Pricing Wireless Access Services: The Effect of Offloading and Users ’ Bounded Rationality (original) (raw)

The Effect of WiFi Offloading on Pricing Wireless Services

2015

WiFi offloading has been recently proposed as a cost-effective solution for coming up against the unprecedented increase in the mobile data traffic volume. However, apart from reducing the operational costs of a network operator, WiFi offloading can be also promoted as an alternative low-cost access service for users with low willingness-to-pay. In this paper, we consider a monopolistic scenario of a Mobile Virtual Network Operator (MVNO) offering LTE and WiFi access services and find the optimal pricing decisions. We further illustrate that the presence of reluctant users to switch to the WiFi service could increase the profits of the MVNO.

How beneficial is the WiFi offloading? A detailed game-theoretical analysis in wireless oligopolies

2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2016

The rapid advances in networking, mobile computing, and virtualization, lead to a dramatic increase in the traffic demand. A cost-effective solution for serving it, while maintaining a good quality of service (QoS), would be to offload a part of the traffic originally targeted for cellular base stations (BSs) to a WiFi infrastructure. Related work on the WiFi offloading often considers markets with a single provider and omits parameters, such as the effect of the offloading on the perceived QoS by users, the capacity of the WiFi infrastructure, and competition of providers. In contrast to these approaches, this paper develops a detailed modeling framework for analysing the WiFi offloading using network economics, game theory, and queueing networks. It also proposes a novel network aggregation technique to reduce the computational complexity of the analysis. Using this framework, the performance of WiFi offloading was evaluated under various scenarios with respect to the bandwidth of BSs and APs, coverage of WiFi, and user preferences. Our results highlight that it is not always profitable for providers to invest in a large WiFi infrastructure. The limited capacity of the WiFi APs restricts the benefits of the offloading.

Pricing for Mobile Virtual Network Operators: The contribution of u-map

The mobile traffic growth is a catalyst of further technological advancements and evolution in wireless access markets. This work focuses on the joint problem of price setting for a Mobile Virtual Network Operator (MVNO), which serves end users in the retail market, and for the Mobile Network Operator, which leases its network to the MVNO at the wholesale market. We show that information about user profiles enables operators to achieve maximum profit. U-map, a crowd-sourcing platform that collects users preferences and builds user profiles, can provide such information. The analysis demonstrates that when only one operator employs (partial) information, the profit of both operators is affected. Furthermore, the cooperation between the operators results in higher profit compared to blind competition.

Pricing and revenue sharing in secondary market of mobile internet access

2015 IEEE 34th International Performance Computing and Communications Conference (IPCCC), 2015

There is a fast growing number of public spaces offering Wi-Fi access to meet the rising demands for Internet access. It is common for such service to be offered to users at no charge or for a flat fee. Both situations provide very little incentive for Wi-Fi providers to offer better service to the users. Similarly, Wi-Fi providers pay a monthly flat rate to ISP for Internet access and, this too does not incentivize ISP to offer better service to Wi-Fi users. As a result, Wi-Fi users may experience poor connection when network becomes congested during peak hours. In this paper we propose a dynamic pricing scheme for Internet access and a revenue sharing mechanism that provides incentives for both ISP and Wi-Fi providers to offer better service to their users. We build our revenue sharing model based on Shapley value mechanism. Importantly, our proposed revenue sharing mechanism captures the power negotiation between ISP and Wi-Fi providers, and how shifts in power influences revenue division. Specifically, the model assures that the party who contributes more receives a higher portion of the revenue. In addition, our simulation demonstrates that our model captures the bargaining power shifts between Wi-Fi providers and ISP, and shows that the division of revenue asymptotically converges to a percentage value.

Technology Choices and Pricing Policies in Wireless Networks

2011

This paper studies the provision of a wireless network by a monopolistic service provider who may be either benevolent (seeking to maximize social welfare) or selfish (seeking to maximize provider profit). The paper addresses questions that do not seem to have been studied in the engineering literature on wireless networks: Under what circumstances is it feasible for a provider, either benevolent or selfish, to operate a network in such a way as to cover costs? How is the optimal behavior of a benevolent provider different from the optimal behavior of a selfish provider, and how does this difference affect social welfare? And, most importantly, how does the medium access control (MAC) technology influence the answers to these questions? To address these questions, we build a general model, and provide analysis and simulations for simplified but typical scenarios; the focus in these scenarios is on the contrast between the outcomes obtained under carrier-sensing multiple access (CSMA) and outcomes obtained under time-division multiple access (TDMA). Simulation results demonstrate that differences in MAC technology can have a significant effect on social welfare, on provider profit, and even on the (financial) feasibility of a wireless network.

