{"title":"Information sharing across competing platforms with varying information capabilities","authors":"Haoruo Zhu, Yaodong Ni, Yongbo Xiao","doi":"10.1016/j.ejor.2024.11.048","DOIUrl":null,"url":null,"abstract":"Competing online retail platforms frequently function as both agency and reselling channels. This paper explores a manufacturer’s channel selection strategy in the context of downstream platform competition and information sharing, taking into account the platforms’ varying levels of information capability. Our research indicates that the manufacturer opts for a hybrid channel approach. Competing platforms aim to be selected as agency channels by offering information sharing and reduced commission fees. Interestingly, the manufacturer chooses the platform with lesser information capability as her agency channel to gain access to shared demand data, while opting for the platform with greater capability as reselling channel without accessing his demand data. The platform with inferior information capability is more inclined to establish a revenue-sharing partnership with the manufacturer to mitigate risks, leading him to decrease his commission rate to attract the manufacturer to select him as the agency channel. We demonstrate that, under conditions of demand uncertainty, a significant distinction between agency and reselling channels lies in the distribution of risk, i.e., whether the platform assumes the risk alone or shares it with the manufacturer. Furthermore, we highlight the <ce:italic>free-ride effect</ce:italic>, wherein an agency platform can benefit from his rival’s superior information capability. As a result, a complex relationship, characterized by both cooperation and rivalry, may develop between the two platforms.","PeriodicalId":55161,"journal":{"name":"European Journal of Operational Research","volume":"19 1","pages":""},"PeriodicalIF":6.0000,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Operational Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1016/j.ejor.2024.11.048","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Competing online retail platforms frequently function as both agency and reselling channels. This paper explores a manufacturer’s channel selection strategy in the context of downstream platform competition and information sharing, taking into account the platforms’ varying levels of information capability. Our research indicates that the manufacturer opts for a hybrid channel approach. Competing platforms aim to be selected as agency channels by offering information sharing and reduced commission fees. Interestingly, the manufacturer chooses the platform with lesser information capability as her agency channel to gain access to shared demand data, while opting for the platform with greater capability as reselling channel without accessing his demand data. The platform with inferior information capability is more inclined to establish a revenue-sharing partnership with the manufacturer to mitigate risks, leading him to decrease his commission rate to attract the manufacturer to select him as the agency channel. We demonstrate that, under conditions of demand uncertainty, a significant distinction between agency and reselling channels lies in the distribution of risk, i.e., whether the platform assumes the risk alone or shares it with the manufacturer. Furthermore, we highlight the free-ride effect, wherein an agency platform can benefit from his rival’s superior information capability. As a result, a complex relationship, characterized by both cooperation and rivalry, may develop between the two platforms.
期刊介绍:
The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making.