臺灣博碩士論文加值系統

回顧近年來由於世界各地的重大突發災變事件頻傳，不論是自然災害、人為破壞、公共衛生、經濟風暴、地緣政治不穩定等所帶來的風險，隨著企業供應鏈向全球化延伸，突發事件所產生直接或間接性的影響已經超越了地理位置的限制，企業供應鏈面臨著各類型無法預測的突發中斷意外，其所帶來的潛藏危機與毀壞性的嚴重後果常是企業難以預測與想像的。因此，面對供應鏈突發中斷事件風險，企業如何主動採取有效的應變策略來減少重大的損失以及如何展現快速的恢復力已成為業界及學術界熱門關注的課題。有鑑於此，本文探討近十餘年來全球供應鏈中斷風險管理相關文獻及最佳典範實例的危機處理方式進行深度解析，並重新檢視供應鏈流程的脆弱環節，將管理中斷風險策略歸納為供應中斷策略、生產中斷策略、運輸中斷策略、需求中斷策略等四大主要策略、二十二個次要策略以及欲評選層級策略作為減災、整備、應變與復原等四個連續解決方案的行動決策組合，從而歸納建構了一個管理中斷風險之解決方案評選層級策略的決策組合架構圖。
在實證研究方面，本文以特別重視供應鏈發生機率低且高嚴重後果中斷事件的航空製造業作為研究對象。研究結果發現應用直覺模糊熵權重搭配品質屋(HOQ)的中心相關矩陣評價方式，作為管理供應鏈中斷風險之解決方案的多準則決策方法，經專家確認具有不錯的綜合效果；另外我們也發現將專家評選為中、高重要度的次要策略重新歸納成制度、技術、管理、執行等四個策略構面的決策組合優於原四大主要策略的決策組合更適合作為解決方案之行動決策組合(repetoire)。基於此，應用本研究決策組合架構搭配直覺模糊熵權重與相關矩陣之多準則決策方法，可提供有意建立韌性供應鏈的製造業者管理中斷風險評選層級策略作為連續解決方案的最佳決策組合之指導方針與重要參考。

In recent years, the frequent disasters all over the world caused unpredictable disruptions of globalized supply chain and resulted in serious consequences to those companies running the global businesses. Because of this, how enterprises can adopt active and effective response strategies to minimize losses due to broken supply chains, and how they can effectively maintain supply chain resilience, has become an important topic for both industry and the academic researchers. In such view, this article reviewed the research on disruption risk management of global supply chain and made in-depth analysis and learning from best practices in the industry on dealing with disruption risk in the recent decade. This study thus summarized the foregoing literature and best practices in crisis management, this paper attempted establish a hierarchical framework includes four primary strategies of supply disruption, production disruption, transportation disruption, demand disruption；22 secondary strategies；and four solutions of mitigation, readiness, response and recovery. The purpose of this study is to provide the supply-chain owners a decision framework for delivering the planning strategic and contiguous solution to confront disruption risk in global supply chain.
This framework was tested and evaluated on a local aerospace manufacturer which is particularly sensitive to low probability - high consequence disruption risk in supply chain. The study''s findings indicate that application of IFEW with the correlation matrix method to MCDM in dealing with the risk of supply chain disruption yields excellent results, and can provide enterprises wishing to establish a resilient supply chains important guideline in the selection of an optimal decision-making portfolio (ODMP).

