DEBIASING STRATEGIES IN SUPPLY MANAGEMENT DECISION-MAKING

Journal of Business Logistics, 2009 by Kaufmann, Lutz, Michel, Alex, Carter, Craig R

INTRODUCTION

Decision biases are likely to arise in the area of business-to-business sourcing (Bendoly, Donohue, and Schultz 2006) as many supply management decisions are made within contexts of uncertainty (Kaufmann and Carter 2006; Ogden et al. 2005; Zsidisin 2003) and thus challenge supply managers' rational decision-making. As decision makers' rationality is bounded due to limitations in information gathering, computing capabilities, and a limited memory (Arrow 1986; Koh, Ang, and Straub 2004; Miller 1956; Nordstrom, Williams, and LeBreton 1996; Slovic and Lichtenstein 1971), they may fail when it comes to judging probabilities, making predictions, or otherwise attempting to cope with uncertain decision-making environments (Arrow 1986; Thaler 1985). This view challenges the traditional rationality assumptions in economics (Hogarth 1987; Tversky and Kahneman 1974). Specifically, it suggests that decisions are vulnerable to decision biases and might only meet the decision quality criterion of "satisficing" (Simon 1957, p. 204) or "reasonable" (Bazerman 1998, p. 5), rather than "rational".

Strategies to mitigate the influence of decision biases and to enhance rational decision-making have been developed by several researchers in the fields of psychology, decision theory, and economics. However while some individual studies surrounding sourcing decisions can be found in the extant supply management literature (Snijders, Tazelaar, and Batenburg 2003), up to now no comprehensive overview about respective applications has been presented. Consequently, there is a pressing need to identify deployed debiasing strategies in supply management environments and to evaluate their efficiency when it comes to reducing the effects of decision biases. Despite the vital role that supply management contributes to an organization's overall logistics system-including product design and selection, and the management of inventory and supplier relationships (Bowersox et al. 1992; Cavinato 1992; Lambert and Stock 1993)-the subject of purchasing and supply management has received insufficient coverage in the Journal of Business Logistics in the past (La Londe 1988) and continues to be underrepresented vis�-vis other logistics topics (Miyazaki, Phillips, and Phillips 1999). Throughout this article we use the terms sourcing and supply management interchangeably (Monczka, Trent, and Handfield 2005), and define decision-making within the context of our study as the criteria-based search, evaluation, and selection of alternatives in the upstream supply chain.

The goal of the present study is to examine how buying organizations support rational decision-making and, by comparing these results with the current state-of-the-art debiasing strategies in the existing literature, to identify possible 'gaps' and thus potential for improving the rationality of supply management judgment and decisionmaking in the context of uncertainty. In doing so, the authors first developed a conceptual framework of decision supporting strategies based on a classification of the extant 'debiasing' literature and on Duncan's (1972) conceptualization of environmental uncertainty. An inductive data collection approach (Eisenhardt 1989; Miles and Huberman 1994) was then used to investigate the study's research objectives:

(1) to understand how rational supply management decision-making is currently supported in supply management organizations, and

(2) to develop research propositions, grounded in the study's data, which will help to guide future research.

The remainder of our article is organized as follows. In the next section, we outline our initial conceptual framework which is based on Duncan's (1972) conceptualization of uncertainty. Here, we review the extant literature and describe how we developed the framework. We then describe the study's methodology, which involved building grounded theory based on 441 data points which were collected from 133 embedded cases from 15 buying organizations. In the final sections, we present the results from these case studies, followed by a discussion of the implications and future research that is needed in this area of debiasing strategies in supply management decision-making.

CONCEPTUAL FRAMEWORK

In this work we will treat environmental uncertainty as a two-dimensional construct based on the research of Duncan (1972, p. 313), who integrated the work of decision theorists (Luce and Raiffa 1957) and organizational researchers (Thompson 1967) to describe uncertainty as: (1) simple-complex ("the number of factors taken into consideration in decision-making") and (2) static-dynamic ("the degree to which these factors in the decision maker's environment remain basically the same over time or are in a continual process of change").

The literature describes different strategies which help to mitigate the influence of single or multiple decision biases under uncertainty. The evidence in the extant literature on decision biases shows that 'environmental uncertainty' as defined in the previous paragraph can be interpreted as the source of vulnerability to decision biases caused by cognitive constraints (Bazerman 1998; Kahneman 2003; Simon 1957; Tversky and Kahneman 1974, 1986). Accordingly, a mitigation of deviations from rationality could be achieved by (a) enhancing the decision maker's capabilities of rational decision-making at a given level of uncertainty of the decision environment and/or (b) reducing the level of uncertainty consisting of dynamism and complexity.