隨著全球暖化及化石燃料短缺的問題日益嚴重，發展再生能源成為國家政策的重點與帶來競爭力的產業，太陽能光電為再生能源發展的重點之ㄧ。但自2000年以來政府提供許多補助獎勵措施推廣太陽能光電系統之應用，除了一些公家機關、示範建築以及政府計畫採用之外，對於一般家庭採用上卻仍未達到推廣擴散的效果，其主要原因是太陽能光電的推廣擴散受到（1）供給端的技術、成本，以及（2）使用端的民眾態度、使用型態等因素的影響，這些因素在未來隨著時間有動態的變化，進而對太陽能光電的推廣擴散造成影響，因此如何科學化的預測其未來的推廣擴散與需求，值得深入研究。本研究以聯合分析法結合技術預測，先從（1）供給端未來太陽能光電的技術發展與預測進行探討，將技術未來發展趨勢以及消費者對太陽能光電系統在意的產品屬性轉換為聯合分析中的屬性水準，透過聯合分析法探討（2）需求端消費者的偏好及效用結構變化情形。運用聯合分析法與技術預測的結合可以連結供給端與需求端，同時考慮未來技術變化以及消費者個人差異性，探討不同消費群對太陽能光電系統產品屬性重視程度與偏好結構，以及技術進步下產品屬性變化對偏好結構影響造成不同技術市佔率之變化，進行不同太陽能光電技術之競爭與擴散分析。研究結果可得2010-2030年各種太陽能光電系統的需求成長情形，矽晶型技術市佔率從2010年91.38%到了2030年下降至59.69%，薄膜型技術市佔率從2010年8.62%到了2030年上升至40.31%，其中不同技術之需求是受到系統的裝置費用和發電效率影響。不同消費者分群偏好分析發現偏好矽晶型技術的消費群為大電力用戶消費群、北部消費群以及功能導向群；偏好薄膜型技術的消費群為小電力用戶消費群、中南部消費群以及價格導向群。

Developing renewable energy, i.e photovoltaic electricity system, has become the emphasis of national policy with the shortage of energy. Though there are subsidies from government to expand the application of photovoltaic electricity system, it is not popular in ordinary family. Two reasons account for this, one is technology and cost of photovoltaic electricity system, and the other is consumers’ demand for attitude, willingness to pay, and patterns of photovoltaic electricity system. Therefore it is critical to forecast scientifically how the photovoltaic electricity system diffuse and demand with time. This study combines the conjoint analysis and the technology forecasting to focus on consumers’ preference structure variation which is influenced by development of supply. According to combining the conjoint analysis and the technology forecasting, we consider changes in technology and difference in individual preference, then discussing consumers’ relative importance of an attribute and preference structure, as well as the changes of market share and diffusion in different technologies of photovoltaic electricity system. The results show that (1) in the market share, c-Si technology is from 91.38% in 2010 down to 59.69% in 2030, and thin film technology is from 8.62% in 2010 up to 40.31% in 2030 due to cost and efficiency and (2) c-Si technology is preferred by consumers who need much electricity, reside in northern Taiwan and prefer attribute of function while thin film technology is preferred by consumers who need less electricity supply, reside in Taiwan except north and prefer attribute of price.

