Original Research

Leveraging infrastructure for regional integration and economic growth in the Southern African Development Community: A conceptual framework

Morake C. Morolo, Kambidima Wotela

Received: 26 May 2025; Accepted: 08 Aug. 2025; Published: 28 Oct. 2025

Copyright: © 2025. The Author(s). Licensee: AOSIS.
This work is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license (https://creativecommons.org/licenses/by/4.0/).

Abstract

Background: While the Southern African Development Community (SADC) region is endowed with rich deposits of mineral resources, yet it is confronted with slow economic growth as compared to other regions. Road infrastructure quality is considered an enabler to economic growth for interconnected countries. Therefore, road infrastructure investment is significant to enable trade openness and ultimately economic growth.

Objectives: This study explores the role of road infrastructure quality in fostering regional economic integration and economic growth within the SADC.

Method: By analysing the relationship between road quality, trade openness and economic growth, the study employs panel data regression methods on a sample of four SADC countries (Botswana, Mozambique, South Africa and Zimbabwe) from 2010 to 2020.

Results: The findings suggest that while road quality has an indirect impact on trade openness, government spending and foreign direct investment are key factors enhancing trade integration. Furthermore, trade openness positively influences economic growth, especially when supported by favourable macroeconomic policies.

Conclusion: Based on these findings, the study recommends prioritising sustainable road infrastructure investments, strengthening public–private partnerships to bridge funding gaps, harmonising trade and transport policies to reduce cross-border inefficiencies and integrating road development with broader economic and trade facilitation strategies.

Contribution: These measures can amplify the benefits of road infrastructure improvements, foster greater regional connectivity and stimulate inclusive economic growth. The study offers a conceptual framework to guide policymakers in the SADC region towards maximising the economic gains from infrastructure-led integration.

Keywords: road infrastructure quality; trade openness; economic growth; Southern African Development Community; regional integration.

Introduction

Road infrastructure is a corner-stone of economic development, serving as a catalyst for growth and regional integration, particularly in developing regions, such as the Southern African Development Community (SADC). The SADC, comprising 16 member states, represents a diverse economic bloc grappling with infrastructural disparities that hinder seamless trade and connectivity. High-quality road infrastructure reduces transportation costs, improves accessibility and fosters market linkages, enabling regions to maximise economic opportunities (Duernecker, Meyer & Vega-Redondo 2022). Yet, disparities in road quality and infrastructural investment remain pervasive challenges for the SADC.

The role of road infrastructure in facilitating trade openness – a vital driver of economic growth – has been underscored in numerous studies. For instance, research in China has demonstrated that trade openness contributes to economic stabilisation in the short term and fosters sustained growth in the long term, particularly when supported by robust infrastructure (Kong et al. 2020). Similar findings in Pakistan and Uganda reveal a bidirectional relationship between trade openness and economic growth, underlining the importance of infrastructure quality in amplifying these dynamics (Esaku 2021; Khan, Anwar & Anwar 2020). Road infrastructure and trade openness are closely linked, with improvements in road networks generally reducing trade costs and facilitating greater movement of goods and people, thereby enhancing trade openness and economic growth. Evidence from large-scale projects like China’s Belt and Road Initiative (BRI) shows that infrastructure investment, particularly in roads, significantly boosts foreign trade, economic growth and welfare by lowering transportation costs and improving connectivity between regions and countries (Morten & Oliveira 2024; Wu & Han 2022; Yang et al. 2020). However, the benefits are not uniform: while infrastructure investment tends to benefit less developed regions more, trade openness can sometimes exacerbate economic disparities within and between countries, especially in middle- and high-income areas (Zhou 2024). Studies also highlight that while physical infrastructure is crucial, improvements in trade facilitation (such as border administration) can have an even greater impact on exports (Ramasamy & Yeung 2019). In Africa, the interaction between infrastructure and trade openness can also influence environmental outcomes, with trade openness sometimes mitigating the negative environmental effects of infrastructure development up to a certain threshold (Ng’ang’a 2022). Overall, robust road infrastructure supports trade openness by making trade more efficient and accessible, but the full benefits depend on complementary policies and regional contexts (Morten & Oliveira 2024; Ramasamy & Yeung 2019; Wu & Han 2022; Yang et al. 2020; Zhou 2024).