中文摘要……………………………………………………………………………I
Abstract…………………………………………………………………………II
誌 謝…………………………………………………………………………III
目 錄…………………………………………………………………………IV
圖目錄…………………………………………………………………………VIII
表目錄……………………………………………………………………………IX
第一章 緒論………………………………………………………………………1
1.1 研究背景與動機……………………………………………………………1
1.1.1 傳統企業應對供應中斷事件……………………………………………2
1.1.2 傳統企業應對營運中斷事件……………………………………………2
1.1.3 傳統企業應對需求突變事件……………………………………………3
1.2 研究目的……………………………………………………………………4
1.3 研究範圍……………………………………………………………………5
1.4 研究流程……………………………………………………………………5
第二章 供應鏈中斷的影響與企業的危機處理方式……………………………8
2.1 中斷災變事件對供應端的影響……………………………………………11
2.1.1 台灣921大地震…………………………………………………………12
2.1.2 日本強震引發海嘯及核災………………………………………………14
2.1.3 泰國洪水久滯未退………………………………………………………15
2.1.4 工廠發生火災……………………………………………………………15
2.1.5 北美卡崔娜颶風強襲……………………………………………………16
2.2 中斷災變事件對生產端的影響……………………………………………17
2.2.1 釣魚島主權爭議…………………………………………………………17
2.2.2 SARS疫情襲捲亞洲………………………………………………………18
2.2.3 日本強震引發海嘯及核災………………………………………………19
2.2.4 泰國洪水久滯未退………………………………………………………20
2.3 中斷災變事件對運輸端的影響……………………………………………21
2.3.1 美國911恐佈攻擊………………………………………………………21
2.3.2 美國西岸封港……………………………………………………………22
2.3.3 冰島火山灰四處散播……………………………………………………24
2.4中斷災變事件對銷售端的影響……………………………………………24
2.4.1 嬌生止痛藥泰諾遭下毒…………………………………………………24
2.4.2 比利時和法國可口可樂中毒……………………………………………24
2.4.3 全球金融海嘯……………………………………………………………25
2.4.4 釣魚島主權爭議…………………………………………………………25
2.4.5 亞洲爆發黑心食品事件…………………………………………………26
2.5 小結…………………………………………………………………………27
第三章 供應鏈中斷風險管理策略探討…………………………………………28
3.1 供應中斷策略………………………………………………………………28
3.1.1 採購政策…………………………………………………………………28
3.1.2 績效衡量…………………………………………………………………29
3.1.3 替代商源資料庫…………………………………………………………30
3.1.4 轉移需求…………………………………………………………………30
3.1.5 協作………………………………………………………………………31
3.1.6 決策支援系統……………………………………………………………31
3.2 生產中斷策略………………………………………………………………32
3.2.1 庫存政策…………………………………………………………………32
3.2.2 需求拉動生產……………………………………………………………33
3.2.3 分散生產基地……………………………………………………………34
3.2.4 彈性產能…………………………………………………………………34
3.2.5 有效溝通…………………………………………………………………35
3.2.6 異地互援…………………………………………………………………36
3.2.7 整合………………………………………………………………………36
3.2.8 標準化……………………………………………………………………37
3.2.9 模組化……………………………………………………………………37
3.3運輸中斷策略………………………………………………………………38
3.3.1 彈性運輸…………………………………………………………………38
3.3.2 平滑運輸…………………………………………………………………38
3.3.3 經濟運輸…………………………………………………………………39
3.4 需求中斷策略………………………………………………………………39
3.4.1 資訊共享…………………………………………………………………39
3.4.2 需求推遲…………………………………………………………………41
3.4.3 動態規劃…………………………………………………………………41
3.4.4 銷售管理…………………………………………………………………42
3.5 小結…………………………………………………………………………42
第四章 災變管理之決策組合……………………………………………………43
4.1 災變管理解決方案探討……………………………………………………43
4.2 具體可實踐策略……………………………………………………………43
4.3 建立評選決策組合架構……………………………………………………46
第五章 驗證與分析………………………………………………………………45
5.1 驗證的研究方法探討………………………………………………………45
5.1.1 層級策略之重要度評價…………………………………………………47
