An Experimental Investigation of Managing Quality Through Monetary and Relational Incentives
Andrew M. Davis () and
Kyle Hyndman
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Andrew M. Davis: Samuel Curtis Johnson Graduate School of Management, Cornell SC Johnson College of Business, Cornell University, Ithaca, New York 14850
Management Science, 2018, vol. 64, issue 5, 2345-2365
Abstract:
We investigate the efficacy of monetary and relational incentives for managing the quality of a product in a two-tier supply chain. In our setting, a retailer offers a supplier contract terms for a product, where the product can be low or high quality. The supplier can choose to exert high effort, which is costly but guarantees high quality, or low effort, which does not assure high quality with certainty. We compare how monetary incentives, such as a bonus that is paid to the supplier when high quality is received by the retailer, and relational incentives, such as the two parties engaging in a long-term relationship where there is the threat of punishment, affect overall quality and supply chain efficiency. Two of our primary results suggest that (1) relational incentives improve both quality and supply chain efficiency, regardless of whether a monetary incentive is present, and (2) when relational incentives are present, the impact of adding monetary incentives is nonmonotonic: less efficient monetary incentives appear to crowd out the benefits of relational incentives leading even to a reduction in supply chain efficiency, whereas more efficient monetary incentives actually complement relational incentives and lead to significant increases in both quality and supply chain efficiency. We then proceed by demonstrating that a behavioral model of fairness can organize the data quite well.
Keywords: behavioral operations; quality; incentives; supply chain contracting; experimental economics (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (12)
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:64:y:2018:i:5:p:2345-2365
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