ㄧ、中文文獻
中華民國公用瓦斯事業協會 (2014) 。83期2008年4月-1台灣地區天然氣市場需求與展望【資料檔】線上檢索日期:2014 年 11 月 1 日。網址:http://www.rocga.org.tw/
中華民國公用瓦斯事業協會 (2014) 。95期2011年4月號【資料檔】線上檢索日期:2014 年 11 月 1 日。網址:http://www.rocga.org.tw/
行政院主計處 (2014)。歷年各季國內生產毛額依行業分【資料檔】。上檢索日期:2014 年 11 月 1 日。網址:http://www.stat.gov.tw/ct.asp?xItem=14616&CtNode=3564&mp=4
何建達 (民 92)。台灣上市電子業營運效率及股票市場性之研究,產業論壇,5 (3),30-55。孫遜 (民 93)。資料包絡分析法-理論與應用。台北市:揚智文化。
張世其、李宗耀與虞孝成 (民 92)。我國IC設計上市公司經營效率之分析,產業論壇,5 (1),169-194。陳正平、朱道凱、張淑芳、劉麗真與高子梅譯 (民 93)。策略地圖:串聯組織策略從形成到徹底實施的動態管理工具,台北市:臉譜文化出版城邦文化發行。原著:Kaplan, R., & Norton, D. P. ( 1994 )。
財團法人國家實驗研究院科技政策研究與資訊中心 (2014)。93年國內能源供需概況【資料檔】。線上檢索日期:2014 年 11 月 1 日。網址:http://cdnet.stpi.narl.org.tw/techroom/market/macro/macro023.htm
能源知識庫 (2014) 。台灣液化天然氣價格與北美管線天然氣價格差異之分析【資料檔】線上檢索日期:2014 年 11 月 1 日。網址:http://km.twenergy.org.tw/
經濟部統計處 (2014)。歷年國內各業生產與平減指數【資料檔】。線上檢索日期:2014 年 11 月 1 日。網址:http://www.stat.gov.tw/ct.asp?xItem=14616&CtNode=3564&mp=4
經濟部能源局 (2014)。2014年能源產業技術白皮書【資料檔】。線上檢索日期:2014 年11月1日。網址:http://web3.moeaboe.gov.tw/ECW/populace/content/SubMenu.aspx?menu_id=2324
經濟部能源局 (2014)。能源法規【資料檔】。線上檢索日期:2014 年 11 月 1 日。網址:http://web3.moeaboe.gov.tw/ECW/populace/content/SubMenu.aspx?menu_id=220
二、英文文獻
Adler, N., Friedman, L., & Sinuany-Stern, Z. (2002). Review of ranking methods in the data envelopment analysis context. European Journal of Operational Research, 140, 249-265.
Aivazian, V.A., Callen, J.L., Chan, M.W.L., & Mountain, D.C. (1987). Economies of scale versus technological change in the natural gas transmission industry. The Review of Economics and Statistics, 69, 55-561.
Ali, L. A., & Nakosteen, R. (2005). Ranking industry performance in the US. Socio-Economic Planning Sciences, 39, 11-24.
Al-Shammari, M. (1999). Optimization modeling for estimating and enhancing relative effciency with application to industrial companiesey. European Journal of Operational Research, 115, 488-496.
Amado, A. F. C., Santos, P. S., & Marques, M. P. (2012). Integrating the data envelopment analysis and the balanced scorecard approaches for enhanced performance assessment. Omega, 40, 390-403.
Amirteimoori, A. (2006). Data envelopment analysis in dynamic framework. Applied mathematics and computation, 181(1), 21-28.
Amirteimoori, A., & Kordrostami, S. (2012). A distance-based measure of super efficiency in data envelopment analysis: An application to gas companies. Journal of Global Optimization, 54(1), 117-128.
Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10) , 1261-1264.
Baker, R. C., & Talluri, S. (1997) A closer look at the use of data envelopment analysis for technology selection. Computers and Industry Engineering, 32(1), 101-108
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30, 1078-1092.
Banker, R﹒D.﹐& Thrall, R﹒C. (1992). Estimating most productive scale size using data envelopment analysis. European Journal of Operational Research, 62, 74-84.
Banxia Software Ltd. (2003). Frontier analyst professional (version 4.0)
Caves, D.W., Chrstensen, L. R., & Diewert, W. E. (1982). The economic theory for index number of the measurement of input output and productivity. Econometrica﹐50 (6), 1393-1414.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2, 429-444.
Coelli, T. J. (1996). A guide to DEAP version 2.1: A data envelopment analysis (computer) program. Working paper, Center for efficiency and productivity analysis. University of New England.
Cooper, W. W., Deng, H., Gu, B., Li, S., & Thrall, R. M. (2001). Using dea to improve the management of congestion in Chinese industries (1981-1997). Socio-Economic Planning Sciences, 35, 227-242.
Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis – A comprehensive text with models, applications, references and DEA–solver software. Boston:Kluwer Academic Publishers.
Doyle, J., & Green, R. (1994). Efficiency and cross-efficiency in DEA: Derivations, meanings and uses. Journal of Operational Research Society, 4(5), 567-578.
Düzakin, E., & Düzakin, H. (2007). Measuring the performance of manufacturing firms with super slacks based model of data envelopment analysis: An application of 500 major industrial enterprises in Turkey. European Journal of Operational Research, 182, 1412-1432.
Ebnerasoul, S. A., Yavarian, H., & Azodi, M. A. (2009). Performance evaluation of organizations: An integrated data envelopment analysis and balanced scorecard approach. International Journal of Business and Management, 4(4), P42.
