Juha Nieminen Smart city How smart is it actually? Vaasa 2020 School of Technology and Innovations Master’s thesis in Information Systems Science Master’s Programme in Digital Business Development 2 VAASAN YLIOPISTO Tekniikan ja innovaatiojohtamisen akateeminen yksikkö Tekijä: Juha Nieminen Tutkielman nimi: Smart city : How smart is it actually? Tutkinto: Kauppatieteiden maisteri Oppiaine: Digitaalinen liiketoiminnan kehittäminen -maisteriohjelma Työn ohjaaja: Ahm Shamsuzzoha Valmistumisvuosi: 2020 Sivumäärä: 118 TIIVISTELMÄ: Väestönkasvu, siitä aiheutuva muuttoliike ja nopea kaupungistuminen ovat maailmanlaajuisia megatrendejä, jotka usein vaikuttavat kielteisesti elämisen ja asumisen laatuun kaupungeissa. Älykaupunki on ylemmän tason konsepti, jonka avulla kaupungit yrittävät muokata sosiaalista, taloudellista ja ympäristönsä kehitystä kestävämmälle pohjalle. Tässä tutkielmassa tarkastel- laan, miten älykaupungin konsepti on määritelty, mitkä ovat ne taustaolettamukset ja perusteet, joiden varaan älykaupunkien tieteellinen tutkimus pohjautuu, mitkä ovat älykaupunkitutkimuk- sen viimeisimmät tulokset ja innovaatiot, miten älykaupunkihankkeet saavuttavat tavoitteensa ja miten niiden perusteet ja taustaolettamukset vaihtelevat älykaupunkien välillä. Tämän tutki- muksen tavoitteena on kriittisesti tarkastella älykaupunkien tutkimusparadigmaa ja löytää mah- dollisia sudenkuoppia sekä ristiriitaisia tutkimusaiheita ja -tuloksia, joita voitaisiin käyttää äly- kaupunkien jatkotutkimukseen ja -kehittämiseen tulevaisuudessa. Tämä tutkimus on toteutettu perinteisenä kriittisenä kirjallisuustutkimuksena. Lähdeaineistona on käytetty älykaupunkien vii- meisimpiä akateemisia tutkimustuloksia ja julkaisuja, älykaupunkihankkeiden omia nettisivus- toja ympäri maailman sekä kontrastin vuoksi myös viimeisimpiä populaarin lähdekirjallisuuden käsittelemiä aiheita ja ilmiöitä. Kirjallisuustutkimusta on täydennetty kvalitatiivisella älykaupun- kivertailulla, jossa Helsingin, Singaporen ja Lontoon älykaupunkihankkeita on vertailtu keske- nään. Työn tutkimusstrategia muistuttaa ankkuroitua teoriaa, jossa induktiivisen päättelyn avulla pyritään lähdeaineistosta löytämään ja luomaan väitteitä, perusteluja ja johtopäätöksiä älykaupunkien muodosta, olemassaolon oikeellisuudesta ja tulevaisuudesta. Tutkimuksessa ha- vaittiin seuraavat pääkohdat: älykaupunki voidaan määritellä usealla, myöskin samanaikaisesti päällekkäisellä tavalla; älykaupunkien kehittäminen nähdään yleensä tieto- ja viestintäteknolo- gisten innovaatioiden kehittämisenä, vaikka samanaikaisesti usein vaaditaan myös inhimillisem- män näkökulman korostamista; älykaupunkihankkeet muodostavat monitahoisia, monia tie- teenaloja koskettavia alustoja, jotka vaativat nykyistä kokonaisvaltaisempaa tarkastelua ja arvi- ointia; nykyiset älykaupunkien menestyksen mittarit ja arviointitavat vaihtelevat huomattavasti, jolloin älykaupunkien älykkyyden ja onnistumisen yhteismitallinen arviointi on vaikeaa; jotkut havaituista älykaupunkien ominaisuuksista ja ratkaisuista ovat tehottomia tai jopa kielteisesti älykaupunkien tavoitteisiin vaikuttavia. Tässä tutkimuksessa päädyttiin seuraaviin johtopäätök- siin: älykaupunkihankkeiden monimutkaisen ja ristiriitaisen luonteen takia nykyinen älykaupun- kitutkimus- ja kehitys ei täysin pysty vastaamaan näiden ristiriitaisuuksien ja keskinäisriippu- vuuksien tuomiin haasteisiin; nykyinen älykaupunkitutkimus ei myöskään ole tieteellisesti riittä- vän monialaista. Tämän tutkimuksen pohjalta voidaan suositella, että tulevaisuudessa älykau- punkien kehitys voisi pohjautua enemmän tietojärjestelmätieteiden tutkimusmetodologioiden hyödyntämiseen, jolloin älykaupunkien vaatimat sosiotekniset ja monitieteelliset näkökulmat saataisiin paremmin havaittua, katettua ja arvioitua tutkimustuloksissa. Tulevaisuudessa tarvi- taan myös tutkimusta siitä, kuinka tehokkaasti monitieteellinen älykaupunkitutkimus onnistuu. AVAINSANAT: Avoin tieto, kaupungistuminen, kestävä kehitys, älykaupunki, älykkäät kansa- laiset, älykäs hallinto, älyliikenne, älytalous 3 UNIVERSITY OF VAASA School of Technology and Innovations Author: Juha Nieminen Title of the Thesis: Smart city : How smart is it actually? Degree: Master of Science in Economics and Business Administration Programme: Master’s Programme in Digital Business Development Supervisor: Ahm Shamsuzzoha Year: 2020 Pages: 118 ABSTRACT: The global megatrends of population growth and fast urbanisation are negatively impacting the life in the cities. Smart city is the high-level concept by which the cities try to address the need to improve their social, economic and environmental sustainability. This thesis studies how the smart city concept is defined, what are the underlying hypotheses and assumptions on which the smart city research is based on, what are the latest results and innovations of the smart city research, how the smart city initiatives are meeting their objectives, and how the hypotheses and assumptions may vary between the smart city initiatives. The objective of this study is to critically review the smart city research paradigm to find possible pitfalls, conflicting results and topics for further study and improvement. This research is conducted as a traditional critical literature review, covering the current academic literature on the smart city topic, the websites presenting the smart city initiatives around the world, and the latest popular literature for con- trasting views. A qualitative comparison of the smart city initiatives in selected cities – Helsinki, Singapore and London – complements the literature review. The research strategy in this study approximates the grounded theory, utilising inductive reasoning to generate arguments and conclusions about the form, validity and future of the smart city. This study produced the fol- lowing key findings: there are many different and overlapping definitions of smart city; the smart city development is mostly seen as the responsibility of smart ICT implementations, while sim- ultaneously demanding for a more focused human viewpoint; the smart city initiatives form complex, multidisciplinary platforms that require holistic evaluation; the current evaluation methods and rankings of the smart cities vary considerably, making the evaluation of the success of the smart cities difficult; some of the existing smart city elements and proposed solutions are ineffective or even counterproductive for the smart city objectives. The main conclusions of this study were that the complex nature of the smart city initiatives and the conflicts and interde- pendencies of the smart city objectives are not fully addressed in the current smart city research, and that the current smart city research is not adequately multidisciplinary in nature. For the future, this research argues for the increased utilisation of research methods used in infor- mation systems science for their ability to address socio-technical and multidisciplinary prob- lems. Also, the need for a future research on the efficacy of the multidisciplinary research of smart cities is identified. KEYWORDS: Open data, smart citizens, smart city, smart economy, smart governance, smart traffic, sustainability, urbanisation 4 Contents 1 Introduction 8 1.1 Background 8 1.2 Research focus 9 1.3 Research aim 9 1.4 Research method and strategy 10 1.5 Literature review 10 1.6 Value of this research 11 2 Definition of smart city 13 2.1 European smart city 13 2.2 Smart city infrastructure 16 2.3 Smart city dimensions 18 2.3.1 Technology dimension 19 2.3.2 Human dimension 20 2.3.3 Institutional dimension 21 2.4 Smart city by stakeholders 21 2.4.1 Smart universities 22 2.4.2 Smart citizens 22 2.4.3 Smart governance 23 2.4.4 Smart urban planners 24 2.4.5 Smart businesses 25 2.5 Smart cities of the world 26 3 Building blocks of smart city 31 3.1 E-governance 31 3.2 Smart traffic 32 3.3 Smart sustainability 35 3.4 Smart technology 37 3.5 Smart data 41 3.5.1 Open data 42 3.5.2 Smart applications 44 5 3.5.3 Data privacy and security 44 3.6 Measuring smart city performance 46 4 Literature review synthesis 51 4.1 Research synthesis of smart city definitions 51 4.2 Smart city framework 52 5 Smart city comparison 55 5.1 City selection criteria 55 5.2 Helsinki 56 5.2.1 Forum Virium Helsinki 57 5.2.2 Helsinki Lighthouse 60 5.2.3 Smart data of Helsinki 61 5.2.4 Smart traffic of Helsinki 62 5.3 Singapore 65 5.3.1 Smart Nation Singapore 66 5.3.2 Smart data of Singapore 69 5.3.3 Smart traffic of Singapore 70 5.4 London 73 5.4.1 Smart London 73 5.4.2 Smarter London Together 75 5.4.3 Smart data of London 76 5.4.4 Smart traffic of London 77 5.5 Smart city comparison summary 80 6 Discussion and study outcomes 85 7 Conclusions 91 References 95 Appendices 111 Appendix 1. ISO 37120:2018 themes and indicators 111 6 Figures Figure 1. Six key fields of urban smartness (adapted from Giffinger, et al., 2015). 15 Figure 2. Smart city infrastructure (adapted from Silva, et al., 2018). 16 Figure 3. Smart city dimensions (adapted from Nam & Pardo, 2011). 19 Figure 4. Smart city technology architecture (adapted from Silva, et al., 2018). 39 Figure 5. 17 themes of ISO 37120:2014 (adapted from WCCD, 2020). 49 Figure 6. Conceptual smart city framework. 53 Tables Table 1. Research synthesis of smart city definition. 51 Table 2. Smart city comparison summary. 84 Abbreviations 3G Third generation wireless digital cellular network technology 4G Fourth generation wireless digital cellular network technology 5G Fifth generation wireless digital cellular network technology AI Artificial intelligence ANN Artificial neural networks API Application programming interface CaaP City as a platform CAD Canadian Dollar CANN Cascaded artificial neural network CAV Connected and autonomous vehicles CI Community informatics CKAN Comprehensive knowledge archive network CO2 Carbon dioxide EC European Commission EIP-SCC European Innovation Partnership on Smart Cities and Communities ENoLL European Network of Living Labs FaaS Freight as a service GBP Pound sterling GDP Gross domestic product GNSS Global navigation satellite systems GPS Global Positioning System HRI Helsinki Region Infoshare 7 HSY Helsingin seudun ympäristöpalvelut, Helsinki Region Environmental Ser- vices Authority IC Information and communication ICT Information and communication technology IMD International Institute for Management Development IMDA Infocomm Media Development Authority IoT Internet of things IS Information systems ISS Information systems science ISO International Organization for Standardization L3 London Living Labs LL Living lab LoRa Long-range, low-power wide-area network technology MaaS Mobility as a service NFC Near-field communication NGO Non-governmental organisation ODI Open Data Institute OIP Open Innovation Platform PIR Private information retrieval PPDM Privacy-preserving data mining QoL Quality of life R&D Research and development RFID Radio-frequency identification SDC Statistical disclosure control SMLL Smart Mobility Living Lab TfL Transport for London TTP Trusted third party UN United Nations UK United Kingdom USD United States Dollar WCCD World Council on City Data Wi-Fi Wireless local access network technology 8 1 Introduction Today’s world is facing two trends that greatly affect our way of life simultaneously: pop- ulation growth and urbanisation. While the growing cities offer job opportunities, ac- commodation and infrastructure to support better quality of life (QoL) for the increasing number of citizens the dramatic urbanisation also negatively impacts the environment, the lifestyles in the societies and the governance of the cities (Silva, Khan, & Han, 2018). 