Exploratory Research on the Success Factors and Challenges of Smart City Projects
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Asia Pacific Journal of Information Systems
Vol. 24, No. 2, June 2014 http://dx.doi.org/10.14329/apjis.2014.24.2.141
1)
Exploratory Research on the Success Factors and
Challenges of Smart City Projects
Natalia Kogan*, Kyoung Jun Lee**
As urbanization and its consequences become the issue of modern cities, the concept of Smart City comes
as the solution. Though a lot of researches on the topic is done, still no clear definition is given for both:
Smart City itself and the factors of a successful Smart City. While most of the literature centers the role
of ICT it is not a sufficient condition for a city to become Smart; the role of intellectual capital is underestimated.
Using a collection of Smart City definitions across the time and providing concrete cases, this research seeks
to bridge definition gaps and creates a tool for understanding Smart Cities. Drawing on the findings of several
case studies, this research derives several explanatory factors. The citizen’s engagement and governance
are identified as the two key success factors of Smart City Projects along with ICT and other factors as
enablers.
The research has purpose as follows: 1) To bridge definition gaps of the “Smart City” by defining the
term “Smart City,” based on existing concepts and characteristic mechanisms across times.; 2) To develop
an analytical tool for Smart City success factors through Explanatory Variables.; and 3) To identify major
challenges and barriers of Smart City Projects implementations and to provide recommendations and solutions,
based on existing governmental initiatives and pilot projects.
The research contributes to the knowledge of smart cities and ICT integration for urbanization issues solution.
By applying the findings of this research at the managerial level stakeholders may benefit by getting higher
efficiency of the Smart City Projects and by utilizing knowledge and values of a Smart City Projects in a
prioritized way.
Keywords : Smart City, Success Factors and Challenges, Sustainable Urban Development, Citizens Engagement,
Role of ICT
* Corresponding Author, Natalia Kogan, KyungHee University, Department of Business Administration
** Professor at KyungHee University, Department of Business Administration
Exploratory Research on the Success Factors and Challenges of Smart City Projects
Ⅰ. Introduction mation, will face new challenges with the prog-
ress of urban communities. They will have to adapt
“Our cities are fast transforming into artificial accordingly for successful implementation of “Sus-
ecosystems of interconnected, interdependent in- tainable Development” and “Smart City” concept.
telligent digital organisms.” William J. Mitchell, As ABI Research predicted that while $8.1 bil-
MetropolisMag. lion was spent on smart city technologies in 2010,
In an era where telecommunications and social by 2016 that number is likely to reach $39.5 billion
networking dominate the social and cultural [Schelmetic, 2011]. As of today, there are 102
character of the population, reality shows that smart city projects worldwide, says ABI, with
they can influence where a person decides to Europe leading the way at 38 cities, North
settle. Bringing a revolutionary concept of sus- America at 35, Asia Pacific at 21, the Middle
tainable development, quality of life and in- East and Africa at six, and Latin America with
novative use of media, the “Smart City” concept two. This research will review 13 Smart City
now appears to be the wave of the future urban Projects, which are represented widely in the
planning. With the majority of people migrating media and ranked by major data institutions and
to urban communities management of public agencies. From these cases essential variables,
transport, infrastructure and development of a which are already recognized as the comprising
sustainable economy becomes more complex. factors of the success of Smart City Projects, while
According to statistics more than 50% of the new variables, which have not yet received the
world population (3, 5 bln) now is living in the recognition, will be discovered as well.
cities and by the year 2050 the percentage will
raise to 70%. Though cities occupy only 2% of 1.1 Methodology and Reason of Choice
the Global Land Area they consume 75% of all
energy and produce 80% of all CO2 emissions. Case study is chosen as a research method-
Growing needs of cities and its citizens urge ology for this thesis. Robert Yin’s work [Yin,
governments to underatke new «smarter» path 2002] and Izak Bensbasat Case Research Strategy
to utilize current and potential resources more [Bensbaat, 1987] are used as guiding principles
effectively and efficiently. Not only cities are the for case study research. As Benbasat noted the
main consumer of energy, they are also the main goals of the researcher and the nature of the
driving power, producing 50% of the world GDP research topic influence the selection of a strategy.
(cities with the population over 750 thousands) Here provided are 3 reasons why case study
and adding up to 10~15 trillion dollars to global research method is a viable option for information
GDP production. Governments now have to im- systems research:
plement sustainable development models, based 1. The researcher can study information systems
on renewable energy and technologies, that in a natural setting, learn about the state
change the structure of the industry and percep- of the art, and generate theories from practice.
tions of major players. Consequently, cities and 2. The case method allows the researcher to
citizens, as major stakeholders in this transfor- answer “how” and “why” questions, that
142 Asia Pacific Journal of Information Systems Vol. 24, No. 2Exploratory Research on the Success Factors and Challenges of Smart City Projects
is, to understand the nature and complex- case analysis and the extension of theory. Multiple
ity of the processes taking place. Questions cases yield more general research results, which
such as, “How does a manager effectively can be later used for stakeholders’ implications.
introduce new information technologies?” Multiple data collection methods are typi-
are critical ones for researchers to pursue. cally employed in case research studies. Ideally,
3. A case approach is an appropriate way to evidence from two or more sources will con-
research an area in which few previous stud- verge to support the research findings. Yin
ies have been carried out. With the rapid identifies several sources of evidence that work
pace of change in the information systems well in case research [Yin, 2002]. In this paper
field, many new topics emerge each year two major methods are used:
for which valuable insights can be gained 1. Documentation: written materials, ranging
through the use of case research. from memoranda to newspaper clippings
In this case above-mentioned methodology is to formal reports.
particularly appropriate for certain types of 2. Direct observations: absorbing and noting
problems, including those in which research details, actions, or subtleties of the field envi-
and theory are at their early, formative stages ronment [Webb and Campbell, 1966]. Also
[Bensbaat, 1987]. Smart cities constitutes a mul- physical artifacts such as devices, outputs,
tidisciplinary field of research and development tools, etc. are used for these purposes.
and despite various approaches from different
sources this field is still rather young and char- Ⅱ. Theoretical Background
acterized by constant technological change and
innovation. Also, researchers usually learn by 2.1 Smart City: Concept and Definition
studying the innovations put in place by practi-
tioners, rather than by providing the initial wis- Despite the fact that numerous articles and
dom for these novel ideas. researches have attempted to define the smart
Case Research strategy is well-suited to cap- city it is still fuzzy, as there is no uniform con-
turing the knowledge of practitioners and de- cept and different approaches are used for this
veloping theories from it. purpose. There is a need to define Smart City
Finally, this method allows to point out main in a more “gerenal” sense. To do this it is desir-
factors of Smart City projects and to make gen- able to look into the history of the smart city
eralizations to all stakeholders of Smart City definition starting from its “Theoretical Past”
Projects. till the “Economic Future.”
