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研究生:黃鈺堯
研究生(外文):Yu-Yao Huang
論文名稱:以Fuzzy Delphi與 DEMATEL應用於散裝航運論時傭船營運關鍵影響因素之認知分析
論文名稱(外文):Analyses of Key Influence Factors of Timecharter Operations in the Dry Bulk Shipping Sector by the Application of Fuzzy Delphi and DEMATEL
指導教授:鍾政棋鍾政棋引用關係
指導教授(外文):Cheng-Chi Chung
學位類別:碩士
校院名稱:國立臺灣海洋大學
系所名稱:航運管理學系
學門:運輸服務學門
學類:運輸管理學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:中文
論文頁數:88
中文關鍵詞:傭船決策論時傭船模糊德菲法決策實驗室法
外文關鍵詞:chartering decisiontime charterfuzzy delphiDEMATEL
相關次數:
  • 被引用被引用:8
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  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
散裝航運市場具有高度不確定性與週期循環特性,傭船決策是營運管理最困難任務之一。論時傭船期間較長、船東面臨違約風險較大。2009年7月1日起波羅地海乾散貨運價指數(BDI)組成結構亦僅以論時傭船租金計算。於高度風險航運市場中,如何進行最適的論時傭船決策,俾能創造航運公司最大收益是重要課題。本文經文獻回顧與專家訪談,彙整散裝航運論時傭船營運關鍵影響因素,透過問卷調查方式,以專家決策模糊德菲法(Fuzzy Delphi)探求關鍵影響因素之重要性,以決策實驗室法(DEMATEL)釐清各項關鍵影響因素間之因果關係。本文研究結果如下:
1.採用模糊德菲法(Fuzzy Delphi)分析關鍵影響因素之重要性,散裝航運論時傭船營運整體評估準則最重要的影響因素為「當事人信譽名聲」,其次依序為「船速及其耗油量」、「危機處理的能力」、「航行貿易與限制」與「市場運價與預測」。
2.採用決策實驗室法(DEMATEL)分析關鍵影響因素之關聯性,總影響程度最重要的因素為「傭船期間之長短」,其次較為「租金與支付條件」與「當事人信譽名聲」。其中,最主要的影響因素為「當事人營運規模」,其次依序為「航行貿易與限制」、「除外貨載與轉租」;最主要被影響因素為「租金與支付條件」,其次為「交還船相關約定」與「當事人信譽名聲」。
本文研究結果可以作為散裝航運公司制定論時傭船決策之依據。

Due to the bulk shipping market is uncertain and risky, making chartering decision is one of the most difficult challenges of operation management. Generally, the charter period of timecharter is longer than voyagecharter, and the risk of breaching the contract which the shipowners face is higher than voyagecharer. Since 1 July 2009 the Baltic dry index (BDI) components only calculated by trip timecharter hire. The shipping market is under considerable risks, how to make the chartering decisions the most efficiency to make the profit of shipping companies maximum. Therefore, according to the results of literature reviews and in-depth interviews, this research concludes timecharter operations key influencial factors of bulk shipping, to discuss these factors by questionnaire. In order to understand the key influencial factors of timecharter operations, this research applied the method of Fuzzy Delphi Method to analyze the importance of key influencial factors of timecharter operations, and meanwhile, clarify the causal relationship among each influential factor by utilizing the decision making and trial evaluation laboratory (DEMATEL).
1. Using Fuzzy Delphi analysis the importance of key factors, concerning the integral evaluation criteria, “Reputation” is valued the most, followed by “Speed and consumption”, “Crisis handling”, “Trading limits” and “Forecast of market price”.
2. Using DEMATEL analysis the relevance of key factors, concerning the integral criteria, “Chartering period” exerts the greatest effect on the overall influential degree, followed in descending order by “Payment condition” and “Reputation”. More specifically, the main influential factor is “Scale of operation”, and following are “Trading limits” and “Cargo exclusion and sub-let”. Additionally, the most crucial influenced factor is “Payment condition”, and the second and third among those being affected are “Delivery and redelivery” and “Reputation”.
