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The Language of Smart Cities

Using Discourse Analysis to Study India’s Smart Cities Mission
Uttara Purandare


This paper uses discourse analysis methods to get a better understanding of India’s Smart Cities Mission which was launched in 2015. It focuses on nine policy documents and assessment frameworks published by the nodal ministry at federal level to guide 100 smart cities. The paper situates the Mission within the global smart city rhetoric and within the rhetorical shifts toward a softer version, smart city 2.0. The paper examines whether the Indian Mission follows a similar trajectory or whether it has persisted with the techno-utopian, economic driven, and citizen-blind version of the smart city paradigm. Studying the discourse and imagery of these documents, it brings to light the fact that, while the language has changed and become more inclusive, the interventions recommended by the Ministry have become more data dependent and technologically driven. The paper presents the reasons for which discourse analysis is a useful method for studying smart cities, and offers a basis on which more detailed city-level analyses can be undertaken in the Indian smart city context.

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1As the smart city concept began to gain popularity in the late 2000s (de Jong et al. 2015), some of the criticisms levied against it were its lack of definition, its conceptual ambiguity, and its use as a marketing strategy rather than being an inherently meaningful label (Hollands 2008). Various authors have argued that the term smart is “value-laden” (Hollands 2008), “evocative” (Vanolo 2014), “utopian” (Grossi and Pianezzi 2017), and a means of “corporate storytelling” (Söderström, Paasche, and Klauser 2014). More importantly, they have argued that these characteristics are by design so that the smart city concept can be applied to a variety of interventions in diverse contexts and geographies. Smart city proponents and policymakers, whether governments, corporations, or think tanks, have used language, illustrations, and videos to conjure the varied imagery of what makes a city smart. It is clear, therefore, that one does not even have to go beyond this policy paradigm’s label to see that discourse is a crucial part that needs unraveling.

2India’s smart city story begins with the development of greenfield cities in the western state of Gujarat. Ayona Datta in her 2015 paper, New urban utopias of postcolonial India, discusses the development of Dholera, a rural area within the Delhi-Mumbai Industrial Corridor, as India’s first proposed smart city. She argues that, unlike planned cities of the post-Independence era (Chandigarh, Bhubaneshwar), smart cities are not being designed and built by architects and urban planners but by corporate interests with a neoliberal, growth-driven logic. Datta also writes that Dholera (2015) was “hailed as the model for 100 new smart cities to be built in India in the next few decades” (p. 4). While the Bharatiya Janata Party (BJP)—which was in power in the state of Gujarat when Dholera was conceptualized—did mention the creation of 100 new cities in its 2014 election manifesto (BJP 2014), these plans were modified once it formed the federal government. When the Smart Cities Mission (SCM) was launched in 2015, it announced that 100 existing Indian cities would be transformed into smart cities instead. However, other characteristics that have been lionized in the Dholera project—the use of digital technologies, privatized technocracy, and limited definitions of growth, progress, and modernity—have been largely incorporated into the SCM. Furthermore, the SCM is but one aspect in a large-scale push for digitalization and state entrepreneurialism in India. Around the same time, a number of other government initiatives were introduced, such as the Digital India Mission and Startup India, in addition to schemes focusing on urban development, such as housing and the provision of basic services. The SCM brings together a number of these objectives. Through these various initiatives, technology has been presented as a solution to infrastructure deficits, for good governance, and for economic development. Other than techno-solutionism, which is often associated with concepts such as the smart city, there has also been an aggrandization of the entrepreneurial spirit which even state institutions are expected and encouraged to emulate (Irani 2019). Competition, austerity, and the profit motive have been celebrated as the state is pushed to remake itself in the image of the private sector. Even within this broader context, however, given its reach, scale, and financial outlay, the SCM is a complex policy that has changed over the past seven years and requires close study. Not only is it an important urban policy in itself, it is also the precursor to the recently launched National Urban Digital Mission whose sole focus is urban digitalization and e-governance in cities across India.

3This paper uses discourse analysis methods to study the SCM’s policy documents. It argues that using discourse analysis helps to analyze the smart city as a process and a diverse set of interventions that have changed since 2015. This approach also helps to situate India’s approach to smart city development within the global rhetoric of the smart city concept, which has itself undergone a number of changes. It helps to identify certain aspects unique to the Indian case. More specifically, the questions this paper attempts to answer are: how does the Indian smart city discourse relate to global smart city discourses? Are the changes in the latter reflected in Indian policy? What might this reflect but also what might this obscure? To answer these questions, the paper focuses on the objectives and processes of India’s SCM: what are the policy’s priorities? How, according to the federal government, should city governments go about achieving these priorities? Who are the actors? What is the language used? What do the images tell us?

4The next section of the paper discusses what discourse analysis is, how it is applied here, and its merit in studying a policy like the Smart Cities Mission. Following this, Section III looks at certain operational aspects of the Mission and describes the policy documents analyzed in this paper. Section IV looks at what a smart city is, focusing on the way it was originally conceived. This section then analyzes certain aspects of Mission documents and the ways in which they borrow from and build on the early version of the smart city paradigm. Following this, Section V analyzes the shifting global discourse of the smart city paradigm to what is termed smart city 2.0. The next part of this section takes up again the analysis of the SCM, addressing shifts and continuities in the policy. The conclusion discusses India’s smart city discourse in the context of global discourses and presents a research agenda that would enrich the study of urbanization trajectories in the country.

