Advice in Crisis: Principles of Organizational and Entrepreneurial Resilience

Sheen S. Levine (), Michael J. Prietula and Ann Majchrzak
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Sheen S. Levine: The University of Texas
Michael J. Prietula: Emory University
Ann Majchrzak: The University of Southern California

Journal of Organization Design, 2022, vol. 11, issue 4, 145-168

Abstract: Abstract When facing a crisis (or preparing for one), decision-makers often turn to peer networks, seeking advice and providing it. Scholars and practitioners endorse sharing knowledge and experience, especially for boosting resilience and combating crises. They believe such decentralized, peer-to-peer contact suits the ill-structured challenges organizations encounter. Yet, this endorsement overlooks a bias known as the Dunning-Kruger effect: People regularly misjudge their own and their peers’ skills. Thus, ascertaining whether a peer is sufficiently skilled to advise is an error-prone endeavor. Because of the bias, a person in need may mistakenly accept poor advice—and then proceed to unintentionally spread it. To understand advice networks in crisis, we weave case studies and experimental evidence into a formal model. Seeding the model with empirical data on skill (mis)judgment, we confirm that advice improves performance, but only if skill misjudgment is assumed away. When the bias is incorporated into the model, the risk of transmitting poor advice increases. As it cascades from one person to another, poor advice undercuts skill throughout organizations and networks. And it reduces the diversity and range of knowledge and advice, further hampering crisis response. Seeking a remedy, we introduce a theoretically-derived mechanism for carving up the advice network, showing how organizational design can ameliorate the risk. We conclude with implications for resilience and crisis research and practice whether in established organizations or entrepreneurial ventures.

Keywords: Computer simulation/agent-based modeling; Mathematical modeling; Advice; Network; Knowledge transfer/replication (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s41469-022-00128-4

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