ORIGINAL RESEARCH

 

Citizen perceptions of digital transformation in local municipalities: The case of South Africa

 

 

Vusani Netshirando; Willard Munyoka; Armstrong Kadyamatimba

Department of Business Information Systems, Faculty of Management, Commerce and Law, University of Venda, Thohoyandou, Limpopo, South Africa

Correspondence

 

 

---

ABSTRACT

BACKGROUND: Local municipalities are vital in providing residents, businesses and other stakeholders services. Adopting disruptive digital technologies like predictive analytics, social media analytics, intelligent chatbots, the Internet of Everything and self-serving kiosks in local municipalities promises citizens better and more efficient service. These technologies have the potential to eliminate operational silos and bureaucracy, resulting in cost savings and offering 24/7 service accessibility. However, citizen perceptions of the digital transformation agenda influence disruptive technology adoption in South Africa and deserve further scrutiny
OBJECTIVES: The study examined the effect of facilitating conditions, effort expectancy, price value, perceived privacy, perceived risk, perceived trust and optimism bias on citizens' behavioural intention to adopt and use disruptive technologies in accessing local municipality services
METHOD: Underpinned by a quantitative research design and a deductive approach, data were collected from 288 citizens in local municipalities in South Africa to establish the model fit of the proposed model using structural equation modelling
RESULTS: Effort expectancy, facilitating conditions, price value, perceived privacy, perceived risk and perceived trust positively influenced citizens' intention to adopt e-government in local municipalities in South Africa. Meanwhile, optimism bias and intention to use positively influenced use behaviour in e-government. The structural equation model results confirmed the model's fit. All eight hypotheses were confirmed
CONCLUSION: The results of this research offer guidance to policymakers and implementers involved in digital transformation in local government on factors affecting citizens' intention to adopt e-government
CONTRIBUTION: The study significantly contributes to digital transformation discourse in local government

Keywords: local government; disruptive technologies; citizen perceptions; e-government; digital transformation; South Africa.

---

 

 

Introduction

Worldwide, local governments are embracing digital transformation in response to calls for better and more efficient 24/7 public service provision (Scupola & Mergel 2022; Ahn & Chen, 2022). Moreover, the widespread adoption of emerging technologies across societies provides fertile ground for local governments to offer online services (Van Veldhoven & Vanthienen 2022). Terán (2018) defines emerging technologies in three characteristics: creating new industries or transforming the existing ones, creating new investment opportunities and changing the world by offering new benefits and improving people's standard of living. Transforming society is one of the mandated outcomes in democratic states, and digital transformation can be used as a catalyst for achieving this agenda (Sanina, Balashov & Rubtcova 2023). Thus, in this study, the three elements of emerging technologies are combined to create a contextual definition of emerging technologies. Therefore, emerging technologies define digital innovation as enabling societal and organisational transformation. The potential of emerging technologies to transform various spheres of society, such as political and economic, is well-documented by multiple scholars (Castro & Lopes 2022; Lindgren et al. 2019; Van Veldhoven & Vanthienen 2022). Therefore, with governments in developing nations like South Africa undergoing digital government to enhance service delivery, it is essential to investigate citizens' perceptions towards digital transformation. In this study, the terms digital government and e-government are interchangeably used to cover the broad concept of digital transformation in local government.

Success stories in the private sector on adopting and using emerging technologies trigger the government to adopt intelligent government (Androutsopoulou et al. 2019). Mergela, Edelmann and Haug (2019) suggest that citizens already adopting online services offered by private companies have the exact expectations of efficient service delivery when interacting with government systems. Moreover, the rise of digital platform adoption by citizens is one of the major government drivers towards digital transformation (Sanina et al. 2023). However, for most developing nations, there is a gap between citizens' expectations and the actual services rendered to them (Alkraiji & Ameen 2022). To narrow this service expectation gap, some scholars call for digital transformation in all spheres of service provision to all stakeholders (Alkraiji & Ameen 2022; Sanina et al. 2023). The adoption of emerging technologies in governments is in different stages across the globe (Gökalp & Martinez 2022), and this varies according to how they respond to technological advancement. According to Gökalp and Martinez (2022), this could be attributed to governments' efforts and resource allocation towards digital transformation.

Most studies on digital transformation in local government focus on how digital innovations bring efficiencies in internal processes and intergovernmental communication (Adam & Fazekas 2018; Sanina et al. 2023). Similarly, Valle-Cruz (2019) suggests that it is easier for local governments to adopt emerging technologies in the public service delivery system because they are funded from the central treasury. However, on the citizen side, adopting emerging technologies among citizens in developing countries is mainly for personal and essential use and social purposes (Hooks et al. 2022). The adoption rate of emerging technologies among citizens in South Africa is sluggish and suboptimal when performing transactions and higher-order tasks like generating and manipulating online content (Ramirez-Madrid et al. 2024). Thus, more studies are needed to establish citizens' intentions to adopt e-government systems at the local municipality level in South Africa (Abdurahman & Kabanda 2024; Galushi & Malatji 2022).

This study investigates citizens' perceptions of adopting and using specific advanced technologies, such as social media, intelligent chatbots and self-serving kiosks in rural local municipalities. The focus is on understanding citizens' perceptions of the potential impact of these technologies on public service delivery and the factors affecting their adoption of such technologies. Thus, this study seeks to answer the following research questions:

• What are the perceptions of citizens towards digital transformation in local governments?

• Which factors influence citizens' behavioural intentions towards adopting disruptive technologies to access local government services?

• What can governments do to ensure citizens' active participation in digital transformation initiatives and the adoption of disruptive technologies?

The findings of this study will inform policymakers, practitioners, decision-makers and other vital stakeholders seeking better and more efficient citizen-centric local government service provision through digital transformation.

This article is structured as follows: it begins with a discussion of the literature review and theoretical underpinnings, followed by a conceptual framework and hypotheses. The research methodology follows, leading to the findings, discussions and conclusions.

