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INTRODUCTION

Arturo Bris, Christos Cabolis and Bruno Lanvin

According to the United Nations, in 1960 almost 34% of the global population lived in urban settings. Half a century later, in 2010, nearly 52% of the world’s population inhabited cities; a number that is estimated to reach 68% by 2050. 1 Urbanization affords many benefits to city dwellers that stem from decreasing the transaction costs associated with fulfilling their needs. Be it the labor market, the goods market, or the services market, living in an urban environment increases both the quality of and the options available for work, schools, cultural events and entertainment. No benefit comes without a cost, however; the downsides of living in a city vary from congestion and traffic to crime, pollution, corruption and poverty. For years, numerous studies have explored ways to balance the advantages and disadvantages of urbanization. The most recent evolution of sorting these trade-offs with the objective of creating a “better” urban environment is the design of “smart cities.” “Smart city” is a term used widely to describe residential areas that apply technology to enhance the benefits and diminish the shortcomings of urbanization. A Google search delivers 41 million results for the exact term “smart city,” while a search for a smart city definition returns almost 3 million entries. Indeed, an attempt to provide a precise and yet universally acceptable definition of a smart city is an impossible task. A similarly overwhelming undertaking is how to identify “best practices” that make a city smart. A partial answer may be offered by the available rankings of smart cities. A more detailed examination suggests that those rankings tend to concentrate on specific dimensions, such as competitiveness, mobility, quality of life and safety, among others; or focus on certain countries, such as Italy and the United Kingdom. There are several rankings of cities that evaluate a broader notion of smartness produced by academic institutions (IESE Business School at the University of Navarra, or the Center of Regional Science at the Vienna University of Technology), consulting firms (AT Kearney, Roland Berger, PricewaterhouseCoopers), providers of services (information and communication technology provider Ericsson, parking solutions provider EasyPark, or real estate agent Savills UK), to mention just a few. And there are plenty that concentrate on one or a few dimensions of smartness, be it, for example, competitiveness (Economist Intelligence Unit, Financial Times,

1 https://data.worldbank.org/indicator/sp.urb.totl.in.zs and https://www.un.org/development/desa/en/news/population/2018-revi- sion-of-world-urbanization-prospects.html, both accessed May 13, 2019.

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KPMG), mobility (Deloitte, Waze, TomTom), quality of life (Deutsche Bank, Mercer, UN Habitat), or sustainability (Siemens). There are also country-specific rankings of cities, such as the UK Smart City Index (Huawei); the Italia Smart City Index (Ernst & Young); and the Smart Dubai Index (Smart Dubai Initiative). However incomplete this short account of the landscape of rankings may be, it points out the stakeholders in a smart city undertaking. In addition to residents and local government, these include the private providers of services, entities that can study the needs and impacts of different options and, of course, the enterprises that provide local employment. It is, therefore, no easy task to navigate this landscape of smart city initiatives while doing justice to multiple (and sometimes conflicting) stakeholder interests. Why, then, do we need another project on smart cities, given the amount of information that is already out there? The simple answer is that it is exactly because of the extensive interest in smart cities that there is a need for a careful focus on the term and its measures. What exactly do we mean by classifying a city as smart and which entity makes this decision? Equally important is the question of quantifying the smartness of a city, especially since certain aspects are tangible and therefore, measurable, while others are intangible, yet there is a need to place them in a measurable framework. This book presents the first step towards a systematic study of what makes a city smart. What are the smart initiatives undertaken? Who decides on the projects? And how are the outcomes quantified? Our approach relies on an in-depth study of a specific group of cities, comparing them for potential common elements and differences. By exploring and comparing the cases of individual cities thoroughly, we shall contribute to the second step of our project, that is to outline a potential framework for designing and producing a smart city index. Smart city definition Several alternative dimensions have been suggested for the definition of a smart city. For instance, Albino et al. (2015) outline the notions of the intelligent, knowledge, virtual, ubiquitous or, simply, digital city to name just a few. In this article, the authors provide a (partial) list of 23 definitions that appeared between 2000 and 2014. A notable distinction arises between the sustainable city and the smart city. In general, a smart city implies the utilization of information technology to enhance the services and goods provided to the residents. While a sustainable city is one that focuses more exclusively on environmental protection and air quality to improve the lives of residents. More recently, the United Nations Economic Commission for

