臺灣博碩士論文加值系統

頻寬使用率最大化是目前政府電信政策的重要目標，適合的拍賣機制是影響頻寬使用率與政府收入最大化和的重要因素。近年來，學者不斷提出各種頻譜拍賣機制，以符合下世代無線通訊之需求，並滿足前述目標。唯如何設計與選擇最適合頻譜拍賣機制對於已開發國家和開發中國家之政府始終是最重要的電信政策。設計良好的拍賣機制可引起廠商參與競標的興趣，經營能力較佳的廠商自然有能力付出較高標金獲取執照，而支付意願最高之廠商通常能使頻譜之價值最大化，而標金也會接近市場價值並可為國家政府帶來可觀的收益。但如何定義頻譜拍賣機制並無絕對的答案，為了設計符合權變理論之決策分析架構以拍賣次世代無線通訊頻譜，本研究 將使用基於決策實驗室分析法(DEMATEL)之網路流程，已DEMATEL建構決策分析問題架構，並以基於決策實驗室分析法之網路流程求取對應因素之權重值，並以前述權重使用VIKOR法對應於各拍賣機制之評估準則績效值訂定適合的拍賣模式作為政府評估拍賣機制和決策之基準。本研究結果顯示出資訊是最重要的構面，而資訊當中的勾結度是最具有影響力來設計頻譜拍賣機制準則並決策公開向上的模式拍賣。本議題的標準可以作為政府電信政策定義選擇最合適的頻譜拍賣機制的基礎。

Maximization of the bandwidth utilization efficiency is the ultimate goal for the telecommunication spectrum management policy. An appropriate spectrum auction mechanism is essential for the maximization of spectrum utilizations and government income. Various spectrum auction mechanisms are available. How the most suitable spectrum auction mechanism can be designed and selected is always the essential issues for national governments. A well-designed auction mechanism will motivate telecommunication service provider’s interests in bidding. Firms with better operation capability always have the intention to pay a higher price to obtain license. The firms which can pay with the highest price usually get the usage right of the spectrum and thus, contribute considerable revenue to the national government. Albeit important, such issues have seldom been addressed and have no definite answers. In order to define a decision making framework for the selection of an appropriate spectrum auction mechanism, the DEMATEL based Network Process (DNP) will be proposed. The criteria will first be summarized by literature review and then confirmed based on experts’ opinions by using the modified Delphi method. Then, the influence weights being associated with the criteria will be derived by DNP. The Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) will then be introduced for performance evaluation by aforementioned weighting to define a suitable auction mechanism. An empirical study based on opinions being provided by experts from Taiwanese government, academic as well as research institutes will be introduced to verify the feasibility of the analytic framework. The empirical study results demonstrate that information is the most important aspect, while the collusion on bidders of information is the most influential criteria which may influence the decision of spectrum auction mechanism. Further, the open ascending-bid is selected as the most suitable spectrum auction model being derived by VIKOR. Based on the empirical study results, the proposed criteria and derived open ascending-bid mechanism can serve as the basis for governmental telecommunication policy definitions for the next generation wireless telecommunication spectrum allocations .

摘要 ii
Abstract iii
Chapter 1 Introduction 9
1.1 Research Backgrounds 9
1.2 Research Motivations and Problems 10
1.3 Research Objectives and Limitations 11
1.4 Research Method and Framework 12
Chapter 2 Literature Review 14
2.1 Spectrum Trading Approach 15
2.1.1 Beauty Contest 15
2.1.2 Lottery 16
2.1.3 Auction 16
2.2 Spectrum Auctions and Auction Theory 19
2.2.1 Open auctions 21
2.2.2 Sealed-bid auctions 22
2.2.3 Independent private values case 23
2.2.4 Common values case 25
2.2.5 Simultaneous and Sequential Auction 28
2.2.6 What is winner's curse? 33
2.2.7 Collusion 34
2.3 Spectrum Auction and Mechanism 35
Chapter 3 Research Method 38
3.1 Modified Delphi Method 38
3.2 The DEMATEL Method 41
3.2 The ANP Method 46
3.2 DEMATEL based Network Process 52
3.2 VIKOR 57
Chapter 4 Empirical Study 62
4.1 Empirical Study Based on Modified Delphi Method 62
4.2 Decision Problem Structuring by DEMATEL 64
4.3 Calculating the Aspect Weights by DNP 69
4.4 Rank the Mechanisms by VIKOR 73
Chapter 5 Discussions 76
Chapter 6 Conclusions 79
References 81

Brooks, K. W. (1979). Delphi technique: Expanding applications. North Central Association Quarterly, 54(3), 377-385.
