A Digital Transformation Framework for Smart Municipalities

Abstract

Smart cities, as defined by Sustainable Development Goal 11, strive to make cities more inclusive, safe, resilient, and sustainable. Digital technologies addresses urbanisation concerns, such as rising energy use, pollution, waste disposal, and social inequities. The Internet of Things (IoT) and data-driven technologies are essential drivers, with a focus on infrastructure and decision-making in smart cities and municipalities. Digital Transformation (DT) is a prerequisite for becoming a Smart Municipality. The research objective of this paper is to investigate the role of digital technologies in improving urban processes, focusing on Smart City dimensions for municipalities, namely smart governance, environment, living, and technology. Municipalities in South Africa, particularly in the Eastern Cape, used digital adoption to boost productivity and skill development. However, the need for standardised DT principles presents problems for transitioning municipalities into data-driven organisations. The paper also examines the global energy issue and how smart cities can contribute to energy solutions. Finally, the paper addresses the following research question: ‘How can lessons learned from the Eastern Cape Municipalities digital adoption be scaled to other developing nations facing similar challenges in energy management and urban planning?’ Using a survey method, it provides guidelines in the DT framework, offering empirical insights into Smart Municipality digitalisation.

1. Introduction

Goal 11 of the Sustainable Development Goals (SDG), which focuses on making cities and human settlements inclusive, safe, resilient, and sustainable, highlights cities as key drivers of sustainable development. Municipalities are, however, also playing an essential similar role at the local level, due to their closeness to citizens and ability to enhance collaboration, partnerships, and governance in support of sustainable development [1]. Due to urbanisation, municipal management in developing countries faces sustainability challenges. These include increased energy consumption, pollution, the disposal of toxic wastes, resource depletion, ineffective management of urban infrastructures, ineffective planning processes, overloaded transportation networks, endemic congestion, social inequality, and socio-economic disparity [2].

Smart cities are focused on producing quick solutions for urban problems, such as those identified above. Technology is key in enabling new development opportunities for smart cities, especially by enhancing existing urban processes, such as transport, health, education, government, and energy and waste management [3]. Smart cities use digital technology to improve existing urban processes by achieving more efficient coordination of smart services and providing added value to citizens through digitalisation [4].

The implementation of digitalisation has involved the use of the IoT and data-driven technologies, which are important drivers for the growth and development of smart cities and smart municipalities in maintaining their sustainability [5]. The IoT is a significant digitalised technology for infrastructure development in smart cities [6]. According to Čolaković and Hadžialić [7], the IoT is considered one of the most advanced technologies for creating a global network of machines and devices that enable effective communication and data transmission through suitable Internet connections. Therefore, it has been regarded as one of the important indicators in the development of smart cities and digital transformation (DT), enabling businesses and governments to reinvent their products, services, mode of operations, and business strategies [8].

Big data technology plays an important role in how smart cities run, especially in terms of their attempts to promote sustainability [9,10]. Large amounts of data are acquired, analysed, and used to manage, control, and regulate urban life [11]. A new phenomenon, called the data-driven city, is emerging as a result of the rise in the data faction of cities, which is mostly made possible by IoT technology. The most crucial mode of production for smart cities and sustainable smart cities has emerged as data-driven urbanism [12,13].

The IoT and Big data have been identified as enablers of DT [14]. DT primarily refers to the transformations necessary to drive digitalisation, following a digital policy [15]. DT affects the entire city or municipality, specifically the stakeholders and the environment. DT further affects how city and municipal operations are run and goes beyond digitalisation by altering basic urban processes. It restructures the city’s value creation process and business logic [3].

In 2023, the global digital adoption rate was reported as 5.3 billion people using the Internet, which is 65.7% of the global population; of this percentage, 61.4% are using social media [16]. The South African population stood at 60.14 million in 2023, and digital adoption in terms of Internet use is 43.48 million (72.3%), of which 25.80 (49.9%) million are social media users [17].

Digital adoption in South Africa has provided municipalities with a learning opportunity to evolve into data-driven smart municipalities to increase productivity, growth, employment, and highly skilled citizens. However, there are no guidelines to standardise the concept of smart cities across municipalities in South Africa. There are also no DT guidelines for municipalities to guide them on how to become data-driven smart municipalities. The ad hoc implementation of DT solutions shows that limited digital transformation framework and guidelines directs municipalities on how they can transform into smart municipalities and, therefore, become data-driven.

A Value Alignment Smart City Stakeholder (VASCS) model that contributes to the success of a Smart City was developed and empirically validated by van der Hoogen et al. [18]. This paper adapts and implements the VASCS model to provide a better understanding of the adoption guidelines of digitalisation and the use of DT for smart municipalities in developing countries. Therefore, this paper will present the DT framework and guidelines that municipalities may use to guide their transformation into smart municipalities in the Eastern Cape, South Africa [19].

Cities are major energy consumers and account for 75% of the world’s fossil fuel usage [20]. Increasing energy demands, the impact of COVID-19 on global working trends, and the war in Ukraine have all contributed to a global energy crisis that requires urgent attention and solutions [21,22]. In South Africa, the energy crisis, due to poor infrastructure and a reliance on conventional sources, such as coal, began in 2015 and has intensified over the past few years, and has hampered productivity and economic growth [23]. A coordinated energy strategy and a shift towards renewable energy are possible solutions that can be driven by the Smart City digital adoption process.

This paper addresses the following research question: ‘How can lessons learned from the Eastern Cape Municipalities digital adoption be scaled to other developing nations facing similar challenges in energy management and urban planning?’ Therefore, the objective of this study is to empirically develop and present a DT framework for smart municipalities. A survey was conducted in four municipalities in the Eastern Cape, South Africa, and the results were used to identify the lessons learnt and guidelines provided in the DT framework for smart municipalities. The rest of the paper is structured as follows: a literature review is presented (Section 2), the important Smart Municipality factors included in this study are indicated in Section 3, and Section 4 shows the Smart Municipality conceptual model indicating all the core concepts of this study. In Section 5, the research design followed is indicated, the results are presented (Section 6), the guidelines are included in the DT framework (Section 7), which follows a discussion about this study (Section 8), and, finally, the conclusions are shown (Section 9).

2. Literature Review

The literature review addressed the following core concepts, which were needed to guide the data collection of this study. These concepts are urbanisation (Section 2.1), smart cities, and the related dimensions (Section 2.2). The review continues to delve into the Smart Municipality (Section 2.3) concept by addressing the international and national aspects of these municipalities. Furthermore, the state of municipalities in South Africa is highlighted (Section 2.4). The role of IoT and how it drives digitalisation is investigated (Section 2.5) and how the data explosion of smart cities has taken on the concept of data-driven cities/municipalities (Section 2.6). The best practices for smart municipalities are identified in Section 2.7, and the independent factors for each of the core Smart Municipality dimensions of this study are in Section 3. Finally, the literature review ends by highlighting the conceptual model for a Smart Municipality (Section 4), which shows all the core concepts of this paper.

2.1. Urbanisation

By 2050, the world’s urban population is expected to grow by 63% [24]. As of 2018, 55% of the world’s population lived in cities and this number is expected to increase to 68% by 2050 [25]. Urbanisation, the increasing concentration of populations in urban areas, brings a myriad of challenges for cities and municipalities worldwide. These challenges span various dimensions, including infrastructure, public health, economy, public safety, and social equity.