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Europe (UNECE) and the International Telecommunication Union (ITU) suggested a definition that integrated these two strands: the “smart sustainable city,” which is “an innovative city that uses ICTs and other means to improve quality of life, efficiency of urban operation and services, and competitiveness, while ensuring that it meets the needs of present and future generations with respect to economic, social, environmental as well as cultural aspects.” 2 Irrespective of the attempts to find a more inclusive designation for smart cities, there is currently no universally accepted definition of what they are or should be. There are different reasons for this; Neirotti et al. (2014) suggest that the ambiguity arises because the term attempts to incorporate “hard,” tangible aspects, like energy grids, transportation and public security, and “soft,” intangible dimensions like social inclusion, welfare and culture. Alternatively, Finger and Razaghi (2017) point out that the numerous urban studies in existence reveal a disciplinary shortsightedness depending on authors’ academic affiliations: sociologists, urban planners, architects, economists and information systems scholars, among others, have contributed to the debate, each from their own academic point of view. In approaching the study of smart cities, we adopt Razaghi and Finger’s (2018) understanding that cities are socio-technical systems where technology can expand the quality of and the number of goods and services available to the city’s residents. In this way, the basic framework becomes much broader, and shields our approach from the limitations of any narrow or mono-dimensional definition. Listening to cities With the clear exception of Ramallah, the cities chosen are self-identified as smart, and generally considered so by most definitions and previous rankings. They have designed smart initiatives and have implemented smart projects. In working with the cases, however, we did not assume a specific definition of smartness. Instead, we let each city command its own narrative on why it believes that it is smart. In this way, we avoided confronting them with any externally imposed “ideal” definition of what a smart city is or should be. By letting cities dictate the narrative, we accepted their own interpretation of smartness. We allowed each city to define the challenges it wants to tackle, clarify the technology it utilizes to address these issues, and identify the ingredients of “smartness” it chooses to introduce. The exact definition of “smart” employed by each city may be different, yet, the common element is that cities utilize technology to improve the lives of their residents. In doing so, each urban setting focuses on the elements that are more problematic and relevant to it. Those elements range from

2 See https://www.unece.org/housing-and-land-management/united-4-smart-sustainable-cities-u4ssc.html, accessed May 13, 2019.

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security and corruption to mobility and inclusiveness, from governance and health to the environment, education and culture. They can be classified in six categories: basic needs, opportunities, governance, built environment, health and culture, and future needs. Figure 1 presents the range of challenges faced by the cities studied.

Figure 1: Priority areas of the cities studied

Basic amenities (water, waste, recycling)

Basic needs

Security

Unemployment

Opportunities

School education Social mobility / inclusiveness

Corruption / transparency

Governance

Governance

Urban planning Road congestion Public transport

Built Environment

Air pollution

Health & Culture

Culture (museum) Environment (green space, cleanliness)

University education Fulfilling employment

Future needs

We studied 16 cities, from East and South Asia, the Middle East, Europe, and North and South America (see Figure 2 ). 3 In addition to the wide geographical range, the cities studied differ also in population size. Table 1 presents each city’s estimated population for 2019. According to these figures, the largest city studied is Buenos Aires with 15.2 million people and the smallest is Ramallah with 57,000. Size provides important insights about the approach taken to making the lives of their citizens “better.” The wide

3  For this initial study, the choice was made to have a limited number of cities, which led to difficult decisions about how represen- tative the sample identified could be in all the dimensions studied. The absence of African cities is conspicuous, and further work on city cases will address this limitation.

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range, however, also points out that a direct comparison between the 16 cities may be misleading. In fact, the advantages and disadvantages of urbanization depend heavily on the size of the urban community.

