A Multicriteria Analysis on the Strategies to Open Taiwan's Mobile Virtual Network Operators Services

[[abstract]]This study investigates the trends followed by MVNOs (Mobile Virtual Network Operators) in the last three years and analyzes the strategies that can contribute to the success of Taiwan's telecommunications industry and marketing. We apply the method and concept of PATTERN (Planning Assistance Through Technical Evaluation of Relevance Number) to establish relevant systems for searching out the key successful factors of strategies to attract MVNOs. We also use the fuzzy Multi-Criteria Decision Making (MCDM) method for analyzing the different preference of a decision group in the criteria weights and for ranking the alternatives in a fuzzy environment in order to provide a strategy scheme. These results provide a reference to assist telecommunications operators, 3G license owners, potential MVNOs, and equipment manufacturers when working out business plans.[[incitationindex]]SCI[[booktype]]紙

Game Theoretical Analysis of a Multi-MNO MVNO Business Model in 5G Networks

This work has been supported by the Spanish Ministry of Science, Innovation and Universities (MCIU/AEI) and the European Union (FEDER/UE) through Grant PGC2018-094151-B-I00 and partially supported by Politecnica Salesiana University (Salesian Polytechnic University) in Ecuador through a Ph.D. scholarship granted to the first author.Sacoto Cabrera, EJ.; Guijarro, L.; Maillé, P. (2020). Game Theoretical Analysis of a Multi-MNO MVNO Business Model in 5G Networks. Electronics. 9(6):1-26. https://doi.org/10.3390/electronics9060933S12696Gruber, H. (2001). Competition and innovation. Information Economics and Policy, 13(1), 19-34. doi:10.1016/s0167-6245(00)00028-7Berne, M., Vialle, P., & Whalley, J. (2019). An analysis of the disruptive impact of the entry of Free Mobile into the French mobile telecommunications market. Telecommunications Policy, 43(3), 262-277. doi:10.1016/j.telpol.2018.07.007Nakao, A., Du, P., Kiriha, Y., Granelli, F., Gebremariam, A. A., Taleb, T., & Bagaa, M. (2017). End-to-end Network Slicing for 5G Mobile Networks. Journal of Information Processing, 25(0), 153-163. doi:10.2197/ipsjjip.25.153Son, P. H., Son, L. H., Jha, S., Kumar, R., & Chatterjee, J. M. (2019). Governing mobile Virtual Network Operators in developing countries. Utilities Policy, 56, 169-180. doi:10.1016/j.jup.2019.01.003Archivo Situacionista HispanoHttp://Www.Statista.Com/Statistics/671623/Global-Mvno-Market-Size/Lingjie Duan, Lin Gao, & Jianwei Huang. (2014). Cooperative Spectrum Sharing: A Contract-Based Approach. IEEE Transactions on Mobile Computing, 13(1), 174-187. doi:10.1109/tmc.2012.231Sacoto-Cabrera, E. J., Sanchis-Cano, A., Guijarro, L., Vidal, J. R., & Pla, V. (2018). Strategic Interaction between Operators in the Context of Spectrum Sharing for 5G Networks. Wireless Communications and Mobile Computing, 2018, 1-10. doi:10.1155/2018/4308913Samdanis, K., Costa-Perez, X., & Sciancalepore, V. (2016). From network sharing to multi-tenancy: The 5G network slice broker. IEEE Communications Magazine, 54(7), 32-39. doi:10.1109/mcom.2016.7514161Rost, P., Banchs, A., Berberana, I., Breitbach, M., Doll, M., Droste, H., … Sayadi, B. (2016). Mobile network architecture evolution toward 5G. IEEE Communications Magazine, 54(5), 84-91. doi:10.1109/mcom.2016.7470940Afolabi, I., Taleb, T., Samdanis, K., Ksentini, A., & Flinck, H. (2018). Network Slicing and Softwarization: A Survey on Principles, Enabling Technologies, and Solutions. IEEE Communications Surveys & Tutorials, 20(3), 2429-2453. doi:10.1109/comst.2018.2815638Barakabitze, A. A., Ahmad, A., Mijumbi, R., & Hines, A. (2020). 