Guokai Li, Ningyuan Chen, Guillermo Gallego, P. Gao, Steven Kou
{"title":"Dealership or Marketplace with Fulfillment Services: A Dynamic Comparison","authors":"Guokai Li, Ningyuan Chen, Guillermo Gallego, P. Gao, Steven Kou","doi":"10.1287/msom.2022.0253","DOIUrl":null,"url":null,"abstract":"Problem definition: We consider two business models for a two-sided economy under uncertainty: dealership and marketplace with fulfillment services. Although both business models can bridge the gap between demand and supply, it is not clear which model is better for the firm or for the consumers. Methodology/results: We show that, whereas the two models differ substantially in pricing power, inventory risk, fee structure, and fulfillment time, both models share several important features with the revenues earned by the firm from the two models converging when the markets are thick. We also show that, for thick markets, there is a one-to-one mapping between their corresponding optimal policies. Managerial implications: Our results provide guidelines for firms entering two-sided markets: when the market is thick, the two business models are similar; when the market is thin, they should carefully inspect a number of market conditions before making the choice. Funding: The research of G. Li is partially supported by the National Natural Science Foundation of China [Grants 72150002, 72394361] and the Guangdong Provincial Key Laboratory of Mathematical Foundations for Artificial Intelligence [Grant 2023B1212010001]. The research of N. Chen is partially supported by the Natural Sciences and Engineering Research Council of Canada Discovery [Grant RGPIN-2020-04038]. The research of G. Gallego is partially supported by Collaborative Research Funding Hong Kong [Grant C6032-21G]. The research of P. Gao is supported by the National Natural Science Foundation of China [Grants 72201234, 72192805], Collaborative Research Funding Hong Kong [Grant C6032-21G], and the Guangdong Provincial Key Laboratory of Mathematical Foundations for Artificial Intelligence [Grant 2023B1212010001]. Supplemental Material: The online supplement is available at https://doi.org/10.1287/msom.2022.0253 .","PeriodicalId":119284,"journal":{"name":"Manufacturing & Service Operations Management","volume":" 37","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Manufacturing & Service Operations Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1287/msom.2022.0253","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 two business models for a two-sided economy under uncertainty: dealership and marketplace with fulfillment services. Although both business models can bridge the gap between demand and supply, it is not clear which model is better for the firm or for the consumers. Methodology/results: We show that, whereas the two models differ substantially in pricing power, inventory risk, fee structure, and fulfillment time, both models share several important features with the revenues earned by the firm from the two models converging when the markets are thick. We also show that, for thick markets, there is a one-to-one mapping between their corresponding optimal policies. Managerial implications: Our results provide guidelines for firms entering two-sided markets: when the market is thick, the two business models are similar; when the market is thin, they should carefully inspect a number of market conditions before making the choice. Funding: The research of G. Li is partially supported by the National Natural Science Foundation of China [Grants 72150002, 72394361] and the Guangdong Provincial Key Laboratory of Mathematical Foundations for Artificial Intelligence [Grant 2023B1212010001]. The research of N. Chen is partially supported by the Natural Sciences and Engineering Research Council of Canada Discovery [Grant RGPIN-2020-04038]. The research of G. Gallego is partially supported by Collaborative Research Funding Hong Kong [Grant C6032-21G]. The research of P. Gao is supported by the National Natural Science Foundation of China [Grants 72201234, 72192805], Collaborative Research Funding Hong Kong [Grant C6032-21G], and the Guangdong Provincial Key Laboratory of Mathematical Foundations for Artificial Intelligence [Grant 2023B1212010001]. Supplemental Material: The online supplement is available at https://doi.org/10.1287/msom.2022.0253 .