Perspective Chapter: Smart City(ies) – Citizen Equalisers or Inequality Generators

Abstract

The UN predicts that by 2050, 72% of the world’s population will be urban dwellers, a global migration and human shift that will ultimately lead to a significant social, economic and environmental transformation of urban environments. Not surprisingly, such a prediction has led to an increased interest in the growth of smart city(ies). Literature suggests that these ecosystems, that is smart city(ies), increase productivity and grow social, human and economic capital, and have the potential to reduce inequality(ies) amongst its citizens. This chapter will argue, that such expectations of inequality reduction, may not be the case. That current technocentric approaches fail to address urban problems associated with inequality, including urban sprawl, poverty, higher rates of unemployment, growing urban costs, and housing affordability. Recommendations will be made for the use of alternative mechanisms in the design of these ecosystems, to achieve the ultimate goal of reduced inequality, while simultaneously creating more liveable, vibrant and social, economic and sustainable city(ies) and community(ies) of the future.

1. Introduction

Urban populations and the city(ies) that they live in, are both transforming and are being reshaped, economically, socially and environmentally [1, 2]. Resulting from increased urban migration, expansive global changes are predicted to continue, with current estimates forecasting that by 2050, the world’s population of urban dwellers will grow from more than 50% to in excess of 72% [3]. With such migration predictions, both positive(s) and negative(s) outcomes are expected. Urban growth has been seen to make positive contributions to society. In that, increased knowledge sharing, idea creation, innovation and entrepreneurship [2, 4], will contribute to increased productivity [5] and social, human and economic capital growth [6, 7]. However, some have further noted, that rapid urban growth also creates significant conflicting externalities that result in increasing rates of poverty, higher urban unemployment, growing urban costs, housing affordability issues, rising inequality and environmental degradation. Issues that are compounded by limited investment in infrastructure, and weak fiscal and urban governance by municipal governments [8].

The need to address these issues within urban environments, has led municipal governments around the world to partner with global technology firms to design and implement smarter city ecosystems [9, 10]. Such technology driven ecosystems promise a technology driven utopia for urban citizens. In that, the creation of smart cities leads to a growth in economic, social and human capital and simultaneously promise increased prosperity, healthier lifestyles for its citizens and a more highly educated population [10, 11, 12]. In essence, by increasing digitisation, harnessing the power of information and telecommunication technologies (ICT) and investing in smart technology(ies), municipal governments can improve citizenship collaboration and create more effective institutions with increased ability to address and resolve urban problems [1]. In that, technology driven city infrastructures enable the necessary social, cultural and economic foundations required for sustainable urban development ([13, 14], p. 307), along with reductions in environmental degradation [15]. Additionally, through the creation of smart city(ies), municipal governments can enhance their ability to identify and implement mechanisms targeted at integrating growing populations from diverse socioeconomic, ethnic, and religious backgrounds [16, 17]. Consequentially, making our cities greener, safer and more culturally vibrant [18, 19].

Whilst to date, there is limited evidence to doubt that increased use of ICT is transforming and reshaping the nature of urban life [2, 20, 21, 22], some commentators question the increasing reliance on and use of technology(ies) in planning urban ecosystems. For example, some have questioned the one-dimensional techno centric perspectives associated with most smart city implementations. Arguing that the smart city movement has inadvertently been left to politicians, administrators and global technology firms to identify which problems are to be addressed, and to implement mechanisms aimed at strengthening the capacity of urban systems to tackle them [23, 24]. In so doing, a limited space to accommodate the vital social aspects and dimensions of city life is created [25], failing to take into consideration the competing and often conflicting perspectives from the diverse stakeholders, communities and groups that arise from the complex, dynamic and shifting nature of city realities [26, 27, 28]. Commentator [29] goes further, by suggesting that such ICT driven urban environments, potentially limits their citizens capacity for independent thinking and effective communication(s).

Such debates have ultimately led to questioning the ideological basis for smart cities. Suggesting that it is flawed, and that it somewhat hides the economic and social fragmentation and polarisation [14, 30, 31] resultant from the creation of gentrified neighbourhoods for wealthy highly skilled smart workers [30, 32]. Consequentially, creating urban environments that are not politically inclusive and culturally creative, otherwise more difficult than those promoting smart city ideologies would suggest [14, 33, 34]. Thus, suggesting that creating smart city(ies) requires more than ICT considerations alone. Rather, as this chapter will argue, preventing such negative outcomes within smart city(ies), requires an increased recognition and awareness of the role played and impacts arising from and on diverse stakeholder(s), including businesses, community groups, and citizens, particularly those who are already disadvantaged within our current urban environments as a consequence of their ethnicity and or economic and social status.

Commentator [35] argues that, how urban planners and policy makers perceive and embrace such diverse stakeholder viewpoints, has an impact on how they contextualise, plan and implement smart cities, and on the decisions made across the urban design process(es), particularly in areas directed at improving economic wellbeing, sustainability and livability. Others argue, that creating vibrant and liveable city(ies) can only be achieved if those responsible for smart city(ies) design and policy making, take into consideration and make accommodations for the needs of a wide range of stakeholders, including businesses, and in so doing harness, tap into and leverage from the innovation and creative power of human, social, entrepreneurial, and infrastructure capital that exists within these groups [36]. Such viewpoints raise a number of questions: What can be done to limit the potential inequality(ies) emergent from current approaches to smart city(ies) design? How can business(es) contribute to reducing urban inequality(ies) within smart city(ies), and what does this mean for those who govern our cities?

By leveraging the corporate social responsibility (CSR) and corporate citizenship (CC) literature, this chapter builds an argument for alternative ways in which those responsible for urban policy and design, and governance of smart city(ies) can meaningfully, productively and efficiently create closer collaborations with business(es), with the aim of minimising the potential for smart city(ies) to create additional urban socioeconomic problems such as income, ethnic, cultural and educational inequality. To set the scene, this chapter will first explore how and why our city(ies) and smart city(ies) ecosystems have and may continue to contributed to an increase in socio-economic and cultural inequality(ies). The chapter will then explore the contributions and promises that businesses make to our cities, and identify the contribution(s) they can make to addressing urban inequality(ies) and to creating socially, economically, and environmentally sustainable city(ies), whilst simultaneously making them smarter, more liveable, healthy and vibrant. The chapter will then discuss the role of the public and citizenship inter-play in addressing urban inequality(ies) within smart city(ies) ecosystems. A case is made for greater collaboration between municipal governments, institutions, business(es) and community stakeholder groups, including citizens, within smart city contexts. The chapter concludes with recommendations as to how those responsible for smart city(ies) design, policy making and implementation can improve the way they work with businesses, to more effectively harness their capabilities in resolving the emergent issues associated with rising inequality in our cities in general, and how they drive smart city ecosystem(s) creation.