中文部份
1. （社）化學工學會 SCE.Net原編，賈要勤、溫榮弘編譯，圖解新能源百科，初版，全華圖書股份有限公司，2008。
2. 任禮恩，「機車使用者移轉至電動腳踏車偏好之研究」，台灣大學土木工程所碩士論文，2004。
3. 余序江、許志義、陳澤義，科技管理導論：科技預測與規劃，初版，五南圖書出版公司，1998。
4. 吳兆益，「聯合分析在果汁消費者知覺與偏好上之應用研究」，國立政治大學企業管理研究所碩士論文，1982。
5. 周子筠，「消費者對家庭用太陽光電系統之租與購願付價格與相關影響因素探討」，國立成功大學資源工程所碩士論文，2009。
6. 周文賢、張欽富，聯合分析在產品設計之應用，初版，華泰書局，2000。
7. 邱清泉，「臺灣地區推廣太陽能發電系統之研究」，大葉大學電機工程所碩士論文，2003。
8. 徐翠華，「台灣地區太陽輻射及太陽能發電潛力之研究」，國立臺灣師範大學地理研究所碩士論文，2002。
9. 真誠知己，陳耀茂編審，聯合分析的SPSS使用手冊，鼎茂圖書出版，2006。
10. 許瓊文、劉尚志、蔡千姿、龍仕璋，科技管理，初版，智勝文化，2005。
11. 陳思潔、陳文輝，「全球太陽光電發展趨勢」，經濟部溫室氣體減量資訊網，2008。
12. 黃聖儼，「太陽能發電技術暨經濟分析之研究」，雲林科技大學電機工程技術研究所碩士論文，2000。
13. 楊宏澤、廖建棠、董宗翰，「高聚光太陽光伏電池於中國發電產業的優勢與展望」，第五屆兩岸能源與環境永續發展科技研討會論文，2009。
14. 趙貴祥「太陽光電產業之發展趨勢與應用」，國立勤益科技大學電機工程系，2008年12月2日。
15. 劉智生、洪儒生「太陽光電池的高效率化」，行政院國家科學委員會， 2009年7月6日。
16. 歐文生、何明錦、陳瑞玲、陳建富、羅時麒，「台灣太陽能設計用標準日射量之研究」，中華民國建築學會「建築學報」，第64期，103-118頁，2008年6月。
英文部分
1. Auty, S., “Using Conjoint Analysis in Industrial Marketing: The role of judgment,”Industrial Marketing Management, Vol. 24, Iss. 3, 1995, pp191-206.
2. Bartels, R., Fiebig, D. G. and McCabe, A., “The Value of Using Stated Preference Methods: a Case Study in Modelling Water Heater Choices,” Mathematics and Computers in Simulation, Vol. 64, No. 3-4, 2004, pp. 487-495.
3. Bagnall, D. M. and Boreland, M., “Photovoltaic technologies,” Energy Policy Vol. 36, Iss. 12, 2008, pp. 4390-4396.
4. Batley, S. L., Colbourne, D., Fleming, P. D. and Urwin, P., “Citizen Versus Consumer: Challenges in the UK Green Power Market,” Energy Policy, Vol. 29, No. 6, 2001, pp.479-487.
5. Berger, W., “Catalysts for the Diffusion of Photovoltaics-A Review of Selected Programmes,” Progress in PVs: Research and Applications, Vol. 9, No. 2, 2001, pp.145-160.
6. Bergmann, A., Hanley, N. and Wright, R., “Valuing the Attributes of Renewable Energy Investments,” Energy Policy, Vol. 34, No. 9, 2006, pp.1004-1014.
7. Bhuiyan, M. M. H., Asgar, M. A., Mazumder, R. K. and Hussain M., “Economic Evaluation of a Stand-alone Residential Photovoltaic Power System in Bangladesh,” Renewable Energy, Vol. 21, Iss. 3-4, 2000, pp.403-410.
8. Borchers, A. M., Duke, J. M. and Parsons G. R., “Does Willingness to Pay for Green Energy Differ by Source,” Energy Policy, Vol. 35, No. 6, 2007, pp. 3327-3334.
9. Bright, J. R., “A Brief Introduction to Technology Forecasting: Concepts and Exercises,” Austin, TX: The Pemaquid Press, 1972.
10. Cox, D. N., Evans, G. and Lease, H. J., “The Influence of Information and Beliefs About Technology on the Acceptance of Novel Food Technologies: A Conjoint Study of Farmed Prawn Concepts,” Food Quality and Preference, Vol. 18, No. 5, 2007, pp. 813–823.
