题　目：The Value of Logistic Flexibility in E-commerce

嘉　宾：Bing Bai, Ph.D. Candidate, Washington University in St. Louis

主持人：花成 助理教授 tyc1286太阳成集团

时　间：2022年11月3日（周四）9:00-10:30am

地　点：腾讯会议（校内师生如需获取会议号和密码，请于11月2日下午17点前发送电邮至managementscience@acem.sjtu.edu.cn）

内容简介:

Shipping experience improvement has been an essential business strategy in e-commerce. Beyond investing directly in reducing shipping speed, online retailers have recently expanded their focus on other shipping strategies, such as offering consumers the option to pick up orders locally in a station. This paper uses the opening of hundreds of such pick-up stations as a natural experiment to study the impact of these stations on consumers. We find that the introduction of pick-up stations has increased total sales by 3.8%. In contrast with past literature, we show that shipping time reduction is not the driving factor on the impact of pick-up stations. Yet, the logistic flexibility introduced by pick-up stations explains the sales impact. To explicitly examine how logistic flexibility affects consumers' decisions on purchases, we develop and estimate a structural model on consumer choice. In our model, consumers value two types of logistics flexibility--the flexibility to choose to pick up their items in their preferred time, denoted as the value of time flexibility, and the flexibility to delay such picking time decisions after packages arrive, denoted as the value of choice flexibility. We show that the value of time flexibility accounts for 76.2% of the impact on sales, while the value of choice flexibility accounts for the remaining 23.8%. Using our estimated model, we develop a counterfactual strategy in building pick-up stations that could achieve the sales lift with 56.4% fewer stations. Last but not least, using our estimated time flexibility, we also develop a novel shipping strategy without pick-up stations that could improve the sales by 8.4%.

演讲人简介：

Bing Bai is a Ph.D. candidate of Supply Chain, Operations, and Technology at Olin Business School, Washington University in St. Louis. Her research focuses on data-driven problems in the digitization of online platforms. She implements field experiments, and uses structural models, causal inference and machine learning to study human behaviors and the human-algorithm connections on platforms. She was the second place of 2021 CSAMSE Best Paper Award Competition, and the finalist of 2020 CBOM Junior Scholar Paper Competition. Before she entered Olin Business School, she got her BS degree in Mathematics and Physics from Tsinghua University. For more information, please visit her website at https://bingbai.net/.

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