Methodology: using discourse analysis to study the smart city concept

5Discourse analysis is not just the study of language, grammar, and texts. An important part of this approach is the contextualization of texts—though “text” itself is fairly expansive and includes audiovisual communications, photographs, and conversations—within broader social systems. Fairclough (2003), in his approach to critical discourse analysis, attempts to go beyond the distinction between linguistic analysis which only pays attention to texts, and social analysis which does not pay adequate attention to texts, to offer a more nuanced and complex analysis of discourse and its impacts. He builds on this approach, arguing that language is impacted by social systems, institutions, and power relations; in turn, language also has a causal impact (Fairclough 2003:8), creating a dialectic and dynamic relationship between language and society. Gasper and Apthorpe (1996) point out that “Such work [discourse analysis] situates and elucidates texts as typically reflecting social-political world views and contexts but it tries to do this through precise and detailed analyses, not declaration alone” (p. 5).

6Discourse analysis includes several tools and can be applied in a number of ways. It can be used to compare texts, to identify themes, to critique concepts or vocabularies, and to analyze arguments. Gee, in his 2011 book, How to do Discourse Analysis: A Toolkit, identifies 28 tools that can be used within this methodology. These include looking at the frequency of words or phrases, words that often appear alongside one another (known as collocation), studying the metaphors used, deconstructing arguments and rhetoric, and carrying out a more in-depth analysis of the content. These tools can be used in various combinations depending on the research questions and the types of data analyzed. Researchers are increasingly including analyses of visual elements such as photographs, graphics, film, and videos (Lorquet and Pauwels 2020), since these visual elements are often used in conjunction with—or even instead of—texts to communicate ideas and therefore form an important part of critical discourse analysis.

7How relevant, then, is discourse analysis to the study of smart cities? Authors argue that understanding policy language is an important part of understanding the policy itself. Jacobs (2006) writes that discourse analysis can be used to uncover “how language is used to pursue political and organisational objectives” (p. 40) how problems are framed and what the possible solutions to these problems are. When discourse analysis is used to study public policy, there are a number of other factors that gain significance, including the vocabulary used, what is included and what is excluded, whose voices are taken into account and whose are disregarded, underlying ideologies, the relationship that the policy might have to other texts, the prevailing circumstances, the author(s), the intended audience, and relations of power.

8As discussed previously, discourse is an important part of the smart city concept and is “integral to its social practice" (Joss et al. 2019:22). Smart city rhetoric is also an important part of its mobilization (Purandare 2021) across national and city settings, wherein language, concepts, and terms travel along with interventions and projects—and also change as they are adopted in new contexts. The smart city discourse “shapes concepts and programs, and is a key means by which ideas and practices are borrowed, transmitted, and reproduced within different geographical, cultural, and institutional settings” (Joss et al. 2019:3–4). Such an approach also helps us to understand the recontextualization (Wodak and Fairclough 2010) of policy concepts; that is, not just how and where these concepts move to but how they change along the way and in their new setting.

9This paper analyzes certain SCM policy documents published by the MOHUA (Ministry of Housing and Urban Development) by looking at words and concepts that are used in and across these texts, what assessments aim to measure and how these indicators are defined, what processes are introduced, and how these choices are justified. It also discusses the authorship and audience of these texts, comparing some aspects of these texts to offer an analysis of how the Mission has changed over time. Finally, given the importance of the image in smart city discourse where, to a certain extent, ‘the images are the argument’ (Traue, Blanc, and Cambre 2018:1), the paper analyses how imagery has been used in these texts. Through this, it attempts to analyze the logics and ideology that underline the Mission, its core features, and how it views Indian urbanization and its own role in this project.

An overview of the Smart Cities Mission and its documents

10When the Smart Cities Mission was launched in 2015, the MOHUA (then known as the Ministry of Urban Development), a federal-level Ministry that coordinated the SCM, published the Mission Guidelines which outlined the aims of the Mission and how it would be implemented. While the document did not offer a comprehensive definition of smartness (MOUD 2015:5), it did recommend smart city features and solutions, which were fairly broad and included both technology-based interventions and infrastructure projects. The Ministry determined how many smart cities would be selected from each state based on the size of the state and its level of urbanization, with each state having at least one smart city. Competition was encouraged among cities to be selected by their respective state governments and subsequently for their proposals to be scored well by the Ministry. The Guidelines also introduced the smart city’s governing body, the Special Purpose Vehicle (SPV) (MOUD 2015:12–13), and advocated the employment of consulting firms and handholding agencies (MOUD 2015:10), considered to be essential for the success of the Mission. Money provided by the Ministry would come to the SPV in the form of an annual grant, with the state government and the Urban Local Body (ULB) each being expected to match that amount. The Guidelines encouraged SPVs to also find other means of funding, including private investments, user fees, municipal bonds, and public-private partnerships (PPPs). The 100 cities were to draw up smart city plans which addressed several urban issues ranging from improved governance and citizen services to infrastructure development. These proposals were also expected to detail funding plans and to demonstrate how cities would introduce interventions that used information and communication technologies (ICTs), sensors, apps, and data (MOUD 2015). Taraporevala (2018), Khan, Taraporevala, and Zérah (2018), Purandare and Parkar (2020), and Purandare (2021) offer a more detailed discussion on the Mission and its particularities. However, much of the literature on the SCM builds on these Guidelines or offers a more empirical analysis of how interventions play out at city level. Parkar and Purandare (2023) review various documents, assessments, standards, and interventions introduced under the Mission. However, they focus on urban digitalization and do not offer a textual analysis of SCM documents.

