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Lookup NU author(s): Dr Matt WalkerORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
A primary objective of creating competition among suppliers is the procurement of higher quality goods and services at lower prices. When procuring non-standard goods, it is often difficult to write a complete specification of desired quality in the contract. Thus, payments to suppliers cannot be perfectly conditioned on the quality provided. We develop a simple model to distil several real-world features and illustrate how contract structure within price priority competition jointly affects bid aggression and incentives for the provision of surplus-enhancing quality. We implement the contingent payments as probabilistic. The selected supplier’s payment is, according to a fixed probability, either their bid or a quality contingent amount that depends on the bid and an exogenous norm for allocating social surplus. We use a lab experiment to show that there is a ‘Goldilocks’ region for high quality in which the probability of quality contingent payment is large enough to incentivize provision, but not so large as to induce overly aggressive bidding. This implementation only relies upon preferences for maximizing one’s own profit and the rationality of backward induction. An experimental finding not predicted in our setting is that suppliers earn positive economic profits inside the Goldilocks region, which can be explained by suppliers’ risk aversion. The results have implications for the effective design of contingent payments in contracts.
Author(s): Shachat J, Walker MJ, Wei L
Publication type: Article
Publication status: Published
Journal: European Economic Review
Year: 2024
Volume: 170
Print publication date: 01/11/2024
Online publication date: 23/10/2024
Acceptance date: 12/10/2024
Date deposited: 23/10/2024
ISSN (print): 0014-2921
ISSN (electronic): 1873-572X
Publisher: Elsevier BV
URL: https://doi.org/10.1016/j.euroecorev.2024.104886
DOI: 10.1016/j.euroecorev.2024.104886
ePrints DOI: 10.57711/az13-zd33
Data Access Statement: The data and associated programs are available for download from the OSF repository at: https://doi.org/10.17605/OSF.IO/AT672
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