Abstract
Background: Driven by citizen engagement and open government initiatives, local governments increasingly use social media and artificial intelligence (AI) chatbots to share information and enhance public service efficiency. However, limited literature exists on their acceptability in Zimbabwe.
Aim: We assessed the acceptability of using social media platforms and AI chatbots for citizen engagement and service delivery in Kadoma.
Methods: A mixed-methods approach was used, incorporating an analytic cross-sectional survey and qualitative interviews. A sample size of 404 was calculated, and stratified sampling was used to select households from which one member aged 18 years or above was interviewed. Data were collected using a pretested questionnaire and analysed using Epi Info 7.2.5™. Thematic analysis was used for qualitative data.
Results: We recruited 402 respondents. Most were female, 217 (54.0%), and the median age of respondents was 30 (Q1 = 24; Q3 = 40). Only 111 (27.6%) reported receiving communication from the council, and 323 (80.3%) were dissatisfied with the current communication methods. Acceptance of social media and AI chatbots was high, with 343 (85.3%) preferring WhatsApp™ and 266 (66.2%) supporting AI chatbots. Barriers to using these tools included privacy concerns 136 (33.8%) and high data costs 81 (20.1%).
Conclusion: The study highlighted low communication coverage and high dissatisfaction with existing methods. Acceptance of social media and AI chatbot use was high; however, adoption barriers, such as privacy concerns, need to be addressed. Implementing user training and ensuring data privacy are key to their successful adoption.
Contribution: This study provides valuable insights into the acceptability and potential of using social media and AI chatbots to communicate between local governments and residents.
Keywords: social media; AI chatbots; local government; acceptability; communication; Kadoma City.
Introduction
The effective dissemination of information by local government authorities is pivotal to fostering community engagement and the well-being of citizens (Oye 2019). Social media and artificial intelligence chatbots (AI chatbots) have instigated revolutionary changes, emerging as dominant means of communication. They provide a platform for the timely dissemination of information and enable automated responses to user queries in an efficient manner (Abel Lamidi & Gana 2014; Androutsopoulou et al. 2018). This transformation has significantly influenced the ways in which organisations, in both private and public sectors, interact with citizens. Driven primarily by citizen engagement and open government initiatives, local governments make increasing use of social media and AI chatbots in information sharing, reaching the community, enhancing public service efficiency and increasing interagency exchanges (Gulati & Williams 2013; Mergel & Bretschneider 2013; Norris & Reddick 2013).
In the digital age, social media platforms such as Facebook™, WhatsApp™ and X™ (formerly known as Twitter™) facilitate the creation, sharing and exchange of information, ideas and multimedia content within virtual communities (Obar & Wildman 2015). These platforms serve as effective channels for disseminating announcements and allow citizens to report service-related issues in real time (Obar & Wildman 2015). Similarly, AI-powered chatbots, a sophisticated application of artificial intelligence, engage users in natural language conversations and simulate human-like interactions. They provide instant responses to queries, thereby enhancing self-service transactions in local government settings (Zhang et al. 2020). The integration of social media and AI chatbots constitutes a disruptive technology, a phenomenon described by Girasa in 2020, that has transformed communication strategies by enabling real-time information sharing, enhancing citizen engagement and improving overall service efficiency within local governments (Girasa 2020).
On the global stage, various governments have initiated the integration of social media and AI chatbots into their communication strategies, as evidenced by reports from the United Nations. However, reservations still exist in this regard, particularly in developing nations (Distor, Khaltar & Moon 2023). According to the AI Watch European Landscape Report (2022), although the private sector has been swift in adopting these modern communication technologies, the public sector is still lagging behind. Nonetheless, several European governments are actively working to bridge this gap, recognising the imperative of innovation and technology integration in delivering enhanced services to citizens (Khuram & Jakub 2020).
In Africa, the adoption of social media and AI chatbots in government communication strategies varies across regions. While some nations have made significant advancements, others face challenges related to infrastructure, digital literacy and socio-economic factors, as was evidenced, for example, by attempts to introduce e-government into Ghanaian governmental institutions (Abusamhadana, Bakon & Elias 2021). In South Africa, several government institutions have established a social media presence; however, there is limited research on citizens’ perceptions of the value of these interactions with government institutions (Grawe, Nkoala & Makwambeni 2023).