Borgers, T. &; Dustmann, C.(2005).STRANGE BIDS: BIDDING BEHAVIOUR IN THE UNITED KINGDOM’S THIRD GENERATION SPECTRUM AUCTION. The Economic Journal, 115 (July), 551–578. Royal Economic Society. Published by Blackwell Publishing, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.
Chiu, Y. J. &; Chen, H. C. &; Tzeng, G. H. &; Shyu, J. Z. (2006).Marketing strategy based on customer behavior for the LCD-TV. International Journal of Management and Decision Making, vol. 7, no. 2/3, pp. 143-165.
Chiu, W. Y. Tzeng, G. H., &; Li, H. L.(2010). Advances in intelligent decision technologies: proceedings of the second KES international symposium IDT 2010, Scientific Publishing Services Pvt. Ltd, Chennai, India.
Chen. Y. C., Lien. H. P. &; Tzeng, G. H. (2010). Measures and evaluation for environment watershed plans using a novel hybrid MCDM model. Expert System with Applications, 37(2), 926-938.
Chou, Y. (1999). Policy Mandates and Their Efficacy in Restructuring Telecommunications: The Transaction Cost Approach Applied to An International Study, Ph.D. Dissertation of Public Policy, George Washington University, Washington, D.C. (unpublished manuscript). 223
Cramton, P. (1997).The FCC Spectrum Auctions: An Early Assessment. Journal of Economics and Management Strategy, 6:3, 431-495.
Dalkey, N. &; Helmer, O.(1963).An experimental application of the Delphi method to the use of experts. Management Science, 9(3), 458-467.
Dalkey, N. C. (1972). The Delphi method: an experimental application of group opinion. In: N. C. Dalkey, D. L. Rourke, R. Lewis, and D. Snyder (Eds.), Studies in the Quality of Life. MA: Lexington Books.
E - Commission. (2001).The Introduciton of Third Generation Moblile Communications in the European Union: State of Play and the Way Forward.
Fritts, B. C. (1999). Private Property, Economic Efficiency, and Spectrum Policy in the Wake of the C Block Auction, 51 Fed. Comm. L.J. 849, 855.
FCC REPORT.(2006) .Generally see Implementation of Section 309(i) of the Communications Act – Competitive Bidding, PP Docket No.93-253(May. 1. 1997),and Second Report and Order, 9 FCC Rcd 2348.
FCC REPORT.(2006) .supra note 20, at 7.
Furubotn, E. &; Rudolf, R.(2000).Institutions and Economic Theory: The Contribution of the New Institutional Economics. Ann Arbor: Michigan Univ. Press. 71-5
Gabus, A. &; Fontela, E.(1972).World problems an invitation to further thought within the framework of DEMATEL, Battelle Geneva Research Centre, and Geneva, Switzerland.
Huang, J. J. &; G. H. Tzeng, &; Ong, C. S.(2005). Multidimensional data in multidimensional scaling using the analytic network process, Pattern Recognition Letters, vol. 26, no. 6, pp. 755-767.
Huang, C. Y. &; Shyu, J. Z. &; Tzeng, G. H.(2007).Reconfiguring the innovation policy portfolios for Taiwan's SIP Mall industry, Technovation, vol. 27, no. 12, pp. 744-765.
Huang, C. Y. &; Tzeng, G. H.(2007).Reconfiguring the innovation policy portfolios for Taiwan’s SIP mall industry. Technovation, 27(12), 744-765.
ITU. (2001). The Introduction of 3G Mobile Communications in the European Union: State of Play and the Way Forward, Brussels 20.3.2001 COM (2001) 141final.3G Briefing Paper.
Judd, R. C. (1972). Forecasting to consensus gathering: Delphi grows up to college needs. College and University Business.53(1), 35-38.
Jones, J. &; Hunter, D.(1995). Qualitative research: Consensus methods for medical and health services research. British Medical Journal, 311(5), 376-380.
Klemperer, P. (1999). AUCTION THEORY A GUIDE TO THE LITERATURE.
Klemperer, P. (2002). How (not) to run auctions: The European 3G telecom auctions.
Nu eld College, Oxford University, Oxford OX1 1NF, UK
Klemperer, P. (2002) THE BIGGEST AUCTION EVER THE SALE OF THE BRITISH 3G TELECOM LICENCES
Klemperer, P. (2003). Auctions: Theory and Practice
Kloeck, C. &; Jaekel, H. &; Jondral, F. K.(2005). Dynamic and Local Combined Pricing, Allocation and Billing System with Cognitive Radios. Proc. IEEE DySPAN ’05, pp. 73–81.
Katyal, N. K.(1982). supra note 82, at 613-615.