1.1 Background The smart city is a common concept under which various research and development programmes are collected to prevent and mend the negative impacts of the rapid urban- isation. The term smart city is said to have first appeared in the middle of the 1990s, when the cities promoted themselves after introducing new information and communi- cation technology (ICT) infrastructure or e-governance services, or when attracting tech- nology companies to provide new economic growth to the region (Hollands, 2008). The smart city development is today a global phenomenon and it is closely related to the 17 so called sustainable development goals listed in the 2030 Agenda for Sustainable De- velopment of the United Nations (UN) Department of Economic and Social Affairs (United Nations, 2019). All UN member states have adopted the agenda in 2015. Espe- cially, the sustainable development goal 11 lists objectives for inclusive, safe, resilient, and sustainable cities on which many of the background assumptions and hypotheses of the smart city research are based. However, regardless of the recent visible enthusiasm on the smart city development, it is not yet quite clear if the smart city initiatives really are making the cities smarter. Are the alleged smart city innovations useful or effective in improving the city sustainability? Are the cities becoming easier to plan and govern? Is the modern technology simplifying or complicating the smart city development? And, do the citizens find the smart cities more liveable and desirable places to dwell and work in? What if the smart city 9 development is found to be counterproductive for the objectives and good intentions of the smart city? 1.2 Research focus This study first focuses on the many definitions of smart city to find common nominators and differing factors among them. Secondly, the typical innovation areas within the smart city research are introduced. Special attention is paid to the smart city innovations touching the information systems science (ISS). At the same time, it is realised how mul- tidisciplinary the smart city research needs to be in order to produce practical and useful results by which the cities and the life of their citizens can be further developed and improved. Thirdly, a set of three representative smart cities – Helsinki, Singapore and London – are studied to compare what are the actual smart city research projects and innovations they are concentrating on, are there any similarities or differences to be found in their background assumptions, and how these cities value and utilise their re- sults. Finally, this study then concludes with the evaluation on how the smart city ideol- ogy meets its objectives. 1.3 Research aim The research aim of the study is to better understand the underlying hypotheses and background assumptions of the smart city ideology. The objectives of this study can be formulated as the following four Research Questions: 1. What attracts the current enthusiastic smart city research and development? 2. Is the evaluation of the smartness of the cities based on sound judgement? 3. Are there any issues or challenges that may have been overlooked or neglected in the smart city research so far? 4. What may be the opportunities for better future smart city research and devel- opment? 10 1.4 Research method and strategy This study is carried out as a traditional literature review to find out what are the current points of interest in the smart city research. The emphasis is on the latest academic and peer-reviewed literature, but the novelty of the subject also necessitates a peek into the popular business and science publications to see if there are any new trends or under- currents that may have so far been neglected by the science community. The selected research strategy for this study approximates the grounded theory. This exploratory strategy allows for the empirical study and perception of the largely unstruc- tured smart city phenomena. The grounded theory also enables the building up of a more holistic conceptual model of the smart city as a synthesis influenced by the re- viewed literature. 1.5 Literature review The literature review for this study is conducted as keyword-based searches for academic literature, popular literature and websites that cover the topic of smart city. The keyword “smart city” is complemented by searching for keywords that further define the smart city, including “smart sustainability”, “smart governance”, “smart economy”, “smart traf- fic”, “smart mobility”, “smart technology, “smart data” and “smart citizens”. It is evident that the keywords “smart technology” and “smart data” result in numerous references to detailed topics of cloud-based services, internet of things, sensor networks, artificial intelligence, big data, and information and communication technology. Each of these topics would be an interesting study subject of their own. In this work, however, it is not feasible to describe and explain these topics in detail. Instead, the intention is to capture only their essence in forming and enabling the smart city. The tools used for the literature search consisted of a normal Windows base personal computer and the Google Chrome web browser. The main sources of literature were the 11 Finna search services through the Tritonia Finna portal, and the Google search tools, es- pecially through its Google Scholar search engine. The smart city is relatively young as a research topic. Therefore, it was not difficult to limit the age of the articles. All the used articles are from the third millennium, and the bulk of them from the latter half of the 2010s. In the following chapters the literary review is structured so that first, in Chapter 2, the definition of the smart city is studied from various perspectives: what is the infrastruc- ture of the smart city, what are the dimensions of the smart city, and who are the stake- holders of the smart city. The chapter ends with an introduction to the interesting smart cities and smart city initiatives around the world. Chapter 3 contains the grounded the- ory section of the literature review. By inductive reasoning from the literature, the ap- parent building blocks of the smart city are formulated and introduced. Chapter 4 con- cludes the literature review by providing a synthesis and a framework of the smart city based on the findings of Chapter 2 and Chapter 3. The literature review is complemented in Chapter 5 with a qualitative comparison of three representative smart cities and their smart city initiatives around the globe. The aim of this chapter is to present how the cities themselves define their smart city initia- tives, and the practical actions the cities take towards becoming smart. Here the official smart city websites of the selected communities offer and interesting starting point to explore what achievements the cities themselves value the most in their smart city de- velopment, and what challenges they rather may not mention. 1.6 Value of this research This study adds value to the research on smart cities by providing a critical view to the topic. The study combines the results of the latest academic smart city research and the practical smart city initiatives and draws conclusions on the practicality and usefulness of the smart city development. This study also endeavours to add a philosophical 12 approach to the ICT research and to the discussion about the topic of the digital trans- formation of the society. The topic and the findings of this thesis hopefully also interest the broader audience and scientific community as the smart city concept considers so many of today’s megatrends: urbanisation, sustainability, clean and safe environment, intelligent traffic, and mobility solutions. The topic is also very closely related to internet of things (IoT), open data, and especially the privacy and safety of personal data, which are increasingly utilised the more sophisticated and complex the smart city applications become. This should offer opportunities and complex challenges for truly multidisciplinary research projects and scientists in the future. 13 2 Definition of smart city This chapter seeks to find out how a smart city is defined and why smart cities are con- sidered important, or even necessary, today. There are various stakeholders involved in the smart city development, for example: citizens, educational institutions, municipal administrators, and urban planners, and they all have a slightly differing view of the smart city. 2.1 European smart city The digital single market policy of the European Commission (EC) provides a good start- ing point for defining what a smart city is: A smart city is a place where traditional networks and services are made more ef- ficient with the use of digital and telecommunication technologies for the benefit of its inhabitants and business. A smart city goes beyond the use of information and communication technologies (ICT) for better resource use and less emissions. It means smarter urban transport networks, upgraded water supply and waste disposal facilities and more efficient ways to light and heat buildings. It also means a more interactive and responsive city administration, safer public spaces and meeting the needs of an ageing popu- lation (European Commission, 2019). This smart city definition suggests that the smartness of the city is built on the old, ex- isting city infrastructure, instead of having to build a completely new infrastructure. Then, the old infrastructure is put to better use with the help of digital ICT innovations. This should ensure higher efficiency, lower resource consumption and less waste and pollu- tion, while making the city safer, more liveable, and the city administration more ap- proachable. Interestingly, in the European context the ageing of the population is high- lighted in the smart city definition over the accelerating population growth of the cities. The EC definition of smart city also illustrates the enormous depth of the smart city prob- lematics and the unfaltering confidence in the information systems. The clever use of ICT 14 is expected to solve any problem from the old plumbing and sewage to city administra- tion all the way up to the political decision making, too. The EC addresses the issue of growth from the viewpoint of the economic and financial crisis experienced during the first decade of the new millennium (European Commission, 2010). In order to catch up with the lost years of economic and social progress, the Eu- rope 2020 strategy has prioritised objectives for smart, sustainable and inclusive grow: The smart growth develops the economy from the innovation and knowledge perspec- tive. The sustainable promotes the competitiveness of the economy from the resource efficient and environmentally friendly perspective. The inclusive growth targets higher employment rates through social and regional unity. Vienna University of Technology has been profiling and benchmarking medium-sized, between 100 000 and 500 000 inhabitants, and large, 300 000 to 1 million inhabitants, European smart cities since 2007 (Giffinger, Kramar, Haindlmaier, & Strohmayer, 2015). Their fourth, and latest, release of the smart city model is from 2015. The model ranks the smart cities by comparing how the cities perform in six key fields of smartness: smart governance, smart economy, smart mobility, smart environment, smart people and smart living, depicted in Figure 1. These six key fields provide a good starting point for comparing how the other definitions of smart city cover these same fields: The smart governance ranks the cities by their political awareness, the quality of public and social services and the efficiency and trans- parency of the city administration (Giffinger, et al., 2015). 