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Why Does It Fail? A Systematic Review of End-Users’ Challenges in Business Intelligence

Author

Listed:
  • Mohd Mustafa Alfariz

    (Faculty of Business and Management, Universiti Teknologi MARA, Shah Alam, Malaysia)

  • Ariff Md Ab Malik

    (Faculty of Business and Management, Universiti Teknologi MARA, Shah Alam, Malaysia)

  • Anitawati Mohd Lokman

    (College of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Shah Alam, Malaysia)

Abstract

Business Intelligence (BI) has become an essential tool for modern organisations, facilitating strategic decision-making through data analysis and actionable insights. Despite extensive research on organisational challenges, there is a gap in understanding the adoption and usage barriers at the individual level. Following the PRISMA 2020 protocol, this systematic literature review includes empirical studies from Scopus and Web of Science, published between 2021 and September 2024. Using automation and qualitative methods, 18 documents were selected, identifying 12 themes across three domains: technology, individual, and organisation. The study reveals the interconnected nature of these determinants, with some acting as antecedents or precedents to others. Subsequent research should delve into external influences on users and other understudied factors. This review offers comprehensive insights into the multifaceted challenges faced by end-users, offering valuable guidance for researchers and practitioners in successful BI implementation.

Suggested Citation

  • Mohd Mustafa Alfariz & Ariff Md Ab Malik & Anitawati Mohd Lokman, 2024. "Why Does It Fail? A Systematic Review of End-Users’ Challenges in Business Intelligence," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(11), pages 304-315, November.
    • Handle: RePEc:bcp:journl:v:8:y:2024:i:11:p:304-315
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    References listed on IDEAS

    as
    1. Zhang, Yucheng & Xu, Shan & Zhang, Long & Yang, Mengxi, 2021. "Big data and human resource management research: An integrative review and new directions for future research," Journal of Business Research, Elsevier, vol. 133(C), pages 34-50.
    2. Maria José Sousa & Ivo Dias, 2020. "Business Intelligence for Human Capital Management," International Journal of Business Intelligence Research (IJBIR), IGI Global, vol. 11(1), pages 38-49, January.
    3. Sascha Kraus & Matthias Breier & Sonia Dasí-Rodríguez, 2020. "The art of crafting a systematic literature review in entrepreneurship research," International Entrepreneurship and Management Journal, Springer, vol. 16(3), pages 1023-1042, September.
    4. Junwen Zhu & Weishu Liu, 2020. "A tale of two databases: the use of Web of Science and Scopus in academic papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 321-335, April.
    5. Reinking, Jeff & Arnold, Vicky & Sutton, Steve G., 2020. "Synthesizing enterprise data to strategically align performance: The intentionality of strategy surrogation," International Journal of Accounting Information Systems, Elsevier, vol. 36(C).
    Full references (including those not matched with items on IDEAS)

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