主题：【海外名家讲堂】“数字化管理”高端讲堂系列（一）
Untangling the Impact of Matchmaking Rules on Operational and Financial Performance in B2B Sharing Economy Platforms: A Mixed Methods Approach
主讲人：哥本哈根商学院 陈致玮（Chee-Wee Tan） 教授
主持人：工商管理学院 陈扬教授
时间：2022年11月8日（周二）16:00-17:30
举办地点：腾讯会议 ID：812-562-681
主办单位：工商管理学院 国际交流与合作处 科研处
主讲人简介：
Chee-Wee Tan is a Professor at the Department of Digitalization in Copenhagen Business School (CBS), an Honorary Professor of Business Analytics and Digitalization at the Nottingham University Business School China in the University of Nottingham Ningbo China (UNNC), an Adjunct Professor at the School of Business in Monash University, a Distinguished Research Scholar at the Faculty of Business in Lingnan University (LNU), a Guest Professor at the School of Management in the University of Science and Technology of China (USTC), and a Visiting Professorial Fellow at the School of Information Systems and Technology Management in University of New South Wales (UNSW). He received his Ph.D. in Management Information Systems from the University of British Columbia. His research interests focus on design and innovation issues related to digital services. His work has been published in leading peer-reviewed journals such as MIS Quarterly (MISQ), Journal of Operations Management (JOM), Information Systems Research (ISR), Journal of Management Information Systems (JMIS), and the Journal of the Association for Information Systems (JAIS) among others. Apart from his current appointment as a Senior Editor for MISQ, Chee-Wee has served or is currently serving on the editorial boards for ACM Distributed Ledger Technologies: Research and Practice (DLT), DSS, EJIS, Industrial Management & Data Systems (IMDS), IEEE Transactions on Engineering Management (IEEE-TEM), Information & Management (I&M), Information Systems Journal (ISJ), Internet Research (IntR), Journal for the Association of Information Systems (JAIS), Journal of Computer Information Systems (JCIS), Journal of Management Analytics (JMA), and JMIS. Finally, Chee-Wee is the co-director of the joint research center between CBS and the Antai College of Economics and Management (ACEM) in Shanghai Jiao Tong University (SJTU) as well as the Vice President of Publications for the Association of Information Systems (AIS).
陈致玮教授是哥本哈根商学院数字化系教授，宁波诺丁汉大学商学院中国区商业分析与数字化荣誉教授，莫纳什大学商学院兼职教授，岭南大学商学院杰出研究学者，中国科学技术大学管理学院客座教授，澳大利亚新南威尔士大学信息系统与技术管理学院客座教授。他在英属哥伦比亚大学获得管理信息系统博士学位。他的研究兴趣集中在与数字服务相关的设计和创新问题。他的论文发表在领先的同行评审期刊上，如MIS季刊(MISQ)、运营管理杂志(JOM)、信息系统研究(ISR)、管理信息系统杂志(JMIS)和信息系统协会杂志(JAIS)等。除了担任MISQ的高级编辑之外，陈致玮教授曾经或目前在ACM Distributed Ledger Technologies编委会任职:《研究与实践》(DLT)、《DSS》、《EJIS》、《工业管理与数据系统》(IMDS)、《IEEE工程管理汇刊》(IEEE-TEM)、《信息与管理》(I&M)、《信息系统学报》(ISJ)、《互联网研究》(IntR)、《信息系统协会学报》(JAIS)、《计算机信息系统学报》(JCIS)、《管理分析》(JMA)和《JMIS》。此外，陈致玮教授是CBS和上海交通大学(SJTU)安泰经济与管理学院(ACEM)联合研究中心的联合主任，也是信息系统协会(AIS)出版部副主任。
内容简介:
Armed with automated matchmaking rules, B2B sharing economy platforms solicit labor from the crowd to fulfill the needs of enterprise clients and generate revenue from repeated orders. To this end, we endeavor to identify focal considerations in the design of matchmaking rules and validate the effectiveness of these considerations in meeting the interests of platforms, clients, and service providers. To identify matchmaking considerations, we interviewed employees of a B2B sharing economy platform for container truck road transportation. Thematic analysis on primary data reveals situational and experiential fit as focal considerations in designing matchmaking rules. Empirical analysis on secondary operational data was conducted to validate the effectiveness of situational and experiential fit on order operational efficiency, platform profitability and truck driver income. Results indicate that experiential fit exerts a predominant effect on order dispatching and execution performance cared by clients but a negative effect on financial performance cared by platform and service providers whereas the role of situational fit in several business processes remains insignificant despite generating more profit per order. Empirical findings not only attest to the instrumental role of experiential fit when developing matchmaking in B2B sharing economy platforms, but they further reveal that striking a balance between situational and experiential fit is dependent on the tradeoff between operational efficiency and financial profits for catering to the interests of different parties on platform.
B2B共享经济平台借助自动配对规则，从人群中招揽劳动力，满足企业客户的需求，并通过重复订单产生收入。为此，我们努力确定配对规则设计中的重点考虑因素，并验证这些因素在满足平台、客户和服务提供者利益方面的有效性。为了确定配对的考虑因素，我们采访了一家集装箱卡车道路运输B2B共享经济平台的员工。对原始数据的主题分析表明，情境匹配和经验匹配是配对规则设计的重点考虑因素。对二手运营数据进行实证分析，验证情景匹配和经验匹配对订单运营效率、平台盈利能力和卡车司机收入的影响。结果表明，经验匹配对客户关心的订单调度和执行绩效有显著影响，但对平台和服务提供商关心的财务绩效有负向影响，而情境匹配在多个业务流程中的作用并不显著，尽管每单利润更高。实证结果不仅证明了经验匹配在B2B共享经济平台发展配对时的工具作用，而且进一步揭示了在情境匹配和经验匹配之间取得平衡依赖于运营效率和财务利润之间的权衡，以满足平台上不同各方的利益。
