This study aims to explore the adoption and utilization of data analytics tools by traditional fashion businesses in Ghana, focusing on the types of tools used, factors influencing adoption and challenges faced.
The study used purposive sampling to select 20 participants, including business owners and managers, for a semi-structured interview. This approach provided a detailed understanding of the technology adoption process within the sector.
Findings indicated that Ghanaian fashion businesses primarily use basic tools, such as social media analytics (Facebook Insights, Instagram Analytics), for inventory management and customer trend analysis. Barriers such as limited technical expertise, financial constraints and resistance to change hinder the widespread adoption of advanced analytics tools.
This study is limited by its qualitative design and relatively small sample of 20 participants, which may constrain generalizability beyond Ghana’s traditional fashion sector. The reliance on self-reported data may also introduce response bias. However, the study provides rich, contextual insights and offers a foundation for future research. Subsequent studies could adopt mixed-methods or quantitative approaches to test and extend the proposed relationships, as well as conduct comparative studies across countries or creative industries to enhance generalizability and theoretical development.
The findings provide actionable guidance for traditional fashion businesses and support institutions. Entrepreneurs should adopt a phased approach to analytics, starting with simple tools before progressing to advanced systems. Policymakers and agencies should invest in digital infrastructure, subsidize access to analytics tools and provide targeted training programs. Industry associations can develop hands-on workshops and mentorship platforms to improve digital skills and reduce technological anxiety, thereby enhancing adoption and effective utilization.
The study highlights the role of data analytics in promoting digital inclusion, economic empowerment and sustainability within Ghana’s traditional fashion sector. Increased adoption can enhance business performance, create employment opportunities and improve market access for artisans. By enabling more efficient production and customer engagement, analytics can also support the preservation and modernization of cultural heritage industries, contributing to inclusive economic growth and resilience in developing economies.
This study offers contextual originality by examining data analytics adoption within Ghana’s traditional fashion industry, a largely underexplored, craft-based sector. It extends existing models (Technology Acceptance Model/Organizational Technology Acceptance Model) by incorporating socio-cultural and infrastructural factors such as technological anxiety and resource constraints. The study also conceptualizes adoption as a continuum rather than a binary outcome, providing nuanced insights into varying levels of utilization and their implications. These contributions enhance understanding of technology adoption in heritage-based SMEs within developing economy contexts.
