Relationship between Determinants of Financial Assistance and Credit Accessibility of Small and Medium-Enterprises (SME’s): A Case Study of SME’s in Takoradi Metropolis in the Western Region of Ghana

Abstract

In Ghana and other countries' economies, small and medium scale enterprises (SME's) play a principal role that significantly impacts economic stability. SMEs contribute prominently to the economy by creating more noteworthy work openings, making higher creation volumes, growing conveys and introducing progression and business capacities. This study used a sample of 336 SMEs out of 500 SME's located in the Western Region (Takoradi Metropolis). These SMEs data were obtained using questionnaire in which its instrument was validated by experts in the field of finance and was administered to the respondents. Primary data were obtained to assess the determinants of financial assistance available to SME's in Ghana (Takoradi Metropolis). Strategies were used to obtain the outcome of the result, such as ANOVA (analysis of variance), regression analysis, and descriptive statistics to analyze the relationship between the determinants of financial assistance and SMEs' credit accessibility. It showed that firm's age, size, performance, and collateral security all have a positive impact that determines financial assistance to the credit accessibility of SMEs in Takoradi Metropolis. The research discovers enough information that confirms critical factors that push the credit accessibility available to SME's. It can be recommended that the availability of credit opportunities to SME's in the form of loans should be given a maximum consideration.

Unleashing Potential: Overcoming Bottlenecks and Catalyzing Innovations in Intellectual Capital Intellectualization of Small and Medium-Sized Enterprises in Jiangsu During the Post-Industrial Era

“…By examining the interactions between the environment, the economy, and sustainable development, this study intends to give insight on the complexities of achieving environmental sustainability in key sectors (Ahakwa et al, 2023; Ahmed et al, 2022; Xu & Li, 2020). Prior studies have demonstrated that this sampling methodology is accurate and provides reliable outcomes (Cobbinah et al, 2020; Kir et al, 2021; Owusu et al, 2022; Sappor et al, 2023; F. A. Sarpong et al, 2022, 2023).…”

“…Using t-statistics and path coefficient values, bootstrapping was applied to evaluate the relevance of the linkages between model components and the strength of associations between these structures. For a t-statistic to be considered significant, it should exceed the threshold of 1.96 (Chin et al, 2018). Our analysis incorporated multiple evaluation metrics, including adjusted R2, Q2, and F2, to assess the effectiveness and accuracy of our proposed models.…”