| Abstract (ENG): |
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. |
| Citation: |
Engel, Tobias and Sadovskyi, Oleksandr and Heininger, Robert and Böhm, Markus and Krcmar, Helmut
(2014)
A Conceptual Approach for optimizing Distribution Logistics using Big Data.
In: (Proceedings of the) 20th American Conference on Information Systems (AMCIS), August, 7-9, 2014, Savannah, GA, USA.
ISBN 9780692253205
|
