1. NCCU Academic Hub
  2. 學術產出
  3. 商學院
  4. 學位論文
  5. Item

學術產出-學位論文

文章檢視/開啟

書目匯出

Google ScholarTM

政大圖書館

引文資訊

TAIR相關學術產出

題名 供應鏈彈性評估模式建立之研究－以資訊電子產業為例
The Research on Developing a Flexibility Assessment Model in Supply Chains - using Information and Electronics Industry as an example
作者 陳信呈
Chen, Hsin Cheng
貢獻者 林我聰
Lin, Woo Tsong
陳信呈
Chen, Hsin Cheng
關鍵詞 供應鏈彈性
彈性衡量
模糊理論
失效模式與效應分析法
決策實驗室分析法
分析網路程序法
Supply Chain Flexibility Management
Flexibility Measure
Fuzzy Theory
FMEA
DEMATEL
ANP
日期 2016
上傳時間 9-八月-2016 10:44:21 (UTC+8)
摘要 企業為有效降低成本、接近顧客市場與提升整體供應鏈效率，紛紛尋找最佳解決方案，專業高效率、有彈性及低成本合作夥伴遍及全球，形成一個複雜全球化的供應鏈網路，導致整體供應鏈的風險大幅提升。當供應鏈危機發生時，有效並快速的回應危機事件漸漸成為企業必須具備的重要能力，企業如何提升供應鏈彈性的能力以應映供應鏈中斷已成為重要的議題。而過去的供應鏈彈性研究上，大部分著重於單一階段進行討論，從整體供應鏈角度的研究仍屬有限，導致無法提供可供決策者參考的供應鏈彈性策略，且供應鏈彈性衡量的研究領域尚處於百家爭鳴的階段，至今相關的研究仍沒有一致的看法。因此，本研究將針對「如何有效評估供應鏈彈性程度」主要問題進行研究。
針對此問題來進行研究，本研究提出一個整體供應鏈彈性評估模式以有效評估供應鏈的彈性程度。首先透過文獻探討確認整理出供應鏈的彈性因子，並以SCOR模式的將彈性因子歸類於各階段內；接著藉由彈性因子的數量範疇、異質性範疇、移轉性與一致性，應用模糊理論篩選出需改善的彈性因子；再使用模糊決策實驗室分析法(Fuzzy Decision Making Trial and Evaluation Laboratory；Fuzzy DEMATEL)建構出供應鏈流程中重要的彈性因子間之關連性；由於彈性因子間具有相依關係，本研究並採用分析網路程序法(Analytic Network Process；ANP)計算彈性因子的影響權重。最後結合上述模糊理論、Fuzzy DEMATEL與ANP方法，建立出整體供應鏈彈性評估模式，並就由計算出彈性因子對企業供應鏈的影響，排列出彈性因子的程度大小，讓企業能夠知道彈性因子的優先順序。這將協助企業有效瞭解目前所處供應鏈的彈性程度，並據以研擬相關的因應策略，以增加企業回應不確定性環境的能力。
As part of the division of labor and globalization, enterprises, customers and suppliers are located in various countries and regions. Complex, globalized supply chain network have greatly increased total supply chain risks. Therefore, improving the management of flexibility associated with the supply chain has become important to many enterprises. And whole supply chain have include four stage, source, make, deliver and return, but previous supply chain flexibility management research has focused mainly on single-stage flexibility factors and assumed all flexibility factors to be mutually as independent and also not consider the whole supply chain flexibility factors associated characteristics. The lack of consideration for these relationships will lead to incorrect measuring flexibility and applying improper flexibility management strategies to response these risk events. Therefore, this research concentrates on a topic: How to effectively assess flexibility.
About the main issue, this research will propose an effectively flexibility assessment model. First, the research will consider whole supply chain flexibility factors from literature and then classify these factors into source stage’s factors, make stage’s factors, deliver stage’s factors and return stage’s factors in accordance with SCOR Model (Supply Chain Operations Reference Model) framework. Second, Fuzzy Theory, Fuzzy Decision Making Trial and Evaluation Laboratory (Fuzzy DEMATEL) and Analytic Network Process (ANP) will be adopted and integrated to develop a supply chain flexibility assessment model.
The results in this research will enable enterprises to determine manner the effects of various flexibility, enabling them to develop strategies to increase their responses capability under uncertain environment.