5.1.2 次要策略與解決方案之相關性評價……………………………………49
5.2 研究的驗證方式……………………………………………………………52
5.2.1 研究對象…………………………………………………………………52
5.2.2 專家問卷設計……………………………………………………………52
5.2.3 問卷的信度與效度………………………………………………………53
5.3 評價結果驗證………………………………………………………………54
5.3.1 受訪專家及問卷評價結果………………………………………………54
5.3.2 問卷評價結果之可信度分析……………………………………………55
5.4 評價結果演算分析…………………………………………………………55
5.4.1 層級策略之重要度評價…………………………………………………55
5.4.2 次要策略與解決方案之相關性評價……………………………………57
5.5 小結…………………………………………………………………………69
第六章 研究成果…………………………………………………………………71
6.1 以策略構面作為解決方案的行動決策組合………………………………71
6.1.1 減災方案的行動決策組合………………………………………………72
6.1.2 戰備方案的行動決策組合………………………………………………73
6.1.3 應變方案的行動決策組合………………………………………………73
6.1.4 復原方案的行動決策組合………………………………………………73
6.1.5 綜合方案的行動決策組合………………………………………………74
6.2 以主要策略作為解決方案的行動決策組合………………………………74
6.2.1 減災方案的行動決策組合………………………………………………75
6.2.2 戰備方案的行動決策組合………………………………………………75
6.2.3 應變方案的行動決策組合………………………………………………75
6.2.4 復原方案的行動決策組合………………………………………………75
6.2.5 綜合方案的行動決策組合………………………………………………75
6.3 小結…………………………………………………………………………75
第七章 結論與未來研究建議……………………………………………………78
7.1 研究發現……………………………………………………………………78
7.2 研究限制……………………………………………………………………79
7.3 未來研究方向………………………………………………………………80
參考文獻…………………………………………………………………………81
英文文獻…………………………………………………………………………81
中文文獻…………………………………………………………………………93
附錄一 符號說明…………………………………………………………………94
附錄二 專有名詞對照……………………………………………………………97
附錄三 專家問卷………………………………………………………………102
圖目錄
圖1.1 研究流程圖 6
圖2.1 供應鏈突發中斷的八個階段…………………………………………………8
圖2.2 災變發生的的機率與對企業衝擊的後果…………………………………10
圖2.3 供應鏈突發事件對企業的衝擊……………………………………………11
圖4.1 管理供應鏈中斷風險解決方案評選層級策略之決策組合架構圖…46
圖5.1 品質屋架構圖………………………………………………………………..50
圖5.2 次要策略與解決方案之關係矩陣圖 57
表目錄
表 4.1最佳典範之具體可實踐策略集成 44
表 5.1 語意變數與直覺模糊數的轉換表 52
表 5.2 次要策略評價結果之信度分析 55
表 5.3 次要策略的直覺模糊熵權值表……………………………………56
表 5.4 主要策略的直覺模糊熵權值表………………………………………….....57
表 5.5 解決方案與策略準則之絕對權值及相對權值演算表…………………….59
表 5.6 綜合方案與次要策略之相對權值排序及累積權值重要度評價表…….…60
表 5.7 解決方案之相對權值排序及累積權值重要度評價表…………………..60
表 5.8 減災方案與次要策略之相對權值排序及累積權值重要度評價表……….62
表 5.9 戰備方案與次要策略之相對權值排序及累積權值重要度評價表…….…63
表 5.10 應變方案與次要策略之相對權值排序及累積權值重要度評價表……...64
表 5.11 復原方案與次要策略之相對權值排序及累積權值重要度評價表…....65
表 5.12 解決方案與次要策略列為高、中重要度之相對權值對照表……………66
表 5.13 綜合方案與主要策略之相對權值排序及累積權值重要度評價表……67
表 5.14 減災方案與主要策略之相對權值排序及累積權值重要度評價表……...68
表 5.15 戰備方案與主要策略之相對權值排序及累積權值重要度評價表……...68
表 5.16 應變方案與主要策略之相對權值排序及累積權值重要度評價表……...68
表 5.17 復原方案與主要策略之相對權值排序及累積權值重要度評價表……...69
表 5.18 解決方案與主要策略列為高、中重要度之相對權值對照表……….…...69
表 6.1 次要策略的構面分類表……………………………………………71
表 6.2 策略構面作為管理中斷風險之解決方案的行動決策組合………….…....72
表 6.3 主要策略作為管理中斷風險之解決方案的行動決策組合…………….....74
表 6.4 策略構面作為解決方案行動決策組合的次要策略項數統計表……….....76
表 6.5 主要策略作為解決方案行動決策組合的次要策略項數統計表…….........76
表 6.6 主要策略之無相關次要策略作為解決方案行動決策組合…………….....77

英文文獻
1.Akao, Y. (1990). Quality Function Deployment: Integrating Customer Requirements into Product Design. Productivity Press. Cambridge. MA.
