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研究生:徐佳佑
研究生(外文):Chia-Yu Hsu
論文名稱:模糊環境下供應彈性評估之研究—以台灣工具機產業為例
論文名稱(外文):Measuring Supply Flexibility Performance in Fuzzy Environment according to Taiwan''s Machine Tool Industry
指導教授:張洝源張洝源引用關係
指導教授(外文):An-Yuan Chang
學位類別:碩士
校院名稱:國立虎尾科技大學
系所名稱:工業工程與管理研究所
學門:工程學門
學類:工業工程學類
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:供應彈性評估模糊德爾菲法多準則決策群體決策模糊積分
外文關鍵詞:Supply Flexibility MeasuringFuzzy Delphi MethodMultiple Criteria Decision MakingGroup Decision MakingFuzzy Integral
相關次數:
  • 被引用被引用:2
  • 點閱點閱:306
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
在企業面臨全球化競爭、資訊科技進步迅速、以及產品生命週期日益縮短等因素下,迫使企業的經營環境不僅日趨險峻,其不確定性亦同時增加。有鑑於此,為在競爭激烈與多變的商業環境中謀生存,企業必須具備隨環境變化而調整之能力,從而建構一個穩健的彈性供應鏈乃為因應環境不確定性之重要對策;藉由彈性供應鏈具備能迅速回應各種不確定因素的特性,以降低營運成本並提高經營績效,進而快速滿足多樣多變的顧客需求。再者,由於經營理念的轉變,企業必須建構新的評估模式,以利與供應商建立長期可靠的夥伴關係。因此,供應商遴選將是企業建構供應鏈體系的核心要務,而供應彈性評估則是執行供應商遴選與建立長期夥伴關係的首要工作。
本研究經彙整文獻所提及之供應鏈彈性作為建構供應彈性評估架構之參考依據,同時運用模糊德爾菲法求解架構內各屬性與行為之合理性,並結合多準則決策與群體決策作為評估之運算方法,最後以模糊積分為基礎的決策模式加以整合以產生結果,此舉不僅將有效降低極端值對整合決策值之影響,同時亦能得到評估最佳解。


In order to survive in a highly competitive and changing business environment, scholars agree that enterprises must have the ability to adjust to the changing environment. A strong Supply Chain Flexibility has been developed and is an important countermeasure to respond to the uncertainty of the environment. As business concepts change, enterprises have to build a new assessment model to facilitate and establish long-term and reliable partnerships with suppliers. Therefore, supplier selection is a core task in the construction of the supply chain system. While the supplier selection and establishing the long-term partnership, the Supply Flexibility Measurement is the primary task.
This study reviews the liferafure that are referred to Supply Chain Flexibility to establish a Supply Flexibility Measurement reference. It uses the Fuzzy Delphi Method to solve the rational of property and behavior within the framework, and is combined with Multiple Criteria Decision Making, Group Decision Making as an operational method of measuring. Finally, use of a decision integration model that is based on Fuzzy Integral will reduce the effects from extreme value on the decision integration results and get the optimal measuring solution.