參考文獻 西文部分：
1. Barad, M. and Sapir, D. E., Flexibility in logistic systems－modeling and performance, International Journal of Production Economics, 2003, Vol. 85, pp. 155–170.
2. Behrbohm, P., Flexibility in the Industrial Production, Frankfurt: Western Germany, 1985.
3. Chang, B., Chang, C. H. and Wu, C. H., Fuzzy DEMATEL method for developing supplier selection criteria, Expert Systems with Application, Vol. 38, No.3 ,2011, pp. 1850-1858.
4. Chen, S. J. and Hwang C.L., Fuzzy Multiple Attribute Decision Making Methods and Applications, Berlin, New York, 1992.
5. Chong, A. Y. L., Ooi, K. B. and Sohal, A., The relationship between supply chain factors and adoption of e-Collaboration tools: An empirical examination, International Journal of Production Economics, Vol. 122, No.1, 2009, pp. 150-160.
6. Chopra, S. and P. Meindl , Supply Chain Management: Strategy, Planning, and Operation, New Jersey: Prentice-Hall., 2001.
7. Christopher, M. , The agile supply chain: competing in volatile markets, Industrial Marketing Management, Vol. 29,2000, pp.37–44.
8. Das, S. K. and Abdel-Malek, A.M., Modeling the flexibility of order quantities and lead-times in supply chains, International Journal of Production Economics, Vol. 85, 2003, pp. 171-181.
9. Derrick, E. D., Fredrik, W., Toward a taxonomy of manufacturing flexibility dimensions, Journal of Operations Management Vol.18, Issue 5, 2000, pp. 577–593
10. Dowlatshai S., Developing a theory of reverse logistics, Interfaces, 30(3), 2000, pp.143-155.
11. Duclos, L.K., Vokurka, R.J. and Lummus, R.R., A conceptual model of supply chain flexibility., Industrial Management and Data Systems, Vol. 103, 2003, pp.446 -456.
12. Frazelle, E., Flexibility: A strategic response in changing times”, Industrial Engineering, 1986, pp. 16-20.
13. Gaudenzi, B. and Borghesi, A., Managing risks in the supply chain using the AHP method, The International Journal of Logistics Management, Vol. 24, No. 9, 2007, pp. 958-971.
14. Gerwin, D., Manufacturing Flexibility: A Strategic Perspective, Management Science, Vol.39, No.4, 1993, pp. 395-410.
15. Gupta, D., Buzacott, J. A., A Framework for Understanding Flexibility of Manufacturing Systems, Manufacturing Systems Journal, 1989, pp. 89-97.
16. Gupta, Y. P. and Soners, T, M., The measurement of manufacturing flexibility, European Journal of Operational Research, Vol. 60, 1992, pp. 166-182.
17. Haji, A. and Assadi, M., Fuzzy expert systems and challenge of new product pricing, Computer and Industrial Engineering, Vol. 56, No. 2, 2009, pp. 616-630.
18. Handfield, B. and Nichols, L., Introduction to Supply Chain Management, New Jersey: Prentice-Hall.,1999.
19. Ho, C.F., A Contingency Theoretical Model of Manufacturing Strategy, International Journal of Operations and Production Management, 16(5), 1996, pp.74-98.
20. Kamath, Rajan R. and Liker, Jeffrey K., A Second Look at Japanese Product Development, Harvard Business Review, 72(6), 1994, pp.155-170.
21. Koste, Lori L , Malhotra, Manoj K., A theoretical framework for analyzing the dimensions of manufacturing flexibility, Journal of Operations Management, 1999, Vol.18(1), pp.75-93
22. Lambert, D. M. and Cooper, M. C., Issues in supply chain management, Internal Marketing Management, Vol. 29, No. 1, 2000, pp. 65-83.
23. Lee, L. and Whang, S., Information sharing in a supply chain, International Journal of Technology Management, 20(3), 2000, pp.373-387
24. Liou, J. J. H., Yen, L. and Tzeng, G. H., Building an effective safety management system for airlines, Journal of Air Transport Management, Vol. 14, No. 1, 2008, pp. 20-26.
25. Maloni, I. and Benton, C., Supply Chain Partnerships: Opportunities for operations research, European Journal of Operational Research, 101, 1997, pp.419-429.
26. Martin, D., Conrad, N., Patrick, K. and Amy, W. , Executive`s Guide to E-Business: Form Tactics to Strategy, LLP. ,2000.