Digital transformation in local governments

The purpose of local government is to provide administrative duties, supply goods and services to various stakeholders sustainably and safely, and represent and engage citizens in democratic and governance issues affecting their daily lives (Masuda et al. 2022). In today's digital tech-driven world, local governments recognise the urgency of digital transformation to boost operational efficiencies and achieve the set goals (Kuhlmann & Heuberger 2023). Thus, local government digital transformation involves using disruptive technologies smartly to serve residents and various community stakeholders in the best and most sustainable ways possible (Pittaway & Montazemi 2020). Similarly, digital transformation in local government yields efficiencies and effectiveness in public service provision in line with the United Nations' sustainable development goals on social, economic and environmental considerations (Palos-Sánchez et al. 2023). To create a more responsive and citizen-centric digital government, local municipalities should focus on the four driving forces of changing citizen expectations, accelerating technological innovations and having the correct regulatory requirements, cost efficiencies and resource optimisation measures (Tangi et al. 2021).

Citizens have experiences of seamless connection, interaction and transactions with systems from various sectors, such as the banking sector and online shopping apps (Chang & Li 2022). Thus, when citizens hear the discourse of digital transformation in local government, they have similar efficient and seamless service expectations. Local government, therefore, has the mandate to change citizen expectations by providing top-notch digital services that align with citizens' expectations and needs (Chang & Li 2022; David et al. 2023).

Disruptive technologies are at the heart of accelerating technological innovations and digital transformation in local government (Madan & Ashok 2023). Innovative technologies like intelligent chatbots, predictive analytics, smart cities, social media analytics, the Internet of Everything (IoE), queuing management systems and self-serving kiosks have more significant potential to revolutionise public service systems in developing countries (Yigitcanlar, Agdas & Degirmenci 2023). Several scholars suggest that these smart technologies offer the most significant potential to overcome the bureaucracy and operational silos that mar the public service system in most emerging economies (Lekkas & Souitaris 2023; Vogl et al. 2020). Furthermore, by embracing these technologies, local governments become agile and efficient in their internal processes and responding to local communities' needs.

To effectively adopt disruptive technologies in local government, the right regulatory environment and various policies are indefensible (Brunetti et al. 2020). For instance, local governments should adhere to policies on data protection, accessibility and securing transactions to ensure that personal data and sensitive customer information are secure from cyberattacks. These policies should be updated frequently to reflect and align with emerging technologies (ElMassah & Mohieldin 2020). However, for most developing nations, information and communication technology (ICT) policies are often outdated and fail to address trending innovations and meet citizens' public service needs (Wilson & Mergel 2022). Thus, to gain citizens' trust, local governments should adhere to regulatory frameworks and adopt a citizen-centric approach in all digital transformation initiatives.

One of the primary goals for digital transformation in local government is resource optimisation and cost efficiency of operations. Leveraging disruptive technologies in all local government operations and public services through data-driven decision-making yields economies of scale and curbs rampant operational expenses (Deganis et al. 2021). For example, adopting cloud-based solutions such as Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) will significantly reduce ICT acquisition costs, promote open data access and increase the scalability of local government operations (Golightly et al. 2022). Several scholars suggest that a significant sector of society perceives the local government service system as inefficient and sometimes marred by corrupt deals in areas like tendering (ElMassah & Mohieldin 2020; Sadik-Zada, Gatto & Niftiyev 2022). Thus, by adopting disruptive technologies for sustainability, local governments can maximise their impact on society through cost-effective, efficient operations and high-quality service provision.

The relentless economic lockdowns during the coronavirus disease 2019 (COVID-19) pandemic resulted in digital transformation towards smart governance across many countries worldwide (Hujran et al. 2023). While most developed nations like the United Kingdom, Australia, the United States and Canada quickly adjusted to online services because of their well-established e-government systems, most developing nations struggled (Dammak, Mbarek & Moalla 2023). Thus, it took some time for most government entities in Southern Africa to offer public services fully online because of resource constraints (Dammak et al. 2023). Worse still, citizens' acceptance and adoption of e-government services remained suboptimal because of various factors like the lack of the right skills to use such systems and the exorbitant cost of the Internet needed to access e-government (Munyoka 2020). The momentum in online presence and public service provision gained during COVID-19 continues to expand across various government entities in South Africa (Abdurahman & Kabanda 2024). For instance, the South African Department of Home Affairs Biometric Identification System is one success story now integrated with various systems in the banking sector, police, and correctional services for citizen fingerprint verification. Similarly, the Gauteng Department of Education's (GDE) Admissions Online System for enrolment of Grades 1 and 8 school-going children across the Gauteng province in South Africa is another digital transformation success story in local government (Parker, Hamann & De Kadt 2021). The GDE systems allocate school places to children based on the proximity of the applicant's residence to the school to minimise traffic congestion in the central business district because of parents dropping their children across the city. Thus, in all these success stories, local government and system designers put much effort into engaging, orienting and buying into citizens' input, suggestions and participation (Biljohn & Lues 2020). Moreover, citizens tended to adopt the GDE system because it is the only way to apply for a school place (Parker et al. 2021). In contrast, in cases like payment of municipality bills and application and renewal of driver's licence where online access to local government is optional, most citizens preferred the 'over-the-counter' services for various reasons. Some citizens cited the lack of skills to use such systems, the exorbitant cost of Internet data bundles required to access online services, and the lack of human-to-human touch of service provision in e-government systems (Abdurahman & Kabanda 2024).

The next section analyses the various theories that underpin this study.

Theoretical underpinnings

The complexity of digital transformation in local government and citizens' subsequent adoption of online services requires a multiple theoretical understanding to study and fully understand the phenomena. Thus, this study draws from the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2), technology-organisation-environment (TOE) framework, the National Institute of Standards and Technology (NIST) Cybersecurity Framework and the affective decision-making theory (ADM) of optimism bias and risk.

The extended unified theory of acceptance and use of technology

The UTAUT2 model posits that an individual's decision to adopt and continuously use technological innovation is influenced by seven determinant variables: performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value and habits (Venkatesh, Thong & Xu 2012). These seven factors are moderated by an individual's age, gender and experience in system use. This study draws the facilitating conditions, effort expectancy, price value, intention to adopt and the use behaviour constructs from the UTAUT2 model.