In Zimbabwe, a nation with a rapidly evolving technological landscape, understanding the integration of social media and AI chatbots into local government communication strategies is of great importance. To explore this issue, we conducted a survey among residents of Kadoma City, one of the country’s 32 urban local councils. We assessed the acceptability of using social media platforms and AI-driven chatbots to enhance citizen engagement and improve service delivery. We focused specifically on the perceived acceptability of these platforms for disseminating information, identified facilitators and barriers to their use and explored best practices for optimising their implementation in Kadoma.
Theoretical and conceptual framework
In this study, we employed the Theory of Planned Behaviour (TPB) as the overarching framework to investigate the acceptability of utilising social media and AI chatbots in local government communication strategies among the residents of Kadoma City. The TPB was chosen because it explains how attitudes, subjective norms and perceived behavioural control influence an individual’s intention to adopt a particular behaviour (Ajzen 1991). In the context of this study, TPB helped to identify the factors that facilitate or hinder residents’ acceptance of social media and AI chatbots for local government communication. Within the TPB framework, we integrated key components from the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), as outlined in Figure 1. To assess residents’ attitudes, TAM’s perceived usefulness and ease of use concepts were employed, capturing perceptions about the benefits and simplicity associated with social media and AI chatbots (Alhashmi, Salloum & Abdallah 2020; Davis, Bagozzi & Warshaw 1989). In addition, UTAUT’s social influence, facilitating conditions, performance expectancy and effort expectancy factors were considered to assess the social and external factors affecting the acceptance and utilisation of social media and AI chatbots (Davis et al. 1989; Venkatesh 2022).
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FIGURE 1: Conceptual framework for theory of planned behaviour integrating key concepts of technology acceptance model and unified theory of acceptance and use of technology. |
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Research methods and design
Study design
We used a mixed methods study design, incorporating quantitative (analytic cross-sectional) and qualitative data. The quantitative component measured the acceptance of social media and AI chatbots, identifying key factors influencing acceptance, such as perceived usefulness, ease of use and social influence. Qualitative data provided deeper insights into motivations, concerns and barriers to adoption, contextualising the quantitative findings. This approach ensured a comprehensive understanding of the acceptability of these communication tools in Kadoma by integrating statistical trends with nuanced resident perspectives.
Study setting
The study was conducted in Kadoma City, one of Zimbabwe’s 32 urban local authorities. It is divided into 17 administrative wards, and according to the 2022 populations and housing census, it had a total population of 117 380 (UNFPA Zimbabwe 2022). The city has 100% Internet coverage, and it is estimated that more than 50% of its residents have access to smart devices. The City Council is equipped with computers, smart devices and Internet access through Wi-Fi. This is supported by a fully established ICT and Public Relations department. Communication between the Council and its stakeholders is carried out using digital platforms such as Facebook™, X™ and WhatsApp™, as well as traditional paper-based channels, with a noticeable preference for engagement on the WhatsApp™ platform.
Study population and sampling strategy
The study population consisted of residents of Kadoma City aged 18 years and above. We used the stratified sampling method using the suburbs of Kadoma City as the strata. To ensure representativeness, a uniform sampling fraction within each stratum was used to calculate the number of households for interviews. Simple random sampling was then used to select households to be interviewed within each suburb. One household member, aged 18 years or above and consenting to participate, was conveniently selected for the interview from each of the selected households. Key informants were purposively sampled based on their expertise and involvement in local government communication strategies. They included representatives from Kadoma City’s Information Technology (IT) and Public Relations departments, as well as community representatives. A total of eight key informants were interviewed, providing diverse perspectives on the best practices and challenges of implementing digital communication tools in Kadoma.
Sample size calculation
The sample size was calculated using Dobson’s formula: n = Za2 (p) (1–p)/delta2 (Sadiq et al. 2024).
Where:
n = Minimum required sample size
Z = Critical value corresponding to the desired confidence level (1.96 for a 95% confidence interval)
p = Estimated prevalence of social media and AI chatbot utilisation acceptance (assumed at 50% in the absence of prior studies)
d = Margin of error or precision (5%)
Assuming a social media and AI chatbot utilisation acceptance rate of 50% at a 95% confidence interval and precision of 5%. The minimum sample size calculated was 404 after factoring in a 5% non-response rate (Equation 1).
n = 384 expecting a 95% response rate n = 384/0.95 = 404. However, 402 respondents were successfully recruited during data collection, representing a 99.5% response rate.