27. Mentzer, T., Min, S. and Zacharia, G., The Nature of Inter-Firm Partnering in Supply Chain Management, Journal of Retailing, 76(4), 2000, pp.549-568.
28. Merschmann, U. and Thonemann, U.W., Supply chain flexibility, uncertainty and firm performance: an empirical analysis of German manufacturing firms., International Journal of Production Economics, 130(1), 2011, pp. 43-53.
29. Min, H. and Zhou, G., Supply Chain modeling: past, present and future, Computer and Industrial Engineering, Vol. 43, No. 1, 2002, pp. 231-249.
30. Morlok, E.K. and Chang, D.J., Measuring capacity flexibilityof a transportation system. Transportation Research Part A: Policy and Practice, 38(6), 2004, pp.405-420.
31. Moon, K.K.L., Yi, C.Y. and Ngai, E.W.T., An instrument for measuring supply
chain flexibility for the textile and clothing companies. European Journal of Operational Research, 222(2),2012, 191-203.
32. Muckstadt J.A., Murray, D.H., Rappold, J.A. and Collins, D.E., Guidelines for collaborative supply chain system design and operation , Information Systems Frontiers, 2001, Vol. 3, Issue 4, pp. 427-453
33. Nagarur, N., Some performance measures of flexible manufacturing systems, International Journal of Production Research, Vol. 30, No. 4, 1992, pp. 799-809.
34. Opricovic, S. and Tzeng, G. H., Defuzzification within a multi criteria decision model,International Journal of Uncertainty, Vol. 11, No. 5, 2003, pp. 635-652.
35. Prater, E., Biehl, M. and Smith, M.A., International supply chain agility Tradeoffs between flexibility and uncertainty, International Journal of Operations and Production Management, Vol. 21, 2001, pp.823 – 839.
36. Pujawan, I.N. , Assessing supply chain flexibility: a conceptual framework and case study, International Journal of Integrated Supply Management, Vol. 1, No.1 , 2006, pp. 79 - 97.
37. Beacha, R, Muhlemanna, A.P., Pricea, D.H.R., Patersonb, A., Sharpb, J.A., A review of manufacturing flexibility, European Journal of Operational Research　Vol. 122, Issue 1, 2000, pp. 41–57
38. Rajesh, R., Ravi, V., Supplier selection in resilient supply chains: a grey relational analysis approach , Journal of Cleaner Production, 2015, pp. 343-359.
39. Saaty, T. L., Decision Making with Dependence and Feedback: The Analytic Network Process, 2nd edition, PA:RWS Publication, 2001.
40. Saaty, T. L., The Analytic Hierarchy process – Planning, Priority Setting, Resource Allocation, New York, McGraw-Hill, 1980.
41. Seidmann, A. and Sundararajan, A., “Building and Sustaining Inter-Organizational Information Sharing Relationships: The Competitive Impact of Interfacing Supply Chain Operations with Marketing Strategy, Proceedings of the eighteenth international conference on Information systems, 1997, pp.205-222.
42. Sethi, A., Sethi, S., Flexibility in manufacturing: A survey, International Journal of Flexible Manufacturing Systems, 1990, Vol.2(4), pp. 289-328.
43. Stefan, M., Multiple-supplier inventory models in supply chain management: A review, International Journal of Production Economics, Vol. 81-82, No. 11, 2003, pp. 265-279.
44. Stevenson, M. and Spring, M., Flexibility from a supply chain perspective definition and review. International Journal of Operations and Production Management,27(7), 2007, pp. 685-713.
45. Swafford, P.M., Ghosh, S. and Murthy, N., Achieving supply chain agility through IT integration and flexibility. International Journal of Production Economics, 116(2), 2008, pp. 288-297.
46. Swamidass, M., and Newell, T., Manufacturing Strategy, Environment Uncertainty and Performance: A Path Analytic Model, Management Science, 33(4), 1987, pp.509-524.
47. Tseng, M. L. and Lin, Y. H., Application of fuzzy DEMATEL to development a case and effect model of municipal solid waste management in Metro Manila, Earth and Environmental Science, Vol. 158, No. 1-4, 2009, pp. 519-533.
48. Tuncel, G. and Alpan, G., Risk assessment and management for supply chain network: A case study, Computer in Industry, Vol. 61, No. 3, 2010, pp. 250-259.
