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Big data analytics adoption: an empirical study in the Malaysian warehousing sector

Author

Listed:
  • Siti Norida Wahab
  • Muhammad Iskandar Hamzah
  • Nazura Mohamed Sayuti
  • Wei Chern Lee
  • Say Yik Tan

Abstract

This paper aims to identify the factors affecting big data analytics (BDA) adoption in the Malaysian warehousing sector. The technology-organisation-environment (TOE) model serves as the underpinning framework. The survey data from 110 logistics firms were collected and analysed using PLS-SEM. The empirical results revealed that relative advantage, technological infrastructure, absorptive capability and government support influence the levels of BDA adoption, whilst industry competition appeared to be of no significant influence. This study is expected to facilitate warehousing firms in implementing the most appropriate strategies in adopting BDA. Warehousing firms that place great emphasis on operational superiority, ICT infrastructures, and technology assimilation, are more likely to adopt BDA. Considering that there is a paucity of evidence regarding the determinants of BDA adoption among Malaysian warehousing firms, this study enriches TOE-based literature on BDA. Furthermore, the findings potentially assist logistics practitioners in developing a holistic blueprint in managing their large data sets.

Suggested Citation

  • Siti Norida Wahab & Muhammad Iskandar Hamzah & Nazura Mohamed Sayuti & Wei Chern Lee & Say Yik Tan, 2021. "Big data analytics adoption: an empirical study in the Malaysian warehousing sector," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 40(1), pages 121-144.
    • Handle: RePEc:ids:ijlsma:v:40:y:2021:i:1:p:121-144
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    Citations

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    Cited by:

    1. Abdalwali Lutfi & Adi Alsyouf & Mohammed Amin Almaiah & Mahmaod Alrawad & Ahmed Abdullah Khalil Abdo & Akif Lutfi Al-Khasawneh & Nahla Ibrahim & Mohamed Saad, 2022. "Factors Influencing the Adoption of Big Data Analytics in the Digital Transformation Era: Case Study of Jordanian SMEs," Sustainability, MDPI, vol. 14(3), pages 1-17, February.
    2. Lutfi, Abdalwali & Alrawad, Mahmaod & Alsyouf, Adi & Almaiah, Mohammed Amin & Al-Khasawneh, Ahmad & Al-Khasawneh, Akif Lutfi & Alshira'h, Ahmad Farhan & Alshirah, Malek Hamed & Saad, Mohamed & Ibrahim, 2023. "Drivers and impact of big data analytic adoption in the retail industry: A quantitative investigation applying structural equation modeling," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    3. Abdalwali Lutfi & Akif Lutfi Al-Khasawneh & Mohammed Amin Almaiah & Ahmad Farhan Alshira’h & Malek Hamed Alshirah & Adi Alsyouf & Mahmaod Alrawad & Ahmad Al-Khasawneh & Mohamed Saad & Rommel Al Ali, 2022. "Antecedents of Big Data Analytic Adoption and Impacts on Performance: Contingent Effect," Sustainability, MDPI, vol. 14(23), pages 1-23, November.
    4. Jingmei Gao & Zahid Sarwar, 2024. "How do firms create business value and dynamic capabilities by leveraging big data analytics management capability?," Information Technology and Management, Springer, vol. 25(3), pages 283-304, September.

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