makes establishing a common language for Smart City development a chal-
lenge. For cities that have just gotten started with Smart City development pro-
grams, this is in fact the first challenge they face. With the broader question in mind
of how best to govern one’s Smart City development, an urban manager may look
at a variety of examples, their practices, and outcomes.
Notes
1
In-depth interviews were held (during 2018 -2019) with 32 Smart City stakeholders
including: the City Experience advisor, the executive manager, the ideologist of Smart Dubai
Office, a professor from Zayed University, the executive director of Sustainable City in Dubai,
the executive director and the program manager of TAQATI, the executive director of DEWA,
The of Dubai Supreme Council of Energy, and the managing director of a magazine called
The Sustainabilist; Executive Director Erasmus Centre for Data Analytics, the Program Man-
ager Urban Data & Intelligence - Amsterdam Institute for Advanced Metropolitan Solutions,
Classifying Pathways for Smart City Development: Comparing Design, Governance and
Implementation in Amsterdam, Barcelona, Dubai, and Abu Dhabi 97
4
the Program Lead Living Labs - Amsterdam Institute for Advanced Metropolitan Solutions,
Advisor Smart Cities, Netherlands Enterprise Agency, Ministry of Economic Affairs, CTO of
Amsterdam, Delegations Lead - Amsterdam Smart City, Project manager Smart City Acad-
emy, Program Director Amsterdam Smart City at Amsterdam Smart City, and EVP Sales and
Business Development at HAL24K; Direcció de Telecomunicacions i Infraestructures,Institut
Municipal d’Informàtica, Ajuntament de Barcelona, Director of Digital Transformation and
ICT International Relations, Commisisoner on Technology and Digital Innovation Office, Bar-
celona City Council; Professor of Practice at Masdar Institute of Science and Technology.
99
5
TOWARDS AN INTEGRATED
FRAMEWORK TO MEASURE SMART
CITY READINESS: THE CASE OF
IRANIAN CITIES
The contents of this chapter have been adapted from the following peer-reviewed article: Noori, N.; de
Jong, M.; Hoppe, T. Towards an Integrated Framework to Measure Smart City Readiness: The Case of
Iranian Cities. Smart Cities 2020, 3, 676-704.
100 Introduction
5
5.1. INTRODUCTION
Conferences, seminars, and statements of executives and government officials
and academic articles around the Smart City topic reflect growing attention to start-
ing programs associated with Smart City development in most of the countries
around the world. Growing urbanization, economic competition, citizens’ expecta-
tions, and environmental challenges, along with rapidly improving technological
opportunities, are the main drivers (Smart Cities Council, 2015; Hollands, 2020;
Wiig, 2018; Breslow, 2020). Some pioneering cities have gained valuable experience
from which both positive and negative lessons can be drawn. Followers can learn
from these and join in this emerging trend. The Iranian government, as one of these
followers, has always mentioned globalization in its policy documents and visions
and recently smart urban development amidst globalization appears in many policy
documents drafted by Iran’s largest cities. Tehran, Mashhad, Isfahan, Shiraz, Urmia,
and Qom are the largest Iranian cities and are using a smart label in their profile.
This is part of an overarching national Smart City program. Some of Iran’s neigh-
boring countries have taken considerable steps to develop Smart Cities of their own.
They have used Internet of Things (IoT) solutions to solve urban management prob-
lems by learning from strategic and technical approaches to develop ‘smart-city’ ca-
pabilities, in particular based on good practice. For instance, in the UAE, Dubai has
made significant progress in recent years (Harvey & Ponzini, 2019; Breslow, 2020).
In chapter 2, I examined the credibility of the city brands adopted by Iran’s
largest cities. The results revealed that, among the cities with a smart profile, only
four cities (Tehran, Mashhad, Isfahan, and Shiraz) actually have credible brands.
Credibility is defined in terms of six factors contributing to credibility of a city brand:
(i) generate feelings of loyalty; (ii) facilitate the development of an overarching strat-
egy or policy; (iii) evoke positive feelings; (iv) demonstrate uniqueness or distinct-
ness; (v) allow for different, yet non-contradictory, messages to various stakehold-
ers; and (vi) logically connect past heritage, current profile, and future ambitions.
Still, the question remains on whether these cities are truly ready to become smart?
In view of the fact that the formulation and implementation of a Smart City policy,
like any other policy, needs to be tailored to the contextual conditions and would
require infrastructures, assessment of the readiness of these cities to participate in
this global trend is essential (Achmad et al., 2018). Therefore, the present study
aimed to provide a systematic, integrated theoretical framework that can be used to
measure Smart City readiness and, based on that, a Theory of Change which cities
can consider when they prepare themselves for their transition to become ‘smart’.
Basically, they can learn from pioneers and good practice, and localize the policies
and solutions since each city has its own unique features and challenges, as well as
requires its very own set of solutions (Dameri et al., 2019).
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 101
5
Multiple studies have addressed the transition process cities engage into be-
coming smart (Chourabi et al., 2011; Lee et al., 2014; Neirotti et al., 2014; Ibrahim et
al., 2018). But less attention has been awarded to the readiness of cities into becoming
a Smart City (Berst et al., 2013). In their overview study, Ibrahim et al. (2018) assessed
city readiness for change during the transition process into becoming smart sustain-
able cities by focusing on local assets. In another study, Achmad et al. (2018) evaluate
city readiness considering technological, social, and political conditions for change.
The study showed that the Smart City enablers are particularly brainware, hard-
ware, and software. The authors hold that these are indicators that should be as-
sessed for evaluating Smart City readiness. Although Ibrahim et al. (2018) discern
different aspects of readiness, like the non-technical readiness, the study itself fo-
cuses predominantly on technical aspects, and, in particular, stresses the examina-
tion of readiness for Information and Communication Technology (ICT). The Smart
Cities Council (2013) has investigated the barriers to Smart City development from
working on Smart City projects all across the world. Their results show that a fre-
quently emerging barrier is the lack of a system-wide view and integrated approach.
Developing a Smart City requires integrating technological and non-technological
contexts and create a holistic vision. This present study aims to add non-technolog-
ical aspects to the readiness mix to enable urban governments in developing a more
comprehensive ex ante assessment of their Smart City readiness.
The aim of this study is to examine the contextual conditions and readiness of
cities to become smart. Consequently, our research questions (RQs) are the follow-
ing:
How to determine whether cities are ready to transition into Smart Cities? What
does an indicator system measure to determine whether a city is ready to become
smart? And to what extent do Iranian cities meet the minimum requirements for
becoming smart?
To address these questions, I conducted a qualitative study based on two theo-
retical frameworks: first, one presented by Dameri et al. (2019), which identifies a
list of global and local Smart City features; and second, the framework for Smart
City design variables (IO model) presented in chapter 4. I add social and institutional
variables based on a literature study and my intention to compensate for the short-
comings of current theoretical frameworks and develop a more holistic integrated
theoretical framework. I apply this to four cases in order to analyze their specifica-
tions in terms of being ready to become Smart Cities. The contribution of this study
is in highlighting the role of technological, socio-economic, and political readiness
of governing an urban transition process towards a Smart City with an indicator
system to measure Smart City readiness.
102 Transition Towards a Smart City and Readiness for Change
5
The structure of this chapter is as follows. Section 2 maps the academic litera-
ture to explore more in-depth insights on cities’ readiness for transition into smart
urbanism and also presents the urban transition theory and the theory of change.
Section 3 presents the research design, methodology, and data collection and shows
our adjustment and elaboration of existing theoretical frameworks to develop an in-
dicator system subsequently applied the case studies. Section 4 provides the analysis
and exploratory insights on Iranian cities’ readiness to become Smart Cities. In Sec-
tion 5, the results of the study are presented and discussed. Finally, in Section 6, the
conclusions and suggestions are presented. In addition, policy recommendations are
provided for ‘smart initiatives’, particularly Iranian smart initiatives, to find out how
they can prepare for their transformation.
5.2. TRANSITION TOWARDS A SMART CITY AND READINESS FOR
CHANGE
5.2.1. URBAN TRANSITION
Transforming a city into a Smart City first of all requires consideration of the
readiness of a city for change (Berst et al., 2013). The term ‘change’ refers to both
technological and non-technological changes in the urban context. The transition
discourse appears when a specific way of knowing long-term transitions is consid-
ered (Jhagroe, 2016). Frantzeskaki and De Haan (2009) view ‘transition’ as a societal
process of fundamental change in culture, structure and practices. According to
Geels and Schot (2007), transitions are changes from one socio-technical regime
(which pertains to a network of actors and institutions, and cultural or social norms
along with technological trajectories) to another. In the quest for an urban transition
into Smart Cities, change is primarily described using insights on transitional change
of socio-technical regimes in urban environments.
According to Jhagroe (2016), ‘urban transition’ can be defined as the creation
and normalization of urban regimes and practices in the replacement and reforming
of other urban regimes and practices. In this sense, it fits the more general definition
of transition coined by Geels and Schot (2007) and applies it to the urban domain.
To conceptualize the notion of urban transition, one needs to know how the transi-
tion process is initiated, guided, and how it evolves over time. Smith et al. (2005)
point out that regime change is the result of internal or external pressures on the
regime, which can range from political, economic, social, environmental, to techno-
logical pressures. They argue that the resources available inside and outside the re-
gime should be coordinated to adjust to the pressures. By combining the availability
of resources and the degree of coordination, Smith et al. (2005) developed a two-
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 103
5
dimensional framework for a typology of four transitions. They argue that system-
level change requires coordination of different actors and resources. Stripple and
Bulkeley (2019) also highlight the alliance between different actors in the process of
a transition to promote certain transition pathways.
Over the past decade, the concept of urban transition has been used in a grow-
ing number of studies addressing ecological modernization of cities (Berst et al.,
2013; Frantzeskaki & De Haan, 2009; Berkhout et al., 2009; Stripple & Bulkeley, 2019).
A momentous discourse is the one on sustainable technology transitions, which is
supposed to be one of the main contributions of Smart Cities development. Smith et
al. (2005) understand sustainable technology transitions as changes mediated by the
resources, interests, and expectations of institutionally embedded networks of ac-
tors. In an investigation of Asian development pathways and sustainable socio-tech-
nical regimes, Berkhout et al. (2009) stress the absence of linkages between different
government levels (i.e., between the local, regional, and national levels) in socio-
technical systems as an obstacle in sustainability transitions. All the studies men-
tioned above stress the importance of contextual factors, resources, and networks of
actors in transition processes (Hoppe et al., 2016).
5.2.2. TECHNOLOGICAL READINESS
Several scholars argue that technological readiness is an essential condition for
transition towards Smart Cities (Achmad et al., 2018; Berst et al., 2013; Calderon et
al., 2018; Blut & Wang, 2019; Buyle et al., 2018; Madsen, 2018; Yu et al., 2019). In their
study, Ibrahim et al. (2018) stress the importance of checking city readiness for
change before planning a transition process. ‘Technological change’ is obviously
part of this urban transitional change, including the adoption of emerging technolo-
gies and providing appropriate and adequate infrastructures. In the Smart Sustain-
able City transition roadmap, these authors propose to add two pre-phases that per-
tain to ‘city vision’ and ‘city readiness’. In the ‘city vision’ phase, city priorities are
identified through current city state analysis, vision and strategies, and identifying
stakeholders. During the ‘city readiness’ phase, the readiness of ICT-based infra-
structures, non-ICT-based infrastructures, and availability of any previous Smart
Sustainable City initiatives are checked. In terms of ICT-based readiness, the authors
propose to assess the hardware and software infrastructures, as well as ICT-related
skills (Ibrahim et al., 2018). In 2009, the International Telecommunication Union
(ITU) presented an ICT development index (IDI) that combines eleven indicators on
ICT access, use, and skills, capturing key aspects of ICT development in one measure
that allows for comparisons between countries and over time. Among many studies
(Lee et al., 2014; Calderon et al., 2018; Ibrahim et al, 2018; Achmad et al., 2018), the
104 Transition Towards a Smart City and Readiness for Change
5
Smart City readiness guide presented by the Smart Cities Council (2015) appears to
be the most comprehensive guide for assessing technological readiness.
The definition of the Smart City behind this Smart City readiness framework
by the Smart Cities Council (2015; p. 6) is: a city that uses information and commu-
nications technology (ICT) to enhance livability, workability, and sustainability. The
definition shows that the core enabler of Smart Cities is ICT, and the ultimate goal
is to establish a better future city to live and work in, while preserving, the environ-
ment. The framework holds that all the city functions (including energy, transporta-
tion, telecommunication, health, human services, waste management, payments,
and finance, as well as public safety) that Smart Cities promise to improve are ena-
bled through the power of technology (Smart Cities Council, 2015). It proposes dif-
ferent technology enabling indicators to assess Smart City readiness to provide in-
sights in where to start and where to end up for decision-makers.
In the present study, in order to assess the technological readiness based on
urban transition concepts, I started with an analysis of the current situation of the
available technological resources. For this purpose, I relied on an Input-Output (IO)
model of Smart Cities that determined the key resources for Smart City development
process. It proposes different design variables for ICT infrastructures as one of the
key resources in the development process. For developing a Smart City technologi-
cal readiness framework (see Table 1), I also deemed it necessary to pay attention to
insights pertaining to the Smart City readiness guidelines presented by the Smart
City Council (2015) and IDI issued by ITU (2017).
Table 1-Smart City technological readiness framework (adopted from the Input-Out-
put (IO) model of Smart City and the Smart City readiness guidelines (Smart Cities
Council, 2015)).
Smart City Attributes
Design Variables
Indicators (Presence of)
ICT and Data resources
Data aggregation
Big data establishment
Sensors and actuator equipped
devices, CCTVs & cameras
Connectivity
ICT Development Index (IDI)
Data processing
Data science centres
Data real-time analysis
Data visualization platforms
Data management capa-
bilities
Establishing a data au-
thorization
Data Laws
Security
Establishing a cyber security
framework
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 105
5
The key purpose of developing ICT infrastructures for Smart City development
concerns: (1) connection to things that facilitate collecting data; (2) connection to
things for targeted information; and (3) connection to things for data serving in
smart applications. The IO model emphasizes that, along with the required re-
sources, there is also a need for dynamic capabilities to manage these resources. A
vital resource for smart urbanism that needs to be managed is data. Watts et al.
(2009) state that the complexity of managing data increases with increasing data vol-
umes. The aim of big data management is to ensure the quality of data and trans-
forming data into knowledge (Watts & Shankaranarayanan, 2009). But this is not the
only purpose of data management; there also are concerns about the misuse of data
and cybercrime. Issues like data theft, data ownership, data accessibility, and pri-
vacy issues can arguably be managed by establishing data authorization and cyber
security platforms (Dijkers, 2019; Chierici et al., 2019).
5.2.3. SOCIO-ECONOMIC READINESS
Urban transitions influence the societal system in several ways, but this is not
to be considered one-way traffic. In fact, it is an interaction between the societal sys-
tem and technology regimes governed through authorization. Change in urban tran-
sitions requires input of human resources to make the transition happen, and the
new urban regimes and practices need to be supported by social networks (Smith et
al., 2015). The central activities for Smart City readiness may be to provide human
resources for the Smart City development process and to support formation of social
networks around the Smart City development process. Context matters in this re-
gard (Dameri et al., 2019). Using a knowledge-based conceptual vision of the Smart
City is a fundamental requirement for improved decision-making (Geels, 2005).
Providing the required knowledge for Smart City development can either be ex-
tracted from data flows (explicit knowledge) or from human capital (including tacit
knowledge) (Geels, 2005). Nam and Pardo (2011) even argue that human factors
form the core components of a Smart City, along-side technology and institutional
factors. Human factors entail concepts like social learning, creativity, and education.
However, knowledge alone is not sufficient. Knowledge and creativity can, rather,
be viewed as two enabling wings of innovation fostering smart solutions (Negre et
al., 2015). Based on these arguments, the IO model proposes resources to provide
both human and entrepreneurial infrastructure as: educated and trained people, an
innovation environment, and a supporting system for innovative companies and
start-ups. The output in the IO model pertains to smart applications (in terms of
energy, mobility, healthcare, governance, and citizens) (Hoppe et al., 2016).
In the context of Smart Cities, innovation studies provide insight into which
type of citizens are most likely to support Smart City technologies and policies and
106 Transition Towards a Smart City and Readiness for Change
5
be involved in the development process. Sepasgozar et al. (2019) found that the cul-
ture and needs of urban citizens are important factors for acceptance of related urban
service technology. Dameri et al. (2019) enumerate geographical localization, cul-
ture, mentality and values of people, educational level, different ideas of quality of
life, national laws, and territorial governance models as characteristics that are spe-
cific to Smart Cities. In an extensive survey, Calderon et al. (2018) also mention the
knowledge level citizens have about the Smart City concept and smart technologies
for checking Smart City readiness in Latin American cities.
Insights taken from the previously mentioned literature led us to conceive the
following framework for social readiness of city residents to Smart City transitions
(Table 2).
Table 2- Smart City socio-economic readiness framework.
Factors
Definition and Operationalization
Education
Number of universities and research centres
Knowledge transfer and knowledge sharing programs
Innovation
Specific policy in place to promote Smart City innovation
Supporting and encouraging programs for innovative companies
(science and technology parks, free zones, etc.)
Awareness
Level of citizens’ awareness of the Smart City program in their city
Level of citizens’ awareness of the Smart City concept and technol-
ogies
Perceived usefulness
Level of perceived usefulness of the smart solutions for the city’s
challenges by citizens
Mentality and values
Citizens’ opinion about a Smart City
Citizens’ image of their cities
Citizens’ different ideas of quality of life
5.2.4. POLITICAL READINESS
An important additional contextual factor affecting Smart City readiness is the
policy environment, including national policies, legislation, and local governance
arrangements. Smith and Stirling (2010), through highlighting the relation between
‘policy institutions and political activities’ on the one hand and the transition man-
agement processes on the other, stress the importance of political power to decide
when and how to make the transition happen. When many actors are involved in a
process and their interactions vary across time and policy issues, the process is com-
plex in terms of policymaking and implementation (Sepasgozar et al., 2017). Smart
City programs deal with this complexity, having to cope with different actors who
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 107
5
have divergent interests (Cairney, 2012; Joss, 2015; Yigitcanlar, 2016). Cairney (2012)
believes that power diffusion makes public policy processes and outcomes different.
It is also important to consider governance models that are used in urban tran-
sitions. Governance model here refers to all the processes of governing the city, both
formal and informal institutions, undertaken by a government or any other actors.
Governance includes formal policy instruments, such as laws, rules, municipal or-
dinances, and territorial policies, and non-institutional mechanisms, such as public–
private partnerships, subsidiaries, negotiations, and citizen participation (Bevir,
2012). Governance is not only about what governments do but also about the out-
comes of interactions between all actors in the public domain (Scholl& Scholl, 2014;
Dameri& Benevolo, 2016). Therefore, there are two characteristics in the political en-
vironment that have impact on Smart City development: the governance structure,
and the interaction between government and other actors (see Table 3). Government
also has a role to play in the interaction among actors. In Smart Cities known as good
practice examples, like Dubai or Amsterdam, local government takes the initiative
for Smart City transition and is responsible for coordinating joint action involving
multiple local stakeholders. This includes alignment of visions and expectations, for-
mulation of the Smart City vision, and alignment with the overarching policy, re-
gional, and national programs, providing a platform to involve different actors, at-
tracting funds, and eventually implementation of a Smart City transition policy. In
addition, public leadership is necessary to support establishing a vision for policy
making and implementation, while, at the same time, maintaining transparency and
building trust among local stakeholders and residents (The Government Summit,
2015; Scholl& Scholl, 2014).
108 Research Design and Methods
5
Table 3-Smart City political readiness framework.
Political Context
Definition and Practices
National policy and govern-
ance
National leadership
Government structure, governance arrangements, policy
networks
Rules, laws, legal and regulatory reforms
Legitimacy, transparency, and trust
Municipal policy and gov-
ernance
Local leadership
Partnerships with industry, academia, and citizens
Providing a platform for multi-stakeholder partnership
Smart City innovation clusters and networks
5.3. RESEARCH DESIGN AND METHODS
The analytical framework used is based on the IO model of Smart City devel-
opment and the Smart City readiness guide by Smart City Council (2015). I use the
framework derived from a qualitative data analysis of scientific papers and existing
frameworks for Smart Cities readiness (Appendix A, Table. A3). My approach ap-
plies the IO model and existing related frameworks to develop a framework for tech-
nological, socio-economic, and political readiness and uses the theory of urban tran-
sitions to understand how technological, social, and political features influence the
cities’ readiness to become smart. Then, I use the integrated framework on Smart
City readiness based on Tables 1, 2, and 3 to identify indicators and collect and or-
ganize our data. The integrated framework is shown in Table A1. The next step is to
apply this framework to the cases of Iranian cities. These cases pertain to four large-
scale Iranian cities (with over 500,000 residents each) that have Smart City policies
in place and have also adopted a Smart City brand that is considered credible as
discussed in chapter 2. The four cities are: Tehran (the capital of Iran), Mashhad (the
capital of the Khorasan-e Razavi Province), Isfahan (the capital of the Isfahan Prov-
ince), and Shiraz (the capital of the Fars Province).
