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An Empirical Investigation of Analytics Capabilities in the Supply Chain

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Smart Business: Technology and Data Enabled Innovative Business Models and Practices (WeB 2019)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 403))

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Abstract

This study conceptually develops the construct of Supply Chain Analytics Capability. Preliminary analysis of survey data collected from more than 100 firms in India supports several hypotheses relating supply chain analytics architecture modularity and decentralized governance, in a moderating manner, with Supply Chain Analytics Capability. The capability creation path model suggested in this study establishes the antecedents of Supply Chain Analytics Capability and is helpful to firms seeking to develop such a capability.

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Author information

Authors and Affiliations

  1. Prairie View A&M University, 700 University Drive, Prairie View,, TX 77446, USA

    Thiagarajan Ramakrishnan

  2. Indian School of Business, Hyderabad, Telangana, India

    Abhishek Kathuria

  3. University of Colorado Denver, 1475 Lawrence Street, Denver, CO, USA

    Jiban Khuntia

Authors
  1. Thiagarajan Ramakrishnan
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  2. Abhishek Kathuria
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  3. Jiban Khuntia
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Editor information

Editors and Affiliations

  1. Baruch College, New York, NY, USA

    Karl R. Lang

  2. Bentley University, Waltham, MA, USA

    Jennifer Xu

  3. Oregon State University, Corvallis, OR, USA

    Bin Zhu

  4. University of Utah, Salt Lake City, UT, USA

    Xiao Liu

  5. University of Illinois, Champaign, IL, USA

    Michael J. Shaw

  6. Georgia Institute of Technology, Atlanta, GA, USA

    Han Zhang

  7. University of Washington, Seattle, WA, USA

    Ming Fan

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Ramakrishnan, T., Kathuria, A., Khuntia, J. (2020). An Empirical Investigation of Analytics Capabilities in the Supply Chain. In: Lang, K.R., et al. Smart Business: Technology and Data Enabled Innovative Business Models and Practices. WeB 2019. Lecture Notes in Business Information Processing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-030-67781-7_6

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  • DOI: https://doi.org/10.1007/978-3-030-67781-7_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-67780-0

  • Online ISBN: 978-3-030-67781-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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