15 Figure 1. Six key fields of urban smartness (adapted from Giffinger, et al., 2015). The smart economy field considers the spirit of innovativeness and entrepreneurship, how well the labour market is working, how productive the city is, and how deep the city is integrated internationally (Giffinger, et al., 2015). Additionally, the smart economy re- gards a softer factor of what is the overall city image. The smart mobility combines the two main definitions of mobility – the local transport system, and mobility provided by the ICT infrastructure – under one heading (Giffinger, et al., 2015). The sustainability of the transport system and the accessibility of the city, both domestic and from abroad, are also evaluated under the smart mobility field. The smart environment evaluates the air quality, the sustainability of the resource man- agement and the ecological awareness of the city (Giffinger, et al., 2015). Interestingly, pollution is only mentioned separately related to the air quality, without considering the possible pollution of the ground, water or built environment. The smart people are defined by their level of education and their affinity for lifelong learning (Giffinger, et al., 2015). The smart city also assumes a level of open-mindedness 16 and ethnic plurality from its citizens. The definition does not advise how the smart city should react in the presence of possible narrow-minded and uneducated people, though. The smart living is a broad field ranging from the quality of the housing to the facilities available for education, culture, and leisure. It also includes considerations for personal safety and health (Giffinger, et al., 2015). Furthermore, smart living should provide social cohesion and an attractive city for tourists. 2.2 Smart city infrastructure Another way of defining the smart city is to look at the infrastructure on which the smart city is built. In a recent study the smart city lays on four infrastructure pillars: institutional infrastructure, physical infrastructure, social infrastructure and economic infrastructure, depicted in Figure 2 (Silva, et al., 2018). Figure 2. Smart city infrastructure (adapted from Silva, et al., 2018). 17 The institutional infrastructure consists of the smart city governance including the polit- ical strategy development, transparency of the governance with the citizens participat- ing in the decision making and the public and social services of the city (Silva, et al., 2018). The institutional infrastructure should provide cooperation and integrate with public, private and civil organisations both locally and nationally to ensure adequate interoper- ability between services and integration of various administrative bodies. The institu- tional infrastructure should also form liaisons with both regional and national govern- ment levels. It is seen that the technocratic governance, that is, the availability of all smart city services and features through technical solutions, enables the optimisation of complex social issues via computational capabilities. Finally, a careful and sensitive con- sideration of political perspectives is said to make the governance of a smart city much easier. This can lead into an interesting dilemma: how a smart city, predominantly as- sisted with an information systems solution implemented with digital technology and true-false logic, is able to adjust and provide reliable results for the both ends, with usu- ally opposing opinions, of the political spectrum? The physical infrastructure consists of the natural resources and energy, ICT infrastruc- ture, buildings, and urban planning (Silva, et al., 2018). The main goal of the physical infrastructure is to ensure the sustainability of the smart city today and in the future. With the help of green buildings, green urban planning, sustainable renovation of the buildings and municipal services, the use of renewable energy sources and the sustain- able conservation of scarce natural resources the physical infrastructure can ensure the longevity of the smart city. The social infrastructure covers the intellectual and human capital and the quality of life (Silva, et al., 2018). It is noted that the smart city concept can become popular and suc- cessful only if the citizens are aware of, responsible for and committed to its goals. The social infrastructure and social awareness are seen essential for the evolution and sus- tainability of the smart city. The three other infrastructure pillars would not be able to guarantee the success of the smart city without the social infrastructure pillar properly 18 in place. It is stated that the smart city attracts better educated and competent citizens enabling the growth and further knowledge based urban development. Another study further defines similar social infrastructure factors, like smart inhabitants, degree of ed- ucation, social interaction skills, integration with the public life and open attitude to the wider world as factors of a successful smart city (Ismagilova, Hughes, Dwivedi, & Raman, 2019). Typically, the studies present that the socially smart citizens help to build smarter cities from bottom up. It is seldom considered how the smart cities could improve the QoL of their less fortunate or less educated citizens. There are several definitions for the economic infrastructure of the smart city, or the smart economy, ranging from the utilisation of e-commerce and e-business to the vari- ous performance indicators to analyse the public expenditure, energy consumption, em- ployment rates, funding of the smart city projects and the GDP of the citizens (Silva, et al., 2018). Interestingly, constant and steady economic growth is seen as a key success factor for the smart economy of a prosperous smart city. The attitudes towards economic growth, especially in relation to sustainability, have not always been as straightforward, and the issue has traditionally been the topic of much debate (Haughton, Counsell, & Vigar, 2008). 2.3 Smart city dimensions Apart from the six smart city dimensions by EU, as in chapter 2.1, the smart city can also be categorised by just three dimensions: the technology dimension, the human dimen- sion and the institutional dimension, depicted in Figure 3 (Nam & Pardo, 2011). Each of these dimensions can then be further defined by collecting conceptual relatives of the smart city terminology under each dimension. These various concepts within the dimen- sions are at first sight slightly overlapping, interconnected, and even contradicting, but together they give a holistic understanding of the contents of the smart city. 19 Figure 3. Smart city dimensions (adapted from Nam & Pardo, 2011). 2.3.1 Technology dimension The technology dimension consists of concepts, like digital city, intelligent city, ubiqui- tous city, hybrid city and information city (Nam & Pardo, 2011). The digital city is built around a broadband communications network that connects the community for seam- less information sharing, interoperability, and collaboration between the citizens. The intelligent city emphasises the knowledge and creativity of the society, where hu- man and social capital are the most important factors (Nam & Pardo, 2011). The ICT in- frastructure together with the latest telecommunications, electronics and mechanical technology enable the conscious transformation of the intelligent city. This transfor- mation is seen as fundamental and significant, instead of an incremental change. The ubiquitous city extends the idea of the digital city by providing the citizens with an access to all services regardless of the time, place or device (Nam & Pardo, 2011). All 20 elements of the built environment – the citizens, buildings, infrastructure, and open spaces – have ubiquitous access to computing. The hybrid city combines the elements of the physical smart city with the latest devel- opments of a fully virtual city that exist only in the cyberspace of cloud computing (Nam & Pardo, 2011). One interesting new research topic for the hybrid city is the development of the smart city digital twins (Mohammadi & Taylor, 2017). A digital twin is a parallel virtual version of the city that receives real IoT data from the city infrastructure and makes progressive and adaptive predictions of the future behaviour of the real city. The information city collects data from the local communities and transfers it to the pub- lic use through web portals (Nam & Pardo, 2011). The information city generates an ur- ban platform of commerce, social and civic services and social media for its citizens. Many of them become info-habitants that can work and live on the internet domain. 2.3.2 Human dimension The human dimension emphasises the concepts of a creative city, knowledge city, learn- ing city and humane city (Nam & Pardo, 2011). Learning and education of the citizens are the driving forces towards smart city. The learning city should also generate compet- itive and skilled workforce for the information economy. The knowledge city can be used as a synonym for the learning city. The earlier concepts of technopolis and ideapolis have evolved into a knowledge city that provides digital, purposefully built facilities to pro- mote the knowledge economy. The creative city must provide a creative atmosphere for the emergence of the smart innovations (Nam & Pardo, 2011). This includes knowledge networks and the involve- ment in the voluntary organisations. It is also mentioned that the creative city should provide a crime-free society where the after-dark entertainment economy can thrive. 21 The concept of a humane city openly admits that it is meant mostly for the creative, better-educated citizens (Nam & Pardo, 2011). The smart city provides higher education to create and attract skilled knowledge workers and high technology industries. This causes the smart cities to become even smarter with the inflow of smarter and more creative people, while the other communities suffer from the opposite. 2.3.3 Institutional dimension The institutional dimension covers the governance and the urban planning of smart city (Nam & Pardo, 2011). The governance of the smart community is seen as a partnership of shared interest between the citizens, governing institutions, businesses, and other organisations, where information technology is consciously used for improving and transforming the work and life significantly for the better. The role of urban planning is to ensure smart growth so that the smart city becomes bigger, while not necessarily wider (Nam & Pardo, 2011). The urban planning should also find solutions for the environmental challenges like congested traffic, pollution, dimin- ishing open space, overcrowding, and increasing cost of public facilities. 2.4 Smart city by stakeholders The smart city development attracts various groups of people, institutions, and corpora- tions. The all have a slightly differing view about the direction, goals, and results of this development. It is sometimes difficult to combine and coordinate these views. The var- ying smart city perspectives of some of the key stakeholders of the smart city develop- ment – universities, citizens, government, urban planners, and businesses – are pre- sented in the following chapters. 22 2.4.1 Smart universities The universities and research institutions see the smart city as a possibility to collect and coordinate the other smart city stakeholders on an open platform (Ferraris, Belyaeva, & Bresciani, 2018). The universities then coordinate the sophisticated innovation and re- search of the independent participants. The role of the universities is to provide qualified personnel, knowledge, facilities, and opportunities for innovation development. The uni- versities also offer a creative and educational environment, and an independent and im- partial access to public funding for the smart city development projects. 