Multiple-case study research is desirable,
when the intent of the research is description, 2.2 Past: ICT-Driven City; Efficient
theory building, or theory testing. These three City; Cyber City; Digital City; U-City
correspond to Bonoma's design, prediction, and
disconfirmation stages, respectively [Bonoma, The history of smart cities begins in 1994,
1985]. Multiple-case designs also allow for cross- Netherlands, when the term Digital City was
Vol. 24, No. 2 Asia Pacific Journal of Information Systems 143Exploratory Research on the Success Factors and Challenges of Smart City Projects
launched as a virtual public domain [van den common though it is quite similar to U-City.
Besselaar and Beckers, 2005]. That was the period The difference of former is in the Degree of
which saw enormous growth in the Internet and Intelligence. Smart city is considered as a Post
increasing use of public media. Many researches Ubiquitous city. Newly introduced Smart City
began to pay attention to information and com- is a development from U-City after the in-
munication technologies (ICT). Other researchers troduction of smart phones, or similar tele-
at the Brookhaven National Laboratory made communication concept, which allows con-
public the ideas of Effecient Cities. By late 1999, nection of individuals to the city like human
when the commercial Internet came in its full neural network. Smart Cities assumes people
use such terms as Ubiquitous Computing, U-city, involvement and inter-communication. The sig-
Cyber city were presented, and finally in 2000 nificance of two assets-social and environmental
the idea of Smart City came into use. capital-distinguish smart cities from their more
It is worth to note the case of Korea in the technology-laden counterparts, drawing a clear
development of the term U-City. The term U-City line between them and what goes under the
is used here since 1998 after accepting the concept name of either digital or intelligent cities. Thus
of ubiquitous computing, a post-desktop model Smart City depends not only on the endow-
of human-computer interaction created by Mark ment of hard infrastructure (“physical capital”),
Weiser, the chief technologist of the Xerox Palo but also, and increasingly so, on the availability
Alto Research Center. There have been a lot of and quality of knowledge communication and
research in this field since 2002. As a result, many social infrastructure (“intellectual capital and
local governments in Korea have applied this social capital”) [Caragliu, 2009].
concept to various development projects since
2005. A ubiquitous city or U-city is a concept 2.4 Future: MESH City; Sense, Soft
of integration of ubiquitous computing within and “Warm” Technology City
an urban environment. It can be described as
a merge of information systems and social sys- More modern way of calling SMART cities
tems, where virtually every device and service is MESH cities [Komninos, 2001]. MESH stands
is linked to an information network through wire- for: M = Mobile (mobile devices and the net-
less networking and RFID tags and sensors [Lee, works that support them provide the bottom-up,
2013]. Anthony Townsend, a research director real-time information, conduit to supply feed-
at the Institute for the Future in Palo Alto, and back about a city, its users, and its systems),
a former Fulbright scholar in Seoul views U-city E = Efficient (about sustainability achieved through
as an exclusively Korean idea [O'connel, 2005]. effective use, monitoring and management of
energy, traffic, etc), S = Subtle (invisible and
2.3 Present: Intelligent City; non-intrusive systems, easy-to-use modern city
Knowledge City; Smart City systems for citizens), H = Heuristics (heuristics-
based continuous improvement, which makes
Nowadays the concept of Smart City is more the system self-reflexing, adaptive self-forming
144 Asia Pacific Journal of Information Systems Vol. 24, No. 2Exploratory Research on the Success Factors and Challenges of Smart City Projects
and citizen-focused). 2.5 Mechanisms and approaches to
In the future, ICT is going to develop to the Define Smart City Projects
soft as well as warm techniques [Shin, 2012].
Future of today's Smart Cities can be referred The singular definitions, mentioned above, are
to as Sense, Soft and Warm Technology City. not the only way to explain Smart City. Taking
Lee and Hancock categorize the definitions into consideration the fuzzy nature of the Smart
of Smart City by subjective view on them [Lee City definition it is better to summarize the char-
and Hancock, 2012]. Three definitive categories acteristics of a smart city, using the most common
are presented in the table below. characteristic mechanisms, which show the main
values a smart city project. Several mechanisms,
Working Definitions of a Smart City existing in the scientific researches are to be de-
Practitioners’s view scribed in this research:
A city “combining ICT and Web 2.0 technology
with organizational, design and planning efforts 1) Six–axes approach, suggested by European
to dematerialize, speed up bureaucratic processes Cities Project [Giffinger, 2007]
and help to identify new, innovative solutions to
2) Three dimensions mechanism by Korean
city management complexity, in order to improve
sustainability and livability” [Toppeta, 2010]. University Industrial Technical Force [Shin,
Scholars View 2012]
“A city is «smart» when investments in human 3) Smart Operation Model by ICT, Climate
and social capital and traditional transport and Group [Webb, 2011]
modern ICT communication infrastructure fuel
sustainable economic growth and a high quality
of life, with a wise management of natural re-
2.5.1 The Six-axes Approach,
sources, through participatory governance” [Hall, Suggested by European City
2000]. Project
City’s view
Smart City as a high-tech intensive and advanced The smart city model presented by European
city that connects people, information and city Cities Project defines a Smart City as a city well
elements using new technologies in order to
performing in 6 main characteristics, built on
create sustainable greener city, competitive and
innovative commerce and an increase life quality the ‘smart’ combination of endowments and ac-
with a straightforward administration and main- tivities of self-decisive, independent and aware
tenance system of city” [Barcelona City Hall, 2011]. citizens.