11This paper analyzes nine SCM documents—approximately 670 pages in all—published between 2015 and 2021. These documents largely fall under the category of policy guidelines and assessment frameworks which measure the performance of cities according to various parameters. Figure 1 offers an overview of these documents. Whereas each of the smart cities has published some of its own documents, including reports and information booklets, this paper focuses on documents published by the MOHUA. Apart from providing 50% of the Mission’s funding, cities are also expected to report their progress and accounts to the Ministry. By publishing these documents for the 100 cities to incorporate in their planning, it can be argued that the Ministry maintains greater control over how smart cities are envisioned and developed in India. On the one hand, these documents stress the importance of contextualized solutions that are city-specific but, on the other hand, they provide detailed and step-by-step procedures that cities ought to follow and adhere to. Studying these documents, therefore, gives us an idea of the Mission’s objectives, how these objectives should be achieved, and how they have changed over seven years. By using this analysis, we can begin to answer these questions. This would be a more informed approach to looking more closely at what actually happens at city level. We can also begin to understand how smart city rhetoric is operationalized outside of urban policy—in other interventions, in politics, and for business interests. In other words, analyzing smart city documents will help us to better understand the actually existing smart city in India and how it converges with—or diverges from—the Ministry’s policy objectives, and with globally circulating knowledge networks.

Figure 1

Figure 1

Documents analyzed in this study. The documents indicated above the time line are policy/strategy documents, while the ones below it are assessment frameworks.

  • 1 The National Institute of Urban Affairs (NIUA) is a “national think tank on urban planning and deve (...)

12Following the publication of the Mission Guidelines in 2015, the years 2018 and 2019 saw a surge in publications by the MOHUA in association with the National Institute of Urban Affairs1 (NIUA). It is possible that, up until 2018, the Mission was more focused on completing the selection process of the 100 cities (the final round of city proposals was approved in 2018) before the Ministry shifted its focus to the Mission’s mandate and its progress. During these years, the DataSmart Cities Strategy was published, as was the National Urban Innovation Stack Strategy, and four major assessment frameworks, viz the Data Maturity Assessment Framework, the Ease of Living Index, the Municipal Performance Index, and the ClimateSMART CITIES Assessment Framework. A draft of the Integrated Command and Control Centre Maturity Assessment Framework (IMAF) was circulated for comments in 2018, but the final framework was released in 2021. That year, the Ministry also published a smart city “workbook,” titled Making a City Smart: Learnings from the Smart Cities Mission, which aims to showcase learnings from the Mission and to offer a step-by-step guide for non-Mission cities to follow in order to become smart. Finally, the Bureau of Indian Standards along with the MOHUA and NIUA published “15 Standards for Smart Cities … to act as guideline for cities in their journeys of adopting ICTs in their strategies & practice” (Smartnet n.d.). However, these Standards have not been substantially included in this analysis. The sections that follow discuss the shifting global rhetoric around the smart city concept and compare this to India’s smart city discourse.

What is a smart city? India’s relationship to global discourses

13This section looks more closely at the characteristics encompassed by the term ‘smart city’ and the extent to which India’s SCM is congruent with this global discourse.

The original smart city

14The smart city finds its origins among technology firms. According to Anthony Townsend (2013), the smart city concept was first introduced by IBM in its “smarter cities, smarter planet” challenge following the 2008 financial crisis. This culminated in the building of Rio de Janeiro’s Urban Operations Centre—an integration of various municipal departments, sensors, cameras, and other digital technologies that collect and analyze granular data. As IBM took this concept to other cities, firms like Cisco and Siemens also began to offer their services and expertise to city governments (Townsend 2013). By the early 2010s, smart city policies were being introduced by local and national governments across the world, as both greenfield and brownfield initiatives. The term was used by both governments and businesses to signal an extended use of digital technologies and to attract global capital in what Söderström et al. (2014) term “corporate storytelling.”

15While projects differ in scale and sector, there are certain characteristics that make a city or a technology-based intervention smart. Since there is no single definition of a smart city, these characteristics have been identified by various authors and have been compiled here. The characteristics include (1) the use of digital technologies (Kitchin 2014; Sadowski 2020). These technologies (2) collect large amounts of data which are then analyzed—often in real -time—to govern the city (Kitchin 2014). Algorithms, artificial intelligence (AI), and machine learning (ML) are used to make decisions, predict what might happen, and respond to what the city might need. This can be understood as an “algorithmic turn” (Gurumurthy and Bharthur 2018) in governance and is considered to be one of the strengths of the smart city given its basis in data, scientific methods, and the reduction in human error. Smart city interventions also coincide with (3) the privatization of services and the rise of a technocracy, including technology firms, data experts, and management consultants (Purandare 2021). These three features help buttress the argument that (4) the smart city is an apolitical and scientifically governed city (Kitchin 2015; Green 2019). Urban problems are often portrayed from a broad perspective that cannot be disputed, such as sustainability or equity, but these portrayals conceal power imbalances (Vogelpohl 2019). Finally, (5) one of the most significant aims of the smart city is to attract businesses, people, and capital. Smart city rhetoric therefore tends to present a global outlook in terms of being an international city and attracting international businesses (Söderström et al. 2014); a city that is good for economic growth.

16Another common theme that runs through most smart city literature is the claim to newness, of the smart city being a revolutionary shift in urban development. While the technologies being introduced to collect and analyze city data might be new, the principles that underline the smart city concept—the efficiency and accountability of technology, the desirability of private expertise and management, and the disadvantages of political and democratic processes—are not new (Shelton et al. 2015). As Sadowski (2020) writes, “the rise of the digital age is not a disruptive break from history. It is a new way of repackaging, reproducing, and revitalizing what came before. We have to look beyond the high-tech veneer that covers up the machinations of old power regimes” (p. 52). Similarly, Grossi and Pianezzi (2017) argue that the smart city is an extension of earlier forms of neoliberal urbanism that privileges small government, competition, the profit motive, and the privatization of urban services and solutions.