2. The changing shape of city(ies) and urban inequality(ies)

Scholars studying the changing nature of urban environments have noted that to date, changes and transformations in our city(ies), even those that are significant in nature, have not necessarily contributed to a rise in equality for urban citizens. Rather, inequality in city(ies) continues to grow. Rapid population growth and urban migration, coupled with a lack of investment, poor financial and urban governance by municipal administrators, has led to a rise in the cost of living due to growing housing and urban costs [37], urban sprawl, higher urban unemployment, and a rise in income and social inequalities [38, 39, 40]. Others have suggested, that due to their simultaneity, these factors are creating urban environments that are characterised by increasing poverty and inequality [41, 42], and environmental degradation [8, 43, 44].

Whilst for researchers, these issues have long been an area of focus, discussion and debate, interest in these areas has grown as researchers work towards developing a greater understanding of the impacts and implications of growing income and socio-cultural inequalities emerging from a rise in globalisation, international migration and increased neoliberalism by government(s) [45, 46, 47]. However, to date, most studies overly focus on income data only, as a means of measuring the degree to which our society(ies), city(ies) and community(ies) are less or more equal. Consequentially, such studies fail to take into consideration the fact that inequality is a multifaceted phenomenon that has economic, social, environmental and political dimensions. Meaning that, several variables influence inequality(ies) and their impacts, including those of; class, race ethnicity, age, gender and citizenship status [48, 49, 50], the changing shift to new modes of production and new economic models, for example, increased digitalisation, information-based economy(ies) and consumer-oriented service models [51], alterations in labour relations [40], and the increased focus by municipality(ies) in reviving urban centers [52, 53]. Thus, developing a deeper understanding of the nature of urban inequality(ies), their impact(s) and identifying appropriate responses, requires evaluating how these interrelated factors impact urban citizens.

2.1 Inequality: income and employment

Most researchers and commentators suggest that the rise and, in some areas, relative decline in manufacturing has driven most of the changes in urban life. In the US alone, studies indicate that the share of workforce participation in manufacturing dropped from 24% in 1960 to 8% in 2016 [40], a trend that is predicted to continue [54, 55]. Research also indicates, that over this period, urban and population growth has been directed by a move from manufacturing, to a dynamic new economy characterised by new modes of production based on an information and digital driven economy and a rise in finance, professional, business services and high-technology industries [51, 56, 57]. Despite this, this dynamic new urban economy has not improved urban inequalities. Given that most company and job growth in city(ies), for example New York, and even traditional manufacturing hubs such as Chicago and Pittsburgh, has been driven by technology, finance, insurance, pharmaceutical, business services, such as accounting and insurance cultural industries and firms. With these firms requiring, highly educated, highly-skilled and highly-paid white collar workers to operate as ‘symbolic analysts’ [58].

In the US, such change has inadvertently led to an increase in income inequality that is most extreme. For example, 2016 in New York, 40% of all income went to the top 1% of income earners, with only 1% of all income going to the bottom income earners [59]. A trend that is also seen in Europe, China and India [38, 39]. Such trends creating a deepening of inequalities between these professional class workers and clerical, service, retail and hospitality workers who are lower-skilled and lower-paid [40, 50]. In response, some commentators suggest that our urban environments are characterised by bi-modal income(s), bifurcated workforce(s), and polarised social and cultural structure(s) [40, 57, 60], and that these complex and inter-related factors are having a significant impact on the social and economic fabric of our city(ies) [61, 62, 63, 64].

2.2 Inequality: access to affordable housing

Across most city(ies), rising housing and other costs associated with living in urban centers have led to an increase in inner city deterioration and a growing migration to urban fringes and suburbia [65, 66], particularly by citizens from lower-skilled, low-medium incomes and disadvantaged groups [67]. For these citizens, such changes creating additional disadvantages, in that they are faced with longer commutes to lower-paid jobs often in urban centers, by means of inefficient and unreliable public transport systems and or to rely on costly car ownership [68, 69, 70]. Consequentially adding pressure to already over-burdened public transport systems and networks [71], by those whom it could be argued can least afford to do so. Whilst simultaneously worsening inner city environment(s) due to increased air pollution problems [72, 73], and creating infrastructure challenges for municipal governments who are already suffering with fiscal problems [74].

2.3 Socio-cultural inequality(ies)

When considering the growing migration of lower-skilled citizens to urban fringes and suburbia, citizens with low-medium incomes and disadvantaged groups, scholars further suggest that those living on the urban fringe, including the unemployed, low-level services workers, low-status immigrants and minorities, are feeling more socially excluded. Equally such people groups, also find it difficult to access social and community services that are readily available to those living closer to urban centers [75, 76, 77, 78, 79, 80, 81, 82]. Social disparities that have not only persisted through periods of economic growth, but are seen to be worsening for low-income, ethnic and other disadvantaged groups [83]. With disadvantaged groups having less access to social and community networks, essential services and education, yet seen as necessary for inclusion and participation in society, health and wellbeing [84, 85]. Consequentially, urban social spaces are becoming increasingly divided, fragmented and marginalised [80].

Scholars also argue that there has been an emergent increase in socio-cultural inequality within urban centers. A significant body of work exists relating to the relationship between that of race, class, and urban inequality. Studies have found a direct relationship between urban racial and class stratification and poverty, within inner city black neighbourhoods as a result of deindustrialisation and a rise in the new economy [86, 87, 88, 89]. Author [86] found that the drive towards new economic models within urban centers is creating a consequential increase in racial and ethnic wage inequalities, and a perpetuation of white worker advantage within urban labour markets. Scholars have argued that these racial and ethnic citizens are more likely to form part of an uncertain, informal, and insecure labour force, working in casualised, part-time, temporary, and non-formal employment under non-standard work arrangements [90, 91], with lower wages and fewer health insurance and retirement benefits [92, 93, 94, 95, 96]. A situation that commentators [97] attributes to a significant reduction in longer term economic wellbeing, and for those in this group, a growing income inequality [98]. A position supported by commentator ([99], pp. 56–61), who suggests that these citizen groups rarely receive the same socio-economic benefits as their white counterparts. Commentators [100] go further, by suggesting that such inequality also drives inequitable access to public services and goods, including an increase in political inequality and growing inter-group animosity, envy, and citizen perception that the public system remains unfair for these socio-cultural groups.

Thus, it could be argued that urban citizens from lower-socioeconomic backgrounds and those from sociocultural diverse groups, face a storm of factors that both individually and collectively, lead to inequality in urban centers. For example, take the case of the United States. Over the past four years alone, data suggests (see Tables 1 and 2), that the difficulties and challenges these citizens face, has and will continue to grow. Whereby, US house price increases have not kept pace with the share of income to these already disadvantaged groups, rental vacancies have remained steady, though rental costs continued to rise, and during 2021, interest rates remaining at a low 2.9% p.a. despite inflation sitting at a rate of 4.7% p.a.

Year	2018	2019	2020	2021
Median House Price [101]	USD$824,000	USD$864,000	USD$902,000	USD$1,232,000
Approximate Home Ownership-Active Listings [102]	1.4 million	1.2 million	800,000	<500,000
Rental Vacancy Rates [103]	7.0%	6.4%	6.5%	5.6%
Rental price increases p.a. [102]	17.5%	17.6%	18.0%	18.0%

Table 1.