above presents the concept of
There are mechanisms and approaches to de- Smart Cities as a complex of components from
fine the term, such as: six-axes approach by environmental to social perspective. The ability
European City Project; three-dimensions mecha- to integrate these components with the help of
nism by Korean University Industrial Technical innovative technologies will therefore ensure
Force; Smart Operation Model by ICT from project success. In summary, a Smart city re-
Climate Group, etc. mains:
Vol. 24, No. 2 Asia Pacific Journal of Information Systems 145Exploratory Research on the Success Factors and Challenges of Smart City Projects
Six axes Approach by European City Project
SMART ECONOMY SMART PEOPLE SMART GOVERNANCE
(Competitiveness) (Social and Human Capital) (Participation)
Innovative spirit Level of qualification Participation in decision-making
Entrepreneurship Affinity to life long learning Public and social services
Economic image and trademarks Social and ethnic plurality Transparent governance
Productivity Flexibility Political strategies and Perspectives
Flexibility of labor market Creativity
Embedded Internationally Cosmopolitanism/Open
Ability to transform mindedness
Participation in public life
SMART MOBILITY SMART ENVIRONMENT SMART LIVING
(Transport and ICT) (Natural resources) (Quality of life)
Local accessibility Attractiveness of natural Cultural facilities
(Inter-) national accessibility conditions Health conditions
Availability of ICT infra Pollution Individual safety
Sustainable, innovative and safe Environmental protection Housing quality
transport systems Sustainable resource Education facilities
Management Touristic attractiveness
Social cohesion
1) a city, where citizens and services pro- 2.5.2 Three dimensions Mechanism
viders have an access to enhanced inform- by Korean University Industrial
ation flow. Technical Force
2) such city maximizes the utilization of its
key resources by leveraging data gathered Another mechanism to describe a Smart city
through widespread embedded sensors and
is Three Dimension Mechanism, developed by
controls, real time data analytics and ubi-
UNITEF, Korean University Industrial Technical
quitous communications.
Force. It is not a secret that Korea is at the top
3) a city, which combines disparate data sets
of leading countries in IT sector and it also leads
to offer productivity insights and enhance-
the development of smart city concepts with
ment to its citizens and service providers.
it government and corporate agencies. Accor-
4) a city, which maximizes the economies of
ding to the UNITEF the first and most important
scope and scale across its multiple infra-
structure layers through a common service issue is the infrastructure of the smart city such
delivery platform, or Urban Operating as platform, security, and service scenario. The
System (“Urban OS”). second issue is the paradigm of smart city such
5) a city, which uses innovative technology as role-play between Central Government and
and innovation to strive to go beyond eco- Local Government. The third issue is the con-
nomic targets, to deliver sustainable, qual- sulting in order to have the best service model
ity of life improvements for its citizens, its according to many types of organs, and busi-
industry and the local environment. ness.
146 Asia Pacific Journal of Information Systems Vol. 24, No. 2Exploratory Research on the Success Factors and Challenges of Smart City Projects
Role play between
Platform Projects, as stated by different organizations, we
Security
Central Government
& Local Gevernment
Service Scenario could find even more definitions. The European
IT & ICT
Union sees it as an urban growth in a Smart
Sense for its metropolitan city-regions [Del Bo,
2008].
Consulting as a best
Service Model At a mesoregional level, we observe renewed
attention for the role of soft communication
Three Dimension Mechanism to Define infrastructure in determining economic perfor-
a Smart City mance [Paskaleva, 2009]. However, the avail-
ability and quality of the ICT infrastructure is
2.5.3 Smart Operation Model by ICT
not the only definition of a smart or intelligent
from Climate Group
city. Other definitions stress the role of human
capital and education and learning in urban
Climate Group suggests another Smart City
development. It has been shown, for example,
Operation model. As presented on the picture
that the most rapid urban growth rates have
below (See ), it is a complex system
been achieved in cities where a high share of
of values with the TECH as the core. This mod-
educated labor force is available [Komninos,
el emphasizes Policy and Funds as two pillars
2009].
of harmonic functioning and support system
Despite their abundance and difference all
for the Smart City Project. Public education, in-
these concepts in their separateness cannot pro-
centives, coordination mechanisms serve as
vide a full complex of values and a complete
tools for effective operation and values gen-
definition, derived from concrete examples and
eration of the Smart City Project.
cases of real Smart City Projects. Using already
existing concepts and approaches and analy-
zing 13 cases of Smart City Projects, this paper
will attempt to derive full complex of variables
including those, which are not yet covered in
the academic literature, to define the term “Smart
City.” By analyzing cases this paper will define
the main factors of a Smart City’s success. These
factors, brought together, will comprise an es-
Smart Operation Model by ICT, Climate
sential tool for understanding smart cities ini-
Group
tiatives and advancing the vision of charac-
The models, mentioned above, are only a few terizing smart city design initiatives, implemen-
operational models to define Smart City Projects, ting shared services and navigating their emer-
and all they put different factors as a core for ging trends and challenges. This tool will also
the success of the Smart City Project. If we take make the concept of a Smart City Project more
a more detailed look on the core of Smart city applicable and will help to understand how
Vol. 24, No. 2 Asia Pacific Journal of Information Systems 147Exploratory Research on the Success Factors and Challenges of Smart City Projects
each factor works for each case, and what ac- sentativeness of cases used for analysis, so as
tions are to be undertaken from a managerial to include the most renowned and highly cov-
perspective. ered ones in recent researches, and those, which
have not yet received attention of ranking in-
Ⅲ. Analysis of Smart City stitutes, but are increasingly referred to as the
Projects ones, deserving consideration.
There are many rankings relevant to Smart
3.1 Reason of choice for Case Studies Cities. This paper uses rankings, developed by
researchers and research institutes.
