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Triad of Big Data Supply Chain Analytics, Supply Chain Integration and Supply Chain Performance: Evidences from Oil and Gas Sector

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  • Mobashar Mubarik
  • Raja Zuraidah binti Raja Mohd Rasi

Abstract

The objective of the paper is to examine the impact of big data supply chain analytics on supply chain performance. Second, study also examines the role of supply chain integration in the association between big data supply chain analytics and supply chain performance. The data were collected from 166 experts working in Oil and Gas Marketing companies. The experts were selected through expert sampling, a sub case of purposive sampling. We employed covariance based structural equation modeling to estimate the modelled relationships. The results of measurement model indicated the reliability, validity and fitness of measurement models. The findings of the study revealed a significant direct impact of big data supply chain analytics upon the five major dimensions of supply chain i.e., plan, supplier management, procurement management, make, and inventory management. Whereas the results did not show any effect of BDSCA on transportation management. Likewise, findings also revealed that distribution and network designing part of supply chain could be radically improved with the application of BDSCA. The study concludes that despite sea-potential of BDSCA in supply chain management field, the research work in this area is yet in infancy stage. Primarily, the research work aiming to know the level of BDSCA orientation and its application strategy requires immediate attention of the researchers and practitioners.

Suggested Citation

  • Mobashar Mubarik & Raja Zuraidah binti Raja Mohd Rasi, 2019. "Triad of Big Data Supply Chain Analytics, Supply Chain Integration and Supply Chain Performance: Evidences from Oil and Gas Sector," Humanities and Social Sciences Letters, Conscientia Beam, vol. 7(4), pages 209-224.
    • Handle: RePEc:pkp:hassle:v:7:y:2019:i:4:p:209-224:id:831
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    Citations

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    Cited by:

    1. Muhammad Noman Shafique & Ammar Rashid & Sook Fern Yeo & Umar Adeel, 2023. "Transforming Supply Chains: Powering Circular Economy with Analytics, Integration and Flexibility Using Dual Theory and Deep Learning with PLS-SEM-ANN Analysis," Sustainability, MDPI, vol. 15(15), pages 1-23, August.
    2. Kalaitzi, Dimitra & Tsolakis, Naoum, 2022. "Supply chain analytics adoption: Determinants and impacts on organisational performance and competitive advantage," International Journal of Production Economics, Elsevier, vol. 248(C).
    3. Sharfuddin Ahmed Khan & Muhammad Shujaat Mubarik & Simonov Kusi‐Sarpong & Himanshu Gupta & Syed Imran Zaman & Mobashar Mubarik, 2022. "Blockchain technologies as enablers of supply chain mapping for sustainable supply chains," Business Strategy and the Environment, Wiley Blackwell, vol. 31(8), pages 3742-3756, December.

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