Cognitive biases as impediments to enhancing supply chain entrepreneurial embeddedness

Abstract

The recently introduced concept of supply chain entrepreneurial embeddedness (SCEE) refers to the extent to which large firms integrate entrepreneurial capabilities into their supply chains. Achieving a higher degree of SCEE can involve assimilating entrepreneurial practices by copying entrepreneurial firms’ behavior, allying with entrepreneurial firms to gain access to and learn from them, and acquiring entrepreneurial firms to bring their practices inside the firm. Because SCEE appears to be a pathway to enhanced firm performance, enhancing SCEE should be attractive. However, our thesis is that efforts to do so may be undermined by cognitive biases—heuristics used by the human mind to simplify complex situations that result in distorted thinking. We explore the possible problems arising due to 11 cognitive biases discussed by Schwenk (Strategic Management Journal, 1984, 5(2), 111). We offer two brief case examples of companies that are seeking to make their supply chains more entrepreneurial; each illustrates several of the biases in action. We also consider whether supply chain complexity and entrepreneurial orientation can mitigate or strengthen cognitive biases’ harmful effects on SCEE. In doing so, we construct an important interface across entrepreneurship and supply chain management.

Untying the Gordian knot: A systematic review and integrative framework of supply network complexity

“…Another worthwhile aspect to explore is the influence of SNC on the speed and quality of managerial decisions. Recently, Ketchen Jr and Craighead (2022) proposed that complexity can hinder supply chain managers' cognitive abilities and reduce supply chain entrepreneurial embeddedness. To address such issues, conducting experiments by utilizing a wide spectrum of theories, such as information processing theory, signaling theory, and schema theory, would significantly enhance our understanding in this domain.…”

Pulled in opposite directions: A joint consideration of supply and demand uncertainty in supply chain decision‐making

“…Similarly, the dynamic complexity which manifests itself as demand uncertainty in our experiment may be present in a different business setting as internal volatility, such as unpredictable manufacturing schedules and unstable capacities or yields of the focal firm. In facing such growing complexity, the decision‐maker could embrace an oversimplification heuristic akin to pull‐to‐center, as we notice in our experiment, leading to a highly uncertain outcome for a new strategic initiative (Ketchen & Craighead, 2022). Our study has the potential to inform decisions when such uncertainties are present together.…”

“…This underscores the need for empirical examinations of “the human element,” toward better understanding, anticipation of effects, and counter‐measures. For example, as elaborated by Ketchen and Craighead (2022), various cognitive biases and heuristics, such as escalating commitment, prior hypothesis, reasoning by analogy, inferences of impossibility, representativeness, and illusion of control, impact the three steps of the strategic decision‐making process, namely goal formulation, strategic alternatives generation, and evaluation and selection. Depending on the effects these biases and heuristics cause, firms may need to decide to discourage human judgment in the decision‐making process and substitute it with technology (Fahimnia et al, 2019).…”

“…For example, the presence of devaluation of partially described alternatives bias is discernible in our experiment as decision‐makers seem to order more from the reliable supplier compared with its unreliable counterpart as supplier uncertainty level increases. This systemic undervaluation of alternatives with uncertain outcomes and preference toward alternatives with certainty occasionally leads to suboptimal decisions (Ketchen & Craighead, 2022), as evident in other supply chain contexts beyond inventory ordering, such as recalling all potentially affected product lots regardless of their likelihood of containing defective items (Ketchen et al, 2014; Wowak et al, 2016). Similarly, the dynamic complexity which manifests itself as demand uncertainty in our experiment may be present in a different business setting as internal volatility, such as unpredictable manufacturing schedules and unstable capacities or yields of the focal firm.…”

“…Depending on the effects these biases and heuristics cause, firms may need to decide to discourage human judgment in the decision-making process and substitute it with technology (Fahimnia et al, 2019). Alternatively, the decision-making process could be redesigned to minimize cognitive oversimplification tendencies by promoting devil's advocacy and dialectical inquiry (Ketchen & Craighead, 2022).…”