Cry-Wolf Syndrome in Recommendation

Production and Operations Management

24 Pages Posted: 14 Nov 2019 Last revised: 6 Jul 2022

See all articles by Baixun LI

Baixun LI

affiliation not provided to SSRN

Meng Li

University of Houston - Department of Decision & Information Sciences

Chao Liang

China Europe International Business School (CEIBS)

Date Written: November 5, 2019

Abstract

We incorporate the cry-wolf syndrome into a setting in which a manufacturer commissions a forecaster for recommendation. In this context, we define cry-wolf as a behavioral syndrome that leads the manufacturer to become less compliant with the forecaster's valuable recommendation after the forecaster is proven guilty of false alarms. We obtain three findings with regard to cry-wolf. First, although cry-wolf unequivocally leads to a lower performance for the manufacturer when the forecaster's decision is exogenous, cry-wolf can help boost the forecaster's investment in forecasting and, thus, benefit the manufacturer when the forecaster's decision is endogenous. Second, cry-wolf can improve the performance of the system — the manufacturer and forecaster together — if the manufacturer pays a moderate commission to the forecaster. Finally, cry-wolf can improve both the manufacturer's and the system's performance, even if the forecaster is not knowledgeable (unaware) of the manufacturer's cry-wolf; perhaps more interestingly, the forecaster's unawareness of the manufacturer's cry-wolf can be its comparative advantage relative to the manufacturer. Our findings are helpful in understanding the conditions when cry-wolf can be detrimental or beneficial and, thus, call caution to the design and adoption of strategies aimed at improving decisions and curtailing cry-wolf syndrome among executives.

Keywords: managerial bias, behavioral operations management, demand uncertainty, forecasting

Suggested Citation

LI, Baixun and Li, Meng and Liang, Chao, Cry-Wolf Syndrome in Recommendation (November 5, 2019). Production and Operations Management, Available at SSRN: https://ssrn.com/abstract=3481358 or http://dx.doi.org/10.2139/ssrn.3481358

Baixun LI

affiliation not provided to SSRN

Meng Li

University of Houston - Department of Decision & Information Sciences ( email )

United States

Chao Liang (Contact Author)

China Europe International Business School (CEIBS) ( email )

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