The National Institute of Standards and Technology Cybersecurity Framework

The NIST Cybersecurity Framework is an all-inclusive set of guiding principles for organisations to identify, protect, detect, respond to and overcome cyberattacks (Hossain et al. 2024). The plausible aspect of the NIST framework is that it can be used by organisations of any size, with or without any cybersecurity plans, to guide and strengthen their cybersecurity controls and resilience. This framework provides the perceived privacy and perceived trust constructs to this study.

The affective decision-making theory

The ADM is a strategic model of choices people must undertake in risky circumstances (Bracha & Brown 2012). The ADM theory states that an individual's decision to use a particular service is based on the interaction between rational and emotional cognitive processes. This interaction results in optimism bias, that is, the conviction that having used a particular system before reduces a user's susceptibility to hazards compared to an ordinary user (Lei, Hu & Hsu 2023). In risky situations, rational thinking guides behaviour, while emotions shape risk perception, leading to an optimistic bias in individuals. Thus, the ADM model provides the perceived risk and the optimism bias construct variables to inform the conceptual model (see Figure 1).

 

 

Technology-organisation-environment framework

The TOE framework attests that digital transformation in an organisation is influenced by technological, organisational and environmental contexts (Baker 2012). The technological context focusses on internal and external innovations like disruptive technologies that local governments can adopt to enhance public service provision. Organisational context is concerned with various internal measures, features and resources at the disposal of an organisation required for digital transformation. The environmental context focusses on an organisation's ability to attract and utilise resources, competitiveness, and legal and regulatory matters that affect its competitiveness. Various scholars have established some driving factors related to the technological, organisational and environmental elements influencing digital transformation in local municipalities (Clement, Manjon & Crutzen 2022; Gasco-Hernandez et al. 2022). Thus, the TOE framework provides a rich grounding for understanding the interplay of various factors affecting the adoption of disruptive technologies in local municipalities.

Research model and hypotheses

Figure 1 displays the proposed research model for this study, including seven construct variables influencing citizens' behavioural intentions to adopt technological innovations in local municipalities. These are facilitating conditions, effort expectancy, price value, perceived privacy, perceived risk, perceived trust and optimism bias, which influence behavioural intention to adopt and use disruptive technologies in accessing local municipality services.

According to the model suggested in Figure 1, this study is based on the following hypotheses:

H1: Facilitating condition (FC) positively influences citizens' intentions to adopt e-government (ITAEG).

H2: Effort expectancy (EE) positively influences citizens' intentions to adopt e-government (ITAEG).

H3: Price value (PV) positively influences citizens' intentions to adopt e-government (ITAEG).

H4: Perceived privacy (PP) positively influences citizens' intentions to adopt e-government (ITAEG).

H5: Perceived risk (PR) positively influences citizens' intentions to adopt e-government (ITAEG).

H6: Perceived trust (PT) positively influences citizens' intentions to adopt e-government (ITAEG).

H7: Optimism bias (OB) positively influences citizens' continuous use behaviour on e-government (UBOEG)

H8: Citizens' behavioural intention to adopt e-government leads to continuous use behaviour (UBDT).

 

Research methods and design

This study is underpinned by a quantitative research design and a deductive approach (Bloomfield & Fisher 2019). This study's use of a quantitative research design and a deductive approach aligns with previous research on digital transformation in local municipalities (Batara et al. 2017; Dias 2020). Using self-administered structured questionnaires, quantitative data were collected from 300 respondents from the Mpumalanga province (Ehlanzeni District) and 2 in Limpopo province (Capricorn and Vhembe Districts). Purposive sampling was then used to select five local municipalities from these districts, that is, two under Ehlanzeni District (Bushbuckridge and City of Mbombela), one from Capricorn District (Lepelle Nkumpi) and two from the Vhembe District (Thulamela and Makhado). These districts were selected because they have contrasting economic developments, rural versus urban setups, have an online presence and adopt disruptive technologies at various stages (Abdurahman & Kabanda 2024). The 300 participants were identified using multistage sampling techniques. Firstly, the purposive sampling technique was used to select the districts and local municipalities. Secondly, a combination of purposive sampling and random sampling techniques was used to identify the final participants for this study based on the individual's previous experience in accessing local municipality services online. The target participants for this study comprised community members from these five municipalities aged 18 years and above who access local government services. A self-administered questionnaire was distributed to 300 participants. These are active people who, by default, are entitled to services from their local government of any form.

The questionnaire included two parts. Section A focussed on demographic questions, and Section B contained five items on a 5-point Likert scale (from completely disagreeing to agreeing) designed to assess the nine elements of the research model presented in Figure 1. The questionnaire was adapted from the United Nations E-Government Survey Databases' (United Nations 2024) set of questions to align with the proposed model in Figure 1. The questionnaire was tested with 20 participants with previous experience using e-government platforms. The final research instrument incorporated feedback from the pilot test.

The data collection was conducted over 10 weeks, involving the five local municipalities. The proposed model was validated using structural equation modelling (SEM) with IBM SPSS AMOS version 29. The SEM enabled a thorough examination of hypotheses by utilising confirmatory factor analysis (CFA) to determine the significance of the relationships between observed and latent variables in the proposed e-government utilisation model, as discussed in the next section.

Ethical considerations

An application for full ethical approval was made to the Research Ethics Social Sciences Committee (RESSC) of the University of Venda. Ethical consent was received with the ethics approval number FMCL/21/BIS/03/1309.

 

Results

Data cleaning procedures

Following Osborne's (2012) recommendation, the data were carefully examined to detect missing data, address common method bias, and identify and remove any outliers or deviations from univariate normality that may affect the results.