Figure 2: Location of the cities studied

Table 1: Population of the cities studied

Cities

Countries

Status

Buenos Aires

Argentina

15,236,835

Bangalore (Bengaluru)

India

11,750,143

Seoul

Korea Rep.

11,259,643

Jakarta

Indonesia

11,205,946

Chongqing

China

7,794,709

Singapore

Singapore

5,956,108

Dubai

United Arab Emirates

4,106,812

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Cities

Countries

Status

Medellin

Colombia

2,553,372

Montreal

Canada

1,914,592

Kuala Lumpur

Malaysia

1,760,000*

Amsterdam

Netherlands

903,349

Boston

USA

706,979

Tallinn

Estonia

427,389

Zurich

Switzerland

415,783

Bilbao

Spain

354,860**

Ramallah

Palestinian Teritorries

57,000***

Note: Source: www.population.city

* Source: http://worldpopulationreview.com/world-cities/kuala-lumpur-population/ ** Source: http://worldpopulationreview.com/countries/spain-population/cities/ *** Source: https://wikitravel.org/en/Ramallah

An additional element that distinguishes the cities studied is the level of development. Unfortunately, data at a city level is not convincing in its reliability and thus we also show the GDP per capita at the country level. Figure 3 – Panel A reports this variable for the 16 economies in which the cities studied are located. As can be seen, GDP per capita ranges from almost US$81,000 in Switzerland down to approximately US$2,000 in India. The subsequent step is to establish if there is a relationship between the challenges revealed by the smart initiatives and projects undertaken by the cities and the economic development level of the country in which they are located. This important connection is presented in Figure 3 – Panel B which reveals some interesting insights into the direct association between the challenges urban settings are facing and the GDP per capita of the country. Issues related to basic amenities, security, corruption and governance are important challenges for cities with low per capita income. Alternatively, challenges related to advanced health and future employment are issues more often prominent in high-income per capita cities.

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Of course, some of the challenges that cities face may be independent of economic development. Instead, they may be related to the size of the city. For instance, smart initiatives related to the environment are adopted in high-income cities and, at the same time, in lower income, populous urban settings such as Bengaluru (Bangalore) and Jakarta. This is one reason why letting cities provide their own narrative and operate choices among various priorities was preferred. There are additional elements present in all the cities studied. The first relates to addressing economic activity and, therefore, strengthening commerce. This serves to make the city more appealing for employment (both for maintaining the city’s talent base and for attracting talent from outside), as well as for entrepreneurs and companies that may consider investing in a particular city, or selecting it as a local, national, regional or global hub. The second element is related to information technology infrastructure. This point comes as no surprise given that the cities studied have generally used information technology to enhance their services for a number of years. The final dimension is that of sustainability, which includes efforts to enhance safety, improve public and private transportation, and protect the environment through, for example, better waste management and cleaner air. Another insight gained from the cases regards the relationship between the tools and mechanisms used by specific cities to implement smart initiatives and projects on one hand, and the amount of resources available to them on the other. Figure 4 captures this relationship.

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Figure 3: City level challenges and GDP per capita

80,699

Zurich

Switzerland

59,390

Boston

USA

48,217

Amsterdam

Netherlands

45,193

Canada

Montreal

57,723

Singapore

Singapore

19,697

Tallinn

Estonia

28,171

Bilbao

Spain

40,514

Dubai

UAE

8,840

Chongqing

China

29,755

Seoul

Korea

14,474

Buenos Aires

Argentina

1,928

Bengaluru

India

3,880

Indonesia

Jakarta

9,828

Kuala Lumpur

Malaysia

6,273

Medellin

Colombia

Country GDP per capita 3,094 Basic amenities Security

Palestinian Teritorries

Ramallah

City

Housing

Transport

Country

Corruption

Governance

Environment

Transparancy

Urban planning

Advanced health

Education / culture

Social mobility / inclusiveness

Future-proof employment (tech)

Panel A

Panel B. Top priorities

Source: IMD World Competitiveness Dataset.