US access to affordable housing 2018–2021.

Year	2018	2019	2020	2021
Inflation Rate: p.a.				4.7%
Interest Rate: p.a.				2.9%
Median Income [104]	USD$68168	USD$72,808	USD$71,186	USD$70,784

Table 2.

US economic factors impacting inequality [103].

Meaning that, as our earlier discussions have shown, in the case of US, those who are already disadvantaged may be faced with multiple binds associated with lack of affordable housing, rising inflation, growing interest rates, less disposable income, and a falling share of overall net wealth to meet rising housing and other costs. In addition, a further concern that this data suggests, is that of non-white ethnic minority(ies) who are accessing higher education at lower rates than white citizens, and who are also less likely to have access to the internet (see Tables 3 and 4). While for urban citizens with income levels below the poverty line, reportedly representing 15% lower than all rates shown in these tables, factors that in and of themselves, further present difficulties for the smart city(ies) movement.

Share of aggregate income - top 5%	23%	23.5%
Share of aggregate income - lowest 5% quintile	3%	2.9%
Gini coefficient	0.488	0.499

Table 3.

Income inequality increase & GINI index [104].

Year	2013	2014	2015	2016
White-Enrolment	350,000	300,000	295,000	290,000
Non-white Enrolment	255,000	250,000	220,000	210,000
Percentage by race/ethnic group digital access in 2017 [106]	Asian/Pacific Islanders - 89.7%	American Indians/Alaska Natives 77.2%	Hispanic - 78.8%	Black/African Americans – 77.2%

Table 4.

US education inequality trends (n = 4360 degree granting institutions) [105].

Some commentators go further and argue that the grand vision of equal rights of access for all citizens in urban settings does not play out in reality [107]. Arguing that those from diverse ethnic, social and cultural communities, refugees, persons with disabilities, the elderly and LGBTQ communities, as a consequence of low socioeconomic status, limited education and poverty, find that their access and rights to our city(ies) is limited. Whereby such citizens, often find that their ability to pursue individual goals and opportunities, and obtain the social, economic and cultural benefits arising from living in these new urban environments is limited, given that they are excluded from urban discourse [108, 109, 110, 111, 112, 113, 114, 115]. In essence, these complex and inter-related factors create and deepen inequalities in urban settings, and lead to a widening and deepening of social and cultural inequalities within urban environments [40, 57].

3. Smart City(ies) as a solution to urban challenges

As this chapter explores the landscape of smart cities and debates of inequality amongst urban dwellers and its citizens, our discussions thus far have suggested that within our urban environments, income, social and cultural inequality(its) are continuing to grow [41, 42, 83]. Commentators argue, that such ongoing growth in and of itself, is inadvertently leading our city(ies) to be characterised by increased urban sprawl, higher levels of poverty, growing urban unemployment, higher urban costs, problems with housing affordability and environmental degradation [38, 39, 40]. Factors that are enhanced by weak financial and urban governance, lack of investment by municipal governments, and the increased urban migration it is creating [8]. Resolving such complex problems and issues, often rests with municipal governments, politicians, and administrators. In essence, it becomes their responsibility, to identify the nature of these problems, determine their prioritisation, and design and implement appropriate mechanisms targeted at increasing the ability for urban system(s) to know how best to respond to them [2, 23, 24].

In response to such challenges, scholars have repeatedly suggested that municipal governments can address and respond to the challenges in our urban environments, by relying on and deploying smart technology(ies), by embracing and exploiting; the power of information technology(ies) (ICT), smarter collaboration, a highly educated population, and the effectiveness of our city institutions to make our city(ies) smarter [1, 30]. For example, author [14] suggests that, leveraging ICT use in city(ies) and associated network infrastructure improves the urban economy, while making political institutions that are more efficient as they drive social, cultural and urban development. This theme, also supported by Datta [13], who indicates that driving ICT implementation and use within city(ies) furthers sustainable urban development. Further, commentators [116] propose, that smart city(ies) have the potential to address many urban challenges, including increasing individual and community participation, and improving the quality of life for citizens by reducing environmental degradation. Thus, by conceptualising cities as network places and using advance ICT’s, scholars argues that through such initiatives, urban environments ultimately become greener, safer, and more culturally vibrant [18, 19]. Such claims attributed to, improving the integration and inclusion of urban citizens from diverse socioeconomic, ethnic, and religious backgrounds [16, 17].

3.1 Smart city: critique

More recently however, scholars have begun to criticise the nature of the approaches taken to the design and implementation of ICT driven urban environments and smart city(ies) ecosystems. These scholars have questioned the one-dimensional ICT perspectives, and the top-down nature of problem identification and decision making [2]. A case in point, is [25] who argues, that smartness does not necessarily equate to an improvement in the social welfare of urban citizens. In that, smart city(ies) somewhat leave limited space for addressing the basic social needs of urban citizens and somewhat fail to address the social dimensions of sustainable development. Others, for example [117] question the notion that smart city(ies) are inclusive. These commentators suggest that inclusive smart city(ies), and by extension the idea that these forms create equality, is nothing more than a policy vision and a marketing strategy by municipal governments and large ICT firms to gain the attention and acceptance of their citizens. In the same vein, they question how municipal governments can align citizen’s choice with such concepts as urban scale, economic growth, and expansion.

Others suggest that, those implementing ICT driven smart city(ies), view the world through a realist epistemology. Leading them to view the reality of urban life through a lens that is objective and totalising. Meaning that, they often claim certain truths about urban realities and systems in ways that hide the political nature of discourse within smart city(ies) [118]. Consequentially, promoting conceptualisations of urban management that are information driven and technocratic, where data and software take primacy, to the exclusion of knowledge, interpretation, and specific thematic expertise [119]. As such, municipal decision makers often fail to: - (i) Recognise that our city(ies) consist of intertwining and inter-related “complex systems of systems” ([2], p. 3) operating across “different space-time patterns of nodes and links” ([27], p. 8); (ii) Consider the potential impacts on and from competing and often conflicting stakeholders and groups, when designing and implementing smart city(ies) [26, 28]; and (iii) Evaluate the potential threats to democracy that could arise from the pervasive collection, distribution and ownership, by private corporations, of urban citizen’s data from personal devices [120].

Scholars are becoming concerned regarding the involvement of large ICT firms in the design and implementation of smart city(ies), and the idea that urban problems can simply be resolved through technical solutions. Suggesting that, insufficient quantitative evidence exists regarding urban smartness and the assumption that this alone increases economic benefits. Rather, the involvement of large corporations, coupled with the implementation of technical solutions to urban problems, will otherwise increase urban inequality(ies) [117, 121, 122]. In the main, these claim’s rest on anecdotal evidence and general conceptualisations. With rigorous and empirically grounded studies on the relationship between smartness and inequality(ies), particularly income, being limited [9]. However, these perspectives should not be readily dismissed, given our earlier discussions on the general rise in income, social and cultural inequalities within urban environments. Authors [9] contends that, it may be somewhat difficult to comprehend how an ICT driven approach to urban challenges through technical, data and software driven solution(s), can address the complex nature of the inequality(ies) emerging in city(ies). After all, ICT driven smart city(ies) require urban citizens to have access to smart technology(ies) in order to participate fully in their urban environment(s).