Handling missing data

This step focussed on scrutinising the completed questionnaires for item non-response and erroneous completion by the participants. Out of the 300 collected questionnaires, 288 were used for data analysis. The remaining 12 were incomplete or erroneously completed and excluded from the analysis. This gave an overall response rate of 96%, which is adequate for quantitative data analysis and aligns with Bougie and Sekaran's (2019) 30% minimum response rate recommendation.

Handling common method bias

Common method bias occurs when a survey leads to inconsistent responses because of its design and wording rather than reflecting the true opinions of the participants (Podsakoff, MacKenzie & Podsakoff 2012). The same questionnaire measured the independent and dependent variables, which might have introduced common method bias. Harman's one-factor test was employed to identify common method variance before conducting exploratory factor analysis, while CFA was utilised for common method variance detection. In Harman's single-factor test, it is suggested that the eigenvalue of the first major component should be below 50% to show no common method bias (Podsakoff et al. 2012). The initial primary element was isolated, explaining only 15.23% of the variability. This shows that the unextracted variance accounts for numerous factors, thus the absence of common method bias.

Dealing with univariate normality

Before statistical analysis, data should be tested for normality and homogeneity to confirm the data distribution of the variables (Knief & Forstmeier 2021). Pearson's initial parameter test for skewness was utilised to determine the normality of the univariate distribution (Cain, Zhang & Yuan 2017). Knief and Forstmeier (2021) suggest that skewness and kurtosis should be used to test univariate normality for a sample size above 300. Thus, it is ideal for this study. Kurtosis measures how much a distribution differs in terms of its peakedness or flatness compared to the normal distribution (Cain et al. 2017). Meanwhile, skewness measures how much a statistical distribution deviates from symmetry around the mean (Cain et al. 2017). A perfectly symmetrical graph has kurtosis and skewness values of zero for a histogram that follows a normal distribution (Cain et al. 2017). The skewness values for this study range from -1.1250 to 1.0250, while the kurtosis value varies from -0.1310 to 1.0241. Hence, the kurtosis and skewness values for all constructs in this research fell within acceptable ranges (Kim 2013).

Descriptive analysis

Most of the 288 respondents were females (54.5%). The 26-35 age group was the dominant range, while those aged above 56 years constituted the least (1%). Moreover, 95.5% of the participants said they access the Internet daily, mostly on their mobile phones or from the workplace. The respondents, aged between 25 and 36 years, were the largest group (44.44%) utilising the Internet, followed by the 18-25 years (38.99%). Moreover, 33.3% of participants aged between 26 and 35 years confirmed using online platforms to access various public and private services. Most interestingly, participants above 55 years indicated they are good mobile platform users. Most participants (39.6%) held a university degree, 25.0% had a postgraduate qualification, 14.2% possessed a college diploma, and the rest had either a grade 12 certificate or no formal qualifications.

Measurement model analysis

This study utilised CFA to establish the measurement model and assess how well it aligns with the collected data. Standardised factor loadings, construct reliability and average variance factor were used to evaluate convergent validity (Mardia, Kent & Taylor 2024). Table 1 shows the construct reliability tests for the study. Standardised loadings indicate the degree of connection between items on a scale and a latent variable, with only values higher than 0.50 included in Table 1 (Hair et al. 2014). Construct reliability was conducted to guarantee that the latent variables within each construct demonstrated internal consistency.

 

 

Table 1 displays each construct's reliability coefficients, ranging from 0.708 to 0.885. This indicates that the constructs demonstrated internal consistency as all coefficients exceeded the commonly accepted threshold of 0.70.

The average variance extracted (AVE) was utilised to confirm the convergent validity of the constructs. Table 1 shows that all AVE values scored above the 0.50 rule of thumb (Mardia et al. 2024). This confirms that the proposed model's constructs accounted for over half of the variances in the construct items.

In this study, discriminant validity was conducted to confirm that each construct in the study instrument was distinct from the other constructs and represented the specific phenomena being studied in the structural equation model (Mardia et al. 2024). To assess discriminant validity, this study compares the 'absolute values of correlations between the constructs' with each construct's square root of the AVE (Hair et al. 2014). The criterion is that the square root of the AVE for that construct should always exceed both the AVE and all correlations with other constructs (Rönkkö & Cho 2022). Table 2 shows that the square roots (shaded areas) exceeded the correlations of all other constructs, and this demonstrates satisfactory discriminant and convergent validity for the construct measurements in the survey.

Structural model analysis

This section evaluates the model's overall fit using different fit indices. The Chi-square (χ²) had a total value of 482.95 with 227 degrees of freedom and p < 0.05. The Chi-square over degrees of freedom for the research model was 1.53. Thus, within the 1 and 3 acceptable range (Kenny, Kaniskan & McCoach 2015). This study utilised various indices to assess the overall model fit. The normed-fit index value obtained (NFI) was 0.983, while the comparative fit index (CFI) was 0.904, and the goodness-of-fit index (GFI) equalled 0.942. All three (NFI, CFI and GFI) exceeded the minimum acceptable range of 0.90 (Kline 2023). The Tucker-Lewis index (TLI) obtained was 0.985, while the index of fit (IFI) was 0.972, which is all greater than the 0.95 rule of thumb (Kline 2023). To show excellent model fit, the root mean square error of approximation (RMSEA) value should be lower than 0.08; for this study, RMSEA equalled 0.04. The adjusted goodness-of-fit index (AGFI) value was 0.890, thus above the 0.80 recommendation (Henseler, Ringle & Sarstedt 2015).

Model path coefficients and hypotheses testing

This section evaluates the construct variables' path coefficients to test each proposed hypothesis's significance. A path coefficient is considered significant (at p < 0.05 level) if its critical t-value for a standardised regression weight exceeds 1.96 (Mardia et al. 2024). Table 3 shows that the t-values for all eight hypotheses were above 1.96, with significant values less than 0.05. Based on this criterion, all eight hypotheses were accepted (see Table 3).

Figure 2 illustrates that citizens' utilisation patterns of e-government systems accounted for 86% of the variances among the eight endogenous constructs. This demonstrates that the suggested model effectively predicts the usage behaviour of e-government systems in South African local municipalities.

