臺灣博碩士論文加值系統

散裝航運市場與運價波動劇烈，凸顯散裝航運公司經營不易。於全球散裝航運市場競爭環境下，我國散裝航運公司雖不以臺灣為市場，但我國進口市場規模相對較小，使臺灣散裝航運公司營運更加困難。對散裝航運公司而言，為了提升航運競爭力，如何改善營運績效是重要的研究課題。過去文獻對此課題研究較少，有關航運產業之績效評估，大部分是以貨櫃航運公司為主要研究對象，或與散裝航運公司合併評估。而航運產業績效評估主要採用一階段分析，無法進一步探討產業生產過程中各階段的真正效率。且多以DEA基本模式作橫斷面分析，較少探討縱斷面的跨期效率變化。因此，本文基於散裝航運公司立場，以2005-2010年資料針對我國八家上市櫃散裝航運公司為研究對象，採用二階段資料包絡分析法(Data Envelopment Analysis, DEA)，進行不同階段與不同時期的優劣勢之評估。
本文研究發現，對散裝航運公司而言，多角化經營將對營運效率產生正面之影響，於航運市場景氣低迷時期尤為明顯。市場效率方面，具市場效率的航運公司表示其股價被市場充分反映，反之表示營收並未反映於股價上。為改善市場效率，建議航運公司首應提升收益之穩定性以降低市場不確定性。根據Malmquist生產力指數分析可知，於2008年第三季金融海嘯後，散裝航運公司成長受限，營運效率與市場效率尚有改善空間。此研究結果可以提供散裝航運公司作為營運決策之參考。

The sharp fluctuation in bulk shipping markets and freight rates highlights the difficulty in operating bulk shipping corporations. In the highly competitive global environment, the relatively small-scale of bulk shipping market in Taiwan makes the business operations much more difficult than other bulk shipping markets. Therefore, how to enhance shipping competitiveness by improving the operational performance is an important issue for bulk shipping corporations. However, seldom researches focused on this issue in the past. The evaluation of operational performance on shipping industry mostly focused on the container shipping corporations only, or put both bulk shipping and container shipping corporations together. Besides, the evaluation of shipping industry mainly used the DEA approach with one stage analysis, which failed to explore the real efficiency of different stages. Lastly, past researches used cross-sectional analysis, and less explortion of the changes of vertical-sectional efficiencies. Therefore, this research evaluates the operational performance of eight listed bulk-shipping corporations in Taiwan over the period of 2005-2010 by using the DEA approach with two-stage production process, to analyze the advantages and disadvantages of bulk shipping corporations in different stages and periods.
As a result, for bulk shipping corporations, diversification strategies may have a positive impact on operational performance, especially when facing the market’s downturn of shipping industry. When it comes to the market efficiency of shipping companies, some were found to exhibit market efficiency, which represented that the company's stock price has been fully reflected on the market. The others were market inefficient, which represented that the revenues have not been reflected on the company's stock price. In order to improve market efficiency, shipping companies should promote the stability of revenues to reduce the uncertainty in bulk shipping market. This research also used Malmquist production index to analyze the operating performance in different periods. It shows that the growth of bulk shipping companies have been slowed down after the financial tsunami in the third quarter of 2008. Therefore, operational efficiency and market efficiency still have some room for improvement. The results may provide a good reference on operational decision making for bulk shipping corporations.

謝誌 i
摘要 ii
Abstract iii
目錄 iv
表目錄 vi
圖目錄 vii

第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究問題與目的 4
1.3 研究內容與方法 5
1.4 研究架構 6
1.5 研究流程 7

第二章 文獻回顧與評析 8
2.1 散裝航運市場特性 8
2.2 散裝航運市場風險 9
2.3 DEA方法相關文獻 12
2.3.1 績效評估 12
2.3.2 國外DEA方法相關文獻 14
2.3.3 國內DEA方法相關文獻 18
2.4 綜合評析 21

第三章 散裝航運市場現況分析 22
3.1 船噸供給分析 22
3.2 貨源需求分析 24
3.3 散裝航運市場分析 26
3.4 臺灣散裝航運公司現況 29
3.5 綜合評析 32

第四章 研究方法 33
4.1 資料包絡分析法 33
4.1.1 受評單位之選擇 33
4.1.2 DEA模式特性及限制 34
4.1.3 投入產出項目選取原則 35
4.2 效率評估模式之探討 35
4.2.1 CCR模式 36
4.2.2 BCC模式 37
4.2.3 Malmquist生產力指數 37

