摘要：Digital platforms, such as e-commerce and peer-to-peer sharing platforms, often take an active role in assisting sellers with prod
平台参与的涟漪效应
The Ripple Effect of Platform Participation
讲座信息
主讲人
沈俏蔚教授
北京大学光华管理学院
日期和时间
2025年1月17日（周五）
10:30-12:00
地点
综合教学楼D504会议室
论文摘要
Digital platforms, such as e-commerce and peer-to-peer sharing platforms, often take an active role in assisting sellers with product descriptions, pricing, quality checks, and selling processes. While this platform participation benefits direct adopters, its impact on nonadopters, the entire platform, and the long-term impact on adopters remains unclear. We address this gap by examining a natural experiment in which a platform launched a platform-participated submarket to assist sellers. We find that the platform participation improves adopters' sales performance and listing behaviors. It also has a long-lasting effect beyond the platform-participated market as adopters learn from the platform practices and adjust their future behaviors. Interestingly, nonadopters experience a U-shaped effect: they are negatively impacted when the adoption rate is low but benefit when the adoption rate is high. Platform-level analyses reveal a similar nonlinear relationship: with a low adoption rate, platform-wide sales performance drops and sales concentration increases, while a higher adoption rate leads to improved overall sales performance and decreased sales concentration. Regardless of the adoption rate, both the platform and buyers benefit from improved listing behaviors among adopters and nonadopters alike. These findings have important implications for platform designers and policymakers concerned about the anticompetitive effects of platform participation.
主讲人简介
沈俏蔚教授
北京大学光华管理学院
沈俏蔚为北京大学光华管理学院市场营销系教授。她的研究领域包括企业与消费者决策的量化模型，社交与新媒体以及营销策略等。多篇论文发表于《Marketing Science》 和 《Management Science》等管理学领域国际顶级学术期刊， 并获2014年度美国运筹学与管理学协会 （INFORMS）营销科学John Little最佳论文提名奖。2017年获国家自然科学基金优秀青年科学基金。目前为国际顶级学术期刊 《Marketing Science》《Journal of Marketing》以及《International Journal of Research in Marketing》 的编委会成员，中国高等院校市场学研究会秘书长。她于2008年获得美国加州大学伯克利分校（UC Berkeley) 市场营销专业博士学位，此前获得北京大学经济学学士、硕士学位。2008年至2015年任教于美国宾夕法尼亚大学沃顿商学院，2015年秋至今任教于北京大学光华管理学院。
即时与及时：
加急服务承诺对订餐平台销量的影响
Expedited Service Promises: Evidence From a Food Ordering Platform
讲座信息
主讲人
李思敏教授
杜兰大学
日期和时间
2025年1月17日 (周五)
10:30 - 12:00
地点
综合教学楼D604会议室
论文摘要
Setting appropriate service promises is a challenge for on-demand platforms. Speedy promises are widely believed to boost sales, but should all service providers adopt aggressive promises? In this study, we leverage a quasi-experimental setting where expedited service promises (ESPs) were introduced for a subset of food items on a platform in a staggered manner. Using a stacked difference-in-differences framework, we find that ESPs increased overall item sales by 22.9%, driven by a 32.4% rise in on-demand orders, while advance-scheduled orders remained unaffected. This resulted in an 11.9 percentage point increase in the share of on-demand orders. However, not all items benefit equally from speedy promises. Dishes that were frequently delivered earlier than requested prior to ESPs saw larger sales boosts compared to those that were consistently late. This highlights how customers evaluate service promises against actual on-time performance. Interestingly, the biggest beneficiaries of ESPs were hot dishes that were delivered early—i.e., those hot dishes with “slack” in their promises. This provides empirical evidence of “earliness costs” and the risks of quality deterioration when promises are overly conservative. Contrary to the common wisdom of “under-promise and over-deliver,” our findings suggest otherwise for hot dishes. After all, no one wants their fries to go soggy before pickup. Our results provide actionable insights for restaurants when deciding how to quote promises for their food items based on serving temperature and current on-time performance.
主讲人简介
李思敏教授
杜兰大学
李思敏现任美国杜兰大学弗里曼商学院管理科学助理教授。她的研究主要聚焦于数字平台与医疗领域的运营管理挑战及创新。她运用因果推断结合经济学建模，探索包含需求管理，劳动力供应和信息共享等核心运营议题。李思敏拥有西北大学凯洛格管理学院的运营管理博士学位。在攻读博士学位前，她曾供职于微软，担任数据科学家一职。
来源：新浪财经