In the context of the SADC, the integration of road networks is pivotal for enhancing intraregional trade and economic cooperation. However, uneven infrastructure development among member states often stymies these goals. Poor road conditions and logistical bottlenecks lead to increased transportation costs, limited access to regional markets and reduced trade efficiency (Blyde 2013). These limitations underscore the need for targeted investments in road infrastructure as a pathway to economic growth and regional integration.

Furthermore, trade openness has been identified as a critical enabler of regional economic cooperation and development. Studies indicate that enhanced trade integration can significantly boost economic performance, as observed in regions like the European Union (Arribas, Bensassi & Tortosa-Ausina 2020). However, the effectiveness of trade openness is often contingent on infrastructural adequacy. In SADC, where infrastructural gaps remain substantial, realising the full benefits of trade openness necessitates addressing these deficiencies.

This background sets the stage for exploring how investments in road infrastructure can serve as a lever for achieving both regional economic integration and economic growth in the SADC. By addressing the critical interplay between road quality, trade openness and economic outcomes, this study seeks to provide actionable insights for policymakers aiming to optimise infrastructural development for sustainable growth.

Problem statement

Despite the proven relationship between road infrastructure, trade openness and economic growth, SADC countries face persistent challenges in leveraging these synergies. The region’s road infrastructure varies widely in quality, with many remote areas struggling to access markets because of poor connectivity (Blyde 2013). This disparity hinders the flow of goods and services, exacerbating economic inequalities and slowing progress towards regional integration.

Trade openness in SADC remains limited, with intraregional trade accounting for a small proportion of overall trade activities. This is despite evidence that enhanced trade openness significantly contributes to economic growth in both developed and developing regions (Udeagha & Ngepah 2020). Additionally, factors such as population growth, inflation and limited government spending on infrastructure complicate the relationship between road quality and economic growth, necessitating a nuanced understanding of how these variables interact.

This study addresses the pressing need for a conceptual framework to explore the relationships between road quality, trade openness and economic growth in the SADC. By identifying key mediating and moderating variables and synthesising insights from empirical and theoretical literature, this research aims to provide actionable recommendations for policymakers to optimise road infrastructure investments and achieve regional economic integration.

Objectives

The study is guided by the following specific objectives:

• To analyse the effect of road quality on trade openness, examining population growth, inflation, government spending, employment and foreign direct investment (FDI) as potential mediators and moderators in this relationship.
• To evaluate the impact of trade openness on economic growth, investigating the roles of population growth, inflation, government spending, employment and FDI as mediating and moderating variables.

Literature review

Overview of literature

The relationship between trade openness and economic growth has been a central focus in economic literature, with studies consistently showcasing its complex and multifaceted impacts. Trade openness is often heralded as a catalyst for economic integration, technological advancements and enhanced global market access, particularly in developing regions. Jalil and Rauf (2020) underscore the necessity of methodological precision in demonstrating that trade openness positively influences economic growth, while Ozigbu (2022) highlights its role in improving living standards through enhanced economic well-being in developing countries.

Esaku (2021) corroborates these findings by showing that in Uganda, trade openness contributes significantly to long-term economic growth, largely through increased exports and imports. The benefits of trade openness are also evident in fostering technological diffusion, promoting productivity and providing access to competitive markets, as seen in studies examining both regional and global contexts. For instance, Tran (2020) suggests that the liberalisation of trade has wide-ranging implications for economic and environmental policies, particularly in developing economies experiencing rapid industrialisation.

However, the discourse around trade openness is not devoid of contention. Ahmad et al. (2020) bring attention to the dualistic impact of trade openness on environmental quality, emphasising its potential to both enhance and harm ecological sustainability. Similarly, studies like those of Tachie et al. (2020) and Udeagha and Ngepah (2020) demonstrate that trade openness can lead to uneven outcomes, such as exacerbating regional disparities and environmental degradation in economies with insufficient regulatory measures. These controversies highlight the necessity for region-specific policies that align trade practices with sustainable growth objectives, particularly in regions like the SADC.

Thus, while the broad benefits of trade openness are well established, its implications for specific regions remain understudied. The SADC region, characterised by varying levels of economic development and infrastructure quality, provides a unique case for exploring how trade openness can be leveraged for regional economic growth and integration. Addressing the infrastructural disparities and aligning trade policies with developmental goals are critical to optimising these benefits.