Yet, for some time, scholars have noted that the growing digital divide and the consequential segregation that can occur for non-privileged groups within smart city(ies), continues to be a reality [123]. Consequentially, it is considered difficult to imagine how urban citizens who are less-skilled, poorly educated and on lower-incomes, gain equitable access to the promised smart city economic, social, and cultural benefits. Nevertheless, a review of the commentary concerning citizen inequality, the digital divide, and the impacts of smartness on these socio-economic groups may provide municipal governments with insight and direction for how smart city(ies) improvements are conceptualised, designed, and implemented.

Central to the debate on whether or not smart cities are solutions to urban challenges, are arguments that suggest these smart solutions inadvertently lead to an unequal distribution of benefits. Scholars base these arguments on the idea that adopting ICT driven smart technologies to create smart city(ies), somewhat favours those who are highly skilled and well paid. In essence, the concern that urban smartness exacerbates income inequality(ies) by championing those who are most capable of obtaining the emerging benefits [9]. These commentators argue that smart city(ies) often rely on costly access to advanced ICT, data and software that worsen income inequality by limiting access for low-skilled urban citizens, while remaining somewhat unaffordable for those on low-incomes [124]. A position supported by [125] who argues, that this access gap has the potential to further widen and re-enforce income gaps for some segments of the population, and between the wealthy and poorer populations in smart urban environments. Yet to date, governments have become increasingly reliant on technology vendors and consultancies (e.g., IBM, CISCO, and KPMG etc.), who have a growing appetite for active involvement in a sector that they perceive to be growing rapidly, and that offers huge financial potential for them [126, 127].

3.2 Smart city(ies): private corporations and inequality(ies)

When considering smart cities and corporations, commentators [126, 127] argue that these private actors (i.e., IBM, CISCO, and KPMG etc.), often promote and overemphasise the role and importance of ICT, data and software technology(ies), to make urban environment(s) smarter through the creation of smart city(ies). However, these solution(s) do not necessarily equate to a reduction in and or resolution of the challenges associated with broader urban inequality problems. Commentators [128] suggest, the way municipal governments invest in smart city(ies) may inadvertently contribute to a growth in income and human capital divisions that are already impacting urban environments across developed countries, due to spatial differences in ICT skills. Consequentially, increasing poverty levels that have already been on the rise for some time [1, 14]. Other commentators argue that, the smart city concept has become a corporate driven initiative aimed at maximising profits for private corporations, particularly large global ICT firms [33], often to the detriment of the welfare of urban citizens. A review by commentators [129] of corporate driven smart city(ies) approaches in Abu Dhabi and Tianjin, highlighted several examples of inequality(ies). These commentators note that, whilst Abu Dhabi’s grand vision is for a city that supports sustainable living, it does not appear to eventuate in reality. In that, the design and implementation leaves limited space for underprivileged and disadvantaged groups, and is not as sustainable as government claims [25]. Further, a similar pattern emerges in Tianjin, and their use of eco-technology(ies) and smart city developments, which fail to consider and recognise the complex web of sociocultural and economic factors that inter-relate within urban environments. As such, leading to a smart city that lacks recognition for the needs and wants of transient populations and those facing urban poverty [130].

A case in point is IBM’s smart city program, which is driven by their recognition of an untapped and growing market for urban technology(ies) [12]. For IBM, addressing urban problems such as rising populations and inequality(ies), ageing municipal infrastructure, and diminishing fiscal revenue, requires that municipal governments adopt non-traditional solutions [130]. IBM’s smart city solution(s), rests on their provision of expert solutions in; urban planning and management, city infrastructure, and human services divided into sub-areas including public safety, smarter solutions for buildings and government and agency administration, energy, water, environment and transportation and technological approaches to social programs, health care, and education [131].

Of importance, is that IBM intends for municipal governments to monitor and regulate these solutions through IBM’s intelligent operations systems. However, several problems emerge from IBM’s solution and the assumptions made. Firstly, the IBM model seeks to redefine and re-orientate city administration functions in ways that suggest a level of homogeneity in the functions of city(ies) around the world. Doing so, allows IBM to create a vision for urban environments that sees city(ies) as one world, which is the opposite of the case in reality [2]. Secondly, IBM assumes that urban problems can be resolved individually, with solutions deployed in isolation. Yet city(ies) are complex systems of systems [2], with inter-related and interdependent urban problems, particularly those pertaining to inequality(ies). Thirdly, IBM takes for granted that there is existing city infrastructure available for them to layer their solution on. Yet as commentators [132] note, many city(ies) lack infrastructure, or it often breaks down, particularly in under-developed countries around the world. In essence, corporations such as IBM, somewhat erroneously believe that they alone can transform urban environments from the top down, by turning their technological solutions into reality through the use and adoption of their organisational rhetoric. Such belief and action leading to a vision, that whilst admirable, fails to take into consideration that city(ies) consist of many different world(s) that are often not commensurable (e.g., education, business, and safety). Consequentially resulting in a flattened city(ies), where those who are disenfranchised, powerless, poor, and on the margins are ultimately treated as disturbances and irritations for IBM’s system of systems [119].

3.3 The digital divide and inequality(ies)

Others, including commentators [133], find that smart city(ies) often have negative externality(ies) including information insecurity, leakage of personal data, and that they may inadvertently create information islands and a greater digital divide. However, the digital divide is influence by more than income inequality(ies). For example, study [134] of 126 countries, using internet data and the Gini coefficient, found a growing digital divide (see Table 4). With access to ICT being shaped by factors not only by income-inequality, rather including socioeconomic, political, cultural, social, and technological factors. Thus, the digital divide is not merely driven by the availability of ICT hardware, such as computers, but also skills access and availability, skills of citizens, democratic divides in society(ies), and the ability to capitalise on the opportunity(ies) inherent in economic developments [135, 136, 137, 138].

Author [135] goes further by suggesting, that ICT access is dependent on personal factors, including age, ethnicity and ability, and the temporal, material, social and cultural resources available to citizens. The latter being fashioned by the prevailing structural, labour, educational, household, and national positions. Other commentators also found that, access to ICT is determined by income, education, ethnicity, gender, and geography [138, 139, 140, 141]. Consequentially, the digital divide is not just a technological or economic issue as believed by those such as IBM, but also driven by stratifications in society [134]. Meaning that, studying the impacts and implications of the digital divide, and developing relevant research frameworks and policies, is complicated and further biased by, the very fact that it somewhat mirrors societal inequality(ies) already existing within the culture of our city(ies) [142].

Nevertheless, scholars generally agree that citizens with similar levels of income, who have higher educational levels, have higher rates of access to technology(ies). Meaning that, less-educated citizens often find it more difficult than those with higher levels of education to access the ICT and the associated benefits [134, 143, 144, 145]. Equally, studies such as [9] of income inequality in 106 European city(ies), found that smart city(ies) are associated with lower levels of income inequality. In general, factors influencing digital access also includes, income and the extent to which citizens can afford the costs associated with internet access, whereby, household and individual income are acknowledged as key determinants of ICT adoption [144].