第五章 營運績效評估實證研究 41
5.1 受評單位、投入與產出項之選取 41
5.2 單期相對效率評估 43
5.3 單期效率綜合評析 54
5.4 管理意涵 55
5.5 跨期相對效率評估－Malmquist生產力指數 57
5.6 跨期效率綜合評析 60

第六章 結論與建議 61
6.1 結論 61
6.2 建議 63

參考文獻 64
【附件一】 投入產出變數原始資料 69
【附件二】 研討會論文 71
學生簡歷與著作 88

1.林郁芳(2001)，應用資料包絡分析法於航運公司定期航線營運績效之評估，國立交通大學經營管理研究所碩士論文。
2.高強、黃旭男、Toshiyuki Sueyoshi (2003)，管理績效評估：DEA，臺北：華泰文化事業股分有限公司。
3.陳永順(2012)，「國際散裝乾貨船海運市場行情分析」，船舶與海運通訊，第九十九期，頁5-14。
4.陳永順(2004)，價格波動與最適避險模型之研究－以散裝乾貨船市場為例，國立臺灣海洋大學航運管理研究所博士論文。
5.陳正成(2006)，臺灣貨櫃航運業生產效率比較之研究，義守大學管理科學研究所碩士論文。
6.陳佳婉(2006)，臺灣海運公司經營績效評估－以資料包絡分析法，立德管理學院公業管理研究所碩士論文。
7.陳澄隆(2000)，以國內定期航線公司營運績效之研究－應用資料包絡分析法(DEA)，國立交通大學交通運輸研究所碩士論文。
8.游智超(2003)，應用資料包絡分析法評估國籍貨櫃航商整體營運效率之研究，國立高雄第一科技大學運輸倉儲營運所碩士論文。
9.張瑋成(2005)，結合平衡計分卡與資料包絡分析法做績效評估之研究－以臺灣定期航運業為例，國立臺灣海洋大學航運管理研究所碩士論文。
10.張瀞之(2007)，「國際散裝海運營運風險因子特性分析」，兩岸三地航運與物流研討會論文集，中華航運學會，國立臺灣海洋大學，頁219-232。
11.黃舒豊(2006)，應用資料包絡分析法評估臺灣散裝航運上市公司經營績效，國立臺灣海洋大學航運管理研究所碩士論文。
12.鍾政棋(2009)，航業經營政策，臺北：複合文具印刷有限公司。
13.鍾政棋(2004)，我國散裝航運公司船舶設籍與營運績效之分析，國立交通大學交通運輸研究所博士論文。
14.蔡耀德(2009)，以資料包絡分析法評估臺灣航運業經營績效之研究，朝陽科技大學工業工程管理學系碩士論文。
15.Adland R. and Jia H. (2008), “Charter Market Default Risk: A Conceptual Approach,” Transportation Research Part E, Vol. 44, Iss. 1, pp. 152-163.
16.Aigner, D. J., Lovell, C. A. K. and Schmidt, P. (1977), “Formulation and Estimation of Stochastic Frontier Production Function Models,” Journal of Econometrics, Vol. 6, Iss. 1, pp.21-37.
17.Akatsuka, K. and Leggate, K. (2001), “Perceptions of Foreign Exchange Rate Risk in the Shipping Industry,” Maritime Policy and Management, Vol. 28, Iss. 3, pp. 235-249.
18.Alexandros, M. and Psifia, M. (2006), “Shipping Finance: Time to Follow a New Track?” Maritime Policy and Management, Vol. 33, No. 3, pp. 301-320.
19.Banker, R. D., Charnes, A., and Cooper, W. W. (1984), “Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis,” Management Science, Vol. 30, No. 9, pp. 1078-1092.
20.Barros, C. P. (2003), “The Measurement of Efficiency of Portuguese Sea Port Authorities with DEA,” International Journal of Transport Economics, Vol. 30, No. 3, pp. 335-354.
21.Bijwaard, G. E. and Knapp, S. (2009), “Analysis of Ship Life Cycles -The Impact of Economic Cycles and Ship Inspections,” Marine Policy, Vol. 33, No. 2, pp. 350-369.
22.Cave, D. W., Christensen, L. R., and Diewert, W. E. (1982), “The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity,” Econometrica, Vol. 50, No. 6, pp. 1393-1414.
23.Charnes, A., Cooper, W. W., and Rhodes, E. (1978), “Measuring the Efficiency of Decision Making Units,” European Journal of Operational Research, Vol. 2, No. 6, pp. 429-444.
24.Cinca, C. S., Callén, Y. F., and Molinero, C. M. (2005),“Measuring DEA Efficiency in Internet Companies,” Decision Support Systems, Vol. 38, Iss. 4, pp. 557-573.
25.Clarkson (2012), “Shipping Review Database” Clarkson Research Services, Spring.
26.Cullinane, K. P. B. and Wang, T. (2006), “The Efficiency of European Container Ports: a Cross-sectional Data Envelopment Analysis,” International Journal of Logistics: Research and Applications, Vol. 9, No. 1, pp. 19-31.
27.Dikos, G. and Papapostolou, N. (2002), “The Assessment of Market Efficiency in Shipping Sector: a New Approach,” Maritime Policy and Management, Vol. 29, No. 2, pp. 79-181.
28.Drucker, P. F. (1980), Managing in Turbulent Times, New York: Harper and Row.
29.Färe, R., Grosskopf, S., Lindgren, B., and Roos, P. (1992), “Productivity Change in Swedish Pharmacies 1980-1989: A Non-parametric Malmquist Approach,” Journal of Productivity Analysis, Vol. 3, No. 2, pp. 85-102.