A key challenge with growing urbanisation is the need for substantial infrastructure improvements. Infrastructure is critical for the economic and social wellbeing of urban residents. Climate change exacerbates these challenges, as cities must also focus on building climate-resilient infrastructure capable of withstanding extreme weather events, like floods, storms, and heatwaves [26]. Municipalities will be required to increase spending on infrastructure due to climate change as 88% of forecasted costs of adapting to climate change will be on infrastructure [26].

Urbanisation also highlights issues of social equity and public safety. The systemic discrimination and exclusion of the poor in urban agendas, coupled with an increase in violent crime rates in some areas, present significant governance challenges. Municipalities recognise the interconnections between public safety, mental health, health services, and economic development. The management of agencies responsible for public safety is influenced by municipal size and other local factors, further complicating the governance of these issues [26,27]. The path forward involves acknowledging and addressing these multifaceted challenges to ensure sustainable urban futures. Smart cities have emerged as a response to the growing challenges and opportunities created by this urbanisation [28].

2.2. Smart Cities and Dimensions

Albino et al. [29] (p. 6) conducted a study on Smart City definitions; although no consensus about a Smart City concept exists, for this paper, the definition adopted is as follows: ‘A Smart City is based on intelligent exchanges of information that flow between its many different subsystems. This flow of information is analysed and translated into citizen and commercial services. The city will act on this information flow to make its wider ecosystem more resource-efficient and sustainable. The information exchange is based on a smart governance operating framework designed to make cities sustainable’. In this definition, information flow is a key driver for smart cities and their governance in achieving sustainability.

The VASCS model [18] identified nine dimensions of a Smart City: smart economy, smart environment, smart governance, smart living, smart mobility, smart organisation, smart people, smart policies, and smart technology. Smart technology was identified as one of the supporting dimensions for the rest. In adopting the VASCS model, this paper focuses on four of the nine Smart City dimensions, applicable to smart municipalities. The four dimensions discussed are smart governance, smart environment, smart living, and smart technology. These four are selected based on their impact on energy as an important and scarce resource due to urbanisation.

It is expected that by 2050, 70% of the world’s population will live in cities, which will increase energy demands [30]. Therefore, cities must use smarter ways to generate, manage, and distribute energy.

Municipalities in these cities are seen as the most significant energy consumers, showing they use 75% of the world’s energy and generate 70% of global CO₂ emissions [31] and growing figures are expected if nothing changes. Energy is one of the most common areas of technological innovation in smart cities because managing its consumption is a major challenge for cities [32,33]. These innovations are applied to optimise energy consumption, reduce costs and promote environmental sustainability [32]. Smart technologies, such as smart grids, smart metering and IoT technologies for real-time monitoring and data collection have been implemented to meet challenges in Smart City dimensions, such as smart living (electric vehicles, smart homes and buildings) and smart environment (renewable energy sources) [32]. The success of these technologies will largely depend on the implementation of appropriate governance (smart governance) strategies.

2.2.1. Smart Governance

Several cities have launched transformational programs, known as Smart City initiatives, to serve inhabitants better and improve their quality of life [34,35]. Multiple stakeholders are involved in these initiatives. As a result, a greater demand for stronger governance to oversee these projects and initiatives has emerged in various studies [36]. In order to achieve goals and objectives, governance entails implementing processes involving stakeholders who share information according to norms and standards [37].

The introduction of IT that improves governance has benefited several cities. Smart governance refers to IT-based government. It encompasses various technologies, people, laws (such as energy consumption), practices, resources, social norms, and data that work together to enable municipal governance. Smart governance lies at the heart of Smart City projects [38].

2.2.2. Smart Environment

On the environmental front, Smart City efforts should be forward-thinking [39]. The use of technologies to promote sustainability and better manage natural resources is central to the concept of a Smart City [31,40]. Natural resources and related infrastructure, such as canals and sewers, as well as green areas, such as parks, are relevant [41]. These elements, taken together, impact a city’s sustainability and liveability; hence, they should be considered while evaluating Smart City programmes.

Law and Lynch [31] emphasise that the sustainability of a smart environment must be approached through the prevention of high energy consumption, and through renewable energy, smart grids, pollution control, green buildings, green urban management, efficiency, utilisation, urban grid, street lighting, waste management, drainage systems, monitoring water resources, reducing contamination, and improving water quality.

2.2.3. Smart Living

Globally, the development of smart cities aims to provide residents with a higher quality of life using new and improved IT. The Smart City, which has connected and effective parts, is the most complex urban plan based on IT. Smart living is not easy for all residents to understand, because it is based on immersive information and data and is driven by intelligent networking by people and services [37]. Providing citizens with information based on modern technologies and raw data is important. More importantly, by developing their thinking, citizens must be aware of the services and accessibility that may be available to them in their specific geographic contexts based on their interests and preferences [42].

2.2.4. Smart Technology

The availability and quality of IT infrastructure are critical for smart cities [43,44]. Wireless infrastructure, including fibre optic channels, Wi-Fi networks, wireless hotspots and kiosks [45,46], and service-oriented information systems are examples of these critical IT infrastructures [47,48]. E-government technology barriers shall be referred to as Smart City IT infrastructure barriers, as these projects are similar to e-government initiatives in their use of IT [49].

When using IT, it is important to emphasise the need to remove inequities, close the digital divide, and improve individual capability and resource availability [37]. Regardless of their willingness to participate in smart urbanisation, vulnerable members of society grow more and more estranged because of inequality [50]. When implementing IT, municipal administrators should consider willingness, institutional resources, availability, capability, dissimilarity, changing culture, digital divide, and habits.

2.3. Smart Municipalities

Smart municipalities, promote sustainable development and support the achievement of environmental goals using technology [51]. Improved quality of life should also be a goal for any Smart Municipality’s effort to enhance the lives of citizens. This is measured by comparing the citizens’ quality of life before and after these efforts. The VASCS model [18] proposes that transitioning from the traditional to a Smart City model and using the benefits/value realisation component can aid in mapping the value for such efforts and understanding where the gaps exist.

According to Vial [52] and Verhoef et al. [3], municipalities are required to increase their service delivery operations through digital transformation by using various digital technologies [52]. However, using digital technology alone would not guarantee digital municipal transformation, especially if their adoption is poorly planned and improperly implemented or lacks the support of high management [53].

2.3.1. Smart Municipalities at the International Level

The Case of Vienna

In 2011, the Vienna Smart City drive was launched and the city started the essential process by uniting partners from different municipal offices and other relevant stakeholders in 2013 [54]. This led to the ‘Smart City Wien Framework Strategy’ in 2014, which aimed to provide guidelines for developing the Smart City initiative. This strategy had three main areas: quality of living, resources, and innovation, which coordinated specific issues and points. Despite the common points and differences in models for implementing a Smart City, stakeholders in the Vienna Smart City project agreed that governance was the most important dimension, followed by people and the environmental dimension. However, in terms of implementation, there were more projects for the environmental dimension. This highlighted a disconnect between actual project implementation and stakeholder perspective.