However, these researchers [9], did not take into consideration the impacts of the digital divide on other aspects of inequality. Thus, it may be argued that these positive findings do not necessarily equate to a rise in educational, social and cultural equality(ies), unless other factors that increase digital divides are taken into consideration. A case in point are elderly citizens, a significant proportion of whom have never accessed the internet, are not digital natives, and often face difficulties using digital technology(ies).

Studies indicate that in the United Kingdom, 4 million elderly citizens do not have access to the internet and face digital exclusion [146]. While across Europe, internet access ranges from 4% in the UK to 14% in Bulgaria [147]. Rather, evidence from surveys and observational studies that investigate broader impacts on inequality in urban environment suggest that, for urban citizens, smart city(ies) often lead to an increase in socio-economic segregation. For example, researchers [123] mixed methods case study of Harlem in New York City, found an emerging digital segregation, with some citizens; the privileged group of elites, gleaning financial and social rewards and improved recreational and social lives, while others who were less advantaged, were feeling excluded, victimised and preyed upon.

Additionally, a recent study of US cities progress towards smartness by [148], found that only 70% of city(ies) took into consideration the needs of citizens with disabilities, particularly those with specific functional impairments such as those who are vision impaired, and or, those who require wheel chair access. From those studied, only one city, Columbus Ohio, sought to address the needs of citizens with cognitive challenges, in their approach to smart city design and implementation. Leading the authors to suggest that, municipal governments somewhat exclude the needs of other marginalised groups such as, those with communication and cognitive challenges, pregnant women, those whereby English is not their native language, low-income, and other under-represented groups such as LGBTQ+ community(ies). Thus, suggesting that the drive towards smartness in urban environments, as a consequence of lower inclusion and increased socio-economic segregation, may actually be increasing social, economic and cultural inequality(ies) in urban environments. Such arguments lead commentators such as [149] to suggest that, within smart city(ies), the digital divide further creates a scenario where not all urban citizens have access to digital technology(ies). Such insights having profound implications for smart city(ies). After all, smart city(ies) in their very concept, require equal access to ICT, data, software and digital solutions to improve the welfare of urban citizens, enable more liveable environments for urban citizens, while simultaneously generating income, whereby meeting the expectations for a return on investment by municipal governments [149].

In essence, these arguments suggest that smartness may not necessarily equate to inclusion and equality for all urban citizens [25, 117]. Rather, current approaches to smart city(ies) design and implementation, driven by the narrative of large ICT firms, may be inadvertently creating a confluence of socio-economic and socio-cultural factors that lead to a growing proliferation of social inequity process(es), and the creation of inequality within urban environments. Our discussions on the current state of income inequality in urban environments, suggests that this often leads to an increase in poverty and associated lack of access to educational opportunity(ies) [84, 85, 105, 106]. The author would argue, that this means, that those urban citizens who are already disadvantaged, will as a consequence face difficulty in gaining access to the highly skilled jobs that are in demand in smart city environments. Further, as we have demonstrated, urban citizens who are from lower socio-economic, ethnic, and elderly groups are also more likely to face digital disadvantages [108, 109, 115]. Thus, suggesting that these groups of citizens face a double bind problem that is further compounded by the current approaches to smart city(ies) design. In that, these citizens not only have limited income and access to the educational opportunity(ies), but may also not have the means or skills available to access and capitalise on the intended benefits emergent from the smart technology(ies) being deployed in smart city(ies).

With such things in mind, if municipal governments intention is to create smart community(ies) through smart city(ies) programs that create vibrant cities that enable and enhance equality for all urban citizens, then that intention also requires these government bodies to actively work more closely with these firms to improve access to the ICT technology(ies), services and software platforms provided by corporations. Doing so will require a move away from approaches that emphasise the implementation of data and software driven ICT technology(ies) [2], while taking action to modify societal and community perceptions and behaviours [150]. In essence, what is needed, is not a dismissal of corporate involvement and the smart city vision, but a more holistic universal approach to its design and implementation. One that simultaneously recognises the diverse and complex needs of urban populations, and understands that different groups of citizens have limitations to some degree [151].

In practice, this means that those who design and implement smart city(ies), need to recognise the role those multiple stakeholders, including businesses, community groups, ethnic, disadvantaged, low-income, low-educated groups and citizens, play in identifying urban issues and resolving them. Such diverse viewpoints should not be ignored, given that the degree to which municipal decision makers take into consideration diverse stakeholder viewpoints, influences how they contextualise smart city(ies), the choices, decision and approaches they adopt in the design and implementation of smart urban environments, to enable economic growth, sustainability and livability for all citizens [35]. In this way, all urban citizens and community groups are given the opportunity to participate in the identification and customised development of locally tailored solutions, and the measures by which their relevance is assessed and evaluated. Thus, ensuring that the solutions identified are culturally and socially relevant for those urban citizens who are impacted by them. Whilst, facilitating knowledge creation and sharing creative and innovative solutions aimed at simultaneously addressing economic and sustainable development, and citizens participation in identifying resolutions to factors, such as inequality(ies), to make smart cities more productive, liveable, accessible and inclusive [129].

4. Leveraging business(es) involvement, CSR and its directives

From a business perspective, CSR is built on the argument that the continual survival of the firm needs to rest on more than economic criteria alone. As a result of societal pressures, governments, organisations and institutions have placed CSR at the forefront of their efforts to address current and future environmental, human, and social challenges and problems. For businesses, adopting CSR means taking into consideration, social, environmental, human, moral and ethical criteria in their decision making [152]. However, as [2] notes, one of the challenges for businesses regarding CSR and what is required, is an ongoing lack of a universal definition. Meaning that, scholars, practitioners, and organisations, have somewhat differing views about CSR, what it encompasses, and how to best conceptualise and strategically implement the concept. For example, these two definitions, CSR is: (i) “The continuing commitment by business to behave ethically and contribute to economic development, while improving the quality of life of the workforce and their families as well as the local community and society at large” [153]; and (ii) “Specific policies and practices involving codes of conduct, environmental management systems, stakeholder dialogues, community investment and philanthropy, as well as auditing and certification related to social and environmental aspects” [154]. The former places an emphasis on ethics, societal responsibility(ies) and business investments in economic development, and the later on systems, institutions and stakeholder dialogue [155]. As such, organisations often find it difficult to identity which approach to adopt, and the actions needed to align their CSR strategies with their organisational needs and societal expectations ([2], p. 11).