Lin, C. J. &; Wu, W. W.(2008). A causal analytical method for group decision-making under fuzzy environment. Expert Systems with Applications, vol. 34, no. 1, pp. 205-213.
Lee, Y. S. &; Huang, J. C., &; Hsu, Y. S.(2008). Using modified Delphi method to explore the competition strategy for software companies of Taiwan. Journal of Informatics &; Electronics, 13(1), 39-50.
Lee, Y. T. &; Wu, W. W. &; Tzeng, G. H.(2004).Combining the DEMATEL with the ANP and ZOGP for selecting IT projects. Information Science , vol. Forthcoming.
Liou, J. J. H., Tzeng, G. H., &; Chang, H. C.(2007).Airline safety measurement using a hybrid model. Journal of Air Transport Management, 13(4), 243-249.
Linstone, H. A. &; Turoff, M.(1975). The Delphi method: Techniques and applications, reading. MA: Addison-Wesley.
McMillan, J.(1994).Selling Spectrum Rights.
MOTC optimal planning of Taiwan’s Mid- to Long-Term Radio Spectrum.(2009).
Murry, J. W. &; Hammons, J. O.(1995). Delphi: A versatile methodology for conducting qualitative research. The Review of Higher Education, 18(4), 423-436.
McMillan, J. (1995). Why Auction the Spectrum. Telecommunications Policy, 19, 191-199.
Milgrom, P. &; Roberts, J.(1992). Economics, Organization &; Management, New Jersey: Prestice Hall, Englewood Cliffs. 289-90
McAfee, R. P. &; McMillan, J.(1996).Analyzing the Airwaves Auction.
McAfee, R. P. &; McMillan, J.(1987). Auctions and Bidding.
Malvey, P. F. &; Archibald, C. M. &; Flynn, S. T.(1996).Uniform Price Auctions Evaluation of the Treasury Experience.
NCC research report.(2006).
Opricovic, S.(1998).Multicriteria Optimization of Civil Engineering Systems, Faculty of Civil Engineering, Belgrade.
Opricovic, S. &; Tzeng, G. H.(2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455.
Opricovic, S. &; Tzeng, G. H.(2007).Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, 178(2), 514-529.
Rodriguez, V. &; Moessner, K. &; Tafazolli, R.(2005).Auction Driven Dynamic Spectrum Allocation: Optimal Bidding, Pricing and Service Priorities for Multi-Rate, Multi-Class CDMA,” Proc. IEEE PIMRC ’05, vol. 3, pp. 1850–54.
Ralph, E. &; John S.(2001). Spectrum Auctions, Mimeo, Network Economics Consulting Group.
Sung, W. C.(2001).Application of Delphi method, a qualitative and quantitative analysis, to the healthcare management. Journal of Healthcare Management, 2(2), 11-19.
Saaty, R. W. (2003). The Analytic Hierarchy Process (AHP) for Decision Making and The Analytic Network Process (ANP) for Decision Making with Dependence and Feedback. Pittsburgh, PA: Creative Decisions Foundation.
Saaty, T. L.(1980).The Analytic Hierarchy Process. New York: McGraw-Hill.
Saaty, T. L. (1990). "Fundamentals of the Analytic Network Process," in Proceedings of International Symposium on Analytical Hierarchy Process, 1999 Japan .
Saaty, T. L. (1996). Decision Making with Dependence and Feedback: The Analytic Network Process. Pittsburgh: RWS Publication.
Saaty, T. L.(2005).Theory and Applications of the Analytic Network Process. Pittsburg, PA: RWS Publications.
Saaty, T. L. (2004). Fundamentals of the analytic network process - dependence and feedback in decision-making with a single network. Journal of Systems Science and Systems Engineering, vol. 13, no. 2, pp. 71-91.
Tzeng, G. H. &; Chiang, C. H. &; C. W. Li. (2007).Evaluating intertwined effects in e-learning programs: a novel hybrid MCDM model based on factor analysis and DEMATEL. Expert Systems with Applications, vol. 32, no. 4, pp. 1028-1044.
Wang, X. &; Xu, Y. &; Zhang, Qian.(2011).Spectrum Trading in Cognitive Radio Networks: A Contract-Theoretic Modeling Approach. VOL. 29 , NO. 4.
Xing, Y. R. &; Chandramouli, R. &; Cordeiro, C. M.(2007).Price Dynamics in Competitive Agile Spectrum Access Markets. IEEE JSAC, vol. 25, no. 3, pp. 613–21.
Yu, P. L. (1973). A class of solutions for group decision problems. Management Science, 19(8), 936-946.
Zeleny, M.(1982).Multiple Criteria Decision Making. New York: McGraw-Hill.