 

 

Discussion

This research sought to understand digital transformation in local government by examining the impact of facilitating conditions, effort expectancy, price value, perceived privacy, perceived risk, perceived trust and optimism bias on the intention to adopt and use e-government systems by citizens in South Africa. This study proposed eight hypotheses to test the proposed model to reach this goal.

This study found that local governments should facilitate the adoption of digital technologies to access government services online if they create an awareness among citizens of the benefits and capabilities of such services. Digital skills and competence are the key components of digital transformation in local government. Moreover, the findings show that governments should implement various schemes to orient and assist local citizens in effectively using disruptive technologies like social media analytics, mobile platforms, intelligent chatbots and self-serving kiosks; they will most likely not develop some adoption resentments. Such initiatives are bound to reduce citizens' time and effort to learn to use e-government systems. In turn, this goes a long way towards enticing citizens to accept and adopt any digital transformation initiatives in local municipalities by citizens. This finding concurs with previous studies on digital transformation and e-government (Al Sayegh et al. 2023; Venkatesh et al. 2012), which established facilitating conditions and effort expectancy as strong predictors of behavioural intention.

This research found that the costs associated with mobile data and Internet access can impact citizens' decisions to utilise e-governance in South Africa. Local governments in the Limpopo and Mpumalanga provinces serve customers from rural, farming, peri-urban and urban areas. Government intervention is necessary to regulate Internet prices and ensure affordability for all citizens because of large differences in disposable incomes among people in different areas. This finding concurs with scholars (Chohan & Hu 2022; Kouladoum, Wirajing & Nchofoung 2022) who suggest governments in emerging markets and developing countries in sub-Saharan Africa should develop various programmes and initiatives aimed at the digital and financial inclusion of all citizens.

The findings of this study establish that citizens tend to adopt e-government systems that they trust, perceive as secure, and guarantee the privacy of personal data. With citizens' growing adoption of local e-government systems, governments should hire experienced cybersecurity specialists to deal with and handle cyber vulnerabilities (Hossain et al. 2024). This finding aligns with previous scholars who suggested that citizens tend to transact on e-government systems with a track record of robust security features (Kassen 2022). Thus, governments should invest more in addressing cybersecurity vulnerabilities in e-government.

Optimism bias positively impacted the behaviour of users in a significant way. Although individuals had concerns about privacy, trust and risks with e-government usage, those who felt more tech-savvy with electronic systems were more inclined to use them. The findings of this research align with the practical findings of a study conducted by Weerakkody et al. (2015). One possible reason for this finding could be that as individuals become skilled and comfortable utilising e-government platforms, they no longer see themselves as vulnerable to cybersecurity risks.

The findings of this study establish that a person's intention to adopt local e-government is influenced by their perception of trust, privacy and risk, as well as the effort needed to learn to use the system. Similarly, the government should assist citizens in easing e-government adoption by ensuring they have the necessary skills and resources to adopt. In turn, a positive intention leads to system acceptance and widespread utilisation. This finding concurs with previous studies, which establish behavioural intention as a strong positive predictor of use behaviour in digital government (Faulkner, Jorgensen & Koufariotis 2019; Zahid et al. 2022).

Theoretical and practical implications

This study has implications for both theory and practice. This research adds to the current body of knowledge by explaining the impact of facilitating conditions, effort expectancy, price value, perceived privacy, perceived risk, perceived trust and optimism bias on citizens' decisions to utilise e-government systems. Optimism bias motivates citizens to continue utilising e-government systems even when they see potential risks. The study has added to the understanding of theory development by suggesting a framework for guiding e-government uptake in South African local government. Furthermore, the suggested model could serve as a launching pad for future research efforts and be combined with other established models to deepen the discourse of digital transformation in local governments.

On the practice frontier, this study underscores that citizens' decisions to adopt digital transformation are influenced by their perceptions and lived experiences of security and trust in e-government. Optimism bias is most effective when citizens are tech-savvy, trust the government, and believe in the security and privacy of e-government systems. Thus, the design and implementation of e-government systems should involve equal input from citizens and governments, emphasising people-driven initiatives.

 

Conclusion

This study explored how facilitating conditions, effort expectancy, price value, perceived privacy, perceived risk, perceived trust and optimism bias influence citizens' decisions to adopt e-government systems. In the current fast-paced, tech-driven era, digital transformation allows local governments to transform the public sector landscape by ushering in responsive, agile and citizen-centric governance. This is achieved by continuously aligning government strategic goals and disruptive technologies with citizens' expectations and priorities. Survey data were collected from 288 local government customers in two provinces in South Africa to test and refine the proposed model, which integrated the seven latent variables. This study found that digital transformation provides citizens many public service delivery benefits: improved 24/7 public services, data-driven decision-making, enhanced productivity and efficiency, cost savings, and bolstering transparency and accountability. However, because of wide socioeconomic disparities across the urban, peri-urban and rural local municipalities, local governments should pay special attention to these factors if the digital transformation agenda is to succeed. Most customers for rural local municipalities are low- to middle-income members of society who are often financially and technologically constrained. Thus, for digital inclusion through local government digital transformation, governments should pay attention to digitally upskilling local citizens through various training and system orientation. To promote the widespread adoption of e-government by citizens, the government should regulate the cost of Internet access and reduce the uncertainty associated with cybersecurity vulnerabilities. The results of this research can assist policymakers and practitioners in developing digital transformation solutions that focus on the needs of citizens. The research is restricted as it did not investigate the opinions of local government workers on incorporating new technologies in service provision to enhance community services. This forms the future research direction.

 

Acknowledgements

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Authors' contributions

V.N. conducted the conceptualisation, investigation, data collection and wrote the original article. W.M. supervised the project, reviewed the original article, implemented major revisions, assisted with data analysis and wrote the article based on reviewers' comments. A.K. also supervised the project, rendered validation, and assisted with writing, reviewing and editing.

Funding information

This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Data availability

The data that support the findings of this study are available upon reasonable request from the corresponding author, W.M.