The Case of Aarhus

Denmark provides a favourable environment for developing and testing the Smart City concept due to the country’s long history of incorporating different stakeholders in its decision-making process, especially in urban planning and environmentalism [55]. As a result of this legacy, the country was the first to pass an environmental protection law in 1973. Aarhus is Denmark’s second-largest city, with a population of more than 320,000 individuals. The initiative was built around Smart Aarhus and traces back to a gathering in 2010 where interested managers and directors met with agents from Aarhus University and the Alexandra Institute. This exclusive, charitable association helps public and private associations create innovative IT-based products and services to encourage development and prosperity in Danish society. Confronted with similar difficulties as numerous urban communities worldwide, which are increasing populations, limited revenue, and high expectations for what the city should offer, an alternative approach was envisaged to make the city liveable for all inhabitants.

Smart Aarhus has completed three milestones during the last few years. These are known as the ‘pillars’ of Smart Aarhus’ success, and each continues to grow. The first pillar is Open Data Aarhus. The city of Aarhus was the first in Denmark to create such a service, and Open Data Aarhus now presents more than 75 datasets [55]. Internet Week Denmark is the next pillar. This event started in April 2014 and aimed at making IT solutions more relevant and visible to the community. The third pillar, Aarhus Challenges, involves figuring out the city’s social problems. This critical thinking strategy, for instance, uses digital means to make it easier for the elderly to use the Internet.

2.3.2. Smart Municipalities at the National Level (South Africa)

Cities continue to be the engine of the economy and the homes of most South Africans. Still, they continue to face challenges, such as insufficient infrastructure, service delivery funding, and consumer affordability of municipal services [56]. Municipalities, also known as local governments in South Africa, are recognised as a distinct and independent level of government, with assigned powers and responsibilities unique to this level. There are 278 municipalities in South Africa, with 8 metropolitan municipalities, 44 district municipalities, and 226 local municipalities [57]. They are mostly interested in strengthening local economies and providing infrastructure and services.

Following the definition of smart municipalities in Section 2.3, it can be confirmed that most South African municipalities are not yet smart municipalities. This is because they use IT on an ad hoc basis and the status quo in South African municipalities is the opposite of what is defined as smart municipalities [58].

The Smart City concept was primarily implied in government objectives and plans, with private real estate developers yet to embrace the concept fully. However, during his State of the Nation Address in 2022, President Cyril Ramaphosa declared that his Smart City goal had become a ‘reality in the making’ with the launch of the Lanseria Smart City [59]. The city focuses on adopting ‘best practices’ in urban sustainability and the ideas underpinning a Smart City to build the first post-apartheid metropolis in South Africa’s democratic, developing economy [60]. Other examples of smart cities in South Africa are discussed below.

The Case of Johannesburg

The most unprecedented increase in the use of the term Smart City in the South African mediascape is from Johannesburg [61]. From 2014 to 2018, the term and discussions around the topic had precedent. For instance, the Joburg Broadband Network Project has existed since 2007, when the regional government established a framework for public–private collaboration [62,63,64]. The main goal was to place Johannesburg as an investment-friendly city with a state-of-the-art ICT infrastructure, increasing access to broadband and decreasing the digital gap [61]. Due to the challenges in the public sector, it was determined that working with the private sector would be important to understand this target. Under the rationales of the digital city, such joint initiatives with the private sector were accordingly not centred around the broader deregulation of the governance space but focused more on executing a state-driven project.

The Case of Cape Town

Cape Town is South Africa’s second largest metropole. Businesses, industries, public society, and academia founded the Western Cape Economic Partnership, a non-profit organisation that developed a long-term vision for the province as a center of innovation and creativity in IT programming. The purpose of local government, according to the plan, is to enable access to IT and related services through integrated service nodes and IT access at public facilities and buildings, as well as at hotspots in public areas [50].

The Western Cape Department of Economic Affairs and Tourism launched another project dubbed ‘Connected Cape’ as part of their broadband rollout plan. Through infrastructure construction, guaranteeing readiness to use this infrastructure, and encouraging adoption of these services, the plan focuses on connected citizens, connected government, and a connected economy. As a result, the government’s role in accelerating and facilitating the development and growth of ICT infrastructure is dominating. The City of Cape Town additionally helps bulk infrastructure rollout by providing internet access between provincial and local government facilities, as well as schools in underserved areas [50].

The Case of eThekwini

eThekwini (Durban) is South Africa’s third-largest metropolitan region. It was one of the main urban regions that implemented the Smart City concept. The Smart City articulation frames the relationship between equitable infrastructure and market pressures, in which local policy agendas are intertwined with the developmental power of IT [50]. Although this concept exists in various urban communities (for example, Cape Town, Johannesburg, and Ekurhuleni), eThekwini dubbed these rationales ‘Smart’ much earlier, emphasising the need to market its broadband fibre optic link network with a private sector partner and to begin the rollout of less expensive broadband and telecommunication services to businesses and residents as early as 2007 [65]. The eThekwini strategy demonstrates that the Smart City concept may be implemented locally without centralisation.

2.4. Role of the Internet of Things (IoT)

According to Čolaković and Hadžialić [7], approximately 1.6 billion IoT components and devices were used to develop smart cities globally. The IoT will connect objects to the Internet, enabling new insights, improving operations, streamlining automation, and reducing costs [66]. Different types of sensors, support technologies, and background environments have been considered to be among the most important aspects for successfully completing Smart City development [67].

The IoT has efficiently provided user-customised services by collecting data through electronic home appliances in the smart home environment [68]. The role of the IoT has been observed in the efficient management of energy and electricity by providing convenient and economically sound infrastructure for smart cities. The services provided by the IoT technologies for Smart City developments have resulted in a sustainable and pleasant living environment for the citizens. Hence, the IoT is efficient enough in collecting, analysing, and distributing data to promote Smart City development.

2.5. Role of Digital Transformation (DT)

Digitalisation has evolved rapidly in alignment with expanding urbanisation while providing the technologies for Smart City development and enhancing sustainability [11]. Digitalisation is defined by Brennen and Kreiss [69] (p. 6) as ‘the way in which many domains of social life are restructured around digital communication and media infrastructures’. The Gartner glossary describes digitalisation as ‘the use of digital technologies to change a business model and provide new revenue and value-producing opportunities; it is the process of moving to a digital business’ [70].

There is a global trend toward digital-based urbanisation, with approximately four billion people living in cities today [71]. Many municipalities pursue Smart City development initiatives [72]. A Smart City can generate, collect, and process data to support intelligent forecasting and decision-making for better urban improvement and scheduling [73].

Public sector organisations, as well as private sector organisations, aim to start and accelerate their DT and take advantage of the potential of digital technology to meet the growing demand from citizens [74]. This goal is not new; it is the next phase of the public sector’s digitalisation. It follows e-government programs that use digital technologies to give residents and stakeholders faster access to public services [75]. The IT department’s job in the public sector is to supply essential technologies and facilitate extensive municipal change [76].

Implementing DT in municipalities involves incorporating new methods for working with stakeholders to develop new service delivery frameworks and generate new interactions [74]. The successful DT in municipalities is represented only when the appropriate implementation of change management, its initiatives, and the transformation of digital projects are initiated within the system. Also, the involvement of leadership and management buy-in is important for the successful implementation of DT in the municipalities [77]. Most of the challenges and issues of municipalities are resolved by the performance of DT projects. It provides efficient services and communication that improves the citizens’ quality of life and changes the organisation’s culture, evolving the Smart City concept [74].