5.3.1. DATA COLLECTION
In order to collect data, I used both desk research and a survey. For assessing
technological readiness, both qualitative and quantitative data were collected from
the city websites, available statistical datasets, and policy documents, such as mas-
terplans and policy reports. To collect data related to social readiness, I conducted a
survey among citizens using a questionnaire. I conducted a survey in 2020 asking
for citizens’ views on the Smart City program in their city (whether respondents are
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 109
5
aware of it or not; whether respondents agree with or not; whether respondents find
it useful to solve their urban issues or not; to what extent respondents are familiar
with Smart City technologies, and the perceptions respondents have of a Smart City
in general, the main issues playing in their city, respondents’ perception image of
the city; and their assessment of quality of life). I distributed the questionnaire
through email and social media (i.e., via WhatsApp and Telegram groups) until I
received responses from at least 20 participants in each city. The response rate varied
per city: i.e., in Tehran (21/ 37), Isfahan (23/34), Mashhad (20/52), and Shiraz (20/78).
All participants were citizens of one of the four cities and had lived there for at least
three years. The sampling method was intended to be random. However, the final
sample was biased because an online survey was used. For this reason, respondents
are mostly citizens who are familiar with and use the internet, use smart phones,
and, in this sense, already have some affiliation with the concept of the Smart City.
For political readiness, we used qualitative data available on the international index
rankings and reports on Iran’s governance assessment (Bertelsmann Stiftung’s
Transformation Index (BTI) 2018), cities’ official websites, governmental reports,
and policy documents.
5.3.2. DATA ANALYSIS AND THEORY OF CHANGE
To analyse data, I applied the approach of the Theory of Change (ToC), which
included a situational analysis as a form of empirical analysis, prior to designing a
Theory of Change. Weiss (1995) introduced ’Theory of Change’ (ToC) as a theory to
clarify how and why a given (policy) intervention initiative works. It was mainly
generated to support ex ante evaluation of a given intervention. Connell and Ku-
bisch (1998) argue that there are three main reasons to develop a ToC for interven-
tions: First, by sharpening the planning and implementation; second, by facilitating
the measurement and data collection elements of the evaluation process; and third,
by reducing problems associated with causal attribution of impact by articulating a
roadmap for the change and making an agreement between different stakeholders.
The United Nations Children’s Fund (UNICEF) defines ToC as follows (Rogers, 2014
p. 3):
‘A ToC explains how activities are understood to produce a series of results that con-
tribute to achieving the final intended impacts. It can be developed for any level of interven-
tion – an event, a project, a program, a policy, a strategy or an organization’.
Starting with the definition by UNICEF that stresses using the ToC for different
levels, I associate the theory of change with Smart City policy planning to identify
the current situation, the intended situation, and what needs to be done to transform
a city into a Smart City. According to the UNICEF definition, the ToC deals with the
110 Iranian Smart City Development: Smart City Readiness
5
interventions. It makes the theory responsible for addressing three fundamental
questions: (1) What are the interventions? (2) What is the current situation in terms
of needs and opportunities for future development? And (3), what needs to be done
to move from situation ‘A’ to situation ‘B’? (Rogers, 2014; Connell& Kubisch, 1998).
In the present study, the object for the ToC is ‘the readiness of Iranian cities to be-
come smart’, the interventions refers to ‘technological resources and capabilities’,
individuals and society’, and ‘national and municipal political systems, while ‘situ-
ation’ refers to the plans, projects and actions regarding technological, social, and
political readiness to becoming a Smart City. The current situation analysis provides
insights on available resources, current issues, and problems in need of solutions, as
well as contextual conditions. Analysis of the desired situation clarifies what out-
comes the initiative should reach with those interventions and available (or planned)
resources in a certain context. The comparison between the current situation analysis
and the intended outcomes reveals the gap between situation ‘A’ and situation ‘B’,
and the challenges and opportunities for the transition from ‘A’ to ‘B’. Generating a
ToC -based on the gap analysis considering challenges and opportunities can guide
decision-makers on how the gap can be bridged. They may either decide to plan for
making necessary resources available and some contextual changes, or to adjust
their intended goals.
In order to take the first step of generating a ToC in the present study I need to
specify what the situation (both the current situation and the desired future situa-
tion) means in our intervention (or initiative), including technological, social, and
political readiness. Based on the ToC, I take the following three steps for all four city
cases data analysis: Step1: A situational analysis; Step 2: An analysis of the gap be-
tween current situation and intended situation, laying bare the challenges and op-
portunities; and Step 3: Mapping a ToC about how to get from the current situation
to the desired situation.
To conduct a situational analysis (step 1), I rely on a qualitative analysis of data
organized through the integrated framework for Smart City readiness in this study.
To perform step 2 (determining the challenges and opportunities), I rely on qualita-
tive data reflecting the cities’ visions and goals of Smart City development, as well
as statements of the officials about their Smart City programs. And, finally, based on
the analysis, I provide policy recommendations for the change (being ready to trans-
form into a Smart City).
5.4. IRANIAN SMART CITY DEVELOPMENT: SMART CITY READINESS
Iran started promoting Smart City development in its third Five-Year Plan
(2018–2022). It sought to deal with urban problems ahead and looked at new ap-
proaches in the development of future cities around the world. It selected five cities
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 111
5
(Isfahan, Uremia, Tabriz, Tehran, and Mashhad) for the development of Smart Cit-
ies. Later, the municipalities of Shiraz, Qom, and Kish Free Zone also joined to the
national Smart City program and adopted a vision to profile themselves as ‘smart’.
In most cases, expressing the wish to become smart was a reaction to urban prob-
lems, such as traffic congestion, air pollution, energy crisis, or ideals for improving
the general well-being of citizens. I examined the credibility of the Iranian mega cit-
ies brands in chapter 2 and found that four cities among them had the most credible
Smart City brands, i.e., Tehran, Mashhad, Isfahan, and Shiraz.
In this section, the readiness framework presented in Section 2 is applied to the
case of these cities to map their current technological, socio-economic, and political
situation in terms of being ready for transition towards a Smart City.
5.4.1. TECHNOLOGICAL READINESS
Tehran, which is more engaged with urban issues, like traffic and air pollution,
and has different urban policy layers, perhaps would be one of the most complex
Smart City projects in Iran. Although all cities in the mainland operate in a multi-
level government context, Tehran, as the political centre of the country, has always
attracted more attention. This most important city of Iran, with a population of more
than 8 million people, accounts for about 11% of the country’s total population and
ranks 28th among the world’s most populous cities (Shabestar et al., 2017).
ITU ranks Tehran province 1st in Iran with an IDI value of 7.24 in 2017, while
Shiraz (6.25), Isfahan (6.24), and Mashhad (5.35) ranked, respectively, 7th, 8th, and
18th. Most of Iran’s datacentres are located in Tehran, to serve the entire country
from the capital where the equipment and infrastructure is most advanced. Iran’s
IoT research centre launched ‘The Things Network of Tehran’ as a global open
crowd-sourced IoT data network, which is the first of its kind in the Middle East. An
integrated city data portal and application, so-called ‘My Tehran’, was established
in 2018. Citizens of Tehran can access many services through this integrated portal
with a citizen account in which city statistical data are openly available and visual-
ized in eighteen categories. Yet, the portal is under development and a limited num-
ber of data (and not critical data) was accessible at the time of writing this article.
The ICT organization of Mashhad municipality is planning to launch a city por-
tal, as well. The goal is that citizens can access all the smart applications through a
single user account (ICT Organization of Mashhad Municipality). Isfahan launched
the ‘Network Real Time Kinematic’, which aims to develop an integrated platform
for spatial information so-called ‘Sima’ (Isfahan Municipality ICT Organization).
Shiraz’s financial and economic deputy announced setting up a data centre in the
city of Shiraz in order to achieve smart features. The goal of the Shiraz Big Data
Centre is to establish Smart City features through which services in terms of smart
112 Iranian Smart City Development: Smart City Readiness
5
governance and policies, smart economy, smart living and working environment,
smart transportation, and smart citizen can be provided (City of Farda, 2020).
Iran’s Minister of Communications and Information Technology (2015) claimed
that the fiber-optic network expansion program in Isfahan that is in progress will in
the near future provide appropriate infrastructure for Smart Isfahan. The 2019–2020
plan of Isfahan indicates the focus on expanding the fiber-optic network and data
centre projects. The Geographical Information System projects based on developing
a Geo-data base is also another focus of this one-year plan (IRNA, 2015). Sensors and
actuator-equipped infrastructures can enrich big data establishments by providing
real-time inputs. According to the ICT Director of Tehran Municipality (2019), im-
porting needed sensors for the Smart City program will be expensive due to the ris-
ing exchange rate and sanctions, so that promoting domestic production will be a
cost-effective solution to provide these sensors and actuators (
ICTNA, 2019). In Mash-
had, the municipal ICT organization has announced it will provision flood alert sen-
sors, air quality sensors, and traffic sensors for the Smart City development program
(ICT Organization of Mashhad Municipality). To improve traffic conditions, the ICT
Organization has started to produce and operate the ‘Traffic Image Analysis System’
(Sobh Mashahd News, 2019).
Four main data centres are based in Tehran (Supreme Council of Cyberspace,
ICT research institute, Iranian Institute of Information Science and Technology, and
Iran’s IoT Academy) and one in Mashhad (IT and Cyberspace Research Centre). In
2017, Iran’s Supreme Council of Cyberspace established IoT laws and regulations
for the whole country, which were approved and authorized by Iran’s Leader (Su-
preme Council of Cyberspace, 2017). In terms of establishing a cyber security plat-
form, Tehran has a cyber security research institute, and Mashhad’s and Isfahan’s
master plans indicate specific budget allocation for cyber security projects.
5.4.2. SOCIO-ECONOMICAL READINESS
In examining whether a given society has a suitable platform for developing a
Smart City, the educational status is a first indicator. There are 119 universities and
academic centres in the city of Tehran, and 24% of its population is high educated.
There were 1,382,515 students enrolled in Tehran universities in 2018, with 149,544
professors and faculty members. These figures for Isfahan are 67 universities and
academic centres, with 140,374 enrolled students in 2018. These numbers for Shiraz
and Mashhad are at 25 and 30, respectively, for universities and academic centres
(Iran Universities Reference, 2018).
One of the main knowledges and experience sharing programs around Smart
Cities was founded in 2008 following the proposal of Tehran Municipality to the
Asian Parliamentary Assembly (APA), Asian Mayors Forum (AMF): the Asian
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 113
5
Smart Cities Committee. The Tehran Urban Innovation Center (TUIC) was founded
in 2017, aiming to present new urban solutions influenced by the Smart City dis-
course. TUIC’s innovation model is based on the network innovation approach,
striving to build a foothold in the international network of knowledge generation
and idea sharing in the field of urban innovation (TUIC, 2017).
Isfahan Urban Creativity and Innovation Centre was also established in 2017 as
a bridge between the citizens’ ideas and the municipality (Iran’s Metropolises News
Agency, 2017). In 2018, the Urban Innovation Centre in Mashhad was put into oper-
ation to establish a link between urban management and emerging technologies
(IRNA, 2018). The City Council of Mashhad and Mashhad municipality have raised
the issue of establishing an urban innovation centre to achieve the 20-year vision of
city as a knowledge and Smart City (Mashhad Urban Innovation Centre, 2018). Ac-
cording to the ICT Director of Isfahan Municipality (2017), Isfahan has adopted the
international standards and indicators as its Smart City model, issued by the Smart
City World Council and the International Organization for Standardization (ISO
37120) (Isfahan Today, 2017). The head of the Centre for Strategic Technologies De-
velopment of the Scientific Deputy stated that the Shiraz Innovation Factory will be
launched in 2020. Ghaderifar (2020) mentions that the innovation factory is a cam-
paign for start-ups aimed to support ideas and train human resources and specialists
to create knowledge-based companies and innovative solutions.
There are eight science and technology parks and incubators around Tehran to
support innovative companies and start-ups by providing benefits to businesses
based in the parks. These are based on: tax exemption, annual performance exemp-
tion, exemption of duty payments, commercial interests and export duties, and for-
eign exchange transactions, like free economic zones (Iran Academic Centre for Ed-
ucation, Culture, and Research, 2008). All science and technology parks in Iran are
allowed to offer these advantages. In Mashhad, there is a science and technology
park, and there are eleven incubators. Isfahan has three science and technology
parks and 10 incubators, and Shiraz has one and five, respectively, science and tech-
nology parks, and incubators (EcoSystem).
The results from this four-city survey show that the level of citizen awareness
of the Smart City program in their cities are almost similar, and citizens mainly have
heard about it but have not received enough information. They also have an average
level of awareness of the of the Smart City concept and technologies. The level of
perceived usefulness of the smart solutions for the city’s challenges by citizens (of
all four cases) is significantly higher for traffic, pollution and environmental issues.
However, in Isfahan, the usefulness of smart solutions for housing issues was also
mentioned. In terms of citizens’ opinion about a Smart City, our preliminary results
114 Iranian Smart City Development: Smart City Readiness
5
from a pilot survey indicate that, in Tehran and Mashhad, the most frequent state-
ments by the survey respondents are related to ‘green’ and ‘surveillance’ city; in Is-
fahan, are linked to ‘surveillance’ and ‘happy’ city ‘surrounded by technology’; and,
in Shiraz, are associated with a ‘safe’ and ‘green’ city. Regarding the image of the
respondents from Tehran of their city, the most frequent images are intertwined
with a ‘polluted city’, ‘over-crowded’, and ‘expensive’, but still an ‘alive’ city. The
images that appear most frequently by the respondents of Mashhad minds regard-
ing their city are linked to a ‘crowded’ and ‘polluted’ city with deficiencies in public
transportation. In Isfahan, in addition to crowds and pollution, the respondents have
the image of a ‘beautiful’ and ‘historical’ city ‘with a lot of potential’. The most fre-
quent images of the city expressed by the respondents of Shiraz are ‘happy’ and
‘beautiful’ city. Regarding citizens’ different ideas of quality of life, the most fre-
quent statements in Tehran by the respondents are: ‘safety’, ‘prosperity’, ‘happi-
ness’, ‘peace’, and ‘citizen’s (human) rights’; in Mashhad, they are: prosperity’, and
‘happiness’; in Isfahan, they are: ‘health’, ‘safety’, and ‘happiness’; and in Shiraz,
they are : ‘safety’, ‘prosperity’, and ‘happiness’. However, these statements are not
based on a large sample from among citizens but, given the internal variation, they
still represent the opinions, images, and ideas of a relatively random group of citi-
zens such that it can at least serve as a first approximation in this exploratory study.
5.4.3. POLITICAL READINESS
In terms of political readiness assessment, the BTI report in 2018, on the gov-
ernance index, such as political participation; rule of law; stability of democratic in-
stitutions; socioeconomic development; economic transition; private property, ranks
Iran 115th out of 129 nations (Figure 1) (Bertelsmann Stiftung, 2018). The report (p.
4) states that:
‘Ideological and religious dogmas are basic principles of politics and the econ-
omy in Iran, often preventing the implementation of professional strategic plans,
projects and expertise. The leadership style and the entire ideological-religious foun-
dation of the Islamic Republic are the major constraints.’
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 115
5
Figure 1- Bertelsmann Stiftung’s Transformation Index (BTI) 2018 Iran Country Re-
port.
Iran has a multi-level governance structure, governing cities through a central-
ized approach. Each city has a city council of which candidates should be examined
by a central council overseeing the elections, and people will elect members of the
city council from among them. Each city has a municipality and its own municipal
laws and regulations that have to be aligned with the upstream policy documents
under the overarching Islamic law (Shariah). One of the main trustees of the Smart
City program in the Iranian cities is the ICT Organization of Municipality. It is re-
sponsible for directing and supervising the activities of the municipality and all its
116 Iranian Smart City Development: Vision and Expectations
5
affiliated organizations in the field of information and communication technology.
Another highlight in the BTI report (2018) is its emphasis on the lack of transparency
of the political system in their financing and administrative structures, which play a
crucial role in Smart City governance. A poll conducted by the state-run Iran Stu-
dents Polling Agency (ISPA) in 2019 confirmed that only 15 percent of the citizens
of Tehran were satisfied with the government (Radio Farda, 2019). Moreover, in
2020, only 26 percent of Tehran’s citizens participated in the parliamentary election.
Political analysts believe that, based on recent events (such as suppression of public
protests in November 2019 and the Ukrainian plane crash in Iran), the level of public
trust in government institutions has declined even further (FINANCIAL TIMES,
2020; Behravesh, 2020; Von Hein, 2020). The results of the survey presented in this
study, on the other hand, indicate that all respondents emphasize the importance of
citizen participation in urban decision-making. Appendix A (Table. A3) summarizes
the results and empirical observations from the four Iranian Smart Cities in address-
ing the research questions.
5.5. IRANIAN SMART CITY DEVELOPMENT: VISION AND
EXPECTATIONS
According to the analysis of about one million scientific articles, the topics
around Smart City concepts, such as ‘sustainability’, ‘information technology’, ‘qual-
ity of life’, ‘environment’, ‘data mining’, ‘knowledge management’, and ‘entrepre-
neurship’, are among the top 20 research topics in Iran over the last 10 years (Iran
Universities Reference, 2019). These themes are derived from academic channels.
But what do urban managers and policy makers aim for? Tehran has clearly men-
tioned the ‘smart’ program in its third Five-Year Plan (2019–2023) (Ilna News, 2019).
In both strategic documents of Isfahan 2021 and Isfahan 2026, the Smart City pro-
gram is referred to in the vision, goals, and missions. The Five-Year Plan (2017–2021)
of Mashhad Municipality has been compiled as the fourth operational plan, in which
smartening is clearly one of the goals mentioned, in line with the 2026 vision docu-
ment of Mashhad city. Shiraz’s third Five-Year Plan stresses smartening of urban
management, in particular by having an electronic municipality, i.e., making digital
public service delivery facilities available. Iran’s Minister of ICT, during the third
Smart Cities Conference (Tehran, 2019), emphasized the duty of the government to
provide infrastructures for Smart City projects and noted that ‘…the activities carried
out in the field of the Smart City over the past year show that we have moved beyond the
infrastructure layer, and this year we need to focus on developing inter-sectoral collabora-
tion’ (Tehran Nameh, 2019). There is a strong emphasis on preparing the infrastruc-
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 117
5
tures for Smart Cities in which the Ministry of ICT will be involved, and it also re-
quires the involvement of other ministries. He added ‘…apart from the above-men-
tioned investors, also universities, knowledge-based companies, Internet companies and mo-
bile operators must be active in this sector to ensure Smart City development’.
Vice President of Science and Technology, Sattari, during the third Tehran
Smart Conference (2019), pointed out the necessity of Tehran’s smartness. He stated
that: ‘The Smart City is a new operating system that will be installed on Tehran hardware
and will change the city’s usage; all the cities around the world are moving in this direction
and Tehran must take important steps in this regard to achieve the intended goals’(Tehran
Nameh, 2019) . A deputy of the Technology and Innovation department at the Min-
istry of Communications during the recent Smart Cities Panel in Tehran (2019) stated
that ‘…we need a shared discourse to create Smart Cities’ (IRNA, 2019). Hashemi, head
of the Tehran City Council during the third Smart Tehran Conference and Exhibition
(2019), emphasized that data aggregation and management, open data platform, and
big data establishment are Tehran’s most important challenges in the path towards
becoming smart (Tehran Nameh, 2019). Hanachi (2018), Tehran’s Mayor, believes
that Smart Tehran can make a profound difference in the lives of its citizens through
the development of technological infrastructure and technological advances (The
Online Version of the Iranian Daily Hamshahri, 2018). Regarding the current situa-
tion in Tehran, he reported that: ‘In September 2017, in a poll conducted by Tehran mu-
nicipality, citizens introduced the two problems of air pollution and traffic as the main prob-
lems of the city’. In response to the question of what his plans to combat air pollution
were, he said ‘Reducing the share of private cars on the roads and developing the
public transportation system are our main goals’. It is mentioned in the Tehran
Smart program that ‘…the Smart City approach does not just mean hiring urban infor-
mation and communication technology (ICT) infrastructure, but six dimensions of smart
economy, smart mobility, smart environment, smart infrastructure, smart governance and
smart living will be noticed at the same time’ (The Official Website of Smart Tehran).
The Tehran Mayor emphasizes that the supreme leader advised him to use experts
in the city administration and preserve the cultural identity of Tehran (Tasnim
News, 2018).
Mashhad puts its main focus on smart citizens. The Mashhad Smart City portal
marks as its slogan ‘Smart City, Smart Citizen’. Currently, Mashhad profiles itself as
‘Mashhad; Smart City, city of hope and life’ (Official Portal of Mashhad Municipal-
ity). Managing Director of ICT Organization in Mashhad Municipality (2019) in the
annual report of 2018 states that in 2018, we witnessed positive developments to-
wards the Smart City, which mostly related to smart applications and services for
citizens. He also stresses smart mobility goals ‘...the issue of traffic is still at the top of
urban issues and is one of the most important concerns of citizens’ (Sobh Mashahd News,
118 Iranian Smart City Development: Vision and Expectations
5
2019). According to the city council announcement, the city of Mashhad also follows
smart economic objectives, including the development of regional-global competi-
tion and access to business opportunities.
Isfahan, with its historical, cultural, and tourist attractions, has a distinctive
look to be smart, sets its goal for smart citizen services, smart traffic and tourism,
and smart buildings. Isfahan Municipality’s Deputy Minister of Transportation and
Traffic announced that Isfahan’s smart traffic infrastructures were put into operation
at a cost of more than 402 billion Rials (Ettelaat News). Nonetheless, the most im-
portant project currently is the integrated spatial information system. In Isfahan mu-
nicipality, a headquarters was established for the Smart City under the direct super-
vision of the Mayor of Isfahan, whose task it is to implement a comprehensive plan
for the Smart City with the cooperation of the city council research center (Ham-
shahri, 2017). The director of Isfahan Municipality’s ICT Organization (2017) points
out: ‘Our movement is based on a 5-year plan, which is proposed as Isfahan’s 1400
vision program and as the municipality’s ICT representative’. According to this
plan, it intends to achieve the indicators of the Smart City in the next three years.