17Many of these smart city characteristics have been criticized. One of the most significant criticisms concerns how smart cities either exclude citizens from their narrative or include only a specific kind of ‘smart’ citizen—the elite and middle classes, and young professionals who are technologically savvy, educated, global, and aspirational (Vanolo 2014; Datta 2015). Often, the exclusion of citizens is reflected in smart city imagery, as in the image below taken from the website of one of India’s top smart cities, Pune. The image represents a park being developed for “specially-abled children” (PSCDCL n.d.). It provides very little information on what makes this park special and, perhaps more crucially, fails to address why not all parks are accessible to people with disabilities. It also does not feature any people.

Figure 2

Figure 2

Pune Smart City park design titled, “Park for Specially Abled—Placemaking” (PSCDCL n.d.)

18Many of these characteristics have persisted, been valorized, and incorporated into national policies such as the SCM, as we will see below.

Fitting in with the global rhetoric: what do SCM documents reveal?

19An analysis of the Mission documents shows numerous instances of the SCM building upon and borrowing heavily from global smart city discourses. All nine documents begin with largely the same paragraph which sets out why urban development is urgent. It describes India’s growing urban population and the predicted size of the population by 2030 or 2050. The paragraph also describes the share of India’s GDP that comes from cities and how this is expected to grow as well. Population growth and economic growth therefore seem to be the most significant driving forces behind urban policy in India.

Objectives and principles

20Rather than offer a clear definition or a set of criteria for a smart city, the SCM attempted to frame interventions around three objectives: liveability, economic growth, and sustainability. In addition, the Mission documents often mention inclusivity and citizens’ aspirations. However, there is no acknowledgement of the complexities of urban disparities and of the fact that data and technology might not be able to capture these and may even worsen the situation, given inherent biases. More importantly, data is never disaggregated, an aspect discussed in detail below.

21Both the DataSmart Strategy and the National Urban Innovation Stack (NUIS) argue that in order to achieve the given objectives, smart cities have to focus on “people, processes, and platforms”. Focusing on these implies building the capacity of ULBs, including creating new positions, and capitalizing on citizens’ and businesses’ innovation and entrepreneurship; institutionalizing the use of data and introducing necessary policies for governing this data; and deploying technologies to sense the city, collect and analyze data, share information, and offer services so that the city itself serves as a platform.

22When it comes to data privacy and security, the documents mention these aspects but do not have a uniform narrative. To begin with, even where data privacy and security are promised, this is done in the absence of an actual law to guarantee these rights and hold government and other institutions accountable (Purandare and Parkar 2020). On the one hand, certain documents discuss data minimization (MOHUA 2018c:6), privacy and security by design (MOHUA 2018a:32) and anonymization (MOHUA 2018b:27). On the other hand, however, there is a push for centralization (MOHUA 2018a:33), data integration, and interoperability (MOHUA 2018a:31), all of which can adversely affect the former. Furthermore, promoting trust in the government is given greater priority than rooting it in a rights-based framework. This is seen in the Workbook which states,

an unwritten social contract exists between the city and its citizens: the citizens pay taxes in lieu of the services they receive from the city. Ease, quality, transparency, and efficiency in processes to access these services help strengthen the social contract, thereby increasing the trust that citizens have on their cities [sic]. This builds capacity in the city through a virtuous cycle of reinforcement of trust (MOHUA 2021a:42).

23Or, in the DataSmart Strategy which states, “Managing security and privacy of data is crucial to building and maintaining trust between ecosystem participants and thus will be a critical element of the city data policy” (MOHUA 2018b:26). The right to privacy is in fact a fundamental right and should not be presented as an act of altruism or to promote trust (for a detailed discussion, see Purandare and Parkar 2020).

24In other words, irrespective of whether data is from citizens or the city, SCM documents reify data and technology as integral to urban solutions, and sometimes as being the solution itself. This has an impact on which problems are identified and how problems are framed.

Challenges, justifications, solutions

25Most of the Mission documents have a section on urban challenges. These essentially form justifications for the SCM itself and the interventions it introduces. This subsection focuses specifically on how urban challenges have been framed in the National Urban Innovation Stack (NUIS).

26The NUIS has the most extensive section on “systemic challenges in urban India” (MOHUA 2018a:19–20). It paints a grim picture of Indian cities, using words like “plagues,” “suffers,” “not robust or evolutionary,” “incapable,” “inefficient,” “bottlenecks,” “paucity,” and “blind spots.” The NUIS (2018a) describes poor governance, a lack of trust and accountability, a lack of capabilities in ULBs, limited innovation, and a lack of planning and evaluation. In the opening paragraph of this section, the document states, “in its current form, urban India is a roadblock in achieving our aspiration of becoming a 7-trillion-dollar economy that is secure from risk and hence resilient and sustainable” (p. 19).

Figure 3

Figure 3

How Indian cities are depicted in the NUIS (2018a:19), in black and white.

27The solutions offered to these myriad and complex problems all stem from increased digitization and the expanded collection of and access to data. Such a shift, the NUIS promises, will “catalyse,” “unleash,” and “transform” Indian cities at both “speed and scale.” The document states, “in order to address the need for scale and speed, it is therefore essential that the country should use the transformational force of digitalization in all aspects of the urban sector” (MOHUA 2018a:21). It goes on to say that India’s “underutilised capacity can be catalyzed … by creating a thriving ecosystem … that would best be served through a digital presence” (MOHUA 2018a:22).

28The assessment framework also reduces India’s urban challenges—and solutions—to a question of data. The justification of digitalization therefore is as follows: a lack of measurable data means a lack of clarity about India’s urban reality and therefore ineffective solutions. Technologies can help the collection and analysis of data to produce more effective, scientific and innovative solutions, creating virtuous cycles.