2.Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1), 87–96.
3.Borana, F.E. Gença, S. Kurt, M., &; Akay, D. (2009). A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36(8), 11363–11368.
4.Bouchereau, V., &; Rowlands, H. (2000). Methods and techniques to help quality function deployment (QFD). Benchmarking: An International Journal, 7(1), 8-20.
5.Brindley, C. (2004). Supply Chain Risk. Ashgate Publishing, Aldershot, UK.
6.Caldwell, F. Hunter, R., &; Bace, J. (2002 August). ’Digital Pearl Harbor’ War Game Explores ‘Cyber-terrorism.’ Gartner Research, E-17-6580.
7.Chang, K. H., &; Cheng, C. R. (2013a). A Study of Supply chain Enterprise Risks：Solutions of Sudden Catastrophic Event, 2013 International Conference on Business Expertise &; Ethics, 12(A8), http://w3.ocu.edu.tw/ba/icbee/index.htm.
8.Chang, K. H., &; Cheng, C. R. (2013b). A Study of Supply Chain Management Disruption Risks for Manufactures, The 7th International Conference on Advanced Information Technologies, 103(046), http://ait.inf.cyut.edu.tw/ait.asp.
9.Chang, K. H., &; Cheng, C. R. (2013c). Risk management on the disruption risk of supply chain. The 4th International Asia Conference on Industrial Engineering and Management Innovation, 38(TW-OR014), http://www.ie.ntu.edu.tw/IEMI /program.html.
10.Chang, K. H., &; Cheng, C. R. (2016). Application of Intuitionistic Fuzzy Entropy to Disruption Risk management in Aerospace Supply Chain. Applied Mathematics &; Information Sciences, 10(3), 1-12.
11.Chang, M. S., Tseng, Y. L., &; Chen, J. W. (2007). A scenario planning approach for the flood emergency logistics preparation problem under uncertainty. Transportation Research Part E: Logistics and Transportation Review, 43(6), 737–754.
12.Chen, C. T., Fu, P. C., &; Hung, W. Z. (2013). Appling Interval Linguistic Variables on Project Evaluation of New Product Development. Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation. Springer Science &; Business Media, 171-198.
13.Chongvilaivan, A. (2011). Managing Global Supply Chain Disruptions: Experience from Thailand’s 2011 Flooding, Regional Economic Studies Programme. Institute of Southeast Asian Studies (ISEAS). 30 Heng Mui Keng Terrace. Singapore 119614.
14.Chopra, S., &; Sodhi, M. S. (2004). Managing Risk To Avoid Supply-Chain Breakdown. MIT Sloan Management Review, 53–61.
15.Christopher, M., &; Peck, H. (2004). Building the resilient supply chain. The International Journal of Logistics Management, 15(2), 1–14.
16.Cohen, M. A., &; Kunreuther, H. (2007). Operations Risk Management：Overview of Paul Kleindorfer''s Contributions. Production and Operations Management, 16(5), 525–541.
17.Craft, R. C., &; Leake, C. (2002). The Pareto principle in organizational decision making. Management Decision, 40(8), 729–733.
18.Craighead, C. W., Blackhurst, J., Rungtusanatham, M. J., &; Handfield, R. B. (2007). The severity of supply chain disruptions: design characteristics and mitigation capabilities. Decision Sciences, 38(1), 131–156.
19.Dapiran, P. (1993). Benetton-Global Logistics in Action. International Journal of Physical Distribution and Logistics Management, 23(1), 1–5.
20.Dat, L. Q., Phuong, T. T., Kao, H. P., Chou, S. Y., &; Van Nghia, P. (2015). A new integrated fuzzy QFD approach for market segments evaluation and selection. Applied Mathematical Modelling, 39(13), 3653-3665.
21.de Fátima Cardoso, J., Casarotto Filho, N., &; Miguel, P. A. C. (2015). Application of Quality Function Deployment for the development of an organic product. Food Quality and Preference, 40, 180-190.
22.Deng, Y., &; Chan, F. T. S. (2011). A new fuzzy dempster MCDM method and its application in supplier selection. Expert Systems with Applications, 38(8), 9854–9861.
