Pricing optimization of rollover data plan

Abstract

Rollover data plans are attractive to mobile users by allowing them to keep their unused data for future use, and hence has been widely implemented by Mobile Network Operators (MNOs) around the world. In this work, we formulate a three-stage Stackelberg game to analyze the interactions between an MNO and its subscribed users under both traditional and rollover data plans. Specifically, in Stage I, the MNO decides which data plan(s) to implement; In Stage II, the MNO decides the price(s) of the data plan(s) to maximize its expected revenue; In Stage III, users make their individual subscription decisions to maximize their expected payoffs. Our analysis shows that in general, high evaluation users are more likely to choose the rollover data plan than medium evaluation users. More precisely, as the network substitutability increases, high evaluation users tend to choose the rollover data plan, while medium evaluation users tend to choose the traditional data plan. We further prove that the MNO can achieve the maximum revenue by only providing the rollover data plan (without bundling with the traditional data plan). Numerical results show that the rollover data plan can increase not only the MNO's revenue but also the users' payoffs (and hence the social welfare) comparing with the traditional data plan. We also compare two rollover data plans that differ in whether the rollover data is consumed prior to monthly data cap, and show that allowing the rollover data to be consumed before the monthly data cap is more beneficial to both users and the MNO.

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