{"title":"The Design of Optimal Pay-as-Bid Procurement Mechanisms","authors":"Je-ok Choi, D. Sabán, G. Weintraub","doi":"10.2139/ssrn.3785023","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":18108,"journal":{"name":"Manuf. Serv. Oper. Manag.","volume":"26 1","pages":"613-630"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Manuf. Serv. Oper. Manag.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3785023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","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 .