A General Equilibrium Model for Industries with Price and Service Competition
Operations Research
A network pricing game for selfish traffic
Proceedings of the twenty-fourth annual ACM symposium on Principles of distributed computing
Selfish Routing and the Price of Anarchy
Selfish Routing and the Price of Anarchy
Competition and Efficiency in Congested Markets
Mathematics of Operations Research
Price competition with elastic traffic
Networks - Games, Interdiction, and Human Interaction Problems on Networks
Price war with partial spectrum sharing for competitive wireless service providers
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Investment and Market Structure in Industries with Congestion
Operations Research
Price dynamics in competitive agile spectrum access markets
IEEE Journal on Selected Areas in Communications
Competition among telecommunication providers
Telecommunication Economics
Competition between wireless service providers sharing a radio resource
IFIP'12 Proceedings of the 11th international IFIP TC 6 conference on Networking - Volume Part II
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With the development of new technologies in a competitive context, infrastructure investment and licence purchase as well as existing technology maintenance are crucial questions for current and emerging operators. This paper presents a three-level game analysing this problem. At the highest level, the operators decide on which technologies to invest, given that some may already own licences or infrastructures. We limit ourselves to the realistic case where technologies are 3G, WiFi and WiMAX. At the intermediate level, with that set of operated technologies fixed, operators determine their service price. Finally, at the lowest level, customers choose their provider depending on the best combination of price and available quality of service. At each level, the best decision of actors depends on the actions of others, the interactions hence requiring to be studied as a (non-cooperative) game. The model is analysed by backward induction, meaning that decisions at a certain level depend on the equilibria reached at the lower levels. Different real-life cost scenarios are studied. Our model aims at helping both the operators to make their final decision on technological investments, and the regulator to determine an appropriate licence fee range for a better competition among providers.