5G network slicing using SDN and NFV: A survey of taxonomy, architectures and future challenges. Computer Networks, 167, 106984. doi:10.1016/j.comnet.2019.106984Khan, L. U., Yaqoob, I., Tran, N. H., Han, Z., & Hong, C. S. (2020). Network Slicing: Recent Advances, Taxonomy, Requirements, and Open Research Challenges. IEEE Access, 8, 36009-36028. doi:10.1109/access.2020.2975072Kim, D., & Kim, S. (2018). Network slicing as enablers for 5G services: state of the art and challenges for mobile industry. Telecommunication Systems, 71(3), 517-527. doi:10.1007/s11235-018-0525-2Foukas, X., Patounas, G., Elmokashfi, A., & Marina, M. K. (2017). Network Slicing in 5G: Survey and Challenges. IEEE Communications Magazine, 55(5), 94-100. doi:10.1109/mcom.2017.1600951Cricelli, L., Grimaldi, M., & Levialdi Ghiron, N. (2012). The impact of regulating mobile termination rates and MNO–MVNO relationships on retail prices. Telecommunications Policy, 36(1), 1-12. doi:10.1016/j.telpol.2011.11.013Shakkottai, S., & Srikant, R. (2007). Network Optimization and Control. Foundations and Trends® in Networking, 2(3), 271-379. doi:10.1561/1300000007Habib, M. A., & Moh, S. (2019). Game theory-based Routing for Wireless Sensor Networks: A Comparative Survey. Applied Sciences, 9(14), 2896. doi:10.3390/app9142896Su, R., Zhang, D., Venkatesan, R., Gong, Z., Li, C., Ding, F., … Zhu, Z. (2019). Resource Allocation for Network Slicing in 5G Telecommunication Networks: A Survey of Principles and Models. IEEE Network, 33(6), 172-179. doi:10.1109/mnet.2019.1900024Guijarro, L., Pla, V., Vidal, J. R., & Naldi, M. (2019). Competition in data-based service provision: Nash equilibrium characterization. Future Generation Computer Systems, 96, 35-50. doi:10.1016/j.future.2019.01.044Banerjee, A., & Dippon, C. M. (2009). Voluntary relationships among mobile network operators and mobile virtual network operators: An economic explanation. Information Economics and Policy, 21(1), 72-84. doi:10.1016/j.infoecopol.2008.10.003Caballero, P., Banchs, A., De Veciana, G., & Costa-Perez, X. (2019). Network Slicing Games: Enabling Customization in Multi-Tenant Mobile Networks. IEEE/ACM Transactions on Networking, 27(2), 662-675. doi:10.1109/tnet.2019.2895378Fantacci, R., & Picano, B. (2020). When Network Slicing Meets Prospect Theory: A Service Provider Revenue Maximization Framework. IEEE Transactions on Vehicular Technology, 69(3), 3179-3189. doi:10.1109/tvt.2019.2963462Fossati, F., Moretti, S., Perny, P., & Secci, S. (2020). Multi-Resource Allocation for Network Slicing. IEEE/ACM Transactions on Networking, 28(3), 1311-1324. doi:10.1109/tnet.2020.2979667Cooperation among Competitors: Network sharing can increase Consumer Welfarehttp://dx.doi.org/10.2139/ssrn.3571354Mendelson, H. (1985). Pricing computer services: queueing effects. Communications of the ACM, 28(3), 312-321. doi:10.1145/3166.3171Liu, C., Li, K., Xu, C., & Li, K. (2016). Strategy Configurations of Multiple Users Competition for Cloud Service Reservation. IEEE Transactions on Parallel and Distributed Systems, 27(2), 508-520. doi:10.1109/tpds.2015.2398435Liu, C., Li, K., Li, K., & Buyya, R. (2017). A New Cloud Service Mechanism for Profit Optimizations of a Cloud Provider and Its Users. IEEE Transactions on Cloud Computing, 1-1. doi:10.1109/tcc.2017.2701793Niyato, D., & Hossain, E. (2008). Competitive Pricing for Spectrum Sharing in Cognitive Radio Networks: Dynamic Game, Inefficiency of Nash Equilibrium, and Collusion. IEEE Journal on Selected Areas in Communications, 26(1), 192-202. doi:10.1109/jsac.2008.080117Guijarro, L., Vidal, J., & Pla, V. (2018). Competition in Service Provision between Slice Operators in 5G Networks. Electronics, 7(11), 315. doi:10.3390/electronics7110315Sacoto-Cabrera, E. J., Guijarro, L., Vidal, J. R., & Pla, V. (2020). Economic feasibility of virtual operators in 5G via network slicing. Future Generation Computer Systems, 109, 172-187. doi:10.1016/j.future.2020.03.044Mandjes, M. (2003). Pricing strategies under heterogeneous service requirements. Computer Networks, 42(2), 231-249. doi:10.1016/s1389-1286(03)00191-9Reynolds, S. S. (1987). Capacity Investment, Preemption and Commitment in an Infinite Horizon Model. International Economic Review, 28(1), 69. doi:10.2307/252686