29There is a unidimensional understanding of the urban and of urban populations. There is no acknowledgement that it might not be possible to quantitatively measure certain parameters or the biases that these types of data might contain and embed, or even the perils of algorithmic governance. While the SCM seems to have taken into account the major criticism levied against the smart city paradigm, namely the exclusion of citizens (more detail below), it has done little to address the way it might ensure just and answerable technology-led governance. Within the SMC’s approach, measurement itself is presented as a solution (Lorquet and Pauwels 2020:7).

30SCM documents are similar to other global narratives of the smart city in that they present the paradigm as a revolutionary ahistorical concept, and data and technology as silver bullets. They do not acknowledge India’s history of e-governance and urban digitalization which began in the early 2000s with the National Urban Renewal Mission and the National e-Governance Plan (Parkar and Purandare 2023). More importantly, these documents make promises of transparency, efficiency, and accountability through digital technologies without considering why previous interventions did not achieve these or the required scale of digitalization. While the SCM’s technological mandate is much broader, not least because of the advancements in ICTs, the descriptions of urban India’s problems and the solutions offered have not changed significantly over two decades.


31Visual representation is an important part of smart cities. As discussed in the methodology section, it is also an important part of the discourse and is used in texts to expand or support arguments, to communicate ideas, or to add to the aesthetics. Smart-city policy proponents often use visuals, both still images and videos, to convey their vision of the city and the citizen. In most of the documents analyzed there is mention of the importance of visualizing data for better analysis and dissemination. In other words, how the smart city is seen and how it sees are both significant.

32The imagery in these documents can be divided into four categories. The first includes illustrations and graphics that are used for aesthetic purposes, to make the document more engaging and two-dimensional, as shown in Figures 4 and 5. In keeping with this, many of the documents also use bright colors that are eye-catching and attractive. These embellishments have increased significantly in the documents published after the 2015 Mission Guidelines.

Figure 4

Figure 4

Representation of a data marketplace (MOHUA 2018b:47)

Figure 5

Figure 5

Representation of an ICCC (MOHUA 2021b:21)

33The second type of image provides a visualization of data using graphs, tables, pie charts, etc. Interestingly, these have only been used in the ClimateSMART Framework to depict data such as greenhouse gas emissions across countries and sectors, and carbon intensity per country (MOHUA 2019c). Closely related to this is the third category which provides a visualization of certain aspects of the text itself, primarily processes, weightages for assessments, and images. Figures 6 and 7 are examples.

Figure 6

Figure 6

Smart city selection process (MOUD 2015:10)

Figure 7

Figure 7

Making a smart city process (MOUHA 2021a:15)

34Finally, the documents contain photographs most of which are in the Workbook and depict existing smart city projects. The NUIS uses photographs not only to show the unplanned and chaotic character of Indian cities, as in the black and white photograph in Figure 3 above, but it also uses a colored photograph to show what a smart city would be like (MOHUA 2018a:21). This photograph shows a busy intersection with fast cars, lights, and commercial spaces but no pedestrians, greenery, and limited public transport.

35The imagery used in the Mission documents is to show what it expects of cities—the conveying and presentation of information in diverse and attractive ways. Cities are expected to showcase data using illustrations and visualizations and are expected to engage with citizens on social media platforms and via apps and dashboards. These are visual-heavy media and many of these documents set the tone that cities are meant to emulate. Another possible outcome of such an approach is to further reify the types of data collected and analyzed by smart cities, even if this data is not particularly meaningful.

36The Integrated Command and Control Centre (ICCC), which is described as the “brain and nervous system of the city” (MOHUA 2021b:24), and central-level initiatives, such as the India Urban Data Exchange, are designed as physical spaces with large screens on which the city can not only be watched or made visible via CCTV footage but also visualized—through maps and graphs, with color codes, GIS layers, and the ability to move through time, space, and data without having to physically interact with the city. These images, like the platforms and apps that smart cities want to create, act as a way to filter the city, to make it more legible, and also more simplified. The imagery in the smart city documents represents a deconstructed city and the stick figures used to represent people are interchangeable. Images are used not only to simplify data and facilitate communication; they seem to be a way to simplify the city itself. This is in keeping with much of the early rhetoric on the smart city concept—data and technologies are fetishized through these images. Furthermore, the diversity of Indian cities and their citizens is erased by standardized, simplified images that airbrush the messiness that is inherent to cities or that frames it negatively.

Smart city 2.0: is the shifting global rhetoric reflected in India?

37Smart city literature and policies have evolved and adapted. While much of the earlier literature was utopian, this has changed to more measured expectations of what smart cities can achieve and how advanced these technologies and algorithms really are, as we will see here. This section is divided into two parts. The first considers whether, globally, the language of smart cities has been changing over the past decade and a half, since it first gained prominence as an urban policy approach. The second part returns to the Indian Mission in an attempt to understand what has changed and what persists therein.

38It appears that smart city proponents, both in government and in the private sector, have taken cognizance of the criticisms levied against the smart city concept and have come to realize that the utopian promises made by smart city rhetoric have not come to pass, including the capacity of ICTs and data to solve complex problems. This has led to a shift in smart city language and objectives, labeled smart city 2.0 (Trencher 2019).

39Smart city 2.0 focuses on more incremental changes. While a number of characteristics, like the use of digital technologies and algorithmic governance, persist, there are notable shifts. In particular, more recent smart city literature and interventions have made an effort to focus on citizen participation and to include a more rights-based narrative in smart city policies. Joss, Cook, and Dayot (2017) attempt to understand whether this shift in smart city rhetoric indicates a new citizenship regime, one that does not consider urban citizens merely as consumers; and whether this shift brings about more substantive changes or is limited to the realm of rhetoric. According to the authors, “at the core of UK’s smart city discourse is a call for a new form of governance” (Joss et al. 2017:7) which, rather like in the original smart city, can be achieved with the use of data and technology. Similarly, citizenship has been tied into accountability, entrepreneurship, productivity, and better businesses. While this is more positive than the entire exclusion of citizens, it may not help to address complex and multi-faceted issues that cities face and could lead to “citizenship washing,” similar to the greenwashing that neoliberal policies have been criticized for with regard to sustainability.

