In the global construction industry, small and medium-sized enterprises (SMEs) are the foundation of economic growth ( World Bank, 2020 ). Notably, SMEs play a vibrant role in the construction industry of emerging economies ( World Economic Forum, 2016 ). Construction SMEs account for 56% of private employment and 36% of South Africa’s GDP; and in Sierra Leone it employs 95% of the labor work force ( Berry et al., 2002 ). In Nigeria’s construction industry, SMEs account for 28% of its GDP ( Usman & Alaezi, 2016 ). According to Amoah et al. (2011) , SMEs in Ghana constitute over 90% of all contractors in the construction industry.

Owing to the critical role SMEs play in emerging economies and the potential to deliver high-level construction projects, it is imperative to explore measures and factors that can guide SMEs in the construction sector to survive and grow ( Asante et al., 2017 ). Nonetheless, most studies continue to discover that, SMEs underperform in terms of project delivery and are usually confronted with the risk of collapse, with statistics showing that sixty percent of them fail within the first few years ( Kristanti et al., 2019 ). The survival of SMEs in developing economies is typically hampered by numerous limitations. One key variable identified from extant literature is the lack of capacities of indigenous SMEs in emerging economies to compete with foreign competitors ( Asante et al., 2017 ; Offei et al., 2019 ).

In developing economies, considerable number of studies have emerged on SMEs. For example, studies have investigated the opportunities for SMEs in developing nations ( Humphrey, 2003 ), the challenges that SMEs face ( Ametepey et al., 2022 ; Offei et al., 2019 ; Thwala & Phaladi, 2009 ), the critical success factors for managing SMEs ( Sarvari et al., 2021 ), the capacity needs of SMEs ( Asante et al., 2017 ), the contributions of SMEs to sustainable development ( Faki, 2021 ), and the role of SMEs in economic development ( Usman & Alaezi, 2016 ). Gancarczyk et al. (2021) employed the theoretical lenses of RBV to understand growth phenomena of SMEs. North et al. (2020) proposed a theoretical framework to guide SMEs to leverage on digitally enabled growth opportunities, as well project-based learning in order to remain competitive in turbulent environments.

While these prior studies provide useful insights, it is also apparent construction SMEs in emerging economies still lack the requisite capacity to be competitive ( Strategy & Research Dept, 2023 ). The problem resides in the fact that, preponderances of the prevailing research on SMEs examined the capacity building mechanisms based on linearity assumptions and as if they existed completely in isolation. In reality, however, such linearity assumption is hardly meaningful in explaining the dynamic and interrelated behaviour of the mechanisms for building the capacity of SMEs. A study that offers an inclusive picture and understanding of the capacity building mechanisms of SMEs is still missing in the literature. Consequently, there are no comprehensive frameworks for building the capacities SMEs in the literature.

Hence, this study provides a unified model of Keynesian theory of job creation, scientific management theory, and Resource Based View theory (KBV) to explain how the capacity of SMEs can be enhanced to make them competitive. The findings to this aim provide a new theoretical lens on how construction SMEs can be empowered.

This section presents the PLS-SEM results that guided the framing of the capacity building model. The Reliability and Validity Measures of the PLS-SEM, Discriminant Validity using Cross loadings, Path Coefficients and Test of Significance, Diagram for the Measurement Assessment and the Path Coefficient and Significance are presented in Tables 3-5 and Figures 1-2 respectively.

Evaluation of Measurement Models

In Table 3 , the factor loading of the measurement item JP4 (Subcontracting) was lower than 0.50. Hence, it was deleted from the list of measurement items. As can also be seen in Table 3 , all of the Cronbach’s alpha coefficients and composite reliability scores of the included variables were greater than 0.70, indicating that the measurement items had adequate internal consistency reliability. Furthermore, all factor loadings and average variance extracted (AVEs) were greater than 0.50, indicating that the constructs were convergently valid.

CA: Cronbach’s Alpha, CR: Composite Reliability and AVE: Average Variance Extracted. Source: Authors own work.

As indicated in Table 4 , no correlation between any two constructs exceeded the square roots of their AVEs, demonstrating the prime evidence of discriminant validity of the constructs.

Source: Authors own work.

Examining the cross loadings of the measurement items provides additional evidence of discriminant validity. There is no cross-loading concern, as each measurement item had the maximum loading on its related construct, as shown in Table 5 . These findings show that the measurement models were reliable and valid for the structural path modeling.

Source: Authors own work.

Evaluation of Structural Model

Table 6 , Figures 2 and 3 show the bootstrapping results for the capacity building model. The findings suggest that the path linking the path linking “Job creation policy for SMEs” (JP) to capacity building (CB) had a t-statistics = 3.139; p value = 0.090), implying that, at the 0.05 level, it was statistically significant. Therefore, hypothesis H1 was supported. Similarly, the path linking “Enhancing SMEs Business management practices” (BM) to capacity building (CB) t-statistics = 2.293; p value = 0.022), indicating that it was statistically significant at the 0.05 level. Hence H2 was supported. Likewise, the path linking the path linking “Building the resource capabilities of SMEs” (RC) to capacity building (CB) had a t-value (2.315) with corresponding p-value (0.021) and hence H3, was supported. Finally, the path linking “capacity building” (CB) to SMEs performance/competitiveness (PC) had a t-value (10.693) greater than 1.96, implying that it was statistically significant at the 0.05 level. Therefore, hypothesis H4 is also supported.