Before introducing cases and variables, used Let’s first consider the ranking, developed by
in this research it is worth mentioning, that Boyd Cohen, who is a climate strategist and the
though a lot of data about existing Smart Cities CEO of CO2 IMPACT. He leveraged about a doz-
is given, some cities still may not be taken into en global and regional rankings of smart-city
account due to rapidly changing statistics on components in order to develop a global ranking
this question. That’s why none of the statistics of smart cities (see below).
about Smart Cities, presented in the media, Cohen referred to the rankings of the following
would guarantee its accuracy and fair repres- research organizations and institutions;
entativeness. By using the most recent data on 1) Innovation Cities ranking by 2 thinknow
Smart Cities and emerging projects from major (to get a fair comparison of the level of
research institutes, this research will attempt to innovation in top global cities)
provide more accuracy by distributing repre- 2) Rankings of the quality of life of cities and
Global Ranking of Smart Cities by B. Cohen
Innovation Quality
CITY Region Green City Ranking* Digital City Ranking
Ranking of Life
1 Vienna EURP 5 4th in Europe 1 8
2 Toronto NA 10 9th in North America 17 10
3 Paris EURP 3 10th in Europe (RC: 6) 30 11
4 New York NA 4 3rd in North America (RC: 8) 47 4
5 London EURP 11 11th in Europe (RC: 9) 38 13
6 Tokyo ASIA 22 Above Average in Asia (RC: 10) 46 15
7 Berlin EURP 14 8th in Europe 17 32
8 Copenhagen EURP 9 1st in Europe (RC: 1) 9 39
9 Hong Kong ASIA 15 Above Average in Asia 70 3
10 Barcelona EURP 19 NR in Siemens (RC: 3) 40 NR in DCR (IDC: 2)
10 Boston NA 1 6th in North America 36 NR in DCR (DC: 8)
10 Sydney ASIA 20 N/A Siemens (RC: Runnerup) 11 33
*
RC-Resilient Cities Ranking.
**
NR means not rated in Digital Governance Survey/(IDC and DC rankings used instead.
148 Asia Pacific Journal of Information Systems Vol. 24, No. 2Exploratory Research on the Success Factors and Challenges of Smart City Projects
infrastructure levels (Mercer survey: 2012 of 75,000 to 124,999 population are presented,
Quality of living worldwide city rankings) following top 10 priorities:
3) Siemens regional rankings of green cities 1. Open Government/Transparency/Open
4) The digital city rankings of Digital Commun- Data
ity for cities in the U.S. (see ) 2. Mobility/Mobile Applications
5) The IDC rankings of smart cities in Spain 3. Budget and Cost Control
(indicated as IDC in the ) 4. Hire and Retain Competent IT Personnel
6) The digital governance in municipalities 5. Broadband and Connectivity and Portal/
worldwide study to compare cities on E-government
their innovative use of ICT. Besides, the 6. Cyber Security
following rankings were used in this pa- 7. Shared Services
per as well: 8. Cloud Computing
7) Rankings and data by Alcatel Lucent, Cli- 9. Disaster Recovery/Continuity of Operations
mate Group, Arup, Smart Cities Council. 10. Virtualization: Server, Desktop/Client, Sto-
8) IBM’ “Smarter Cities Challenge” (competi- rage, Applications.
tive grant program to award $50 million Innovation Cities Global Index 2012~2013 from
worth of technology and services to 100 2 thinknow used in B. Cohen’s work, is another
municipalities way of ranking, which is considered as the most
Rankings, offered by Digital Community for comprehensive city ranking and scoring. The
the cities in the U.S. choose the top digital cities, process of scoring is explained below.
leading in open data, transparency efforts and Each city was selected from 1,540 cities based
innovation in deploying mobile applications to on basic factors of health, wealth, population,
citizens while conforming to fiscal standards. In geography as well as potential relative to peers.
the top ten cities within the category The final 450 cities had data extracted from the
city benchmarking data program on 162 in-
13th Annual Digital Cities Survey dicators, and this was reduced to 445 published
75,000~124,999 population category cities. Each of the benchmarking data was scor-
1st City of Avondale, Ariz. ed by analysts, using best available qualitative
2nd City of West Palm Beach, Fla. analysis and quantitative statistics. Underlying
3rd City of Roseville, Calif.
data was then balanced against current global
4th City of Westminster, Colo.
5th City of Lowel, Mass. trends by analysts to form a simplified 3 factor
5th City of Davenport, Iowa score for Cultural Assets, Human Infrastructure
5th City of Richardson, Texas and Networked Markets [Tothinknow, 2013]
6th City of Lynchburg, Va. For city classification, these scores were com-
7th City of Independence, Mo.
petitively graded into 5 bands (Nexus, Hub,
8th City of Arvada, Colo.
8th City of Boulder, Colo
Node, Influencer, Upstart) based on how broad
9th City of Roanoka, Va. based (multiple indicators) the city perform-
10th City of Pueblo, Colo. ance was. As per Innovation Cities Global
Vol. 24, No. 2 Asia Pacific Journal of Information Systems 149Exploratory Research on the Success Factors and Challenges of Smart City Projects
Innovation Cities Global Index 2012～2013 from 2 thinknow
# Rank City Country Region Sub Region Class Score Index
1 3 Vienna Austria EUROPE EURP 1 nexus 57
2 5 Paris France EUROPE EURP 1 nexus 56
3 9 Amsterdam Holland EUROPE EURP 1 nexus 55
4 24 Manchester UK EUROPE EURP 1 nexus 52
5 30 Singapore Singapore ASIA ASIA 1 nexus 51
6 34 Dubai UAE MIDDLE EAST MID-EAST 1 nexus 50
7 36 Helsinki Finland EUROPE EURP 2 HUB 49
8 38 Oslo Norway EUROPE EURP 2 HUB 49
9 56 Barcelona Spain EUROPE EURP 2 HUB 48
10 123 Boulder, Colorado USA S. AMERICA USA 2 HUB 45
11 N/A Malaga Spain EUROPE EURP 3 NODE 40
Rankings all cities are graded into award cate- 1) We choose 11 cases from 2 thinknow Inno-
gories based on their band score in descending vation Cities Global Index as these cities
order of importance to the innovation economy: are most frequently appear in the ranking
1) NEXUS: Critical nexus for multiple eco- lists of the relevat research institutes across
nomic and social innovation segments; different regions. Among them Vienna,
2) HUB: Dominance or influence on key eco- Paris and Barcelona are also appear in B.
nomic and social innovation segments, Cohen’s Global City Rankings.
based on global trends; 2) Other cases, also appearing frequently in
3) NODE: Broad performance across many in- the media, though somewhat less clear
novation segments, with key imbalances; and simetimes contradicting in assessment
4) INFLUENCER: Competitive in some seg- by ranking institutions, are cases, like
ments, potential or imbalanced; Kochi, Amsterdam, and Malta, as they ap-
5) UPSTART: Potential steps towards relative pear in Smart Cities Readiness Guide by
future performance in a few innovation Smart Cities Council [Berst, 2013]. While
segments. From the above we Amsterdam appears under the ranking 9th
can see that 11 out of 13 cases, presented in the Innovation Cities Global Index from
in this paper later, are included into 3 first tothinknow, Malta case is reviewed in
categories (NEXUS, HUB and NODE) of Smart Cities Council Readiness Guide by
Innovative Cities Global Index. 2 thinknow.
