A conceptual approach for optimizing distribution logistics using big data

Tobias Engel, Oleksandr Sadovskyi, Markus Böhm, Robert Heininger, Helmut Krcmar

Research output: Contribution to conferencePaperpeer-review

9 Scopus citations

Abstract

Big data analytics creates new opportunities and potentials in the field of supply chain management (SCM). Specifically, linking inter-firm supply chain processes of two entities such as freight forwarder and final customer were identified as relevant areas for performance improvements. Automatic analysis of data from sources such as mobile equipment, sensor networks, and geospatial devices can significantly improve accuracy of SCM transportation processes; thus contributing to supply chain performance by minimizing delivery attempts, and ensures higher customer satisfaction, as deliveries are carried out when customers are able to receive them. Therefore, we develop a distribution concept targeted at realization of this potential. We chose the online shopping domain for our concept, as current research provides evidence that delivery of goods acquired in online stores often causes multiple delivery attempts, and many firms struggle with providing good service to the customers. Finally, we discuss limitations, implications and possibilities for future research.

Original languageEnglish
StatePublished - 2014
Event20th Americas Conference on Information Systems, AMCIS 2014 - Savannah, GA, United States
Duration: 7 Aug 20149 Aug 2014

Conference

Conference20th Americas Conference on Information Systems, AMCIS 2014
Country/TerritoryUnited States
CitySavannah, GA
Period7/08/149/08/14

Keywords

  • Actor network theory
  • Big data
  • Distribution concept
  • Online shopping
  • Supply chain management

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