Economic Analysis of Network Effects on Sponsored Content: A Hierarchical Game Theoretic Approach

The growing competition drives the mobile network operators (MNOs) to explore adding time flexibility to the traditional data plan, which consists of a monthly subscription fee, a data cap, and a per-unit fee for exceeding the data cap. The rollover data plan, which allows the unused data of the previous month to be used in the current month, provides the subscribers with the time flexibility. In this paper, we formulate two MNOs' market competition as a three-stage game, where the MNOs decide their data mechanisms (traditional or rollover) in Stage I and the pricing strategies in Stage II, and then users make their subscription decisions in Stage III. Different from the monopoly market where an MNO always prefers the rollover mechanism over the traditional plan in terms of profit, MNOs may adopt different data mechanisms at an equilibrium. Specifically, the high-QoS MNO would gradually abandon the rollover mechanism as its QoS advantage diminishes. Meanwhile, the low-QoS MNO would progressively upgrade to the rollover mechanism. The numerical results show that the market competition significantly limits MNOs' profits, but both MNOs obtain higher profits with the possible choice of the rollover data plan.

Section: Related Literaturementioning

confidence: 99%

Duopoly Competition for Mobile Data Plans with Time Flexibility

Wang

Gao

Huang

2020

“…There have been many excellent studies on the wireless data plan optimizations (e.g., [10], [11], [12], [13]). However, they did not take into account the recently introduced rollover mechanism or the ubiquitous multi-cap scheme.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Cap Optimization for Wireless Data Plans with Time Flexibility

Wang

Gao

Huang

2020

An effective way for a Mobile network operator (MNO) to improve its revenue is price discrimination, i.e., providing different combinations of data caps and subscription fees. Rollover data plan (allowing the unused data in the current month to be used in the next month) is an innovative data mechanism with time flexibility. In this paper, we study the MNO's optimal multi-cap data plans with time flexibility in a realistic asymmetric information scenario. Specifically, users are associated with multi-dimensional private information, and the MNO designs a contract (with different data caps and subscription fees) to induce users to truthfully reveal their private information. This problem is quite challenging due to the multi-dimensional private information. We address the challenge in two aspects. First, we find that a feasible contract (satisfying incentive compatibility and individual rationality) should allocate the data caps according to users' willingness-to-pay (captured by the slopes of users' indifference curves). Second, for the non-convex data cap allocation problem, we propose a Dynamic Quota Allocation Algorithm, which has a low complexity and guarantees the global optimality. Numerical results show that the time-flexible data mechanisms increase both the MNO's profit (25% on average) and users' payoffs (8.2% on average) under price discrimination. Index Terms-Price discrimination, time flexibility, rollover data plan, multi-dimensional contract. ! • Part of the results appeared in ACM MobiHoc 2018 [1] and ACM NetEcon 2017 [2].Step I: MNO collects information from market and estimates the statistics of users' preferences.Step III: MNO optimizes the multi-cap contract under the chosen data mechanism considering users' private preferences.

“…Some prior studies analyzed mobile services by jointly considering the congestion effect and network effect among users [25], [26], [27], [28]. For example, Zhang et al in [25] studied mobile caching users, who pre-cache contents and disseminate the contents to users requesting them.…”

Section: Congestion Effect and Network Effectmentioning

confidence: 99%

Pricing for Collaboration between Online Apps and Offline Venues

Iosifidis

Shou

et al. 2020

An increasing number of mobile applications (abbrev. apps), like Pokemon Go and Snapchat, reward the users who physically visit some locations tagged as POIs (places-of-interest) by the apps. We study the novel POI-based collaboration between apps and venues (e.g., restaurants). On the one hand, an app charges a venue and tags the venue as a POI. The POI tag motivates users to visit the venue, which potentially increases the venue's sales. On the other hand, the venue can invest in the app-related infrastructure, which enables more users to use the app and further benefits the app's business. The apps' existing POI tariffs cannot fully incentivize the venue's infrastructure investment, and hence cannot lead to the most effective app-venue collaboration. We design an optimal two-part tariff, which charges the venue for becoming a POI, and subsidizes the venue every time a user interacts with the POI. The subsidy design efficiently incentivizes the venue's infrastructure investment, and we prove that our tariff achieves the highest app's revenue among a general class of tariffs. Furthermore, we derive some counter-intuitive guidelines for the POI-based collaboration. For example, a bandwidth-consuming app should collaborate with a low-quality venue (users have low utilities when consuming the venue's products).