The results of this study can contribute to dry bulk corporations in making timechartering decisions.

謝誌 i
摘 要 ii
Abstract iii
目錄 iv
表目錄 viii
圖目錄 x
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 3
1.3 研究內容與方法 4
1.4 研究架構 5
1.5 研究流程 6
第二章 文獻回顧與評析 8
2.1 散裝航運論時傭船相關研究 8
2.2 傭船營運影響因素相關研究 9
2.3 研究方法相關文獻 15
2.3.1 模糊德菲法 15
2.3.2 決策實驗室法 16
第三章 傭船市場現況分析 18
3.1 船噸供給分析 18
3.2 貨源需求分析 22
3.3 波羅地海指數 18
3.4 綜合討論 20
第四章 研究方法 20
4.1 模糊德菲法 20
4.2 決策實驗室法 22
4.3 分析架構與內涵 23
4.4 問卷調查與統計 28
第五章 關鍵影響因素重要性分析 29
5.1 整體評估 29
5.2 分群評估 30
5.2.1依船噸規模大小區分 30
5.2.2依營運型態區分 32
5.2.3依船東/傭船人或經紀人身分區分 33
5.3 綜合評析 35
第六章 關鍵影響因素關聯性分析 38
6.1 整體評估 38
6.2 分群評估 42
6.2.1依船噸規模大小區分 42
6.2.2依營運型態區分 49
6.2.3依船東/傭船人或經紀人身分區分 56
6.3 綜合評析 63
6.4 重要性與關聯性之討論 64
七、結論與建議 67
7.1 結論 67
7.2 建議 68
參考文獻 68




1. 吳偉銘、周俊賢(2009),「不定期海運市場動態均衡與系統安定分析─最適控制理論之應用」,運輸計劃季刊,第三十八卷第二期,頁201-228。
2. 施光訓、謝茵如、陳貞妤(2008),「金融服務業智慧資本衡量指標之研究」,中華管理學報,第九卷第四期,頁113-134。
3. 陳立民(2010),「隱性失誤與海難事故之探討」,航海技術季刊,第一卷第九期,頁67-86。
4. 陳永順(2007),「國際散裝乾貨船海運市場行情分析」,船舶與海運,第七十期,頁14-24。
5. 曾國雄(1984),「定期傭船契約之法律性質」,海洋學報,第十九期,頁9-22。
6. 張嘉珮(2008),論時傭船營運關鍵影響因素與傭船方案之組合分析,國立台灣海洋大學航運管理研究所碩士論文。
7. 張學孔、吳奇軒、陳育生(2009),「計程車產業政策關鍵因素分析」,運輸計劃季刊,第三十八卷第二期,頁173-200。
8. 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。
9. 蘇東濤,王麗萍(2009),「影響女學生上船工作意願因素之研究」,航海技術季刊,第一卷第五期,頁37-50。
10. Adland, R. and Cullinane, K. (2005), “A Time-varying Risk Premium in the Term Structure of Bulk Shipping Freight Rates,” Journal of Transport Economics and Policy, Vol. 39, No. 2, pp. 191-208.
11. Adland, R. and Jia, H. (2008), “Charter Market Default Risk: a Conceptual Approach,” Transportation Research Part E, Vol. 44, Iss. 1, pp. 152-163.
12. Anderson, H. E. (2000), “Shipbrokers’ Authority and Ability to Bind Principals: at the Juncture of Chartering and Agency,” Journal of Maritime Law and Commerce, Vol. 31, No. 1, pp. 89-106.
13. Bausch, D. O., Brown, G. G., and Ronen, D. (1998), “Scheduling Short-term Marine Transport of Bulk Products,” Maritime Policy and Management, Vol. 25, No. 4, pp. 335-348.