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Figure 4: Mechanisms to introduce smart initiatives and GDP per capita

80,699

Zurich

Switzerland

59,390

Boston

USA

48,217

Amsterdam

Netherlands

45,193

Montreal

Canada

57,723

Singapore

Singapore

19,697

Tallinn

Estonia

28,171

Bilbao

Spain

40,514

UAE

Dubai

8,840

Chongqing

China

29,755

Seoul

Korea

14,474

Buenos Aires

Argentina

1,928

Bengaluru

India

3,880

Indonesia

Jakarta

9,828

Kuala Lumpur

Malaysia

6,273

Medellin

Colombia

Country GDP per capita 3,094 Top-down

Palestinian Teritorries

Ramallah

City

Country

E-government

Fail-early pilots

Public-private partnerships Bottom-up /participative Crowdsourced ideas

Open-data / transparancy

Tools / Characteristics

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Cities with lower levels of GDP per capita have typically pursued smart projects by employing a top-down approach. Thus, smart initiatives that focus on basic amenities (such as Ramallah’s online classrooms for students who cannot leave their homes, or the basic safety and anti-corruption measures implemented by Medellin) are provided as a result of decisions made at the highest levels of local government (typically mayors). In contrast, cities that are characterized by high GDP per capita tend to rely more on bottom- up (citizen-driven) and crowdsourced alternatives. However, a top-down approach can be also found in high GDP per capital cities like Dubai and Singapore. A common element in all the cases studied is the decision by local governments to employ information technology to provide services to the inhabitants of a city. Thus, the e-government component is widely used by all the cities we studied. The final point relates to the data and information available. All the cities we studied provide information about the initiatives and projects they undertake. From detailed websites, or through sharing reports, the narratives were readily available, either from websites managed by local authorities, or in dedicated websites related to specific smart initiatives. On the other hand, it was more difficult to get hard data on the projects. There were instances, as the reader will encounter in the cases, where detailed information was available and others where measurements were more difficult to find. Significantly, what all the cases lacked, was the evaluation of the projects by the beneficiaries of the provisions – the residents of the cities. 4 The same holds for the different rankings we have studied concerning smart cities. We have not found an index that measures residents’ satisfaction of the smart provisions, and this may be one differentiator of a future index. The chapters in this book provide a detailed account of 16 cities around the globe and their efforts to make the lives of their residents better. Reading through the cases, we invite you to keep the big picture in mind: cities are socio-technical systems that provide goods and services to their residents. Revolutionary and rapidly changing information technology allows for the amelioration and multiplication of services. The important question to be addressed is how city authorities will satisfy the various multiple stakeholders involved in the processes: local and national governmental authorities, private technology providers, international organizations, and residents. This book is a first attempt to offer us a better understanding of the unit of analysis: the smart city.

4  The only partial exception is the city of Medellín for which there is a survey conducted by an interinstitutional entity founded in 2006 (Medellin Cómo Vamos: https://www.medellincomovamos.org/quienes-somos/). The survey covers areas such as health, employment, culture, sports and transportation. Yet, the organization is not associated with any smart city project or initiative.

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References

Albino, V., Berardi, U., and Dangelico, RM. “Smart Cities: Definitions, Dimensions, Performance, and Initiatives.” Journal of Urban Technology , Vol. 22, No. 1, 2015: 3–21. Finger, M., and Razaghi, M. “Conceptualizing ‘Smart Cities’.” Informatik-Spektrum , Vol. 40, No. 1, 2017: 6–13. Neirotti, P., De Marco, A., Cagliano, A.C., Mangano, G., and Scorrano, F. “Current Trends in Smart City Initiatives: Some Stylised Facts.” Cities , Vol. 38, 2014: 25–36. Razaghi, M., and Finger, M. “Smart Governance for Smart Cities.” Proceedings of the IEEE , Vol. 106, No. 4, 2018: 680–689.

To be continued... buy the book on Amazon