{"title":"The Design of Optimal Pay-as-Bid Procurement Mechanisms","authors":"Je-ok Choi, Daniela Saban, Gabriel Weintraub","doi":"10.1287/msom.2022.1180","DOIUrl":null,"url":null,"abstract":"Problem definition: We consider the mechanism design problem of finding an optimal pay-as-bid mechanism in which a platform chooses an assortment of suppliers to balance the tradeoff between two objectives: providing enough variety to accommodate heterogeneous buyers, yet at low prices. Academic/practical relevance: Modern buying channels, including e-commerce and public procurement, often consist of a platform that mediates transactions. Frequently, these platforms implement simple and transparent mechanisms to induce suppliers’ direct participation, which typically results in pay-as-bid (or first-price) mechanisms where suppliers set their prices. Methodology: We introduce a novel class of assortment mechanisms that we call k-soft reserves (k-SRs): If at least k suppliers choose a price below the soft-reserve price, then only those suppliers are added to the assortment; otherwise, all the suppliers are added. Results: We show the optimality of k-SRs for a class of stylized symmetric models to derive the intuition behind these mechanisms. Then, through extensive numerical simulations, we provide evidence of the robustness of k-SRs in more general and realistic settings. Managerial implications: Our results give intuitive and simple-to-use prescriptions on how to optimize pay-as-bid assortment mechanisms in practice, with an emphasis on public procurement settings. Funding: J. Choi thanks the Samsung Scholarship and Stanford Graduate School of Business for financial support. G. Weintraub thanks Joseph and Laurie Lacob for the support during the 2018–2019 academic year as a Joseph and Laurie Lacob Faculty Scholar at Stanford Graduate School of Business. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2022.1180 .","PeriodicalId":49901,"journal":{"name":"M&som-Manufacturing & Service Operations Management","volume":"32 1","pages":"0"},"PeriodicalIF":4.8000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"M&som-Manufacturing & Service Operations Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1287/msom.2022.1180","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
Problem definition: We consider the mechanism design problem of finding an optimal pay-as-bid mechanism in which a platform chooses an assortment of suppliers to balance the tradeoff between two objectives: providing enough variety to accommodate heterogeneous buyers, yet at low prices. Academic/practical relevance: Modern buying channels, including e-commerce and public procurement, often consist of a platform that mediates transactions. Frequently, these platforms implement simple and transparent mechanisms to induce suppliers’ direct participation, which typically results in pay-as-bid (or first-price) mechanisms where suppliers set their prices. Methodology: We introduce a novel class of assortment mechanisms that we call k-soft reserves (k-SRs): If at least k suppliers choose a price below the soft-reserve price, then only those suppliers are added to the assortment; otherwise, all the suppliers are added. Results: We show the optimality of k-SRs for a class of stylized symmetric models to derive the intuition behind these mechanisms. Then, through extensive numerical simulations, we provide evidence of the robustness of k-SRs in more general and realistic settings. Managerial implications: Our results give intuitive and simple-to-use prescriptions on how to optimize pay-as-bid assortment mechanisms in practice, with an emphasis on public procurement settings. Funding: J. Choi thanks the Samsung Scholarship and Stanford Graduate School of Business for financial support. G. Weintraub thanks Joseph and Laurie Lacob for the support during the 2018–2019 academic year as a Joseph and Laurie Lacob Faculty Scholar at Stanford Graduate School of Business. Supplemental Material: The online appendices are available at https://doi.org/10.1287/msom.2022.1180 .
期刊介绍:
M&SOM is the INFORMS journal for operations management. The purpose of the journal is to publish high-impact manuscripts that report relevant research on important problems in operations management (OM). The field of OM is the study of the innovative or traditional processes for the design, procurement, production, delivery, and recovery of goods and services. OM research entails the control, planning, design, and improvement of these processes. This research can be prescriptive, descriptive, or predictive; however, the intent of the research is ultimately to develop some form of enduring knowledge that can lead to more efficient or effective processes for the creation and delivery of goods and services.
M&SOM encourages a variety of methodological approaches to OM research; papers may be theoretical or empirical, analytical or computational, and may be based on a range of established research disciplines. M&SOM encourages contributions in OM across the full spectrum of decision making: strategic, tactical, and operational. Furthermore, the journal supports research that examines pertinent issues at the interfaces between OM and other functional areas.