|
1.江雪真(2015),「臺灣航運業之經營績效評估-運用資料包絡分析法」,國立臺灣海洋大學航運管理研究所碩士學位論文。 2.汪傳旭(1999),國際航運市場與政策,人民交通出版社。 3.周達剛、馬興超(2013),「燃用澳洲煤防止磨煤機自然爆炸分析」,能源與節能,第10卷,頁101-103。 4.徐少波、曾憲鵬、於敦喜、姚洪、徐明厚(2015),「基於大型電廠配煤方案的顆粒物生成實驗研究」,煤炭學報,第40卷,第3期,頁 684-689。 5.郭哲榮(2015),「散裝航運市場指數模型之建立及預測---以臺灣、中國及BDI指數為例」,國立中央大學土木工程學系研究所碩士論文。 6.高強、黃旭男、Toshiyuki Sueyoshi(2003),管理績效評估:資料包絡分析法,台北市:華泰文化事業股份有限公司。 7.孫遜(2004),資料包絡分析法-理論與應用,台北:揚智文化事業股份有限公司。 8.徐穎珍(2015),「網絡資料包絡分析法應用於散裝航運公司之績效評估」,國立臺灣海洋大學航運管理研究所博士學位論文。 9.黃羽婕(2015),「臺灣上市散裝航運公司股價與波羅的海運價指數的關聯性研究」,國立臺灣海洋大學商船系碩士學位論文。 10.黃怡慈(2009),「頻譜分析運用於散裝海運經營風險之研究」,國立高雄海洋科技大學航運管理研究所碩士論文。 11.黃承傳、鍾政棋(2005),「我國散裝船舶設籍關鍵影響因素之分析」,運輸計劃季刊,第34卷,第1期,頁 27-61。 12.黃純輝、李羅明(2005),「國際船員立法趨勢及對我國船員立法的思考」,世界海運, 第28卷,第3期,頁37-38。 13.馮磊、張世紅、楊晴、車慶豐、聞明、梅豔陽、陳漢平 (2015) ,「焦煤微波乾燥特性及動力學研究」,煤炭學報,第40卷,第10期,頁2458-2464. 14.溫珮伶、林晉勗、林師模(2008),「國際原物料價格與散裝海運運價指數之連動及其對運價指數預測之影響」,運輸學刊, 第20卷,第4期,頁351-375。 15.楊鈺池、王志敏(2006),「海岬型船租金費率與船價波動關係之時間序列研究」,運輸計劃季刊,第35卷,第4期,頁415-441。 16.鄭晏晴(2008),「散裝海運市場運價與原物料價格間之關連性研究」, 國立高雄海洋科技大學航運管理研究所碩士論文。 17.劉小盟(2014),「世界海運強國海運服務貿易效率分析」,東北財經大學國際貿易研究所碩士論文。 18.劉佳讓 (2013),「全球金融危機對散裝航運市場船貨供需之影響」,國立臺灣海洋大學航運管理研究所碩士學位論文。 19.鍾政棋 (2004),「我國散裝航運公司船船設籍與營運績效之分析」,交通大學交通運輸研究所博士論文。 20.鍾政棋、梁金樹、何孟唐 (2011),「散裝航運公司因應港口國管制機率模式之構建與應用」,運輸學刊,第23卷,第3期,頁315-334。 21.鍾政棋、張雅涵、張志清(2006),「我國船舶設籍問題與因應對策之研擬」,航運季刊,第15卷,第3期,頁41-62。 22.Adland, R., Cariou, P. and Wolff, F. C. (2016). The influence of charterers and owners on bulk shipping freight rates. Transportation Research Part E: Logistics and Transportation Review, 86, 69-82. 23.Ariel, A. (1989). Delphi forecast of the dry bulk shipping industry in the year 2000. Maritime Policy and Management, 16(4), 305-336. 24.Bang, H. S., Kang, H. W., Martin, J. and Woo, S. H. (2012). The impact of operational and strategic management on liner shipping efficiency: a two-stage DEA approach. Maritime Policy and Management, 39(7), 653-672. 25.Banker, R. D., Charnes, A. and Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078-1092. 26.Banker, R. D., Cooper, W. W., Seiford, L. M., Thrall, R. M., and Zhu, J. (2004). Returns to scale in different DEA models. European Journal of Operational Research, 154, 345-362. 27.Barros, C. P. and Athanassiou, M. (2015). Efficiency in European seaports with DEA: evidence from Greece and Portugal. In Port Management (pp. 293-313). Palgrave Macmillan UK. 28.Belu, C. (2009). Ranking corporations based on sustainable and socially responsible practices. A data envelopment analysis (DEA) approach. Sustainable Development, 17(4), 257-268. 29.Bichou, K. (2011). A two-stage supply chain DEA model for measuring container-terminal efficiency. International Journal of Shipping and Transport Logistics, 3(1), 6-26. 30.Byrne, B. (2014). Solid bulk shipping: cargo shift, liquefaction and the transportable moisture limit, University of Oxford. 31.Charnes, A., Cooper, W. W., Golany, B., Seiford, L. and Stutz, J. (1985). Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions. Journal of econometrics, 30(1), 91-107. 32.Charnes, A., Cooper, W. W. and Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444. 33.Charnes, A., Cooper, W. W. and Rhodes, E. (1979). Measuring the efficiency of decision-making units. European journal of operational research, 3(4), 339. 34.Chen, K. K., Ho, H. P. and Chang, C. T. (2015). Estimating attributes importance for container shipping industry by closing the listening gap with maximum convergent validity. Transportation Research Part E: Logistics and Transportation Review, 79, 145-163. 35.Chen, S., Meersman, H., Van de Voorde, E. and Frouws, K. (2014). Modelling and Forecasting in Dry Bulk Shipping. CRC Press. 36.Chen, Y. S. and Wang, S. T. (2004). The empirical evidence of the leverage effect on volatility in international bulk shipping market. Maritime Policy and Management, 31(2), 109-124. 37.Chistè, C. and Van Vuuren, G. (2014). Investigating the cyclical behavior of the dry bulk shipping market. Maritime Policy and Management, 41(1), 1-19. 