In closing, the above interpretation indicates that social life must be considered in the process of sustainability of a Smart City (smart environment). This is due to many demands that citizens require to be met (smart living) and using the process of DT to manage these demands has been indicated to be better than manually managing areas, such as municipalities. Also, DT aids the concept of Smart City initiatives, such as a connected city, to achieve transparency in information flow to discover where societies have disparities and gaps with access to services using technology and digitalised services (smart technology). However, officials through e-governance and governance (smart governance) within a city or municipality must approve such structures and support such Smart City initiatives.

2.6. Data-Driven Smart Municipalities

The data-driven Smart Municipality describes the successful development of smart cities, comprising digitalised techniques, which are monitored through ICT for effective management of the city towards the development and implementation of solutions for the issues faced by the citizens [11]. IoT technology and Big data have given rise to the data-driven concepts implemented by cities by adopting DT. The data-driven concept has also emerged in the urbanisation aspects considered important for developing smart cities and generating smart municipalities [78,79]. Hence, data-driven governance efficiently improves smart municipalities by maintaining effective communication with communities and further building trust by enhancing the transparency and effectiveness of municipal governance [80]. Some of the data-driven municipalities have paid major attention to the development of regulations concerning the municipal authorities, which has influenced citizens during municipal operations [81].

The large demographic density of cities has provided large-scale data for the municipalities to collect and analyse. Smart municipalities are using data-driven tools to produce modernised products and effective delivery services to improve citizens’ lives. Hence, this will increase the economy’s growth and social influence [82].

Bunders and Varró [83] have identified some challenges with this approach. According to the authors, the first challenge, even in developed countries, is that access to the technology that drives the ‘smartness’ of municipalities, such as modern computers at home and high-speed Internet access, is not widely or equitably distributed. Therefore, the push for a data-driven city and the conscious allocation of resources to drive it means some communities will be left behind as they cannot afford the necessary enabling technologies. This inevitably creates a digital divide, which is not a desirable scenario. At the same time, the practical benefits to the general populace might be tangible. Still, the actual benefits are much smaller, especially in financial terms and access to investment and actionable opportunities. This creates even more inequality as the investment in smart cities is not distributed proportionally.

2.7. Best Practices for Smart Municipalities

The adoption of smart municipalities complies with some best practices, which promote transparency, open disclosure and accountability. Schwertner [84] proposes five essential best practices for effective smart municipal adoption. These are frequent engagement, open decision-making, good governance, documented consideration of privacy implications, and robust open data practice.

2.7.1. Engage Early and Often

Early engagement requires that the community be involved in helping public officials decide what technologies to buy when they might impact privacy and security issues [85]. Engagement includes making decisions about collecting, using and protecting personal data in the public interest. The community should also be included in determining if the advantages of proposed smart municipal projects outweigh their costs, particularly when considering the non-financial expenses related to surveillance, such as loss of privacy and civil liberties [35]. This confirms a dedication to obtaining input from various stakeholders, including university partners and the neighbourhood technology community, for subject matter expertise and education.

2.7.2. Open Decision-Making

Smart municipal regulations should require that public officials disclose how and why smart municipal initiatives are chosen. This must be carried out before they are formally implemented to foster confidence and ensure that acquired technologies are used in ways that do not infringe on civil freedoms [86]. For this purpose, there should be a public discussion of the plans for acquiring new smart technology before the procurement procedure starts. This includes describing the issue, why this technology offers a solution, any competing options, and why this is the best option. Public officials should be subject to explicit transparency and public accountability norms regarding technology use, according to smart municipalities policies. This entails passing legislation requiring personnel to monitor smart municipal policy to disclose how, where, and why a project will be executed within a set timeframe following the launch of a new smart municipal initiative.

2.7.3. Good Smart Municipal Governance

The public disclosure of the types of data being gathered and the techniques used for data storage and transit should be provided under smart municipal laws. This could be attained by creating a data inventory to keep track of fundamental details regarding data gathered through smart technologies, such as name, contents, update frequency, usage license, owner/maintainer, privacy issues, and data source [52]. Public officials should also carefully evaluate data ownership, especially when engaging in Public-Private-Partnerships (PPPs) and ensure that municipalities have the right to own or control the data produced by the platforms and devices used. Visvizi and Lytras [87] stress that contracts with outside vendors should include a formalisation of these rules. Municipalities should continue to be transparent in their use of and analysis of data. If algorithms are being used to process data, automate procedures, or analyse data, these algorithms should be made available to the public and subject to expert and public review.

2.7.4. Documented Consideration of Privacy Implications

According to Sorescu [88], smart municipal regulations require public officials to assess how new technologies may affect residents’ right to privacy and ensure that this right is adequately protected. In this case, proactive community engagement is essential because community members and public officials should jointly determine what the right to privacy implies. A privacy effect assessment created before each smart technology purchase could serve as an effective approach to ensure privacy assurance.

2.7.5. Robust Open Data Practice

Smart municipalities should work to collect more data and analyse it in real-time to optimise efficiency and data transparency as essential elements to attain a successful Smart Municipality. As a result, smart municipalities should treat information as a public benefit and default to using open data [89]. In this view, smart municipalities should prioritise open data through open data infrastructure, such as open data portals, enabling more innovative data applications and new opportunities for citizen empowerment and public involvement. Prioritising digital inclusion and closing the digital divide will be necessary for realising the vision of an open, Smart Municipality [89].

3. Smart Municipality Factors

This paper focuses on the four dimensions of a Smart Municipality that incorporates energy and or electricity management as important aspects to consider. The sections to follow (Section 6.2–6.5) highlight each dimension as an independent factor and contain codes for each dependent question based on the literature. These questions formed part of the survey for municipalities in the Eastern Cape province (Appendix A). The VASCS model [18] was validated and empirically confirmed for Smart City initiatives within the EC. Therefore, this study was conducted to test the model in practice for those municipalities adopting Smart City and digitalisation practices.

Although DT is a global phenomenon, the pace of digitisation adoption and policy response is highly dependent on countries and regions, reflecting differences in economic structures and levels of digitalisation. In terms of digital infrastructure and connectivity channels, the Eastern Cape is geographically located on the southeast coast of South Africa, and the location has proven to be an advantage, due to its proximity to the submarine cable network commonly known as the Undersea Cable Network.

The Eastern Cape is one of the poorest provinces in South Africa and, therefore, can benefit from this research and may use it to adopt a digital transformation framework to embrace smart municipalities. This research uncovers the necessary DT framework and guidelines for adopting smart municipalities.

4. Smart Municipality Conceptual Model

Different models for smart cities have been introduced in the literature. Chourabi et al. [37] developed a model focusing on Smart City initiatives. They observed three internal factors that affect the Smart City: technology, organisations, and policy. External factors (government, people and communities, natural environment, and infrastructure) have an auxiliary impact. The triple helix model was used to explore the metropolitan economy’s information base by Leydesdorff and Deakin [90]. It was offered as a tool for innovation opportunities in smart cities. In a modified triple helix, Lombardi et al. [91] extended their model to incorporate civil society and in subsequent work [92] updated the model with five city clusters (governance, economy, human capital, living, and environment). Three of these clusters were confirmed in this paper as important dimensions in a Smart Municipality (governance, living, and environment) and technology as the support dimension.