2.4.2 Smart citizens From the citizens’ perspective the smart city enthusiasm is unfortunately not always that tangible. It is noted that the research and literature tend to focus on the technology aspects of the smart city, instead of the topics associated with its citizens (Marrone & Hammerle, 2018). In a study conducted in Curitiba, Brazil – a city often mentioned as being one of the ten smartest cities in the world – the results indicate a low citizen satisfaction with their hometown as a smart city (Macke, Casagrande, Sarate, & Silva, 2018). The citizens’ QoL was analysed to be defined by four factors: socio-cultural relationships, environmental wellbeing, material wellbeing, and community integration. However, regardless of the award-winning smart city status of Curitiba, the study points out that these human factors are often ne- glected in the digitally enhanced urban experiments. Instead of helping the less privileged people, the smart city often tends to require the people to become smart citizens first, before the city itself can become smart. In Caguas, Puerto Rico, the integration of the educational institutions to the city strategy should produce knowledge and intellectual capital for smart people that may then provide sustainability to the city (Ortiz-Fournier, Márquez, Flores, Rivera-Vázquez, & Colon, 2010). Similarly, the in- crease in citizens’ social, cultural and environmental awareness are seen as the key to the 23 sustainable future of the smart city (Staffans & Horelli, 2014). Also, in the ranking of the European Smart Cities, the education and lifelong learning of the citizens are seen as the building blocks of a smart city, not vice versa (Giffinger & Haindlmaier, 2010). The social-cultural relationships and the ability to be a smart citizen can also be defined with a 3T definition: tolerance, technology and talent (Nam & Pardo, 2011). A smart citizen must have the creativity and talent to create and understand the technology needed and used in a smart city. Surprisingly, the smart citizen also needs increased levels of tolerance to cope and thrive in a smart city. One would think that a smart city would be a more tolerable place to live than a conventional city. Apparently, it is vice versa. 2.4.3 Smart governance The problem of low satisfaction with the smart city has been noticed elsewhere, too. A study about the smart city governance concludes that the most advanced technology does not necessarily provide an atmosphere where the citizens would enjoy developing a sustainable and vital city together (Effing & Groot, 2016). At the same time, it is seen essential that the citizens and companies should cooperate with the local government in the co-creation of the smart city, instead of the government having to be the leading authority alone. The innovative participation of the citizens in the development of vari- ous e-participation methods would enable the cities to transform into so called social smart cities. Where the traditional urban governance relies on steering through norms, policies, pro- grammes, information and economic incentives, the smart city is increasingly governed by self-organisation, co-governance, deliberation and monitoring (Staffans & Horelli, 2014). This leads to recursive decision-making between formal and informal governance methods, involving citizens, businesses and local forums to interact with the city councils. 24 2.4.4 Smart urban planners The urban planning of the smart city can be viewed as an evolutionary process (Komninos, Kakderi, Panori, & Tsarchopoulos, 2018). Cities are becoming so complex and chaotic systems, that it is not practical anymore to plan and construct them from scratch. Instead, the decision-making should take place under constant and non-linear change, which converts the smart city planning into an evolutionary process, where the digital technology utilized in the planning changes so rapidly that the technology does not often even exist at the beginning of the planning process. This new evolutionary urban smart city planning idea of “cities are becoming cities” differs greatly from the conventional 20th century urban planning concept where “cities are planned as cities”. Another view to the smart city planning expands the traditional top-down, comprehen- sive-rationalistic urban planning theory, which is said to still being applied today, by em- phasising the incremental and pragmatic planning of the smart cities with the help of the participating citizens and other stakeholders (Staffans & Horelli, 2014). The introduc- tion of ICT and the empowerment of the communities in the form of community infor- matics (CI) has enabled city planning to transform into participatory e-planning. Further- more, the urban planning is not seen any more as an individual, separate activity. Instead, the city planning function has become an interweaved activity with the city governance and community development. Ultimately, the citizen participation and innovation needed in the smart city planning and governance is transforming the city into a platform. Instead of the city being a bu- reaucratic mechanism of separately organised silos, the urban planning and governance can be offered on a unified city as a platform (CaaP) (Anttiroiko, 2016). The CaaP is the place where the citizens and other stakeholders can gather to discuss, exchange ideas and participate in the co-creation of smart solutions. The CaaP is said to democratise the smart city innovation. 25 2.4.5 Smart businesses For the businesses in the ICT sector the smart city development has been identified as an enormous global market potential. A few years ago, it was estimated that the value of the smart city market would be over 20 billion USD in 2020. This has interested the corporations in developing and promoting their own smart city strategies (Söderström, Paasche, & Klauser, 2014). However, the rapid development and inaccuracy of the esti- mations regarding smart city is clearly demonstrated in another study, which is only four years newer, which estimates that the global market would actually be 400 billion USD in 2020, instead of 20 billion USD (Yigitcanlar & Kamruzzaman, 2018). In many views the smart city development is seen having a too strong and overempha- sised focus on technical solutions, prioritising public spending on ICT and relying too heavily on data and software at the expense of human knowledge and expertise (Söderström, et al., 2014). This has given an opportunity for private technology busi- nesses to define urban management models for smart cities. IBM is used as a prime ex- ample of an IT company that has shaped the smart city ideology towards IT centric en- trepreneurialism, having registered the Smarter Cities trademark already in 2011. A study has used IBM as a reference to describe and criticise how the corporations have used their communications power to create a story of a positive transformation by which the smart city technology solutions of the corporations are essential in solving the urban problems (Söderström, et al., 2014). This may lead to the corporatisation of city govern- ance where technocratic systems analysis largely replaces the political debate on the direction and priorities of the municipal development. Ultimately this raises the question about who actually has the authority to define the smartness of the city. IBM also arranges Smarter Cities Challenge competitions, where the winning cities are granted with a team of IBM experts and computing platforms and tools for three weeks to develop the winning project ideas further (IBM, 2020). The latest competition was held in 2017, with the focus on topics related to the environment, economic 26 development, social services, and emergency management. The winning cities were Busan in South Korea, Yamagata City in Japan, Palermo in Italy, San Isidro in Argentina, and San Jose, in the United States. From the viewpoint of the participating cities the winners are provided with fast access to the needed smart city expertise and resources. This also easily locks one vendor permanently in to drive their own technology-based smart city vision, instead of allowing the city to proceed freely based on their smart city needs. Often mentioned other IT companies shaping the smart city include Cisco and Siemens (Söderström, et al., 2014), Alcatel (Staffans & Horelli, 2014) and Intel (Mulligan & Olsson, 2013). Interestingly, Nokia has acquired large parts of both Siemens and Alcatel, together with Bell Labs, enabling also Nokia to strongly promote their smart city strategy (Nokia, 2020). It has been noted that this kind of division into ICT players and telecommunica- tions players is also a cause for the development of the smart city architecture being hindered by the battle between two business models: ICT and telecommunications. An architectural evolution is required to integrate these two technologies optimally in smart cities (Mulligan & Olsson, 2013). 2.5 Smart cities of the world It is nowadays easy to find smart cities, or cites wanting to be called smart, all over the world. It is much more difficult to evaluate what is the actual smartness level in these cities. It is criticised that many of the alleged smart cities use the term for self-promo- tional purposes to become more acceptable and attractive in the eyes of the stakehold- ers the cities hope to tempt in. A study presents examples where the investments in the ICT, in the name of smartness, do not yet reveal or solve the underlying social problems of the city, or how the temporary boost in the ICT investments may not guarantee a longer term accumulation of smartness or wealth in the city (Hollands, 2008). It is also noted how the public funding of private ICT innovations may benefit the multinational corporations elsewhere rather than the intended smartness development locally. 27 In India, the smart city initiatives are coordinated on the government level. The big and world’s second most populous country is battling with fast urbanisation. The problems ahead and the measures taken are massive. In 2015 the Smart Cities Mission, hosted by the Ministry of Housing and Urban Affairs of India, launched a Smart Cities Challenge to find and select 100 cities whose smart city initiatives would receive funding from the government (Smart Cities Mission, 2020). The total budget for the Smart Cities Mission is estimated to 7,5 billion USD over five years. The target is to develop urban planning, governance, and the economic, social and physical infrastructure of the selected 100 cities. The project impacts the life of almost 100 million citizens in India. As in India, the smart city initiatives in Canada are also organised under a government coordinated competition, named Smart Cities Challenge (Impact Canada, 2020). The challenge statement of the competition exemplifies the key focus areas and the current biggest concerns of the cities in Canada: The safety and security of the high crime rate neighbourhoods is surprisingly listed as the first issue requiring a smart solution. The post-industrial transformation of old industrial neighbourhoods and the stimulation of economic growth after a long decline is another major concern in Canada. The health and wellbeing related topics of activating, especially, the ageing population require at- tention from the smart city innovations. The environmental health and the inclusion and empowerment of the most vulnerable citizens are also highlighted. Interestingly, the Ca- nadian smart city challenge is one of the few where the focus on innovations in IC tech- nology are not apparently visible as one of the key development areas. Instead, the focus and the targets are much softer and more citizen-oriented, and ICT just provides the possible underlying tools to achieve the targets. The winning cities of the currently latest competition round were announced in May 2019 (Infrastructure Canada, 2019). Mont- réal won the grand prize of 50 million CAD, while the smaller prizes from 5 to 10 mil- lion CAD were awarded to the town of Bridgewater, Nunavut communities and the joint proposal of the city of Guelph and Wellington county. 