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Establishing the use of cloud computing in supply chain management

Author

Listed:
  • Qing Cao

    (University of Houston-Downtown)

  • Dara G. Schniederjans

    (University of Rhode Island)

  • Marc Schniederjans

    (University of Nebraska-Lincoln)

Abstract

Despite having various benefits associated with greater information flow in the supply chain, empirical cloud computing research is scarce in the supply chain management domain. This paper explores the managerial perceptions on the use of cloud computing in supply chain management. Specifically, this paper seeks to address: how cloud computing impacts information sharing among supply chain partners, the impact of trust in cloud information sharing and the impact of cloud computing on supply chain performance. Using a multi-method research design we present a combined semi-structured interviews of four different companies in the United States and a survey to analyze and empirically assess our results. Structural equation modeling was used to analyze the results of this study. Our analysis provides empirical support based on managerial perceptions regarding cloud computing, information sharing and supply chain performance. The data provide evidence on the impact of cloud computing in enhancing information sharing. This information sharing through cloud computing appears to positively impact supply chain performance. This paper also provides support on the important role of inter-organizational trust in facilitating the use of cloud computing for information sharing purposes.

Suggested Citation

  • Qing Cao & Dara G. Schniederjans & Marc Schniederjans, 2017. "Establishing the use of cloud computing in supply chain management," Operations Management Research, Springer, vol. 10(1), pages 47-63, June.
    • Handle: RePEc:spr:opmare:v:10:y:2017:i:1:d:10.1007_s12063-017-0123-6
    DOI: 10.1007/s12063-017-0123-6
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    References listed on IDEAS

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    Cited by:

    1. Schniederjans, Dara G. & Curado, Carla & Khalajhedayati, Mehrnaz, 2020. "Supply chain digitisation trends: An integration of knowledge management," International Journal of Production Economics, Elsevier, vol. 220(C).
    2. Shahriar Akter & Katina Michael & Muhammad Rajib Uddin & Grace McCarthy & Mahfuzur Rahman, 2022. "Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics," Annals of Operations Research, Springer, vol. 308(1), pages 7-39, January.
    3. A. V. Thomas & Biswajit Mahanty, 2021. "Dynamic assessment of control system designs of information shared supply chain network experiencing supplier disruption," Operational Research, Springer, vol. 21(1), pages 425-451, March.
    4. Osterrieder, Philipp & Budde, Lukas & Friedli, Thomas, 2020. "The smart factory as a key construct of industry 4.0: A systematic literature review," International Journal of Production Economics, Elsevier, vol. 221(C).
    5. Chau Thi Diem Le & Miklós Pakurár & István András Kun & Judit Oláh, 2021. "The impact of factors on information sharing: An application of meta-analysis," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-24, December.
    6. Puneeta Ajmera & Vineet Jain, 2019. "Modelling the barriers of Health 4.0–the fourth healthcare industrial revolution in India by TISM," Operations Management Research, Springer, vol. 12(3), pages 129-145, December.
    7. Andrea Ferrari & Giulio Mangano & Anna Corinna Cagliano & Alberto De Marco, 2023. "4.0 technologies in city logistics: an empirical investigation of contextual factors," Operations Management Research, Springer, vol. 16(1), pages 345-362, March.
    8. Xiaozhen Wang & Ki-Hyun Um & Shu Wang & Mingu Kang, 2023. "The mediating role of key supplier adaptability and involvement in the relationship between supplier relationship management and NPD project success," Operations Management Research, Springer, vol. 16(2), pages 794-807, June.

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