Disclaimer

The views and opinions expressed in this article are those of the authors and are the product of professional research. It does not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this article's results, findings and content.

 

References

Abdurahman, S. & Kabanda, S., 2024, 'Factors influencing the design and implementation of accessible e-government services in South Africa', The Electronic Journal of Information Systems in Developing Countries 90(3), e12317. https://doi.org/10.1002/isd2.12317        [ Links ]

Adam, I. & Fazekas, M., 2018, 'Are emerging technologies helping win the fight against corruption in developing countries?', Pathways for Prosperity Commission Background Paper Series 21, 2-28.         [ Links ]

Ahn, M.J. & Chen, Y.C., 2022, 'Digital transformation toward AI-augmented public administration: The perception of government employees and the willingness to use AI in government', Government Information Quarterly 39(2), 101664. https://doi.org/10.1016/j.giq.2021.101664        [ Links ]

Al Sayegh, A.J., Ahmad, S.Z., AlFaqeeh, K.M. & Singh, S.K., 2023, 'Factors affecting e-government adoption in the UAE public sector organisations: The knowledge management perspective', Journal of Knowledge Management 27(3), 717-737. https://doi.org/10.1108/JKM-09-2021-0681        [ Links ]

Alkraiji, A. & Ameen, N., 2022, 'The impact of service quality, trust and satisfaction on young citizen loyalty towards government e-services', Information Technology & People 35(4), 1239-1270. https://doi.org/10.1108/ITP-04-2020-0229        [ Links ]

Androutsopoulou, A., Karacapilidis, N., Loukis, E. & Charalabidis, Y., 2019, 'Transforming the communication between citizens and government through AI-guided chatbots', Government Information Quarterly 36(2), 358-367. https://doi.org/10.1016/j.giq.2018.10.001        [ Links ]

Baker, J., 2012, 'The technology-organization-environment framework', Information Systems Theory: Explaining and Predicting Our Digital Society 1, 231-245. https://doi.org/10.1007/978-1-4419-6108-2_12        [ Links ]

Batara, E., Nurmandi, A., Warsito, T. & Pribadi, U., 2017, 'Are government employees adopting local e-government transformation? The need for having the right attitude, facilitating conditions and performance expectations', Transforming Government: People, Process and Policy 11(4), 612-638. https://doi.org/10.1108/TG-09-2017-0056        [ Links ]

Biljohn, M.I.M. & Lues, L., 2020, 'Citizen participation, social innovation, and the governance of local government service delivery: Findings from South Africa', International Journal of Public Administration 43(3), 229-241. https://doi.org/10.1080/01900692.2019.1628052        [ Links ]

Bloomfield, J. & Fisher, M.J., 2019, 'Quantitative research design', Journal of the Australasian Rehabilitation Nurses Association 22(2), 27-30. https://doi.org/10.33235/jarna.22.2.27-30        [ Links ]

Bougie, R. & Sekaran, U., 2019, Research methods for business: A skill building approach, John Wiley & Sons, New Jersey.

Bracha, A. & Brown, D.J., 2012, 'Affective decision making: A theory of optimism bias', Games and Economic Behavior 75(1), 67-80. https://doi.org/10.1016/j.geb.2011.11.004        [ Links ]

Brunetti, F., Matt, D.T., Bonfanti, A., De Longhi, A., Pedrini, G. & Orzes, G., 2020, 'Digital transformation challenges: Strategies emerging from a multi-stakeholder approach', The TQM Journal 32(4), 697-724. https://doi.org/10.1108/TQM-12-2019-0309        [ Links ]

Cain, M.K., Zhang, Z. & Yuan, K.H., 2017, 'Univariate and multivariate skewness and kurtosis for measuring nonnormality: Prevalence, influence and estimation', Behavior Research Methods 49, 1716-1735. https://doi.org/10.3758/s13428-016-0814-1        [ Links ]

Castro, C. & Lopes, C., 2022, 'Digital government and sustainable development', Journal of the Knowledge Economy 13(2), 880-903. https://doi.org/10.1007/s13132-021-00749-2        [ Links ]

Chang, Y.P. & Li, J., 2022, 'Seamless experience in the context of omnichannel shopping: Scale development and empirical validation', Journal of Retailing and Consumer Services 64, 102800. https://doi.org/10.1016/j.jretconser.2021.102800        [ Links ]

Chohan, S.R. & Hu, G., 2022, 'Strengthening digital inclusion through e-government: Cohesive ICT training programs to intensify digital competency', Information Technology for Development 28(1), 16-38. https://doi.org/10.1080/02681102.2020.1841713        [ Links ]

Clement, J., Manjon, M. & Crutzen, N., 2022, 'Factors for collaboration amongst smart city stakeholders: A local government perspective', Government Information Quarterly 39(4), 101746. https://doi.org/10.1016/j.giq.2022.101746        [ Links ]

Dammak, S., Mbarek, S. & Moalla, M., 2023, 'E-government, political system and COVID-19 in Africa: Lessons for future disruptive shocks', Transforming Government: People, Process and Policy 17(3), 288-302. https://doi.org/10.1108/TG-07-2022-0100        [ Links ]

David, A., Yigitcanlar, T., Li, R.Y.M., Corchado, J.M., Cheong, P.H., Mossberger, K. et al., 2023, 'Understanding local government digital technology adoption strategies: A PRISMA review', Sustainability 15(12), 9645. https://doi.org/10.3390/su15129645        [ Links ]

Deganis, I., Haghian, P.Z., Tagashira, M. & Alberti, A., 2021, Leveraging digital technologies for social inclusion, United Nations Department of Economic and Social Affairs, viewed 17 July 2024, from https://www.un.org/development/desa/dpad/wp-content/uploads/sites/45/publication/PB_92.pdf.

