Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-8923
Main Title: Archetypes of Supply Chain Analytics Initiatives—An Exploratory Study
Author(s): Herden, Tino T.
Bunzel, Steffen
Type: Article
Language Code: en
Abstract: 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.
URI: https://depositonce.tu-berlin.de/handle/11303/9913
http://dx.doi.org/10.14279/depositonce-8923
Issue Date: 8-May-2018
Date Available: 27-Aug-2019
DDC Class: 380 Handel, Kommunikation, Verkehr
Subject(s): supply chain analytics
business analytics
cluster analysis
License: https://creativecommons.org/licenses/by/4.0/
Journal Title: Logistics
Publisher: MDPI
Publisher Place: Basel
Volume: 2
Issue: 2
Article Number: 10
Publisher DOI: 10.3390/logistics2020010
EISSN: 2305-6290
Appears in Collections:FG Logistik » Publications

Files in This Item:
File Description SizeFormat 
logistics-02-00010.pdf830.77 kBAdobe PDFView/Open


This item is licensed under a Creative Commons License Creative Commons