How to Schedule the Marketing of Products with Negative Externalities

TL;DR

This paper investigates optimal scheduling strategies for marketing two products with negative externalities in social networks, aiming to maximize sales and ensure regret-free decisions, and provides efficient algorithms with guarantees.

Contribution

It introduces the first algorithmic approach to scheduling marketing of products with negative externalities, addressing both maximization and regret-proofness.

Findings

Maximizing sales is NP-hard.

Provided efficient algorithms with performance guarantees.

Developed regret-proof scheduling algorithms reaching Nash equilibria.

Abstract

In marketing products with negative externalities, a schedule which specifies an order of consumer purchase decisions is crucial, since in the social network of consumers, the decision of each consumer is negatively affected by the choices of her neighbors. In this paper, we study the problems of finding a marketing schedule for two asymmetric products with negative externalites. The goals are two-fold: maximizing the sale of one product and ensuring regret-free purchase decisions. We show that the maximization is NP-hard, and provide efficient algorithms with satisfactory performance guarantees. Two of these algorithms give regret-proof schedules, i.e. they reach Nash equilibria where no consumers regret their previous decisions. Our work is the first attempt to address these marketing problems from an algorithmic point of view.