The Smart Municipality was conceptualised by Nam and Pardo [93] as a worldview that included institutional, technological, and human factors. The VASCS model [18] introduced five core components, which included the nine dimensions: stakeholders, benefits/value realisation phases, data/digital value chain, and stakeholder value alignment [94]. These components were empirically validated and the VASCS model highlighted key suggestions for the success of Smart City projects.

The conceptual model presented in this paper contributed to undergirding the DT Framework for Smart Municipalities in developing countries and highlights all the concepts that should contribute to the DT guidelines of a Smart Municipality. The concepts are Smart City dimensions, especially smart technology as a foundation for DT using IoT, data-driven smart municipalities, and best practices. The conceptual model is illustrated in Figure 1. For statistical analysis purposes, the dimensions will be referred to as factors to be tested to accept or reject the hypotheses. These independent and dependent factors (Section 3) facilitate the creation of a conceptual model of the Smart Municipality.

This Smart Municipality conceptual model (Figure 1) positions smart technology (IoT, DT) and data-driven concepts as important for Smart Municipality development. From the reviewed literature, several authors assert that a Smart Municipality’s success depends on data availability (Section 2.7). This is the central point where raw data are collated in real-time using Big data technologies for categorisation, curation, analysis and storage. Municipalities would need to acquire Big data technologies, such as artificial intelligence, IoT, and cloud computing to ensure that data dashboards are functional based on their requirements. Therefore, it is proposed that municipalities can become citizen-centric and connected based on applying the concepts identified in the Conceptual Model of a Smart Municipality (Figure 1). Smart City factors, such as smart governance, smart environment, smart living, and smart technology, positively influence the success of a Smart Municipality.

5. Research Design

Based on Saunders et al. [95], the positivism philosophy was explored in this research study as it supports the quantitative research methodological choice. The positivism philosophy interprets relevant results and effectively infers the connection among the different variables objectively and independent of the researcher. This study seeks to determine the connection between the Smart City dimensions and a successful Smart Municipality through measurable and observable facts. The positivism paradigm is, therefore, most suitable for the study. A deductive approach has also been used to test existing research studies established from the literature study. A descriptive research design has been followed in this study as it aims to obtain information to describe a phenomenon, situation, or population systematically. More specifically, it helps answer what, when, where, and how questions regarding the research problem rather than why [96].

5.1. Population and Data Collection

The primary data for this study were gathered by using an online QuestionPro survey. The survey used a five-point Likert rating scale, where statements were rated on a rating scale of 1 = Strongly Disagree; 2 = Disagree; 3 = Uncertain; 4 = Agree; 5 = Strongly Agree. The literature study undertaken served as the foundation for the creation of the questionnaire and the operationalisation of the questionnaire items.

This study was conducted in four municipalities, namely: Chris Hani District Municipality, Dr AB Xuma Local Municipality, Enoch Mgijima Local Municipality, and Intsika Yethu Local Municipality. These municipalities were selected based on convenience, since the primary researcher’s hometown falls under Dr AB Xuma Local Municipality; the primary researcher currently resides in Enoch Mgijima Local Municipality, previously worked for Intsika Yethu Local Municipality, and is currently working for Chris Hani District Municipality. The study targeted the following employees of a municipality: municipal managers, councillors, executive management, IT officials, unit managers, computer users, and other municipal employees who use IT to perform their job responsibilities within the municipalities. The population mentioned was from different departments in the selected municipalities.

In total, a population of 270 people from the 4 municipalities under study, using the confidence of 95% and margin error of 5.0%, was decided on (

Table 1. Population and sample size.

Category	Population	Sample Size
Chris Hani District Municipality	111	66
DR AB Xuma Local Municipality	45	24
Enoch Mgijima Local	77	47
Intsika Yethu Local Municipality	37	22
Total	270	159

). From the 159-person sample size, a total of 142 respondents was deemed adequate to start data analysis (Section 6.1).

Various statistical analyses were conducted, such as descriptive statistics, reliability and validity of the research instrument, correlation coefficients, and exploratory factor analysis (EFA). However, the NMU statistical consultant indicated that there was no need to conduct a confirmatory factor analysis (CFA) because the results of the EFA indicated that all the items have high loadings on the factors they are supposed to reflect. The quantitative analysis enables the researcher to investigate and analyse various factors, such as how these factors relate to the research questions.

The characteristics of the sample compared to the population were as follows: cost-effectiveness (proximity of the municipalities to the researchers); an indication during the requirements elicitation that the municipalities lack formal DT guidelines; participants’ position held at the municipalities; seniority within the municipality organograms; key stakeholders with an interest in municipal matters, such as Smart Municipality initiatives.

5.2. Hypotheses

The following hypotheses were tested using empirical analyses through statistical procedures:

• Smart governance: H₁—smart governance positively influences the success of a Smart Municipality.
• Smart environment: H₂—smart environment positively influences the success of a Smart Municipality.
• Smart living: H₃—smart living positively influences the success of a Smart Municipality.
• Smart technology: H₄—smart technology positively influences the success of a Smart Municipality.

5.3. Ethical Considerations

Research ethics entails the application of fundamental ethical principles in research activities, such as the design and implementation of research, respect for society and others, as well as resource outputs and scientific misconduct [97]. The study involves various municipalities within the Eastern Cape, which need a risk assessment to be conducted before data collection could be executed; thus, ethical considerations to ensure data confidentiality and confidentiality, as well as informed consent, were critical The Research Ethics Committee at Nelson Mandela University provided ethical clearance with an ethics clearance reference number H22-SCI-CSS-006 on the 19 August 2022. The study data can be requested from the authors if required.

6. Results

6.1. Participants Demographics

The distribution of participants (Figure 2) from each municipality shows that the highest percentage, 43% (n = 61), of the respondents were from Chris Hani District Municipality, 25% (n = 36) were from Intsika Yethu Local Municipality, 17% (n = 23) were from Enoch Mgijima Local Municipality, and the least percentage of respondents was from Dr AB Xuma Local Municipality with 15% (n = 22).

The distribution of respondents’ positions within the municipalities (Figure 3) indicates that employees who selected ‘Other’ had the highest response rate of 34% (n = 48), followed by computer users with 23% (n = 33). Unit managers accounted for 16% (n = 23), followed by ICT unit officials with 13% (n = 18). Councillors accounted for 7% (n = 10) and executive management accounted for 5% (n = 7). Municipal managers accounted for the least number of responses, with 2% (n = 3).

6.2. Independent Factor: Smart Governance

This section of the questionnaire aimed to establish the degree to which the respondents perceive smart governance. The section summarises the responses to the eight items related to the independent factor of smart governance.

Eighty-seven percent (n = 123) of respondents agreed with the statement SGov_01 (smart governance influences the quality of human settlements in smart municipalities), whereas ten percent (n = 14) of respondents were uncertain. Ninety-one percent (n = 129) of respondents agreed with the statement SGov_02 (smart governance influences the education system of smart municipalities). Seven percent (n = 10) of respondents were uncertain with only two percent (n = 3) of respondents disagreeing with the statement SGov_02. Furthermore, eighty-nine percent (n = 127) of respondents agreed that smart governance influences smart municipalities’ healthcare (SGov_03).