40Gregory Trencher, in a 2019 paper, looks at the rise of smart city 2.0 in Aizuwakamatsu smart city, Japan. He argues that literature, whether critical of the smart city concept or not, tends to consider the smart city a homogenous category, which “underplays the importance of local circumstances in shaping unique smart city imaginaries and on-the-ground projects” (Trencher 2019:117). Trencher elaborates on the characteristics of smart city 2.0 which focus more on citizens and the governance of cities. Rather than technology being an end in itself, it has now become a means of achieving other goals to “improve the urban living experience and wellbeing of residents” (ibid). The technology itself can be simpler and less sophisticated. Finally, Trencher explains that, as opposed to smart city 1.0 that tended to apply imported solutions or those recommended by and for the benefit of large corporations, in the smart city 2.0 paradigm, solutions are ‘endogenous’ and target citizens and local businesses.

41However, there remains the question about the extent of these changes and their effectiveness. As argued by Joss et al. (2017), even in smart city 2.0 the idea of citizenship continues to be framed in a problematic manner wherein citizens are expected to be entrepreneurial; complex issues are reduced to measurable indicators; and quantifiable data continues to be the mainstay of smart urban governance. Trencher (2019:126) points out that, while the smart city 2.0 approach is gaining ground, the original approach persists, leading to hybrid smart city policies and interventions.

Smart Cities Mission 2.0?

42To what extent can the shift from smart city 1.0 to 2.0 be seen in Mission documents? What is the depth of these shifts, and what impact might this have on the 100 smart cities in India?

Authors and audience

43Who are the authors of these documents and who is their intended audience? Who are the actors included or alluded to in these documents? Not only is an analysis of authorship an important part of critical discourse analysis, it is also necessary in order to provide a better analysis of these documents—why they have been written, what some of the underlying ideologies might be, the roles that different actors are expected to play, and how these aspects have changed.

44As far as the authors are concerned, all documents—except the Mission Guidelines—begin with a note from the MOHUA secretary, Mr. Durga Shanker Mishra, and the Smart Cities Mission Director, Mr. Kunal Kumar, both bureaucrats. Some of the documents also include a message from the minister concerned and quotes from or references to the prime minister. Some mention other individuals from the Mission and even some consultants in their capacity as authors or in the acknowledgements. Most of the documents have been published by the MOHUA and the National Institute of Urban Affairs (NIUA), and these bodies are assumed to be the authors of these publications. The documents refer to working with multiple experts and other stakeholders but it is never made clear who these individuals/organizations are, what their role is, or details about the consultation process. Interviews with stakeholders reveal that management consultants working with the Ministry and the NIUA have played an important role in drafting these strategies and assessments. Interactions with experts are also mediated by these consultants. However, the absence of any explicit mention of these blurs the line between government and consultant, with the latter speaking in the voice of the former.

45In many respects, these documents are stand-alone publications that have largely been framed as ways to guide cities rather than to instruct. It is only the assessment frameworks that provide blanket applicability across cities. Nonetheless, the documents are interlinked, refer to one another, and sometimes even build on one another. A city’s Data Maturity Assessment Framework score makes up 20% of its Integrated Command and Control Centre (ICCC) assessment (MOHUA 2021b). Similarly, links exist between the DataSmart Cities Strategy and the NUIS, such as the focus on people, process and platform, and even some of the interventions mentioned, such as the India Urban Data Exchange. The NUIS is mentioned in the DataSmart Strategy a number of times as one of the “foundational pillars” for becoming data smart (MOHUA 2018b:5). Many documents often replicate ideas, interventions, structures, and may even use similar imagery. The language is fairly consistent and suggests authorship overlap. The Workbook mentions these documents and assessment frameworks and even lists them as resources. However, they are not presented as indispensable to the smart city endeavor. Interestingly, the Mission Guidelines are not referred to in subsequent documents and while there are some similarities, most successive documents focus almost exclusively on aspects relating to data and technology.

46Let us now turn to the audience of Mission documents. It would seem at first that SPVs and, to some extent, city governments (including non-Mission cities) are the target audience for these documents. The Workbook, for example, clearly states that it has been designed for non-Mission cities and for students and practitioners of urban planning and policy (MOHUA 2021a:13). However, the picture is a little more complex and SCM documents often discuss the roles that other types of actors are expected to play if Indian cities are to become smart cities. These actors are represented by each vertex of what the Mission terms the “quadruple helix model”—governments, citizens, businesses, and academic institutions. Academic institutions are largely referred to in passing but they are expected to benefit from access to city data and to contribute to innovation in the city.

47As expected, governments play a fairly complex role. Local, state, and federal governments are expected to contribute to and benefit from the Mission. The benefits come largely in the form of data centralization and interoperability. The documents also instruct each level of government to set up various smart city committees to manage and advise on policy and projects. Documents published after the Mission Guidelines make no mention of the SPV. Instead, these documents emphasize the building of ULB capacity and the training of ULB staff. The Workbook is also less enthusiastic about the role that consulting firms can play in smart city design and governance, advising cities to “look beyond jargons and consultant speak!” (MOHUA 2021a:44); and, while “it is often tempting to contract a large consulting firm,” cities should instead consider “forming a consortium of local firms and civil society organisations that understand your city well and are invested in its shared future” (ibid). This is a good example of a shift in language without a substantive shift in practice. The Workbook does not move away from or update the SCM’s core tenets—determined in large part by these consulting firms—and continues to be prescriptive about what determines smartness and how this can be achieved.