28 In Russia, the smart city activities have a showcase in Moscow. There are seven main smart city initiatives listed on the official website of the Moscow mayor (Moscow Government, 2020). A city-wide mobile internet and free Wi-Fi access to the internet is available in the streets, parks and public transport system. The smart transport is con- trolled by the traffic management centre, which can make forecasting based on traffic patterns. The city government provides an internet access to e-services. There is also a unified medical services portal for finding medical centres, arranging doctor’s appoint- ments and handling medical paperwork online. The citizens of Moscow are encouraged to participate in the city planning and management by awarding points and small re- wards to the most active voters in the opinion polls. The electronic school project of Moscow includes an electronic library of lesson material that the teachers can share and co-create. The school records and registering are also provided online. Finally, Moscow also boasts about its 146 000 publicly installed surveillance cameras, allegedly being one of the top ten cities in the number of cameras. It is mentioned that the camera record- ings are used in solving 70 % of the crimes and violations is Moscow. The camera footage is used also used for supporting and monitoring the city utility services. In Brazil, the public and private smart city initiatives are collected and ranked by a private event organising company Connected Smart Cities (Urban Systems, 2019). They arrange annually a Connected Smart City exhibition and conference, and since 2015 they have annually published a ranking of the Brazilian smart cities. There are 11 main smart city indicators by which the performance and the ranking of the cities are evaluated. These follow the typical smart city dimensions and building blocks: mobility and accessibility, environment, urbanism, technology and innovativeness, quality of life, security, educa- tion, entrepreneurship, energy, governance, and economy. The latest publication of the Connected Smart Cities ranking is from September 2019, and according to it the top three smartest cities in Brazil are Campinas, São Paulo and Curitiba. The smart cities of Africa still have a long way ahead before surfacing on top of the smart city polls. For example, Cape Town, Abuja, Cairo, Nairobi, Rabat and Lagos, the only 29 African cities mentioned on the latest smart city index of IMD, are occupying the rankings below 90 on the list of 102 smart cities, Lagos holding the last position (International Institute for Management Development, 2019a). Interesting critique of the African smart city aspirations is presented in a Cape Town based study, which argues that the fantasies of creating glass-box tower architecture, mimicking renowned smart cities like Dubai, Shanghai or Singapore, is actually worsening the inequality of the citizens in the African cities (Watson, 2015). Many of the smart cities in Africa are implemented as satellites of existing cities, which ignores the citizens’ human and social dimension of co-created in- novation essential for the smart cities. The low education level and poverty of the citi- zens, uprooted and disconnected from their original habitation due to urbanisation, am- plifies the disproportion between the smart city vision and the reality of the citizens. The rhetoric of urgency to create smart cities to fix the problems of fast urbanisation takes resources and attention away from the more urgent needs of clean water, housing, san- itation, and uninterrupted power supply. The history of the rapidly expanded smart city development in China is said to trace back to the government’s publication of the 12th Five-Year Plan in 2010 (Yu & Xu, 2018). This study about smart city innovation diffusion theories and quantitative empirical analysis of the performance of the Chinese smart cities presents two interesting viewpoints: First, the differences between the smart city approaches in the East and West are noticed to still exist. China, representing the eastern culture, is said to prefer the central govern- ment controlled top-down approach, while in the west the direction of the development prefers local bottom-up approach. Secondly, it is argued that the smart cities can fix en- vironmental issues only to a point. If the pollution situation, as in many aspiring Chinese smart cities, gets too severe, the resources and the attention of the city gets distracted from the smart city initiatives towards the more pressing environmental issues. If only one example from the United States should be named, then New York would be the winner or top contestant of many smart city rankings. In New York, the smart city activities are driven directly from the mayor’s office. The city has a long-term 30 OneNYC 2050 strategy that has been kept updated since its original launch in 2015 (OneNYC, 2020). The OneNYC 2050 strategy summarises the focal points of the smart city initiatives in New York: The continuing urbanisation and population growth put pres- sure on the city development. The diversity, safety, security, and affordability of the housing are the key for the neighbourhoods of New York. The emphasis on children’s equal access to quality education and the availability of health care for everyone are topics that seem to be deriving from the national level debate over the American social system. The environmental sustainability requires ending the reliance on private cars and fossil fuels, with the hope of developing technologies for new modes of transportation. In 2050 New York should also have a modern and reliable infrastructure, the economic power to provide entrepreneurial or job opportunities for all, and a vibrant democracy that encourages the citizens to actively participate in the development of the city. In Europe, the individual smart city initiatives are supported by the common objectives of the urban agenda of the EU (European Commission, 2020). The priority themes for the EU cities cover familiar smart city topics, including digital transition, sustainable en- ergy and environmental issues, urban mobility, prevention of poverty and unemploy- ment, affordability and sustainability of housing, culture and education. Three themes in the EU agenda seem unique among the many international smart city initiatives: The recent influx of refugees into the EU has prompted the inclusion of migrants and refu- gees in cities as one priority theme. The theme of circular economy is also seldom men- tioned in other smart city initiatives. Finally, the governance related activities within the EU concentrate on the special theme of innovative and responsible public procurement in the cities. Also unique in the European smart city development is the deliberate aspi- ration for cooperation and partnerships (European Innovation Partnership on Smart Cities and Communities, 2020). The EU maintain a special platform, or a marketplace of the European Innovation Partnership on Smart Cities and Communities (EIP-SCC), with funding, matchmaking, guiding and various initiatives and projects that foster European inter-city cooperation on smart city development. 31 3 Building blocks of smart city The various definitions of the smart city in the previous chapter also reveal the most important building blocks of the smart city. This chapter introduces the most important, typical or interesting innovations, implementations and research initiatives by which the smart cities are built in practice. 3.1 E-governance The smart city is often defined by requiring a citizen-centric, participatory, collaborative, integrated and transparent governance, which is achieved by e-governance solutions that rely on ICT infrastructure (Nam & Pardo, 2011). E-governance is the area of smart city development where the innovations in infor- mation technology intersect with the political evaluation of the success of the admin- istration. A study has noticed that the political side of the e-governance requires more research as it is currently not adequately represented in the literature (Abu-Shanab, 2013). This study uses transparency as the measure of the quality of the administration in e-government. By investigating international reports on e-governance development, it was noticed that the e-governance readiness correlates significantly with the per- ceived level of corruption and the openness of the budget of the government, which were the two selected indicators for the transparency of the governance. Even though this study demonstrates the success of e-governance with the transparency of the ad- ministration, the study concludes that more research on the subject is needed with more measures and indicators than just transparency, corruption, and openness of the budget. Another study points out that the smart governance should take care of the proper local spatial development plans so that the highest investor interest, like technology parks, R&D companies, business incubators, technology transfer centres and industrial com- plexes should be incorporated in the plans, as these are seen as crucial parts of the smart 32 city (Hajduk, 2016a). This kind of planning ensures the accumulation of adequate intel- lectual resources, institutions, and developed infrastructure to form a smart city. E-governance enables collaboration, but this does not yet ensure that the citizens, com- munities, public institutions, corporations, voluntary organisations, and schools are com- mitted or willing to collaborate. It is said that without the commitment from the stake- holders to collaborate the smart city does not really exist (Nam & Pardo, 2011). It could also be asked, do the citizens really want to collaborate with the government, or do they want the government to increasingly collaborate with them just for the sake of city smartness? When does the government collaboration turn into unnecessary intervening with all community initiatives? Also, when the openness and improved transparency of the smart e-government is said to increase the public support to raise more funding for the e-government projects (Abu- Shanab, 2013), it could be asked if the political objective of the smart city and smart governance is to collect more money from the citizens? Should the technology and po- litical objective actually help in creating a leaner, more economical and less laborious governance system? 3.2 Smart traffic Smart traffic, or more broadly smart mobility, is one of the key initiatives of all smart city developments today. The challenges of the traffic largely include the same topics that drive also the development of the smart cities in general: fast urbanisation, mobility is- sues of the aging population, control and reduction of the climate change and pollution, mobility service development through innovative digitalisation, and discovery of sustain- able and efficient energy sources for the traffic (Hautala, Karvonen, Laitinen, Laurikko, Nylund, Pihlatie, Rantasila, & Tuominen, 2014). 