49. Upton, D.M., The management of manufacturing flexibility, California Management Review, Vol. 36, 1994, pp. 72–89.
50. Upton, D.M., What really makes factories flexible ? , Harvard Business Review, 1995, pp. 73-74.
51. Vickery, S., Calantone, R. and Droge, C., Supply chain flexibility, The Journal of Supply Chain Management, 1999, pp.16-24.
52. Vickery, V., Roger, C. and Cornelia, D., Supply Chain Flexibility: An Empirical Study, Journal of Supply Chain Management, 35(3), 1999, pp.16-24.
53. Wu, W. W. and Lee, Y. T., Development global managers’ competencies using the fuzzy DEMATEL method, Expert Systems with Application, Vol. 32, No. 2, 2007, pp. 499-507.
 
中文部分：
1. 吳介勛、孫雅彥、林珮珺，民103，供應鏈彈性、資訊科技能力、環境不確定性與組織績效-以定期海運業為例，航運季刊第23卷第三期，頁79~107。
2. 吳昀峰，民103，供應鏈風險管理策略運用之研究，國立政治大學資訊管理學系研究所碩士論文。
3. 吳銘智，民96，模糊理論應用於供應鏈彈性衡量之研究，國立虎尾科技大學工業工程與管理研究所碩士論文。
4. 林宗明，民94，管理問題因果複雜度分析模式建立之研究-以DEMATEL為方法論，私立中原大學企業管理研究所碩士論文。
5. 林盈君，民97，綠色供應鏈中風險評估之研究-以國內某主機板廠商為例，國立政治大學資訊管理學系研究所碩士論文。
6. 紀岱玲，民94，供應商績效評估研究－結合ANP及DEMATEL之應用，國立政治大學資訊管理學系研究所碩士論文。
7. 胡雪琴，民92，企業問題複雜度之探討及量化研究-以DEMATEL為分析工具，私立中原大學企業管理研究所碩士論文。
8. 孫宗瀛、楊英魁，民94，Fuzzy控制：理論、實作與理論，台北：全華圖書股份有限公司。
9. 孫宗瀛、楊英魁，民94，Fuzzy控制：理論、實作與理論，台北：全華圖書股份有限公司。
10. 陳有慶，民102，供應鏈風險評估模式建立之研究-以資訊電子產業為例，國立政治大學資訊管理學系研究所碩士論文。
11. 陳璟鴻，民96，紡織業全球運籌績效指標架構，國立政治大學資訊管理學系研究所碩士論文。
12. 潘俊宏，民94，一衡量供應鏈績效之整合性架構，國立中央大學工業管理研究所碩士論文。
13. 鄭志傑。民99，供應鏈復原能力評估指標之建立－以製造業為例，私立東吳大學企業管理研究所碩士論文。
14. 謝長宏，民69，系統動態學-理論．方法與應用，台北：中興管理顧問公司。
描述 碩士
國立政治大學
資訊管理學系
100356041
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0100356041
資料類型 thesis
dc.contributor.advisor 林我聰zh_TW
dc.contributor.advisor Lin, Woo Tsongen_US
dc.contributor.author (作者) 陳信呈zh_TW
dc.contributor.author (作者) Chen, Hsin Chengen_US
dc.creator (作者) 陳信呈zh_TW
dc.creator (作者) Chen, Hsin Chengen_US
dc.date (日期) 2016en_US
dc.date.accessioned 9-八月-2016 10:44:21 (UTC+8)-
dc.date.available 9-八月-2016 10:44:21 (UTC+8)-
dc.date.issued (上傳時間) 9-八月-2016 10:44:21 (UTC+8)-
dc.identifier (其他 識別碼) G0100356041en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/99763-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 100356041zh_TW
dc.description.abstract (摘要) 企業為有效降低成本、接近顧客市場與提升整體供應鏈效率，紛紛尋找最佳解決方案，專業高效率、有彈性及低成本合作夥伴遍及全球，形成一個複雜全球化的供應鏈網路，導致整體供應鏈的風險大幅提升。當供應鏈危機發生時，有效並快速的回應危機事件漸漸成為企業必須具備的重要能力，企業如何提升供應鏈彈性的能力以應映供應鏈中斷已成為重要的議題。而過去的供應鏈彈性研究上，大部分著重於單一階段進行討論，從整體供應鏈角度的研究仍屬有限，導致無法提供可供決策者參考的供應鏈彈性策略，且供應鏈彈性衡量的研究領域尚處於百家爭鳴的階段，至今相關的研究仍沒有一致的看法。因此，本研究將針對「如何有效評估供應鏈彈性程度」主要問題進行研究。
針對此問題來進行研究，本研究提出一個整體供應鏈彈性評估模式以有效評估供應鏈的彈性程度。首先透過文獻探討確認整理出供應鏈的彈性因子，並以SCOR模式的將彈性因子歸類於各階段內；接著藉由彈性因子的數量範疇、異質性範疇、移轉性與一致性，應用模糊理論篩選出需改善的彈性因子；再使用模糊決策實驗室分析法(Fuzzy Decision Making Trial and Evaluation Laboratory；Fuzzy DEMATEL)建構出供應鏈流程中重要的彈性因子間之關連性；由於彈性因子間具有相依關係，本研究並採用分析網路程序法(Analytic Network Process；ANP)計算彈性因子的影響權重。最後結合上述模糊理論、Fuzzy DEMATEL與ANP方法，建立出整體供應鏈彈性評估模式，並就由計算出彈性因子對企業供應鏈的影響，排列出彈性因子的程度大小，讓企業能夠知道彈性因子的優先順序。這將協助企業有效瞭解目前所處供應鏈的彈性程度，並據以研擬相關的因應策略，以增加企業回應不確定性環境的能力。		zh_TW
