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Sourcing Decisions under Conditions of Risk and Resilience: A Behavioral Study
Author(s) -
Mena Carlos,
Melnyk Steven A.,
Baghersad Milad,
Zobel Christopher W.
Publication year - 2020
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/deci.12403
Subject(s) - macro , supply chain , variance (accounting) , resilience (materials science) , perception , psychological resilience , supply chain management , macro level , risk perception , psychology , social psychology , business , marketing , risk analysis (engineering) , economics , computer science , physics , thermodynamics , economic system , accounting , neuroscience , programming language
ABSTRACT This article continues a recent trend of exploring the linkages between supply chain risk, resilience and decision‐making at an individual level. Specifically, the article reports the results of a behavioral study that explores whether and how the perceptions of supply chain risk and resilience influence the decisions made regarding the selection of a new source of critical components. The study uses a full factorial design for a scenario‐based role‐playing experiment involving over 1,000 valid responses drawn from multiple sampling pools including supply chain managers, students, and crowd‐sourced respondents. The results indicate that the perception of supply chain resilience—whether it is by systemic resilience communication, such as training or corporate pronouncements, or through personal exposure—significantly influences decision‐making, although personal exposure appears to have a stronger impact on the outcome. This relationship is significantly moderated by the risk propensity of the individual decision‐makers. The article concludes with a discussion of the results and their implication for both theory and practice. The discussion provides a framework for integrating the macro and micro levels by arguing that the micro issues can potentially moderate and mediate the relationships and findings observed at the macro level. Failure to integrate the micro effects can result in variance that the macro‐level analysis is unable to explain.