48Businesses are expected to gain from the SCM due to improved infrastructure, increased access to data, and the creation of a ‘data marketplace’ (MOUHA 2018b). Promising greater transparency, the SCM suggests incentivizing problem-solving and improved investments. The NUIS states, “greater digitization and automation of routine interactions between industry and government… will reduce friction within the system and improve ease of doing business” (MOHUA 2018a:72). Finally, businesses are also expected to play a role in smart city governance as consultants, project managers, builders of infrastructures, and providers of technology (MOHUA 2021a:45)—the PPP model is highly regarded by the SCM. The question as to whether this will come to pass remains to be seen. Nevertheless, the private sector has already benefited from the SCM given the varied role private sector actors play, from strategy consultants to project managers, and as vendors of technology solutions, builders of infrastructures, and providers of software and data management. These are often large firms like Deloitte, PwC, IBM and Cisco. These firms rewrite themselves in these documents and interventions, often as the only entities capable of offering necessary solutions to scale and efficiently, thereby prolonging their engagement with the policy, for example the SCM, and increasing their gains.

49While citizens are often mentioned throughout the documents and their being at the center of this policy is reiterated, they form a single, homogenous, and unproblematic category. This is especially reflected in the assessment frameworks where indicators are not disaggregated by gender, caste, income, religion, geography, level of education, access, age, or ability. Instead, data is aggregated and does not offer sufficient insights into urban inequalities and how these are often reinforced by city systems. On the one hand, inclusivity is mentioned several times in each document while, on the other hand, there are no recommendations on how to ensure this—or how to measure it. Rather, there is an underlying expectation of a certain type of “smart citizen,” one who is connected, could innovate (specifically, using technology and data), or could invest along the same lines.

Smart city definitions, data, and technology

50In order to understand how the Mission itself defines a smart city, one may consider whether, following the vagueness of the definition in the 2015 Guidelines, there is a better understanding of what an Indian smart city now is.

51The Guidelines stated that there can be multiple definitions of a smart city and that it would be up to the 100 cities to determine smartness for themselves (MOUD 2015:5). Seven years on, the 2021 Workbook stated that a smart city is a city that “works for its people” (MOHUA 2021:18). Over the years, however, the Mission has identified three core focus areas, viz liveability, economic growth, and sustainability, which are now mentioned in every Mission document. While all three were mentioned in the 2015 Guidelines, they have since been fleshed out, as reflected in the assessment frameworks that have been developed—the Ease of Living Index and the ClimateSMART Assessment directly address two of these three core areas.

52Mission documents also make clear that a city cannot become smart without data. The DataSmart Cities Strategy states, “the future of governance is data-driven and Indian cities are beginning to adopt this change in their functioning… To support complex and elaborate city planning, we need a robust indicator framework, and the accuracy of this framework depends heavily on reliable data input” (MOHUA 2018b:17). A number of documents encourage cities to engender “culture of data” (MOHUA 2018c:7, emphasis mine).

53Data is limited to “objective” indicators that can be measured and compared across cities and over time. For this, complex aspects of urban development are broken down into measurable indicators. For example, the Ease of Living Index measures the availability of recreational centers, parks, cinemas, and restaurants, but it does not map these onto the city or even measure accessibility by the cost of access to these facilities. Similarly, under “economic ability”, there is no disaggregation of data to see how many women work outside the home and what, for them, might hamper workforce participation. Furthermore, the use of existing data is encouraged rather than the collection of new, more relevant, disaggregated, city-level data.

54Apart from existing data sets, data can be collected when technologies capable of sensing the city are introduced, as detailed in the NUIS (2018) and Workbook (2021). However, the use of digital technologies has been emphasized less consistently than the importance of data across the documents. I have already written about the publication of the DataSmart Cities Strategy in 2018 signaling a shift in the Mission’s approach, from one that was more focused on physical infrastructures to one that prioritized the use of digital technologies and the collection and analysis of data (Purandare 2019). In documents such as the DataSmart Strategy, the DMAF, the ICCC Assessment Framework, and the NUIS, technology is often treated as an end in itself and as lying at the very heart of what makes a city smart. This is reflected in passages like,

We are witnessing the manifestation of this technology revolution in various cities under the aegis of Smart Cities Mission … [Cities] have taken a quantum leap to embrace, adopt & adapt technology to reimagine the way cities deliver citizen services, manage their infrastructure and core civic operations with the objective to deliver quality of life to its citizens and local businesses (MOHUA 2021b:14).

55On the other hand, the 2021 Workbook makes it clear that digital technologies are a means to an end and should be introduced only when relevant and useful. Although it mentions that Artificial Intelligence and Machine Learning (AI & ML) are expected to play a role in the planning and managing of cities (MOHUA 2021a:57), it states that “technology has to be regarded as an enabler by cities, subservient to the goals set by them” (38, emphasis mine).

56Despite this ambiguity and occasional contradiction in ideas, the smart city is presented as an inevitability, as the only viable solution to India’s urban challenges. For example, the Workbook states, “being smart is no more a choice, it is a need” (MOHUA 2021:28, emphasis in original). What has also remained consistent is the idea that the 100 smart cities are to be emulated by other urban areas, especially in India, and across the world. The term “lighthouse cities” is used throughout the documents to suggest replicability in approach and outcome, and the smart city is presented as a paradigm shift in India’s urban story (MOHUA 2019:13).