Nevertheless, despite such a fundamental challenge resulting from definition confusion, research suggests that by 2013, 93% of global corporations had invested in CSR initiatives, and were voluntarily reporting on their performance [156]. Meaning that, CSR remains high on the business agenda, with most businesses embracing the triple-bottom-line approach, that encourages them to evaluate their impact on people, planet and profit [157, 158]. However, to date, the CSR concept has not remained static. The evolving and dynamic nature of global and governmental changes, coupled with increasing societal expectations, have led an advancement in the way CSR theories, models, and frameworks are both understood and embraced. Leading to several reconceptualisation of CSR, from a single organisational view, to multi-stakeholder engagement perspective(s) [2]. Scholars suggest that, this has been achieved through four stages; from corporate philanthropy and voluntary actions, to social responsibility and the adoption of stakeholder approaches and institutionalisation of extended corporate action [155, 159], and the implementation of integrated approaches (e.g., the creating shared value (CSV) frameworks [160]. It could be argued that, understanding this evolution and how in practice it has played out, has an impact for and on business perception and adoption of CSR initiatives. Thus, a cursory review of the history of CSR, its impacts on business(es) and society, and its evolution, will be used to aid our understanding in the role of businesses in addressing urban problems and issues in general but also applicable to those of smart cities, and that of reducing the impact of urban inequality(ies) as per the discussion of topic across this chapter.

4.1 The history of CSR: a critique

During the post war era, and especially post 1960, CSR grew in focus, significance and prominence on the agendas of governments and corporations around the globe [152, 161]. This significant shift was mainly due to renewed governmental recognition, that they alone could not address or solve societal challenges, and that large firms could and must do more. Consequentially, pressure was brought to bear on organisations to increase their investment in “social goods” [162, 163]. This led to extensive debate amongst scholars, from those who argued that CSR does not have a role or place in business, and that it would mean that they would give up their freedom, efficiency and meritocracy [164], to the enlightened perspective that doing so serves organisational best interests, and that it is the right, moral and ethical thing to do [163, 165]. The later emphasised that, even if it does not result in economic gain(s) [163], organisational pursuit of CSR would result in longer-term benefit generation and improvements in society [163, 166, 167]. Coupled with an increase in societal challenges, governments and organisations began to face pressure from labour and social movements to improve labour standards, employee income, address environmental and human rights issues, deal with corruption, and become more ethical [168, 169]. Such increasing pressures further led to a shift that suggested that organisations cannot operate in isolation. Rather, they were embedded in an interdependent and interrelated system wherein the attitudes, behaviours and responses of organisational stakeholders had an impact on organisational performance, and that the organisations decision and actions impacted society [163, 170].

Adopting this approach, meant that organisations needed to focus beyond a singular viewpoint of maximising shareholder value, to addressing the needs and expectations of diverse stakeholder groups including employees, community(ies) and citizen(s) (i.e., a stakeholder approach) [168]. This led author [168] in his seminal work, to suggest that organisations measure and evaluate their corporate social performance across three domains, legal, ethical and discretionary, and to argue that by adopting this perspective, organisations can identify and measure the degree to which they shrink or grow their responsive approaches to social issues, depending on the number of societal issues they include in their CSR strategy(ies). However, some scholars have noted that often in practice, managers in organisations utilise this model somewhat incorrectly. In that they assume they are managing rational closed systems, and consequentially adopt a closed viewpoint on CSR. Meaning that, managers failed to recognise: (i) That the dimensions in [168] model interact; and (ii) The sociological complexity of their role(s), and that their decisions and actions simultaneously impact on, and are impacted by, society(ies) [2, 163, 171]. This has led scholars to further suggest that, businesses adopt a multi-stakeholder approach to CSR. Suggesting that, organisations address societal issues, including the challenges associated by urban inequality, by considering descriptive, instrumental and normative views of CSR [172].

For commentators [172], adopting a multi-stakeholder approach to CSR that considers descriptive, instrumental and normative views, requires sound management within businesses to identify and evaluate the linkages between groups in society, and an acceptance that these groups have a legitimate stake in the way business operates [2, 159, 168]. However, some scholars have questioned the way that most organisations conceive CSR. Authors [160] seminal article suggests that organisations who adopt CSR practices, are somewhat overly focused on initiatives that enable the optimisation of short-term financial and repetitional gain. Meaning that, they often confine their activities to narrow views of value creation, that in the end, leads to them prospering to the expense of societal group(s), particularly the most disadvantaged. Consequentially, they are often caught in a cycle of increased government policy making, and decreasing societal trust targeted at altering their behaviour [2, 160].

To address these challenges, ([160], p. 64) suggest that, businesses reframe CSR as creating shared value (CSV), and suggest that “learning to create shared value is our best chance to legitimise businesses again”. Doing so, they argue, will enable businesses to more effectively address and respond to societal problems and simultaneously grow profitability. However, this approach has also been criticised. For example, scholars [172] suggest that; (i) CSV somewhat ignores earlier work on CSR which argued that engaging in CSR, particularly social programs through social responsibility initiatives, increases profits [168]; (ii) This approach somewhat fails to adequately deal with or address trade-offs that occur between economic and social value creation, and negative impacts on some stakeholder groups; and (iii) That this approach conceptualises CSR as a simple addition to businesses operational strategies, and as such part of their usual activity(ies). The latter being a position that is at variance with CSR literature and research [163, 168]. This means, that a situation is created where there is a continuing methodological, conceptual, analytical, and theoretical pluralism within the CSR literature. Rather, a trend that should be encouraged is, to ensure that organisations develop a more comprehensive understanding of the dynamic and inter-related nature of CSR, encouraging them to move away from a business-centric approach, and towards one that is more societally centric [173], while remaining more focused on addressing societal problems, issues and challenges, particularly those related to social, culture and income inequality(ies). Thus, enabling organisations to redirect their effort towards the enhancement of community wellbeing in urban environments in general, while also addressing issues of inequalities within city(ies) and their developing smartness. This begs the question: - are organisations adopting a societal-centric approach to CSR?

4.2 CSR and inequality(ies)

When reviewing organisations and their potential adoption of societal-centric approaches to CSR, it seems that some organisations are doing a lot and others are not. Part of the problem lies in the somewhat uncoordinated implementation of CSR initiatives, including a lack of logical connections between the numerous programs within organisations. Equally, with those that are in the main initiated and run by managers, whose CEOs often suggest the ideal of creating shared value, yet remain inactive to the overall aims and strategic implications. For most businesses or organisations however, this is not the norm. Rather, most organisations practice multi-faceted forms of CSR, ranging from corporate philanthropy to environmental sustainability, through to proactive approaches to CSV. Further, most organisations approaches to CSR are aimed at addressing the organisations social and environmental mission, improving standing and reputation, and increasing employee motivation and cost reduction [174].

An additional issue is that the CSR literature mainly focuses on outputs, and provides limited evidence on outcomes for different stakeholder groups, beyond shareholders [175]. This anomaly has led scholars to repeatedly accuse large organisations of failing to live up to their CSR commitments. They argue, that CSR literature “suffers from a lack of understanding of the differences between ‘CSR talk’ (i.e., impression management and symbolic practices), and ‘CSR walk’ (i.e., substantive implementation of CSR policies, structures, and procedures)” ([173], pp. 8–9). In large organisations, such arguments as these have led to an implementation gap. Wherein, the organisational costs associated with CSR, drive large organisations towards a symbolic communication of CSR rather than a translation of practical results and outcomes [176]. It could be argued that, these symbolic and business-centric approaches limit a firm’s ability to identify and address pressing societal issues, particularly inequality in urban environments. Consequentially, it is not surprising to find that out of 142 senior executives surveyed, 60% were dissatisfied with their organisational approaches to CSR [174], particularly given that these executives remain observant of the rising inequality within urban community(ies).

