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Predictive Procurement Insights: B2B Business Network Contribution to Predictive Insights in the Procurement Process Following a Design Science Research Approach

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Designing the Digital Transformation (DESRIST 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10243))

Abstract

Significant recent developments in the domain of big data analytics provide the basis for leveraging predictive procurement insights in the procurement process. Following the path of other business domains, B2B business networks now have the potential to fill the gap of providing sufficient data for predictive technologies to be applied to the procurement domain, opening the door for significant efficiency gains. Based on the conceptual framework of the procurement process the methodology of design science research is applied to analyze prototype dashboards that leverage available data from B2B business networks.

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Author information

Authors and Affiliations

  1. Business School, University of Mannheim, 68131, Mannheim, Germany

    Jan Gruenen & Christoph Bode

  2. Sam M. Walton College of Business, University of Arkansas, Fayetteville, AR, 72701, USA

    Hartmut Hoehle

Authors
  1. Jan Gruenen
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  2. Christoph Bode
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  3. Hartmut Hoehle
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Corresponding author

Correspondence to Christoph Bode .

Editor information

Editors and Affiliations

  1. Karlsruhe Institute of Technologie (KIT) , Karlsruhe, Germany

    Alexander Maedche

  2. University of Liechtenstein , Vaduz, Liechtenstein

    Jan vom Brocke

  3. University of South Florida , Tampa, Florida, USA

    Alan Hevner

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Gruenen, J., Bode, C., Hoehle, H. (2017). Predictive Procurement Insights: B2B Business Network Contribution to Predictive Insights in the Procurement Process Following a Design Science Research Approach. In: Maedche, A., vom Brocke, J., Hevner, A. (eds) Designing the Digital Transformation. DESRIST 2017. Lecture Notes in Computer Science(), vol 10243. Springer, Cham. https://doi.org/10.1007/978-3-319-59144-5_16

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  • DOI: https://doi.org/10.1007/978-3-319-59144-5_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59143-8

  • Online ISBN: 978-3-319-59144-5

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