For the items SGov_04 to SGov_08, the respondents consistently continued to agree with the statements. SGov_04 (smart governance influences the social welfare of smart municipalities) had 89% (n = 126) of respondents agreeing to the statement, SGov_05 (smart governance influences the sanitation and refuse and waste removal in smart municipalities) had 91% (n = 129) of respondents agreeing to the statement, SGov_06 (smart governance influences transport of smart municipalities) had 81% (n = 115) of respondents agreeing to the statement, with 15% (n = 21) of respondents that were uncertain, and 4% (n = 6) of respondents that disagreed with the statement. SGov_07 (smart governance influences the provision of electricity and energy in smart municipalities) had 88% (n = 125) of respondents agreeing, and SGov_08 (smart governance influences water delivery in smart municipalities) had 89% (n = 127) of respondents agreeing to the statement.

In summary, it can be concluded that the largest proportion of respondents consider that all smart governance factor items influence Smart Municipality’s success. Therefore, it is evident that the independent factor, smart governance, should be included in the DT framework (Figure 4), and the DT guidelines for this factor should be developed.

6.3. Independent Factor: Smart Environment

The extent to which the respondents believe that a smart environment can influence the success of smart municipalities was established in this section. The responses to the eight items regarding the smart environment are discussed here.

The largest number of respondents (92%, n = 130) agreed that a smart environment influences the promotion of sustainability and can improve the management of resources of smart municipalities (SEnv_01). Ninety-two percent (n = 130) agreed that the smart environment has an influence on the quality of life of residents in smart municipalities (SEnv_02). Furthermore, 86% (n = 122) agreed with the statement SEnv_03 (smart environment influences the control of pollution in smart municipalities), 92% (n = 130) also agreed with statement SEnv_04 (smart environment influences the urban environment quality of smart municipalities). A notable majority agreed with SEnv_05 to SEnv_08, with SEnv_05 (87%, n = 124), SEnv_06 (89%, n = 126), SEnv_07 (83%, n = 118), and SEnv_08 for 89% (n = 127).

In summary, it can be concluded that the largest proportion of respondents consider that all smart environment factor items influence a Smart Municipality’s success. Therefore, it is evident that the independent factor, smart environment, should be included in the DT framework (Figure 4), and the DT guidelines for this factor should be developed.

6.4. Independent Factor: Smart Living

Here, we summarise the responses to the six items related to the independent factor of smart living. The aim was to establish the extent to which the respondents believe smart living influences smart municipalities’ success.

Several respondents agreed with statements SLiv_03, SLiv_05, and SLiv_06 at 92% (n = 130) for each statement, respectively, that smart living influences mobility, improvement of health, education, social services, and the use of ICT in smart municipalities. In the SLiv_01 and SLiv_02 statements, 90% (n = 128) of respondents, respectively, agreed with the statements that smart living has an influence on technology to enable intelligent lifestyles of citizens and the use of renewable energy in smart municipalities. However, few respondents were uncertain, with 8% (n = 11) for SLiv_02 and 7% (n = 10) for SLiv_01, and there were some respondents with disagreements, with 2% (n = 3) for SLiv_02 and 3% (n = 4) for SLiv_01. Eighty-seven percent (n = 124) of respondents also agreed that smart living has an influence on energy use efficiency in homes in smart municipalities (SLiv_04), whereas nine percent (n = 13) were uncertain and four percent (n = 5) disagreed with the statement.

In summary, it can be concluded that the largest proportion of respondents consider that all smart living factor items influence a Smart Municipality’s success. Therefore, it is evident that the independent factor, smart living should be included in the DT framework (Figure 4), and the DT guidelines for this factor should be developed.

6.5. Independent Factor: Smart Technology

This section of the questionnaire aimed to establish the extent to which the respondents believe that smart technology influences smart municipalities’ success. The responses of respondents illustrated frequency distribution on the independent factor of smart technology.

Most respondents (95%, n = 135) agreed that smart technology influences the smart economy of smart municipalities (Stech_03). In addition, 94% (n = 133), 92% (n = 131) ,and 90% (n = 128) of the respondents felt positive or agreed with statements Stech_01 (smart technology influences the deployment of smart technology infrastructure influences the success of technology-driven smart municipalities), Stech_02 (smart technology influences the integration of smart technology into municipal development plans influences the improvement of Smart Municipality functioning), and Stech_05 (smart technology influences the promotion of collaborative eco-systems in smart municipalities), respectively. Stech_04 (smart technology influences promotion of inequality and contributes to a digital divide in smart municipalities) and Stech_06 statements are also more than 80% agreed with, with STech_04 at 85% (n = 121) and STech_06 (smart technology influences minimising environmental impact while maximising social wellbeing in smart municipalities) with 88% (n = 125) of respondents agreeing with the statements.

In summary, it can be concluded that the largest proportion of respondents consider that all smart technology factors influence a Smart Municipality’s success. Therefore, it is evident that the independent factor, smart technology, should be included in the DT framework (Figure 4), and the DT guidelines for this factor should be developed.

6.6. Hypotheses Acceptance

According to

Table 2. Hypotheses Testing.

Hypothesis	Hypothesis Description	Pearson Correlation	Correlation Strength	Accepted/Rejected
H1	Smart governance positively influences the success of a Smart Municipality	r = 0.702	Highly positive	p < 0.0005 Accepted
H2	Smart environment positively influences the success of a Smart Municipality	r = 0.759	Highly positive	p < 0.0005 Accepted
H3	Smart living positively influences the success of a Smart Municipality	r = 0.765	Highly positive	p < 0.0005 Accepted
H4	Smart technology positively influences the success of a Smart Municipality	r = 0.704	Highly positive	p < 0.0005 Accepted

, all four hypotheses investigated were accepted through empirical evaluation and statistical analysis. For all hypotheses related to the Smart Municipality conceptual model, all p-values were less than 0.0005. Table 2 displays the hypotheses and their Pearson product moment correlation values, t-test scores, correlation strength, and status.

6.7. Frequency Distribution and Reliability of the Factors

Table 3. Central tendency and dispersion: factors (n = 142).

Factor	n	Mean	S.D.	Minimum	Quartile 1	Median	Quartile 3	Maximum
Smart governance	142	4.20	0.60	1.00	4.00	4.25	4.63	5.00
Smart environment	142	4.19	0.61	1.00	4.00	4.25	4.63	5.00
Smart living	142	4.24	0.61	1.00	4.00	4.33	4.67	5.00
Smart technology	142	4.23	0.61	1.00	4.00	4.25	4.67	5.00

presents the statistical analyses performed, which encompassed calculations of the mean, standard deviation, and the first and third quartiles. These statistics focused on central tendencies, like the mean, measures of variability (standard deviation), and range (minimum and maximum values), along with the first and third quartiles for detailed examination.

The variability of responses, as indicated by the standard deviation, ranged between 0.60 and 0.61, suggesting minimal variation among respondent answers. In contrast, ‘Smart Environment’, ‘Smart Living’, and ‘Smart Technology’ each had a standard deviation of σ = 0.61. The lowest standard deviation was observed in ‘Smart Governance’ at σ = 0.60.