中文摘要 ..............................................i
Abstract ..............................................ii
誌謝 ..............................................iii
目錄 ..............................................iv
表目錄 ..............................................vi
圖目錄 ..............................................vii
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 .....................................2
1.4 研究範圍 .....................................3
1.5 研究架構 .....................................3
第二章 文獻探討 .....................................6
2.1 彈性 .....................................6
2.1.1 製造系統彈性 ............................7
2.1.2 供應鏈彈性 ............................8
2.1.3 供應鏈彈性應用 ............................9
2.2 群體決策與多準則決策 ...................11
2.2.1 群體決策 .....................................12
2.2.2 多準則決策 ............................12
2.2.3 層級分析法 ............................15
2.2.4 群體決策整合層級分析法 ...................18
2.3 模糊積分 .....................................19
2.3.1 模糊積分運算模式 ............................19
2.3.2 模糊積分之應用 ............................21
第三章 研究方法 .....................................23
3.1 模糊德爾菲法 ............................24
3.2 層級分析法 ............................26
3.3 Super Decisions軟體簡介 ...................29
3.4 模糊積分 .....................................30
3.4.1 模式架構 .....................................30
3.4.2 定義h(xi) .....................................30
3.4.3 定義gi .....................................31
3.4.4 模式進行步驟 ............................34
第四章 實驗分析 .....................................35
4.1 建立彈性評估準則 ............................36
4.2 評估層級架構 ............................40
4.3 層級分析 .....................................41
4.3.1 屬性層面公式分析範例 ...................44
4.3.2 屬性層面(準則)權重值分析 ...................45
4.3.3 評估準則(次準則)權值分析 ...................46
4.4 模糊積分整合 ............................50
第五章 結論與建議 .....................................53
5.1 結論 .....................................53
5.2 建議 .....................................54
參考文獻 ..............................................56
附錄一 Super Decisions軟體下載處 ..................66
附錄二 主管資料 ....................................67
附錄三 第一階段問卷調查 ...........................68
附錄四 第二階段問卷調查 ...........................72



1.Aprile, D., Garavelli, A.C., and Giannoccaro, I. (2005). “Operations planning and flexibility in a supply chain”, Production Planning and Control, Vol. 16, NO. 1, pp. 21-31.
2.Barad, M., and Sapir, D.E. (2003). “Flexibility in logistic systems-modeling and performance evaluation”, International Journal of Production Economics, Vol. 85, NO. 2, pp. 155-170.
3.Barad, M., and Sipper, D. (1988). “Flexibility in manufacturing systems: Definitions and petri net modeling”, International Journal of Production Research, Vol. 26, NO. 2, pp. 237-248.
4.Barzilai, J., Lootsma, F.A. (1997). “Power relations and group aggregation in the multiplicative AHP and SMART”, Journal of Multi-Criteria Decision Analysis, Vol. 6, NO. 1, pp. 155-165.
5.Basak, I. (1998). “Probabilistic judgments specified partially in the Analytic Hierarchy Process”, European Journal of Operational Research, Vol. 108, NO. 2, pp. 153-164.
6.Beamon, B. (1999). “Measuring supply chain performance”, International Journal of Operations and Production Management, Vol. 19, No. 3, pp. 275–292.
7.Benjaafar, S. (1994). “Models for performance evaluation of flexibility in manufacturing systems”, International Journal of Production Research, Vol. 32, No. 6, pp. 1383-1402.
8.Bhatia, P.K. (1997). “On measures of information energy”, Information Science, Vol. 97, No. 3-4, pp. 233-240.
9.Braglia, M. and Petroni, A. (2000). “A quality-assurance oriented methodology for handling trade-offs in supplier selection”, International Journal of Physical Distribution & Logistics, Vol. 30, No. 2, pp. 96-111.
10.Brill, P.H. and Mandelbaum, M. (1989). “On measures of flexibility in manufacturing systems”, International Journal of Production Research, Vol. 27, No. 5, pp. 747-756.
11.Bryson, N. and Joseph, A. (1999). “Generating consensus priority point vectors: a logarithmic goal programming approach”, Computers & Operations Research, Vol. 26, No. 6, pp. 637-643.
12.Buckley, J.J. (1985). “Fuzzy Hierarchical Analysis”, Fuzzy Sets and Systems, Vol. 17, pp. 233-247.
13.Bui, T.X. and Jarke, M. (1986). “Cummunications design for co-oP: A group decision support system”, ACM Transcations on Office Information Systems, Vol. 4, No. 2, pp. 81-103.
14.Buzacott, J.A. and Mandelbaum, M. (1985). “Flexibility and productivity in manufacturing systems”, Proceedings of the Annual IIE Conference, Los Angeles and Chicago, pp. 404-413.
15.Carter, M.F. (1986). “Designing flexibility into automated manufacturing systems”, In: Stecke, K.E., Suri, R. (Eds.), Proceedings of the 2nd ORSA/TIMS Conference on Flexible Manufacturing Systems: Operations Research Models and Applications. Elsevier, Amsterdam, pp. 107-118.