33 In an assessment of urban transport, it is noted that the urbanisation and the related increase in road traffic will cause congestion and air pollution, simultaneously reducing the quality of life (Hajduk, 2016b). The EC has made a forecast that the freight transport will increase by 40 % and the passenger transport will increase by 34 % from 2016 to 2030. Thus, the EC has obliged the European cities to develop sustainable mobility strat- egies with the goal of improving passenger and freight traffic and reducing environmen- tal degradation in the cities. The proposed means to achieve this include the promotion of public transport as well as alternative forms of movement, like walking and cycling. The coordination of timetables between different transportation means, the integration and creation of rhythmic timetables between train, tram, subway, and bus services, with properly planned interchange locations enable the creation of synchronised, multi- modal transport means. The development of intelligent transport systems allows the management of public and private traffic on the roads, including rail traffic, fleet, and cargo transport, and even information for the drivers about traffic congestion and the availability of parking spaces. Interestingly, the study also encourages the cities to invest in road construction, especially the modernisation of the ring roads and the exit routes from the city to the national roads are seen important. Still, for example, the city of Hel- sinki continues the controversial planning of converting its main exit routes into slower and narrower city boulevards (Lempinen, 2019). The latest international research presents some interesting examples that widen the scope of the smart traffic concept to new areas of innovation. For example, the typical car-sharing services have so far used standard mass-produced cars. However, a design and manufacturing study in Bogotá, Colombia, attempts to create an electric super-com- pact vehicle uniquely for car-sharing purposes (Mendoza-Collazos, 2018). The design of the car is motivated by the desire to reduce the congestion with the small car size, the goal to preserve the user experience of a private car, and the wish to simultaneously improve the usability of a super-compact car. 34 Another study example presents how the computational power available today can be utilised in a traffic flow forecasting method that is based on a cascaded artificial neural network (CANN) (Zhang, S., Kang, Hong, Zhang, Z., Wang, & Li, 2018). The writers assume that this is the first study where CANN is used in traffic flow prediction. The developed system utilises open data and APIs to input and process weather information, map and route information, and traffic schedule, holiday, and behaviour information of the citi- zens to the system. The municipal road surveillance cameras provide pattern recognition information from the license plates to identify and timestamp the cars on the road. This information is fed into three artificial neural networks (ANNs): The long-term ANN cal- culates the periodicity of the traffic on a weekly lever, the medium-term ANN computes the daily periodicity and travel habits of the drivers, and the short-term ANN calculates the numeric variation trends of the flow of the traffic. The cascaded results of these three ANNs indicate promising performance and increased effectiveness in the traffic flow predictions compared to the more traditional prediction methods. A prime example of a solution for the last-mile problem in multi-modal smart traffic ini- tiatives is proposed in the form of shared, short-term rental electronic scooters. These e-scooters promise sustainability, reduced environmental impacts, and the benefits of collaborative consumption as part of the burgeoning sharing economy. However, a re- cent study has noticed that the e-scooters may not necessarily reduce the environmental impacts, and potentially may increase the life cycle emissions in comparison to the trans- portation methods they replace (Hollingsworth, Copeland, & Johnson, 2019). More effi- cient collection of the e-scooters for charging, shorter distances of e-scooter distribution, and prolonged e-scooter lifetimes could reduce much of these negative effects. Unfortunately, the recent news indicate that the lifetime of the e-scooters may often be calculated in days instead of years, that the sharing economy may leave the e-scooter collectors with low wages, while the riders increasingly find themselves injured by e- scooter accidents. A study by an online business publication reports from Louisville, Ken- tucky, that the average lifespan of an e-scooter is only about 29 days, the longest lifespan 35 observed was just 112 days, and about 4 % of the e-scooters disappear during their first day in service (Griswold, 2019). A Finnish newspaper reports that the e-scooter compa- nies may pay only one euro per a scooter for the collectors, with a possible freelancer agreement including inadequate employment terms and conditions (Harju & Nuuttila, 2019). Furthermore, the daily newspaper from Helsinki reports increasing amounts of injured e-scooter riders with fractured facial bones, even brain injuries, broken teeth and upper limb fractures requiring surgery (Kantola, 2019). A research from the United States confirms similar findings, with close to a fourfold increase in hospital admissions, with nearly a third of the patients having a head injury, due to e-scooter accidents between 2014 and 2018 (Namiri, Lui, Tangney, Allen, Cohen, & Breyer, 2020). 3.3 Smart sustainability Sustainability and the ICT are often seen as the main tools that drive the smartness of the cities. Moreover, both these tools should also be used when developing and studying the smart cities further. The sustainability of the smart cities usually focuses on three dimensions: the economic, social, and environmental sustainability. The economic sus- tainability is addressed by smart economy solutions, like e-commerce and e-business, that drive the attractiveness of the smart city in the eyes of both the potential employers and employees in order to maximise the employment rate (Silva, et al., 2018). Smart economy also drives the optimisation of public expenditure and energy consumption. The maturity of the social infrastructure and the social awareness of the citizens drive the social sustainability of the smart city. The overall urban ecosystem must also maintain environmental sustainability, otherwise the longevity of the smart city and the entire planet is in danger. The smart city can con- tribute to the sustainable environment directly by smart environment initiatives that ad- dress the air quality, resource management and ecological awareness of the city (Giffinger, et al., 2015). The smart environment initiatives include smart technology so- lutions for cleaner energy, energy savings, and smarter, more sustainable housing. Also, 36 the smart traffic solutions address environmental sustainability from many, partly con- tradictory angles. The smart traffic solutions try to reduce the overall amount of traffic, improve the traffic flow, reduce the used amount of energy, and increase the use of re- newable energy sources. However, the environmental sustainability is interlinked with the economic sustainability and the social sustainability. The environmental sustainabil- ity cannot be achieved if the goals of also the social sustainability and economic sustain- ability are not aligned with the environmental goals. Smart economy can help in optimi- sation of, for example, the energy efficiency, while the social responsibility and under- standing of the environmental issues can be increased by the goals of social sustainability. In a study a content analysis was made to see how ICT and sustainability are connected in official smart city reports with the six smart city characteristics of the European Smart City Model: smart economy, smart people, smart governance, smart mobility, smart en- vironment and smart living (Bifulco, Tregua, Amitrano, & D'Auria, 2016). It was noticed that the sustainability had the strongest connection with the smart governance, smart economy, and smart people characteristics. Thus, the smart city reports seem to empha- size the economic and social dimensions of sustainability. The fourth strongest connec- tion was noticed between sustainability and smart mobility, indicating that the environ- mental sustainability dimension is mostly seen as the responsibility of the reduced CO2 emissions and renewable fuels provided by smart traffic solutions. An interesting recent study investigated how the level of the city smartness impacts the carbon dioxide emissions and, therefore, the level of sustainability the smart cities achieve with their smart city initiatives (Yigitcanlar & Kamruzzaman, 2018). The study investigated 15 cities, with various levels of city smartness, in the UK during 2005–2013. Surprisingly, the study concluded that there is no strong evidence on positive correlation between the adoption of smart city technology and the increase of sustainability. Fur- thermore, it was noted that the smartness of the city did not have any real effect on changing the CO2 emissions over time, either. The researchers suggest that the smart 37 city strategies should be better investigated and aligned to gain any substantial results on sustainability. Similar conclusions regarding the sustainability of smart cities have been reached in a study analysing and comparing smart city assessment frameworks and urban sustaina- bility assessment frameworks (Ahvenniemi, Huovila, Pinto-Seppä, & Airaksinen, 2017). It was noticed that the smart city frameworks tend to concentrate much more on the modern technologies and smartness of the city than on the urban sustainability frame- works. The smart city frameworks emphasize the social and economic indicators while lacking environmental indicators. Thus, even though one of the main goals of the smart city is to improve the economic, social, and environmental sustainability of the city, this goal is not adequately represented in the smart city performance indicators. The apparent conflict between the methods of achieving the objectives of the mutually exclusive dimensions of economic, social, and environmental sustainability is another topic of lively debate and study. For example, a concept of sustainable sufficiency is de- veloped and presented to tackle all three dimensions of sustainability simultaneously (Lamberton, 2005). It is proposed that the neoclassical economic priorities of the West- ern society should be replaced by the principles of the Buddhist economics, emphasizing the mutually beneficial, tolerant, peaceful, and environmentally friendly aspects of the Buddhist economics. Unfortunately, this interesting study does not yet include any real- life cases of predominantly Buddhist societies where the smart cities would present suc- cessful examples of sustainable sufficiency. 3.4 Smart technology Much of the smartness of the smart city relies on the innovative, interoperable, and syn- chronised use of various IC technologies, forming a network on top of which the socio- technical information systems of the smart city can operate. Fast communication net- works are needed to convey the massive amounts of data generated and collected by 38 the smart cities. The data is processed in powerful cloud-based computing systems. The use of IoT technologies have a pivotal role in enabling the collection, access and utilisa- tion of the data that makes the cities smart. The importance of the role and use of the IoT technology in successful smart city imple- mentations has been recognised in a study (Park, del Pobil, & Kwon, 2018). The utilisa- tion of IoT in the smart city can be categorised into five main sectors: First, in the energy sector the IoT technology is essential in creating smart grid systems that automate the electricity services and optimise the energy consumption of the cities. The energy sector is said to be one of the biggest potential markets for the IoT technology. Correspondingly, the IoT technologies related to energy are also considered the most essential for the smart city infrastructure. Secondly, in the smart home sector IoT is utilised in the imple- mentation of home automation, building automation, and building management solu- tions. Energy usage monitoring and energy load management play an important role in the smart home control. The smart building optimisation is implemented based on big data that is collected on cloud servers and analytical prediction and modelling technol- ogy. Connected home appliances, home sensor networks, context aware technology, and advanced user interface methods with speech and image recognition are the other im- portant enablers of the smart home services. Thirdly, in the smart traffic sector IoT ena- bles a more sustainable mobility by solutions for fleet management, vehicle telematics and smart parking. Fourth, the security sector uses IoT for surveillance, home security, and protection of children and elderly citizens. Fifth, the use of IoT is rapidly increasing in the smart healthcare and smart hospital sector with, for example, electronic medical records, order communication systems and medical personnel tracking solutions. It is naturally not feasible to define a universal smart city technology architecture due to the many variations needed in the solutions. However, a study has formed an illustrative approximation of a generic smart city technology architecture based on an analysis of various existing architectures (Silva, et al., 2018). The constructed generic smart city ar- chitecture is comprised of four bottom-up technology layers: data