Data collection
Data were collected using a pre-tested, digital interviewer-administered questionnaire, created on Kobo Toolbox™. The platform was selected because of its suitability for field data collection in low-resource settings, particularly its ability to function offline, ensuring uninterrupted survey administration in areas with limited connectivity. The questionnaire collected information on socio-demographic factors, preferred modern communication platforms, questions about the environment supporting the adoption of modern communication tools and factors influencing the acceptance of modern communication technologies. Questions intended to measure these factors were extracted from existing studies and re-framed to fit the context of this study (Distor et al. 2023).
Data analysis
This software was used to calculate means for continuous variables and derive frequencies and/or proportions for categorical variables. These were used to assess the distribution of attitudes towards social media platforms and AI chatbots, providing a quantitative understanding of the overall acceptability in Kadoma City.
The mean scores for acceptance of the use of Facebook™, X™, WhatsApp™ and AI chatbots, along with the factors influencing their acceptance, were determined by assigning numerical values to responses on a 3-point Likert scale. Participants expressed whether they accepted (assigned a value of 3), felt neutral (assigned a value of 2) or did not accept (assigned a value of 1) the use of social media and AI chatbots in communication with the City Council. The mean scores were calculated by summing up these assigned values for all responses and dividing the total by the number of responses, providing a single, interpretable measure of overall acceptance. Although the Likert scale data were ordinal, the mean score was used because it effectively summarised trends in acceptance levels and facilitated comparisons across different platforms and demographic characteristics. In this study, a high mean acceptance score was considered ≥ 2.5, indicating strong acceptance, moderate acceptance ranged from 2.0 to 2.4, while a low mean score (< 2) reflected low acceptance.
To assess factors influencing acceptance, five key factors were analysed: behavioural intention, attitude, perceived usefulness, perceived ease of use and social influence. Each factor (except behavioural intention) was assessed using three questions on the same 3-point Likert scale (1 = Disagree, 2 = Neutral, 3 = Agree), while behavioural intention was assessed using two questions. For each factor, the overall mean score was determined by averaging individual responses across all participants. The scores were then interpreted using the same grading scale, where a mean score ≥ 2.5 indicated a strong positive influence on acceptance, 2.0 – 2.4 suggested a moderate influence and < 2 indicated a low influence. As anxiety about AI chatbots is a negative factor, its interpretation was reversed, with higher scores indicating greater concern and lower scores reflecting minimal anxiety.
Qualitative data were manually analysed using Colaizzi’s steps for phenomenological study to identify common patterns and trends within the narratives of residents and key informants. The qualitative insights complemented the quantitative findings, allowing for a comprehensive understanding of the factors facilitating and impeding acceptability.
Ethical considerations
Ethical clearance to conduct this study was obtained from the City of Kadoma Department of Health and Environmental Services. The ethical clearance number is Mun/03/24. Written informed consent was obtained from all the respondents prior to the interviews. A detailed explanation of the survey’s objectives was provided to respondents so as to allow for informed decision-making. In order to maintain confidentiality, coded questionnaires without personal names were used. Data and consent forms were securely stored.
Results
Socio-demographic characteristics
A total of 402 residents (99.5% response rate) from the 17 administrative wards in Kadoma City were interviewed. A total of 217 (54.0%) were females, and the median age of respondents was 30 years (Q1 = 24; Q3 = 40). A higher proportion of the respondents had lived in Kadoma for over 10 years, 272 (67.7%), and the median duration of stay was 18 years (Q1 = 9; Q3 = 25). The socio-demographic characteristics of the respondents are presented in Table 1.
| TABLE 1: Socio-demographic characteristics of respondents in Kadoma City, Zimbabwe, 2024 (N = 402). |
Social media platforms that were currently being used by respondents included WhatsApp™ 340 (84.6%), Facebook™ 215 (53.5%), X™ 98 (24.4%) and 46 (11.4%) respondents reported not used any. The platforms that were currently being used by respondents are presented in Figure 2.