dc.description.abstract (摘要) As part of the division of labor and globalization, enterprises, customers and suppliers are located in various countries and regions. Complex, globalized supply chain network have greatly increased total supply chain risks. Therefore, improving the management of flexibility associated with the supply chain has become important to many enterprises. And whole supply chain have include four stage, source, make, deliver and return, but previous supply chain flexibility management research has focused mainly on single-stage flexibility factors and assumed all flexibility factors to be mutually as independent and also not consider the whole supply chain flexibility factors associated characteristics. The lack of consideration for these relationships will lead to incorrect measuring flexibility and applying improper flexibility management strategies to response these risk events. Therefore, this research concentrates on a topic: How to effectively assess flexibility.
About the main issue, this research will propose an effectively flexibility assessment model. First, the research will consider whole supply chain flexibility factors from literature and then classify these factors into source stage’s factors, make stage’s factors, deliver stage’s factors and return stage’s factors in accordance with SCOR Model (Supply Chain Operations Reference Model) framework. Second, Fuzzy Theory, Fuzzy Decision Making Trial and Evaluation Laboratory (Fuzzy DEMATEL) and Analytic Network Process (ANP) will be adopted and integrated to develop a supply chain flexibility assessment model.
The results in this research will enable enterprises to determine manner the effects of various flexibility, enabling them to develop strategies to increase their responses capability under uncertain environment.		en_US
dc.description.tableofcontents 第一章 緒論 1
1.1研究背景 1
1.2研究動機 2
1.3研究目的 3
1.4論文架構 3
第二章 文獻探討 5
2.1供應鏈管理 5
2.2 Supply-Chain Operations Reference-model(SCOR)模型 7
2.3供應鏈彈性 11
2.3.1供應鏈彈性衡量 11
2.3.2供應鏈彈性因子分類 12
2.4模糊理論(Fuzzy Theory) 16
2.5決策實驗分析法(Decision Making Trial & Evaluation Laboratory, DEMATEL) 18
2.5.1 DEMATEL簡介與應用 18
2.5.2 DEMATEL架構與運算步驟 18
2.6網路程序分析法(Analytic Network Process, ANP) 22
2.6.1 ANP簡介與應用 18
2.6.2 ANP架構與運算步驟 23
第三章 研究方法 27
3.1研究流程與研究對象 27
3.1.1研究流程 27
3.1.2研究對象 29
3.2運用模糊理論篩選出供應鏈流程中重要的彈性因子 29
3.3 Fuzzy DEMATEL方法找出供應鏈彈性因子的因果關係 34
3.4 ANP方法決定彈性因子之影響權重 39
3.5彈性評估模式建立 45

第四章 彈性評估模式建立之範例 46
4.1供應鏈彈性因子之確立與定義 46
4.2運用模糊理論篩選出重要的供應鏈彈性因子 46
4.3利用Fuzzy DEMATEL 方法找出重要彈性因子間的因果關係 50
4.4彈性因子之因果關係 53
4.5運用ANP方法找出重要彈性因子間的相對影響權重 55
4.6本研究建立之彈性評估模式 60
第五章 模式之模擬驗證 61
5.1模擬系統設計 61
5.1.1模擬假設 62
5.1.2模擬模型結構 63
5.2模擬過程與實驗設計 68
5.3模擬模式之效度分析 69
5.4模擬之結果 71
第六章 結論與建議 74
6.1 研究結論 74
6.2未來研究方向 75
參考文獻 76		zh_TW
dc.format.extent 9263575 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0100356041en_US
dc.subject (關鍵詞) 供應鏈彈性zh_TW
dc.subject (關鍵詞) 彈性衡量zh_TW
dc.subject (關鍵詞) 模糊理論zh_TW
dc.subject (關鍵詞) 失效模式與效應分析法zh_TW
dc.subject (關鍵詞) 決策實驗室分析法zh_TW
dc.subject (關鍵詞) 分析網路程序法zh_TW
dc.subject (關鍵詞) Supply Chain Flexibility Managementen_US