Being guided by rakings from different in- We can see the difference in rankings, given
stitutions and researches we then choose the by different institutions and researches. Thus
cases randomly, taking into account the fre- Cohen ranks Vienna, Paris and Barcelona as num-
quency of their appearance in the ranking lists, ber 1, number 3 and number 10 (see ),
as follows: while Innovation Cities Global Index ranks them
150 Asia Pacific Journal of Information Systems Vol. 24, No. 2Exploratory Research on the Success Factors and Challenges of Smart City Projects number 3, number 5 and number 56 respectively While SmartCity Council ranking shows only (. Singapore goes at the ranking #30 positive side of Amsterdam City (such as ICT (Mid-East Region, Nexus 1, index score 50), and Governance) we will show later in this pa- Dubai, goes few positions below at the rank # per, that Amsterdam lacks some crucial essence 34 (Mid-East Region, Nexus 1, index score 50), to be called Smart City, as the project couldn’t Helsinki is ranked #36 (Europe, 2 HUB, index satisfy the needs of citizens, failed to get the score 49), Oslo ranked #38, Europe, 2 HUB, index feedback and cooperation from the stake- score 49). Then goes Manchester at rank #106 holders, what ultimately led to its “death” [van (USA, 2 HUB, index score 46), Boulder at rank den Besselaar and Beckers, 2005]. 123 (USA, 2 HUB, index score 45) and Malaga, The same can be said about Malta and Kochi which is not ranked but goes under NODE 3, cases, which have contradicting assessments by with index score 40. different researchers. That’s why further de- As mentioned above, Boulder has been ranked tailed analysis of cases is necessary to provide by Digital Cities Survey in 75,000 to 124,999 comprehensive assessment of the cases taking population category and positioned at number into account all recently available data from the 8 (see ). media and researches. Thus, to keep representativeness ballance we chose cases with different band scores (Nexus, 3.2 Reason of Choice for Variables Hub, Node), different categories (population category) and methods (individual researcher Just as the definition of the term “Smart City” B. Cohen versus Research Institutions) is not yet fixed among researchers there are no However, we should note that assessments standards, rules or fixed sets of variables to de- and rankings of the above-mentioned organ- fine Smart City Project’s success. The plenteous- izations (Smart City Council, Digital Cities ness of Smart City Projects, named successful Survey, etc.) serve only for initial choice of cas- in the media and existing researches will not es and can not guarantee the status of the con- guarantee the fact, that all essential factors were crete case as a success or failure, before a more included, while determining Smart City success. detailed case analysis is done. This relates to It is explained by the variety of variables, ex- specific cases, like Amsterdam, Malta, Boulder, plaining different cases and the “novelty na- which though have being ranked highly by ma- ture” of such variable considering the rapidly jor assessing institutions, yet not finally recog- changing statistics and trends on Smart City nized as successful, given the results of case Projects. The variables set can not be fixed in analysis in this paper and data from other exist- time as more values will be added for Smart ing researches and media sources. That’s why City definition as time goes by. Rather it should it is important to cover full set of variables re- be logically flexible, leaving the space for new sponsible for Smart City Project success, which factors to be included. With the above-men- certain research institutes ranking lists are miss- tioned in mind this paper will not only take ing out. into account existing factors, from available Vol. 24, No. 2 Asia Pacific Journal of Information Systems 151
Exploratory Research on the Success Factors and Challenges of Smart City Projects
sources, but also develop new factors by either organization, technology, governance, policy
combining several existing factors into one or context, people and communities, economy, built
coming up with new factors, not yet covered infrastructure, and natural environment. These
in previous researches. For this purpose differ- factors form the basis of an integrative framework
ent sources of variables are to be used, such that can be used to examine how local govern-
as: ments are envisioning smart city initiatives. The
1) Smart City Initiatives Framework (see framework suggests directions and agendas for
). smart city research and outlines practical im-
2) The Smart Cities Wheel, B. Cohen (see plications for government professionals. The
). framework addresses several internal and ex-
3) Research by A. Caragliu, Del Bo, and P. ternal factors that affect design, implementation,
Nijkamp [Caragliu, Del Bo, and Nijkamp, and use of smart cities initiatives. The goal is
2009]. not to produce a set of components to rank smart
4) Six-Axes Approach by European City cities, but to create a framework that can be used
Council () as well can be used to characterize how to envision a smart city and
as an example of variables generation. design initiatives, which advance this vision by
implementing shared services, and navigating
3.2.1 Smart city Initiatives Framework their emerging challenges. The eight clusters of
factors include (1) management and organ-
Based on the exploration of a wide and ex- ization, (2) technology, (3) governance, (4) policy,
tensive array of literature from various dis- (5) people and communities, (6) the economy,
ciplinary areas authors identify eight critical fac- (7) built infrastructure, and (8) the natural
tors of smart city initiatives: management and environment.