Further studies on CSR activity(ies) by firms, found that many businesses and organisations focus on those actions that they believe will result in increased organisational performance. For example, of all organisations listed in the S&P500 index where data was available, authors [177] found that most firms focused on areas related to employment strengths, diversity and environmental concerns, with limited value being placed on CSR actions that sought to address community issues. Further and more concerning, were findings that suggest the market does not value organisational philanthropy activities and seems even less concerned when firms’ behaviour conflicts with community needs. However, what these organisations seem to miss is that, their long-term profitability is predicated on more than efficient and effective production mechanisms, but also on good worker-employer relationships, and the ability of citizens to purchase their products and services. Such insights have led some scholars to suggest that, CSR can only be a solution to inequality if organisations move away from a narrow focus on profitability when making decisions on CSR, to re-aligning social relations of production [178], and reduce antagonism between divided social classes [179].

When considering CSR initiatives however, organisations appear reluctant to address some of the major barriers to reducing inequalities, for example income inequality as result of low-wage growth. As a result of reduced employee bargaining power and structural issues, wage growth of recent years relative to inflation, has been sluggish at best or declined for most developed countries [180]. Studies of life-cycle wage growth across 18 countries, shows that manual workers have flatter wage profiles than knowledge and educated workers [180]. Thus, suggesting not unsurprisingly, that firms value the human capital of educated workers more highly [181]. Yet these less educated and low-income workers are often most impacted by urban inequality(ies) [38, 39], and face the double bind of lower wages and a rising cost of living [33, 40, 57, 86]. This has led to growing unrest and increased antagonism between workers and employers [107]. In response to the global financial crisis, a case in point is the Occupy Wall Street protest, wherein citizens demonstrated dissatisfaction with organisational responses, and its impacts on firms profits, whereby ‘Transfer Day’ a spin off event encouraged consumers to switch their financial services away from traditional banks to credit unions and cooperatives [182, 183]. Events that impacted firms profits and resulted on over 1/2 million new credit union customers [184].

Research suggests, such situations grow when sentiments against corporate behaviours rise [185]. This lack of willingness by organisations to address the issue of income inequality, puts a question mark over their approaches to CSR, and their ability to demonstrate that they are acting in moral, ethical and socially responsible ways. A situation that the authors finds somewhat puzzling, given that citizenship activism aside, failing to act here has the potential to impact firms in the longer term. By delegitimising market incumbents, disrupting organisational forms as a larger share of the population are driven to entrepreneurship, create political risk, erode trust, and lead to increased government intervention [182].

4.3 Sustainable development goals (SDGs)

In parallel with the evolution in CSR, the United Nations (UN) developed and promoted 17 SDGs as a call to action for governments and businesses to work together to address the most significant problems and challenges facing society(ies). The SDGs include those aspects that are challenges within urban environments, and smart city(ies), such as addressing poverty (SDG1), reducing inequality(ies) (SDG 10), ensuring inclusive and equitable quality education for all (SDG4), and sustainable cities and communities (SDG11) [186]. However, despite growing academic interest in and analysis of country level data on those SDG’s relevant to inequality(ies) in general, and income inequality specifically, to date there has been limited focus on firm level analysis [187]. Rather, scholars investigating firm level support of SDG’s have focused on identifying how organisations can take action(s) to drive the SDG agenda forward [188, 189, 190, 191, 192], and examined the factors that influence SDG engagement [193, 194, 195, 196]. Other commentators [197, 198], have also investigated organisational motivations, barriers and opportunity(ies) for firms as they pursue the SDG goals, and the relationship between SDG goals and targets [199, 200, 201].

What these studies suggest, is that overall organisational engagement and actions towards SDG goal achievement is limited, intentional, and focused on those goals that most align with achieving broader organisational objectives [202]. Findings that align with GRI research on 206 large corporations’ performance against the SDG’s suggests that, 83% are committed to supporting SDG’s and are overly focusing on the SGD’s that had the greatest relevance to business profitability (i.e., economic growth and decent working conditions (SDG 8), responsible consumption and production (SDG12) and climate action (SDG13). What is concerning in the report is, the somewhat limited actions taken to address SDG1, 4, 10 and 11, and that the least supported are goals of no poverty (SDG1) and zero hunger (SDG2) [203]. Factors that as we have seen, impact inequality reduction and are essential to the creation of vibrant and healthy urban environments. Thus, it could be argued that a similar issue occurs with regards to firms responses to SDG’s as for CSR. In that, they are only willing to commit to supporting SDG’s that directly align with their business objectives. This limited willingness by corporations to take action towards reducing inequality and in particular income inequality, has led to what commentators ([187], p. 1) consider “end-of-pipe” solutions, wherein “governments redistribute income and wealth after the unequal distribution has been created by firm-level decision’s”. Meaning that, it is left to governments via fiscal policy, such as taxation and subsidies, to improve income and education inequality(ies) for the most disadvantaged, due to a lack of organisations responsiveness [187].

What does all this mean for city(ies) and smart city(ies)? As already identified through our discussions, the smart city agenda does have the potential to create a more sustainable urban environment and contribute much to the economic and social wellbeing of urban citizens [14, 132], irrespective of the potential negative externalities highlighted earlier. What these insights show, is that more could be done by business from a CSR and SDG perspective, to address inequality. Perhaps, what is at issue here is not lack of awareness by organisational managers of the issues associated with inequality, but rather a sense of confusion as to how best to address them within their resource constraints, whilst still meeting the broader expectations of the market. Resolving such confusion may require organisations to re-orientate their efforts away from top-down approaches, to ones that allow for a closer examination and understanding of the issues and problems by citizens and communities [2, 14]. Author [2] argues, this means that within the context of smart city(ies), businesses should adopt approaches to CSR and SDG development in partnership with the most impacted groups. This would require continuous sense-making by businesses of stakeholder needs, including the disadvantaged, citizens attitudes, behaviours, perspectives, opinions and feelings, coupled with the implementation of targeted actions aimed at resolving them [2]. Indeed, for some time, scholars have been arguing that failure by businesses to do so, particularly in smart city contexts, leads to a breakdown in trust, with questions being raised by the body politic of the relevance of business to their community [159, 168, 172].