dc.subject (關鍵詞) Flexibility Measureen_US
dc.subject (關鍵詞) Fuzzy Theoryen_US
dc.subject (關鍵詞) FMEAen_US
dc.subject (關鍵詞) DEMATELen_US
dc.subject (關鍵詞) ANPen_US
dc.title (題名) 供應鏈彈性評估模式建立之研究－以資訊電子產業為例zh_TW
dc.title (題名) The Research on Developing a Flexibility Assessment Model in Supply Chains - using Information and Electronics Industry as an exampleen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 西文部分：
1. Barad, M. and Sapir, D. E., Flexibility in logistic systems－modeling and performance, International Journal of Production Economics, 2003, Vol. 85, pp. 155–170.
2. Behrbohm, P., Flexibility in the Industrial Production, Frankfurt: Western Germany, 1985.
3. Chang, B., Chang, C. H. and Wu, C. H., Fuzzy DEMATEL method for developing supplier selection criteria, Expert Systems with Application, Vol. 38, No.3 ,2011, pp. 1850-1858.
4. Chen, S. J. and Hwang C.L., Fuzzy Multiple Attribute Decision Making Methods and Applications, Berlin, New York, 1992.
5. Chong, A. Y. L., Ooi, K. B. and Sohal, A., The relationship between supply chain factors and adoption of e-Collaboration tools: An empirical examination, International Journal of Production Economics, Vol. 122, No.1, 2009, pp. 150-160.
6. Chopra, S. and P. Meindl , Supply Chain Management: Strategy, Planning, and Operation, New Jersey: Prentice-Hall., 2001.
7. Christopher, M. , The agile supply chain: competing in volatile markets, Industrial Marketing Management, Vol. 29,2000, pp.37–44.
8. Das, S. K. and Abdel-Malek, A.M., Modeling the flexibility of order quantities and lead-times in supply chains, International Journal of Production Economics, Vol. 85, 2003, pp. 171-181.
9. Derrick, E. D., Fredrik, W., Toward a taxonomy of manufacturing flexibility dimensions, Journal of Operations Management Vol.18, Issue 5, 2000, pp. 577–593
10. Dowlatshai S., Developing a theory of reverse logistics, Interfaces, 30(3), 2000, pp.143-155.
11. Duclos, L.K., Vokurka, R.J. and Lummus, R.R., A conceptual model of supply chain flexibility., Industrial Management and Data Systems, Vol. 103, 2003, pp.446 -456.
12. Frazelle, E., Flexibility: A strategic response in changing times”, Industrial Engineering, 1986, pp. 16-20.
13. Gaudenzi, B. and Borghesi, A., Managing risks in the supply chain using the AHP method, The International Journal of Logistics Management, Vol. 24, No. 9, 2007, pp. 958-971.
14. Gerwin, D., Manufacturing Flexibility: A Strategic Perspective, Management Science, Vol.39, No.4, 1993, pp. 395-410.
15. Gupta, D., Buzacott, J. A., A Framework for Understanding Flexibility of Manufacturing Systems, Manufacturing Systems Journal, 1989, pp. 89-97.
16. Gupta, Y. P. and Soners, T, M., The measurement of manufacturing flexibility, European Journal of Operational Research, Vol. 60, 1992, pp. 166-182.
17. Haji, A. and Assadi, M., Fuzzy expert systems and challenge of new product pricing, Computer and Industrial Engineering, Vol. 56, No. 2, 2009, pp. 616-630.