Key theories or concepts

The theoretical framework for understanding the interplay between road infrastructure, trade openness and economic growth draws upon key economic growth theories. The Neoclassical Growth Theory, particularly the Solow Growth Model, emphasises the importance of capital accumulation, labour and technological progress as determinants of long-term economic growth. Within this framework, trade openness enhances resource allocation efficiency and technological transfer, enabling economies to reach higher steady-state growth levels (Solow 1956). The Solow model also highlights infrastructure, including road quality, as part of physical capital that reduces transaction costs and enhances productivity.

The Endogenous Growth Theory offers a complementary perspective by integrating innovation, knowledge spillovers and policy measures into growth models (Lucas 1988; Romer 1986). Unlike the Neoclassical model, it posits that investments in human capital, infrastructure and research and development can sustain long-term growth without diminishing returns. Road infrastructure, as a facilitator of connectivity and trade, aligns with the theory’s emphasis on increasing returns to scale and the role of public investments in fostering economic expansion.

The Environmental Kuznets Curve (EKC) Hypothesis provides insights into the relationship between trade openness and environmental outcomes. It suggests that while trade-driven growth initially worsens environmental quality, higher income levels eventually enable economies to adopt cleaner technologies and sustainable practices (Ahmad et al. 2020). This underscores the importance of complementary policies in ensuring sustainable development.

Additionally, the Gravity Model of Trade underscores the role of infrastructure in enhancing trade flows. According to this model, geographic proximity and infrastructure quality, such as road networks, significantly influence trade intensity between regions, facilitating economic integration.

This study hinges primarily on the Endogenous Growth Theory because of its emphasis on the role of infrastructure, knowledge transfer and innovation in sustaining economic growth. By focusing on road quality as a critical enabler of trade openness and regional integration, the study aligns with the theory’s view that targeted investments and policy interventions can drive long-term growth. The incorporation of the EKC hypothesis further contextualises the analysis by addressing potential trade-offs between economic growth and environmental sustainability.

Gaps and controversies in the literature

Despite progress, significant gaps persist in understanding the regional dynamics of trade openness and growth. Existing studies often overlook the infrastructural context, particularly the role of road quality, in shaping trade outcomes in regions like SADC. Duernecker et al. (2022) propose systemic integration as a measure of openness but fail to address regional infrastructure disparities. Moreover, Tran (2020) and Tachie et al. (2020) highlight trade openness’s environmental costs, particularly in developing economies with inadequate regulatory frameworks. Methodological variations also contribute to conflicting findings, with differences in proxies for trade openness and econometric techniques resulting in divergent conclusions (Jalil & Rauf 2020; Udeagha & Ngepah 2020). Furthermore, while bidirectional causality between trade openness and growth is evident in some regions, its applicability to SADC remains underexplored.

Addressing these gaps requires a region-specific framework that considers road infrastructure as a critical mediator. For the SADC region, such an approach can bridge the disconnect between trade policy and sustainable development, aligning infrastructure improvements with broader economic goals. This integrated perspective offers new insights into optimising trade openness for regional economic growth and integration.

Research methods and design

Research design

This study adopts a panel data regression framework to analyse the relationship between road quality, trade openness and economic growth in the SADC region, focusing on Botswana, Mozambique, South Africa and Zimbabwe over the period of 2010–2020. The other SADC member states were not included because of the unavailability of adequate and consistent data for the variables of interest over the study period. Furthermore, even for the selected countries, the study period could have been extended, but data availability limited the analysis to the years 2010–2020. Panel data regression is chosen for its capacity to handle both cross-sectional and temporal variations, enhancing the robustness of estimates by accounting for unobserved heterogeneity (Wooldridge 2020). The analysis includes fixed effects (FE) and random effects (RE) models, with the Hausman test employed to select the appropriate specification.

Data collection

Data are sourced from reliable databases, such as the World Development Indicators (WDI) and the Global Economy Database, ensuring comprehensive coverage of variables like road quality, trade openness, economic growth and key control variables – population growth, inflation, government spending, employment and FDI. This dataset allows for an empirical assessment of contemporary trends in infrastructure and economic performance in the SADC region.

Variables and operationalisation

The key variables under study are operationalised as follows.

Dependent variables

Trade openness (TO): Measured as the ratio of the sum of exports and imports to gross domestic product (GDP), reflecting the degree of economic integration with global markets.

Economic growth (EG): Represented by the annual percentage change in real GDP.