Smart City Initiatives Framework
152 Asia Pacific Journal of Information Systems Vol. 24, No. 2Exploratory Research on the Success Factors and Challenges of Smart City Projects Though this integrative framework suggests fluenced more than influential inner factors ICT as key drivers of smart city initiatives, au- (technology, management, and policy) before thors note that despite proclaimed advantages affecting the success of smart city initiatives. and benefits of ICTs use in cities, their impact This counts for both direct and indirect effects is still unclear. Indeed, they can improve the of the outer factors. quality of life for citizens, but they can also in- As authors suggest, technology may be con- crease inequalities and promote a digital divide. sidered as a meta-factor in smart city initiatives, Thus, city managers should consider certain since it could heavily influence each of the oth- factors when implementing ICT with regard er seven factors. Due to the fact that many to resource availability, capacity, institutional smart city initiatives are intensively using tech- willingness and also with regards to inequality, nology, it could be seen as a factor that in some digital divide and changing culture and habits. way influences all other success factors in this Authors suggest each of the factors as im- framework [Hafedh et al., 2012]. However, later portant to be considered in assessing the extent in this research ICT will be given a different of smart city and when examining smart city role as an enabler. initiatives. The factors provide a basis for com- paring how cities are envisioning their smart 3.2.2 The Smart Cities Wheel, by B. initiatives, implementing shared services, and Cohen the related challenges. This set of factors is also presented as a tool to support understanding Let’s now turn to another variables system, of the relative success of different smart city ini- used by B.Cohen: “Smart Cities Wheel.” tiatives implemented in different contexts and This model has been inspired by the work for different purposes. Similarly, this frame- of many others, including the Center of Regional work could help to disentangle the actual im- Science at Vienna University of Technology, pact on types of variables (organizational, tech- Siemens’ work with the Green City Index, and nical, contextual) on the success of smart city Buenos Aires’ “Modelo Territorial” among oth- initiatives. ers). Boyd used blended data from publicly avail- In their work authors see all factors having able sources, with this primary data provided a two-way impact in smart city initiatives (each by some of the eligible cities in an effort to en- likely to be influenced by and is influencing hance the accuracy of the 2013 rankings. Therefore other factors), at different times and in different the results include data from: the Innovation contexts, some are more influential than others. Cities Index, Brookings Metro Monitor for the In order to reflect the differentiated levels of Smart Economy measurement; Corporate Knights, impact, the factors in our proposed framework Siemens and the Green Building Councils for are represented in two different levels of in- Smart Environment; Digital Governance Rankings fluence. Outer factors (governance, people and from Rutgers and open databases counted from communities, natural environment, infrastructure, municipal open data sites for Smart Governance; and economy) are in some way filtered or in- ranking data from Mercer and Monocle for Smart Vol. 24, No. 2 Asia Pacific Journal of Information Systems 153
Exploratory Research on the Success Factors and Challenges of Smart City Projects
Living; modal share data from various sources ipation in co-design. Sustainability is also seen
and bike sharing data from Bike-Sharing World here as a major strategic component of smart
Map for Smart Mobility; and Citi Hot Spots and cities. The move towards social sustainability
GINI inequality index data for assessing Smart can be seen in the integration of e-participation
People [Cohen, 2012, ubmfuturecities.com]. techniques such as online consultation and de-
liberation over proposed service changes to
support the participation of users as citizens in
the democratisation of decisions taken about fu-
ture levels of provision, [Caragliu, Del Bo, and
Nijkamp, 2009]. The system of variables, de-
rived in this research after case analysis, takes
into account all aspects of traditional definitions
and alternative approaches to make it more
comprehensive and inclusive. Based on the
Six-axes approach (), Smart City
Initiatives Framework (), The Smart
Cities Wheel, by B. Cohen () and oth-
er mechanisms and factors to define Smart City,
we derive 7 factors to define Smart City Project
The Smart Cities Wheel by B. Cohen success. As mentioned before some factors will
be combined to form new ones, while others
3.2.3 Research by Andrea Caragliu and will remain the same. Thus, we will be able to
Peter Nijkamp "Smart Cities in include the factors, which yet has not been cov-
Europe" ered in previous researches. Each factor will be
valued a Strong (S), Medium (M) or Weak (W),
However all the variables systems mentioned depending on the level of the certain value in
above do not highlight the role of citizens en- each Smart City case.
gagement, which is used in some alternative
approaches to smart city projects definition. 3.3 Variables Generation and Analysis
An alternative approach by Andrea Caragliu
gives profound attention to the role of social While an exact definition has yet to be
and relational capital in urban development. formed, a smart city provides high quality of
Here, a smart city will be a city whose com- life to its citizens with the following seven driv-
munity has leart to learn, adapt and innovate. ers acting as forces of innovation. These seven
This can include a strong focus on the aim to drivers are used as an explanatory variables
achieve the social inclusion of various urban further in research to define the success or fail-
residents in public services (e.g. Southampton's ure of the certain Smart City Project. The factors
smart card) and emphasis on citizen partic- are as follows:
154 Asia Pacific Journal of Information Systems Vol. 24, No. 2Exploratory Research on the Success Factors and Challenges of Smart City Projects
1. Human Capital (which refers to level of 3.3.2 Social Capital
capital, education, awareness, wealth and
welfare of the people); While Social Capital also refers to people and
2. Social Capital (which is basically a level citizens just as the first factor here the priority
of cooperation and trust within and to the of consideration is given to the level of coopera-
socium and to all stakeholders, including tion, partnership and trust among all stake-
corporations, government, etc.); holders (corporations, customers, government,
3. Level of Economy (which is a mixture of etc.) and communication within the socium
business approaches, holistic and syn- [Hafedh et al., 2012]. Addressing this two fac-
ergetic planning of the city initiatives, flex- tors in general, and the topic of people and
ibility of the labor market and the like); communities in particular as a part of smart cit-
4. Governance (which includes good manage- ies is critical, and traditionally has been ne-
ment with open data and other innovative glected on the expense of understanding more
forms of governance, like e-governance); technological and policy aspects of smart cities.
5. Environmental Sustainability (which is based Projects of smart cities have an impact on the
on green technologies, an “doing-more- quality of life of citizens and aim to foster more
with-less” principle); informed, educated, and participatory citizens.
