The introduction of big data and predictive analytics techniques in the supply chain context constitutes a “hot topic” in both research and practice. Without arguing against this euphoria, this paper critically assesses the consequences of confronting human actors with an increasing usage of these techniques. The underlying case of this paper refers to collaborative supply chain processes that are predestinated for integrating new big data and predictive analytics techniques. By building a theoretical framework for deriving sound hypothesis and introducing and testing the experimental design for validating these hypothesis, this paper paves the way for this important research avenue.
|Number of pages||10|
|Publication status||Published - 2016|
|Event||The 23rd International Annual EurOMA Conference 2016 - Norwegian University of Science and Technology (NTNU), Trondheim, Norway|
Duration: 17 Jun 2016 → 22 Jun 2016
Conference number: 23
|Conference||The 23rd International Annual EurOMA Conference 2016|
|Location||Norwegian University of Science and Technology (NTNU)|
|Period||17/06/2016 → 22/06/2016|
Bibliographical noteCBS Library does not have access to the material
- Supply Chain Management (SCM)
- Collaborative planning
- Behavioral experiments
Schorsch, T., Wallenburg, C. M., & Wieland, A. (2016). On the Interface Between Automated Predictive Demand Planning Techniques and Humans in Collaborative Planning Processes. Paper presented at The 23rd International Annual EurOMA Conference 2016, Trondheim, Norway.