16.Chandra, P. and Tombak, M.M. (1992). “Models for the evaluation of routing and machine flexibility”, European Journal of Operational Research, Vol. 60, pp. 156-165.
17.Chang, P.T., Huang, L.C. and Lin, H.J. (1995). “An efficient approach for large scale project planning based on fuzzy Delphi method”, Fuzzy Sets and System, Vol. 76, pp. 277-288.
18.Chang, S.C., Chen, R.H., Lin, R.J., Tien, S.W., and Sheu, C. (2006). “Supplier involvement and manufacturing flexibility”, Technovation, Vol. 26, No. 10, pp. 1136-1146.
19.Chatterjee, A., Cohen, M., Maxwell, W. and Miller, L. (1984). “Manufacturing flexibility: models and measurement”, Proceedings of First Annual ORSArTIMS Conference on Flexible Manufacturing Systems, Ann Arbor, MI. pp. 49–64
20.Chen Y. W. and Tzeng G. H. (2001). “Using fuzzy integral for evaluation subjectively perceived travel costs in a traffic assignment model”, European Journal of Operational Research, Vol. 130, pp. 653-664.
21.Chen, L.H. and Chiou, T.W. (1999).”A fuzzy credit-rating approach for commercial loans: A Taiwan case”, Omega, Vol. 27, No. 4, pp. 407-419.
22.Chen, T. and Wang, J. (2001). “Identification of λ-fuzzy measures using sampling design and genetic algorithms”, Fuzzy Sets and Systems, Vol. 123, pp. 321-341.
23.Chen, T.Y. and Wang, J.C. (2001). “Identification of λ-fuzzy measures using sampling design and genetic algorithms”, Fuzzy Sets and Systems, Vol. 123, No. 3 , pp. 321-341.
24.Ching, J. H. (1999). “Coquet fuzzy integral-based hierarchical networks for decision analysis”, IEEE Transactions on Fuzzy Systems, Vol. 7, No. 1, pp. 63-71.
25.Choi, H.A., Suh, E.H. and Suh, C.K. (1994). “Analytic hierarchy process: It can work for group decision support systems”, Computers and Industrial Engineering, Vol. 27, No. 1-4, pp. 167-171.
26.Cox, T. (1989). “Towards the measurement of manufacturing flexibility”, Production and Inventory Management Journal, First Quarter, pp.68-89.
27.Dalkey, N.C. (1969). “The Delphi method: an experimental study of group opinion”, The RAND Corporation, Research Paper RM-5888-PR.
28.Das, S.K. and Abdel-Malek, L. (2003). “Modeling the flexibility of order quantities and lead-times in supply chains”, International Journal of Production Economics, Vol. 85, No. 2, pp. 171-181.
29.Daugherty, P.J. and Pittman, P.H. (1995). “Utilization of Time-based Strategies”, International Journal of Operations and Production Management, Vol. 15, No. 2, pp. 54-60.
30.Davis, T. (1993). “Effective Supply Chain Management”, Sloan Management Review, Summer, pp. 35-46.
31.Delgado, M., Verdegay, J. L. and Vila, M. A. (1992). “Linguistic decision making models”, International Journal of Intelligent Systems, Vol. 7, No. 5, pp. 479-492.
32.DeMeyer, A., Nakane, J., Miller, J.G. and Ferdows, K. (1989). “Flexibility: The next competitive battle – The manufacturing futures survey”, Strategic Management Journal, Vol. 10, No. 2, pp. 135-144.
33.DeSantics, G. and Gallupe, R.B.(1987). “A foundation for the study of group decision support systems”, Management Science, Vol. 33, pp. 589-609.
34.Duclos, L.K., Vokurka, R.J. and Lummus, R.R. (2003). “A conceptual model of supply chain flexibility”, Industrial Management and Data Systems, Vol. 103, No. 5-6, pp. 446-456.