38.Chung, C. C. and Hwang, C. (2005). Analysis on vessel registration and operational performance of bulk-shipping firms. Proceedings of the Eastern Asia Society for Transportation Studies, 5, 631-646. 39.Clarkson Research Services (2005~2015), Clarkson Shipping Review and Outlook, London, United Kingdom. 40.Dai, L., Hu, H., Chen, F. and Zheng, J. (2015). The dynamics between newbuilding ship price volatility and freight volatility in dry bulk shipping market. International Journal of Shipping and Transport Logistics, 7(4), 393-406. 41.Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A (General), 120, 253-290. 42.Frisk, G. V. (2012). Noiseonomics: The relationship between ambient noise levels in the sea and global economic trends. Scientific reports, 2. 43.Gkochari, C. C. (2015). Optimal investment timing in the dry bulk shipping sector. Transportation Research Part E: Logistics and Transportation Review, 79, 102-109. 44.Güner, S. (2015). Investigating infrastructure, superstructure, operating and financial efficiency in the management of Turkish seaports using data envelopment analysis. Transport Policy, 40, 36-48. 45.Gutiérrez, E., Lozano, S. and Furió, S. (2014). Evaluating efficiency of international container shipping lines: A bootstrap DEA approach. Maritime Economics and Logistics, 16(1), 55-71. 46.Guo, I. L., Lee, H. S. and Lee, D. (2017). An integrated model for slack-based measure of super-efficiency in additive DEA. Omega, 67 (1), 160-167. 47.Gutiérrez, E., Lozano, S. and Furió, S. (2014). Evaluating efficiency of international container shipping lines: A bootstrap DEA approach. Maritime Economics and Logistics, 16(1), 55-71. 48.He, Y., Wang, S. and Lai, K. K. (2010). Global economic activity and crude oil prices: A cointegration analysis. Energy Economics, 32(4), 868-876. 49.ISL (2004~2015). Shipping Statistics and Market Review (SSMR). Institute of Shipping Economics and Logistics (ISL), Germany. 50.Kalgora, B. and Christian, T. M. (2016). The Financial and Economic Crisis, Its Impacts on the Shipping Industry, Lessons to Learn: The Container-Ships Market Analysis. Open Journal of Social Sciences, 4(1), 38. 51.Kalouptsidi, M. (2014). Time to build and fluctuations in bulk shipping. The American Economic Review, 104(2), 564-608. 52.Karsten, C. V. and Balakrishnan, A. (2015). Modeling Liner Shipping Service Selection and Container Flows using a Multi-layer Network. In 27th European Conference on Operational Research , Glasgow. 53.Kavussanos, M. G. and Alizadeh, A. H. (2002). Efficient pricing of ships in the dry bulk sector of the shipping industry. Maritime Policy and Management,29(3), 303-330. 54.Lee, T. K., Lun, Y. V. and Yan, H. (2013). Price volume relativity in the dry bulk shipping market. International Journal of Shipping and Transport Logistics, 5(4-5), 551-563. 55.Li, D., Luan, W. X. and Pian, F. (2013). The efficiency measurement of coastal container terminals in China. Journal of Transportation Systems Engineering and Information Technology, 13(5), 10-15. 56.Lindstad, H., Asbjørnslett, B. E. and Strømman, A. H. (2015). Opportunities for increased profit and reduced cost and emissions by service differentiation within container liner shipping. Maritime Policy and Management, 1-15. 57.Liu, Q., Wilson, W. W. and Luo, M. (2016). The impact of Panama Canal expansion on the container-shipping market: a cooperative game theory approach. Maritime Policy and Management, 43(2), 209-221. 58.Lun, Y. V., Lai, K. H., Wong, C. W. and Cheng, T. E. (2015). Greening and performance relativity: An application in the shipping industry. Computers & Operations Research, 54, 295-301. 59.Lun, V.Y. and Peter M. (2011). The impact of capacity on firm performance: a study of the liner shipping industry. International Journal of Shipping and Transport Logistics, 3(1), 57-71. 