Independent variable

Road quality (RQ): The road quality indicator is one of the components of the Global Competitiveness Index published annually by the World Economic Forum (WEF). It represents an assessment of the quality of roads in a given country based on data from the WEF Executive Opinion Survey, a long-running and extensive survey tapping the opinions of over 14 000 business leaders in 144 countries. The road quality indicator score is based on only one question. The respondents were asked to rate the roads in their country of operation on a scale from 1 (underdeveloped) to 7 (extensive and efficient by international standards). The individual responses were aggregated to produce a country score.

Trade openness (TO): Measured as the ratio of the sum of exports and imports to GDP, reflecting the degree of economic integration with global markets.

Control variables

Population growth (PG), inflation (INF), government spending (GS), employment (EMP) and FDI are included as controls to isolate the effects of RQ on TO and TO on EG.

Analytical approach

Panel data regression is applied to evaluate two key relationships: (1) the effect of road quality on trade openness and (2) the effect of trade openness on economic growth. Control variables are included in both models to account for confounding factors. Fixed effects (FE) and RE models are estimated, with the Hausman test determining the preferred approach for each analysis.

This approach allows for the examination of within-country and between-country variations, aligning with established methodologies for longitudinal and cross-sectional analysis in economic studies (Baltagi 2021). Diagnostic checks, including tests for multicollinearity and heteroskedasticity, ensure the reliability of findings.

While the models in this study focus on estimating the association between trade openness and economic growth, the potential for reverse causality – where higher economic growth could also lead to increased trade openness is acknowledged. The analysis mitigates this concern to some extent by incorporating multiple macroeconomic control variables and exploiting the panel structure of the data, which captures both cross-country and temporal variation. However, the primary aim is to establish the strength and direction of relationships within the SADC context rather than to claim strict causality. The findings should therefore be interpreted as indicative of associations under the specified model, with causality subject to further investigation in future studies using advanced techniques, such as instrumental variables or dynamic panel estimators.

All modelling and diagnostics were carried out in Stata, version 17 (StataCorp LLC, College Station, Texas, United States [US]). We estimated fixed- and random-effects models with xtreg and used post-estimation diagnostics, including the Breusch-Pagan test for heteroskedasticity and the Information Matrix (IM) decomposition. The analyses are conducted using STATA 17 in order to leverage its advanced capabilities for panel data regression. This ensures precision in handling complex models and the computation of robust statistical inferences.

By applying panel data regression with control variables, this study contributes to the understanding of how road infrastructure quality influences trade openness and economic growth in the SADC region, aligning with its objective to inform strategies for regional economic integration.

Ethical considerations

Ethical clearance to conduct this study was obtained from the University of the Witwatersrand, Johannesburg, Human Research Ethics Committee (Non-Medical) (No. H23/03/22).

Results

Effect of road quality on trade openness

The regression analysis evaluates the relationship between RQ and TO, incorporating key variables, such as PG, INF, GS, EMP and FDI. Fixed-effects (Figure 1) and RE (Figure 2) models are employed, with the Hausman test (Table 1) determining the appropriate specification.

FIGURE 1: Fixed-effects regression results for the impact of road quality and control variables on trade openness in SADC countries (2010–2020).

FIGURE 2: Random-effects regression results for the impact of road quality and control variables on trade openness in SADC countries (2010 –2020).

In the fixed-effects model, the within R² value of 0.247 indicates that 24.7% of the variability in TO is explained by the predictors within countries over time. Population growth (PG) emerges as the sole significant variable (p = 0.045), suggesting that higher population growth is associated with decreased trade openness. This aligns with findings by Udeagha and Ngepah (2020), who emphasised the complex interplay of demographic factors and trade dynamics in Africa. Other variables, including RQ, are statistically insignificant, reflecting potential limitations in the model or the need for more granular data.

The random-effects model, with an overall R² of 0.7106, provides stronger explanatory power for cross-country variations. Government spending (GS) significantly predicts TO (p = 0.000), indicating its role in enhancing trade openness, consistent with literature that highlights infrastructure investment as a catalyst for trade (Duernecker et al. 2022). FDI approaches significance (p = 0.093), resonating with Ahmad et al. (2020), who identified FDI as critical in integrating economies into global trade networks. However, RQ remains insignificant, suggesting potential indirect or moderated effects rather than direct impacts on TO.