Cronbach’s alpha coefficient is a widely utilised method for assessing the internal reliability of a measurement tool. The internal reliability of scales with multiple items was evaluated using this coefficient, as described by Collis and Hussey (2014) [98]. They state that for a measurement to be considered reliable, the Cronbach alpha coefficient should be at least 0.8. A Cronbach alpha coefficient of 0.70 or higher was indicative of ‘good’ reliability.

Consistent with the criteria set by Collis and Hussey [98], this study meets their requirements, as evidenced in

Table 4. Cronbach’s alpha coefficients for the factors (n = 142).

Factor	Cronbach’s Alpha	Interpretation
Smart governance	0.91	Excellent
Smart environment	0.91	Excellent
Smart living	0.90	Excellent
Smart technology	0.87	Good

, where all the Cronbach’s alpha values for the four factors exceed 0.80. This demonstrates that the reliability of the scores for these factors ranges from good to excellent.

7. Digital Transformation (DT) Framework

The DT framework of this study was based on empirical findings and on confirming the importance of each factor through a survey conducted with 142 participants from 4 municipalities in the Eastern Cape Province of South Africa. The following sections highlight the guidelines that could be used by municipalities wanting to adopt DT practices. These guidelines are based on the survey results on the Smart City factors presented individually in Appendix A, where the codes in

Table 5. Guidelines on the Smart Governance dimension.

No.	Code	Guidelines
1	GSGov01	Stakeholder engagement: Engage with the community, including citizens, local organisations, ward committees, ward councillors, traditional leaders, relevant stakeholders, and local authorities to take their views into account, form relationships, facilitate communication, and work together on innovative solutions that will ensure successful implementation of smart governance in municipalities.
2	GSGov02	Invest in digital infrastructure: Invest in robust digital infrastructure. This includes investing in high-speed internet access, cloud computing, and other technologies that can efficiently exchange data between municipalities and citizens.
3	GSGov03	Public–private partnerships: Leverage private sector resources and expertise to develop innovative solutions for municipal challenges. Partner with the department of basic and higher education to introduce Smart Municipality programmes in schools.
4	GSGov04	Citizen engagement: Ensure that citizens are informed about the changes taking place in their communities and have an opportunity to provide feedback on how these changes are impacting their lives.
5	GSGov05	Data management strategies and plans: Develop effective strategies that ensure data is collected, stored, and used responsibly and securely. Develop smart governance strategy to collect data on different aspects of government services, such as traffic, public transport, water supply, or energy consumption. Analyse, interpret, and exploit the collected data.

,

Table 6. Guidelines on the smart environment dimension.

No.	Code	Guidelines
1	GSEnv01	Renewable energy: Use renewable energy sources, such as solar, hydro, and wind-driven power to reduce carbon dioxide emissions and lower energy costs.
2	GSEnv02	Sustainability infrastructure: Build infrastructure that is adapted to climate change, such as solar roofs, rainwater gardens, and asphalt pavements.
3	GSEnv03	Smart environment framework: Develop a comprehensive smart environment framework that outlines the goals, objectives, and strategies for creating a smart environmental municipality. Collect data, store it, analyse it, and use data to inform decision-making. Assess existing infrastructure and resources, existing data sources, evaluate potential of new data sources, and plan for future investments.
4	GSEnv04	Smart metering and applications: Introduce software applications (apps) for the reporting of illegal dumping, refuse removal, and sewer spillages. Install smart meters for provisioning of smart electricity and smart water and replace all meters with smart meters. This will enhance revenue collection and will detect and prevent water losses.
5	GSEnv05	Public–private partnerships: Develop public–private partnerships with technology companies to leverage their expertise in developing innovative solutions for municipal challenges, such as traffic congestion or energy efficiency initiatives. Foster collaboration between citizens, businesses, government agencies, universities, research institutions, and other stakeholders to develop creative solutions for municipal challenges through hackathons or other events that bring together diverse perspectives on problem-solving.
6	GSEnv06	Waste management: Install smarter waste management systems where municipalities can monitor collection and recycling activities, which could result in more effective processes and a reduction in waste.

,

Table 7. Guidelines on the smart living dimension.

No.	Code	Guidelines
1	GSLiv01	Develop a comprehensive Smart Municipality plan: Assess and determine the needs of the community and draw up a plan to use technologies for improving public services and quality of life.
2	GSLiv02	Enhance transport and mobility: Develop efficient and sustainable transportation systems. Introduce municipal buses, convert some pedestrians walk into bike lanes.
3	GSLiv03	Reliable infrastructure: Develop robust and reliable infrastructure to support their operations. Invest in high-speed internet access, advanced telecommunications networks, and energy-efficient buildings and transportation systems. Install sensors, AI cameras, and other sources, so that municipalities can gain valuable insights into their operations and make more informed decisions about how to serve their citizens best. Allocate sufficient budget to fund IT infrastructure.
4	GSLiv04	Increase access to public services: Provide easy access to government services by introducing user-friendly application, websites, and self-service portals. Establish Internet hubs and mobile services, for instance e-governance, e-health, or a smart energy system.
5	GSLiv05	Encourage citizens engagement: Engage with citizens throughout developing and implementing Smart Municipality initiatives to ensure that they are meeting the needs of the citizens.

and

Table 8. Guidelines on the smart technology dimension.

No.	Code	Guidelines
1	GSTec01	Technology integration: Invest in the right technologies tailored to their specific needs of the municipality, such as IoT sensors, cloud computing solutions, data analytics platforms, and AI systems. Integrate these technologies into existing infrastructure and processes to maximize efficiency and cost savings.
2	GSTec02	Public safety: Install closed-circuit television (CCTV) cameras or AI-driven cameras and gunshot detection systems that may contribute to improving public safety. Introduce these systems to law enforcement authorities to detect possible illegal activities and provide valuable evidence in investigations.
3	GSTec03	Research and development: Conduct research on new technologies that supports digitalisation in municipalities for future development.
4	GSTec04	Develop a powerful digital infrastructure: Upgrade internet services to high-speed internet using fibre optic cables. Engage with mobile networks service providers to upgrade from 4G networks to 5G networks. Increase broadband internet access in rural areas. Build broadband networks in underserved areas.
5	GSTec05	Energy efficient lighting: Install smart streetlights to reduce energy consumption. These streetlights shall adapt to daytime and weather conditions with remote controls.
6	GSTec06	Invest in smart infrastructure: Install infrastructure, such as sensors, AI cameras, and other technologies, to improve security for farmers and water management systems. This will help municipalities better understand their environment and make informed decisions about improving services.

correspond to the questions asked in the survey. The guidelines presented reflect the factors most highly rated by respondents in the survey.

7.1. Smart Governance

Table 5 shows the guidelines that can be used to create effective smart governance in municipalities. Each guideline has been assigned a reference number for ease of reference and mapping on the framework.

7.2. Smart Environment

As evident from the research results, smart environment influences the success of smart municipalities. One of the main aspects of urban planning nowadays is to create sustainable environments in municipalities. Initiatives, such as using sensors to measure air quality, traffic congestion, and energy consumption or developing mobile applications to assist citizens with their journeys on public transport or report maintenance problems, may be included. Municipalities can help improve and further connect their communities in the future by adopting smart technologies. Table 6 shows some guidelines that municipalities may follow to implement a smart environment.