23.Employing Activity Based Costing and Management Practices Within the Aerospace Industry: Sustaining the Drive for Lean, Boeing Commercial Airplane Group Wichita Division, 1–16.
24.Faisal, M. N. Banwet, D. K., &; Shankar, R. (2006). Supply chain risk mitigation: Modeling the enablers. Business Process Management Journal, 12(4), 535–552.
25.Gau, W. L., &; Buehrer, D. J. (1993). Vague sets. IEEE Transactions on Systems, Man and Cybernetics, 23(2), 610–614.
26.Gunasekaran, A., Patel, C., &; Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International Journal of Operations &; Production Management, 21(1/2), 71–87.
27.Hauser, J. R. (1993), How Puritan-Bennett used the house of quality, Sloan Management Review, 34(3), 61–70.
28.Hauser, J. R., &; Clausing, D. P. (1988 May-June). The House of Quality, Harvard Business review, 63–73.
29.Hendricks, K. B., &; Singhal, V. R. (2005a). An Empirical Analysis of the Effect of Supply Chain Disruptions on Long—run Stock Price Performance and Equity Risk of the Firm, Production and Operations Management, 14(1), 35–52.
30.Hendricks, K. B., &; Singhal, V. R. (2005b). Association Between Supply Chain Glitches and Operating Performance. Management Science, 5l(5), 695–711.
31.Hsieh, Y. C., Lin, N. P., &; Chiu, H. C. (2002). Virtual factory and relationship marketing—a case study of a Taiwan semiconductor manufacturing company. International Journal of Information Management, 22(2), 109–126.
32.Huang, M., Yang, M., Zhang, &; Y. Liu B. (2012). System dynamics modeling -based study of contingent sourcing under supply disruptions. Systems Engineering Procedia, 4, 290–297.
33.Jin, G., Jeong, Y., &; Yoon, B. (2015). Technology-driven roadmaps for identifying new product/market opportunities: Use of text mining and quality function deployment. Advanced Engineering Informatics, 29(1), 126-138.
34.Juttner, U. (2005). Supply Chain Risk Management：Understanding the business requirements from a practitioner perspective. The International Journal of Logistics Management, 16(1), 120–141.
35.Kleindorfer, P. R., &; Saad, G. H. (2005). Managing Disruption Risks in Supply Chains. Production and Operations Management, 14(1), 53–68.
36.Knemeyer, A. M., Zinn, W., &; Eroglu, C. (2009). Proactive Planning for Catastrophic Events in Supply Chains. Journal of Operations Management, 27(2), 141–153.
37.Kuo, Y., Yang, T., &; Huang, G. W. (2008). The use of grey relational analysis in solving multiple attribute decision-making problems. Computers &; Industrial Engineering, 55(1), 80–93.
38.Lam, J. S. L. (2015). Designing a sustainable maritime supply chain: A hybrid QFD–ANP approach. Transportation Research Part E: Logistics and Transportation Review, 78, 70–81.
39.Lan, R., &; Fan, J. L. (2009). A Multi-criteria Decision Making Method on Intuitionistic Fuzzy Sets. Fuzzy Information and Engineering, Springer Berlin Heidelberg, 210-217.
40.Latour, A. (2001 January). Trial by fire：A blaze in Albuquerque sets off major crisis for cell-phone giants-Nokia handles supply shock with aplomb as Ericsson of Sweden gets burned-Was Sisu the difference? The Wall Street Journal, A1.
41.Lawshe, C. H. (1975). A Quantitative Approach to Content Validity. Personnel Psychology, 28(4), 563–575.
42.Lee, H., &; Tang, C. S. (1998). Variability reduction through operations reversal. Management Science, 44(2), 162–172.
43.Li, M., Jin, L., &; Wang, J. (2014). A new MCDM method combining QFD with TOPSIS for knowledge management system selection from the user''s perspective in intuitionistic fuzzy environment. Applied Soft Computing, 21, 28–37.
44.Li, Y., Deng, Y., Chan, F. T., Liu, J., &; Deng, X. (2014). An improved method on group decision making based on interval-valued intuitionistic fuzzy prioritized operators. Applied Mathematical Modelling, 38(9), 2689-2694.
