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Big data and predictive analytics and Malaysian micro-, small and medium businesses

Author

Listed:
  • Maya Vachkova

    (University of Exeter)

  • Arsalan Ghouri

    (Universiti Pendidikan Sultan Idris)

  • Haidy Ashour

    (Cairo University)

  • Normalisa Binti Md Isa

    (University Utara)

  • Gregory Barnes

    (Leeds Beckett University)

Abstract

Innovative technologies such as big data and predictive analytics are facilitating a global revolution in operational management. The present study aims to investigate the extent of their adoption among micro-, small and medium enterprises. The context of choice is Malaysia—a growing economy hosting some of the relatively more technologically advanced enterprises in ASEAN union. The research plan of the present paper pursued three objectives. First, we aimed to identify the general rate of adoption of BDPA. Second, we explored the most common uses of this set of innovations in Malaysian micro-, small, and medium enterprises. Third, we strove to abstract the antecedents and consequences of BDPA in micro-, small, and large firms in the manufacturing and service sectors. We discovered that BDPA are almost never used to outsource suppliers or to optimise spending and purchasing. Conversely, the most frequent applications of BDPA are in customer relationship management and in warehouse and operations improvement. Moreover, we smaller firms are more resilient to the challenges of adopting BDPA than their smaller and larger counterparts. Thus, this paper presents a snapshot of the BDPA dissemination in the micro-, small and medium ecosystem in Malaysia in 2021, while exploring opportunities for the future development and dissemination of this set of innovations.

Suggested Citation

  • Maya Vachkova & Arsalan Ghouri & Haidy Ashour & Normalisa Binti Md Isa & Gregory Barnes, 2023. "Big data and predictive analytics and Malaysian micro-, small and medium businesses," SN Business & Economics, Springer, vol. 3(8), pages 1-28, August.
    • Handle: RePEc:spr:snbeco:v:3:y:2023:i:8:d:10.1007_s43546-023-00528-y
    DOI: 10.1007/s43546-023-00528-y
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