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FIGURE 2: Social media platforms currently being used by respondents in Kadoma City, Zimbabwe, 2024 (N = 402). |
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Existing methods of communication between residents and Kadoma city council
Of the 402 residents interviewed, 111 (27.6%) reported having received information or communication from the Kadoma City Council in the past. The types of information/communication received included Council utility bills, 97 (87.4%); waste collection schedules, 12 (10.8%); health-related updates, 41 (36.9%); community consultation meeting schedules, 8 (7.2%) and policy updates, 8 (7.2%). The platforms used to share the information were short message services (SMS), 59 (53.1%); WhatsApp™, 49 (44.1%); regular postal mail, 29 (26.1%); in-person communication, 14 (12.6%) and Facebook™, 10 (9.0%). The methods/platforms used in the dissemination of information between the residents interviewed and the Kadoma City Council are shown in Figure 3.
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FIGURE 3: Platforms used to share information with residents in Kadoma City Council, Zimbabwe, 2024 (N = 111). |
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A total of 323 (80.3%) respondents indicated that they were not satisfied with the current communication methods.
Acceptance of social media and artificial intelligence chatbots
The overall mean score for acceptance of social media platforms and AI chatbots for communication with the City Council was 2.6 (SD = ± 0.6). Of the respondents surveyed, 343 (85.3%) reported that WhatsApp™ was an acceptable way of communicating with the City Council. Additionally, 266 (66.2%) found AI chatbots acceptable, 265 (65.9%) accepted using Facebook™ and 222 (55.2%) were in favour of using X™.
Factors influencing acceptance of social media and artificial intelligence chatbots
The overall mean acceptance scores for various factors influencing the acceptance of social media and AI chatbot use in Kadoma were also evaluated. The highest mean acceptance scores were observed for statements on attitudes towards using social media and AI chatbots, 2.8 (SD = ± 1.3), perceived usefulness, 2.8 (SD = ± 1.3) and perceived ease of use, 2.7 (SD = ± 1.3). Social influence had a moderate mean score of 2.4 (SD = ± 2.0), while anxiety about using the tools had the lowest mean acceptance score of 1.3 (SD = ± 1.1). The overall mean acceptance scores for the various factors influencing the acceptance of social media and AI chatbots in Kadoma are shown in Table 2.
| TABLE 2: Factors influencing acceptance of social media and artificial intelligence chatbots utilisation in Kadoma, Zimbabwe, 2024. |
Facilitators and barriers to the use of modern communication tools
Participants were also asked what they perceived to be the facilitators of and barriers to social media and AI chatbot usage in Kadoma City. A total of 375 (93.3%) cited using social media platforms such as WhatsApp™, Facebook™ and X™ (formerly Twitter™), which was a facilitating factor. A further 256 (63.7%) mentioned access to the Internet and possession of a smartphone, 160 (39.8%) as enabling factors. On the other hand, barriers to using the modern communication tools cited by respondents included privacy and security issues, 136 (33.8%), slow mobile internet network, 102 (25.4%), high mobile data costs 81 (20.1%) and language barriers, 74 (18.4%). The facilitators of and barriers to social media and AI chatbot usage in Kadoma City are outlined in Table 3.
| TABLE 3: Facilitators of and barriers to modern communication tools usage in Kadoma City, Zimbabwe, 2024. |
Best practices for optimising social media and artificial intelligence chatbots use
Central to the discussion on best practices for optimising social media and AI chatbot use in Kadoma were recurring themes such as training on social media and AI chatbots, personalised interaction, data privacy measures and provision of timely responses and regular updates. These key themes emerged as crucial considerations emphasised by respondents and key informants. The identified themes and quotations from respondents and key informants to illustrate these are presented in Table 4.
| TABLE 4: Best practices for optimising social media and artificial intelligencce chatbots use in Kadoma City, Zimbabwe, 2024. |
Discussion
The findings of this study provide important insights into the acceptability of using social media and AI chatbots for communication between Kadoma City Council and its residents. In our study, approximately three-quarters of the respondents reported not having received any communication from the Council. This communication gap was further emphasised by the dissatisfaction expressed by over 80% of respondents with existing communication methods, underscoring the need for more effective and inclusive strategies to reach residents of Kadoma.
We further found that communication received by residents was primarily in the form of utility bills, health-related updates and solid waste collection schedules. The platforms used were a mix of traditional and digital methods, including SMS, WhatsApp™ and regular postal mail. Despite the widespread adoption of digital tools, the continued reliance on traditional methods of information dissemination, such as snail mail, and the low utilisation of social media by the Kadoma City Council contrasts with current trends towards more digitally integrated community communication systems. A study conducted in South Africa reported that the use of modern digital technologies improved engagement between local authorities and residents (Nciweni, Matsilele & Abrahams 2023). The limited use of modern communication methods in Kadoma could contribute to low community engagement and dissatisfaction, as was observed in our study.