18. Handfield, B. and Nichols, L., Introduction to Supply Chain Management, New Jersey: Prentice-Hall.,1999.
19. Ho, C.F., A Contingency Theoretical Model of Manufacturing Strategy, International Journal of Operations and Production Management, 16(5), 1996, pp.74-98.
20. Kamath, Rajan R. and Liker, Jeffrey K., A Second Look at Japanese Product Development, Harvard Business Review, 72(6), 1994, pp.155-170.
21. Koste, Lori L , Malhotra, Manoj K., A theoretical framework for analyzing the dimensions of manufacturing flexibility, Journal of Operations Management, 1999, Vol.18(1), pp.75-93
22. Lambert, D. M. and Cooper, M. C., Issues in supply chain management, Internal Marketing Management, Vol. 29, No. 1, 2000, pp. 65-83.
23. Lee, L. and Whang, S., Information sharing in a supply chain, International Journal of Technology Management, 20(3), 2000, pp.373-387
24. Liou, J. J. H., Yen, L. and Tzeng, G. H., Building an effective safety management system for airlines, Journal of Air Transport Management, Vol. 14, No. 1, 2008, pp. 20-26.
25. Maloni, I. and Benton, C., Supply Chain Partnerships: Opportunities for operations research, European Journal of Operational Research, 101, 1997, pp.419-429.
26. Martin, D., Conrad, N., Patrick, K. and Amy, W. , Executive`s Guide to E-Business: Form Tactics to Strategy, LLP. ,2000.
27. Mentzer, T., Min, S. and Zacharia, G., The Nature of Inter-Firm Partnering in Supply Chain Management, Journal of Retailing, 76(4), 2000, pp.549-568.
28. Merschmann, U. and Thonemann, U.W., Supply chain flexibility, uncertainty and firm performance: an empirical analysis of German manufacturing firms., International Journal of Production Economics, 130(1), 2011, pp. 43-53.
29. Min, H. and Zhou, G., Supply Chain modeling: past, present and future, Computer and Industrial Engineering, Vol. 43, No. 1, 2002, pp. 231-249.
30. Morlok, E.K. and Chang, D.J., Measuring capacity flexibilityof a transportation system. Transportation Research Part A: Policy and Practice, 38(6), 2004, pp.405-420.
31. Moon, K.K.L., Yi, C.Y. and Ngai, E.W.T., An instrument for measuring supply
chain flexibility for the textile and clothing companies. European Journal of Operational Research, 222(2),2012, 191-203.
32. Muckstadt J.A., Murray, D.H., Rappold, J.A. and Collins, D.E., Guidelines for collaborative supply chain system design and operation , Information Systems Frontiers, 2001, Vol. 3, Issue 4, pp. 427-453
33. Nagarur, N., Some performance measures of flexible manufacturing systems, International Journal of Production Research, Vol. 30, No. 4, 1992, pp. 799-809.
34. Opricovic, S. and Tzeng, G. H., Defuzzification within a multi criteria decision model,International Journal of Uncertainty, Vol. 11, No. 5, 2003, pp. 635-652.
35. Prater, E., Biehl, M. and Smith, M.A., International supply chain agility Tradeoffs between flexibility and uncertainty, International Journal of Operations and Production Management, Vol. 21, 2001, pp.823 – 839.
36. Pujawan, I.N. , Assessing supply chain flexibility: a conceptual framework and case study, International Journal of Integrated Supply Management, Vol. 1, No.1 , 2006, pp. 79 - 97.
37. Beacha, R, Muhlemanna, A.P., Pricea, D.H.R., Patersonb, A., Sharpb, J.A., A review of manufacturing flexibility, European Journal of Operational Research　Vol. 122, Issue 1, 2000, pp. 41–57
38. Rajesh, R., Ravi, V., Supplier selection in resilient supply chains: a grey relational analysis approach , Journal of Cleaner Production, 2015, pp. 343-359.
39. Saaty, T. L., Decision Making with Dependence and Feedback: The Analytic Network Process, 2nd edition, PA:RWS Publication, 2001.
40. Saaty, T. L., The Analytic Hierarchy process – Planning, Priority Setting, Resource Allocation, New York, McGraw-Hill, 1980.
