Research Seminar Series: Vinayak Deshpande – Logistics Performance, Ratings, and its impact on Customer Purchasing Behavior and Sales in E-commerce Platforms

Thursday October 31, 2019 • 12:30 PM to 1:30 PM

• Kenan Center, 3rd Floor Boardroom

In this research, we examine the impact of logistics performance metrics such as delivery time, delivery delays, customer’s promised speed of delivery, order split, etc. on logistics service ratings of sellers on an e-commerce platform. Further, we analyze and quantify the impact of logistics service ratings and performance on customer purchase likelihood and sales. We use a large data set of customer orders from Alibaba’s Tmall platform and the Cainiao network to utilize ordered regression models to understand the variation in logistics ratings and its drivers. Later, we use a customer utility model to quantify the impact of logistics ratings on customer purchase likelihood.

We show that logistics ratings are negatively impacted by delivery time and delivery delays, but positively impacted by faster promised speed of delivery and total order amount paid. The impact of delivery delays on logistics ratings are moderated by the total order amount paid but not by faster promised speed of delivery. For example, a customer who paid a higher order amount is likely to give a more negative rating to a delayed order compared to an on-time order than a customer who paid a low order amount. Our results also show that splitting a customer order into multiple shipments, so that a part of the order is delivered on-time even if the overall order is delayed, does not improve logistics ratings.

Prior work on online ratings in e-commerce platforms have largely analyzed customer response to product functional performance and biases that exist with-in. Our study contributes to this stream of literature by examining customer experience from a service quality perspective by analyzing logistics service performance, logistics ratings and its impact on customer purchase likelihood. The insights from our study are relevant to independent sellers as well as e-commerce platform managers who aim to improve long-term online traffic and sales.