6. Infrastructure (basic, built, mobile) and ICT; Additionally, smart cities initiatives allow
7. Civic Engagement (which emphasizes cus- members of the city to participate in the gover-
tomer centricity and gives citizens’ major nance and management of the city and become
role to play in the development of the active users. If they are key players they may
Smart City Project. Below there is a more have the opportunity to engage with the ini-
detailed analysis of all 7 factors. tiative to the extent that they can influence the
effort to be a success or a failure. It is critical
3.3.1 Human Capital also to refer to members of the city not only
as individuals, but also as communities and
Human capital is a mixed factor and includes groups and their respective wants and needs
the level of capital, education, awareness, wealth within cities. People and communities is a com-
and welfare of the people. Several cities nowa- ponent that requires smart cities initiatives to
days have started transformational projects and be sensitive in balancing the needs of various
initiatives called “smart city initiatives” to bet- communities.
ter serve citizens and to improve their quality
of life [Giffinger, 2007]. That’s why Human 3.3.3 Economy
Capital along with the Social Capital, following
below, is now receiving more attention from the Level of Economy, which includes the level
City Management as the shift has been made of business development, holistic and syner-
from the “hard” ICT core toward its “soft” and getic planning of the City Initiatives. Giffinger
“social” end. also suggests innovation, entrepreneurship, pro-
Vol. 24, No. 2 Asia Pacific Journal of Information Systems 155Exploratory Research on the Success Factors and Challenges of Smart City Projects
ductivity, flexibility of the labor market as well governance depends on the implementation of
as the integration in the national and global a smart governance infrastructure that should be
market as the compounds of Economy factor accountable, responsive and transparent [Mooij,
for the Smart City. It is crucial for a Smart City 2003]. This infrastructure helps allow collabo-
to create a beneficial environment to get such ration, data exchange, service integration and com-
economic outcomes as business and job crea- munication [Odendaal, 2003].
tion, workforce development, and productivity
improvement [Giffinger, 2007]. Studies by IBM 3.3.5 Environmental Sustainability
institute for Business Value also identify Busi-
ness as one of the core systems of smarter cities, Environmental Sustainability is based on green
comprising city services system [Dirks and technologies, an “doing-more-with-less” princi-
Keeling, 2009]. Capacities for smart business ple. Smart city initiatives are forward-looking
systems include ICT use by firms, new smart on the environmental front [Giffinger et al.,
business processes, and smart technology 2007]. Core to the concept of a smart city is the
sectors. The smart city initiatives are designed use of technology to increase sustainability and
to develop information technology capacities to better manage natural resources. Of a par-
and establish an agenda for change by industry ticular interest is the protection of natural re-
actions and business development [Cairney and sources and the related infrastructure [Hall,
Speak, 2000]. 2000], such as waterways and sewers and green
spaces such as parks. Together these factors
3.3.4 Governance have an impact on the sustainability and liv-
ability of a city, but in our case, Environmental
Governance factor is comprised of manage- Sustainability will be not influential (input)
ment, open data and other innovative approaches factor, but an influenced (output) factor. So
to data management, like e-governance. As of even though it was taken into consideration
now, “smart government” is defined as an admin- when examining smart city initiatives, it will be
istration, which integrates information, communi- removed from the comparative analysis.
cation and operational technologies, optimizes
planning, management and operations across 3.3.6 Infrastructure (Basic, Built, Mobile)
multiple domains, process areas and jurisdictions and ICT
and generates sustainable public value. Smart
governance is described as an important charac- Infrastructure has several meanings, depend-
teristic of a smart city that is based on citizen ing on the term of context used in. In this re-
participation [Giffinger, 2007] and private/public search we refer to the complex of basic, built
partnerships [Odendaal, 2003]. Several cities have and mobile infrastructure (hard infra) as well
felt an increased need for better governance to as the innovative environment in a city, with
manage their projects and initiatives [Griffith, the infrastructure of supporting technologies,
2001]. According to Johnston and Hanssen, smart communication and service delivery among
156 Asia Pacific Journal of Information Systems Vol. 24, No. 2Exploratory Research on the Success Factors and Challenges of Smart City Projects
government, businesses, and citizens (soft in- as a major opportunity to merge power and ICT
fra). We will review each component in details industries and technologies. Thus, the imple-
below. mentation of an ICT infrastructure is funda-
mental to a smart city’s development and de-
(1) Basic Infrastructure pends on some factors related to its availability
In terms of utility and facility functional op- and performance. Indeed, smart object net-
erations, the infrastructure represents the un- works play a crucial role in making smart cities
derground and aboveground cables and pipes a reality. However, despite proclaimed advan-
networks, supported with all related assets. The tages and benefits of ICTs use in cities, their
primary concept of establishing the digital in- impact is still unclear. They can improve the
frastructure networks is to distribute a suffi- quality of life for citizens, but they can also in-
cient number of sensors that meet the needed crease inequalities and promote a digital divide.
level of assets connectivity and control. The net- Thus, city managers should consider certain
work utilizes a variety of communication links, factors when implementing ICT with regard to
including optical fiber, microwave, packet ra- resource availability, capacity, institutional
dio, satellite, and acoustic, resulting in diversity willingness and to inequality, digital divide,
of throughput, latency, and intermittence through- changing culture and habits [Jasseur, 2010].
out the network.
3.3.7 Civic Engagement
(2) Built Infrastructure
It encompasses every object, comprising the This variable can be called “secret ingridient”
“Hard Core” of the City: Buildings, Transportation, that turns the idea of a smart city into reality.
Energy and Power Systems. In a nutshell, we’re talking about people-elected
officials, city planners, policymakers, citizens,
(3) Mobile Infrastructure business leaders, financiers and public-private
It is a complex of all mobile devices, which partnerships [Berst, 2013]. In general, this di-
enables people to access Internet and informa- mension relates to the abilities, behavior, and
tion from their personal mobile phones, tablets, experience of citizens in ICT applications and
etc. services of the city. Civic Engagement under-
lines all above-mentioned factors, as citizens are
(4) ICT Infrastructure the main actors, playing the central role in the
ICT infrastructure, just as basic infrastruc- development of a Smart City. Citizens are en-
ture, includes wireless infrastructure, but in a gaged in the Smart City development process
more complex way (fiber optic channels, Wi-Fi in a million ways as providers or consumers
networks, wireless hotspots, kiosks, etc.) [Al-Hader of information and data, generators of ideas
and Rodzi, 2009]. It encompasses intelligent and initiatives through crowdsourcing and
systems and integrated communication infra- SNS, they are also called prosumers as their role
structure, such as Smart grids, which are seen of consumers and producers became mixed in
Vol. 24, No. 2 Asia Pacific Journal of Information Systems 157Exploratory Research on the Success Factors and Challenges of Smart City Projects
the recent economy trends. This encompasses ter conservation and therefore the smart sol-
the outreach, inclusion and cooperation cities utions will see a bias towards water conserv-
need to get the best results from technology ation. In other European countries the issue is
investments. Experience has proven that for discussed mainly from the standpoint of the so-
smart cities to work, citizens must be consid- ciety to be established through Smart Cities.
