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Coordination for Assembly

Authors: Wen Zhang; Sina Shokoohyar; Anyan Qi; Elena Katok;

Coordination for Assembly

Abstract

Problem definition: Modern assembly projects usually involve many interrelated tasks outsourced to suppliers/contractors, and the project outcome depends on all contractors’ minimum effort level. To mitigate risks in such projects, the original equipment manufacturer (OEM) often uses a risk-sharing contract, under which the payment to the contractors depends on the minimum effort level. The question of how to structure supply contracts in such settings is the focus of our study. Methodology/results: We employ gametheoretic models and behavioral experiments to analyze this problem. We show that, under the risk-sharing contract, contractors may fail to achieve the desired project effort level because they may select the least efficient secure equilibrium due to strategic uncertainty. To mitigate this coordination failure, we introduce a new information-feedback mechanism that involves informing contractors about the effort exerted by other contractors in multiple feedback periods. We fully characterize contractors’ subgame-perfect secure equilibrium strategies under the feedback mechanism and identify the minimum feedback periods to achieve the Pareto optimality. We further show that this minimum feedback period increases with the number of contractors. We finally test the mechanism in the laboratory with human subjects and find qualitative support for the model. Managerial implications: Our study delivers three main messages. Firstly, contractors may fail to coordinate under a risk-sharing contract. Secondly, the OEM should require sufficient periodic feedback among contractors throughout the project to mitigate coordination failure. Thirdly, in order to address the growing challenge of coordinating multiple contractors, the OEM should offer additional feedback periods and encourage contractors to take prompt action during earlier periods. Funding: The authors gratefully acknowledge financial support from the University of Texas at Dallas. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0342 .

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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