11. Dunlop, J. P., Farhi, B. N., Post, H. N., Szaro, J. S. and Ventre, G. G., “Reducing the Costs of Grid-connected Photovoltaic Systems,” Proceedings of Solar Forum, 2001: Solar Energy: The power to Choose, April 21-25, 2001, Washington, DC.
12. ETSU, “Solar Results Purchasing,” Contractor Dulas Ltd. Prepared by J. Sanders. ETSU S/P3/00273/REPDTI/Pub URN 01/1141, 2001.
13. Evans, M., Little, R., Lloyd, K., Malikov, G., Passolt, G., Arent, D., Swezey, B. and Mosey, G., “Advanced Modeling of Renewable Energy Market Dynamics,” Technical report NREL/TP-640-41896, National Renewable Energy Laboratory, August, 2007.
14. Faiers, A. and Neame, C., “Consumer Attitudes to Wards Domestic Solar Power Systems, ” Energy Policy, Vol. 34, No. 6, 2006, pp.1797-1806
15. Farizo, B. A. and Hanley, N., “Using Conjoint Analysis to Quantify Public Preferences Over the Environmental Impacts of Wind Farms. An Example From Spain,” Energy Policy, Vol. 30, No. 2, 2002, pp. 107-116.
16. Goett, A., Hudson, K. and Train, K., “Customers Choice Among Retail Energy Suppliers: The Willingness-to-Pay for Service Attribute,” AAG Associates, and Department of Economics University of California, Berkeley, 2002.
17. Green, M. A., Emery, K., Hisikawa, Y., and Warta, W., “Short Communication: Solar Cell Efficiency Table,”Progress in photovoltaics, Vol. 15, Iss. 5, 2007, pp.425-430.
18. Green, P. E. and Srinivasan, V., “Conjoint Analysis in Consumer Research: Issues and Outlook,” Journal of Consumer Research, Vol. 5, No. 2, 1978, pp. 103-123.
19. Grupp, H., “Demand by Product Characteristics :Measuring Solar Cell Quality Over Time, ” Journal of Evolutionary Economics, No. 19, No. 4, 2009, pp.487 -506
20. Hoffmann, W., Pietruszko, S. M. and Viaud, M., “Towards an Effective European Industrial Policy for PV Solar Electricity,” 19th PVSEC Paris, June, 2004.
21. Hsu, D., “New Challenges and Opportunities for PV Industry,” Taipei Summit-PV Taiwan Forum, October, 2009.
22. Kim, W. J., Lee, J. D. and Kim, T. Y., “Demand Forecasting for Multigenerational Products Combining Discrete Choice and Dynamics of Diffusion Under Technological Trajectories,” Technological Forecasting and Social Change, Vol. 72, Iss. 7, 2005, pp.825-849.
23. Krieger, A. M., Green, P. E. and Wind, Y. J., “Adventures in Conjoint Analysis,” 2004.
24. Lee, J., Cho, Y., Lee, J. D. and Lee, C. Y., “Forecasting Future Demand for Large-screen Television Sets Using Conjoint Analysis with Diffusion Model,” Technological Forecasting and Social change, Vol. 73, Iss. 4, 2006, pp.362-376.
25. Lee, J., Kim, Y, Lee, J. D. and Park, Y., “Estimating the Extent of Potential Competition in the Korean Mobile Telecommunications Market: Switching Costs and Number Portability,” International Journal of Industrial Organization, Vol. 24, Iss. 1, 2006, pp. 107-124.
26. Longo, A., Markandya, A. and Petrucci, M., “The Internalization of Externalities in the Production of Electricity: Willingness to Pay for the Attributes of a Policy for Renewable Energy,” Ecological Economics, Vol. 67, No. 1, 2008, pp. 140-152.