30.Farrell, M. J. (1957), “The Measurement of Productive Efficiency,” Journal of Royal Statistical Society, Series A, Vol. 120, No.3, pp. 253-281.
31.Fiotakis, D. (2005), “The Impact of Information Technology upon the Shipbroking Profession,” Tulane Maritime Law Journal, Vol. 29, Summer, pp. 237-247.
32.Golany, B., and Roll, Y. (1989), “An Application Procedure for DEA,” OMEGA: International Journal of Management Science, Vol. 17, Iss. 3, pp. 237-250.
33.Goulielmos, A. M. and Psifia, M. (2007), “A Study of Trip and Time Charter Freight Rate Indices: 1968-2003,” Maritime Policy and Management, Vol. 34, No. 1, pp. 55-67.
34.Gray, J. W. (1986), Financial Risk Management in the Shipping Industry, New York: Fairplay Publications Limited.
35.Gümüş, Y. and Çelikkol, H. (2011), “Data Envelopment Analysis: An Augmented Method for the Analysis of Firm Performance,” International Research Journal of Finance and Economics, Iss 79, pp. 137-142.
36.ISL (2011), Shipping Statistics and Market Review (SSMR), Institute of Shipping Economics and Logistics (ISL), Germany.
37.Jørgensen, P. L. and De Giovanni, D. (2010), “Time Charters with Purchase Options in Shipping: Valuation and Risk Management,” Applied Mathematical Finance, Vol. 17, Iss. 5, pp. 399-430.
38.Kanas, A. (2001), “Neural Network Linear Forecasts for Stock Returns,” International Journal of Financial Economics, Vol. 6, Iss. 3, pp. 245-254.
39.Karlaftis, M. G., (2004), “A DEA Approach for Evaluating the Efficiency and Effectiveness of Urban Transit Systems,” European Journal of Operational Research, Vol. 152, No. 2, pp. 354-364.
40.Kavussanos, M. G. and Alizadeh-M, A. H. (2001), “Seasonality Patterns in Dry Bulk Shipping Spot and Time Charter Freight Rates,” Transportation Research Part E, Vol. 37, Iss. 6, pp. 443-467.
41.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, Vol. 7, No. 1, pp. 77-91.
42.Kavussanos, M. D. and Visvikis, I. D. (2006), “Shipping Freight Derivative: A Survey of Recent Evidence,” Maritime Policy and Management, Vol. 33, No. 3, pp. 233-255.
43.Leggate, H. K. (1999), “Norwegian Shipping: Measuring Foreign Exchange Risk,” Maritime Policy and Management, Vol. 26, Iss. 1, pp. 81-91.
44.Lu, J., Marlow, P. B., and Wang, H. (2008), “An Analysis of Freight Rate Volatility in Dry Bulk Shipping Market,” Maritime Policy and Management, Vol. 35, No. 3, pp. 237-251.
45.Luo, X., (2003) “Evaluating the Profitability and Marketability Efficiency of Large Banks: An Application of Data Envelopment Analysis,” Journal of Business Research, Vol. 56, Iss. 8, pp. 627-635.
46.Morita, H. and Avkiran, N. K. (2009), “Selecting Inputs and Outputs in Data Envelopment Analysis by Designing Statistical Experiments,” Journal of the Operations Research Society of Japan, Vol. 52, No. 2, pp. 163-173.
47.Oum, T. H., Waters, W. G., and Yu, C. Y., (1999), “A Survey of Productivity and Efficiency Measurement in Rail Transport,” Journal of Transport Economics and Policy, Vol. 33, No. 1, pp. 9-42.
48.Panayides, P. M., Lambertides, N., and Savva, C. (2011), “The Relative Efficiency of Shipping Companies,” Transportation Research Part E, Vol. 47, Iss. 5, pp. 681-694.
49.Pareto, V. (1927), Manuel d’Economic Politique, 2nd Ed., Girard, Paris.