We also found a high level of acceptance of the use of social media and AI chatbots for communication between residents and the Kadoma City Council. WhatsApp™ was the most preferred platform, and more than half of the respondents also expressed a preference for AI chatbots, Facebook™ and X™. These findings are consistent with studies conducted in Nigeria and South Africa, which reported high acceptance rates for digital communication tools in engaging with local authorities (Ade-Ibijola & Okonkwo 2023; Matlala 2024). In Kadoma, the high acceptance rates suggest that integrating these platforms could transform the effectiveness of communication between the local authority and its residents, allowing for real-time interaction, broader reach and instant feedback. The preference for WhatsApp™ can be attributed to its widespread use and familiarity among users, offering instant, direct communication that is accessible, not costly, and is user friendly (Himpong, Waleleng & Warouw 2023). On the other hand, AI chatbots are valued for their ability to provide 24/7 support and quick responses to common user queries, which can enhance user satisfaction as a result of improved responsiveness and efficiency (Distor et al. 2023; Maultasch de Oliveira & Welch 2013). However, potential challenges such as ensuring digital literacy, protecting data privacy and managing the increased volume of interactions need to be planned for in advance (Distor et al. 2023; Horvath et al. 2023; Oseni, Dingley & Hart 2016).
Our study’s findings support the applicability of the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) frameworks in evaluating the acceptance of social media and AI chatbots in local government communication strategies. The mean acceptance scores for attitudes towards using social media and AI chatbots, perceived usefulness and perceived ease of use were notably high, and this is consistent with a similar study conducted by Distor et al. (2023) in the Philippines. These results indicate that residents in Kadoma have a favourable perception of these platforms for purposes of communication with the City Council. Positive attitudes and perceived usefulness have been shown, in literature, to significantly influence the adoption of new technologies (Cheah et al. 2024; Fodouop Kouam & Muchowe 2024; Goli et al. 2023). The relatively high acceptance score for social influence indicates the influential role that community norms and peer opinions have in shaping residents’ acceptance of new technologies. However, the lower mean acceptance score for anxiety suggests that concerns about the use of these technologies, such as their complexity or mistrust of them, could affect their more widespread adoption (Dhagarra, Goswami & Kumar 2020). Similar findings have been reported, highlighting anxiety and fear of technology as significant barriers to the adoption of new communication tools, particularly among populations that are less familiar with digital technologies (Perdana & Mokhtar 2022; Sun & Nakajima 2023). It is imperative, therefore, for the City Council to address these anxieties and concerns so as to facilitate the widespread adoption of these tools.
It was further observed that most respondents mentioned the existence and use of social media platforms such as WhatsApp™, Facebook™ and X™ as key facilitators to the adoption of modern communication tools in Kadoma City. This aligns with trends observed in other urban areas, where the widespread use of social media lays a foundation for integrating digital communication methods into public service frameworks (Abusamhadana et al. 2021; Norris & Reddick 2013; Tetteh & Kankam 2024). The implementation of these modern communication tools requires and is supported by access to the Internet and possession of compatible smartphones. However, several barriers to their adoption need to be addressed to maximise the effectiveness of these tools. The privacy and security concerns mentioned by respondents highlight the need for robust data protection measures. Studies have shown that trust in digital platforms significantly affects their adoption, emphasising the importance of ensuring secure and private communication channels (Distor et al. 2023; Horvath et al. 2023). Furthermore, the slow mobile Internet networks and high mobile data costs reported by some of the respondents suggest that infrastructural improvements and data cost reductions are necessary to facilitate broader access and use of social media platforms and AI chatbots. These issues have been reported to be more common in many developing regions, where digital divides can hinder the adoption of modern communication technologies (Oseni et al. 2016).
The analysis of respondents’ feedback on best practices revealed several key themes essential for optimising communication between residents and the Kadoma City Council using social media and AI chatbots. Both residents and key informants highlighted training on the use of social media and AI chatbots as necessary for both the community and Council workers to facilitate meaningful engagement. This aligns with findings from studies conducted in the United Kingdom and Australia, where training and digital literacy programmes significantly enhanced the adoption and effective use of social media and AI chatbots (Selwyn & Gallo Cordoba 2022; Vogl et al. 2020). Data privacy measures were a significant concern, with most respondents emphasising the need for secure handling of personal information. This reflects a broader trend seen in studies across various regions, where data privacy is a crucial factor in the acceptance of and trust in digital platforms (Horvath et al. 2023; Kaya 2019; Oseni et al. 2016).