35.Fawcett, S.E., Stanley, L.L. and Smith, S.R. (1997). “Developing a Logistics Capability to Improve the Performance of International Operations”, Journal of Business Logistics, Vol. 18, No. 2, pp. 101-127.
36.Forman, E. and Peniwati, K. (1998). “Aggregating individual judgments and priorities with the Analytic Hierarchy Process”, European Journal of Operational Research, Vol. 108, No. 1, pp. 165-169.
37.Frazelle, E.H. (1986). “Flexibility: A strategic response in changing times”, Industrial Engineering, March, pp. 24-32.
38.Garavelli, A.C. (2003). “Flexibility configurations for the supply chain management”, International Journal of Production Economics, Vol. 85, No. 2, pp. 141-153.
39.Gardner Publications, Inc.,http://www.gardnerweb.com/
40.Gerwin, D. (1993). “Manufacturing flexibility: A strategic perspective”, Management Science, Vol. 39, No. 4, pp. 395–410.
41.Grabisch M. (1996). “The application of fuzzy integrals in multicriteria decision making”, European Journal of Operational Research, Vol. 89, No. 3, pp. 445-456.
42.Gupta, D. and Buzacott, J.A. (1989). “A framework for understanding flexibility of manufacturing systems”, Journal of Manufacturing Systems, Vol. 8, No. 2, pp. 89-97.
43.Gupta, D.(1993). “On measurement and valuation of manufacturing flexibility”, International Journal of Production Research, Vol. 31, No. 12, pp. 2947-2958.
44.Gupta, Y.P. and Goyal, S. (1989). “Flexibility of Manufacturing Systems: Concepts and Measurement”, European Journal of Operation Research, Vol. 43, pp. 119-135.
45.Gupta, Y.P. and Somers, T.M. (1992). “The measurement of manufacturing flexibility”, European Journal of Operational Research, Vol. 60, pp. 166-182.
46.Gustavsson, S. (1984). “Flexibility and productivity in complex production processes”, International Journal of Production Research, Vol. 22, No. 5, pp. 801-808.
47.Handfield, R.B. and Nichols, E.L. (1999). Introduction to Supply Chain Management, Prentice Hall, Upper Saddle River, New Jersey 07458.
48.Helmer, O.H. (1966). The Delphi Method for Systematizing Judgments about the Future. Institute of Government and Public Affairs, University of California: Institute of Government and fuzzy statistics.
49.Herrear, F., Herrera-Viedma, E. and Verdegay, J.L. (1996). “Direct approach in group decision making using linguistic OWA operators”, Fuzzy Sets and Systems, Vol. 79, pp. 175-190.
50.Hill, T. and Chambers, S. (1991). “Flexibility-A manufacturing conundrum”, International Journal of Operations and Production Management, Vol. 11, No. 2, pp. 5-13.
51.Hwang, C.L. and Lin, M.J. (1987). Group decision making under multiple criteria – methods and applications, Springer-Verlag, Berlin Heidelberg.
52.Hwang, C.L. and Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications, New York: Springer-Verlag.
53.Ishii, K. and Sugeno, M. (1985). “A model human evaluation process using fuzzy measure”, International Journal of Man-Machine Studies, Vol. 22, pp. 19-38.
54.Ishikawa, A., Amagasa, T., Tamizawa, G., Totsuta, R. and Mieno, H. (1993). “The Max-Min Delphi Method and Fuzzy Delphi Method Via Fuzzy Integration”, Fuzzy Sets and Systems, Vol. 55, pp. 241-253.
55.Keeney, R.L. (1984). “Decision Analysis:An Overview”, Operations Research, Vol. 30, No. 5, pp. 803-838.
56.Kim, C. (1991). “Issues of manufacturing flexibility”, Integrated Manufacturing Systems, Vol. 2, No. 2, pp. 4-13.
57.Klir, G.J. and Floger, T.A. (1988). Fuzzy Sets, Uncertainty and Information, Prentice-Hall.
58.Klir, G.J. and Yuan, B. (1995). Fuzzy Sets and Fuzzy Logic – Theory and Applications, Prentice-Hall, New Jersey.