The Hausman test (χ²(6) = 14.97, p = 0.0205) indicates that the fixed-effects model is preferred, emphasising the importance of within-entity variations. This result underscores that trade openness in the SADC region is influenced by domestic factors, such as population trends and policy implementation. Recent studies, including Esaku (2021), support the view that trade openness benefits from tailored domestic policies that address country-specific barriers. Within the SADC framework, initiatives such as the SADC Protocol on Trade and the Industrialisation Strategy and Roadmap (2015–2063) aim to enhance intra-regional trade by reducing tariff and non-tariff barriers, harmonising customs procedures and promoting cross-border infrastructure development. These policies, when effectively implemented at the national level, can strengthen the link between openness and economic growth by addressing structural constraints that vary across member states.

For the model specification tests, the following results were found (Table 2):

. estat hettest

Breusch-Pagan / Cook-Weisberg test for heteroskedasticity

Ho: Constant variance

Variables: fitted values of to

Chi²(1) = 0.69

Prob > Chi² = 0.4076

The Breusch–Pagan/Cook–Weisberg test for heteroskedasticity produced χ²(1) = 0.69 with (probability) Prob > χ² = 0.4076. At the 5% level, the null hypothesis of constant variance could not be rejected, indicating no evidence of heteroskedasticity in the regression residuals. Cameron and Trivedi’s IM decomposition confirmed this, with the heteroskedasticity component yielding p = 0.2609.

Cameron and Trivedi’s decomposition also examined skewness (p = 0.5396) and kurtosis (p = 0.3038), with neither being statistically significant. These results indicate that residuals did not exhibit abnormal skewness or kurtosis, supporting the normality assumption (Table 3). The Ramsey RESET test returned F (3, 30) = 1.96, p = 0.1405, suggesting no strong evidence of omitted non-linear terms or functional form misspecification.

Variance inflation factors (VIF) indicated that while some predictors, such as road quality (10.63) and employment (9.70), were on the higher end, the mean VIF was 5.44, which is within an acceptable range. This indicates that multicollinearity was not a severe concern for the overall model Refer to Table 4.

Effect size analysis showed that the model explained a substantial portion of the variance in the dependent variable, with an overall eta-squared of 0.7106. Government spending exhibited the largest partial eta-squared (0.5298), indicating it was a strong predictor, while other variables contributed smaller but meaningful proportions to the explained variance.

Effect of trade openness on economic growth

The regression analysis examines the effect of TO on EG using a panel dataset from four SADC countries (Botswana, Mozambique, South Africa and Zimbabwe) between 2010 and 2020. Two models were evaluated: FE (Figure 3) and RE (Figure 4), with the Hausman test (Table 5) determining the most suitable specification.

FIGURE 3: Fixed-effects regression results for the impact of trade openness and control variables on economic growth in SADC countries (2010–2020).

FIGURE 4: Random-effects regression results for the impact of trade openness and control variables on economic growth in SADC countries (2010–2020).

The FE model indicates that TO has a positive but statistically insignificant effect on EG (p = 0.121), while inflation (INF, p = 0.025), employment (EMP, p = 0.011) and population growth (PG, p = 0.033) significantly affect EG. Specifically, higher inflation and population growth negatively influence EG, while employment positively contributes to economic outcomes. These findings align with Udeagha and Ngepah (2020), who argue that demographic and macroeconomic factors play crucial roles in shaping trade-related economic growth.

The RE model corroborates some of the FE findings, showing significant positive effects of TO (p = 0.004) and employment (p = 0.005) on EG. Conversely, inflation (p = 0.001) and population growth (p = 0.020) exert negative impacts, consistent with the literature linking inflation to economic instability and population pressures to strained resources (Esaku 2021; Jalil & Rauf 2020) (Table 5). Government spending (GS) and FDI remain insignificant in both models, suggesting that their roles may be context dependent or moderated by other factors, as discussed by Tosunoğlu (2023).

The Hausman test (χ²(6) = 7.32, p = 0.2927) fails to reject the null hypothesis, indicating no systematic difference between the FE and RE models. Thus, the RE model is preferred for its efficiency. The RE results, particularly the positive relationship between TO and EG, echo findings from global and regional studies (Khan et al. 2020), which highlight trade openness as a driver of economic performance when coupled with conducive policy environments.