ered and consulted from day one and at every Singapore, due to its density of population, is
step along the way. Fortunately, social media an incubator for creative innovation. People are
and web portals make citizen engagement far playing the main role in the success of building
easier today. the Smart Singapore City. Dubai is introducing
the state-of-the-art technology into the concept
3.4 Analysis of Smart City Case Studies of urban development under the theme “digital
city” or “wireless city.” Dubai Internet City will
After we defined explanatory variables it is be reviewed later in this research as one of the
time to see how each variable is presented in 13 Smart City Projects.
a certain Smart City case and what’s the influ- Thus, as Simon Giles states it, Cities are con-
ence of variables on the case’s outcome. stantly trading off priorities and addressing leg-
Before analyzing concrete examples of Smart acy challenges; as such, they will define their
City Projects a brief look at the current global smart city agenda in necessarily differing terms.
state-of-the-art city construction trends shows Again, as been mentioned above, the concept
that smart-cities are being built in consideration of smart cities goes far beyond the technological
of each nation’s unique characteristics [Glaeser progress and pass, first of all by the citizens and
and Berry, 2006]. Different cities have different how the city managers will make citizens theirs
legacies driven by their historic economic and priority. Obviously, good governance of the city
political development, geographical form, en- is undoubtedly another key factor of success for
ergy mix, demographic structure etc. Even cit- a city to become “Smart.” In this case, good go-
ies with similar legacies will differ as their po- vernance as an aspect of a smart administration
litical administrations have differing political often referred to the usage of new channels of
priorities. Each Smart City has characteristics communication for the citizens.
and objectives specific to its situation. For ex- Let’s now analyze Smart City Projects one by
ample, Copenhagen has the ambition to become one in order to find out the “essence” of a smart
carbon neutral by 2025 and to create a world- city. First 4 cases are characterized in .
class hub for clean technology. In Japan Smart As mentioned before, 13 cases, which has
Cities are discussed in the context of environ- been chosen as the most representative, will be
mental issues, so Green City concept is stressed reviewed in this paper in order to carry out a
there. This is something that will be prioritized comprehensive assessment of Smart Cities’
to a greater or lesser extent and will therefore Successful Factors. As the assessment proceeds
define the nature of the smart city strategy. In we can keep some factors, while excluding oth-
a city like Madrid the emphasis may be on wa- ers, which are not directly explaining the out-
158 Asia Pacific Journal of Information Systems Vol. 24, No. 2Exploratory Research on the Success Factors and Challenges of Smart City Projects
Characteristics of Failure Projects
V Amsterdam Malta Kochi (India) Colorado
Medium. Innovative pi- Weak. Bad trans- Strong. Increasing living stand- Strong. People encour-
lots for data and mobi- portation sevices ards and human development aged innovation and the
lity, but lots of setbacks: [timesofmalta.com, indices. More attention is giv- industry’s move into the
failure to deliver right 2011] Malfunction of en to legal system. Empowerment digital age via “smart
info about railways/ meters [Barry, 2013] of women projects (Women- grid” [Helms, 2013] auto-
buses/in the right time. Malta is trailing behind operated auto taxis [KochiCity mated meters have al-
HC
[Houthuijzen, 2013] many other EU count- Forum, 2013] Emphasis on ready been widely de-
ries with its pension open society welcoming out- ployed by many utilities)
system [Taberner, 2013] siders to attract highly edu-
cated specialists and experi-
enced workers, as well as Foreign
Investments.
Weak. Ineffective citizens Strong. Communities and Weak. People are not ready to Weak. Non-awareness of
education system, non companies are invol- face changes, brought by ICT the project benefits and
responsive to citizens' ved into education pro- and Internet of Things. utilization causing by lack
complaints Users' com- cess. Emphasis on the Protests of citizens regarding of communication with
SC
plains about declining question of education: SmartCity initiatives, which lead the citizens [Helms, 2013].
service of DDS how to bring univer- to inconveniences in citizens’ Lack of communication
sities into Smart City lives with customers [King, 2010].
Malta).
Weak. Shortcomings in Weak. No agreed time Medium. Influence of Global Weak. Lack of planning
legitimacy, poor planning, on goals achievement, crisis, but Economy is rising and short seeing of the
high developing costs, no investments attracted due to special economic zones, upcoming scales and costs.
impossibility to manage as planned, detour of boosting FDI and overall in- The market hasn’t ma-
E the system the goal paths and con- fra, attractive IT sector, growth tured for the project
tradiction of the initial of residential, commercial
goal, no promised jobs and retail sector.
created [maltastar.com,
2012]
Weak. Starting as a grass- Weak. Incompetence, Weak. Delay of government Weak. Lack of planning,
root initiative DDS couldn’t non-ability to make up approval for city status and bad management, no clear
get support from govern- plans, costs overrun construction plan. Disputes in- goal, inability to look in-
ment, became a non-pro- [maltastar.com, 2011] side the government over the to the demand side of the
fit organization, and even- Government overpro- smart city project as an anti-na- project, cost over runs
tually transformed into a mised and undelivered. tional project [Neelakandan, [Helms, 2013]
private company. Its vul- [maltastar.com, 2012] 2011]. No tentative date fixed
nerability in a competitive Weak internal control, for launching work. All in-
G
market led to its demise. failure to meet obliga- habitants on the 136 acres
tions regarding Smart moved out KOCHI: The global
City [timesofmalta.com, economic meltdown, technical
2011], [timesofmalta.com, hassles, procedural delays and
2012] a host of other factors are hold-
ing up the implementation of
the proposed SmartCity Kochi
[The Hindu and Kerala, 2011]
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