Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/99763
|
| Title: | 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 |
| Authors: | 陳信呈
Chen, Hsin Cheng |
| Contributors: | 林我聰
Lin, Woo Tsong
陳信呈
Chen, Hsin Cheng |
| Keywords: | 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 |
| Date: | 2016 |
| Issue Date: | 2016-08-09 10:44:21 (UTC+8) |
| Abstract: | 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. |
| Reference: | 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。 |
| Description: | 碩士
國立政治大學
資訊管理學系
100356041 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0100356041 |
| Data Type: | thesis |
| Appears in Collections: | [資訊管理學系] 學位論文
|
Files in This Item:
| File |
Size | Format | |
|---|
| 604101.pdf | 9046Kb | Adobe PDF2 | 113 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