4.4 Addressing community and business expectations

What does this mean in practice? Firstly, municipal governments and the large firms who are driving the smart city agenda need to move away from one-sided approaches where efficiency and profit take primacy. A notion that is at variance with actively contributing to CSR [2], and addressing the SDG goals. After all, as we have shown, communities expect more from governments and business(es) than efficient and effective technology provision and economic growth. The historical overview of CSR and SDG’s, demonstrates that communities expect businesses to not only address societal problems and challenges, but that they also take action to resolve the evolving environmental issues, rising inequality, poverty, and limited access to services [163, 168, 172]. Secondly, firms need to be prepared to invest more in their employees, by providing a larger share of their profits to them via wage increases in return for increased productivity and efficiency [187], to reduce income inequality. Thirdly, those large firms who design smart city(ies) and the ICT vendors who promote techno-centric solutions, need to improve access to the technology(ies), platforms and services, and work proactively to modify the perceptions and behaviours of urban citizens [150], particularly those who are socially, culturally and ethnically disadvantaged. Lastly, municipal governments and organisations need to support and encourage a realignment of the balance of power that exists in smart city decision making processes. This means, giving citizens a greater role and influence on the decision-making process(es) that impact their urban environments and communities [204]. After all, the smart technologies these large ICT vendors promote, offer the potential to empower, educate, engage and involve urban citizens in the debates and decisions that impact their lives, the wellbeing of their communities, and the urban environment they live in [205]. Doing so could involve, giving them the opportunity to evaluate solutions and participate in their customisation and development. Thus, enhancing awareness, knowledge creation and sharing, and the capacity of municipal governments to implement locally tailored solutions to the problems that most impact those citizens concerned. In this way, those factors that contribute to economic growth and sustainable development, and to making smart cities more productive, liveable and accessible, can best be identified and addressed [129].

Thus, if municipal governments commit to smart city(ies) development and to addressing urban problems, including inequality(ies), they need to move away from top-down decision-making and techno-structural viewpoints, while shifting away from addressing problems that they see as relevant and imposing techno-centric solutions to benefit the profitability of their bottom line [2, 14]. Otherwise, urban citizens, particularly those dealing with inequality, will continue to believe businesses and private interests take precedence over their needs [33, 206]. Such a shift requires early involvement by all citizens in smart city development, democratised decision-making, empowering people groups to determine the shape and form of their environments [2], and how ICT should be deployed to meet their needs [14]. A decision-making process that adopts a multi-stakeholder perspective to CSV [160], addressing the descriptive, instrumental and normative aspects of CSR [163] to deepen understanding of SDGs related to inequality. Doing so requires CSV solutions to urban inequality problems [160], balancing CSR with corporate performance [163] (see Figure 1), and demonstrating a willingness to empower and include citizens in problem identification and solutions design [204, 205].

Figure 1.

Smart City design: A simultaneous multi-stakeholder top down/bottom-up feedforward/feedback loop approach.

As illustrated (see Figure 1), organisational involvement in smart city(ies) occurs asynchronously via simultaneously top-down-bottom-up process(es) across four porous layers of activity, with each layer generating feed-forward and feed-back loops, whereby the problems and solutions identified from each layer feeds into the next and vice-versa. The outer layer captures the macro urban environmental factors relating to urban inequality, with businesses working with municipal governments to gather and evaluate evidence on urban inequality and to create collations that are committed to investing resources in addressing them. The next layer, the middle layer, includes stakeholders who have a responsibility for policy making and the planning, design and implementation of changes needed to address the urban inequality(ies) identified in the outer layer, ICT vendors and infrastructure businesses and representatives from those impacted by urban inequality. Here urban inequality problems are re-evaluated by citizens most impacted, and the smart technology(ies) are considered against the broader external environment and findings from the two outer layers. The inner layer illustrates the cyclical, dynamic, evolving and iterative interactions between multi-stakeholder groups, to identify micro (i.e., local) inequality problems and solutions from their perspective(s).

In Stage (1): Business-to-government collaboration and collation formation- businesses and government(s) develop deep understanding of urban inequality problems, evaluate policy, procedural and governance mechanisms and build coalition(s) to create a sense of urgency to address urban inequality(ies). Stage (2): Multi-stakeholder collaboration – emphasises asynchronous collaboration between the stage (1) coalitions and multiple stakeholders. With coalitions proactively working with stakeholders to identify and mutually agree on urban inequality linkages, connections, and commonality(ies), and identify local inequality problems and solutions from their point of view. In Stage (3): Appraising and balancing- the outcomes from stages (1) and (2) are appraised against governmental policies and proposed ICT solutions. The degree to which the solution(s) reduce the urban inequalities identified in stage (2) are debated, including their positive and negative externalities, in light of the findings from stage (1). If needed, the process begins again until appropriate pathways for minimising negative externalities are identified, and action is taken to do so. In the final stage, Stage (4): Encapsulating outcomes- businesses compare the outcomes from stages (1) and (3) against their CSR and SDG strategies with performance, impact measures with specific targets to lower urban inequality being set, and action taken to extend their CSR and SDG strategies based on the gaps identified in stage (3) [172].

This integrative approach to urban inequality, shifts business perceptions away from views that ICT solutions alone can address these challenges. Instead, social, and human elements are balanced with the needs of governments, businesses, and community(ies), with business goals of profit maximisation no longer take priority. Consequentially, the social, economic, cultural and environmental needs and expectations of all citizens are taken into consideration [14, 207]. While those driving smart cities are no longer seen as autocratic and self-serving promoters of techno-centered structurally focused solutions [14], but become inclusive supporters of democratic and empowering decision-making.

5. Conclusion

This chapter shows that an increasing concern about growing urban inequality within smart city(ies) exist [40, 41, 42, 57, 60, 83, 208], and demonstrates that whilst smart city(ies) hold much promise, the primary emphasis on private business interests, specifically global ICT firms [14, 132], raises questions about their ability to create benefits for all [2, 14, 19]. Further, current techno-structural perspectives on smart cities and beliefs that technology alone can improve the lives of urban citizens may inadvertently increase urban inequality(ies) [117, 121, 122]. Consequentially, current approaches to smart city(ies) are flawed, due to profit-driven business outcomes at the detriment of those facing inequality.

Building on the CSR, CSV, and SDG literature, the chapter identified conflicting perspectives, debates, and confusion between businesses, and noted that organisational approaches to CSR overly emphasise improved standing and reputation, increased employee motivation and cost reduction [174], and a focus on SDGs that align with their organisations objectives [202]. Meaning that, for many, addressing urban inequality is low on their agenda. The chapter argued for approach(es) that increased recognition and inclusion of diverse stakeholder groups, and considers the viewpoints of those impacted by urban inequality, to ensure equal access to smart city benefits for all [150], to enhance inclusion, citizen empowerment, increased trust in government and business, and improved policy making across the smart city development process [14]. Through such inclusive measures, more vibrant, healthy and liveable communities can be created, reducing inequality and improving community wellbeing.

The chapter concluded with a conceptual model combining CSR, CSV and SDGs, that places urban citizens and communities at the centre of smart city decision making. This model, enables the sharing of diverse stakeholders’ voices, concerns and perspectives, whilst equally recognising and encouraging debate(s) on the needs and expectations of citizens facing inequality challenges. Thus, empowering, educating, and involving all in identifying the problems relevant to urban inequalities and the selection of solutions to reduce them. An approach requiring business commitment to resolving inequality problems, implementing solutions that may not generate short-term financial gains, and to dissolving and rebalancing power in smart city decision-making [204].