Dias, G.P., 2020, 'Determinants of e-government implementation at the local level: An empirical model', Online Information Review 44(7), 1307-1326. https://doi.org/10.1108/OIR-04-2020-0148        [ Links ]

ElMassah, S. & Mohieldin, M., 2020, 'Digital transformation and localizing the sustainable development goals (SDGs)', Ecological Economics 169, 106490. https://doi.org/10.1016/j.ecolecon.2019.106490        [ Links ]

Faulkner, N., Jorgensen, B. & Koufariotis, G., 2019, 'Can behavioural interventions increase citizens' use of e-government? Evidence from a quasi-experimental trial', Government Information Quarterly 36(1), 61-68. https://doi.org/10.1016/j.giq.2018.10.009        [ Links ]

Galushi, L.T. & Malatji, T.L., 2022, 'Digital public administration and inclusive governance at the South African Local Government, in depth analysis of e-government and service delivery in Musina Local Municipality', Academic Journal of Interdisciplinary Studies 11(6), 116-126. https://doi.org/10.36941/ajis-2022-0154        [ Links ]

Gasco-Hernandez, M., Nasi, G., Cucciniello, M. & Hiedemann, A.M., 2022, 'The role of organizational capacity to foster digital transformation in local governments: The case of three European smart cities', Urban Governance 2(2), 236-246. https://doi.org/10.1016/j.ugj.2022.09.005        [ Links ]

Gökalp, E. & Martinez, V., 2022, 'Digital transformation maturity assessment: Development of the digital transformation capability maturity model', International Journal of Production Research 60(20), 6282-6302. https://doi.org/10.1080/00207543.2021.1991020        [ Links ]

Golightly, L., Chang, V., Xu, Q.A., Gao, X. & Liu, B.S., 2022, 'Adoption of cloud computing as innovation in the organization', International Journal of Engineering Business Management 14, 18479790221093992. https://doi.org/10.1177/18479790221093992        [ Links ]

Hair, J.F., Black, W.C., Babin, B.J. & Anderson, R.E., 2014, Multivariate data analysis, 7th edn., Pearson Publishers, Harlow.

Henseler, J., Ringle, C.M. & Sarstedt, M., 2015, 'A new criterion for assessing discriminant validity in variance-based structural equation modeling', Journal of the Academy of Marketing Science 43, 115-135. https://doi.org/10.1007/s11747-014-0403-8        [ Links ]

Hooks, D., Davis, Z., Agrawal, V. & Li, Z., 2022, 'Exploring factors influencing technology adoption rate at the macro level: A predictive model', Technology in Society 68, 101826. https://doi.org/10.1016/j.techsoc.2021.101826        [ Links ]

Hossain, S.T., Yigitcanlar, T., Nguyen, K. & Xu, Y., 2024, 'Local government cybersecurity landscape: A systematic review and conceptual framework', Applied Sciences 14(13), 5501. https://doi.org/10.3390/app14135501        [ Links ]

Hujran, O., Alarabiat, A., Al-Adwan, A.S. & Al-Debei, M., 2023, 'Digitally transforming electronic governments into smart governments: SMARTGOV, an extended maturity model', Information Development 39(4), 811-834. https://doi.org/10.1177/02666669211054188        [ Links ]

Kassen, M., 2022, 'Blockchain and e-government innovation: Automation of public information processes', Information Systems 103, 101862. https://doi.org/10.1016/j.is.2021.101862        [ Links ]

Kenny, D.A., Kaniskan, B. & McCoach, D.B., 2015, 'The performance of RMSEA in models with small degrees of freedom', Sociological Methods & Research 44(3), 486-507. https://doi.org/10.1177/0049124114543236        [ Links ]

Kim, H.Y., 2013, 'Statistical notes for clinical researchers: Assessing normal distribution (2) using skewness and kurtosis', Restorative Dentistry & Endodontics 38(1), 52-54. https://doi.org/10.5395/rde.2013.38.1.52        [ Links ]

Kline, R.B., 2023, Principles and practice of structural equation modeling, Guilford Publications, New York.

Knief, U. & Forstmeier, W., 2021, 'Violating the normality assumption may be the lesser of two evils', Behavior Research Methods 53(6), 2576-2590. https://doi.org/10.3758/s13428-021-01587-5        [ Links ]

Kouladoum, J.C., Wirajing, M.A.K. & Nchofoung, T.N., 2022, 'Digital technologies and financial inclusion in sub-Saharan Africa', Telecommunications Policy 46(9), 102387. https://doi.org/10.1016/j.telpol.2022.102387        [ Links ]

Kuhlmann, S. & Heuberger, M., 2023, 'Digital transformation going local: Implementation, impacts and constraints from a German perspective', Public Money & Management 43(2), 147-155. https://doi.org/10.1080/09540962.2021.1939584        [ Links ]

Lei, W., Hu, S. & Hsu, C., 2023, 'Unveiling the process of phishing precautions taking: The moderating role of optimism bias', Computers & Security 129, 103249. https://doi.org/10.1016/j.cose.2023.103249        [ Links ]

Lekkas, C.K. & Souitaris, V., 2023, 'Bureaucracy meets digital reality: The unfolding of urban platforms in European municipal governments', Organization Studies 44(10), 1649-1678. https://doi.org/10.1177/01708406221130857        [ Links ]

Lindgren, I., Madsen, C.Ø., Hofmann, S. & Melin, U., 2019, 'Close encounters of the digital kind: A research agenda for digitalizing public services', Government Information Quarterly 36(3), 427-436. https://doi.org/10.1016/j.giq.2019.03.002        [ Links ]

Madan, R. & Ashok, M., 2023, 'AI adoption and diffusion in public administration: A systematic literature review and future research agenda', Government Information Quarterly 40(1), 101774. https://doi.org/10.1016/j.giq.2022.101774        [ Links ]

Mardia, K.V., Kent, J.T. & Taylor, C.C., 2024, Multivariate analysis, vol. 88, John Wiley & Sons, Leeds.