59.Kochikar, V.P. and Narendran, T.T. (1992). “A framework for assessing the flexibility of manufacturing systems”, International Journal of Production Research, Vol. 30, No. 12, pp. 2873-2895.
60.Kumar, V. (1987). “Entropic measures of manufacturing flexibility”, International Journal of Production Research, Vol. 25, No. 7, pp. 957-966.
61.Lee, C., Liu, L.C. and Tzeng, G.H. (2000). “Hierarchical fuzzy integral evaluation approach for vocational education performance: case of junior colleges in Taiwan”, International Journal of Fuzzy Systems, Vol. 3, No. 3, pp. 476-485.
62.Lewis, T.G. (1997). The Friction Free Economy Marketing Strategies for a Wired World, harpercollins publishers, Inc.
63.Liang, S.K., Hsieh, S.Y. and Liang, H.C. (2006). “Determinants of the Assignment of Managers to Foreign Branches by Banks, using the Fuzzy Delphi Method.” International Journal of Management, Vol. 23, No. 2, pp. 261-271.
64.Lin, C., Yeh, J.M., Kreng, B.W., and Gee, J.Y. (1999). “A modified procedure for synthesizing ratio judgments in the analytic hierarchy process”, Journal of the Operational Research Society, Vol. 50, No. 8, pp. 867-873.
65.Linstone, H.A. and Turoff, M. (1979). The Delphi Method:Techniques and Applications, Addison-Wesley Publishing Company, MA.
66.MacKay, D.B., Bowen, W.M. and Zinnes, J.L. (1996). “A thurstonian view of the analytic hierarchy process”, European Journal of Operational Research, Vol. 89, No. 2, pp. 427-444.
67.Mandelbaum, M. (1978). Flexibility in Decision Making: An Exploration and Unification, Unpublished doctoral dissertation, University of Toronto, Canada.
68.Mandelbaum, M. and Buzacott, J. (1990). “Flexibility and decision making”, European Journal of Operational Research, Vol. 44, pp. 17-27.
69.Mascarenhas, B. (1981). “Planning for Flexibility”, Long Range Planning, Vol. 14, No. 5, pp. 78-82.
70.Matsatsinis, N.F. and Samaras, A.P. (2001). “MCDA and preference disaggregation in group decision support systems”, European Journal of Operational research, Vol. 130, pp. 414-429.
71.Mohanty, B.K. and Singh, N. (1994). “Fuzzy relational equations in analytical hierarchy process”, Fuzzy Sets and Systems, Vol. 63, No. 1, pp. 11-19.
72.Mon, D.L., Cheng, C.H. and Lin, J.C. (1994). “Evaluation weapon system using fuzzy analytic hierarchy process based on entropy weight”, Fuzzy Sets and Systems, Vol. 62, No. 1, pp. 127-134.
73.Newman, W.R., Hanna, M. and Maffei, M.J. (1993). “Dealing with the uncertainties of manufacturing: Flexibility, buffers and integration”, International Journal of Operations and Production Management, Vol. 13, No. 1, pp. 19-34.
74.Nilsson, C.H. and Nordahl, H. (1995). “Making Manufacturing Flexibility Operational-Part 1: A Framework”, Integrated Manufacturing Systems, Vol.6, No.1, pp.5-11.
75.Nilsson, C.H. and Nordahl, H. (1995). “Making Manufacturing Flexibility Operational-Part 2: Distinctions and an Example”, Integrated Manufacturing Systems, Vol.6, No. 2, pp.4-10.
76.Olhager, J. and West, B.M. (2002). “The house of flexibility: Using the QFD approach to deploy manufacturing flexibility”, International Journal of Operations and Production Management, Vol. 22, No. 1, pp. 50–79.
77.Onicescu, O. (1966). “Energie informationelle”, Comptes Rendus Acad. Sci. Paris, Vol. 263, No. 22, pp. 841-842.