But certainly, what is planned in the ‘Isfahan 1400′ is still not what it takes to reach
the ideal Smart City. Arbabshirani also mentioned that, comparing Isfahan with Teh-
ran and Mashhad, it is clear that the former two were ahead of Isfahan in this field.
However, it is hopeful that, by using their positive and negative experiences, trial
and error in the Isfahan’s Smart program can be reduced (Hamshahri, 2017). Re-
cently, a member of Isfahan’s City Council (2019) stated: ‘Since 2016, Isfahan has es-
tablished its Smart City program but unfortunately, despite the great emphasis of this coun-
cil, the Smart City project in Isfahan is not going well and at present, Isfahan is not in a good
position compared to Tehran, Mashhad, and Shiraz in terms of Smart City indicators’(Isfa-
han City Council Official Website).
‘In Shiraz, we have tried to define our goals for the realization of the Smart City based
on both scientific definitions, and the situation and problems of our city, in order to draw a
better future for the city’, stated the managing director of Shiraz’s ICT organization.
He stressed that citizen welfare enabled by information technology was the highest
goal of Shiraz’s Smart City program, which was based on the sub-goals of having
clean air, a smart economy, smart transportation, preserving gardens, and greenery
of the city. He believed the lack of integrated urban management was the biggest
hurdle in the pathway toward developing the Smart City and pointed to the scat-
tered policies and activities of various organizations, such as healthcare and tele-
communications, noting that the municipality has a pivotal role to play as coordina-
tor and facilitator (Tamasha News). The head of the Smart and Information Technol-
ogy Commission of Shiraz City Council (2020) emphasized the smart economy as
one of the main goals of Shiraz’s Smart City program. She declared that, in order to
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 119
5
achieve a smart economy, eliminating unnecessary regulations and facilitating ad-
ministrative affairs for the private sector were important issues requiring serious
implementation (Iran’s Metropolices News Agancy, 2020).
Table 4 provides an overview of the current situation (A) based on the evidence
and observations presented in Section 4, as well as the expectations and goals of the
Iranian Smart Cities (situation B) to reveal the challenges and opportunities for a
transition from ‘A’ to ‘B’.
The challenges regarding technological readiness, however, are related to in-
sufficient infrastructures and unavailability of cutting-edge technologies, but, at a
macro level, these are intertwined with Iran’s diplomatic status in the world. The
issues of economic sanctions and exchange rates have reduced Iran’s ability, both
economically and in terms of trade, to transfer technology. Meanwhile, focusing on
knowledge transfer instead of technology transfer to foster innovation, supporting
start-ups, and focusing on the creativity-based solutions instead of high-tech solu-
tions may present opportunities that can boost core competencies for Iran’s Smart
City program. Generating knowledge and innovative ideas is not sufficient, how-
ever. Commercialization of creative solutions and scaling-up innovations are key to
success in developing smart solutions (El Abed et al., 2019). Providing a platform for
multi-stakeholder partnerships, citizen involvement, and partnership with aca-
demia have a critical role in reaching these goals (Geels, 2005). The result analysis
indicates that poor citizen participation is due to low trust and awareness levels. As
several officials state, the main concern among citizens in these four cities relates to
pollution and traffic congestion. The likelihood of changing the citizens’ view in fa-
vor of the Smart City is thus connected with it solving traffic and pollution problems
and may evoke an increase in participation.
The most significant difficulty in getting ready for becoming smart in Iran is
associated with the political context. Iran’s rigid political ideology and administra-
tive structure do not meet the standards for governing a Smart City. Lack of a com-
mon language for the Smart City, lack of a clear vision and roadmap for the Smart
City development, scattered policies and urban administration systems, and low
levels of citizen trust are Iran’s main challenges ahead to be politically ready for any
transition towards the Smart City. Utilization of open data policies and data sharing,
making reforms in government structures to achieve smart government, are sine qua
non’s to gain momentum for it. Smart Governance and developing Smart Govern-
ment applications can be considered as alternative possibilities to raise the level of
citizen satisfaction. Nonetheless, in my opinion, they should still consider that when
the government uses smart solutions and applications for practical issues perceived
as Smart City optimization of various goods and services, the likelihood of every-
body using it, too, will increase. But I fathom that as soon as it is more about strategic
120 Iranian Smart City Development: Vision and Expectations
5
and high-level aspects of policy, trust will be missing among many, and its ac-
ceptance is bound to remain lower. In short, it will probably work for non-politically
sensitive topics. As soon as people get the impression that this is tied up with pro-
moting the interests of the ruling class, they may reject it.
121
Table 4-Challenges and opportunities of Iranian cities for transition towards the Smart City.
RQs
Empirical Evidence and Observations
(Current situation 'A')
Expectations and
Goals
(Future situation
'B')
Challenges & Opportunities to a transition from 'A'
to 'B'
To what extent are Iranian cities
technologically ready for becoming
smart?
Existence of big data establishment is consid-
ering in all four cities,
Limited availability of sensors and actuator
equipped devices,
Notable improvements in terms of ICT Devel-
opment Index (IDI) in 2017,
IoT laws and regulations establishment for the
whole country,
Existence of data visualization platforms in
Tehran & Mashhad,
Establishing a cyber security framework is
considering.
General goals and
expectations: 'Sus-
tainability, Higher
quality of life
Reducing air pollu-
tion and conges-
tion,
Individual goals
and expectations:
Tehran; smart
economy, smart
mobility, smart en-
vironment, smart
infrastructure,
smart governance
and smart living.
Isfahan: smart citi-
zen services, smart
traffic and tourism,
and smart build-
ing.
Mashhad; smart
citizens, smart
Challenges: Insufficient infrastructures, Unavailabil-
ity of some emerging technologies, Restrictions on
buying and transferring technologies due to the sanc-
tions and raising exchange rate.
Opportunities: Focusing on knowledge transfer in-
stead of technology transfer, fostering innovation and
supporting start-ups, focusing on the creativity-based
solutions instead of high-tech solutions through citi-
zen participation.
To what extent are Iranian cities
socio
-
economically
ready for be-
coming smart?
Proper status in knowledge generation,
Organizing Smart City conferences and
events,
Existence of urban innovation centres in all
four cities,
Existence of science & technology parks and
incubators in all four case,
Low level of citizens' awareness of the Smart
City program in all four cases,
Perceived usefulness of the smart solutions
for traffic and pollution issues by citizens,
Challenges: Poor
citizen participation due to lack of
trust and low level of awareness, commercialization
of creative solutions, scaling-up the innovations.
Opportunities: Increasing knowledge and innova-
tion capacity, Expanding the positive view of citizens
towards the Smart City by solving traffic and pollu-
tion problems and then attracting the participation of
citizen.
122 Iranian Smart City Development: Vision and Expectations
5
RQs
Empirical Evidence and Observations
(Current situation 'A')
Expectations and
Goals
(Future situation
'B')
Challenges & Opportunities to a transition from 'A'
to 'B'
Citizens' image of their cities are not com-
monly positive.
economy, changing
the image of Mash-
had into a city of
hope & life.
Shiraz; having
clean air, smart
economy, smart
transportation,
preserving gardens
and greenery of the
city.
To what extent are Iranian
cities politically ready for be-
coming smart?
Having a rigid and narrow vision due to the
ideological and religious dogmas,
Multi-Level Governance structure with a cen-
tralized approach,
Lack of integrated urban management system
The low level of citizens' sovereignty,
The low level of Citizens' trust in the govern-
ment,
Lack of an integrated partnership platform,
Challenges: Lack of a common language for the
Smart City, Lack of a clear vision and roadmap for the
Smart City development, scattered policies and insti-
tutions, Gaining the trust of citizens.
Opportunities
: Utilization of open data policies and
data sharing to gain the trust of citizens, making re-
forms in government structures to achieve smart gov-
ernment, considering the Smart City
as a common
ground to improve international communication and
foreign relations.
123
In consequence, the ToC identifies technological, socio-economic, and political
interventions, as well as output, outcomes, and impact in order to become smart
(Figure 2).
In terms of technological resources, developing the infrastructures for smart
mobility is crucial because of the main urban issues that they face traffic congestion
and air pollution. Developing capabilities in cybersecurity, for which Iran already
has fine knowledge capacities, can be considered an asset in trading knowledge
transfer for technology transfer.
In the national political context, mapping a holistic vision for Smart City devel-
opment programs is essential. This requires support from both leaders and citizens.
At the same time, reforms in international relations and diplomacy are crucial role
to acquire necessary technologies and make exchange and global harmonization
possible. In the municipal context, changes from segregated urban management sys-
tems to more integrated ones based on decentralization and meritocracy are a must.
Last, but not least, making individuals and society at large ready to become
smart makes raising awareness a key consideration. Iran may consider to, if technol-
ogy transfer proves out of reach, promote knowledge transfer and innovation as its
main drivers in Smart City programs.
Figure 2-The infographic Theory of Change (ToC) for the readiness of Iranian cities
to become smart (developed by the author)
Theory of Change
IMPACT
LONG-TERM
OUTPUTS
INTERVENTIONS
Developing the infrastructures for
smart mobility, and increasing the ca-
pabilities in data visualization, and
cyber-security
Organizing
Smart City
events for citi-
zens
Interaction with stake-
holders and dev-
eloping a participation
platform
Sufficient infrastructures for develop-
ing Smart applications, increasing
knowledge capacity in data visualisa-
tion and cyber-security frameworks
Citizens’
awareness and
support
A holistic vision
for the smart city
development
The alliance between different actors
in the process of transition to pro-
mote a pathway
Increased
knowledge, in-
creased skills in ICT
The Iranian cities are ready to become Smart
Establishing a systematic
innovation model and for-
mulating innovation policy
based on that
The coordination of different actors and re-
sources to make the environment ready for
becoming smart
Providing entre-
preneurial infra-
structure and in-
novation environ-
ment
The smart city roadmap
An integrated urban
management system
based on decentrali-
zation and meritoc-
racy
Increased social
inclusion
The social and political environment enabled by tech-
nological infrastructures provides a fertile land for
planting/transplanting the smart city policy
Increased economic
competitiveness of
the cities
124 Conclusion
5
5.6. CONCLUSION
Through a descriptive-analytical approach, the present study sought to address
the following questions: How to determine whether cities are ready for a transition
into Smart Cities? What does an indicator system measuring Smart City readiness
look like? To what extent do Iranian cities meet the minimum requirements to be-
come smart?
The academic merit of the present study was to develop a framework for cities’
readiness to move toward a Smart City through an in-depth study of the existing
literature, and by measuring it in four large Iranian cities, to reveal the challenges
and opportunities ahead for them to become smart. In this study, I developed a The-
ory of Change (ToC) for the transition Iranian cities should go through.
The results of the analysis show that for several reasons the urban governance
model is the most important factor and key bottleneck for Iranian Smart City readi-
ness, making them miss vital opportunities. First, Iran shows significant advances
in ICT development, but for proceeding on that road, it needs to overcome the neg-
ative consequences of international sanctions. Big data availability and competen-
cies in cybersecurity are Iran’s strengths in ICT infrastructures required for Smart
City development. Second, as many studies stress the importance of citizen partici-
pation in transitions towards a Smart City, Iran needs its citizens’ trust and support
to be socially ready. My survey reveals that one of the most frequent ideas among
citizens’ conception of quality of life is connected to ‘safety’. Lastly, fundamentalist
religious considerations affect openness in policymaking negatively and lead to so-
cietal polarization. Rejection of political and religious opponents in governance bod-
ies make the development of a common language and getting citizens on board dif-
ficult. Organizing citizen awareness programs, government openness, and adopting
a bottom-up approach instead of imposing restrictions can be seen as potential so-
lutions for increasing civic trust and participation. However, to enable a bottom-up
approach for developing Smart Cities, Iran basically first needs reforms in its gov-
ernance structure. Starting Smart City experiments, like urban living labs, virtual
forums and meeting hubs, etc., also encourage citizens to participate in the Smart
City development process.
Tehran, Mashhad, Isfahan, and Shiraz have planned to become smart, but it
seems that their plans are neither comprehensive nor sufficiently systematic. They
seem to satisfy neither policymakers nor engineers. Iran requires policy and plan-
ning based on knowledge regarding the effects of information technologies on urban
structures. Compared to good practices of Smart Cities elsewhere (e.g., Amsterdam,
Barcelona, and Dubai), the Iranian cities need to provide a clear horizon and system-
atic plans through taking into account the variety of different aspects involved in
any Smart City program. Poorahmad et al. (2018), who conducted a study on the
Towards an Integrated Framework to Measure Smart City Readiness: The Case of Iranian Cities 125
5
necessities and requirements of Tehran to become smart, believe that many of the
urban issues in Tehran reside in the way the city is governed and the attitude of its
urban managers. They argue that the centralized and authoritarian planning style of
the city administration is increasingly linked to the tastes and wishes of city manag-
ers. In their view, the formulation and implementation of integrated policies, legis-
lation, and aligned vision have a significant role to play in Tehran’s Smart City ini-
tiative. Kazemian and Mirabedini (2011) stress the need for an integrated urban
management system and state that Tehran, with more than a hundred years of sys-
tematic urban management, due to the regime’s centralized approach, still lacks suf-
ficient autonomy in its decision-making process. Similarly, Isfahan and Shiraz have
no clear vision for their Smart City programs. They, too, require an integrated urban
management system, alongside the development of smart infrastructures (Taqvaei,
2015). Zarabi et al. (2019) mention the inequality in infrastructure development in
different neighborhoods of Isfahan. The same holds true for other Iranian large cit-
ies, particularly Tehran. Unequal access to urban services in poor and wealthy neigh-
borhoods is another characteristic of large Iranian cities which constitutes an obsta-
cle to becoming a Smart City. Mashhad, in comparison, has adopted a more system-
atic approach. But none of the four cities use a comprehensive roadmap for devel-
oping their Smart City. The leadership style and chain of command in Iran present
another challenge ahead in promoting systematic urban management. This chal-
lenge is more severe in Mashhad, which has conservative local rulers in place with
extreme religious perspectives.
The present study adds a few significant insights to the existing frameworks for
Smart City readiness in the academic body of knowledge. They contribute
knowledge on how cities that are just getting started can be prepared for their tran-
sition and start the Smart City development process. In the following chapter I dis-
cuss the mechanism that the Smart City initiatives can go through for transplanting
the good practices policy lessons in their own context.
127
6
INTRODUCING A CONCEPTUAL
FRAMEWORK TO ANALYZE
SMART
CITY POLICY TRANSPLANTATION
The contents of this chapter have been adapted from: Noori, N.; Hoppe, T.; De Jong, M.; Stamhuis, E.
Introducing a Conceptual Framework to Analyze Smart City Policy Transplantation. In Smart City: Strat-
egies for City Development and Innovation, 1st ed.; Philips, F., Oh, D., Eds.; World Scientific Publishing
Co (In press).
128 Introduction
6
6.1. INTRODUCTION
The explication of the relationship between technological advancements and
citizens' prosperity is a classic problem in urban policy studies (Krishna, Rama;
Kummitha, 2019). Smart City development, as many believe, is evolving as an urban
policy to find the balance between technology push, urban needs, citizens' desires,
and climate change generated by industrial and technological modernization (Ka-
miya, Marco; Guo, 2020; Woetzel et al., 2018). A drawback to the Smart City and
other techno-driven city approaches is that some believe that these cities need ex-
pensive technological infrastructure, which only rich and developed countries can
provide. Looking at the innovation social adoption curve shows that pioneers al-
ways spend more to adopt and apply a new technology. Developing countries usu-
ally begin adopting innovations in the second or third stages of the S-curve model
of the diffusion of innovation1 (where diffusion among the early majority is to take
place) (Rogers, 2003). The followers in the second and third stages can benefit from
learning from pioneers' experience to make diffusion-innovation processes less ex-
pensive and at the same time more cost-effective (Rose, 2002).
In the quest for Smart City development, numerous examples of ‘best practice’
have been created and circulated in national and international arenas. But based on
their cultural, political, ideological differences it is argued that the differences are so
great that public policy for cities should rightly be nation specific (Braun & Gilardi,
2006; True & Mintrom, 2001). However, I believe that notwithstanding the major
differences between different countries there are significant possibilities for
knowledge exchange, including the sharing of knowledge about best practices. Yet
despite the vast array of examples, demonstration projects, case studies and the like,
little is known about the ways in which best practices develop, are managed and
experienced, as well as their role in processes of policymaking. Therefore, it is essen-
tial that one becomes knowledgeable on how to apply lessons learned from leading
Smart Cities in other contexts. Learning from good practices is a perennial element
found in human developments with various significance and consequences.
In the case of urban development, the object is the city or town, and in my re-
search, the development of Smart City policies. Urban policy, as a general term, con-
cerns (local) government intervening in urban areas. The broad definition of urban
policy I adopt, is based on a definition by Blackman as stated in his book 'Urban
Policy in Practice' (2003, p. 5): ’Urban policy is mainly about the welfare of residents
in an urban society.’ This involves planning and delivering public services and sup-
porting the development of the local economy (Blackman, 2003).
The approach I intend to use in this study to develop Smart City policies is pol-
icy transplantation. Transplanting, as a general term, means moving something from
one location to another. A simple and well-known metaphor is the transplantation
introducing a conceptual framework to analyze Smart City policy transplantation 129
6
of flower bulbs. Meanwhile, a simple and well-known case of this metaphor is trans-
ferring tulip bulbs from Holland to transplant in another country. When the visitors
from around the world enjoy the beauty, and variety of tulip bulbs in Holland, they
are willing to bringing the bulbs to their local place to transplant. However, there
are several steps and considerations for the transplantation process to bring it to
fruition and have the blooms in another ground.
Consequently, in the present study, the bulb (object) for transplantation is 'ur-
ban policy' and more particularly 'Smart City policy.' Smart City policy transplanta-
tion aims to transform a city into a Smart City through transplanting policies from
donor cities. To ensure a successful transplantation of the bulbs, first the bulbs, and
then the ground must be prepared for proper transplantation in which the bulbs will
bloom. In chapter 4, I have analyzed four Smart Cities' good practices to classify their
development pathways, determining their various policies. The awareness of the
fact that lessons are not isolated or separated from the context where they are drawn,
and the necessity of checking the recipient ground guided me to consider policy
transplantation instead of other relevant concepts and discourses that concern the
moving of policy from one jurisdiction or city to another. Although, the term 'policy
transplantation' is rare in the academic literature; the notions of 'policy transfer',
‘policy mobility’, ‘policy diffusion’ and 'policy translation' are found in a number of
theoretical frameworks and policy practices (Benson & Jordan, 2011; Berry & Berry,
1990; Dolowitz & Marsh, 2000; Hettne, 2002; Sausman et al., 2016; Spicker, 2016).
This chapter first reviews the existing academic literature on the different dis-
course around moving policy, including policy oriented learning, policy mobility,
policy transfer, and policy translation (Dussauge-Laguna, 2012), taking insights
from that and introduce ‘policy transplantation’ as the main approach in this re-
search to move the Smart City policy from good practices in one place to Smart City
initiatives in another. The reason behind this is that all these concepts address mov-
ing policy and show considerable overlap in meaning while also emerging each time
for a specific purpose, from a different perspective and using different methodolo-
gies (Dussauge-Laguna, 2012). By mapping the policy transplantation concept in the
Smart City context, the present study attempts to fuel a debate on knowing ‘how to
do’ policy transplantation into Smart City initiatives. Consequently, the main re-
search question is: What is the mechanism of policy transplantation for Smart City
initiatives? Addressing the main question requires us to give a response to the fol-
lowing sub-questions:
• What does policy transplantation mean in the domain of Smart Cities?
• What does a theoretical framework for policy transplantation look like,
more particularly in the domain of Smart Cities?
130 Theory and practice associated with policy travel
6
• And to what extent is it possible to apply this policy transplantation frame-
work to the context of Smart City practice?
In Section 2, the theoretical approach will be introduced in which policy trans-
plantation is rooted and from which it has emerged. In the next section, we explain
the framework for the Smart City policy transplantation analysis. Section 4 presents
the policy transplantation framework, thereafter, the reader is guided on how to ap-
ply the framework to facilitate Smart City policy transplantation. And finally, in Sec-
tion 5 a conclusion is presented.
6.2. THEORY AND PRACTICE ASSOCIATED WITH POLICY TRAVEL
Adopting Smart City good practice is an example of what is called lesson draw-
ing or policy learning in the academic literature. The term ‘learning’ here refers to
the acquisition of new knowledge generated by cognition of the practices, that af-
fects identifying new ideas and fundamental beliefs for policy formulation (Rose,
2002). Therefore, learning could just as likely lead to policy innovation or termina-
tion of existing policy considered as outdated. Policy learning is then associated with
learning from a public program in another polity that focuses on a similar societal
problem in need of a solution (Robertson, 1991). New knowledge is then derived
from the evidence of experiences that address mitigating or solving this problem;
i.e. ‘lessons’ learned (Hall, 1993).
In this context, Rose (1994) presented a scheme for learning policy lessons; i.e.