Masuda, H., Kawakubo, S., Okitasari, M. & Morita, K., 2022, 'Exploring the role of local governments as intermediaries to facilitate partnerships for the sustainable development goals', Sustainable Cities and Society 82, 103883. https://doi.org/10.1016/j.scs.2022.103883        [ Links ]

Mergel, I., Edelmann, N. & Haug, N., 2019, 'Defining digital transformation: Results from expert interviews,' Government information quarterly 36(4), 101385.         [ Links ]

Munyoka, W., 2020, 'Electronic government adoption in voluntary environments - A case study of Zimbabwe', Information Development 36(3), 414-437. https://doi.org/10.1177/0266666919864713        [ Links ]

Osborne, J.W., 2012, Best practices in data cleaning: A complete guide to everything you need to do before and after collecting your data, Sage Publications, London.

Palos-Sánchez, P.R., Baena-Luna, P., García-Ordaz, M. & Martínez-López, F.J., 2023, 'Digital transformation and local government response to the COVID-19 pandemic: An assessment of its impact on the sustainable development goals', Sage Open 13(2), 21582440231167343. https://doi.org/10.1177/21582440231167343        [ Links ]

Parker, A., Hamann, C. & De Kadt, J., 2021, 'Accessing quality education in Gauteng: Intersecting scales of geography, educational policy and inequality', Urban Forum 32(2), 141-163. https://doi.org/10.1007/s12132-021-09418-8        [ Links ]

Pittaway, J.J. & Montazemi, A.R., 2020, 'Know-how to lead digital transformation: The case of local governments', Government Information Quarterly 37(4), 101474. https://doi.org/10.1016/j.giq.2020.101474        [ Links ]

Podsakoff, P.M., MacKenzie, S.B. & Podsakoff, N.P., 2012, 'Sources of method bias in social science research and recommendations on how to control it', Annual Review of Psychology 63(1), 539-569. https://doi.org/10.1146/annurev-psych-120710-100452        [ Links ]

Ramirez-Madrid, J.P., Escobar-Sierra, M., Lans-Vargas, I. & Montes Hincapie, J.M., 2024, 'Factors influencing citizens' adoption of e-government: An empirical validation in a developing Latin American country', Public Management Review 26(1), 185-218. https://doi.org/10.1080/14719037.2022.2078500        [ Links ]

Rönkkö, M. & Cho, E., 2022, 'An updated guideline for assessing discriminant validity', Organizational Research Methods 25(1), 6-14. https://doi.org/10.1177/1094428120968614        [ Links ]

Sadik-Zada, E.R., Gatto, A. & Niftiyev, I., 2022, 'E-government and petty corruption in public sector service delivery', Technology Analysis & Strategic Management 34(3), 1-17. https://doi.org/10.1080/09537325.2022.2067037        [ Links ]

Sanina, A., Balashov, A. & Rubtcova, M., 2023, 'The socio-economic efficiency of digital government transformation', International Journal of Public Administration 46(1), 85-96. https://doi.org/10.1080/01900692.2021.1988637        [ Links ]

Scupola, A. & Mergel, I., 2022, 'Co-production in digital transformation of public administration and public value creation: The case of Denmark', Government Information Quarterly 39(1), 101650. https://doi.org/10.1016/j.giq.2021.101650        [ Links ]

Tangi, L., Janssen, M., Benedetti, M. & Noci, G., 2021, 'Digital government transformation: A structural equation modelling analysis of driving and impeding factors', International Journal of Information Management 60, 102356. https://doi.org/10.1016/j.ijinfomgt.2021.102356        [ Links ]

Terán, M.V., 2018, 'Philosophical Explorations for a Concept of Emerging Technologies,' Techne: Research in Philosophy & Technology 22(1), 28-50.         [ Links ]

United Nations E-Government Survey, 2024, The future of digital government, Department of Economic and Social Affairs, UNDESA, New York, NY, viewed 18 July 2024, from https://desapublications.un.org/sites/default/files/publications/2022-09/Web%20version%20E-Government%202022.pdf.

Valle-Cruz, D., 2019, 'The public value of e-government services through emerging technologies', International Journal of Public Sector Management 32(5), 530-545. https://doi.org/10.1108/IJPSM-03-2018-0072        [ Links ]

Van Veldhoven, Z. & Vanthienen, J., 2022, 'Digital transformation as an interaction-driven perspective between business, society, and technology', Electronic Markets 32(2), 629-644. https://doi.org/10.1007/s12525-021-00464-5        [ Links ]

Venkatesh, V., Thong, J.Y. & Xu, X., 2012, 'Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology', MIS Quarterly 36(1), 157-178. https://doi.org/10.2307/41410412        [ Links ]

Vogl, T.M., Seidelin, C., Ganesh, B. & Bright, J., 2020, 'Smart technology and the emergence of algorithmic bureaucracy: Artificial intelligence in UK local authorities', Public Administration Review 80(6), 946-961. https://doi.org/10.1111/puar.13286        [ Links ]

Weerakkody, V., Irani, Z., Lee, H., Osman, I. & Hindi, N., 2015, 'E-government implementation: A bird's eye view of issues relating to costs, opportunities, benefits and risks', Information Systems Frontiers 17, 889-915. https://doi.org/10.1007/s10796-013-9472-3        [ Links ]

Wilson, C. & Mergel, I., 2022, 'Overcoming barriers to digital government: Mapping the strategies of digital champions', Government Information Quarterly 39(2), 101681. https://doi.org/10.1016/j.giq.2022.101681        [ Links ]

Yigitcanlar, T., Agdas, D. & Degirmenci, K., 2023, 'Artificial intelligence in local governments: Perceptions of city managers on prospects, constraints and choices', AI & Society 38(3), 1135-1150. https://doi.org/10.1007/s00146-022-01450-x        [ Links ]

Zahid, H., Ali, S., Abu-Shanab, E. & Javed, H.M.U., 2022, 'Determinants of intention to use e-government services: An integrated marketing relation view', Telematics and Informatics 68, 101778. https://doi.org/10.1016/j.tele.2022.101778        [ Links ]

 

 

Correspondence:
Willard Munyoka
willard.munyoka@univen.ac.za

Received: 10 Nov. 2023
Accepted: 15 Aug. 2024
Published: 09 Oct. 2024