60.Lun, Y. V. and Quaddus, M. A. (2008). An empirical model of the bulk shipping market. International Journal of Shipping and Transport Logistics, 1(1), 37-54. 61.Lyridis, D.V., Fyrvik, T., Kapetanis, G. N., Ventikos, N., Anaxagorou, P., Uthaug, E. and Psaraftis, H. N. (2005). Optimizing shipping company operations using business process modelling. Maritime Policy and Management, 32(4), 403-420. 62.Miller, A. W., and Ruiz, G. M. (2014). Arctic shipping and marine invaders. Nature Climate Change, 4(6), 413-416. 63.Ng, M. (2015). Container vessel fleet deployment for liner shipping with stochastic dependencies in shipping demand. Transportation Research Part B: Methodological, 74, 79-87. 64.Niavis, S. and Tsekeris, T. (2012). Ranking and causes of inefficiency of container seaports in South-Eastern Europe. European Transport Research Review, 4(4), 235-244. 65.Papapostolou, N. C., Nomikos, N. K., Pouliasis, P. K. and Kyriakou, I. (2014). Investor Sentiment for Real Assets: The Case of Dry Bulk Shipping Market. Review of Finance, 18(4), 1507-1539. 66.Pierre, C. and Olivier, F. (2015). Relevance of the Northern Sea Route (NSR) for bulk shipping. Transportation Research Part A: Policy and Practice, 78, 337-346. 67.Radonjić, A., Pjevčević, D., Hrle, Z., and Čolić, V. (2011). Application of DEA method to intermodal container transport. Transport, 26(3), 233-239. 68.Schøyen, H. and Odeck, J. (2013). The technical efficiency of Norwegian container ports: A comparison to some Nordic and UK container ports using Data Envelopment Analysis (DEA). Maritime Economics and Logistics, 15(2), 197-221. 69.Stopford, M. (2009). Maritime Economics 3e. Routledge. 70.Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130, 489-509. 71.Tone, K. (2002). A slacks-based measure of super-efficiency in data envelopment analysis. European Journal of Operational Research, 143, 32-41. 72.Tran, N. K. and Haasis, H. D. (2015). Literature survey of network optimization in container liner shipping. Flexible Services and Manufacturing Journal, 27(2-3), 139-179. 73.Tseng, P. H. and Liao, C. H. (2015). Supply chain integration, information technology, market orientation and firm performance in container shipping firms. The International Journal of Logistics Management, 26(1), 82-106. 74.UNCTAD (2011~2015). Review of Martime Transport. New York: United Nations Publiucation. 75.Vilhelmsen, C., Lusby, R. and Larsen, J. (2013). The Tank Allocation Problem in Bulk Shipping. In 4th International Conference on Computational Logistics, Copenhagen, Denmark, October. 76.Wang, H. C. and Lee, H. S. (2012). The impact of navigation safety in Kaohsiung harbor. Journal of Marine Engineering and Technology, 11(1), 45-50. 77.Wang, S., Wang, H. and Meng, Q. (2015). Itinerary provision and pricing in container liner shipping revenue management. Transportation Research Part E: Logistics and Transportation Review, 77, 135-146. 78.Wang, Y. J. (2014). The evaluation of financial performance for Taiwan container shipping companies by fuzzy TOPSIS. Applied Soft Computing, 22, 28-35. 79.Yang, C. C. and Wong, C. W. (2016). Configurations of environmental management strategy: evidence from the container shipping service industry. International Journal of Shipping and Transport Logistics, 8(3), 334-356.
參考網址: 80.何秀玲 (2004),「由偶發性的煤荒看起——煤炭價格與運輸」, http://energymonthly.tier.org.tw/outdatecontent.asp?ReportIssue=200405&Page=33 (last view on July 30, 2016) 81.侯仁義(2016),「國際能源價格展望」, http://energymonthly.tier.org.tw/outdatecontent.asp?ReportIssue=201601&Page=19&keyword=%B7%D1%AC%B4 (last view on July 30, 2016) 82.陳芃(2004),「千裡迢迢抵寶島——能源的運輸」, http://energymonthly.tier.org.tw/outdatecontent.asp?ReportIssue=200407&Page=14 (last view on July 30, 2016) 83.臺灣證券交易所之公開資訊觀測站(2016) http://mops.twse.com.tw/mops/web/index (last view on October 11, 2016) 84.臺灣經濟部能源局官方網站 http://web3.moeaboe.gov.tw/ecw/business/content/ContentLink.aspx?menu_id=378 (last view on October 11, 2016)
|