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Business Intelligence in African Small and Medium Enterprises: A Systematic Literature Review
| Nome: | Descrição: | Tamanho: | Formato: | |
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| 1.42 MB | Adobe PDF |
Orientador(es)
Resumo(s)
The adoption of Business Intelligence (BI) by Small and Medium Enterprises (SMEs) in Africa is
an emerging trend with promising potential. However, African SMEs face unique and often
overlooked challenges not commonly encountered in more developed economies, such as
infrastructural limitations, financial constraints, and inadequate institutional support. This
systematic literature review aims to assess the current state of BI adoption among African
SMEs, identify the primary barriers to implementation, and highlight contextual factors that
influence the integration and use of BI tools. Following the PRISMA 2020 guidelines, a
structured search strategy using Boolean logic was conducted across multiple academic
databases and registers. After applying inclusion and exclusion criteria focused on empirical
studies, a final sample of 32 peer-reviewed journal articles was selected for analysis. Findings
indicate that while there is a growing interest in BI adoption among African SMEs, several
critical challenges persist. These include limited financial resources, unstable internet
connectivity, insufficient government support, inadequate digital infrastructure, and a lack of
skilled personnel. Despite these obstacles, the literature affirms that BI holds significant
promise for improving SME competitiveness, market resilience, and sustainable growth. BI
adoption in African SMEs remains a complex and uneven process, with no universal
framework applicable across all contexts. Country-specific disparities and government
inaction in areas such as digital literacy and resource provision continue to hinder widespread
adoption. Nevertheless, BI represents a strategic enabler for SME growth and integration into
global markets. Future research should aim to expand the geographic scope of analysis,
address sector-specific implementation barriers, and explore practical frameworks tailored to
the diverse realities of African SMEs.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Data Driven Marketing, specialization in Marketing Intelligence
Palavras-chave
Business Intelligence Competitive Intelligence Knowledge Management African Small and Medium Enterprises SDG 8 - Decent work and economic growth SDG 9 - Industry, innovation and infrastructure