45.Lineback, J. R. (2000 September). Anadigics expects sales drop due to fire disrupting wireless customer. Silicon Strategies Mello, A.
46.Liu, B., Shen, Y., Chen, X., Chen, Y., &; Wang, X. (2014). A partial binary tree DEA-DA cyclic classification model for decision makers in complex multi-attribute large-group interval-valued intuitionistic fuzzy decision-making problems. Information Fusion, 18, 119-130.
47.Liu, W., Xie, D., Liu, Y., &; Liu, X. (2015). Service capability procurement decision in logistics service supply chain: a research under demand updating and quality guarantee. International Journal of Production Research, 53(2), 488–510.
48.Martha, J., &; Subbakrishna, S. (2002). Targeting a Just-In-Case Supply Chain for the Inevitable Next Disaster. Supply Chain Management Review, 6(5), 18–23.
49.Matzler, K., &; Hinterhuber, H. H. (1998). How to make product development projects more successful by integrating Kano''s model of customer satisfaction into quality function deployment. Technovation, 18(1), 25-38.
50.McDonald, C. J. (1998). The evolution of Intel’s Copy EXACTLY! Technology Transfer Method. Intel Technology Journal, 4(1), 1–6.
51.Mitchell, M. L. (1989). The Impact of External Parties on Brand—name Capital：The 1982 Tylenol Poisonings and Subsequent Cases. Economic Inquiry, 27(4), 601–618.
52.Mohammaditabar, D., Ghodsypour, S. H., &; O''Brien, C. (2012). Inventory control system design by integrating inventory classification and policy selection. International Journal of Production Economics, 140(2), 655–659.
53.Muffatto, M. (1999). Introducing a platform strategy in product development. International journal of production economics, 60, 145–153.
54.Nishiguchi, T., &; Beaudet, A. (1998 fall). The Toyota Group and the Aisin Fire. MIT Sloan Management Review, 40(1), 49–59.
55.Oke, A., &; Gopalakrishnan, M. (2009). Managing Disruptions in Supply Chains：A Case Study of a Retail Supply Chain. International Journal of Production Economics, 118(1), 168–174.
56.Park, T., &; Kim, K. J. (1998). Determination of an optimal set of design requirements using house of quality. Journal of operations management, 16(5), 569-581.
57.Peck, H. (2006). Reconciling Supply Chain Vulnerability, Risk and Supply Chain Management, International Journal of Logistics：Research and Applications, 9(2), 127–142.
58.Pramanik, S., &; Mukhopadhyaya, D. (2011). Grey relational analysis based intuitionistic fuzzy multi-criteria group decision-making approach for teacher selection in higher education. International Journal of Computer Applications, 34(10), 21-29.
59.Rai, A., Patnayakuni, R., &; Seth, N. (2006 June). Firm performance impacts of digitally enabled supply chain integration capabilities. MIS quarterly, 30(2), 226–246.
60.Reynolds, B., &; Seeger, M. W. (2005). Crisis and Emergency Risk Communication as an Integrative Model. Journal of Health Communication: International Perspectives, 10(1), 43–55.
61.Rockart, J. F., &; Flannery, L. S. (1983 October). The management of end user computing. Communications of the ACM, 26(10), 776–784.
62.Şahin, R., &; Yiğider, M. (2014). A Multi-criteria neutrosophic group decision making metod based TOPSIS for supplier selection. arXiv preprint arXiv:1412.5077, 1-10.
63.Sawik, T. (2013). Selection of resilient supply portfolio under disruption risks. OMEGA, 41(2), 259–269.
64.Shao, X. F., &; Dong, M. (2012). Supply Disruption and Reactive Strategies in an Assemble- to- Order Supply Chain With Time-Sensitive Demand. IEEE Transactions on Engineering Management, 59(2), 201–212.
65.Sheffi, Y. (2001). Supply Chain Management Under The Threat of International Terrorism. The International Journal of Logistics Management, 12(2), 1–11.
66.Sheffi, Y. (2005a). The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage. Cambridge, MA：The MIT Press.
