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Data Mining and SME Growth: Exploring Evidence from Ghana
Joseph ADJEI, Daniel Asamoah, Bismark Adjei-Acheampong, Peter Tobbin
In developing economies, Small and Medium Enterprises (SMEs) have emerged as central pillars of growth and innovation, propelled by evolving market dynamics. Among these innovations, data analytics has distinguished itself as a pivotal force driving SME development, enabling these businesses to boost operational efficiency. This exploration delves into the application of data mining within the context of SMEs, specifically examining the catalysts for the adoption of Data Mining Systems (DMS) and assessing their impact on the advancement of SMEs. This research aims to unravel the intricate motivations behind SMEs' incorporation of DMS into their operational frameworks, spotlighting both the opportunities unleashed and the challenges encountered. It accentuates the transformative role of data analytics in demystifying complex business landscapes, converting extensive datasets into actionable intelligence. Moreover, the study emphasizes the need for proficient data analysts who can shepherd SMEs through the digital transition, ensuring the effectiveness of these technological solutions (Venkatesh et al., 2003).
Leveraging data from a fashion enterprise based in Ghana, this qualitative inquiry solicited insights from employees interacting with the firm's DMS. The investigation centered on three pivotal questions regarding the adoption, duration, and motivations behind integrating DMS. Through an interpretive methodology, leveraging the Unified Theory of Acceptance and Use of Technology (UTAUT) as a theoretical lens, the study analyzed interview data to unearth established and emergent factors influencing the use of DMS (Walsham, 2006). A thematic analysis of the responses highlighted key attributes affecting DMS adoption.
Initial findings reveal the profound advantages DMS proffers to SMEs in decision-making. However, the study also uncovers impediments, such as lack of awareness regarding data mining technologies among SME personnel and the acute necessity for qualified data analysts to lead DMS adoption efforts effectively. By synthesizing insights from existing literature with empirical observations, this research offers a nuanced perspective on the dynamics steering DMS adoption within SMEs, enriching the broader dialogue on leveraging data analytics to spur business growth in the developing world (Venkatesh et al., 2016).
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