Online ReviewsE-commerceDelivery PerformanceBayesian Models
New Jersey City University
Customers are increasingly using online reviews in their purchase decision-making processes. As sellers benefit from displaying several reviews with favorable ratings, many sellers solicit reviews from customers. When a customer places an order on an e-commerce platform, the seller gets a notification to fulfill the order, and the customer is notified of the estimated delivery date. Some customers receive their products on time, while others receive their orders either earlier or later than the notified delivery date. After customers receive their products, the sellers often solicit reviews. This research focuses on the impact of delivery performance on review ratings. Specifically, this study addresses two questions: (1) Do customers reward sellers for early delivery in the same way they penalize them for late deliveries? (2) What is the role of the temporal distance of rating in online ratings in the context of delivery performance? The study estimates ordinal logit models in the Bayesian framework. Findings of the study indicate that customers give much lower (a little higher) ratings to orders delivered late (early) than to orders delivered on time. Further, the findings indicate that temporal distance is positively associated with ratings for late deliveries. The study discusses the theoretical and managerial implications of these results.