EU-Turkey Accession Negotiations: Impact assessment of Chapter 10 on information society and media

In the past few years, Turkey has launched very important and ambitious reforms in the information society and media sector. Even more substantial changes are expected in 2009, after the new e-communications law has been approved at the end of 2008. Apart from the 49 expected pieces of secondary legislation foreseen to implement the new Law No 5809, Turkey has also planned important steps in the domain of spectrum policy, with licenses for WiMAX soon to be awarded. This report analyses the current state of advancement of Turkey\u2019s regulatory reform in this sector, and formulates suggestions for reform on the basis of a complex and articulated impact assessment exercise. Our final conclusion is that Turkey may profit significantly from a set of targeted reforms, aimed at solving existing problems that have been highlighted, i.a., by the European Commission and also by the recent ECTA Scorecard 2008

The regulation of national roaming

National roaming is a measure that can be agreed commercially between operators to extend coverage or can be imposed or facilitated by governments as a means to increase competition amongst networks. It has been used with varying degrees of success in a range of countries, notably in the European Union. It has generally faced resistance from established operators, reluctant to assist prospective competitors and reduce their shares of the market. In some countries implementation has been so poor as to fail in the objectives. The absence of agreed procedures and performance indicators may have contributed to some of those failures. The costs of deploying third generation networks are causing some operators to look at more extensive agreements, sharing radio access networks, rather than national roaming. A further factor has been the lack of prospective entrants in mature markets, making national roaming less important than had been expected. --

Matching theory as enabler of efficient spectrum management in 5G networks

This is the peer reviewed version of the following article: Tsirakis, C, Lopez‐Aguilera, E, Agapiou, G, Varoutas, D. Matching theory as enabler of efficient spectrum management in 5G networks. Trans Emerging Tel Tech. 2020; 31:e3769., which has been published in final form at https://doi.org/10.1002/ett.3769. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.This paper analyzes the spectrum trading problem in virtualized fifth generation (5G) networks in order to enhance the network performance with respect to the spectrum utilization. The problem is modeled as a Many-to-Many Matching (M2MM) game with utility-based preferences and determines the matching between mobile network operators and mobile virtual network operators. The two proposed versions of utility functions for each set aim at maximizing the satisfaction of both sets with conflicting interests and improving the overall spectrum efficiency. In the simulation evaluation, the proposed scheme is compared with three different schemes in terms of the system utility, individual and pair matching satisfaction. We also investigate the scalability aspects, the strategy plan impact on the matching performance of our proposed scheme, and, at the same time, we attempt to make appropriate assumptions closer to reality. Our proposed scheme shows much better performance than the other schemes achieving a quite high level of satisfaction for the matching result on both sets.Postprint (author's final draft

Horizontal cooperation on investment: Evidence from mobile network sharing

We present a structural model to investigate the effects of horizontal cooperation on investment in the context of telecommunication networks. More specifically, we estimate the effect of network sharing in the mobile telecommunications industry on prices, network quality and consumer welfare. The presented framework allows estimating the effects of different types of sharing agreements including common ownership of shared assets in a joint venture company or collaboration via geographical separation (geo-split principle). The proposed identification strategy relies on differences in the costs of network deployment of shared versus non-shared network infrastructure, with different costs affecting operators’ optimal choice of price and network quality. We apply the structural model to estimate the effects of a network sharing agreement in the Czech Republic, using a combination of unique datasets on prices, network quality measured as average download speed and operator’s costs of network deployment. The results of our model indicate that horizontal cooperation on investments may be beneficial for consumers. Specifically, the network sharing agreement under study generated cost savings for the sharing parties, which were passed-on to consumers in the form of lower prices and higher average download speed. Our findings are of relevance to the assessment of network sharing agreements, which, considering the substantial investment cost associated with the 5G technology, are likely to play an even greater role in the telecommunications industry in the future. The findings are also of relevance to the general literature on horizontal cooperation on investments