Dilemma of Data Sharing Alliance: When Do Competing Personalizing and Non‐Personalizing Firms Share Data

Abhijeet Ghoshal, Subodha Kumar and Vijay Mookerjee

Production and Operations Management, 2020, vol. 29, issue 8, 1918-1936

Abstract: We analyze a case where two competing firms, a personalizing firm that makes product recommendations and a non‐personalizing firm that does not recommend products, compete with each other and may participate in a data sharing alliance (in which the non‐personalizing firm shares its data with the personalizing firm). The customer is strategic as she first visits the personalizing firm to find out what product to purchase among the recommended ones and purchases the product eventually from one of the firms. Overall, the customer distributes all her purchases across both the firms—she purchases from the personalizing firm to maintain a profile quality with the firm (to continue to obtain good recommendations) and from the non‐personalizing firm to benefit from the lower prices of that firm. We analyze this setup in a two‐stage game to find the subgame perfect Nash Equilibrium. In the first stage, firms decide to share data, or not. In the second stage they play a simultaneous move price game. We find that the non‐personalizing firm is always willing to share its data with the personalizing firm, but the personalizing firm uses it only when the learning rate influence dominates the profile influence. When the personalizing firm improves its system and both firms share data, its own profit always increases and under certain conditions the profit of the non‐personalizing firm also increases. Finally, social surplus may increase as well when firms share data. This result has important implications for the policy‐makers controlling information sharing between firms.

Date: 2020
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