Note on Optimal Procurement Mechanisms for Assembly

Author:

Shan Xi1ORCID,Ye Lixin23ORCID,Zhang Chenglin4ORCID

Affiliation:

1. Supply Chain Management & International Business Department, School of Business and Economics, State University of New York at Plattsburgh, Plattsburgh, New York 12901;

2. Department of Economics, The Ohio State University, Columbus, Ohio 43210;

3. School of Management and Economics, The Chinese University of Hong Kong, Shenzhen 518172, China;

4. School of Finance, Southwestern University of Finance and Economics, Chengdu 610074, China

Abstract

Problem definition: We consider contract confidentiality in a decentralized supply chain, in which a single principal orders different components from different agents, each of which has private cost information. The principal may commit to publicly observed bilateral contracts or offer secretly observed contracts to each agent simultaneously. We also consider the problem of sequential contracting. Methodology/results: By correcting the main analysis in Hu and Qi [Hu B, Qi A (2018) Optimal procurement mechanisms for assembly. Manufacturing Service Oper. Management 20(4):655–666], we employ passive beliefs to study secret contracting. We show that there is a unique configuration of two-part tariffs under secret offers in both simultaneous and sequential contracting. We also extend the analysis to take into account ex post individual rationality (IR), which is arguably more relevant in this assembly setting. With ex post IR, we show that the traditional two-part tariffs should be augmented with payment adjustments. Managerial implications: We find that the efficiency achieved through public offers can be maintained with secret offers in this assembly setting contrary to conventional wisdom. Our analysis, thus, offers an explanation for why nondisclosure agreements are important and common in practice. Funding: This work was supported by the National Natural Science Foundation of China [Grant 72192805]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2024.0907 .

Publisher

Institute for Operations Research and the Management Sciences (INFORMS)

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