IDEAS home Printed from https://ideas.repec.org/a/bla/popmgt/v27y2018i10p1745-1748.html
   My bibliography  Save this article

Big Data in Supply Chain Management

Author

Listed:
  • Nada R. Sanders
  • Ram Ganeshan

Abstract

“Big data” has become ubiquitous. It is impacting every aspect of how companies organize and manage their supply chains. Supply chains are evolving into digital networks connected via devices and sensors revolutionizing how data is generated, shared, and communicated. It is also unlocking new research streams. In this study, we introduce papers in this issue and showcase Big Data research trends across supply chain management.

Suggested Citation

  • Nada R. Sanders & Ram Ganeshan, 2018. "Big Data in Supply Chain Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1745-1748, October.
  • Handle: RePEc:bla:popmgt:v:27:y:2018:i:10:p:1745-1748
    DOI: 10.1111/poms.12892
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/poms.12892
    Download Restriction: no

    File URL: https://libkey.io/10.1111/poms.12892?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tiwari, Sunil & Sharma, Pankaj & Choi, Tsan-Ming & Lim, Andrew, 2023. "Blockchain and third-party logistics for global supply chain operations: Stakeholders’ perspectives and decision roadmap," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 170(C).
    2. Cynthia Hardy & Vikram Bhakoo & Steve Maguire, 2020. "A New Methodology for Supply Chain Management: Discourse Analysis and its Potential for Theoretical Advancement," Journal of Supply Chain Management, Institute for Supply Management, vol. 56(2), pages 19-35, April.
    3. Sushil Gupta & Medha Tekriwal & Carlos M. Parra, 2022. "Permeation of the term “analytics” in production and operations management research," Production and Operations Management, Production and Operations Management Society, vol. 31(10), pages 3651-3667, October.
    4. Eva Labro & Mark Lang & Jim Omartian, 2019. "Predictive Analytics and Organizational Architecture: Plant-Level Evidence from Census Data," Working Papers 19-02, Center for Economic Studies, U.S. Census Bureau.
    5. Xiangyu Chang & Yinghui Huang & Mei Li & Xin Bo & Subodha Kumar, 2021. "Efficient Detection of Environmental Violators: A Big Data Approach," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1246-1270, May.
    6. Görkem Sariyer & Mustafa Gokalp Ataman & Sachin Kumar Mangla & Yigit Kazancoglu & Manoj Dora, 2023. "Big data analytics and the effects of government restrictions and prohibitions in the COVID-19 pandemic on emergency department sustainable operations," Annals of Operations Research, Springer, vol. 328(1), pages 1073-1103, September.
    7. Lu (Lucy) Yan, 2020. "The Kindness of Commenters: An Empirical Study of the Effectiveness of Perceived and Received Support for Weight‐Loss Outcomes," Production and Operations Management, Production and Operations Management Society, vol. 29(6), pages 1448-1466, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:popmgt:v:27:y:2018:i:10:p:1745-1748. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1937-5956 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.