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

IF 8.3 1区 工程技术 Q1 ECONOMICS
Hanyin Zheng , Kevin X. Li , Adolf K.Y. Ng , Yang Liu , Mengjie Jin , Zhuo Chen , Yi Xiao
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引用次数: 0

摘要

随着新技术的发展,基于区块链的数字海上贸易平台已经开发出来,通过让平台参与者参与进来,鼓励他们分享相关业务数据,提高交互效率。然而,平台企业如何普及自己的平台,如何鼓励参与平台的参与者共享数据,是一个挑战。为了促进数据共享,本研究基于委托代理模型设计了一种激励机制,最大化参与者的数据共享意愿。主要研究结果如下:首先,最优激励策略取决于平台总产出对激励补贴的敏感性、外生风险、平台企业的风险厌恶程度、参与者的数据量、努力成本以及对负外部性的担忧等因素之间的相互作用。其次,平台企业和参与者的效用在最优激励补贴和最优努力并存的唯一均衡中相交。第三,为海上物流业平台企业提供政策启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
CiteScore
16.20
自引率
16.00%
发文量
285
审稿时长
62 days
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.
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