Opportunistic Returns and Dynamic Pricing: Empirical Evidence from Online Retailing in Emerging Markets

We investigate how dynamic pricing can lead to higher operational costs through more product returns in the online retail industry. Dynamic pricing has been widely applied by many online retailers. Research has shown that, in response to dynamic pricing, some customers choose to wait strategically in anticipation of a future discount. Using detailed sales data of more than 2 million transactions with return information from the Indian online retail market, we document two types of strategic customer behavior that have not been considered by previous research. First, customers who keep monitoring the price after purchase may initiate opportunistic returns because of price drops. Second, customers who anticipate a future return may strategically choose a payment method with a lower return cost. Our logistic regression model indicates that: (1) realized post-purchase price drops lead to higher probability of returns; (2) anticipated price drops after purchase lead to higher probability of using cash-on-delivery, a payment method with a lower return cost. Our findings are robust to alternative model specifications and sample selection procedures. In conclusion, we demonstrate that an optimal pricing policy should take into consideration the potential operational costs of two types of strategic customer behavior, opportunistic returns and strategic choice of payment method.