The specification tests run for the second model also produced ideal results as follows (Table 6):

. estat hottest

Breusch-Pagan / Cook-Weisberg test for heteroskedasticity

Ho: Constant variance

Variables: fitted values of eg

Chi²(1) = 1.09

Prob > Chi² = 0.2956

The Breusch–Pagan/Cook–Weisberg test for heteroskedasticity returned χ²(1) = 1.09 with Prob > χ² = 0.2956, meaning the null hypothesis of constant variance could not be rejected (Table 7). This indicates no evidence of heteroskedasticity in the residuals.

Cameron and Trivedi’s IM-test confirmed this result, with the heteroskedasticity component producing p = 0.3005. The skewness (p = 0.0722) and kurtosis (p = 0.3349) components were also not statistically significant, suggesting that the residuals followed an approximately normal distribution without severe departures in symmetry or tail behaviour.

The VIF diagnostics showed that all predictors had VIF values below 6, with a mean VIF of 3.53, well within conventional thresholds for concern. This indicates that multicollinearity was not a major issue and that the predictors could be reliably interpreted in the model.

Effect size analysis revealed that the model explained 48.86% of the variation in economic growth (eta-squared = 0.4886). Trade openness (eta-squared = 0.1868), inflation (eta-squared = 0.2161) and employment (eta-squared = 0.1775) emerged as the most influential predictors, indicating that these variables contributed meaningfully to explaining variation in economic growth across the sample (Table 8).

Conclusion

The findings of this study provide critical insights into the role of road infrastructure quality in fostering regional economic integration, measured through TO and its subsequent effect on EG in the SADC. While RQ did not have a direct statistically significant effect on TO, variables such as GS and FDI emerged as significant contributors to enhancing trade integration, consistent with studies highlighting infrastructure investment’s catalytic role in trade facilitation (Duernecker et al. 2022). The results also underscore the importance of domestic factors, such as population growth and inflation, in shaping trade dynamics.

In examining the link between trade openness and economic growth, the study found a positive relationship, particularly evident in the random-effects model, aligning with global literature that recognises trade as a critical driver of economic performance when supported by conducive macroeconomic policies (Khan et al. 2020). Employment emerged as a key factor positively influencing economic growth, emphasising the importance of labour market dynamics in leveraging trade benefits. Conversely, inflation and population growth negatively impacted economic outcomes, highlighting the need for effective policy interventions to mitigate these challenges.

From a policy perspective, these findings align closely with ongoing regional integration efforts under the SADC Protocol on Trade and the Industrialisation Strategy and Roadmap (2015–2063), which aim to reduce tariff and non-tariff barriers, improve cross-border infrastructure and harmonise trade regulations. By integrating road infrastructure improvements with these regional frameworks and complementary initiatives, such as the African Continental Free Trade Area (AfCFTA), member states can better translate trade openness into sustained economic growth. National-level policies that synchronise with regional objectives, such as targeted investment in trade corridors, coordinated customs reforms and macroeconomic stabilisation, can amplify the effectiveness of infrastructure in promoting economic performance.

Based on these insights, the study recommends that SADC policymakers prioritise coordinated investment in high-impact transport corridors, such as the North-South Corridor, while ensuring adequate maintenance funding for existing infrastructure. Harmonising customs procedures and border management systems across member states can further enhance trade efficiency. Additionally, adopting complementary macroeconomic policies, such as inflation control measures, employment generation strategies and targeted incentives for FDI, can maximise the economic benefits of improved road quality. Strengthening monitoring and evaluation frameworks for infrastructure projects will also help ensure that investments deliver long-term economic gains.

Overall, this study contributes to the discourse on leveraging road infrastructure quality to optimise trade integration and economic growth in the SADC region. The findings advocate for a holistic approach that combines infrastructure development with tailored domestic policies addressing macroeconomic and demographic factors.

Acknowledgements

This article is partially based on the author’s thesis entitled ‘Leveraging quality road infrastructure to optimize economic growth in Southern African Development Community countries’ toward the degree of Doctor of Philosophy in the School of Governance, University of the Witwatersrand, South Africa, with supervisor Prof. Kambidima Wotela, received 2025.

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

M.C.M. and K.W. have accepted responsibility for the entire content of this article, consented to its submission to the journal, reviewed all the results and approved the final version of the article.

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

Datasets generated and analysed during the development of this article are available within the article.

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