Source: Authors own work.

The results show that the path linking “Job creation policy for SMEs” to capacity building had a t-value (3.139) greater than 1.96, implying that it was statistically significant at the 0.05 level. Therefore, hypothesis H1 is supported. This finding suggests a deliberate policy to create jobs of SMEs can impact their capacity developments. The capacity of SMEs can be enhanced if they have frequent access to jobs through contract reservations, and also through Joint ventures between large contractors and SMEs.

Likewise the results show that the path linking “Enhancing SMEs business management practices” to capacity building had a t-value (2.293) greater than 1.96, implying that it was statistically significant at the 0.05 level. Therefore, hypothesis H2 is also supported. To enhance their capacities, SMEs must begin to apply scientific analysis to optimize workflows, adopt efficient administrative and site management practices, leverage technology and modern equipment & plants to enhance productivity, practice proper material management, conduct job and practice analysis, competency modelling and workforce planning.

Furthermore, the path linking “Building the resource capabilities of SMEs” to capacity building had a t-value (2.315) greater than 1.96, implying that it was statistically significant at the 0.05 level. Therefore, hypothesis H3 is also supported. The capacities of SMEs can be enhanced by SMEs access to plants and equipment, access to competent human capital, and providing training to improve worker efficiency. The resource capabilities of SMEs could also be improved by an SMEs development fund (Government backed funds to support the growth of SMEs), Asset-Based financing, Mobilization, Government grants and loans, Payment security of SMEs (Ensure Prompt payment to SMEs for contract executed). SMEs could also enhance their capacities by forming alliances and partnerships ( Guribie et al., 2024 ), and building on past experience.

Finally, the path linking “capacity building” to SMEs performance/competitiveness had a t-value (10.693) greater than 1.96, implying that it was statistically significant at the 0.05 level. Therefore, hypothesis H4 is also supported. This finding implies that when the capacity of SMEs (Technical/HR Capacity, Operational Efficiency Social Capital, Financial capabilities and Business management capabilities) is enhanced, this would translate into performance and competitiveness of SMEs (Time performance, Cost performance, Quality performance, Revenue and Profit Margin, Productivity, and Growth and expansion).

The findings confirm that job creation policies, improved business management practices, and enhanced resource capabilities are significant predictors of SME capacity. By applying Keynesian principles in the construction sector, governments can create jobs, stimulate the growth, and capacity needs of SMEs. Likewise, scientific management principles can be applied by SMEs in emerging economies to build the capacity of their workforce by enhancing their skills, knowledge, and productivity ( Millers & Gaile-Sarkane, 2021 ). SMEs can also achieve sustainable competitive advantage by identifying and investing in valuable, rare, and imperfectly imitable resources ( Mady et al., 2023 ). These, in turn will drive the performance and competitiveness of SMEs in emerging economies.

SME job creation Policy, Building the resource capabilities of SMEs, Enhancing SMEs Business management practices were found as measures when instituted can enhance the operations of SMEs in Ghana. These variables have positive effects on capacity building, and consequently the performance of SMEs. The foregoing became the basis of conceptualizing and proposing a unified capacity building framework for construction SMEs. A relationship of themes and theories of the framework is presented in Figure 4 .

Discussion of the Proposed Capacity Building model

To build the capacities of SMEs to enhance their performance and competitiveness, the current study proposes a three phased capacity building framework for construction SMEs: a job creation policy for SMEs, building the resource capabilities of SMEs and enhancing SMEs’ business management practices.

Develop an SME job creation Policy

The first enabler to build capacity of construction SMEs in developing economies is the creation of an SME job creation policy. This entails SMEs’ frequent access to jobs, reservation of large proportion of government contracts for SMEs and joint ventures between large contractors and SMEs.

Building the resource capabilities of SMEs

Having instituted an SME job creation policy, another important enabler is building the resource capabilities of SMEs. This entails SMEs’ access to diverse resources such human, technical, financial and social capital.

Enhancing SMEs Business management practices

The final enabler is to enhance SMEs’ business management practices. Business management practices in this context entails efficient administrative and site management practices through scientific management principles.

Outcomes/Impact of the processes

When these three principles (job creation policy for SMEs, building the resource capabilities of SMEs and enhancing SMEs business management practices) are initiated, the prime benefits would be an increase in SMEs’ Technical/HR Capacity, SMEs’ Operational Efficiency, Social Capital, the financial capabilities of SMEs and SMEs’ business management capabilities. The ultimate outcome would be improved performance and competitiveness of construction SMEs in developing economies.

There is no comprehensive capacity building framework for construction SMEs in the literature. Hence, this study provides a unified model of the Keynesian job creation theory, RBV theory and scientific management theory to explain how the capacity of SMEs can be enhanced to make them competitive. The main research question addressed in this study is: “How can the capacities of construction SMEs in developing economies be enhanced to improve their performance and competitiveness?” This research question was answered from the empirical study of 120 construction SMEs in the Ghanaian construction industry. The findings demonstrated that, building the capacities of construction SMEs in emerging economies involves three thematic phases viz.: a job creation policy for SMEs, building the resource capabilities of SMEs and enhancing SMEs business management practices.