How do you know you won't like it if you've never tried it? Preference discovery and strategic bundling

The Institute of Economics will hold a seminar meeting as part of its Seminar Series on Tuesday, January 23, 2024: Paolo Pin from University of Siena will present the paper “How do you know you won't like it if you've never tried it? Preference discovery and strategic bundling" (with Sebastiano Della Lena and Alessio Muscillo).

Abstract

In this paper, we consider the interaction between a perfectly informed provider and a representative consumer who has taste uncertainty regarding a set of goods and learns through consumption. We characterize the conditions under which the consumer learns or does not learn about their own preferences or qualities of goods, and the consequent optimal strategies of a provider who wants to maximize the perceived preferences of the consumer regarding the goods. We show that the provider can succeed in manipulating the consumer's perceived preferences by exploiting strategic bundling and initial biases. In particular, we assume that, over time, the provider offers different consumption bundles that form a dynamic network of co-occurrences among the goods. After consuming each bundle, the consumer updates their estimations of their own preferences through maximum likelihood. We demonstrate that the provider may want to hide the quality of overestimated goods through bundling, while displaying the quality of underestimated goods through single-item consump-tion. The manipulation is even more effective when the marginal profits for goods are heterogeneous. In such cases, the provider uses underestimated low-margin goods to boost the selling of high-margin goods. In the long run, the consumer learns, unless there is persistent multicollinearity (induced by the provider) in the network of co-occurrences or if consumption stops. In the case of multicollinearity, the con-sumer learns their preference for the whole bundle but not the marginal utility of each good, which allows the provider to exploit different profitability. Strategic bundling can also be used to slow down the learning process and earn higher profits by exploiting temporary positive biases. We show how optimal bundling is related to eigenvector centralities in the co-occurrence and covariance network, depending on the provider's objectives.

The Seminar will be held in Aula 3.

For online partecipation use this link.