Ellig, J., & Giberson, M. (1993). Scale, scope, and regulation in the Texas gas transmission industry. Journal of Regulatory Economics, 5, 79-90.
Erbetta, F., & Rappuoli, L. (2008). Optimal scale in the italian gas distribution industry using data envelopment analysis. Omega, 36, 325-336.
Ertürk, M., & Türüt-Aşık, S. (2011). Efficiency analysis of Turkish natural gas distribution companies by using data envelopment analysis method. Energy Policy, 39(3), 1426-1438.
Fabbri P., Fraquelli G., & Giandrone R. (2000). Costs, technology and ownership of gas distribution in Italy. Managerial and Decision Economics, 21, 71–81.
Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1994). Productivity developments in swedish hospitals : A Malmquist output index approach. In A. Charnes, W. W. Cooper, A. Y. Lewin, & L. M. Seiford (Eds.), Data enveiopment analysis : Theory methodology and applicatins, (pp. 253-272). Boston : Kluewr Academic Publishers.
Goncharuk A.G. (2008). Performance benchmarking in gas distribution industry. Benchmarking: An International Journal, 15(5), 548-559.
Gorak, T.C., & Ray, D. J. (1995). Efficiency and equity in the transition to a new natural gas market. Land Economics, 71(3), 368-385.
Hawdon (2003). Efficiency, performance and regulation of the international gas industry—A bootstrap DEA approach. Energy Policy , 31, 1167-1178.
Hollas, D.R., & Stansell, S.R. (1988). Regulation, interfirm rivalry, and the economic efficiency of natural gas distribution facilities. Quarterly Review of Economics and Business, 28 (4), 2137.
Hollas, D.R., Macleod, K.R., & Stansell, S.R. (2002). A data envelopment analysis of gas utilities' efficiency. Journal of Economics and Finance, 26(2), 123-137.
Jamasb, T., Newbery, D., Pollitt, M., & Triebs, T. (2007). International benchmarking and regulation of european gas transmission utilities. Final Report, Council of European Energy Regulators.
Jamasb, T., Pollitt, M., & Triebs, T. (2008). Productivity and efficiency of US gas transmission companies: A European regulatory perspective. Energy Policy, 36(9), 3398-3412.
Kaplan, R.S., & Norton, D.P. (1992). The balanced scorecard: Measures that drive performance. Harvard Business Review, 70, 71-79.
Kaplan, R.S., & Norton, D.P. (1996). Using the balanced scorecard as a strategic management system. Harvard Business Review, 74(1), 75-86.
Khaki, A., Najafi, S., & Rashidi, S. (2012). Improving efficiency of decision making units through BSC-DEA technique. Management Science Letters, 2(1), 245-252.
Kim, T.Y., & Lee, J.D. (1996). Cost analysis of gas distribution industry with spatial variables. The Journal of Energy and Development, 20, 247–67.
Malmquist, S. (1953). Index number and indifference surfaces. Trabajos de Estatistica, 4, 209-242.
Qazi, Q. A., & Yulin, Z. (2012). Productivity measurement of hi-tech industry of China malmquist productivity index – DEA approach. Procedia Economics and Finance, 1, 330-336.
Rossi, M.A. (2001). Technical change and efficiency measures: The post-privatisation in the gas distribution sector in Argentina. Energy Economics, 23( 2), 295-304.
Sadjadi, S.J., Omrani, H., Abdollahzadeh, S., Alinaghian, M., & Mohammadi, H. (2011). A robust super-efficiency data envelopment analysis model for ranking of provincial gas companies in Iran. Expert Systems with Applications, 38, 10875-10881.
Saitech, Inc. (2004). DEA solver professional (version 4.1)
Saranga, H. (2009). The Indian auto component industry – Estimation of operational efficiency and its determinants using dea. European Journal of Operational Research, 196, 707-718.
Satty, T. L. (1980) The analytic hierarchy process. McGrawHill:New York.
Seifert, M. L., & Zhu, J. (1998). Identifying excesses and deficits in Chinese industrial productivity (1953-1990) : A weighted data envelopment analysis approach. Omega, 26, 279-296.
Sexton, T. R., Slikman R. H., & Hogan, A. (1986). Data envelopment analysis : Critique and extensions. In R. H. Slikman (Eds.), Measuring efficiency : An assessment of data envelopment analysis, (pp.73-105). San Francisco: Jossey Bass Inc.
Shephard, R. W. (1970). Theory of cost and production function. Princeton: Princeton University Press.
Silkman, R. H. (Ed.). (1986). Measuring efficiency: An assessment of data envelopment analysis (No. 32). San Francisco: Jossey Bass Inc.
Sueyoshi, T., & Goto, M. (2010). Measurement of a linkage among environmental, operational, and financial performance in Japanese manufacturing firms: A use of data envelopment analysis with strong complementary slackness condition. European Journal of Operational Research, 207, 1742-1753.
Thanassoulis, E., Boussofiane, A., & Dyson, G. R. (1995). Exploring output quality targets in the provision of perinatal care in England using data envelopment analysisxploring output quality targets in the provision. European Journal of Operational Research, 80, 588-607.
Thompson, R. G., Singleton, F. D., Thrall, R. M., & Smith, B. A. (1986). Comparative site evaluations for locating high energy lab in texas. Interfaces, 16, 1380-1395.
Tobin, J., (1958). Estimation of relationships for limited dependent variables. Econometrica, 26 (1), 24-36.
Tseng, F. M., Chiu, Y. J., & Chen, J. S. (2009). Measuring business performance in the high-tech manufacturing industry : A case study of Taiwan’s large-sized TFT-LCD panel companies. Omega, 37, 686-697.