collection layer, data 39 transmission layer, data management layer and application layer. The protection of the sensitive data moving between the layers is handled by various security modules that vertically cover all the other four layers. This generic smart city technology architecture is illustrated in Figure 4, below. Figure 4. Smart city technology architecture (adapted from Silva, et al., 2018). The data collection layer in the bottom consists of the sensors, actuators, cameras and other sensing devices capable of collecting vast amounts of diverse data, ranging from personal health information to ambient, climate and weather data, and to live video footage and exact geolocation of moving objects (Silva, et al., 2018). The data collection can be considered as the most important operation of the smart city, as it has the control over the rest of the smart city operations. The data collection can also be to most chal- lenging layer because of the enormous amount of heterogenous data that must be han- dled. The data collection layer interacts with the data transmission layer through various wire- less and radio-frequency technologies and protocols, such as Bluetooth, Zigbee, near- field communication (NFC), radio-frequency identification (RFID), and global navigation satellite systems (GNSS, for example GPS) (Silva, et al., 2018). The transmission layer also 40 takes care of delivering the collected source data to the data management layer over the internet or various mobile telephony networks. The reliance of the data transmission on mobile telephony networks potentially constructs a huge legacy problem that should be considered more carefully. First, the older mobile networks will sooner or later start to struggle with the ever-increasing data amounts collected from the sensors. Secondly, the network operators tend to completely shut down older networks in order to free up spectrum for newer network technologies. For example, Vodafone, one of the biggest mobile operators, has announced that they are shutting down their 3G networks globally to make way for the newer 4G and 5G technologies (Vodafone, 2019). This may sound trivial from the operator perspective, and even from the perspective of the mobile phone users who can have various levels of eagerness to update to a newer phone. However, the millions or billions of sensors and cameras scattered around the cities, with an old mobile telephony chipset embedded in them, will render themselves useless the second the operator switches the old network off. The same will happen again with the 4G and 5G technology in due course. The task of changing the installed device base every few years will be enormous and keeping their protocols, operating systems, drivers, software platforms and applications up to date and interoperable nearly impossible. The data management layer takes care of the manipulation, organisation, analysis, and storage of the data (Silva, et al., 2018). The heterogenous nature of the collected raw data causes requirements for the maintenance of the vitality of the data. Data cleaning, data filtration and data fusion enhance the usability and processing efficiency of the data. The data may also include valuable pieces of unknown or hidden information. Data min- ing is a technique for revealing this information. It is proposed that the data analysis performed on the data management layer could consolidate big data analytics methods for the real-time analysis of the large data amounts collected from the smart city envi- ronment. The storage of the data requires innovative use of cloud-based, hybrid and scalable storage architectures. Finally, before conveying the data to the application layer, precise and real-time decisions from the heterogenous data are made by the event man- agement and decision management algorithms of the data management layer. The 41 correct decision making is vital for the uninterrupted operation of the smart city. There- fore, the decision-making algorithms are under extensive research and development now. The application layer on the top provides the citizens with the user interface to the smart city technology and services (Silva, et al., 2018). The application layer is therefore in a crucial position to influence the adaptation of and satisfaction to the smart city services. The applications cover the various topics and initiatives of the smart city, like weather information, transport and mobility solutions, health care solutions, security applica- tions and community development and feedback solutions. It is also emphasised that separate and individual smart applications are not as beneficial to the performance of the smart city as interoperable or integrated solutions with shared information would be. The four-layer architecture representation, above, does not explicitly include or catego- rise the technical devices at the users’ end into the smart city technology architecture. Another study mentions mobile telephones and publicly available interactive screens a such user devices (Staffans & Horelli, 2014). This study also points out that the technical devices themselves do not add smartness, until the intentional choice and coordinated use of the technology can create a real-time digital environment. A study of the smart city from the information systems (IS) perspective also points out the importance of in- tegration, easy usability of the system and seamless interaction of the citizens (Ismagilova, et al., 2019). The benefits of the system need to be also communicated to the users to ensure the adequate adoption of the system. 3.5 Smart data Much of the smartness of the city relies on first collecting, arranging, and storing vast amounts data, and then processing and utilizing it in various applications. The data col- lected or administered by the local government is often shared as open data for the 42 public and private sector to utilise. Similarly, the government or the corporations are not able to alone provide all the innovation resources needed for developing the smart ap- plications that utilise the open data. Therefore, the citizens are engaged and encouraged to participate in open innovation platforms for the application development, too. 3.5.1 Open data The smart ICT technology generates data basically from all spheres of human activity. The processing of this data requires adopting the methods of big data, artificial intelli- gence (AI) and IoT. Many researchers point out that the utilisation of data is essential for enhancing the built urban environment, and that the characteristics of big data bring advantages for which the smart cities are considered as the main beneficiaries (Allam & Dhunny, 2019). It is also pointed out that the adoption of big data increases the complexity of and the reliance on data systems (Allam & Dhunny, 2019). The researchers also warn about blindly adopting technology alone, the confidentiality issues and ethics of using big data, and the reliance on closed systems. Instead, the smart cities should increasingly inte- grate the social element in utilising the smart data. Open data is more and more considered as a defining factor of the smart city (Ojo, Curry, & Zeleti, 2015). The open data initiatives are seen essential for the city governments in their efforts to add transparency, boost innovation and encourage the citizens to partic- ipate and bring a more societal view to the smart city development. The open data initi- atives also bring cost benefits, simultaneously lowering the risk of the complex and risky activities when they can be implemented as pilot or trial projects. A study analysed what kind of impact the open data initiatives and the publicly available datasets have in the smart cities (Ojo, et al., 2015). The biggest impact was noticed on the economy, governance, and transport sectors of the smart city. The economy sector 43 was characterised by the creation of ecosystems and marketplaces of open data appli- cations, services for the social sector, and development of tools and foundations for fur- ther innovation. The governance sector is characterised by the development of enablers for information sharing, data standardisation, increased transparency and enhance- ments in interoperability, policies and decision making. The transport sector concen- trates on smart mobility applications relying on the open data related to traffic flow and public transport schedules. The datasets of open data are typically available for trans- portation, mobility, environment and safety, including data for car parks, electric vehicle charging stations, city bike stations, and traffic accidents, as well as surveillance camera data, road works, weather, and even regional crime figures. The governance of large amounts of open data must also be arranged so that the data is managed effectively by entitled persons who have the authority to make the related de- cisions. This also causes some concerns. A study proposing a data governance framework for smart cities has recognized technical obstacles to the data governance (Paskaleva, Evans, Martin, Linjordet, Yang, & Karvonen, 2017). These include the shortage of historic data, difficulties in managing large data volumes, incompatibilities between various technologies and devices, lack of common standards for the data formats, and chal- lenges related to data security and integrity. Furthermore, it was noticed that, in addition to the open data initiatives shaping the smart city development, the concept of smart city itself shapes the open data initiatives (Ojo, et al., 2015). It could be said that many of the open data innovations still revolve around the better utilisation of the open data itself. The researchers point out, that the assessment of the actual efficacy of the open data initiatives in the context of smart city still requires more rigorous research and formal evidence, however. 44 3.5.2 Smart applications The smart city needs open innovation that combines the knowledge and social capacity of its citizens to develop more competitive and simultaneously more sustainable envi- ronment on top of the physical infrastructure (Paskaleva K. A., 2011). The social and en- vironmental capital on top of the ICT are said to distinguish the smart cities from the merely digital or intelligent cities. The living lab (LL) is an innovation ecosystem for fos- tering and incubating this social and environmental capital from the citizens. The LL is formed usually locally as a partnership of the city government, businesses, and citizens. The LL encourages the citizens to participate in a user-driven research and development of ICT solutions for the smart city. The LL provides a bottom-up approach and a real-time environment for the citizens to create, prototype and utilise new ICT products and ser- vices in a more effective and inclusive manner. The LLs have become an increasingly important platforms for the smart city innovation globally (Paskaleva K. A., 2011). In Europe, the cooperation and benchmarking of the LLs is coordinated within the federation of European Network of Living Labs (ENoLL). There are currently over 150 active global living lab members in ENoLL, with over 440 past members since the founding of ENoLL in 2006 (European Network of Living Labs, 2020). 3.5.3 Data privacy and security Data privacy and security are nowadays always a topic when big data, IoT, AI, cloud- based services and so-called platform economy are concerned. Much of this develop- ment happens inside the smart city context too. A study proposes a privacy aware smart city where the five typical dimensions of citizens’ privacy: identity, queries, location, footprint, and ownership can be preserved with existing privacy enhancement technol- ogies (Martínez-Ballesté, Pérez-Martínez, & Solanas, 2013). 