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Archetypes of Supply Chain Analytics Initiatives—An Exploratory Study

Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany
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Logistics 2018, 2(2), 10; https://doi.org/10.3390/logistics2020010
Received: 27 March 2018 / Revised: 23 April 2018 / Accepted: 2 May 2018 / Published: 8 May 2018
(This article belongs to the Special Issue Data Governance Issues for a Digital Economy)
While Big Data and Analytics are arguably rising stars of competitive advantage, their application is often presented and investigated as an overall approach. A plethora of methods and technologies combined with a variety of objectives creates a barrier for managers to decide how to act, while researchers investigating the impact of Analytics oftentimes neglect this complexity when generalizing their results. Based on a cluster analysis applied to 46 case studies of Supply Chain Analytics (SCA) we propose 6 archetypes of initiatives in SCA to provide orientation for managers as means to overcome barriers and build competitive advantage. Further, the derived archetypes present a distinction of SCA for researchers seeking to investigate the effects of SCA on organizational performance. View Full-Text
Keywords: supply chain analytics; business analytics; cluster analysis supply chain analytics; business analytics; cluster analysis
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MDPI and ACS Style

Herden, T.T.; Bunzel, S. Archetypes of Supply Chain Analytics Initiatives—An Exploratory Study. Logistics 2018, 2, 10. https://doi.org/10.3390/logistics2020010

AMA Style

Herden TT, Bunzel S. Archetypes of Supply Chain Analytics Initiatives—An Exploratory Study. Logistics. 2018; 2(2):10. https://doi.org/10.3390/logistics2020010

Chicago/Turabian Style

Herden, Tino T., and Steffen Bunzel. 2018. "Archetypes of Supply Chain Analytics Initiatives—An Exploratory Study" Logistics 2, no. 2: 10. https://doi.org/10.3390/logistics2020010

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