‘lesson-drawing’. He characterizes this as a future-oriented approach to improve
policy, in contrast with ‘trial-and-error’ which is considered more as a backward
approach. This also is known as an open approach to transfer the knowledge on how
other countries deal with similar issues. Rose (2005) offers ten steps that must be
taken to draw lessons, and some helpful advice on how to go about what he calls
‘instrumental learning’ from other countries. He suggests that policy makers do not
expect to find ‘one-size-fits-all’ solutions, though, and stresses instead to focus on
‘where we look for a lesson’, ‘when we do it’, and ‘how well we learn’ as the critical
challenges of this learning process (Rose, 2002).
De Jong (2009), argues that there are two main weaknesses in Rose's ten steps;
presenting a linear sequence which is neither empirically nor prescriptively desira-
ble, and his rejection of the importance of historical and cultural and specific insti-
tutional factors. Based on what De Jong (2009) points out, Rose’s steps are useful,
but one should realize that they present merely a rationalist perspective of decision
making. Reality is more complicated though. Decision-making processes are com-
plex and local institutions have more impact on policy transfer or adoption than
Rose indicates and allows for.
introducing a conceptual framework to analyze Smart City policy transplantation 131
6
May (1992) suggested to consider ‘the basis for learning’, ‘the level of conscious-
ness need learning be for it to be considered genuine’, and ‘the object of learning’,
for policy-oriented learning (ibid.). In her conceptual model, she distinguishes pol-
icy learning from political learning. Sabatier (1988) on ‘policy-oriented learning’ ar-
gues that learning varies consisting of improving understanding of a concept, refin-
ing understanding of a concept, and identifying and responding to challenges vis-à-
vis a certain concept (ibid.).
Policy learning consists of instrumental policy learning, and social policy learn-
ing. Whereas, political learning pertains to strategy for advocating a given policy
idea or problem that focuses on the policy process and requires awareness of politi-
cal prospects and factors that affect them. Meseguer (2006) on the other hand be-
lieves that the learning approach varies regarding the subject (who learns?), and the
object of learning (about what?) (ibid.).
Inspired by Rose’s steps on lesson drawing, Dolowitz & Marsh (2000) presented
a framework for learning from abroad through policy transfer. In their framework,
policy transfer is understood as a process by which ‘knowledge about how policies,
administrative arrangements, institutions and ideas in one political setting (past or
present) is used in the development of policies, administrative arrangements, insti-
tutions and ideas in another political setting (Dolowitz & Marsh, 2000). Here ‘learn-
ing’ can also be related to policy transfer.
However, this concept is analytically distinct. Placing policy transfer into the
conceptual framework by Dolowitz and Marsh (2000) can advance one’s under-
standing of concepts such as the motivation of policy makers for transferring policy
(ideological or practical), different actors involving in different stages of the policy
transfer process, and the type of transfer (e.g., copying, by emulation, or via inspira-
tion). Dolowitz and Marsh’s framework is mainly developed for transferring poli-
cies (i.e., goals, content, and instruments), programs, and negative lessons – i.e. do-
mestic or from abroad -, and first starts with whether transfers are voluntary (i.e.
lesson-drawing) or coercive (i.e., power and influence) (Dolowitz & Marsh, 2000).
Based on this, nine main categories of political actors are discerned addressing who
are engaged in the policy transfer process: elected officials, political parties, bureau-
crats/civil servants, pressure groups, policy entrepreneurs and experts, transna-
tional corporations, think tanks, supra-national governmental and nongovernmen-
tal institutions and consultants.
Wolman (1992) suggests that site-visits are considered a proper way to collect
more information of programs and practices elsewhere, and to assess or evaluate
these situations(ibid.). For Evans (2009) policy transfer is a cross-cultural transfer of
knowledge from one political system to another one (ibid.). Dussauge-Laguna (2012)
holds that not all scholars agree on whether ‘policy transfer’ is actually the most
132 Theory and practice associated with policy travel
6
adequate term to use and that is the reason that some prefers to use alternatives such
as ‘policy borrowing’, ‘policy mobility’, and ‘policy transplantation’ (Dussauge-La-
guna, 2012).
Even though the concepts of policy transfer, policy diffusion, and policy bor-
rowing have existed in the policy travel literature for a long time, the notion of policy
mobility has emerged for a better understanding of policy movement (Gulson et al.,
2017). Policy transfer is understood as a process of knowledge transfer between po-
litical systems in different jurisdictions, like countries. Policy diffusion on the other
hand, is comprehended as a process by which policy choices in one political system
affect policy choices in another (Obinger et al., 2013). Nonetheless, the cornerstone
of policy mobility is different, as it is situated in earlier work on policy transfer and
diffusion (McKenzie, 2017). Here, moving policy is considered as a contribution to
economic, social, and political relations. Therefore, the term movement is not only
referring to a certain policy traveling but also to flows of ideas, people, and even
technology that surround it (McKenzie, 2017). The aim is to pay attention to the com-
munity and materials that affect the formulation and moving of policies.
Peck and Theodore (2010) argue that mobile policies quite often travel as selec-
tive discourses, and do not in the form as complete policy packages. They consider
policy mobility as a complex non-linear process in which in the destination of policy
travel it can be mutated, and in alternative forms that compare the original form in
the initial point of travel (McCann & Ward, 2014; Peck & Theodore, 2010). This can
eventually trigger policy innovation.
Mintrom, (1997) defines policy innovation as a policy that is new to a political
setting adopting it (ibid.). Jordan and Huitema (2014) define policy innovation as the
responses to ‘non-policy’ triggers seeking to generate societal or technological
change (ibid.). In this study, following Sabatier (1988), I define policy innovation as
a new policy on an issue formulated based on improving and refining understand-
ing of the related concepts around the issue, or identifying and responding chal-
lenges to the concepts.
Baker and Temenos (2015) hold that the knowledge of policy mobility not only
deals with the practices and processes of mobilizing policy but also with territorial-
izing. They identify three theoretical orientations in the urban policy mobility liter-
ature, including: redevelopment of cities through global relational connections, re-
production of political-institutional settlements, and the role of materials (e.g., pol-
icy documents, press releases, websites, and manuals), and techniques (e.g., perfor-
mance indicators, audit regimes) in policy mobility processes (Baker & Temenos,
2015). Robinson (2015), focusing on the movement of policy, drawing attention to
the foreground of arriving policy in the local contexts and actors (Robinson, 2015).
introducing a conceptual framework to analyze Smart City policy transplantation 133
6
There is also a more fluid approach to moving policy; this concerns policy trans-
lation that mainly addresses that policy evolves during the movement. The policy
translation discourse then refers to the emergence of the linguistic mutation of policy
ideas or documents when they arrive in a new political setting to be the right shape
for the new context (Jiao & Boons, 2017). Jiao and Boons (2017) characterize policy
translation as a dynamic process of policy formation by actors, from emerging policy
ideas to materializing them into linguistic objects and practices. For instance, when
applying the discourse to the Smart City context, policy translation begins with
Smart City policy emerging in a given political context. This could mean that when
something emerges in context A, the words are tracked and transferred by actors
from one political setting to another; for example, via an inter or supra national body
like the EU. Next, often academic communities begin to investigate and discuss the
emerging policy in the international events and conferences. This attracts the atten-
tion of the urban policymakers who seek to transfer Smart City policy to their own
local context based on good practice elsewhere. When a Smart City concept ends up
in the (local) context B, the likelihood is high that it ends up having a different mean-
ing. So, it basically comes down to translating the concept of Smart City from A to
B, although the meaning is not the same. Furthermore, the translation can get con-
nected with other terminologies in the new context and affected by the local context
it may become quite different from its original idea. It is almost like translating texts
from one language to another: the translator's (i.e. a certain actor) ideology and the
source language influencing the translation of the original idea (Ow Yong & Cam-
eron, 2019).
De Jong (2002; p4) introduced the general idea of institutional transplantation
to bring improvements to the host society. Borrowing successful institutions from
somewhere else is seen as a mean to speed up a certain desirable development, or to
achieve it at lower cost. The term transplantation in this sense also has been used in
the field of comparative law as ‘legal transplantation’ (Watson, 1993). De Jong &
Stoter (2009) propose a number of design heuristics for good institutional transplan-
tation, from their perspective institutional transplantation is aimed not only at real-
izing legality but also at achieving acceptance of policy initiatives among recipient
countries or institutions (De Jong & Stoter, 2009). They are:
• Strengthening the position of international proponents of change;
• Avoiding ‘xeroxing’ taking hold – i.e. using multiple models and going from
general to the specific;
• Hiring and using proactive institutional entrepreneurs;
• Recognizing and using windows of opportunity when they appear;
• Accounting for cultural and administrative differences and similarities;
• Using only neutral or positive symbols.
134 A framework for the Smart City policy transplantation analysis
6
According to these six heuristics, one needs to consider the needs and wants of
key players in the process of lesson drawing trying to convince them that it can po-
tentially strengthen their position.
Inspired by De Jong’s (1999) idea of institutional transplantation, I applied it in
the context of Smart City policy. So, I use the term policy transplantation since I look
at the policy as a set of actions, programs, and tools for developing a Smart City.
Policy transplantation in this sense can be understood as a policy learning approach
for drawing lesson from abroad in which pays special attention to the context and
environment. In terms of the learning mechanism it is subject to coercion, since coun-
tries need to consider the supranational regulations (Obinger et al., 2013). Nonethe-
less, the emulation as the learning mode must be avoided. This refers to the ambition
of political actors to conform to international trends and to belong to an international
norm-based community (Obinger et al., 2013). Policy transfer then is also a part of
this transplantation process. However, it does not reveal the entire policy transplan-
tation process for Smart Cities. Policy mobility can also be seen as an application of
policy transfer which concerns not only the policy travel but also involves the origin,
destination and accommodating the policy travel. In addition, it can also be viewed
as a type of policy diffusion that promotes various/multiple policy options.
In conclusion, I consider the insights from different theoretical perspectives sur-
rounding policy transplantation that can clarify the characteristics of policy move-
ment. Combining insights from the literature review I conducted with De Jong and
Stoter’s (2009) six heuristics of institutional transplantation, provides one more in-
sight into political and institutional aspects that are relevant to the process of trans-
planting transferred policies (De Jong & Stoter, 2009). Although De Jong and Stoter
(2009) argue that only neutral or positive symbols should be used, analyzing failures
can also be important to have a better understanding of which policies do not result
into meeting the intended goals, and forecast policy rejections. This can help to learn
about the circumstances in which policies fail (when implemented).
6.3. A FRAMEWORK FOR THE SMART CITY POLICY TRANSPLANTATION
ANALYSIS
The literature review reveals that various aspects of policy learning are at play
in the process of policy transfer. Both individuals and firms who are directly and
indirectly involved in the traveling process play a crucial role. Their roles include
influencing different stages of the policy traveling process; from emerging a new
policy idea and make it attractive to move, to determining candidates as ‘best prac-
tices’, and encouraging others to borrow through their policy advice (Dolowitz &
introducing a conceptual framework to analyze Smart City policy transplantation 135
6
Marsh, 2000). The modality of the travel itself as a dynamic process has been inves-
tigate in numerous studies.
However, relatively few of these studies investigate the process of ‘planting’
the transferred policy in the new context directly (Dolowitz & Marsh, 2000; Rose,
2002; De Jong & Stoter, 2009) ; that is, they describe the transfer of ideas or policies
between countries but do not clarify the mechanism of implementing the policy after
arriving in a new political setting. Nonetheless, institutional transplantation and le-
gal transplantation have been studied and analyzed. There are few studies that chal-
lenge the mechanism of institutional transplantation (De Jong & Stoter, 2009), which
is presented by the authors in rather simplistic ways that are too far away from com-
plex reality. Therefore, I suggest developing a comprehensive conceptual frame-
work taking a systems perspective. Employing the policy transplantation frame-
work into a more comprehensive and systemic conceptual framework has the po-
tential to advance one’s understanding of Smart City policy travelling considering
the origin and the destination of travel and the action afterward to adopt and imple-
ment the policy. The intention behind the notion of policy transplantation is to con-
sider accommodation alongside the policy travel. When a given policy lands in a
new destination the host is required to have the accommodation ready, so that adop-
tion of the policy takes place smoothly. To clarify this and visualize the conceptual
mechanism, I place Smart City policy transplantation within a comprehensive con-
ceptual framework. This has the potential to assist Smart City researchers in exam-
ining the mechanism of policy transplantation for Smart City policy borrowing and
help policy makers and practitioners to evaluate the effectiveness of the mechanism
on production and reproduction of the Smart City development idea.
6.4. THE SMART CITY POLICY TRANSPLANTATION MODEL
This theoretical framework I present in this chapter is inspired by the metaphor
of bulb transplantation to develop the conceptual model of the Smart City policy
transplantation mechanism. To map the concept of Smart City transplantation I use
existing lesson drawing, policy transfer and technology transfer concepts and frame-
works as inputs into the construction of the proposed conceptual model. The inputs
stem from the literature review presented in the previous. The conceptual model
focuses on the process of policy transplantation as a circular process starting from
formulating a vision to have the Smart City policy in place. The model presents the
process of policy transplantation consist of four phases. The four phases (as shown
in fig.1) pertain to: (1) preparing the recipient for transplanting smart policies; (2)
formulating the lessons learnt from the good practices; (3) transferring the policies,
and eventually (4) adopting the policies and forming them in the proper shape to be
transplanted.
136 the Smart City policy transplantation model
6
Figure 1- The Smart City Policy Transplantation Process: Phasing
The Smart City transplantation process brings into a political setting the aware-
ness of an emerging policy with the potential to offer solutions for urban problems.
The Smart City solutions and showcases around the world provide the impetus to
borrow the policies and launch the Smart City program. Once the smart profile man-
ifests itself in the recipient context, the intended goals and visions are proclaimed.
The goals and visions as well as having a consistent policy in place aligning with the
overarching policies signal a desirable starting point for the recipient preparation.
This preparation also entails a readiness assessment of the recipient context. In phase
2, the recipient looks outside for good practices to explore policies, programs, net-
works and connections and learn from them. The next step (phase 3) is to transfer
the lessons learnt from good practices (both successes and failures). Consolidation
and embedding the results of phases 1 and 2 form the backdrop for policymakers to
select the policies to adopt and transplant in the local context. The model also shows
various stages and activities related to the four phases. There are six stages to take
to complete this four-phase process. The stages are shown in the grey boxes in Figure
2, while the white boxes present the activities related to each stage. And the arrows
make the key interconnections between the activities visible. The following sections
elaborate this.
Smart city policy (vision, pathway,
programs)
Credible branding (local, international)
Readiness assessment
Good practices analysis and lessons
formulation
Transference (mechanisms, actors,
tools)
Transplanting mutated policies
Phase 1: Recipient preparation
Phase 2: Learning from good practices
Phase 3: Transferring policies from
good practices to the recipient
Phase 4: Policy adoption and trans-
plantation
137
Figure 2-The Smart City Policy Transplantation Mechanism: phases, stages, activities, and interconnections.
Smart city policy
(vision, pathway, pro-
grams)
Credible branding
(local, international)
Readiness assessment
Good practices analysis
and networking
Transference
Transplanting mutated
policies
Policy makers selecting policies, policy adoption and locali-
zation
Transferring policies (ideas, goals, visions, beliefs, institu-
tions, programs, instruments, tools)
Technological environment
● ICT infrastructures
● Data infrastructures
● Data management capabilities
Politics and governance
● Leadership
● National po
licy and governance
● Municipal policy and governance
Socio-economic environment
● Education and innovation
● Awareness
● Perceived usefulness
● Mentality and values
Transfer mechanisms
● Actor
-interactions
● Creating platforms and events to
support transfer
● Provide evidence, knowledge,
and experience on experiments that
worked well.
● Organize conferences, symposia,
excursions and field trips to good
practice projects.
● Institutional interactions based i
n
policy learning
Good practices and experiments
● Vision, goals
● The development pathway and
its Inputs, throughputs, outputs,
design variables, policy tools that
work.
Policy change
● Innovation policy; management
change
● Innovation policy; progr
am
change
● Innovation policy; paradigm shift
● The overarching policy
● Positive feelings
● Uniqueness or distinctness
● Different stakeholders
● Connecting past, current profile
d f t biti
Emulation
Inspiration
Copying
Policy and issue networks
● Sharing good practices and insights on sup-
portive policy instruments/tools.
● Forming advocacy coalitions to advocate and
lobby for smart cities.
● Agency to get Smart cities on political and pol-
icy agendas
● Supranational funding and programs (e.g. EU)
138
6.4.1. PHASE 1: RECIPIENT PREPARATION FOR SMART CITY TRANSPLANTATION
In the initiation phase, Smart City initiatives begin to brand themselves as
‘smart’, after considering the Smart City as their profile to deal with urban issues
and making improvements in the urban environment. This is the first action in the
Smart City development process. Many projects may, however, be stuck in the Smart
City branding stage because they encounter problems that have to do with short-
term political or economic reasons. Nevertheless, this branding has to be credible for
long-term goals in terms of transition towards a Smart City. The study presented in
Chapter 2, identified the six factors that contribute to the credibility of city brands.
They include: generating feelings of loyalty; facilitating the development of an over-
arching strategy or policy; evoking positive feelings; demonstrating uniqueness or
distinctness; allowing for different yet non-contradictory messages to various stake-
holders; and logically connecting past heritage, current profile, and future ambitions
(Noori & De Jong, 2018).
After deciding that the transition into a Smart City is desirable, local and inter-
national credible branding is the first step to joining policy or issue networks that
advocate Smart City adoption. Branding can be of use here. A credible brand of
‘smart’ generates a dynamic among policy actors and influences the socio-economics
environment through raising the awareness of the potential actors to encourage
them to participate from the early stage of the developing pathway. As soon as the
smart profile of a city is established as part of a credible brand, assessing the readi-
ness (as it is investigated in the previous chapter) to explore the possibility of be-
coming smart and being prepared to implement policy that support the transition
towards becoming a Smart City is the next stage. This requires monitoring and pe-
riodical evaluation. The monitoring process needs to reflect both technological and
non-technological readiness assessment. This also consists of socio-economic and
political readiness (Noori, Hoppe et al., 2020).
6.4.2. PHASE 2: LEARNING FROM GOOD PRACTICE
In the quest of Smart City development in the global arena, several indices and
rankings (e.g., the Global Smart City ranking issued by Juniper Research in 2016; the
Smart City Index issued by Ernst and Young, in 2017; the global Smart City Dis-
course Network issued by Joss et al. in 2017) have been put into place to evaluate the
Smart City practices (and performance), and facilitate determination of good or best
practices through which to promote policy transfer and learning (Bulkeley, 2006).
Bardach (2008) underlines the adjective ‘best’ conveys the impression that a practice
should be better than many others, and therefore rare (Bardach, 2008). Nonetheless,
the term ‘good practices’ is assigned to programs and actions which were taken to
introducing a conceptual framework to analyze Smart City policy transplantation 139
6
implement a policy or project and achieve certain intended goals (Boehnke et al.,
2019). Understanding good practices based on information from technical reports,
policy documents, projects and programs descriptions is however not sufficient for
Smart City practitioners and policymakers to accumulate the knowledge and formu-
late the lessons to transfer, though. A good practices analysis to explicit the
knowledge from their experiences about the Smart City development process and
actions considering contextual influences in a systematic approach facilitates lesson
– and hence, policy-formulation and inspiration (Bulkeley, 2006). The Input-output
(IO) model of Smart City development process (presented in Chapter 2) which pro-
vides a systematic approach to analyse the (good) practice in Smart City develop-
ment. Comparing resources, governance, design and the implementation of various
Smart City (good) practices reveals different pathways for Smart City development
(Noori, Hoppe et al., 2020).
6.4.3. PHASE 3: TRANSFERRING POLICIES FROM GOOD PRACTICES TO THE
RECIPIENT
Actions related to the steps mentioned above have been elaborated in previous
chapters (Noori, De Jong et al., 2020; Noori, Hoppe, et al., 2020; Noori et al., 2020;
Noori & De Jong, 2018). At this point, the result of the good practice analysis can be
transferred to the recipient in the form of political and policy lessons, including
ideas, visions, beliefs, institutions, programs and policy instruments for Smart City
development. Sharing good practices and insights on supportive policy instru-
ments/tools often takes place via transnational networks; i.e. via policy or issue net-
works. These networks form vessels that facilitate the trans-national or trans-re-
gional diffusion of discourse and policy. This is evidenced in a wide variety of policy
domains like gender equity or climate change (True & Mintrom, 2001; Kern & Bulke-
ley, 2009). One way of facilitating policy diffusion of Smart Cities is by offering sup-
portive platforms that also provide funding for organising innovative Smart City
experimentation and pilot demonstrations in cities. For example, in its framework
programs the European Union has tenders in place that provide funding to and al-
low cities to experiment with Smart City policy concepts (European Commission,
2019; Noori, Hoppe, et al., 2020).
Seeking how this transfer process takes place, Tamtik and Sa´ (2014) identify
the mechanisms on the individual and organizational level. At the individual level,
the transfer occurs through actors’ interactions. This can for example, take place dur-
ing events organized or facilitated by transnational networks advocating Smart City
development. Actor interaction leading to knowledge accumulation shifts the policy
beliefs of decision-makers and encourage them to pick ideas (Tamtik & Sá, 2014).
140
6
Along with social interaction among individuals, interaction can also take place at
the institutional level. Government officials are not the only actors to transfer poli-
cies. Supranational agencies (provisioning supranational funds and programs e.g.