14. Berg-Andreassen, J. A. (1998), “A Portfolio Approach to Strategic Chartering Decisions,” Maritime Policy and Management, Vol. 25, No. 4, pp. 375-389.
15. Cheng, J. H., Chen, S. S., and Chuang Y. W.,(2008), “A Study of Constructing Fourth Party Logistics' Selection Criterion from Supply Chain Integration and Information Technology Perspectives - An Application of Fuzzy MCDM.,” Electronic Commerce Studies, Vol. 6, No. 4, pp. 401-424.
16. Clarkson (2009), “Shipping Review Database,” Clarkson Research Services, Spring.
17. Cullinane, K. (1995), “A Portfolio Analysis of Market Investments in Dry Bulk Shipping,” Transportation Research Part B, Vol. 29, No. 3, pp. 181-200.
18. Cullinane, K. (1991), “The Utility Analysis of Risk Attitudes in Shipping,” Maritime Policy and Management, Vol. 18, No. 3, pp. 157-169.
19. 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. 179-181.
20. Engelen, S., Dullaert, W., and Vemimmen, B. (2007), “Multi-agent Adaptive Systems in Dry Bulk Shipping,” Transportation Planning and Technology, Vol. 30, No. 4, pp. 377-389.
21. Gabus, A. and Fontela, E. (1972), World Problems, an Invitation to Further Thought within the Framework of DEMATEL, Switzerland, Geneva: Battelle Geneva Research Centre.
22. Gabus, A. and Fontela, E. (1973), Perceptions of the World Problematique: Communication Procedure, Communicating with Those Bearing Collective Responsibility (DEMATEL Report No. 1), Switzerland Geneva: Battelle Geneva Research Centre.
23. Goulielmos, A. and Psifia, M. (2006), “Shipping Finance: Time to Follow a New Track,” Maritime Policy and Management, Vol. 33, No. 3, pp. 301-320.
24. Grammenos, C. Th. and Arkoulis, A.G. (2003). “Determinants of Spreads on High Yield Bonds in the Shipping Industry,” Transportation Research, Vol. 39, Part E, Pages 459-471.
25. Grammenos, C. Th., Alizadeh, A. H., and Papapostolou, N. C. (2007), “Factors Affecting the Dynamics of Yield Premia on Shipping Seasoned High Yield Bonds,” Transportation Research Part E, Vol. 43, Iss. 5, pp. 549-564.
26. ISL (1994-2008), Institute of Shipping Economics and Logistics, Shipping Statistics and Market Review, ISL/SSMR, Germany.
27. Ishikawa, A., Amagasa, M., Shiga, T., Tomizawa, G., Tatsuta, R., and Mieno, H. (1993), “The Max-min Delphi Method and Fuzzy Delphi Method via Fuzzy Integration,” Fuzzy Sets and Systems, Vol. 55, Iss. 3, pp. 241-253.
28. Koekebakker, S. and Adland, R. (2004), “Modelling Forward Freight Rate Dynamics-empirical Evidence from Time Charter Rates,” Maritime Policy and Management, Vol. 31, No. 4, pp. 319-335.
29. Lagoudis, I. N., Lalwani, C. S., and Naim, M. M. (2004), “A Generic System Model for Ocean Shipping Companies in the Bulk Sector,” Transportation Journal, Vol. 43, No. 2, pp. 56-76.
30. Laulajinen, R. (2007), “Dry Bulk Shipping Market Inefficient, the Wide Prespective,” Journal of Transport Geography, Vol. 15, No. 3, pp. 217-224.
31. Li, K. X. and Cullinane, K. (2003), “An Economic Approach to Maritime Risk Management and Safety Regulation,” Maritime Economics and Logistics, Vol. 5, No. 3, pp. 268-284.
32. Lin, C. J. and Wu, W. W. (2008), “A Causal Analytical Method for Group Decision-making under Fuzzy Environment,” Expert System with Applications, Vol. 34, No. 1, pp. 205-213.