27. Mesa, A. Z., “New Home Buyer Solar Water Heater Trade-Off Study,” National Renewable Energy Laboratory, 1999.
28. Matsumoto, M. and Kondoh, S., “Modeling the Social Acceptance of Industrial Technologies -development of an Eco-product Diffusion Analysis Model That Incorporates Three Existing Models,” Synthesiology, Vol. 2, No. 1, 2009, p.23-31
29. Matsumoto, M., Kondoh, S., Jun, F. and Masui, K., “A Modeling Framework for the Diffusion of Green Technologies,” Management of technology innovation and value creation, Selected Papers from the 16th International Conference on Management of Technology, 2009, pp.121-136.
30. Porter, A. L., Roper, A. T., Mason, T. W., Rossini, F. A. and Banks, J., “Forecasting and Management of Technology,” New York: John Wiley & Sons, Inc, 1991.
31. Roe, B., Teislm, F., Levy, A. and Rissell, M., “US Consumers Willingness to Pay for Green Electricity,” Energy Policy, Vol. 29, No. 11, 2001, pp. 917-925.
32. Rogers, E. M., “Diffusion of Innovations,”4th ed., New York: Free Press, 1995.
33. Robbins, T. And Rubbinstein, D., “Solar Rectifier,” IEEE, 1999.
34. Sark, W., Alsema, E., Junginger, H., Moor, H. and Schaeffer, G., “Accuracy of Progress Ratios Determined From Experience Curves: The Case of Crystalline Silicon Photovoltaic Module Technology Development,” Progress in Photovoltaics: Research and Application, John Wiley & Sons. Ltd., 2008, 16: pp.441-453
35. Schiffman, L.G. , Kanuk, L.L., “Consumer Behavior,” 4th ed., New Jersey: Prentice Hall.1991
36. Schrattenholzer, L., “Experience Curves of Photovoltaic Technology,” Environmentally Compatible Energy Strategies (ECS) Project, 2000, March.
37. Sinclair, M., “Mainstreaming Solar PV in the USA,” Renewable Energy Focus, 2008.
38. Thomas, M., Post, H., DeBlasio, R., “Photovoltaic system: an End of –Millennium Review,” Progress in Photovoltaics: Research and Application, John Wiley & Sons. Ltd., 1999, 7:pp.1-19.
39. Timilsina, R., Lefevre, T. and Shrestha, S., “Financing Solar Thermal Technologies Under DSM Programs: An Innovative Approach to Promote Renewable energy,” International Journal of Energy Research, Vol. 24, Iss. 6, 2000, pp.503-510.
40. Wittink, D. R. and Cattin, P., “Commercial Use of Conjoint Analysis: An Update,” Journal of Marketing, Vol. 53, No. 3, 1989, pp.91-96.
41. Wright, T.P. “Factors affecting the cost of airplanes,” Journal of Aeronautical Sciences, Vol. 3, No. 4, 1936, pp.122-128.
42. Zwaan, B. van der and Rabl, A., “The Learning Potential of Photovoltaics: Implications for Energy Policy,” Energy Policy, Vol. 32, Iss. 6, 2004, pp.1545-1554.
網站部份
1. 拓墣產業研究所
http://www.topology.com.tw/tri/
2. 美國能源局國家再生能源研究室
http://www.nrel.gov/
3. NEDO日本新能源產業技術總合開發機構
http://www.nedo.go.jp/english/index.html
4. 日本太陽光電協會
http://www.jpea.gr.jp/
5. EPIA歐洲太陽光電產業協會
http://www.epia.org/
6. 工業技術研究院
http://www.itri.org.tw/
7. 國家實驗研究院科技政策研究與資訊中心
http://www.stpi.org.tw
8. IEK產業情報網
http://ieknet.itri.org.tw/
9. Solarbuzz LLC
http://www.solarbuzz.com/index.asp
10. 台灣電力公司
http://www.taipower.com.tw/
11. 經濟部能源局
http://www.moeaboe.gov.tw/Default.aspx?group=2
12. 經濟部太陽光電資訊網
http://solarpv.itri.org.tw/memb/main.aspx