EU), subnational governments, political parties, non-governmental organization,
private companies and media agencies are the key actors to form the policy and issue
networks to transfer Smart City policies (De Jong, 2003).
6.4.4. PHASE 4: ADOPTION OF SMART CITY POLICY BY THE RECIPIENT AND
TRANSPLANTING POLICIES
Policy improvement forms the driver for governments and institutions to seek
for the new policy ideas and beliefs. As Sabatier (1988) argues, both state and non-
state actors, and their interactions in socio-political formal and informal events, are
the main vehicles for policy transfer (Sabatier, 1988: p.136). Tamtik and Sa´ (2014)
consider another mechanism as an almost automatic process through the dissemi-
nation of knowledge, evidence, and experiences regarding a new policy. This mech-
anism takes place when a government or organization seeks for the evidence and
experience on how particular policy problems have been solved and disseminated
as good examples (Tamtik & Sá, 2014). Regarding the so-called the degree of transfer
by Dolowitz and Marsh (2000) and modes of lesson drawing by Rose (1991), three
forms of transfer (copying, emulation, and inspiration) are demonstrated in the
model I suggest based on these two approaches. Since Rose’s lesson-drawing frame-
work focuses on policy programs, it defines the mode of copying as entirely adop-
tion of a program from another political system. Nonetheless for Warren (2017), ad-
aptation is a different level of policy transfer from direct copying which is connected
to the hybridization and emulation (Warren, 2017). Rose (1991) argues that emula-
tion happens when a program is adopted but with considering the local circum-
stance, and hybridization is to combine elements of programs from two different
places (Rose, 1991). Dolowitz and Marsh (2000) consider these learning modes as
four different degrees in policy transfer that pertain to (i) copying, as a direct and
complete transfer; (ii) emulation, as the transfer of the ideas behind the policy or
program; (iii) combinations, which refers to the combination of several different
policies; and (iv) inspiration, as driver of policy change in one political system in-
spired by policies in another political system (Dolowitz & Marsh, 2000).
When the policies arrive in the recipient context, the results from the prepara-
tion stage form the input for selecting policies based on local circumstance. Results
from credible branding practices, including overarching policy, future ambitions
and goals, and respecting uniqueness and distinctness, can be used as guidelines for
selecting and formulating policies (Noori & De Jong, 2018). The outcome from the
introducing a conceptual framework to analyze Smart City policy transplantation 141
6
readiness assessment analysis also reveals policy preferences (Noori, de Jong, et al.,
2020). Selecting and localizing policies are expected to be conducted by different
stakeholders involved in the credible branding process and the actors involved in
the transfer (Borrás, 2011). This entails the mutation of transferred policies which
leads to so-called policy innovations. In a sense, innovation in policy can be seen as
either incremental (improvements and adjustments) or radical (fundamental
change) innovation based on how big and how novel the particular change is. The
incremental innovation in policy takes place when the stimulus is the change in man-
agement or programs and the radical innovation involves a paradigm shift (Sabatier,
1998). Borrás (2011) believes that innovation in policy correspondingly necessitates
innovation-related techniques such as research program evaluation, constructive
technological assessment, or technological forecasting (ibid.). Eventually, in the
Smart City domain policy innovations may contribute to forming and reforming pol-
icy and its development pathway in the governance and political system of the re-
cipient jurisdiction.
6.5. CONCLUSION
There is a growing number of cities in the world nowadays claiming to be in
the process of becoming Smart Cities. But there are vast ambiguities pertaining to
how they initiate this process, which policy choices they have to make, and the ef-
fects and impact this will create in urban practice. Policy makers and practitioners
in urban planning and city development often find it hard to separate the corn from
the chaff, and to envisage where to begin formulating Smart City policy and pro-
grams. Most of the time there is confusion and even contradiction when a task force
starts working on a Smart City development program. This is often related to a lack
of understanding into the various goals Smart Cities can have, and how programs,
and visions lead to intended outcomes. Using a learning process by policy transfer
avoids city official having to reinvent the wheel. Here, having an evidence-based
approach in place is important. This avoids falling back on trial and error, which can
be painful and often costly.
In this chapter I introduced the conceptual notion of policy transplantation to
the domain of Smart Cities. Based on a literature study and interpretation, I devel-
oped a theoretical framework that provides more insight in the complex process of
policy transplantation of Smart City concepts from one city to another. The literature
overview mapped different perspectives and concepts surrounding the theoretical
concepts of policy-oriented learning and policy travel and presented policy trans-
plantation as an approach in the context of Smart Cities. Based on this I introduced
142 Conclusion
6
a comprehensive framework which makes it possible to further understanding and
map the comprehensive process of Smart City policy transplantation. This would
create more understanding on how to implement the policy transplantation mecha-
nism in the realm of Smart Cities.
Notes
1
The S-curve model of the diffusion of innovation shows the speed of adoption of vari-
ous innovations in the social system. In this model Rogers argues that the innovation
adopters are classified into five categories: innovators, early adopters, early majority, late ma-
jority and the laggards. Rogers’s model shows that innovators are the first 2.5% of adopters,
the early adopters group are 13.5% of adopters in the second stage, the majority of early
adopters include 34% of the adopters in the third stage while late in the majority comprises
the following 34% in the fourth stage of adopting the innovation and the remaining 16% have
been the laggards. See for more details in the article by Rogers et al. (2003).
143
7
CONCLUSIONS & FUTURE
PERSPECTIVES
144 Conclusions
7
7.1. CONCLUSIONS
The evolution of the Smart City concept from the early phase (technology-
driven by companies) until now shows that a lot of progress has been made in both
research, development and implementation in practice (Ismagilova, Hughes,
Dwivedi, & Raman, 2019). In 2008, a debate on the ‘Smart City’ evoked as urban
planning built on high-tech ICT infrastructure for economic growth (Hollands,
2008). Furthermore, the Smart City concept has evolved from a predominantly
techno-driven city profile (i.e. digital, intelligent, ubiquitous and information cities)
to a more integrative profile that also also takes citizens and broader urban interests
into account, while at the same time dealing with the criticism of merely being
techno-centric (Huovila et al., 2019; De Jong et al., 2015).
In recent years there has been a lot of attention to the ambiguity of the Smart
City concept, leading Komninos and Mora (2018) to conclude that it needs more clar-
ification (Komninos and Mora, 2018). One of the main reasons is that there are mul-
tiple stakeholders involved in Smart City development processes with each of them
having their own approach based on their interests and expectations (Anthopoulos
et al., 2015; Dameri & Benevolo, 2016). Business firms expect financial benefits,
whereas governmental organizations have broader political and social concerns.
Moreover, environmentalists wish to minimize the ecological impact, and citizens
are worried about their safety, privacy and well-being (Kuk & Janssen, 2011; Meijer
& Bolívar, 2016; Yigitcanlar & Kamruzzaman, 2018).
More recently scholars have started modelling exercises in a more systematic
way to cover different aspects of the Smart City concept (Chourabi et al., 2012; Lee
et al., 2014; Neirotti et al., 2014). Most conceptual models of Smart City development
reflect different dimensions of the Smart City and all are primarily descriptive in
nature and offer few clues as to how to flesh out Smart Cities in practice. Besides,
various conceptual models that have been developed mostly look at the Smart City
as a phenomenon of urban policy or city branding rather than as an urban develop-
ment process.
Since still there is no best model or clear conceptual definition and defined do-
main of application for ‘Smart City’, learning processes from good practices policies
help initiators to make better choices for Smart City policies and strategies based on
their own pathway and intended outcomes. Analyzing good practices to draw les-
son also helps those Smart Cities good practices to improve their policies over time
through making the Smart City concept, its domains, outcomes and the way their
policy works in practice more transparent. But this learning process requires a tool
to analyze, monitor and benchmark Smart City development process in good prac-
tices. Based on this, lessons can be drawn. Next, based on these lessons a learning
process mechanism can be established and/or elaborated. Most importantly, during
Conclusions & Future Perspectives 145
7
the learning process the complexity of the context should be considered as well. To
address this issue, the present dissertation investigates what local governments that
are just getting started in developing and governing their own Smart City can do to
reach their intended goal of becoming a Smart City? And how do they manage the
process of achieving this, while taking into account their specific circumstances in-
cluding the policy context? Given that one of the most important approaches in ur-
ban policy often is drawing lessons and transplanting concepts and policy from suc-
cessful examples (i.e. good and ‘best’ practice), how can this approach help cities in
this regard that seek to identify good practice and adopt their likely successful ap-
proaches locally? These fundamental questions lead to the main question of this re-
search: ‘How to initiate and manage the process of transforming a city into a Smart
City?’
This main question is answered step by step through five sub-questions, which
are elaborated in previous chapters. Their answers are summarized in the following
sections of this chapter.
7.1.1. SUB-QUESTION ONE: HOW DO CITIES ENGAGE CITY BRANDING PRACTICES
WHEN FACING ECOLOGICAL MODERNIZATION
? TO WHAT EXTENT DO THEY USE
‘SMART’ IN THEIR BRANDS AND HOW?
City branding is an increasingly practiced in cities around the world with a
strong drive to engage in urban (re)development through enhancing ‘ecological
modernization’. For example, largest cities of Iran have all begun to venture into
making profiles of what they think they are or would like to be. However, some of
the adopted city branding strategies lack sophistication. I examined what indicators
can be used for evaluating the credibility of city brands and applied these to Iran’s
fifteen largest cities (Table 1). After offering brief descriptions of the generic features
of each of these cities, I mapped the use of city brand identities and popular city
labels related to ecological modernization and analyzed the credibility of their city
branding practices.
146 Conclusions
7
Table 1-Criteria for credible city branding.
Credibil-
ity As-
pect/City
Generat-
ing Feel-
ings of
Royalty
Facilitat-
ing Over-
arching
Strategy
Evoking
Positive
Feelings
Demon-
strating
Unique-
ness
Allowing dif-
ferent, Non-
Contradictory
Messages
Logically Con-
necting Past,
Present and
Future
City A
City B
…
…
Etc.
Based on the findings, I distinguish five types of cities which the cities with
credible brands belonging to the type of ‘Cities eager to adopt the complete package
of religious, cultural, and modern technological amenities, and want to share in
high-tech development boosting the future economic profile of their city. This ap-
plies to the cities of Tehran, Mashhad, Isfahan, Shiraz and Qom’. I explained what
makes this type of branding more credible in their use than alternatives. Generally
speaking, the most credible branding practices facing ecological modernization per-
tains to ‘Smart’. Tehran, Mashhad, Isfahan, Shiraz, Urmia, and Qom are the largest
Iranian cities, and are using a ‘Smart’ label in their profile. The result from examining
the brand credibility shows that Tehran, Mashhad, Isfahan, and Shiraz use the most
credible brand of ‘Smart’ (Table 2). They facilitate the development of ‘Smart’ policy
aligns with the national program which appears in both brand identity and position.
As the results in Chapter 2 show, their brands of ‘Smart’ demonstrate their unique-
ness and distinctness and their ‘Smart’ profile covers all environmental, economic
(technological and industrial), and cultural aspects.
Table 2 - Evaluating city brand credibility of Iranian large cities.
Credibility
Aspect/City
Facilitating
Overarching
Strategy
Demon-
strating
Uniqueness
Allowing Different,
Non-Contradictory
Messages
Logically Con-
necting Past, Pre-
sent, and Future
Tehran
high
high
high
high
Mashhad
Medium
high
High
high
Isfahan
High
high
High
high
Shiraz
High
high
High
high
Conclusions & Future Perspectives 147
7
7.1.2. SUB-QUESTION TWO: WHAT DOES A CONCEPTUAL MODEL REPRESENTING
DIFFERENT DOMAINS OF THE
SMART CITY LOOK LIKE?
While many national and local governments in the world are placing their bets
on Smart City development in countering challenges such as climate change, air pol-
lution, and congestion, few know exactly how to develop them in practice. A high
and rising number of publications has appeared addressing the concept of ‘Smart
City’, but not many address its implementation. I developed an Input-Throughput-
Output (IO) model (Fig. 1) that aims at increasing a conceptual understanding of the
Smart City by describing its various facets and helping policy makers and analysts
to make better informed design choices. The different domains of Smart City devel-
opment process are categorized into resources (inputs), dynamics capabilities and
governance (throughputs), and smart applications and externalities (outputs & out-
comes). The IO model is developed focusing on a city in an institutional environment
in which a local administration wishes to develop (itself into) a Smart City, and
where policy makers draft and implement Smart City development plans.
The idea is that the various facets of the Smart City development process can
be transformed into sorts of inputs, throughputs and outputs. Clearly, there are sev-
eral factors that affect this development process, including: contextual factors, and
drivers (technology push and needs to solve urban problems). For such a technolog-
ically driven city, technology push along with urban needs would be the main driver
of innovation (Brem & Voigt, 2009). In fact, by promoting innovation in the urban
context they can enable the Smart City development process. When many actors are
involved in the process and their interactions vary across time and over policy is-
sues, the process is complex in terms of decision and making policy implementation
(Cairney, 2012). Smart City programs deal with different actors and various interests
(Joss et al., 2017). Context obviously matters and political, legal, institutional and
cultural contexts all affect the Smart City development process. The key throughputs
of the process – i.e. Smart City capabilities - allow for the modification and alignment
of resources (Gupta et al., 2015).
148 Conclusions
7
However, covering all aspects of Smart City and generalizing the Smart City
concept in one integral model is not possible. This systematic IO model can provide
practitioners and policy makers the required know-how to implement it. Using this
model allows them to further their conceptual understanding of Smart Cities, envis-
age design choices they will face during planning and implementation, and help
them to understand the impact of these choices. Using the IO model is illustrated by
introducing the case of ‘Smart Dubai’. This illustrative case provides insight into
how our IO model can be used to explain what the essential resources for Smart City
initiatives are, and how Smart Dubai has provisioned them, which facets are at play
in each stage of the Smart City development process, what key output facets of Smart
Dubai are, and to what extent they were pursued in the Smart Dubai case. The re-
sults show that Dubai has a specific type of Smart City development process, which
can arguably be characterized as mainly a top-down process supported by visionary
Figure 1
- The IO model for the Smart City development process
Dynamic throughput:
• Data and infrastructure asset
management
• Knowledge and innovation
management
• Financial asset management
Governance and Leadership:
• Intergovernmental relations
• Coordination among actors
• Leadership capabilities
Smart city development process
Resources (input):
• Human resources and
entrepreneurship
• Data
• Modern ICT infrastruc-
ture
• Financial resources
Overarching policy, decisions, and attitudes
Applications (output):
• Mobility
• Energy
• Healthcare
• Smart government
• Smart citizens
Externalities (outcome):
• Environmental sustainability
• Economic sustainability
• Social sustainability/quality
of life
Conclusions & Future Perspectives 149
7
leadership and active branding strategy and actions. The case shows the importance
of having a vision in place to support the development process. Overall, the IO
model provides enhanced understanding of Smart City development processes. It
can be used to analyse complex Smart City development or implementation pro-
cesses. Alternatively, it can be used in decision making processes. Finally, I suggest
to expand it, and use it to design choices for benchmarking Smart Cities develop-
ment process.
7.1.3. SUB-QUESTION THREE: HOW DO SMART CITIES DIFFER FROM EACH OTHER
IN TERMS OF THEIR RESOURCES GOALS AND DEVELOPME
NT PATHWAY?
Policy makers, city planners, and practitioners appear to have quite different
expectations from what Smart Cities can offer them. This has led to the emergence
of different types of Smart Cities and pathways of development. In a follow-up
study I expanded the IO model into a framework (Table 3) to introduce the Smart
City design choices for each facet in the IO model as a benchmarking tool to identify
different pathways of Smart City development.
Table 3-The design variables and indicators of the Smart City development pro-
cess.
Smart City Attributes
Design Variables
Indicators (Presence of)
Inputs
HR and Entrepreneur-
ship
Educating and training
people
Supporting and strengthening uni-
versities and research centres (HR1)
Transferring (attracting)
educated and skilled
people
Launching knowledge transfer pro-
jects (e.g., scholarships, sabbaticals)
(HR2)
Nurturing the innovation
environment
Specific policy in place to promote
innovation (HR3)
Attracting innovative
companies
Supporting and encouraging pro-
grams for innovative companies (Sci-
ence and technology parks, free
zones) (HR4)
Information and Com-
munication Technology
(ICT) and Data
Data aggregation
Big data establishment (D1)
Data processing
Data science centres (D2)
Data real-time analysis
Data visualization (D3)
Financial resources
Supra
-national and na-
tional investment
Supra-national and national Smart
City
development policy and budget
(F1)
Local government invest-
ment
Smart City profile and allocated
budget (F2)
150 Conclusions
7
Public–private invest-
ment
Collaboration with the private sector
(F3)
Foreign investment
International brand and investors
Throughputs
Governance
Governance structures;
technocratic, citizen
-cen-
tric, socio
-technical, hier-
archical, surveillance
Role of the government and deci-
sion-making process (G1)
Actors are involved and engaged
(G2)
Knowledge and Innova-
tion management
Open innovation
Living Labs, idea-sharing champions
(KI1)
In
-house R&D
Innovation Centres, Smart City R&D
department (KI2)
Data management
Establishing a data au-
thorization
Data Laws (DM1)
Open/closed/ or shared
data platform
Data accessibility (DM2)
Financial management
Redirecting funds away
from inadequate, ineffi-
cient urban infrastruc-
ture development
Alignment of the urban master plan
with
Smart City policies (FM1)
Raising
private funds
Having a collaboration platform
(FM2)
Leadership
Leadership styles
Vision creation and the bigger image
(L1)
Motivating and empowering people
(L2)
Collaborating with people and influ-
encing them (L3)
Outputs
Smart Mobility
Smart transportation in-
frastructures
Smart (sensor and actuator
equipped) roads and traffic lights,
smart parking, bicycle routes (SM1)
Smart public transporta-
tion
Interconnected public transporta-
tion, smart vehicles, information ap-
plication (SM2)
Smart private transporta-
tion
EVs (Electric Vehicles), autonomous
driving, car-sharing (SM3)
Smart energy
Renewable energy
Stationary energy use to be supplied
from renewable energy sources (SE1)
Energy-efficient build-
ings
Building regulations, energy certifi-
cates (SE2)
New technology for utili-
ties
Smart grids, smart meters (SE3)
Conclusions & Future Perspectives 151
7
To answer the research question: When comparing a selection of Smart City
projects, how can we classify pathways for their development? We do this by using
a cross-case research design of four cities to explore commonalities and differences
in development patterns. I used the IO model to retrieve which design variables are
at play and lead to which output. The IO model is applied to four cases which are
considered as good Smart City practice in this research. The four cases pertain to the
following Smart City projects: Smart Dubai, Masdar City, Barcelona Smart City, and
Amsterdam Smart City. The four cases have a number of commonalities while they
are different in other like governance structures, political system, and culture. The
analysis shows that the Smart City development pathway in Amsterdam is based on
a business-driven approach that puts innovation at its core. For Masdar technologi-
cal optimism is the main essence of the pathway, while social inclusion is the main
focus of Barcelona Smart City. Finally, visionary ambitious leadership is considered
the main driver for Smart Dubai. Based on these insights, a classification for Smart
City development pathways is established (Table 4). Following the design choices
made for each facet of the Smart City development process, the four cities have dif-
ferent fundamental values and drivers that influenced the pathways they took for
Smart City development. This led me to formulate the lessons from their experiences
Smart health
Smart health monitoring
systems
Remote health monitoring, mobile
health monitoring, or wearable
health monitoring (SH1)
Smart health manage-
ment and information
applications
Mobile applications for medication
information, weight management,
information regarding hospitals and
clinics (SH2)
Smart citizens
One
-
way communication
A participation platform for data
sharing (SC1)
Two-way communica-
tion
A participation platform for idea
sharing (SC2)
Co-creating and co-de-
signing
A participation platform for coopera-
tive policies (SC3)
Smart governance
Smart administration
Redesigning norms based on smart
solutions (technologies) (SG1)
Smart interaction
Participation and collaboration via
social media and social networking
(SG2)
Smart security and safety
Using smart devices and data analyt-
ics for surveillance (SG3)
Smart policies
Using big data analytics for decision-
making (SG4)
152 Conclusions
7
of choosing specific design variables which result in a specific pathway leading to
achieving expected outcomes as well as unexpected outcomes (especially in the case
of Masdar).
Table 4- Smart City development pathways (Amsterdam, Barcelona, Dubai, and
Masdar).
Case
Main Driver
(Core Element)
Development
Path
Key Features
Amsterdam Innovation
Innocratic (start-
up and busi-
ness-driven)
Competition, entrepreneurial In-
novative, Bottom-up approach
Barcelona Inclusion
Sociocratic (Par-
ticipation-
driven)
Democracy, Citizen empower-
ment through technology and
citizens’ data sovereignty Partic-
ipatory, Co-creation
Dubai
Visionary-ambi-
tious leadership
Aristocratic
(State and ser-
vice-driven)
Being first, being best, Top-
down Happiness, government
services, branding
Masdar
Technological op-
timism
Technocratic
(Investment and
branding-
driven)
Visibility, lighthouse projects,
branding
7.1.4. SUB-QUESTION FOUR: HOW TO DETERMINE WHETHER CITIES ARE READY
TO TRANSITION INTO
SMART CITIES?
I answered these questions through introducing an indicator system to measure
and assess Smart City readiness (Table 5).
Table 5- The Smart City Readiness framework.