33. Liou, J. H., Yen, L. and Tzeng, G. H. (2008), “Building an Effective Safety Management System for Airlines,” Journal of Air Transport Management, Vol. 14, No. 1, pp. 20-26.
34. Manoliadis, O. G, Pantouvakis, J. P., and Christodoulou, S. E. (2009), “Improving Qualifications-Based Selection by Use of the Fuzzy Delphi Method,” Construction Management and Economics, Vol. 27, pp. 373-384
35. Murphy, P. R. and Daley, J. M. (1997), “Carrier Selection: Do Shippers and Carriers Agree, or Not?” Transportation Research Part E, Vol. 33, No. 1, pp. 62-72.
36. Sampson, H. and Zhao, M. (2003), “Multilingual Crews: Communication and Operation of Ship,” World English, Vol. 22, No. 1, pp. 31-43.
37. Scarsi, R. (2007), “The Bulk Shipping Business: Market Cycles and Shipowners’ Biases,” Maritime Policy and Management, Vol. 34, No. 6, pp. 577-590.
38. Stopford, M. (1997), Maritime economics, 3rd Ed., Routledge, London.
39. Strandenes, S. P. (2000), “Quality Incentives Pay-off,” Norwegian Shipowners Association and Det norske Veritas, Report No. 1120, pp. 1-14.
40. Tamvakis, M. N. (1995), “An Investigation into the Existence of a Two-tier Spot Freight Market for Crude Oil Carriers,” Maritime Policy and Management, Vol. 22, No. 1, pp. 81-90.
41. Tamvakis, M. N. and Thanopoulou, H. A. (2000), “Does Quality Pay? The Case of the Dry Bulk Market,” Transportation Research Part E, Vol. 36, No. 4, pp. 297-301.
42. Timmermann, K. W. and McConville, J. (1996), “An Analysis of the Quality and Redistribution of Dry Capesize Tonnage,” Maritime Policy and Management, Vol. 23, No. 1, pp. 45-53.
43. Tvedt, J. (1997), “Valuation of VLCCs under Income Uncertain,” Maritime Policy and Management, Vol. 24, No. 2, pp. 159-174.
44. Thanopoulou, H. A. (1998), “What Price the Flag? The Term of Competitiveness in Shipping,” Marine Policy, Vol. 22, No. 45, pp. 359-374.
45. Tvedt, J. (2003a), “A New Perspective on Price Dynamics of the Dry Bulk Market,” Maritime Policy and Management, Vol. 30, No. 3, pp. 221-230.
46. Tvedt, J. (2003b), “Shipping Market Models and the Specification of Freight Rate Process,” Maritime Economics and Logistics, Vol. 5, No. 4, pp. 327-346.
47. UNCTAD (2009), Review of Maritime Transport, United Nations Conference on Trade and Development, United Nations, UNCTAD/RMT, New York and Geneva.
48. Veenstra, A. W. and Ludema, M. W. (2006), “The Relationship Between Design and Economic Performance of Ships,” Maritime Policy and Management, Vol. 33, No. 2, pp. 159-171.
49. Wang, M. L. and Lin, Y. H. (2008), “To Construct a Monitoring Mechanism of Production Loss by Using Fuzzy Delphi Method and Fuzzy Regression Technique - A Case Study of IC Package Testing Company,” Expert Systems with Applications, Vol. 35, Iss. 3, pp. 1156-1165.
50. Wu, W. W. and Lee, Y. T. (2007), “Developing Global Managers’ Competencies Using the Fuzzy DEMATEL Method,” Expert System with Applications, Vol. 32, No. 2, pp. 499-507.
51. Wu, W. W. (2008), “Choosing Knowledge Management Strategies by Using a Combined ANP and DEMATEL Approach,” Expert System with Applications, Vol. 35, No. 3, pp. 828-835.

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