Hanyin Zheng , Kevin X. Li , Adolf K.Y. Ng , Yang Liu , Mengjie Jin , Zhuo Chen , Yi Xiao
{"title":"加强海上区块链平台数据共享:基于委托代理模型的激励机制","authors":"Hanyin Zheng , Kevin X. Li , Adolf K.Y. Ng , Yang Liu , Mengjie Jin , Zhuo Chen , Yi Xiao","doi":"10.1016/j.tre.2025.104153","DOIUrl":null,"url":null,"abstract":"<div><div>With the development of new technologies, blockchain-based digital maritime trade platforms have been developed to enhance interaction efficiency by involving participants in the platforms and encouraging them to share their related business data. However, it is challenging for platform enterprises to popularize their platforms and encourage participants involved with their platforms to share data. To promote data sharing, this study designs an incentive mechanism to maximize participants’ willingness to share data based on a principal-agent model. The main findings are as follows. First, optimal incentive strategy depends on interactions among factors including the sensitivity of platform’s total output to incentive subsidies, exogenous risks, platform enterprises’ risk aversion, participants’ data volumes, effort costs, and concerns over negative externalities. Second, utilities of platform enterprises and participants intersect at a unique equilibrium where optimal incentive subsidies and optimal effort coexist. Third, policy implications for platform enterprises in the maritime logistics industry are provided.</div></div>","PeriodicalId":49418,"journal":{"name":"Transportation Research Part E-Logistics and Transportation Review","volume":"199 ","pages":"Article 104153"},"PeriodicalIF":8.3000,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancing data sharing in maritime blockchain platforms: An incentive mechanism based on principal-agent model\",\"authors\":\"Hanyin Zheng , Kevin X. Li , Adolf K.Y. Ng , Yang Liu , Mengjie Jin , Zhuo Chen , Yi Xiao\",\"doi\":\"10.1016/j.tre.2025.104153\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>With the development of new technologies, blockchain-based digital maritime trade platforms have been developed to enhance interaction efficiency by involving participants in the platforms and encouraging them to share their related business data. However, it is challenging for platform enterprises to popularize their platforms and encourage participants involved with their platforms to share data. To promote data sharing, this study designs an incentive mechanism to maximize participants’ willingness to share data based on a principal-agent model. The main findings are as follows. First, optimal incentive strategy depends on interactions among factors including the sensitivity of platform’s total output to incentive subsidies, exogenous risks, platform enterprises’ risk aversion, participants’ data volumes, effort costs, and concerns over negative externalities. Second, utilities of platform enterprises and participants intersect at a unique equilibrium where optimal incentive subsidies and optimal effort coexist. Third, policy implications for platform enterprises in the maritime logistics industry are provided.</div></div>\",\"PeriodicalId\":49418,\"journal\":{\"name\":\"Transportation Research Part E-Logistics and Transportation Review\",\"volume\":\"199 \",\"pages\":\"Article 104153\"},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2025-04-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Transportation Research Part E-Logistics and Transportation Review\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1366554525001942\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transportation Research Part E-Logistics and Transportation Review","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1366554525001942","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Enhancing data sharing in maritime blockchain platforms: An incentive mechanism based on principal-agent model
With the development of new technologies, blockchain-based digital maritime trade platforms have been developed to enhance interaction efficiency by involving participants in the platforms and encouraging them to share their related business data. However, it is challenging for platform enterprises to popularize their platforms and encourage participants involved with their platforms to share data. To promote data sharing, this study designs an incentive mechanism to maximize participants’ willingness to share data based on a principal-agent model. The main findings are as follows. First, optimal incentive strategy depends on interactions among factors including the sensitivity of platform’s total output to incentive subsidies, exogenous risks, platform enterprises’ risk aversion, participants’ data volumes, effort costs, and concerns over negative externalities. Second, utilities of platform enterprises and participants intersect at a unique equilibrium where optimal incentive subsidies and optimal effort coexist. Third, policy implications for platform enterprises in the maritime logistics industry are provided.
期刊介绍:
Transportation Research Part E: Logistics and Transportation Review is a reputable journal that publishes high-quality articles covering a wide range of topics in the field of logistics and transportation research. The journal welcomes submissions on various subjects, including transport economics, transport infrastructure and investment appraisal, evaluation of public policies related to transportation, empirical and analytical studies of logistics management practices and performance, logistics and operations models, and logistics and supply chain management.
Part E aims to provide informative and well-researched articles that contribute to the understanding and advancement of the field. The content of the journal is complementary to other prestigious journals in transportation research, such as Transportation Research Part A: Policy and Practice, Part B: Methodological, Part C: Emerging Technologies, Part D: Transport and Environment, and Part F: Traffic Psychology and Behaviour. Together, these journals form a comprehensive and cohesive reference for current research in transportation science.