78.Perona, M. and Saccani, N. (2004). “Integration techniques in customer–supplier relationships: An empirical research in the Italian industry of household appliances”, International Journal of Production Economics, Vol. 89, No. 2, pp. 189-205.
79.Pham, T.D. and Yan, H. (1996). Information fusion by fuzzy integral, Proceeding 1996 Australian New Zealand Conference on Intelligent Information Systems, pp. 18-20.
80.Pujawan, I.N. (2004). “Assessing supply chain flexibility: a conceptual framework and case study”, International Journal of Integrated Supply Management, Vol. 1, No. 1, pp. 79 - 97.
81.Ramanathan, R. (2001). “A note on the use of the analytic hierarchy process for environmental impact assessment”, Journal of Environmental Management, Vol. 63, pp. 27-35.
82.Ramanathan, R. and Ganesh, L.S. (1994). “Group preference aggregation methods employed in AHP: an evaluation and an intrinsic process for deriving members’ weightages”, European Journal of Operational Research, Vol. 79, No. 2, pp. 249-265.
83.Ramasesh, R.V. and Jayakumar, M.D. (1991). “Measurement of manufacturing flexibility: A valued based approach”, Journal of Operations Management, Vol. 10, No. 4, pp. 446-467.
84.Roll, Y., Karni, R., and Arzi, Y. (1992). “Measurement of processing flexibility in flexible manufacturing cells”, Journal of Manufacturing Systems, Vol. 11, No. 4, pp. 258-268.
85.Saaty, T.L. (1980). The analytic hierarchy process, McGraw-Hill, New York.
86.Saaty, T.L. (1990). The Analytic Hierarchy Process, RWS publication 2nd edition, Pittsburgh.
87.Saaty, T.L. (2000). Fundamentals of Decision Making and Priority Theory with the Analytic Hierarchy Process, Pittsburg: RWS Publications.
88.Saaty, T.L. and Takizawa, M. (1986). “Dependence and independence: from linear hierarchies to nonlinear networks”, European Journal of Operational Researchs, Vol. 26, pp. 229-237.
89.Salo, A.A. (1995). “Interactive decision aiding for group decision support”, European Journal of Operational Research, Vol. 84, No. 1, pp. 134-149.
90.Sánchez, A.M. and Pérez, M.P. (2005). “Supply chain flexibility and firm performance: A conceptual model and empirical study in the automotive industry”, International Journal of Operations & Production Management, Vol. 25, No. 7, pp. 681-700.
91.Sarker, B.R., Krishnamurthy, S. and Kuthethur, S.G. (1994). “A survey and critical review of flexibility measures in manufacturing systems”, Production Planning and Control, Vol. 5, No. 6, pp. 512-523.
92.Shewchuck, J.P. (1998). “Definitions and classifications of manufacturing flexibility types and measures”, International Journal of Flexible Manufacturing Systems, Vol. 10, pp. 325–349.
93.Slack, N. (1983). “Flexibility as a manufacturing objective”, International Journal of Operations and Production Management, Vol. 3, pp. 4-13.
94.Slack, N. and Correa, H. (1992). “The flexibility of push and pull”, International Journal of Operations and Production Management, Vol. 12, No. 4, pp. 82-92.
95.Son, Y.K. and Park, C.S. (1987). “Economic measures of productivity, quality and flexibility in advanced manufacturing systems”, Journal of Manufacturing Systems, Vol. 6, No. 3, pp. 193-206.
96.Suarey, F., Cusumano, M.A. and Fine, C.H. (1991). Flexibility and Performance: A Literature Critique and Strategic Framework, Sloan School, MIT Cambridge, MA.
97.Suarez, F.F., Cusumano, M.A., and Fine, C.H. (1996). “An empirical study of manufacturing flexibility in printed circuit board assembly”, Operations Research, Vol. 44, No. 1, pp. 223-240.
98.Sugeno, M. (1974). Theory of fuzzy integrals and its applications, PhD thesis, Tokyo Institute of Technology, Tokyo, Japan.
