Behavioral supply management: a taxonomy of judgment and decision-making biases

Purpose - The purpose of this paper is to review and integrate the extensive literature base which examines judgment and decision-making 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.Design methodology approach - The authors use a qualitative cluster analysis, combined with a Q-sort 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 Q-sort 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.Originality value - 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 Q-sort methodology, techniques which have been used rarely if at all in within the field of supply chain management.