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Erschienen in: Soft Computing 9/2020

05.12.2018 | Focus

Impact of decision style on newsvendor ordering behaviors: mean anchoring, demand chasing and overconfidence

verfasst von: Xiaohua Han, Yiwen Bian, Jennifer Shang

Erschienen in: Soft Computing | Ausgabe 9/2020

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Abstract

Prior experimental studies have shown that individuals’ actual ordering decisions significantly deviate from theoretically-proved optimums in newsvendor problems. Several ordering behaviors like mean anchoring, demand chasing, reference dependence, mental accounting and overconfidence have been demonstrated to be the main causes for such deviations. However, less attention has been focused on the impact of decision style on ordering behaviors. To address such challenging issue, we conduct a between-subjects experiment and compare decision results between different groups of individuals, who are characterized by their decision styles, i.e., rational style and experiential style, as well as their tendencies to the three typical behaviors, i.e., mean anchoring, demand chasing and overconfidence. We show that individuals with high rational style or low experiential style can make better inventory order decisions. Furthermore, decision style and profit margin conditions are demonstrated to actually affect individuals’ tendencies to mean anchoring, demand chasing and overconfidence, which subsequently affects their order decisions. More importantly, compared to mean anchoring and demand chasing, overconfidence is identified as a dominated factor in affecting the order decisions. This research sheds light on how to select right inventory managers and how to improve their ordering decision performance more efficiently through recognizing the impact of decision style and their behavioral tendencies in different profit margin conditions in the newsvendor problem.

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Metadaten
Titel
Impact of decision style on newsvendor ordering behaviors: mean anchoring, demand chasing and overconfidence
verfasst von
Xiaohua Han
Yiwen Bian
Jennifer Shang
Publikationsdatum
05.12.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 9/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-03676-8

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