50.Pocuca, M. and Zanne, M. (2009), “The Impact of Global Economic Crisis on the Dry Bulk Shipping Industry,” Scientific of Maritime Research, Vol. 23, No. 2, pp. 477-493.
51.Roll, Y. and Hayuth, Y. (1993), “Port Performance Comparison Applying Data Envelopment Analysis,” Maritime Policy and Management, Vol. 20, No. 2, pp. 153-161.
52.Scarsi, R. (2007), “The Bulk Shipping Business: Market Cycles and Shipowners Biases,” Maritime Policy and Management, Vol. 34, No. 6, pp. 577-590.
53.Seiford, L. M. and Zhu, J. (1999), “Profitability and Marketability of the Top 55 US Commercial Banks,” Management Science, Vol. 45, No. 9, pp. 1270-1288.
54.Seok, M. L. (1996), “Round-the-world Service: the Rise of Evergreen and the Fall of U.S. Lines,” Maritime Policy and Management, Vol. 23, No. 2, pp. 119-144.
55.Sherman, H. D. and Gold, F. (1985), “Bank Branch Operating Efficiency: Evaluation with Data Envelopment Analysis,” Journal of Banking and Finance, Vol. 9, Iss. 2, pp. 297-315.
56.Siems, T. (1992), “Quantifying Management’s Role in Bank Survival,” Economic Review, Federal Reserve Bank of Dallas 1, pp. 29-50.
57.Stopford, M. (1997), Maritime Economics, 3rd Ed., Routledge, London.
58.Stopford, M. (2009), Challenges for Global Shipping, Anniversary of the Danish Shipowners Association, Clarkson Research, pp. 1-13.
59.Strandenes, S. P. (2000), “The Shipbroking Function and Market Efficiency,” International Journal of Management Education, Vol. 2, No. 1, pp. 17-26.
60.Thore, S. A. (2002), Technology Commercialization: DEA and Related Analytical Methods for Evaluating the Use and Implementation of Technical Innovation, Boston: Kluwer Academic Publishers.
61.Tongzon, J. (2001), “Efficiency Measurement of Selected Australian and Other International Ports Using Data Envelopment Analysis,” Transportation Research Part A, Vol. 35, No. 2, pp. 113-128.
62.Tovar, B. and Martin-Cejas, R. R. (2010), “Technical Efficiency and Productivity Changes in Spanish Airports: a Parametric Distance Functions Approach,” Transportation Research Part E, Vol. 46, Iss. 2, pp. 249-260.
63.Tsolakis, S., Cridland, C., and Haralambides, H. (2003), “Econometrics Modelling of Second-hand Ship Price,” Maritime Economics and Logistics, Vol. 5, No. 4, pp. 347-377.
64.Tvedt, J. (2003), “A New Perspective on Price Dynamics of the Dry Bulk Market,” Maritime Policy and Management, Vol. 30, No. 3, pp. 221-230.
65.Veenstra, A. W. (1999), “The Term Structure of Ocean Freight Rates,” Maritime Policy and Management, Vol. 26, No. 3, pp. 279-293.
66.Veenstra, A. W. and Franses, P. H. (1997), “A Co-integration Approach to Forecasting Freight Rates in the Dry Bulk Shipping Sector,” Transportation Research Part A, Vol. 31, No. 6, pp. 447-458.
67.Wright, G. (2007), “Term Risk Premia in Shipping Markers: Reconciling the Evidence,” Journal of Transport Economics and Policy, Vol. 41, Iss. 2, pp. 247-256.
68.Xu, J. J., Yip, T. L., and Marlow, P. B. (2011), “The Dynamics Between Freight Volatility and Fleet Size Growth in Dry Bulk Shipping Markets,” Transportation Research Part E, Vol. 47, Iss. 6, pp. 983-991.
69.Yeh, Q. J. (1996), “The Application of Data Envelopment Analysis in Conjunction with Financial Ratios for Bank Performance Evaluation,” Journal of the Operational Research Society, Vol. 47, No. 8, pp. 980-988.
70.Zhu, J. (2000), “Multi-factor Performance Measure Model with an Application to Fortune 500 Companies,” European Journal of Operational Research, Vol. 123, No. 1, pp. 105-124.