7.3. Smart Living

Smart living is the adoption of technology and data-driven approaches to improve citizens’ quality of life. Initiatives, such as smart road navigation systems, smarter streetlights, waste reduction and recycling programs, as well as effective water and energy management, can also be part of this dimension. The objectives are to create sustainable, connected, and living communities which prioritise the needs of citizens and their wellbeing. As evident in the research results and findings, municipalities can start by using the guidelines in Table 7 to create smart living in municipalities.

7.4. Smart Technology

The research results and findings indicate that smart technology is a key component for adopting smart municipalities. Smart technology can allow municipalities to engage with tools and techniques for connected and improved service delivery and engaging with citizens while providing effective and efficient real-time information through digitally enabled communication channels. Table 8 shows the guidelines in which municipalities can use smart technology.

Therefore, this study contributes to the first digital transformation framework for smart municipalities (Figure 4). The framework includes Smart City dimensions and digital transformation guidelines for municipalities that focus on becoming energy efficient by addressing climate change through their initiatives. The green arrows indicate where technology is applied for each of the dimensions.

The DT Framework for Smart Municipalities provides guidelines for transforming the selected municipalities into smart municipalities. The survey results highlight the perceptions of these municipalities on how smart governance, smart environment, smart living, and smart technology dimensions would influence the day-to-day operations of the municipalities and the personal lives of citizens.

The respondents expect certain aspects of citizens’ lives to be improved through smart governance. To achieve smart governance, the DT framework highlights the need for stakeholder engagement, digital infrastructure, public–private partnership, citizen engagement, and data management strategies and plans.

Regarding a smart environment, respondents expect improved innovation, sustainability, and better environmental quality in terms of pollution and waste. The DT framework suggests that these municipalities set up a smart environment framework, prioritize building sustainable infrastructure, consider moving to renewable sources of energy while employing smart metering tools, implement waste management processes, and focus on public–private partnerships to ensure collaboration between stakeholders and access to innovative solutions.

In responding about smart living, participants in the selected cases expect an improvement in health education, social services, and energy use, and the use of renewable energy sources and technology was highlighted for transitioning to an intelligent lifestyle for citizens. To address these expectations, the DT framework recommends the development and implementation of a comprehensive Smart Municipality plan which should address the provision of reliable infrastructure in the municipality, sustainable transport systems, and easy access to public services using ICT tools while ensuring constant citizen engagement.

The perceptions of respondents in the selected cases concerning smart technology are a technology-driven municipality, improvement of the functioning of the municipality, improvement of the municipality economy, promoting collaborative ecosystems, minimizing the municipality’s environmental impact, and maximizing citizens’ social wellbeing. Respondents also expect technology to introduce inequalities because of the digital divide. To address these, the DT framework suggests an integration of technology, such as IoT sensors, cloud computing solutions, data analytics platforms, and AI systems, into existing infrastructures, upgrading current infrastructure focusing on providing Internet access to citizens, implementing a smart infrastructure that improves citizens lives and allows for better decision-making, investing in technologies for better public safety as well as energy consumption, and advancing research and development within the municipality to identify innovative technological solutions. Operationalising these guidelines within the Chris Hani District Municipality, Dr AB Xuma Local Municipality, Enoch Mgijima Local Municipality, and Intsika Yethu Local Municipality will lead to their successful transformation into smart municipalities.

8. Discussion

The transformation of municipalities into smart entities requires a comprehensive and multi-faceted approach, focusing on integrating smart technology, governance, environment, and living. Based on the research by Axelsson and Granath [99] and insights drawn from a questionnaire, several strategies can be employed to navigate this complex planning process effectively.

Engaging with stakeholders in education about digital technologies is vital. This involves making them aware of the vision, goals, and benefits of digital transformation. Most of respondents (92%) believe a smart environment is key to promoting sustainability and better resource management within the municipality. To this end, municipalities must ensure robust digital infrastructure, such high-speed Internet and secure networks, facilitating not just physical but also digital sustainability. This involves integrating technology into environmental management, such as using sensors to monitor resource use or implementing digital platforms for waste management.

Municipalities can use the DT framework as a tool to evaluate which smart initiatives they should implement. Municipalities can use the framework to measure the level of technology integration within their smart initiatives. The DT framework can be extended with instruments that are unique to a municipality, such as those that the specific stakeholder groups require.

Digital tools provide opportunities for smart governance to enhance the citizen experience by allowing engagement, which leads to improved service delivery, and transparency about the implementation of decisions. Through smart living initiatives, residents can experience improved quality of life by using technology advancements in their homes, public transport, and improving their skills through online and digital learning environments and e-health services. The DT framework includes guidelines that encourage municipalities to adopt smart technology and innovative approaches that meet their citizens’ requirements.

However, if a municipality is in the process of becoming smart, it will require strategies and initiatives from governance, the environment, technology, and their views of how citizens should live. Therefore, this DT framework (Figure 4) provides municipalities with the foundation for monitoring a digital infrastructure for adopting smart initiatives, while creating resilient, sustainable, and liveable urban environments.

9. Conclusions

Smart governance should allow for open and transparent communication and allow stakeholder participation in decision-making, which will allow for improved quality of life, and robust, liveable, and sustainable cities. Municipalities achieve the benefits of smart governance by following the proposed guidelines in Section 7. The results indicated that 88% of respondents agreed that smart governance influences the provision of electricity and energy use in smart municipalities.

The use of data and technologies allows for environmental resource management in municipalities and is categorised as a smart environment initiative. The proposed guidelines to create a smart environment allow municipalities to consider what their impact is on the environment and what initiatives they can adopt to make improvements by getting citizens involved. Therefore, 92% of the respondents in this study agreed that smart environment influences sustainability and improves resource management in smart municipalities, and 86% said the influence is through being able to control pollution (e.g., through CO₂ and fossil fuel emissions).

Smart living refers to the use of technology and data-driven solutions to improve the quality of life for residents in urban areas. Smart living initiatives are intended to create a more sustainable, efficient, and liveable urban environment which delivers a better quality of life for its inhabitants. To achieve this, municipalities may implement these guidelines. Ninety percent of respondents agreed that smart living has an influence on the use of technology to enable citizens intelligent lifestyles and eighty-seven percent agreed that it could lead to influence on informed decisions, such as actions to use renewable and efficient energy sources in households.

Overall, smart technologies refer to the application of technology to enhance the overall efficiency, sustainability, and usability of public services by municipalities and local governments by implementing these guidelines. By taking these guidelines, municipalities can ensure that they can successfully implement smart technology solutions that will benefit both citizens and municipal staff alike. Therefore, the results confirmed that 88% of the respondents agreed that smart technology influences minimising the overall environmental impact of smart municipalities.

In conclusion, this study contributes theoretically to the field of smart cities and smart municipalities, with the first DT framework with formal guidelines for smart municipalities which was empirically confirmed for municipalities within developing countries being developed. The limitation of this study is that it was carried out in the Eastern Cape, one of the poorest provinces in South Africa. Future research will include municipalities from different provinces in South Africa. The study can also be repeated in similar developing countries and a comparison conducted with smart municipalities in developed countries. Digital innovation could be considered as a dimension to be added to future conceptual models and frameworks.