Technological Readiness
Smart City Attributes Design Variables Indicators (Presence of)
ICT and Data re-
sources
Data aggregation
Big data establishment
Sensors and actuator
equipped devices, CCTVs
& cameras
Connectivity
ICT Development Index
(IDI)
Data processing Data science centers
Conclusions & Future Perspectives 153
7
Data real-time analy-
sis
Data visualization plat-
forms
Data management ca-
pabilities
Establishing a data
authorization
Data Laws
Security
Establishing a cyber secu-
rity framework
Socio-economic Readiness
Factors Definition and Operationalization
Education
Number of universities and research centers
Knowledge transfer and knowledge sharing pro-
grams
Innovation
Specific policy in place to promote Smart City inno-
vation
Supporting and encouraging programs for innova-
tive companies (science and technology parks, free
zones, etc.)
Awareness
Level of citizens’ awareness of the Smart City pro-
gram in their city
Level of citizens’ awareness of the Smart City con-
cept and technologies
Perceived usefulness
Level of perceived usefulness of the smart solutions
for the city’s challenges by citizens
Mentality and values
Citizens’ opinion about a Smart City
Citizens’ image of their cities
Citizens’ different ideas of quality of life
Political Readiness
Political Context Definition and Practices
National policy and
governance
National leadership
Government structure, governance arrangements,
policy networks
Rules, laws, legal and regulatory reforms
Legitimacy, transparency, and trust
Municipal policy and
governance
Local leadership
Partnerships with industry, academia, and citizens
Providing a platform for multi-stakeholder partner-
ship
Smart City innovation clusters and networks
154 Conclusions
7
I analysed Smart City initiatives in Iran as case studies and used the indicator
system to do this. I present and reflect on how cities in Iran explore the possibility
of becoming smart and prepare themselves to begin implementing to transition into
Smart Cities. The findings of the analysis reveal that the most significant difficulty
in Iran is associated with the political context. The changing urban governance
model is the most important factor in Iranian Smart Cities’ readiness. Utilization of
open data policies and data sharing, as well as making reforms in government struc-
tures are all considered a sine qua non to gain momentum. Based on the results of
the empirical analysis a Theory of Change is developed to address the cities’ tech-
nological, socio-economic, and political readiness vis-à-vis the desired transition
(Fig. 2). The framework for measuring Smart City readiness and the Theory of
Change provide practical guidelines to developing systematic roadmaps for initiat-
ing implementation of the Smart City policies. The Theory of Change (ToC) is devel-
oped based on the interventions which result in the outputs and long-term outcomes
that Iranian cities need to enhance for being ready to become smart. The long-term
outcomes address impacts that relate to knowledge capacity related to ICT, eco-
nomic competitiveness, social inclusion, and the organised social and political envi-
ronment that influence Smart City policy implementation processes.
Conclusions & Future Perspectives 155
7
Figure 2-The Theory of Change (ToC) for the readiness of Iranian cities to become
smart
7.1.5. SUB-QUESTION FIVE: HOW CAN SMART CITY POLICIES BE TRANSPLANTED
FROM CITIES HOSTING GOOD PRACTICES TO CITIES WHERE
SMART CITY
INITIATIVES ARE TO TAKE PLACE
?
To address this question, I developed a theoretical framework using theoretical
insights from a literature study and insights from empirical studies I conducted pre-
viously (see the previous chapters). What I have done so far for transplanting Smart
City policies from good practice projects to smart initiatives includes studies on re-
cipient preparation for Smart City transplantation and learning from good practices
analysis. Adding insights from policy and issue networks (i.e. transnational net-
works that support policy transfer), transferring mechanisms, and transplanting ap-
proaches, at this step enabled me to sketch a comprehensive image of the compre-
hensive process of Smart City transplantation (Fig. 3). The greatest thing that the
Smart City Transplantation framework can do is to show how the Smart City policy
transplantation process can be implemented in a comprehensive conception as a
Theory of Change
IMPACT
LONG-TERM
OUTPUTS
INTERVENTIONS
Developing the infrastructures for
smart mobility, and increasing the ca-
pabilities in data visualization, and
cyber-security
Organizing
Smart City
events for citi-
zens
Interaction with stake-
holders and dev-
eloping a participation
platform
Sufficient infrastructures for develop-
ing Smart applications, increasing
knowledg
e capacity in data visualisa-
tion and cyber-security frameworks
Citizens’
awareness and
support
A holistic vision
for the smart city
development
The alliance between different actors
in the process of transition to pro-
mote a pathway
Increased
knowledge, in-
creased skills in ICT
The Iranian cities are ready to become Smart
Establishing a systematic
innovation model and for-
mulating innovation policy
based on that
The coordination of different actors and re-
sources to make the environment ready for
becoming smart
Providing entre-
preneurial infra-
structure and in-
novation environ-
ment
The smart city roadmap
An integrated urban
management system
based on decentrali-
zation and meritoc-
racy
Increased social
inclusion
The social and political environment enabled by tech-
nological infrastructures provides a fertile land for
planting/transplanting the smart city policy
Increased economic
competitiveness of
the cities
156 Conclusions
7
roadmap for Smart City initiatives to transplant the policy including knowledge on
processes and the governance setting enabling Smart City policy implementation.
The framework represents the initiation of the Smart City transplantation process,
the activities are taken, and the expected outcomes. The roadmap of policy trans-
plantation process in the presented framework also indicates that the various activ-
ities are intertwined within an issue network.
Figure 3- The Smart City Policy Transplantation framework.
It indicates that the transplantation process occurs when the cities begin to
have a Smart City development policy in place and profile themselves as ‘smart’.
City branding practices can be seen as the motives for moving towards this sort of
development process. When the brand is considered credible, the motives of becom-
ing ‘Smart’ are transformed into being willing to develop towards a Smart City. Pro-
moting a credible brand is the beginning of entering to the Smart City networks and
communities. Interaction with other experienced and leading members (are known
as good practices) and actors inspire the newcomers to learn from them. The Smart
Smart city policy
(vision, pathway, programs)
Credible branding
(local, international)
Readiness assessment
Good practices analysis
and networking
Transference
Transplanting mutated
policies
Policy makers selecting policies, policy adoption and localization
Transferring policies (ideas, goals, visions, beliefs, institutions, pro-
grams, instruments, tools)
Technological environment
● ICT infrastructures
● D
ata infrastructures
● Data management capabilities
Politics and governance
● Leadership
● National policy and governance
● Municipal policy and governance
Socio-economic environment
● Education and innovation
● Awareness
● Perceived
usefulness
● Mentality and values
● Attract investment
Transfer mechanisms
● Actor
-interactions
● Creating platforms and events to sup-
port transfer
● Provide evidence, knowledge, and ex-
perience on experiments that worked
well.
● Organize conferences, sy
mposia, ex-
cursions and field trips to good practice
projects.
● Institutional interactions based in pol-
icy learning
Good practices and experiments
● Vision, goals
● The development pathway and its In-
puts, throughputs
, outputs, design varia-
bles, policy
tools that work.
Policy change
● Innovation policy; management
change
● Innovation policy; program change
● Innovation policy; paradigm shift
● The overarching policy
● Positive feelings
● Uniqueness or distinctness
● Different
stakeholders
● Connecting past, current profile and
future ambitions
Emulation
Inspiration
Copying
Policy and issue networks
● Sharing good practices and insights on supportive
policy instruments/tools.
● Forming advocacy coalitions to
advocate and lobby
for smart cities.
● Agency to get Smart cities on political and policy
agendas
● Supranational funding and programs (e.g. EU)
Conclusions & Future Perspectives 157
7
City initiatives start to learn from different sources (e.g., from actor interactions, dif-
ferent sources of evidence, reports, or policy documents) and transfer the ideas,
goals, vision, beliefs, institutions, programs, and instruments or tools in various
ways (i.e. via copying, emulation, or inspiration). These transferred policies will be
mutated in their local context under their overarching policy, and will affect their
socio-economic, political, and technological environments. This mutation leads to
either radical or incremental policy change that eventually contributes to the Smart
City policy adjustment and modification. This also includes adaptation of multiple
existing sectoral regulatory and policy frameworks.
In closing, all above responses provide frameworks, conceptual models and
empirical findings that enabled the author to answer the main question of this re-
search: ‘How to initiate and manage the process of transforming a city into a Smart
City?’. The present study answers this question in two phases: initiating the Smart
City policy and program, and then governing its further development process. In
the first phase, the author considers the beginnings of a transition to becoming a
Smart City based on the postulates of EM theory and the emerging policy direction
based on it. In this regard, city branding practices can be seen as the earliest activity
of initiating a developmental pathway towards a Smart City. The importance of con-
sidering this point as a starting point becomes even more apparent in light of the
fact that many studies into urban branding suggest that governments sometimes
seek short-term branding benefits rather than long-term development plans. Alt-
hough this study does not contradict the merits of such short-term goals as such, its
main focus is obviously on implementing the Smart City policies and actually realize
the desired goals, including improving the quality of life and sustainable develop-
ment of an urban area. This requires fruitful use of the concept of ‘credible branding’.
Therefore, through developing credible branding criteria, the way to initiate a tran-
sition to a Smart City with a higher likelihood of achieving its desired goals and
promises is mapped.
In response to the other part of the main question, successful governance of a
Smart City, given the current challenges governments face, achieving a clear and
pragmatic understanding of this development process is in order before it can be
implemented. A firm grasp of the various facets of the process and using those as a
common language between policymakers and practitioners is then due. Choosing
the appropriate policies and programs for each city able to meet its needs and be
accepted given its circumstances is another factor conducive to a successful Smart
City program. Learning, drawing inspiration and transferring lessons from existing
good practices is a well-known academic field and governance method, which itself
requires insight, creativity and sensitivity to context to be conducted successfully.
158 Policy recommendations
7
7.2. POLICY RECOMMENDATIONS
Targeting policymakers, in this section, I present some recommendations re-
garding Smart City development. Firstly, to those cities who are just getting started
to become ‘Smart’ I suggest paying attention to their branding practices and consider
the credibility factors proposed above to make a strong start in branding themselves
in line with their long-term objectives. A credible Smart City branding practice in-
troduces a city as a candidate for Smart City policy adoption based on proven good
practices obtained from elsewhere and then flesh it out with full participation from
among the policy actors and networks around the municipal government. This also
influences the local environment by raising awareness among actors and encourage
them to participate in transferring the Smart City policy from other polities (Oha-
nian, 1990). The brand credibility increases the likelihood of being accepted by the
community and allowing the various actors access to the relevant information, pol-
icy instruments and tools, lobbies, funds, etc. (Erdem et al., 2004; Aitken & Campelo,
2011). In terms of citizen engagement, a credible brand which generates feelings of
loyalty and logically connects past heritage, current situation and hopes for futures
has a higher potential to attract citizens. In any kind of innovation, especially inno-
vative policies, resisting acceptance is a major challenge. A credible brand through
allowing for different yet non-contradictory messages given to various stakeholders,
can target different interests and turn resistance into companionship and participa-
tion (Baker, 2012).
Secondly, for Smart City initiatives I recommend following orders to assess
their readiness both technologically and non-technologically. Readiness assessment
is very important from two angles; (1) it reveals the challenges and opportunities
ahead in the transition pathway, and (2) defines a clear horizon of what needs to be
done to succeed on this pathway. This can assist them to develop a Theory of Change
and a roadmap for transition toward becoming ready to initiate their Smart City
development process. Studies and available evidence show that the greatest atten-
tion of governments in assessing their own readiness so far has been on technologi-
cal readiness (Berst et al., 2013). But the centrality of the human factor in the new
generations of Smart Cities has become indisputable so that assessing the non-tech-
nological readiness obtains more and more attention (Achmad et al., 2018).
Thirdly, I suggest Smart City policymakers to start using the IO model both for
implementing and evaluating their Smart City development process. The model can
help policymakers (1) ensure that the required resources have been made available,
(2) help determine priorities for developing smart applications based on their in-
tended goals in meeting the needs and challenges aligned with the overarching pol-
icies, and (3) establish the capability of transforming resources into those applica-
tions while anticipating the emergent externalities. Adding a pragmatic view to
Conclusions & Future Perspectives 159
7
Smart City development enhances the likelihood of that the entire development pro-
cess is indeed completed and diminishes chances of encountering unexpected com-
plications along the way (Yigitcanlar, et al., 2018).
Fourthly, both policymakers and practitioners need to be aware of various de-
sign choices for each of the Smart City facets to make the right choices based on their
respective needs, available resources, and visions. I suggest to use the design varia-
bles and indicators of the Smart City development process proposed in Chapter 4 of
the present study. This can be done first for considering various design choices in
planning their own Smart programs and second, as a tool to analyze relevant Smart
City good practices and their developmental pathways.
Finally, to use experiences of success and failure from others, learn from good
practices, access to the accumulated knowledge inside the issue network, transfer
and adopt the Smart City policy, I propose to use the Smart City policy transplanta-
tion framework to avoid merely copy-pasting policies or isolated policy transfer. En-
tering the policy and issue networks is an essential requirement for Smart Cities in-
itiatives for sharing good practices and insights through forming advocacy coali-
tions to advocate and lobby for Smart Cities, and Smart Cities agencies. Organizing
conferences, symposia, excursions and field trips to good practice projects facilitate
the policy transfer and creating platforms and events supports the transfer. Last but
not least, I encourage policymakers to consider having a clear vision for the Smart
City development as the central point that prevents them from unguided deviations
and translate this vision into a common language for all stakeholders.
7.3. SCIENTIFIC CONTRIBUTION
The added scientific value of this research mostly concerns a contribution to the
academic body of knowledge on Smart Cities in general and governance and policy
of Smart Cities in particular (Hollands, 2008; Komninos & Mora, 2018; Chourabi,
Nam, & Walker, 2012; Yigitcalar, 2015; Kuk & Janssen, 2011; Joss et al, 2019; Negro
et al, 2015; Kitchin, 2019). Considering the Smart City discourse as one of the main
city branding practices and the importance of brand credibility, this doctoral study
has contributed to the emerging body of knowledge on city brand credibility by de-
veloping a methodology to measure this among cities. In this regard, the study first
contributes to the body of knowledge on city branding practices to fill the
knowledge gap in terms of a methodology and criteria to map and evaluate credible
city branding practices. The proposed methodology provides new insights on how
to credibly brand as ‘Smart’ as the first step towards a Smart City development.
The other piece of added value to the academic literature on Smart Cities (Yig-
itcalar, 2015; Yigitcalar, 2016; Anthopoulos, 2015; Negro et al, 2015) concerns clarifi-
cation of the of Smart City concept, reducing ambiguities in it, and making it more
160 Scientific Contribution
7
pragmatic by translating a number of its characteristics into inputs, outputs, and
throughputs. This was done by modelling the Smart City development process as a
specific application of soft system theory (Checkland, 1999). The proposed (IO)
model of Smart City development (presented in Chapter 3) as proposed in this doc-
toral study aims to provide better understanding into the Smart City development
process for researchers, policymakers, and practitioners. It does so by providing by
providing a general model which helps communication between these user groups.
Perceiving Smart City development as a process that needs to be governed (An-
thopoulos, 2015; Neirotti et al., 2014; Lee et al., 2013; Chourabi et al., 2012; Hollands,
2008; Joss, 2015; Joss et al, 2019), the (IO)model elaborates existing concepts in the
Smart City governance literature.
Developing the (IO) model into a framework for Smart City design offers a
range of various choices for designing a Smart City development process according
to the specific needs, resources, and intended goals of policy makers and city plan-
ners. On the one hand, this design framework can be used to analyse good practice
development pathways and learn from them. On the other hand, this framework can
be applied to the Smart City practices to assess or evaluate specific Smart City de-
velopment pathways.
Another significant scientific achievement of this doctoral study concerns the
development of a framework for readiness assessment of cities, and its application
to a real-life case. This illustrates the use of the framework, and enabled develop-
ment of a Theory of Change. To date there was no such comprehensive readiness
assessment framework covering both technological and non-technological (pertain-
ing to) aspects in the existing literature so far. The proposed Smart City readiness
assessment framework classifies non-technological factors into socio-economic and
political factors and operationalizes the indicators to measure them.
The final innovative contribution of this study to science is applying the termi-
nology of ‘policy transplantation’ inspired by the stream of comparative law and
policy transfer studies. Considering Smart City adoption and development in terms
of urban policy, this doctoral study contributes to policy studies and political science
by integrating insights on policy diffusion, transfer and transplantation (Benson &
Jordan, 2011; Berry & Berry, 1990; Dolowitz & Marsh, 2000; Hettne, 2002; Sausman
et al., 2016; Spicker, 2016) into a novel, integrative, comprehensive framework for
Smart City policy transplantation. The Smart City policy transplantation framework
in the present study maps the mechanism for traveling and accommodating policy
ideas from the donors to recipients in the Smart City context. This study provides a
comprehensive framework for municipal governments eager to initiate Smart City
programs, learn from practices, transfer the lessons, make the context ready, and
Conclusions & Future Perspectives 161
7
finally adopt, adapt and adjust their Smart City policies to fit the local context and
meet the specific local ambitions.
7.4. LIMITATIONS
An important limitation in examining brand credibility is that two more sub-
jective and/or emotional factors determining credibility were not included in the
study for lack of measurability. Future research may well introduce viable ways of
including these factors in methodologically-sound ways and build connections with
images of the city as held by outsiders.
In developing the IO model, there is a concern regarding the linearity of the
model, which will be taken up in our future research as well by introducing a new
version of the IO model using a neural network modeling approach that will shed
light on the interconnections between different facets of the Smart City development
process.
Limitations to the comparative study of good practice Smart City projects per-
tain to the case selection, which included only European and Arab countries, and
excluded other ones, like pioneering Smart Cities in North America and East Asia.
Because of this bias in the case selection, it is conceivable that potentially more path-
ways exist in other cities around the world.
Another important limitation is related to the Smart City readiness assessment
study that the cultural factors affecting social readiness were not included for lack
of measurability. Future research may cover the these and other relevant factors to
make the framework even more encompassing. The path dependency in the Smart
City transplantation framework can be seen as another limitation to this research.
There are more ways for cities to adopt Smart City principles than only looking for
good practice elsewhere and adopting the policies to transplant them in their own
context. The alternative pathways can be also reflected in future research.
Lastly, language barriers are the other limitations to conduct a cross-national
study since for this research I read some sources in the original languages i.e. Farsi,
Arabic and translated them into English.
7.5. FUTURE PERSPECTIVES
The present study offers insights that can inform future research agendas on
Smart City development. First, I suggest that future studies on different Smart City
cases across the world (for instance, China and the United States of America) can
provide further detail in the use of the Smart City design choices framework and
discover more pathways. Investigating multiple Smart City cases with contextual
differences—most importantly with variation in cultural and political systems - can
162 Future Perspectives
7
reveal new aspects of development pathways and their relative success and failure.
Moreover, I would like to draw the attention to a current development in Smart City
concepts and pathways; i.e., from a predominantly technology-driven approach to-
wards the emerging approach pertaining to ‘inclusive Smart Cities’. Taking this shift
into account can provide more insight into forecasting and back-casting (Vergragt &
Quist, 2011) as the next steps in Smart City development. This would eventually
benefit local policy makers in developing local Smart City policy, roadmaps and
projects.
Learning from the experiences of leading cities running good practice projects
is a common way to formulate and implement Smart City policies in Smart City in-
itiatives through drawing positive and negative lessons. I expect this trend to con-
tinue in the future and hope to contribute my share to improving this very practice.
This aspect of urban development starts with the rise of Smart Cities as a bridge
between economics and technology. The evolution path of Smart City development
indicates that it will contain attention to both strong technological stimuli, but also
to the human factor, which is arguably the core of its development.
Nowadays, many good practices such as Barcelona, Amsterdam, and Vienna
highlight ‘social inclusion’ in their vision in Smart City development (Smart City
World Congress, 2019). In a similar vein, the ‘Open Innovation approach’ is taking
the place of technology push as the core enabler of the Smart City development pro-
cess (Yun & Liu, 2019). As the results of this doctoral study revealed local govern-
ments have different foci that are central to their Smart City development pathways.
Social inclusion is the focus of Barcelona Smart City, Amsterdam Smart City has its
goal to be an inclusive city, and Dubai Smart City puts the vision as the happiest city
for its citizens. This proves that cities that have leading Smart City projects running
desire for a citizen-centric approach and becoming an inclusive city. The challenge
ahead is that can an inclusive Smart City be realistic or will be a utopian Smart City
that policymakers are dreaming for. To clarify, many aspects of a citizen-centric and
inclusive Smart City such as citizens co-creation, citizens’ participation in decision-
making, open data policies and regulations, citizens’ data ownership, their aware-
ness and duties, privacy and transparency issues, need to be investigated.
