Behavioral supply management a taxonomy of judgment and decisionmaking biases

Purpose The purpose of this paper is to review and integrate the extensive literature base which examines judgment and decisionmaking biases, to introduce this literature to the field of supply management, to create a valid, mutually exclusive, and exhaustive taxonomy of decision biases that can aff...

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Veröffentlicht in:International journal of physical distribution & logistics management 2007-09, Vol.37 (8), p.631-669
Hauptverfasser: Carter, Craig R., Kaufmann, Lutz, Michel, Alex
Format: Artikel
Sprache:eng
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Zusammenfassung:Purpose The purpose of this paper is to review and integrate the extensive literature base which examines judgment and decisionmaking biases, to introduce this literature to the field of supply management, to create a valid, mutually exclusive, and exhaustive taxonomy of decision biases that can affect supply managers, and to provide guidance for future research and applications of this taxonomy. Designmethodologyapproach The authors use a qualitative cluster analysis, combined with a Qsort methodology, to develop a taxonomy of decision biases. Findings A mutually exclusive, and exhaustive taxonomy of nine decision biases is developed through a qualitative cluster analysis. The Qsort methodology provides initial confirmation of the reliability and validity of the cluster analysis results. The findings, along with numerous examples provided in the text, suggest that supply management decisions are vulnerable to the described biases. Originalityvalue This paper provides a comprehensive review of the judgment and decision bias literature, and creates a logical and manageable taxonomy of biases which can impact supply management decision making. The introduction and organization of this vast extant literature base provides a contrasting perspective to much of the existing supply management research, which has incorporated the assumption of the rational agent, or what is known in the economics literature as homo economicus. In addition, the authors describe the use of qualitative cluster analysis and the Qsort methodology, techniques which have been used rarely if at all in within the field of supply chain management.
ISSN:0960-0035
DOI:10.1108/09600030710825694