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Barriers to big data analytics (BDA) implementation in manufacturing supply chains

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  • Amirhossein Dehkhodaei
  • Bahar Amiri
  • Hasan Farsijani
  • Abbas Raad

Abstract

Big data analysis (BDA) can increase the capability of supply chain analysis of manufacturing companies. Therefore, many manufacturing companies want to use BDA, but it has been seen that BDA implementation is difficult, especially in developing countries due to the existence of various barriers related to finance, government regulations, etc. This paper aims to investigate the barriers to BDA implementation in Iranian companies. In literature, limited work has been done on identifying barriers to implementing BDA in developing countries. In this regard, 34 barriers were identified to BDA adoption in Iran by employing a literature review and feedback received from experts. Then, the most important barriers (14) were analyzed using integrated Interpretive Structural Modeling and MICMAC approach. Results show that two barriers; namely, lack of sufficient knowledge of senior managers and weakness of governance policies, are the most significant. Finally, crucial policy measures and recommendations are proposed to assist managers and government bodies.

Suggested Citation

  • Amirhossein Dehkhodaei & Bahar Amiri & Hasan Farsijani & Abbas Raad, 2023. "Barriers to big data analytics (BDA) implementation in manufacturing supply chains," Journal of Management Analytics, Taylor & Francis Journals, vol. 10(1), pages 191-222, January.
    • Handle: RePEc:taf:tjmaxx:v:10:y:2023:i:1:p:191-222
    DOI: 10.1080/23270012.2023.2179430
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    Cited by:

    1. Md Mehedi Hasan Emon & Golam Mustafa MD. Nurullah Rabbani & Avishek Nath, 2023. "Challenges And Opportunities In The Implementation Of Big Data Analytics In Management Information Systems In Bangladesh," Acta Informatica Malaysia (AIM), Zibeline International Publishing, vol. 7(2), pages 122-130, September.
    2. Zhao, Guoqing & Xie, Xiaotian & Wang, Yi & Liu, Shaofeng & Jones, Paul & Lopez, Carmen, 2024. "Barrier analysis to improve big data analytics capability of the maritime industry: A mixed-method approach," Technological Forecasting and Social Change, Elsevier, vol. 203(C).

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