163
A
Appendix
A.1. A
164 A
A
Table A1 -SPSS statically analysis_ correlation between input and output indicators
Educating
& training
people
Transferrin
g
(attracting)
educated
and skilled
people
Nurture
the
innovation
environme
nt
Attracting
innovative
companies
Data
aggregatio
n
Data
processing
Data real-
time
analysis
Supra-
national
and
national
investment
Local
governmen
t
investment
Public-
private
investment
Foreign
investment
Smart
transportat
ion
infrastuctur
es
Smart
public
transportat
ion
Smart
private
transportat
ion
Renewabl
e energy
Buildings
energy
efficiency
New
technologi
es for
utilities
Smart
Energy
average
Smart
health
monitoring
systems
Smart
health
manageme
nt and
information
application
s
Smart
health
average
One-way
communic
ation
Two-way
communic
ation
Co-
creating
and co-
designing
Smart city
average
Smart
administrat
ion
Smart
interaction
Smart
security
and safety
Smart
policies
Smart
governanc
e average
Smart
Mobility
Average
Pearson
Correlation
1 0,816 0,577 0,577 -0,333 0,333 -0,577 0,577 -0,577
1,000
**
.
b
0,522 0,577 0,816 0,577 -0,333 -0,577
.
b
0,000 -0,333 -0,333 0,333 0,870 0,522 0,577
-1,000
**
-1,000
**
.
b
0,333
-1,000
**
0,522
Sig. (1-
tailed)
0,092 0,211 0,211 0,333 0,333 0,211 0,211 0,211 0,000 0,239 0,211 0,092 0,211 0,333 0,211 0,500 0,333 0,333 0,333 0,065 0,239 0,211 0,000 0,000 0,333 0,000 0,239
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,816 1 0,000 0,707 0,000 0,000 -0,707 0,000 0,000 0,816
.
b
0,000 0,000 0,500 0,000 0,000 -0,707
.
b
0,000 0,000 0,000 0,000 0,426 0,000 0,000 -0,816 -0,816
.
b
0,000 -0,816 0,000
Sig. (1-
tailed)
0,092 0,500 0,146 0,500 0,500 0,146 0,500 0,500 0,092 0,500 0,500 0,250 0,500 0,500 0,146 0,500 0,500 0,500 0,500 0,287 0,500 0,500 0,092 0,092 0,500 0,092 0,500
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,577 0,000 1 0,000 -0,577 0,577 0,000
1,000
**
-1,000
**
0,577
.
b
,905
*
1,000
**
0,707
1,000
**
-0,577 0,000
.
b
0,000 -0,577 -0,577 0,577
,905
*
,905
*
1,000
**
-0,577 -0,577
.
b
0,577 -0,577
,905
*
Sig. (1-
tailed)
0,211 0,500 0,500 0,211 0,211 0,500 0,000 0,000 0,211 0,048 0,000 0,146 0,000 0,211 0,500 0,500 0,211 0,211 0,211 0,048 0,048 0,000 0,211 0,211 0,211 0,211 0,048
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,577 0,707 0,000 1 0,577 0,577 0,000 0,000 0,000 0,577
.
b
0,302 0,000 0,707 0,000 0,577
-1,000
**
.
b
0,707 0,577 0,577 0,577 0,302 0,302 0,000 -0,577 -0,577
.
b
0,577 -0,577 0,302
Sig. (1-
tailed)
0,211 0,146 0,500 0,211 0,211 0,500 0,500 0,500 0,211 0,349 0,500 0,146 0,500 0,211 0,000 0,146 0,211 0,211 0,211 0,349 0,349 0,500 0,211 0,211 0,211 0,211 0,349
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
-0,333 0,000 -0,577 0,577 1 0,333 0,577 -0,577 0,577 -0,333
.
b
-0,174 -0,577 0,000 -0,577
1,000
**
-0,577
.
b
0,816
1,000
**
1,000
**
0,333 -0,522 -0,174 -0,577 0,333 0,333
.
b
0,333 0,333 -0,174
Sig. (1-
tailed)
0,333 0,500 0,211 0,211 0,333 0,211 0,211 0,211 0,333 0,413 0,211 0,500 0,211 0,000 0,211 0,092 0,000 0,000 0,333 0,239 0,413 0,211 0,333 0,333 0,333 0,333 0,413
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,333 0,000 0,577 0,577 0,333 1 0,577 0,577 -0,577 0,333
.
b
0,870 0,577 0,816 0,577 0,333 -0,577
.
b
0,816 0,333 0,333
1,000
**
0,522 0,870 0,577 -0,333 -0,333
.
b
1,000
**
-0,333 0,870
Sig. (1-
tailed)
0,333 0,500 0,211 0,211 0,333 0,211 0,211 0,211 0,333 0,065 0,211 0,092 0,211 0,333 0,211 0,092 0,333 0,333 0,000 0,239 0,065 0,211 0,333 0,333 0,000 0,333 0,065
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
-0,577 -0,707 0,000 0,000 0,577 0,577 1 0,000 0,000 -0,577
.
b
0,302 0,000 0,000 0,000 0,577 0,000
.
b
0,707 0,577 0,577 0,577 -0,302 0,302 0,000 0,577 0,577
.
b
0,577 0,577 0,302
Sig. (1-
tailed)
0,211 0,146 0,500 0,500 0,211 0,211 0,500 0,500 0,211 0,349 0,500 0,500 0,500 0,211 0,500 0,146 0,211 0,211 0,211 0,349 0,349 0,500 0,211 0,211 0,211 0,211 0,349
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,577 0,000
1,000
**
0,000 -0,577 0,577 0,000 1
-1,000
**
0,577
.
b
,905
*
1,000
**
0,707
1,000
**
-0,577 0,000
.
b
0,000 -0,577 -0,577 0,577
,905
*
,905
*
1,000
**
-0,577 -0,577
.
b
0,577 -0,577
,905
*
Sig. (1-
tailed)
0,211 0,500 0,000 0,500 0,211 0,211 0,500 0,000 0,211 0,048 0,000 0,146 0,000 0,211 0,500 0,500 0,211 0,211 0,211 0,048 0,048 0,000 0,211 0,211 0,211 0,211 0,048
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
-0,577 0,000
-1,000
**
0,000 0,577 -0,577 0,000
-1,000
**
1 -0,577
.
b
-,905
*
-1,000
**
-0,707
-1,000
**
0,577 0,000
.
b
0,000 0,577 0,577 -0,577
-,905
*
-,905
*
-1,000
**
0,577 0,577
.
b
-0,577 0,577
-,905
*
Sig. (1-
tailed)
0,211 0,500 0,000 0,500 0,211 0,211 0,500 0,000 0,211 0,048 0,000 0,146 0,000 0,211 0,500 0,500 0,211 0,211 0,211 0,048 0,048 0,000 0,211 0,211 0,211 0,211 0,048
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
1,000
**
0,816 0,577 0,577 -0,333 0,333 -0,577 0,577 -0,577 1
.
b
0,522 0,577 0,816 0,577 -0,333 -0,577
.
b
0,000 -0,333 -0,333 0,333 0,870 0,522 0,577
-1,000
**
-1,000
**
.
b
0,333
-1,000
**
0,522
Sig. (1-
tailed)
0,000 0,092 0,211 0,211 0,333 0,333 0,211 0,211 0,211 0,239 0,211 0,092 0,211 0,333 0,211 0,500 0,333 0,333 0,333 0,065 0,239 0,211 0,000 0,000 0,333 0,000 0,239
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
Sig. (1-
tailed)
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,522 0,000
,905
*
0,302 -0,174 0,870 0,302
,905
*
-,905
*
0,522
.
b
1
,905
*
0,853
,905
*
-0,174 -0,302
.
b
0,426 -0,174 -0,174 0,870 0,818
1,000
**
,905
*
-0,522 -0,522
.
b
0,870 -0,522
1,000
**
Sig. (1-
tailed)
0,239 0,500 0,048 0,349 0,413 0,065 0,349 0,048 0,048 0,239 0,048 0,074 0,048 0,413 0,349 0,287 0,413 0,413 0,065 0,091 0,000 0,048 0,239 0,239 0,065 0,239 0,000
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,577 0,000
1,000
**
0,000 -0,577 0,577 0,000
1,000
**
-1,000
**
0,577
.
b
,905
*
1 0,707
1,000
**
-0,577 0,000
.
b
0,000 -0,577 -0,577 0,577
,905
*
,905
*
1,000
**
-0,577 -0,577
.
b
0,577 -0,577
,905
*
Sig. (1-
tailed)
0,211 0,500 0,000 0,500 0,211 0,211 0,500 0,000 0,000 0,211 0,048 0,146 0,000 0,211 0,500 0,500 0,211 0,211 0,211 0,048 0,048 0,000 0,211 0,211 0,211 0,211 0,048
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,816 0,500 0,707 0,707 0,000 0,816 0,000 0,707 -0,707 0,816
.
b
0,853 0,707 1 0,707 0,000 -0,707
.
b
0,500 0,000 0,000 0,816 0,853 0,853 0,707 -0,816 -0,816
.
b
0,816 -0,816 0,853
Sig. (1-
tailed)
0,092 0,250 0,146 0,146 0,500 0,092 0,500 0,146 0,146 0,092 0,074 0,146 0,146 0,500 0,146 0,250 0,500 0,500 0,092 0,074 0,074 0,146 0,092 0,092 0,092 0,092 0,074
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,577 0,000
1,000
**
0,000 -0,577 0,577 0,000
1,000
**
-1,000
**
0,577
.
b
,905
*
1,000
**
0,707 1 -0,577 0,000
.
b
0,000 -0,577 -0,577 0,577
,905
*
,905
*
1,000
**
-0,577 -0,577
.
b
0,577 -0,577
,905
*
Sig. (1-
tailed)
0,211 0,500 0,000 0,500 0,211 0,211 0,500 0,000 0,000 0,211 0,048 0,000 0,146 0,211 0,500 0,500 0,211 0,211 0,211 0,048 0,048 0,000 0,211 0,211 0,211 0,211 0,048
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
-0,333 0,000 -0,577 0,577
1,000
**
0,333 0,577 -0,577 0,577 -0,333
.
b
-0,174 -0,577 0,000 -0,577 1 -0,577
.
b
0,816
1,000
**
1,000
**
0,333 -0,522 -0,174 -0,577 0,333 0,333
.
b
0,333 0,333 -0,174
Sig. (1-
tailed)
0,333 0,500 0,211 0,211 0,000 0,333 0,211 0,211 0,211 0,333 0,413 0,211 0,500 0,211 0,211 0,092 0,000 0,000 0,333 0,239 0,413 0,211 0,333 0,333 0,333 0,333 0,413
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
-0,577 -0,707 0,000
-1,000
**
-0,577 -0,577 0,000 0,000 0,000 -0,577
.
b
-0,302 0,000 -0,707 0,000 -0,577 1
.
b
-0,707 -0,577 -0,577 -0,577 -0,302 -0,302 0,000 0,577 0,577
.
b
-0,577 0,577 -0,302
Sig. (1-
tailed)
0,211 0,146 0,500 0,000 0,211 0,211 0,500 0,500 0,500 0,211 0,349 0,500 0,146 0,500 0,211 0,146 0,211 0,211 0,211 0,349 0,349 0,500 0,211 0,211 0,211 0,211 0,349
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
Sig. (1-
tailed)
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,000 0,000 0,000 0,707 0,816 0,816 0,707 0,000 0,000 0,000
.
b
0,426 0,000 0,500 0,000 0,816 -0,707
.
b
1 0,816 0,816 0,816 0,000 0,426 0,000 0,000 0,000
.
b
0,816 0,000 0,426
Sig. (1-
tailed)
0,500 0,500 0,500 0,146 0,092 0,092 0,146 0,500 0,500 0,500 0,287 0,500 0,250 0,500 0,092 0,146 0,092 0,092 0,092 0,500 0,287 0,500 0,500 0,500 0,092 0,500 0,287
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
-0,333 0,000 -0,577 0,577
1,000
**
0,333 0,577 -0,577 0,577 -0,333
.
b
-0,174 -0,577 0,000 -0,577
1,000
**
-0,577
.
b
0,816 1
1,000
**
0,333 -0,522 -0,174 -0,577 0,333 0,333
.
b
0,333 0,333 -0,174
Sig. (1-
tailed)
0,333 0,500 0,211 0,211 0,000 0,333 0,211 0,211 0,211 0,333 0,413 0,211 0,500 0,211 0,000 0,211 0,092 0,000 0,333 0,239 0,413 0,211 0,333 0,333 0,333 0,333 0,413
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
-0,333 0,000 -0,577 0,577
1,000
**
0,333 0,577 -0,577 0,577 -0,333
.
b
-0,174 -0,577 0,000 -0,577
1,000
**
-0,577
.
b
0,816
1,000
**
1 0,333 -0,522 -0,174 -0,577 0,333 0,333
.
b
0,333 0,333 -0,174
Sig. (1-
tailed)
0,333 0,500 0,211 0,211 0,000 0,333 0,211 0,211 0,211 0,333 0,413 0,211 0,500 0,211 0,000 0,211 0,092 0,000 0,333 0,239 0,413 0,211 0,333 0,333 0,333 0,333 0,413
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,333 0,000 0,577 0,577 0,333
1,000
**
0,577 0,577 -0,577 0,333
.
b
0,870 0,577 0,816 0,577 0,333 -0,577
.
b
0,816 0,333 0,333 1 0,522 0,870 0,577 -0,333 -0,333
.
b
1,000
**
-0,333 0,870
Sig. (1-
tailed)
0,333 0,500 0,211 0,211 0,333 0,000 0,211 0,211 0,211 0,333 0,065 0,211 0,092 0,211 0,333 0,211 0,092 0,333 0,333 0,239 0,065 0,211 0,333 0,333 0,000 0,333 0,065
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,870 0,426
,905
*
0,302 -0,522 0,522 -0,302
,905
*
-,905
*
0,870
.
b
0,818
,905
*
0,853
,905
*
-0,522 -0,302
.
b
0,000 -0,522 -0,522 0,522 1 0,818
,905
*
-0,870 -0,870
.
b
0,522 -0,870 0,818
Sig. (1-
tailed)
0,065 0,287 0,048 0,349 0,239 0,239 0,349 0,048 0,048 0,065 0,091 0,048 0,074 0,048 0,239 0,349 0,500 0,239 0,239 0,239 0,091 0,048 0,065 0,065 0,239 0,065 0,091
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,522 0,000
,905
*
0,302 -0,174 0,870 0,302
,905
*
-,905
*
0,522
.
b
1,000
**
,905
*
0,853
,905
*
-0,174 -0,302
.
b
0,426 -0,174 -0,174 0,870 0,818 1
,905
*
-0,522 -0,522
.
b
0,870 -0,522
1,000
**
Sig. (1-
tailed)
0,239 0,500 0,048 0,349 0,413 0,065 0,349 0,048 0,048 0,239 0,000 0,048 0,074 0,048 0,413 0,349 0,287 0,413 0,413 0,065 0,091 0,048 0,239 0,239 0,065 0,239 0,000
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
0,577 0,000
1,000
**
0,000 -0,577 0,577 0,000
1,000
**
-1,000
**
0,577
.
b
,905
*
1,000
**
0,707
1,000
**
-0,577 0,000
.
b
0,000 -0,577 -0,577 0,577
,905
*
,905
*
1 -0,577 -0,577
.
b
0,577 -0,577
,905
*
Sig. (1-
tailed)
0,211 0,500 0,000 0,500 0,211 0,211 0,500 0,000 0,000 0,211 0,048 0,000 0,146 0,000 0,211 0,500 0,500 0,211 0,211 0,211 0,048 0,048 0,211 0,211 0,211 0,211 0,048
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
-1,000
**
-0,816 -0,577 -0,577 0,333 -0,333 0,577 -0,577 0,577
-1,000
**
.
b
-0,522 -0,577 -0,816 -0,577 0,333 0,577
.
b
0,000 0,333 0,333 -0,333 -0,870 -0,522 -0,577 1
1,000
**
.
b
-0,333
1,000
**
-0,522
Sig. (1-
tailed)
0,000 0,092 0,211 0,211 0,333 0,333 0,211 0,211 0,211 0,000 0,239 0,211 0,092 0,211 0,333 0,211 0,500 0,333 0,333 0,333 0,065 0,239 0,211 0,000 0,333 0,000 0,239
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
-1,000
**
-0,816 -0,577 -0,577 0,333 -0,333 0,577 -0,577 0,577
-1,000
**
.
b
-0,522 -0,577 -0,816 -0,577 0,333 0,577
.
b
0,000 0,333 0,333 -0,333 -0,870 -0,522 -0,577
1,000
**
1
.
b
-0,333
1,000
**
-0,522
Sig. (1-
tailed)
0,000 0,092 0,211 0,211 0,333 0,333 0,211 0,211 0,211 0,000 0,239 0,211 0,092 0,211 0,333 0,211 0,500 0,333 0,333 0,333 0,065 0,239 0,211 0,000 0,333 0,000 0,239
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
.
b
Sig. (1-
tailed)
N 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Pearson
Correlation
0,333 0,000 0,577 0,577 0,333
1,000
**
0,577 0,577 -0,577 0,333
.
b
0,870 0,577 0,816 0,577 0,333 -0,577
.
b
0,816 0,333 0,333
1,000
**
0,522 0,870 0,577 -0,333 -0,333
.
b
1 -0,333 0,870
Sig. (1-
tailed)
0,333 0,500 0,211 0,211 0,333 0,000 0,211 0,211 0,211 0,333 0,065 0,211 0,092 0,211 0,333 0,211 0,092 0,333 0,333 0,000 0,239 0,065 0,211 0,333 0,333 0,333 0,065
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Pearson
Correlation
-1,000
**
-0,816 -0,577 -0,577 0,333 -0,333 0,577 -0,577 0,577
-1,000
**
.
b
-0,522 -0,577 -0,816 -0,577 0,333 0,577
.
b
0,000 0,333 0,333 -0,333 -0,870 -0,522 -0,577
1,000
**
1,000
**
.
b
-0,333 1 -0,522
Sig. (1-
tailed)
0,000 0,092 0,211 0,211 0,333 0,333 0,211 0,211 0,211 0,000 0,239 0,211 0,092 0,211 0,333 0,211 0,500 0,333 0,333 0,333 0,065 0,239 0,211 0,000 0,000 0,333 0,239
N 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 0 4 4 4
Smart policies
Smart
governance
average
**. Correlation is significant at the 0.01 level (1-tailed).
*. Correlation is significant at the 0.05 level (1-tailed).
b. Cannot be computed because at least one of the variables is constant.
Smart private
transportation
Renewable
energy
Buildings energy
efficiency
Smart health
average
One-way
communication
Local government
investment
Public-private
investment
Foreign
investment
Smart
transportation
infrastuctures
Smart public
transportation
Educating &
training people
Transferring
(attracting)
educated and
skilled people
Nurture the
innovation
environment
Smart interaction
Smart security
and safety
New technologies
for utilities
Smart Energy
average
Smart health
monitoring
systems
Smart health
management and
information
applications
Smart
administration
Two-way
communication
Co-creating and
co-designing
Smart city
average
Data aggregation
Data processing
Data real-time
analysis
Supra-national
and national
investment
Attracting
innovative
companies
Appendix 165
A
Table A2-Qualitative analysis of the design throughput choices
Path-
ways
Origin (op-
portunity
window)
Throughput
Management of
input resources
Policy Leadership
Knowledge &
Innovation
Coordina-
tion of ac-
tors
Amsterdam
City of
A'dam and
Alliander
want to
build Smart
City to
lower CO2
emissions.
Second largest
internet ex-
change point
in the world,
Structural vi-
sion 2040:
economy
and sustain-
ability
Economic
Board
Smart City
Academy
and AMS.
ASC plat-
form
High technol-
ogy readiness
level
Specific pol-
icy in place
to promote
innovation
in coordina-
tion with na-
tional and
European
policies
Smart Entre-
preneurial
Lab
Chief
Technol-
ogy Of-
ficer
(CTO)
EU project
funding and
aligned
with Hori-
zon2020
modern tech-
nology infra-
structures
StartupAm-
sterdam
Amsterdam
Science Park
City Data por-
tal
ASC has the
open-house
programs
and open
meeting ups
to empower
citizens
AMS Living Labs
ASC platform
(to generate
ideas)
European
Union’s
DECODE
project aim-
ing to return
data sover-
eignty to the
citizens.
Barcelona
Strategy by
the City of
Barcelona to
create a
more sus-
tainable,
Municipal data
office for pub-
lic data sover-
eignty
Smart City
Expo and
World Con-
gress
City Council,
Barcelona Pro-
vincial Council,
and Area Met-
ropolitana de
Smart inno-
vation; vir-
tual lab
22@ inno-
vation dis-
trict (to co-
ordinate
knowledge
partners)
166 A
A
Path-
ways
Origin (op-
portunity
window)
Throughput
Management of
input resources
Policy Leadership
Knowledge &
Innovation
Coordina-
tion of ac-
tors
smart, and
inclusive
path for de-
velopment
(2011)
CityOS, Open
Data Bcn, and
Monitoring
Gentrification
Smart City
Program
Barcelona
(AMB).
Institute for
Advanced
Architecture
of Catalonia
(IAAC)
EU project
funding and
aligned
with Hori-
zon2020
‘Multi-tenant
DIBA’ plat-
form
‘Barcelona
Smart City
Strategy,
Planning
and Imple-
mentation’
Fab Lab
Several pla-
torms and ap-
plications that
support smart
mobility
Develop-
ment of a
community
of citizens
and develop-
ers, and in-
stallations
for SMEs
(early stage).
Subsidies to
support so-
lar energy
installation
European
Union’s
DECODE
project aim-
ing to return
data sover-
eignty to the
citizens.
‘Dicdim Barce-
lona’, a partici-
patory democ-
racy (digital)
platform for
communi-
cating and em-
powering citi-
zens
22@ innova-
tion district
Dubai
Vision of
Ruler of
Dubai
Khazna Data
Centers
Smart Dubai
Strategy
Executive office
for Dubai Smart
City program
was established.
Dubai Inter-
national Aca-
demic City
(DIAC)
Having all
city stake-
holders on
board is a
corner-
stone of
Smart Du-
bai strat-
egy.
