Should a seller make information about its products readily accessible to customers, so that customers do not have to incur any substantive cost—in terms of time and effort—to learn about those products? To help answer this question, we consider a monopolist selling two substitute products to a population of customers, who have differing tastes about the products. Each customer a priori has uncertainty about whether or not he will like each of the products. The seller may choose to make product information easily accessible, thereby allowing customers to resolve their uncertainties for free. Otherwise, customers may conduct research to resolve their uncertainties by incurring a search cost before making purchase decisions. We consider three “information structures” differing in whether the seller makes information about the products freely accessible or not. Our primary objective is to determine which structure gives the seller the highest revenue, while accounting for the seller’s pricing decisions as well as the induced customer responses to both the information structure and prices. We find that if each customer’s uncertainties are small in magnitude but highly positively correlated, then withholding both products’ information is the best for the seller. If the uncertainties are small in magnitude and negatively correlated, then providing one product’s information but not the other’s is the best. If the uncertainties are large in magnitude and positively correlated, then providing both products’ information is the best. We also show that when the correlation is negative, withholding both products’ information cannot be optimal. In addition, we also analyze various extensions of the model. These include a variant in which customers’ research is imperfect and may yield incorrect information to the customers, and a variant in which each customer’s uncertainty about a product can be decomposed into multiple uncertainties associated with individual attributes of the product.
- consumer search
ASJC Scopus subject areas
- Management Science and Operations Research
- Industrial and Manufacturing Engineering
- Management of Technology and Innovation