99.Sugeno, M. (1977). Fuzzy measures and fuzzy integers-a survey, Fuzzy Automation and Decision Processes, Amsterdam, North Holland.
100.Suresh, N.C. (1991). “An extended multi-objective replacement model for flexible automation investments”, International Journal of Production Research, Vol. 29, No. 9, pp. 1823-1844.
101.Swafford, P., Ghosh, S. and Murthy, N. (2000). “A model of global supply chain agility and its impact on competitive performance”, Proceedings of the 31st National DSI Meeting, Orlando, Florida, November, pp.1037–1039.
102.Swamidass, P.M. and Newell, W.T. (1987). “Manufacturing Strategy, Environmental uncertainty and Performance: A Path Analytic Model”, Management Science, Vol. 33, No. 4, pp. 509-524.
103.Tahani, H. and Keller, J.M. (1990). “Information fusion in computer vision using the fuzzy integral”, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 20, No. 3, pp. 733-741.
104.Taiwan Association of Machinery Industry.,http://www.tami.org.tw
105.Tincknell, D.J. and Radcliffe, D.F. (1996). “A generic model of manufacturing flexibility based on system control hierarchies”, International Journal of Production Research, Vol. 34, No. 1, pp. 19-32.
106.Upton, D.M. (1994). “The management of manufacturing flexibility”, California Management Review, Vol. 36, No. 2, pp. 72-89.
107.Upton, D.M. (1995). “What Really Makes Factories Flexible”, Harvard Business Review, July/August, pp. 74-84.
108.Vargas, L.G. (1990). “An overview of the analytic hierarchy process and its applications”, European Journal of Operational Research, Vol. 48, No. 1, pp. 2-8.
109.Vickery, S., Calantone, R. and Droge, C. (1999), “Supply Chain Flexibility: An Empirical Study”, The Journal of Supply Chain Management, Vol. 35, No. 3, pp. 16-24.
110.Wang, Y.C. and Yen, K.N. (2006). “Exploring and Evaluating Flexibilities of a Supply Chain”, 36thCIE Conference on Computer & Industrial Engineering, Taiwan.
111.Xu, R. and Zahir, X. (1992). “Extensions of the analytic hierarchy process in fuzzy environment”, Fuzzy Sets and systems, Vol. 52, No. 3, pp. 251-257.
112.Xu, Z. (2000). “On consistency of the weighted geometric mean complex judgment matrix in AHP”, European Journal of Operational Research, Vol. 126, No. 3, pp. 683-687.
113.Yager, R.R. and Kelman, A. (1999). “An extension of the analytical hierarchy process using OWA operators”, Journal of Intelligent and Fuzzy Systems, Vol. 7, No. 4, pp. 401–417.
114.Yeh, C.C. and Chang, P.L. (2003). “The Taiwan System of Innovation in the Tool Machine Industry: A Case Study”, Journal of Engineering and Technology Management, Vol. 20, pp. 367-380.
115.Yoon, K. and Hwang, C.L. (1985). “Manufacturing Plant Location Analysis by Multiple Attribute Decision Making: Part I–Single-Plant Strategy”, International Journal of Production Research, Vol. 23, No. 2, pp. 345-359.
116.Yoon, K.P. and Hwang, C.L. (1995). Multiple Attribute Decision Making: An Introduction, Thousand Oaks: Sage PublicationsInc.
117.Zahedi, F. (1986). “The Analytic Process-a Survey of the Method and its Applications”, Interface, Vol. 16, pp. 96- I08.
118.Zahir, S. (1999). “Geometry of decision making and the vector space of formulation of the analytic hierarchy process”, European Journal of Operational Research, Vol. 112, No. 2, pp. 373-396.
119.Zelenovic, D.M. (1982). “Flexibility: A condition for effective production systems”, International Journal of Production Research, Vol. 20, No. 3, pp. 319-337.
120.Zhou, S. and Kocaoglu, D.F. (1996). “Minimum distance method (MDM) for group judgment aggregations”, Proceedings of International Conference on Engineering and Technology Management, pp. 781-786.


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