On Pricing of 5G Services

GLOBECOM 2017 - 2017 IEEE Global Communications Conference, 2017

IT and telco providers are preparing for the era of 5G; in terms of technology, the driving force is virtualization, both for computing and networking. The 5G services will be superior than today's online services not only in technological aspects, but also from an economic and business perspective: fast service creation, effective utilization of resources, dynamic adaption to actual demand are all direct benefits of the virtualized infrastructure. In this paper we study the economic interactions between 5G resource providers and customers: we formalize how resources should be priced and selected for being booked. In particular we show that usage-based pricing is an incomemaximizing scheme for providers, and we derive the problem the customers need to solve for cost-optimizing service deployment.

Technology Choices and Pricing Policies in Public and Private Wireless Networks

2010

This paper studies the provision of a wireless network by a monopolistic provider who may be either benevolent (seeking to maximize social welfare) or selfish (seeking to maximize provider profit). The paper addresses questions that do not seem to have been studied before in the engineering literature on wireless networks: Under what circumstances is it feasible for a provider, either benevolent or selfish, to operate a network in such a way as to cover costs? How is the optimal behavior of a benevolent provider different from the optimal behavior of a selfish provider, and how does this difference affect social welfare? And, most importantly, how does the medium access control (MAC) technology influence the answers to these questions? To address these questions, we build a general model, and provide analysis and simulations for simplified but typical scenarios; the focus in these scenarios is on the contrast between the outcomes obtained under carrier-sensing multiple access (CSMA) and outcomes obtained under time-division multiple access (TDMA). Simulation results demonstrate that differences in MAC technology can have a significant effect on social welfare, on provider profit, and even on the (financial) feasibility of a wireless network.

Demand for and Pricing of Mobile Internet: Evidence from a Real-World Pricing Experiment

SSRN Electronic Journal, 2000

ABSTRACT I study a budget-constrained, private-valuation, sealed-bid sequential auction with two incompletely-informed, risk-neutral bidders in which the valuations and income may be non-monotonic functions of a bidder's type. Multiple equilibrium symmetric bidding functions may exist that differ in allocation, efficiency and revenue. The sequence of sale affects the competition for a good and therefore also affects revenue and the prices of each good in a systematic way that depends on the relationship among the valuations and incomes of bidders. The sequence of sale may affect prices and revenue even when the number of bidders is large relative to the number of goods. If a particular good, say [alpha], is allocated to a strong bidder independent of the sequence of sale, then auction revenue and the price of good [alpha] are higher when good [alpha] is sold first.

Demand and Supply Model in the Network Market: Two-Sided Markets the Case of the Cellular Industry

The Open Management Journal, 2011

In this paper we reconsidered several pricing policies in the network industry and compared the advantages of some (five) policies on other policies from point of views of the monopoly who considers profit maximization The uniqueness of the network industry is that the demands for services include at least two parties, the sender of a message and the receiver of the message. These demands that are not necessarily symmetric can be estimated very accurately using nowadays technologies like RFID etc. by seller of the network services. Knowing the accurate demands the optimal pricing can be determined.

A pricing model of GPRS networks with Wi-Fi integration for" heavy" data users

Proceedings of IEEE second …, 2005

As wireless services have become increasingly integrated and their demand is mounting, Wi-Fi provides an appealing opportunity for the GSM/GPRS operators to enhance their data capability. By integrating both networks, operators are able to provide 3G-like services. However, both networks have different data rates and capacity, which makes pricing a challenging issue. In this paper we propose a pricing model for GPRS networks integrated with Wi-Fi, which applies to data users with high service demand ("heavy"). Through optimization technique, our proposed model identifies how the integration can play a significant role in increasing operators' overall revenue and potentially improving the performance of GPRS networks.