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

Abstract

PurposeThe 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/approachThe authors use a qualitative cluster analysis, combined with a Q‐sort methodology, to develop a taxonomy of decision biases.FindingsA 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/valueThis 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.

Behavioral Finance: History and Foundations

“…For example, availability and representativeness heuristics, in fact, constitute a single heuristic which Kahneman and Frederick (2002) called attribution substitution (however, the tradition to distinguish between the two stuck in both research and practice). Later, Krueger and Funder (2004) produced a list of the 42 most important cognitive biases from the perspective of psychological research, while Carter et al (2007) list 76 decision biases in business and management and divided them into nine categories.…”

Effect of customer demand information sharing on a four-stage serial supply chain performance: an experimental study

“…Most of the previous researchers in their experimental studies have considered long lead time (4 periods) and uniform distribution with a range of 0 to 8 or step-up demand pattern for the customer demand (Sterman, 1989;Croson & Donohue, 2003, Croson & Donohue, 2006, Wu & Katok, 2006; assuming a uniform customer demand is unusual (Steckel et al, 2004) and normal distribution is the best choice for the same (Chan & Chan, 2010). Carter et al (2007), Bendoly et al (2010), Tokar (2010), and Cantor and Katok (2012) highlighted the need for behavioural research in logistics and supply chain management in which human beings are used for conducting experiments. They concluded that the behavioural research in logistics and supply chain management can significantly advance both theory and practice in the logistics and supply chain management.…”

Bounded rationality: the two cultures

“…For example, the new field of behavioral operations management has essentially transferred the approach of behavioral economics to the study of the management of operations such as supply chains (Katsikopoulos & Gigerenzer, 2013). This can be seen in how the field is defined as the study of biases (Carter, Kaufmann, & Michel, 2007), in the flurry of optimization models that are being developed (Loch & Wu, 2005) and in the neglect of the underlying psychological processes (Croson & Donohue, 2002). In the field of engineering design, pragmatic models have been received with furious anger by proponents of idealistic modeling who controlled funding in the United States National Science Foundation for years (see the response of Hazelrigg, 2010to Frey et al, 2009.…”