45 The identity of the user of the smart city services could be preserved by using multiple independent pseudonymiser services (Martínez-Ballesté, et al., 2013). The correlation of users and their queries could be hampered using trusted third party (TTP) solutions and private information retrieval (PIR) approaches. However, the researchers admit that, due to the high computational and communication costs, the PIR approaches are not yet practical in many real-life applications. The location of the user could be preserved with a cloaking service or by the collaboration of the users to veil their exact locations. The footprint of the user refers to the big data and open datasets, collected from e.g. various sensor networks, revealing the users’ whereabouts and utilisation of these services to third parties. The use of statistical disclosure control (SDC) for the datasets is proposed before their publication. The ownership of the queries made across databases can be preserved from third parties with the help of SDC and privacy-preserving data mining (PPDM) techniques. Even though these technologies exist for securing data privacy, there are still many open legal, political and commercial questions related to who should implement these techniques, how this information should be transported between mul- tiple infrastructure domains and what is the related cost. The increasing amount of smart data and user data that is utilised by the big social media and platform economy corporations has raised the concern of data monopolies (Mulligan & Olsson, 2013). These are companies that collect and store vast amounts of user data in exchange for seemingly free services. The users are practically becoming unpaid labour for these platform corporations. There is a concern that the user data of the smart city applications should not become monopolised. Instead, the data should be made available as a public good for common civic improvement, and the users should retain the ownership of their data. Furthermore, it is noted that many of the platform economy and internet giants make profit also by utilising technologies that were originally developed with public funding, like search algorithms, touchscreen displays, Global Positioning System (GPS), and virtual assistants that use machine learning and AI algorithms (Mazzucato, 2018). Even the 46 internet itself has its roots in publicly funded development of military and defence tech- nologies. At the same time these giant data monopolies avoid regulation that would be typical in any other monopolistic industry. It is argued that the citizens’ data should be regulated and owned by a public repository that can sell the data to private companies, instead of the large technology companies imposing their conditions on the data users. 3.6 Measuring smart city performance The smart city can be characterised by three main categories: The level of utilising the ICT infrastructure to improve the efficiency of the urban development, the level of com- petitiveness the city offers to increase the prosperity, and the level of sustainability and social inclusion the city can provide. But how can these characteristics be measured? The smartness of the city cannot be properly evaluated, unless there are some com- monly accepted and reliable measurement and assessment methods in place. Typically, the smartness is measured by various global and regional smart city rankings, provided periodically by research institutions and private consulting companies. There are also municipal environmental services that provide physical measurement data on environ- mental variables. There is nowadays also an ISO standard for measuring the performance of city services and quality of life. A study about the effectiveness of the smart city rankings analysed 20 different smart city rankings (Giffinger & Haindlmaier, 2010). It was able to identify five general types of city rankings with different characteristics. These are: Commissioned economy- or con- sulting-oriented rankings, commissioned rankings by expert panels or private research institutes, rankings by magazines or non-governmental organisations (NGOs), rankings by universities or research institutes, and special rankings that cannot be properly cate- gorised. 47 The commissioned economy- or consulting-oriented smart city rankings typically include relatively many cities globally, but without explaining how the sample cities have been selected (Giffinger & Haindlmaier, 2010). The details of the ranking results are usually only partially included, the number of indicators is moderate, and the actual indicators, the used data base and the calculation methods are usually not documented. The com- missioned rankings by expert panels or private research institutes are typically lacking transparency, and the selection of the city samples is not clear. However, the rankings usually include a wide range of cities. Although the results and some original data is published on a detailed level, the used data base is not documented properly. The city rankings by magazines or NGOs are usually country specific, or they include cities from one continent, resulting in a relatively small number of selected cities. The selection is often based on the size of the population. These rankings are typically made without sponsoring. The selected method is well documented, and the results are presented in a detailed level. The ranking is based on average values. The rankings made by universi- ties or research institutes generally have the methodologically most advanced rankings, with transparent and good-quality documentation rankings, indicators, and calculations. In the fifth category the researchers have found some peculiar city rankings that they call outliers that do not fit in any of the other four groups. The study warns about the potential risks and negative effects of the city rankings (Giffinger & Haindlmaier, 2010). The simple concentration on the final ranks alone can often lead into theatricality, beauty contests, self-promotion, and recursive self-affirma- tion by the winning cities, while the losers simply ignore the results. Instead, the cities should take advantage of the detailed methods and indicators presented in the city rank- ings, and utilise this information as an instrument of strategic planning, as a guide for the cities to evaluate their strength and weaknesses, and as a tool to improve their com- petitiveness. At best, the transparency presented in the better-quality city rankings also forces the cities to make their decision making understandable and transparent accord- ingly. The writers of this study are also behind the development of the European Smart 48 Cities ranking (Giffinger, et al., 2015), which is often referred to in other smart city re- lated studies. Because of the multitude of the smart city rankings and the differing measures, indica- tors, characteristics and city selection criteria used in them it is unfortunately impossible to say what is the smartest city in the world, region or country, although many of the cities and city rankings can be found to proclaim so by themselves. The reader must be aware and take note of the source, sponsor, commissioner, and method of each city rank- ing. Reading through several different city rankings, preferably with both geographical and temporal variation, will give the enlightened reader an approximation and overview of the cities that generally are successful and recognised for their smart city efforts. Another perspective to the evaluation of the smart cities is the way how the cities them- selves measure and report the success of their smart city initiatives. The intention of the ISO 37120:2014 standard: Sustainable Development of Communities – Indicators for City Services and Quality of Life is said to be the most practical method for the cities to meas- ure and monitor the performance and efficiency of their sustainable development (Hajduk, 2016a). The standard and its methodology can be applied regardless of the size, location, or position of the city. The standard also provides five certification levels – as- pirational, bronze, silver, gold and platinum – for the cities to make comparisons and learn from each other The ISO 37120:2014 standard defines 100 city performance indi- cators structured around 17 themes. The 100 indicators are divided into 46 core and 54 supporting indicators. The 17 themes of ISO 37120:2014 are depicted in Figure 5 (World Council on City Data [WCCD], 2020). The standard has been developed to a newer ISO 37120:2018 version, with slightly updated themes and indicators (International Or- ganization for Standardization, 2018). The new themes and indicators are listed in Ap- pendix 1. 49 Figure 5. 17 themes of ISO 37120:2014 (adapted from WCCD, 2020). The ISO 37120 is said to introduce two important benefits that have not been previously available: First, the 100 indicators of the standard are carefully selected and qualified from the thousands of existing and varying city performance indicators. Secondly, the standard also provides precise definitions for the indicators (Fox, 2015). The objective of this is to give the cities consistently interpreted and applied metrics by which the cities can compare their performances. A study has noticed that, although the standard pro- vides objectiveness and relevance to the city performance evaluation, the standard has challenges in providing results which are consistent and sustainable over time, auditable, comparable, effective, and statistically representative. Only the indicator values are re- ported without the background data about the source of the values. Thus, it is only pos- sible to notice that the indicator values may vary over time, or in comparison with other cities, but it is not possible to detect why this may happen. The study seeks to provide an automated method for longitudinal and transversal analysis of the indicator values and their metadata, so that it is possible to evaluate how and why the indicators change over time or vary between each other. This way the root causes of the differences could be detected. 50 On the local level it is also possible for the individual cities to provide metrics and meas- urements of their performance. For example, Helsinki climate watch (Helsingin ilmasto- vahti), measures the progress towards the goal of carbon neutrality by year 2035 (City of Helsinki, 2019). The web page displays over 200 functional, tactical, and strategic measurements by which the city of Helsinki monitors how the goals of the 147 agreed actions are reached. Similar kind of climate change related measurement data is also provided by HSY, Helsinki Region Environmental Services Authority (Helsingin seudun ympäristöpalvelut, 2019). This kind of public measurements data does not only inform the city about the progress, but it is also a good way of getting the citizens committed to the common sustainability goals. 51 4 Literature review synthesis For the smart city, the literature would have known many other definitions than what are presented in this study. However, after a while the smart city terminology starts to repeat itself, the defining terms become synonyms of each other, and the same terms become grouped under different subtopics. In the following two sections the smart city is first synthesised based on the relevant smart city definitions found from the literature, and then synthesised as a conceptual framework based on the goals, initiatives, building blocks and stakeholders of the smart city. 4.1 Research synthesis of smart city definitions Table 1, below, first lists three smart city definitions, found from the literature, that ad- equately cover the various viewpoints to the smart city phenomenon. Additionally, the table also summarises the synthesis of the key smart city stakeholders and building blocks that were identified during the literature review. This information should further answer the questions of who the actors of the smart city really are, and what are they actually doing to build the smart city. Table 1. Research synthesis of smart city definition. Smart city viewpoint Smart city definition European smart city Smart city performance is defined by six key indicators of smartness: smart governance, smart economy, sm