Author Abstract
We investigate how dynamic pricing can lead to more product returns in the online retail industry. Using detailed sales data of more than two million transactions from the Indian online retail market, where price promotions are very common, we document two types of strategic customer behavior that have not been considered in previous research. First, customers who monitor product prices after purchase may initiate opportunistic returns because of price drops. Second, customers who anticipate a future return may strategically choose a payment method that facilitates product returns. Our logistic regression models indicate that (1) realized post-purchase price drops lead to a higher probability of return, and (2) anticipated price drops after purchase lead to a higher probability of using cash on delivery, a payment method with a lower return cost for consumers. Our findings are robust to alternative model specifications and sample selection procedures. We demonstrate that an optimal pricing policy should take into consideration the potential costs of two types of strategic customer behavior: opportunistic returns and strategic choice of payment method.
Paper Information
- Full Working Paper Text
- Working Paper Publication Date: September 2018
- HBS Working Paper Number: HBS Working Paper #19-030
- Faculty Unit(s): Marketing; Technology and Operations Management