Limitations of the study
Although we used a mixed-methods approach, incorporating both quantitative and qualitative data, the findings are limited to the specific context of Kadoma City. They may not therefore, be generalisable to other urban or rural settings in Zimbabwe. In addition, reliance on self-reported data may have introduced response bias, particularly concerning sensitive topics such as dissatisfaction with City Council services or willingness to use digital tools. A further limitation was that the study sample was drawn from individuals who had access to the Internet and smartphones, potentially excluding residents without digital access and thereby underestimating the barriers faced by this subgroup.
Recommendations
Based on a synthesis of the study’s findings, we recommended that Kadoma City Council should expand its communication channels by integrating modern tools such as AI chatbots and social media platforms such as WhatsApp™ and Facebook™ with a view to improving citizen engagement, providing timely updates and enhancing transparency. Furthermore, in order to ensure that these tools are accessible to all residents, the City Council should implement training programmes for both Council workers and residents on the use of these technologies, especially for residents with limited digital literacy or no prior experience with AI. The Council should also establish a dedicated support team to offer ongoing assistance, address technical challenges and respond to queries in real time. Moreover, in order to mitigate concerns around data privacy and build trust, Kadoma City Council should adopt strict data protection measures and communicate these policies clearly to residents.
Conclusion
The study’s findings highlighted several key issues and opportunities relating to communication between the Kadoma City Council and its residents. The proportion of residents who had received information from the City Council was low, and most respondents expressed dissatisfaction with current communication strategies, indicating a need for the Council to improve information dissemination practices. The overall acceptance of using social media and AI chatbots for communication was high, with WhatsApp™, Facebook™ and AI chatbots emerging as the most preferred platforms. This suggests a potential for integrating these tools to enhance resident engagement in Kadoma. Factors such as smartphone ownership, Internet access and familiarity with social media platforms were identified as facilitators for the adoption of these digital tools. At the same time, barriers included slow mobile Internet and high data costs. The best practices for optimising the use of social media and AI chatbots mentioned by respondents included the need to train both community members and Council workers on the use of digital communication platforms. Furthermore, providing regular updates and timely responses, ensuring personalised interactions and maintaining data privacy were also cited as best practices to help adopt social media and AI chatbots use in Kadoma. These findings revealed the need for planning and resource investment in order to harness digital communication platforms, enabling the Kadoma City Council to strengthen its engagement with residents and improve service delivery.
Future studies should explore the long-term impact of social media and AI chatbots on local government communication and assess their effectiveness in building community trust and transparency. In addition, a more in-depth investigation into AI-specific issues, such as user trust, privacy concerns, digital literacy challenges and ethical considerations, would provide deeper insights into the adoption and sustainability of AI-driven communication tools in public service delivery.
Acknowledgements
This article is part of the management core activity for learning for the Field Epidemiology Training Program (FETP), which is a requirement for attaining a Master of Public Health (MPH-FETP) degree at the University of Zimbabwe.
Competing interests
The authors, declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.
CRediT authorship contribution
Clayton Munemo: Conceptualisation, Data curation, Formal analysis, Writing – original draft, Writing – review & editing. Daniel Chirundu: Conceptualisation, Data curation, Formal analysis, Writing – original draft, Writing – review & editing. Addmore Chadambuka: Conceptualisation, Data curation, Formal analysis, Writing – original draft, Writing – review & editing. Tsitsi P. Juru: Conceptualisation. Gerald Shambira: Conceptualisation. Gibson Mandozana: Conceptualisation. Notion T. Gombe: Conceptualisation. Mufuta Tshimanga: Conceptualisation. All authors reviewed the article, contributed to the discussion of results, approved the final version for submission and publication and take responsibility for the integrity of its findings.
Funding information
This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.
Data availability
The authors confirm that the data supporting the findings of this study are available from the corresponding author, Addmore Chadambuka, upon reasonable request and with permission from the Kadoma City Council.
Disclaimer
The views and opinions expressed in this article are those of the authors and are the product of professional research. They do 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.
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