Appendix 167
A
Path-
ways
Origin (op-
portunity
window)
Throughput
Management of
input resources
Policy Leadership
Knowledge &
Innovation
Coordina-
tion of ac-
tors
AI Lab (with
IBM)
major train-
ing pro-
grams to de-
velop hu-
man re-
sources
(train public
staff; civil
servants).
Visionary lead-
ership to foster
happiness
(Ruler of Dubai)
Dubai
Knowledge
Village
Setting up
a cham-
pion in
line with
the over-
arching
policy of
develop-
ing the
Smart City
Global Block
chain Chal-
lenge, Dubai
Smart City
Accelerator
and, Dubai
Future Ac-
celerators
Dubai Inter-
net city
Happiness
champions
Dubai Pulse;
central plat-
form for
providing
compute, stor-
age, and ana-
lytic services
Dubai Data
Dubai Data Es-
tablishment
Science
parks
Hi-tech
free zones
AI roadmap
Dubai Electric-
ity and Water
Authority
Paperless
government
policy is the
goal for
smart ad-
ministration
Dubai Health
Authority
Dubai Now’
platform (to
support e-ser-
vices to citi-
zens)
Dubai Supreme
Council of En-
ergy
Smart Du-
bai Office
Masdar
Abu Dhabi
want to
pursue the
world's
Data manage-
ment driving
innovative so-
lutions
Smart trans-
portation
policies
Mubadala In-
vestment Com-
pany
Research &
Academia
Large scale
free eco-
nomic
zone
168 A
A
Path-
ways
Origin (op-
portunity
window)
Throughput
Management of
input resources
Policy Leadership
Knowledge &
Innovation
Coordina-
tion of ac-
tors
most sus-
tainable city
(2006)
IoT platform
for increased
health,
productivity
and sustaina-
bility (with
Huawei)
Holistic ap-
proach to de-
velop renewa-
ble energy and
sustainability
by creating the
value chain
from research
to investments.
Masdar Insti-
tute of Sci-
ence and
Technology
(MIST)
Ruler of Abu
Dhabi
Honeywell
Masdar In-
novation
Center
Sustaina-
bility week
platform
Mobility Ur-
ban Value
project
Appendix 169
A
Table A3-Iranian Smart Cities’ readiness assessment
Operationali-
zation
Qualitative Analysis
Tehran
Isfahan
Mashhad
Shiraz
Technological readiness assessment
Big data estab-
lishment
My Tehran’ portal
Isfahan Integrated
spatial portal
Mashhad’ portal N/A
Sensors and
actuator
equipped de-
vices,
CCTVs,and
cameras
Air quality sen-
sors, traffic, and
monitoring Cam-
eras
Traffic and moni-
toring Cameras
Flood alert sen-
sors, air quality
sensors, and traf-
fic sensors
Traffic and moni-
toring Cameras
ICT Develop-
ment Index
(IDI)
7.24 (in 2017) 6.24 (in 2017) 5.35 (in 2017) 6.25 (in 2017)
Data science
centers
Supreme Council
of Cyberspace,
ICT research insti-
tute, Iranian Insti-
tute of Infor-
mation Science
and Technology,
Iran’s IoT Acad-
emy
N/A
IT and Cyber-
space research
center
Shiraz Data Cen-
ter
Data visualiza-
tion platforms
IT, Judicial Af-
fairs, Energy, Ed-
ucation, Financial
and Commercial,
Healthcare, De-
mography, Trans-
portation and traf-
fic, Social services,
Buildings and
housing, Environ-
ment, Industry,
Landscape and
urban services,
Culture and reli-
gion, Agriculture,
forestry and fish-
eries, Economy,
Tourism
An integrated
platform for spa-
tial information
Mobile Mashhad
Apps; Transporta-
tion and traffic,
Business, Envi-
ronment, Pay-
ment and Trans-
actions, Waste
management
N/A
Data Laws
IoT laws and reg-
ulation issued by
Supreme Council
of Cyberspace (in
2017)
IoT laws and reg-
ulation issued by
Supreme Council
of Cyberspace (in
2017)
IoT laws and reg-
ulation issued by
Supreme Council
of Cyberspace (in
2017)
IoT laws and reg-
ulation issued by
Supreme Council
of Cyberspace (in
2017)
170 A
A
Operationali-
zation
Qualitative Analysis
Tehran
Isfahan
Mashhad
Shiraz
Establishing a
cyber security
framework
Cyber security re-
search institute
Budget allocation
for cyber security
projects
Budget allocation
for cyber security
projects
N/A
Social Readiness assessment
Number of
universities
and research
centers
119 (in 2019) 67 (in 2019) 30 (in 2019) 25 (in 2019)
Knowledge
transfer and
knowledge
sharing pro-
grams
Asian Smart Cit-
ies Committee of
Asian Mayors Fo-
rum
Joint cooperation
between the Tech-
nical and Voca-
tional University
and the ICT Or-
ganization of Isfa-
han Municipality
Mashhad
SmartExpo
Shiraz Smart City
Exhibition and
Urban Investment
Opportunities
Specific policy
in place to pro-
mote Smart
City innova-
tion
Tehran Urban In-
novation Center
(TUIC)
Isfahan Urban
Creativity and In-
novation Center
Mashhad Urban
Innovation Center
Launching Shiraz
Innovation Fac-
tory
Supporting
and encourag-
ing programs
for innovative
companies
(Science and
technology
parks, free
zones, etc.)
8 Science &Tech-
nology Parks
around Tehran,
The National Fes-
tival of ‘From Sci-
ence to Practice’
to support inno-
vative companies
with commerciali-
zation approach
13 Science and
Technology parks
and incubators
A Science and
Technology parks
and 11 incubators
6 Science and
Technology parks
and incubators
The level of
citizens’
awareness of
the Smart City
program in
their city
Citizens have
heard about it but
have no infor-
mation of the pro-
gram
Citizens have
heard about it but
have no infor-
mation of the pro-
gram
Citizens have
heard about it but
have no infor-
mation of the pro-
gram
Citizens have
heard about it but
have no infor-
mation of the pro-
gram
The level of
citizens’
awareness of
the Smart City
concept and
technologies
Average level of
awareness
Average level of
awareness
Average level of
awareness
Average level of
awareness
Appendix 171
A
Operationali-
zation
Qualitative Analysis
Tehran
Isfahan
Mashhad
Shiraz
The level of
perceived use-
fulness of the
smart solu-
tions for the
city’s chal-
lenges by citi-
zens
The high level of
citizens perceived
usefulness is for
pollution and traf-
fic
The high level of
citizens perceived
usefulness is for
pollution, traffic,
and housing is-
sues
The high level of cit-
izens perceived use-
fulness is for pollu-
tion and traffic
The high level
of citizens per-
ceived useful-
ness is for pollu-
tion and traffic
Citizens’ opin-
ion about a
Smart City
Most frequent
statements are re-
lated to ’green‘
and ’surveillance‘
city
Most frequent
statements are re-
lated to ‘surveil-
lance’ and ‘happy’
city ‘surrounded
by technology’
Most frequent state-
ments are related to
’green‘ and ’surveil-
lance‘ city
Most frequent
statements are
related to ‘safe’
and ‘green’ city
Citizens’ im-
age of their cit-
ies
Most frequent im-
ages are ‘polluted
city’, ‘busy’, ‘ex-
pensive’, and
‘alive’ city
Most frequent im-
ages are
‘crowded’, ‘pol-
luted’, ‘beautiful’,
‘historical’ city
‘with a lot of po-
tentials’
Most frequent im-
ages are ‘crowded’,
‘polluted’ city with
deficiencies in pub-
lic transportation
Most frequent
images are
‘happy’ and
‘beautiful’ city
Citizens’ dif-
ferent ideas of
quality of life
Most frequent
ideas are related
to ‘safety’, ‘pros-
perity’, ‘happi-
ness’, ‘peace’, and
‘citizens (human)
rights ‘
Most frequent
ideas are related
to ‘health’,
‘safety’, and ‘hap-
piness’
Most frequent ideas
are related to ‘pros-
perity’ and ‘happi-
ness’
Most frequent
ideas are related
to ‘safety’,
‘prosperity’ and
‘happiness’
Political Readiness assessment
Leadership vi-
sion/support
for Smart City
program
Ideological and
religious dogmas
Ideological and
religious dogmas
Ideological and reli-
gious dogmas
Ideological and
religious dog-
mas
Government
structure, gov-
ernance ar-
rangements,
policy net-
works
Multi-Level Gov-
ernance, Central-
ized approach
Multi-Level Gov-
ernance, Central-
ized approach
Multi-Level Gov-
ernance, Central-
ized approach, the
power of Astan-e-
Qods, and the con-
servative ruler of
Mashhad (the Fri-
day Prayer leader)
Multi-Level
Governance,
Centralized ap-
proach
172 A
A
Operationali-
zation
Qualitative Analysis
Tehran
Isfahan
Mashhad
Shiraz
Rules, laws, le-
gal and regula-
tory reforms
Existing munici-
pal laws and reg-
ulations, up-
stream policy doc-
uments, Islamic
law (Shariah)
Existing munici-
pal laws and reg-
ulations, up-
stream policy doc-
uments, Islamic
law (Shariah)
Existing municipal
laws and regula-
tions, upstream pol-
icy documents, Is-
lamic law (Shariah),
the Rules by the Fri-
day Prayer leader
Existing munici-
pal laws and
regulations, up-
stream policy
documents, Is-
lamic law (Sha-
riah)
Policies, policy
instruments
Policies of the dif-
ferent levels of na-
tional, regional
and municipal,
are under consid-
eration
Policies of the dif-
ferent levels of na-
tional, regional
and municipal,
are under consid-
eration
Policies of the dif-
ferent levels of na-
tional, regional and
municipal, and As-
tan-e-Qods are un-
der consideration
Policies of the
different levels
of national, re-
gional and mu-
nicipal, are un-
der considera-
tion
Legitimacy,
tranparency
and trust
Extreme religious
considerations,
low level of trans-
parency and trust
Extreme religious
considerations,
low level of trans-
parency and trust
Super-extreme reli-
gious considera-
tions, low level of
transparency and
trust
Extreme reli-
gious considera-
tions, low level
of transparency
and trust
Partnerships
with industry,
academia, and
citizens
Lack of an inte-
grated partner-
ship platform
Lack of an inte-
grated partner-
ship platform
Lack of an inte-
grated partnership
platform
Lack of an inte-
grated partner-
ship platform
Providing a
platform for
multi-stake-
holder partner-
ship
Lack of an inte-
grated partner-
ship platform
Lack of an inte-
grated partner-
ship platform
Lack of an inte-
grated partnership
platform
Lack of an inte-
grated partner-
ship platform
173
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ACKNOWLEDGMENTS
Many supported me during my PhD research project. I appreciate all of you for the
support and accompanying. Here I would like to highlight some of you.
Martin, I can’t even begin to explain how much your help meant to me. Thank you
for giving me the opportunity to do a PhD under your supervision. Thank you for
supporting my dreams, no matter what. I couldn’t ask for a better supervisor. Thank
you for giving me all the freedom to follow my ideas, to lead my project and espe-
cially for coaching me in my personal life.
Thomas, thanks for always stepping in to help when I needed you most. Your critical
and practical view on our papers helped me realize that significant scientific contri-
bution needs to be detailed and exhaustive.
Marijn, you made my heart smile during the difficult time in my PhD project. Thank
you for helping me through that difficult time. Except from inspiring me how to
create new insights and solutions, you always make me feel calm and believe in my
ideas.
Evert, I truly enjoyed that you accepted to be in my supervisory team. Thank you
for having confidence in my abilities.
Daan, thank you for sharing your passion for bibliometric analysis and modelling. I
learned many data analysis methods from you.
Robert, thank you for being such an inspiration to me and others around you. I want
to express my gratitude for everything that you’ve helped me. How did you become
so wise? Thanks again for all of your advice.
Agnes, thank you for taking care of me like a kind mother when I arrived in TU-
Delft. Janine from TPM graduate school, Judith; our HR officer at ESL, and Wilma
from ESL graduate school, without your strong support I wouldn’t be able to suc-
cessfully finish my PhD.
208 Acknowledgments
I would like to thank Prof. Simon Joss, Prof. Luca Mora, Prof. Albert Meijer, Prof.
Suzan Stoter, and Prof. Alessandra Arcuri for accepting to be in my committee. A
special thanks to Simon and Luca for insightful discussions and suggestions.
My first officemates at TU-Delft; Samaneh and Arman, my colleagues at TU-Delft;
Haiyan, and Wenting, my colleagues at Erasmus; Remi, Jiejing, Roel, and Aziza
thank you for making the office a pleasant environment to work.
My friends, Arash, Masoud, Amin, Siamak, Sahar, Elnaz Vahid, Sadaf, Narges, Katy,
Niloo, Pouyan, thanks for giving me a fun, warm world and for always having my
back. A very special thanks to my dear Arash for your kindness and compassion.
Thanks to my friends, Melika, Bijan, Hoda, Moien, Sara, Faraz, Babak, Marjan,
Darya, and Artemis for making my life here enjoyable.
And my family, mom and dad; my two wings to fly, thank you for raising me in a
warm, loving and safe environment. Thank you for always supporting me to take
new adventures in my life and every time I fell, you held my hand to get up again.
I couldn’t love you more, thank you for being so amazing! and my beautiful sisters;
Sahar and Ati you’re the sweetest! Thank you for everything you do! My brother-in-
law Saman, thanks for being amazing! I value and respect you helped me to pursue
my dreams.
Samrad, My sweetie! Thanks for coming to this world and making my life beautiful
.
You are a piece of my heart!
209
CURRICULUM VITAE
210 Curriculum Vitae
211
LIST OF PUBLICATIONS
Noori, N., & De Jong, M. Towards credible city branding practices: How do
Iran’s largest cities face ecological modernization? Sustainability, 2018.
De Jong, M., Hoppe, T., & Noori, N. City Branding, Sustainable Urban Devel-
opment and the Rentier State. How Do Qatar, Abu Dhabi and Dubai Present
Themselves in the Age of Post Oil and Global Warming? Energies 2019.
Noori, N., Jong, M. De, Janssen, M., & Hoppe, T. (2019). Input-Output Mod-
elling for Smart City Development: The Case of Smart Dubai. Journal of Urban
Technology 2020.
Noori, N.; Hoppe, T.; de Jong, M. Classifying Pathways for Smart City Devel-
opment: Comparing Design, Governance and Implementation in Amsterdam,
Barcelona, Dubai, and Abu Dhabi. Sustainability 2020.
Noori, N.; de Jong, M.; Hoppe, T. Towards an Integrated Framework to Meas-
ure Smart City Readiness: The Case of Iranian Cities. Smart Cities 2020.
Noori, N.; Hoppe, T.; De Jong, M.; Stamhuis, E. Introducing a Conceptual
Framework to Analyze Smart City Policy Transplantation. In Smart City:
Strategies for City Development and Innovation, 1st ed.; Philips, F., Oh, D.,
Eds.; World Scientific Publishing Co (In press).
212 PhD Trajectory
PHD TRAJECTORY
Joining a team of policy experts with limited technical background in an Inclu-
sive Smart City development project, I was an intermediate between policymakers
and practitioners using my technological knowledge. I mapped the Smart City de-
sign variables, policies and its development process in a conceptual model through
studying the smart city good practices of Amsterdam, Barcelona, Dubai, and
Masdar. Interacting with different stakeholders and site-visiting helped me to inves-
tigate the key facets, projects and design variables of the smart city programs. I
worked with living labs to analyse end-user’s engagement strategies for co-creating
smart solutions and applications. To develop practical solutions from the results, I
formulated the lessons learned from the good practices into innovation policies to
transfer to Smart City initiatives. The tangible outcomes are a roadmap and guide-
lines for Smart City initiative transition based on developing a Theory of Change.
During my PhD, as an ancillary work I joined a research project on improving
coaching practices for NEDs conducted by a Coaching Practice Director at INSEAD.
I analyzed and processed the data obtained from interviewing NEDs regarding their
expectations and challenges during being coached. The result pertains to the im-
provements in the coaching practices.
WORK AND RESEARCH ACTIVITIES
PhD Candidate; Smart City Policy & Tech Sep 2017 – Sep 2018
Delft University of Technology, Faculty of Technology, Policy and Management
(TPM)
I have started my Ph.D. research project on 'Smart city policy transplantation'
at the Department of Multi Actor Systems (TPM faculty, TU Delft). During my first
year, I have completed all the graduate school courses (55 credits/ 45), passed
Go/nGo, and published my first article. I attended the Smart City World Expo Con-
gress in Barcelona, several events and workshops organized by Amsterdam Smart
City (AMC), such as ‘AMC Open-House’. I also have done the site-visiting and field
research in Dubai and Abu-Dhabi.
PhD Candidate; Smart City Policy & Tech Sep 2018 – Present
Erasmus University of Rotterdam, Erasmus School of Law
PhD Trajectory 213
After finishing the first year in TUDelft, I have been continuing my Ph.D. in the
Erasmus Initiative 'Dynamics of Inclusive Prosperity' (a multidisciplinary partner-
ship of Erasmus School of Law, Rotterdam School of Management and the Erasmus
School of Philosophy). I have been developing my research skills at Erasmus Uni-
versity by attending a ‘Scientific Writing’ course at Law school when I arrived. I have
attended the Smart City World Expo Congress in Barcelona for the second time in
2019. All the courses, field researches, workshops and seminars led me to publish
four scientific journal articles alongside with developing a network with govern-
mental entities and private companies active in Smart City programs.
PHD COURSES
Courses at TUDelft Graduate School: PhD Start-Up Module A,B &C(16 hours)
|Becoming a Creative Researcher in Academia (8 hours)| Cross Cultural Communi-
cation(8 hours)| Developing Your Academic Skills(12 hours)| How to Interact Ef-
fectively with Your Research Team(16 hours)| How to make a questionnaire and
conduct an interview(16 hours)| Leadership, Teamwork and Group Dynamics(12
hours)| Political Decision Making(12 hours)| Problem Solving(12 hours)| Research
design(12 hours)| Self Presentation(16 hours)| Speed-reading and Mind Map-
ping(12 hours)|The Informed Researcher (12 hours) |Developing Your Academic
Skills (12 hours) |The PhD Network Hub(8 hours) |Achieving Your Goals and Per-
forming More Successfully in Your PhD (24 hours) |Creative Tools for Scientific
Writing(16 hours) |Looking For a Job in Netherlands (8 hours)
Course at ESL Graduate School: Scientific Writing (15 hours)
Online Course at ETH University: Smart Cities
WORKSHOPS, SEMINARS AND PRESENTATIONS
Workshops: Working Together on The Central Innovation District (CID)_20
Nov 2017, The Hague| PhD Days for TPM’s Students, March 2018, The Hague|
Writing Effective Propositions, 2 Nov 2017, Delft |Workshop Personal Branding &
Networking, 27 May 2020, Erasmus University| Job crafting workshop, 26 May 2020,
Erasmus University |PNN National PhD Day, 24 Nov 2018, Tilburg University|
Amsterdam Smart City Open-house, 30 March 2017, Amsterdam.
Conferences & Seminars: Netherlands Institute of Government (NIG) Annual
Conference, 9 Nov 2017, Maastricht | Smart City World Expo Congress, Nov 2018 &
2019, Barcelona | Seminar on ‘Are You Ready to Publish? The Importance of Being
214 PhD Trajectory
Open, 20 Sep 2017, TUDelft Science Center |Seminar on Publish for Influence, 1 Nov
2017, Erasmus University.
Presentations: Presenting my first draft paper on City Branding at NIG Confer-
ence, 2017, Maastricht |Presenting my PhD research project for The Hauge Smart
City Department, 2019, The Hague Municipality| Presenting my draft paper on
Smart City IO Modelling for Chinese Delignates, 2019, Erasmus University | Pre-
senting my PhD research project for TPM Research Frontiers Group, 2018, TUDelft
|Presenting my draft paper on Classifying Pathways for Smart City Development
during the Dynamics of Inclusive Prosperity’s scientific meeting.
Teaching Assistance: Policy Game Simulation by Martin De Jong at TUDelft
PUBLICATIONS
Noori, N., & De Jong, M. Towards credible city branding practices: How do Iran’s
largest cities face ecological modernization? Sustainability, 2018.
De Jong, M., Hoppe, T., & Noori, N. City Branding, Sustainable Urban Develop-
ment and the Rentier State. How Do Qatar, Abu Dhabi and Dubai Present Them-
selves in the Age of Post Oil and Global Warming? Energies 2019.
Noori, N., Jong, M. De, Janssen, M., & Hoppe, T. (2019). Input-Output Modelling
for Smart City Development: The Case of Smart Dubai. Journal of Urban Technol-
ogy 2020.
Noori, N.; Hoppe, T.; de Jong, M. Classifying Pathways for Smart City Develop-
ment: Comparing Design, Governance and Implementation in Amsterdam, Barce-
lona, Dubai, and Abu Dhabi. Sustainability 2020.
Noori, N.; de Jong, M.; Hoppe, T. Towards an Integrated Framework to Measure
Smart City Readiness: The Case of Iranian Cities. Smart Cities 2020.
Noori, N.; Hoppe, T.; De Jong, M.; Stamhuis, E. Introducing a Conceptual Frame-
work to Analyze Smart City Policy Transplantation. In Smart City: Strategies for
City Development and Innovation, 1st ed.; Philips, F., Oh, D., Eds.; World Scientific
Publishing Co (In press).
POLICY TRANSPLANTATION FOR SMART CITIES INITIATIVES NEGAR NOORI