57Finally, while, on the one hand, Mission literature stresses the need for contextualization and local solutions, much of its language is prescriptive. Words like “will,” “should,” “must,” etc. reflect a more top-down outlook to urban development. This is reinforced by the step-by-step guide that the Mission has created for other cities in the form of the Workbook, as though there were a single formula to becoming smart and a linear series of steps to follow.


58Using discourse analysis to study SCM documents offers certain insights. The language used by the Mission is in keeping with global smart city discourses, and closely matches the original smart city rather than smart city 2.0. Embodied in the Mission are the various characteristics outlined above, including the centrality of digital technologies and data, a technocratic approach to governance, and a focus on economic development. This suggests that India is using the SCM, and the urban digitalization project more broadly, to present itself as technologically advanced and attractive to national and global capitals. Most documents overlook many of the wicked problems entrenched in Indian cities. Digital technologies and data are not only presented as silver bullets but as profitable, embodied in the idea of the city being a platform and a ‘data marketplace’ (MOUHA 2018b:43). The private sector does not only play a crucial policy role, but is also one of the most significant actors expected to benefit from smart cities. As previously mentioned, citizens are considered a single, homogenous category and are expected to be entrepreneurial and tech-savvy.

59Having said that, over the years, the language of SCM documents has become more inclusive and sensitive to the importance of decentralization and environmental sustainability. This is a shift from the Mission Guidelines that focused more on the development of physical infrastructures and on the provision of basic services, albeit through the SPV. Taraporevala’s analysis of expenditure by the first 60 selected smart cities finds that only 3.7% of city funding was allocated to IT (2018:17). The rest was spent on transport, energy, housing, etc. Later documents, however, significantly shift their focus and use techno-utopian language. The Integrated Command and Control Centre Maturity Assessment Framework, for example, which presents the ICCC as the most fundamental aspect of a smart city, emulates Rio’s Operations Centre, arguably the most quintessential symbol of the earliest smart cities. The Workbook, on the other hand, encourages cities to use technologies as tools rather than solutions and to strengthen their ULB capabilities rather than to rely on consultants and technocrats. Inclusion, citizenship participation, and sustainability have gained greater prominence in later documents compared to the 2015 Guidelines, but are often treated superficially. What we see in the Indian case then is that, while there has been a shift, albeit perfunctory, in discourse towards smart city 2.0, the interventions recommended by the MOHUA have gone in the opposite direction and show a strong similarity with the original smart city and with neoliberal imaginations of urban development.

60Data collection and analysis—of both city-level and citizen data—lie at the heart of SCM documents. Even if results at city level over the past seven years have proved mixed, the SCM has enshrined this approach through its literature. This means that we can expect digitalization to continue and to develop further. Given the emphasis in most documents on the centralization and interoperability of this data, digital technologies will play an increasingly significant role. What is worrisome is the lack of comprehensive data frameworks and policies—aspects that these documents refer to repeatedly but never expand on.

61Methodologically speaking, this paper contributes to demonstrating the validity of discourse analysis for a better understanding and analysis of the smart city concept. This analysis has tried to piece together the SCM narrative by looking at different elements of each document, including authorship, audience and imagery, and the way documents relate to one another. While this paper has focused on analyzing federal-level documents published within India’s Smart Cities Mission and the way they are linked to a more global smart city rhetoric, discourse analysis methods can be used in a variety of ways and for a vast array of cases, either at a micro or macro level.

62Smart cities cannot be studied as a homogenous whole but have to be analyzed within their contexts while also relating local policies and practices with global trends. Future research questions could build on this analysis and look at smart city documents and interventions at city level. We have seen how global discourses can influence national policy; it would therefore be interesting to see what cities might choose to focus on and how they, in turn, might affect the reframing of policies such as the SCM. Furthermore, understanding the SCM discourse could help study its operationalization from a political perspective and what the entrenching of these principles means for the rights of citizens, whom the city serves, and more broadly for the role of the state.


64I would like to thank the organizers and participants of the CEIAS-CESSMA-CSH online workshop, “The Digitalization of Urban Governance in India: Techniques, Ideas, Practices” held on October 11–12, 2021, for their feedback on an early draft of this paper. My thanks especially go to Stéphanie Tawa Lama Rewal and Khaliq Parkar for their critical engagement and insights which helped further develop this paper. I’m grateful to the three anonymous reviewers whose detailed comments were crucial in strengthening this paper and crystalizing its arguments.

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1 The National Institute of Urban Affairs (NIUA) is a “national think tank on urban planning and development” which was set up in New Delhi in 1976 (NIUA n.d.).

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List of illustrations

Title Figure 1
Caption Documents analyzed in this study. The documents indicated above the time line are policy/strategy documents, while the ones below it are assessment frameworks.
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Title Figure 2
Caption Pune Smart City park design titled, “Park for Specially Abled—Placemaking” (PSCDCL n.d.)
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Title Figure 3
Caption How Indian cities are depicted in the NUIS (2018a:19), in black and white.
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Title Figure 4
Caption Representation of a data marketplace (MOHUA 2018b:47)
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Title Figure 5
Caption Representation of an ICCC (MOHUA 2021b:21)
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Title Figure 6
Caption Smart city selection process (MOUD 2015:10)
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Title Figure 7
Caption Making a smart city process (MOUHA 2021a:15)
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Electronic reference

Uttara Purandare, The Language of Smart CitiesSouth Asia Multidisciplinary Academic Journal [Online], 30 | 2023, Online since 30 July 2023, connection on 05 December 2023. URL:; DOI:

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About the author

Uttara Purandare

IIT Bombay-Monash Research Academy

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The text only may be used under licence CC BY-NC-ND 4.0. All other elements (illustrations, imported files) are “All rights reserved”, unless otherwise stated.

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