41. Seidmann, A. and Sundararajan, A., “Building and Sustaining Inter-Organizational Information Sharing Relationships: The Competitive Impact of Interfacing Supply Chain Operations with Marketing Strategy, Proceedings of the eighteenth international conference on Information systems, 1997, pp.205-222.
42. Sethi, A., Sethi, S., Flexibility in manufacturing: A survey, International Journal of Flexible Manufacturing Systems, 1990, Vol.2(4), pp. 289-328.
43. Stefan, M., Multiple-supplier inventory models in supply chain management: A review, International Journal of Production Economics, Vol. 81-82, No. 11, 2003, pp. 265-279.
44. Stevenson, M. and Spring, M., Flexibility from a supply chain perspective definition and review. International Journal of Operations and Production Management,27(7), 2007, pp. 685-713.
45. Swafford, P.M., Ghosh, S. and Murthy, N., Achieving supply chain agility through IT integration and flexibility. International Journal of Production Economics, 116(2), 2008, pp. 288-297.
46. Swamidass, M., and Newell, T., Manufacturing Strategy, Environment Uncertainty and Performance: A Path Analytic Model, Management Science, 33(4), 1987, pp.509-524.
47. Tseng, M. L. and Lin, Y. H., Application of fuzzy DEMATEL to development a case and effect model of municipal solid waste management in Metro Manila, Earth and Environmental Science, Vol. 158, No. 1-4, 2009, pp. 519-533.
48. Tuncel, G. and Alpan, G., Risk assessment and management for supply chain network: A case study, Computer in Industry, Vol. 61, No. 3, 2010, pp. 250-259.
49. Upton, D.M., The management of manufacturing flexibility, California Management Review, Vol. 36, 1994, pp. 72–89.
50. Upton, D.M., What really makes factories flexible ? , Harvard Business Review, 1995, pp. 73-74.
51. Vickery, S., Calantone, R. and Droge, C., Supply chain flexibility, The Journal of Supply Chain Management, 1999, pp.16-24.
52. Vickery, V., Roger, C. and Cornelia, D., Supply Chain Flexibility: An Empirical Study, Journal of Supply Chain Management, 35(3), 1999, pp.16-24.
53. Wu, W. W. and Lee, Y. T., Development global managers’ competencies using the fuzzy DEMATEL method, Expert Systems with Application, Vol. 32, No. 2, 2007, pp. 499-507.
 
中文部分：
1. 吳介勛、孫雅彥、林珮珺，民103，供應鏈彈性、資訊科技能力、環境不確定性與組織績效-以定期海運業為例，航運季刊第23卷第三期，頁79~107。
2. 吳昀峰，民103，供應鏈風險管理策略運用之研究，國立政治大學資訊管理學系研究所碩士論文。
3. 吳銘智，民96，模糊理論應用於供應鏈彈性衡量之研究，國立虎尾科技大學工業工程與管理研究所碩士論文。
4. 林宗明，民94，管理問題因果複雜度分析模式建立之研究-以DEMATEL為方法論，私立中原大學企業管理研究所碩士論文。
5. 林盈君，民97，綠色供應鏈中風險評估之研究-以國內某主機板廠商為例，國立政治大學資訊管理學系研究所碩士論文。
6. 紀岱玲，民94，供應商績效評估研究－結合ANP及DEMATEL之應用，國立政治大學資訊管理學系研究所碩士論文。
7. 胡雪琴，民92，企業問題複雜度之探討及量化研究-以DEMATEL為分析工具，私立中原大學企業管理研究所碩士論文。
8. 孫宗瀛、楊英魁，民94，Fuzzy控制：理論、實作與理論，台北：全華圖書股份有限公司。
9. 孫宗瀛、楊英魁，民94，Fuzzy控制：理論、實作與理論，台北：全華圖書股份有限公司。
10. 陳有慶，民102，供應鏈風險評估模式建立之研究-以資訊電子產業為例，國立政治大學資訊管理學系研究所碩士論文。
11. 陳璟鴻，民96，紡織業全球運籌績效指標架構，國立政治大學資訊管理學系研究所碩士論文。
12. 潘俊宏，民94，一衡量供應鏈績效之整合性架構，國立中央大學工業管理研究所碩士論文。
13. 鄭志傑。民99，供應鏈復原能力評估指標之建立－以製造業為例，私立東吳大學企業管理研究所碩士論文。
14. 謝長宏，民69，系統動態學-理論．方法與應用，台北：中興管理顧問公司。		zh_TW