67.Sheffi, Y. (2005b). Building a Resilient Supply Chain. Harvard Business Review, 1(8), 2–11.
68.Sheffi, Y., &; Rice, J. B. (2005). A Supply Chain View of the Resilient Enterprise. MIT Sloan Management Review, 47(1), 4l–48.
69.Shigeru, M., &; Akao, Y. (1978). Quality Function Deployment: A Company Wide Quality Approach. JUSE Press, Tokyo.
70.Shu, T., Chen, S., Wang, S., &; Lai, K. K. (2014). GBOM-oriented management of production disruption risk and optimization of supply chain construction. Expert Systems with Applications, 41(1), 59–68.
71.Siddique, Z., Rosen, D. W., &; Wang, N. (1998, September). On the applicability of product variety design concepts to automotive platform commonality. In ASME Design Engineering Technical Conferences- Design Theory and Methodology, 98-DETC/DTM-5661, 1–11.
72.Simpson, T. W., Maier, J. R., &; Mistree, F. (1999, September). A product platform concept exploration method for product family design. In ASME Design Theory and Methodology, 9, 1–219.
73.Smock, D. (2002 September). Lucent’s Bright New Idea: Supply Chain Power. Purchasing Magazine.
74.Souza, R., de Goh, M., Kumar, M., &; Chong, J. (2011). Combating Supply Chain Disruptions : Lessons Learned from Japan 2011. The Logistics Institute Asia Pacific, 1–31.
75.Sun, C. C. (2014). Combining grey relation analysis and entropy model for evaluating the operational performance: an empirical study. Quality &; Quantity, 48(3), 1589-1600.
76.Tang, C. S. (2006a). Perspectives in Supply Chain Risk Management. International Journal of Production Economics, 103(2), 45l–488.
77.Tang, C. S. (2006b). Robust strategies for mitigating supply chain disruptions. International Journal of Logistics: Research and Applications, 9(1), 33–45.
78.Tang, C. S., Zimmerman, J. D., &; Nelson, J. I. (2009, December). Managing new product development and supply chain risks: The Boeing 787 case. In Supply Chain Forum: An International Journal, 10(2), 74–86. KEDGE Business School.
79.Temponi, C., Yen, J., &; Tiao, W. A. (1999). House of quality: A fuzzy logic-based requirements analysis. European Journal of Operational Research, 117(2), 340–354.
80.Tombs, M., Henry, M., &; Peter, C. (2004). From research to product using a common development platform. Control engineering practice, 12(4), 503–510.
81.Tomlin, B. (2006). On the value of mitigation and contingency strategies for managing supply chain disruption risks. Management Science, 52(5), 639–657.
82.Treuner F., Hübner D., Baur S., Wagner S. M., &; Zürich ETH, (2014). A survey of Disruptions in Aviation and Aerospace supply chains and recommendations for increasing resilience. Supply Chain Management, 14(3), 7–12.
83.Vlachos, I. K., &; Sergiadis, G. D. (2007). Intuitionistic fuzzy information- Applications to pattern recognition. Pattern Recognition Letters, 28(2), 197–206.
84.Wagner, S. M., &; Bode, C. (2006). An Empirical Investigation into Supply Chain Vulnerability. Journal of Purchasing and Supply Management, 12(6), 301–312.
85.Wakolbinger, T., &; Cruz, J. M. (2011). Supply chain disruption risk management through strategic information acquisition and sharing and risk-sharing contracts. International Journal of Production Research, 49(13), 4063–4084.
86.Wan, S. P., &; Li, D. F. (2014). Atanassov''s intuitionistic fuzzy programming method for heterogeneous multiattribute group decision making with Atanassov''s intuitionistic fuzzy truth degrees. Fuzzy Systems, IEEE Transactions on, 22(2), 300-312.
87.Wang, C. H. (2015). Using quality function deployment to conduct vendor assessment and supplier recommendation for business-intelligence systems. Computers &; Industrial Engineering, 84, 24-31.
88.Wang, J. Q., Nie, R. R., Zhang, H. Y., &; Chen, X. H. (2013). Intuitionistic fuzzy multi-criteria decision-making method based on evidential reasoning. Applied Soft Computing, 13(4), 1823-1831.
89.Wemmerlöv, U. (1984). Assemble-to-order manufacturing: Implications for materials management. Journal of Operations Management, 4(4), 347–368.
90.Whittaker, H. (1979). Comprehensive Emergency Management- A Governor’s Guide. National Governors’ Association Center for Policy Research. U.S. Defense Civil Preparedness Agency, 7–38.
91.Wilson, M. C. (2007). The impact of transportation disruptions on supply chain performance. Transportation Research Part E, 43(4), 295–320.
92.Wu, J. Z., &; Zhang, Q. (2011). Multicriteria decision making method based on intuitionistic fuzzy weighted entropy. Expert Systems with Applications, 38(1), 916-922.
93.Xu, Z., &; Yager, R. R. (2008). Dynamic intuitionistic fuzzy multi-attribute decision making. International Journal of Approximate Reasoning, 48(1), 246–262.
94.Yaghmaei, F. (2003 Spring). Content validity and its estimation. Journal of medical education, 3(1), 25–27.
95.Yan, H. B., &; Ma, T. (2015). A group decision-making approach to uncertain quality function deployment based on fuzzy preference relation and fuzzy majority. European Journal of Operational Research, 241(3), 815–829.
96.Yu, G., Arguello, M., Song, G., McCowan, S., &; White, A. (2003). A new era for crew recovery at Continental Airlines. Interfaces, 33(1), 5–22.
97.Yu, S., Yang, Q., Tao, J., &; Xu, X. (2015). Incorporating Quality Function Deployment with modularity for the end-of-life of a product family. Journal of Cleaner Production, 87, 423-430.
98.Yu, Z., Yan, H., &; Cheng, T. C. E. (2001). Benefits of information sharing with supply chain partnerships. Industrial Management &; Data Systems 101(3), 114–121.
99.Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8(3), 338–353.
100.Zhang, F., Yang, M., &; Liu, W. (2014). Using integrated quality function deployment and theory of innovation problem solving approach for ergonomic product design. Computers &; Industrial Engineering, 76, 60-74.
101.Zhang, N., Cheng, X., &; Liu, C. (2010). Cooperating Emergency Strategies between Enterprises under Supply Chain Disruptions. Supply Chain Management, 6, 4276–4282.
102.Zhang, S. F., &; Liu, S. Y. (2011). A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection. Expert Systems with Applications, 38(9), 11401–11405.
103.Zinn, W., &; Bowersox, D. J. (1988). Planning physical distribution with the principle of postponement. Journal of Business Logistics, 9(2), 117–137.
104.Zsidisin, G. A. (2003). Managerial Perceptions of Supply Risk. The Journal of Supply Chain Management, 39(1), 14–25.
中文文獻
1.施友元(2011)，斷鏈效應對台、中、韓之經濟影響評估與因應對策－以關鍵電子零組件與設備為例，經濟研究，第12期, 第289–325頁。
2.張寧及劉春林(2011年3月)，應對供應鏈突發事件風險的企業協作應急策略，商業經濟與管理，第233期第3卷，第17–23頁。
3.許輔(2010年12月)，介紹歐盟良好食品追溯規範， 2010 年重要人畜共通傳染病國際研討會紀實，臺大農業推廣通訊雙月刊，第84期，第6–12頁。
4.陳竹亭(2015)，起雲劑 vs. 塑化劑，科學. Online - 科技部高瞻自然科學教學資源平台。 http://highscope.ch.ntu.edu.tw/wordpress/?p=27917
5.陳澄河(2011年7月)，起雲劑與塑化劑，科學發展，第463期，第48–55頁。
6.黃弘君及黃新發，現代的危機~環境荷爾蒙，健康管理的新思維，台灣酸痛關懷協會。 http://www.backpain.com.tw/webpage.php?div=div_4&; wid=4_86
7.葉名倉(2008)，順丁烯二酸，科學. Online - 科技部高瞻自然科學教學資源平台。 http://highscope.ch.ntu.edu.tw/wordpress/?p=3380
8.葉神丑(2015)，食品追溯追蹤開創食安新紀元，中衛發展中心，中衛報告，第32期, 第1–9頁。