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研究生：	蕭博文 Hsiao, Bo-Wen
論文名稱：	以混合多評準決策模式建構網通產品製造商回流或境外生產之選址評估模式 A Hybrid-MCDM Based Analytic Framework for Re-shoring or Off shoring Site Selections A Hybrid-MCDM Based Analytic Framework for Re-shoring or Off-shoring Site Selections of a Networking Product Manufacturer
指導教授：	黃啟祐 Huang, Chi-Yo
學位類別：	碩士 Master
系所名稱：	工業教育學系 Department of Industrial Education
論文出版年：	2015
畢業學年度：	103
語文別：	英文
論文頁數：	139
中文關鍵詞：	全球化、約略集合理論、主成份分析方法、決策實驗室網路流程分析、決策試驗與實驗評估法、多準則決策、回流、境外生產
英文關鍵詞：	Re-Shoring
論文種類：	學術論文
相關次數：	點閱：136 下載：0
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摘要
在全球化的時代，企業運用世界各地的人才、技術與其他資源來以維繫甚至提昇競爭優勢。因此，大多數國際企業（尤其是資訊科技製造商）均持續積極探索最適合的國內外地點製造、銷售、行銷、研發、導入當地人力並執行適當的全球財務策略，以求獲利最大化。唯資訊科技產品海外生產活動存在眾多問題。工程之全球分工增加設計協調與物流的複雜度，部分區域因缺乏設計、生產流程、品質管理系統等深度知識，使企業產品品質低落。另，近年來開發中國家之工資持續調昇，因此，部分企業公司開始考慮生產活動回流母國營運。雖然上述議題非常重要，但鮮有相關研究。為了解決此問題，本研究致力定義一混合多準則決策模式。本研究要先導入主成分分析將各準則歸入適當構面，其次，本研究利用決策試驗實驗評估法 (Decision Making Trial and Evaluation Laboratory, DEMATEL)訂定準則與構面間之影響關係。再透過決策實驗式網路流程分析（DEMATEL base Network Process, DNP）推導對應於準則與構面的權重，並使用VIKOR方法評估個可行方案後，使用約略集合理論(Rough Set Theory, RST)找出選擇最佳生產地點之決策規則。本研究將透過位於台灣之全球主要網通產品(路由器)製造商於全球選址問題之實證研究評估分析架構之可行性，實證研究將評估台灣與主要新興國家含巴西、俄羅斯、印度、中國(Brazil, China, Russia, India, BRIC)，本研究提出之分析架構將可作為全球化企業評估最佳生產位址之用，本研究結果亦可作為網通產品製造商訂定全球營運策略的基礎。
本研究結果顯示，最受到網通產品製造商青睞的國家依序為台灣、中國和巴西。這也就說明了，對網通產品製造商(尤其是台灣的廠商)而言，回流到台灣為最佳策略，而在中國或巴西生產則為次佳的決策。

關鍵字:全球化、境外生產、回流、多準則決策、決策試驗與實驗評估法、決策實驗室網路流程分析、主成份分析方法、VIKOR、約略集合理論。

Abstract
In the era of globalization, firms started to tapping into global pools of talent, technologies and other resources to sustain or even enhance the competences and thus, competitiveness. Therefore, the majority of international companies in general, and information technology manufacturers in special, are aggressively and continuously explore to the most appropriate site for optimize the business operations, no matter from aspects of manufacturing, sales and marketing, human resources management, research and development, as well as finance management. However, offshoring of IT products have several problems. Globalized the engineering functions increase the complexity of design coordination and logistics. Further, moving design and production activities into regions with less knowledge depth regarding design, manufacturing processes, quality management system, etc. always affects a firm’s capability ability to produce reliable products. Further, due to the rising labor costs of developing countries, firms are considering re-shoring to move manufacturing back to the country of its parent company. Albeit the above mentioned issues are very important, very few researches are available. To resolve this issue, the author aims to define a hybrid multiple criteria decision making framework. Therefore, the principle component analysis (PCA) will first be introduced to classify the criteria into corresponding perspective. The influence relationship between criteria will be derived by using the Decision Making Trial and Evaluation Laboratory (DEMATEL). The DEMATEL base Network Process (DNP) will be introduced to derive the weight being associated with each criterion. An empirical study based on the world’s leading Taiwanese networking router product manufacturers’ globalization site selection problems will be used for evaluating the feasibility of the proposed analytic framework. Finally, the competence of Taiwan and the major emerging economies, Brazil, China, Russia, India (BRIC) will be evaluated by using the VIKOR method. Then, based on the result of VIKOR, the Rough Set Theory (RST) will be introduced for deriving the decision rules being corresponding to the decision variables for the optimal manufacturing site. The proposed analytic framework can be used for evaluating the best place to locate the manufacturing facilities of a globalized firm. The analytic results can also serve as the basis for the networking product manufacturers’ globalization strategy.
The result of this research shows that the top three attractive candidate countries in order are Taiwan, China and Brazil which means that decision makers, who work in network product manufacturers, now prefer to re-shore to Taiwan, or still off-shoring to China or Brazil.

Keywords: Globalization, Offshoring, Re-Shoring, Multiple Criteria Decision Making. Decision Making Trial and Evaluation Laboratory (DEMATEL), DEMATEL base Network Process (DNP), Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Rough Set Theory (RST).

Table of Contents
中文摘要    II
Abstract    III
List of Table    VII
List of Figure    IX
Chapter 1 Introcustion    1
1.1 Research Background and Motives    3
1.2 Research Purposes    4
1.3 Research Scope and Structure    5
1.4 Research Process    7
1.5 Research Limitations    9
1.6 Thesis structure    9
Chapter 2 Literature Review    11
2.1 Globalization    11
2.2 Re-shoring & Off-shoring    17
2.3 Global Manufacturing    18
2.4 SiteSelection    22
Chapter 3 Methodology    ..27
3.1 Modified Delphi Technique    27
3.2 Principal component analysis (PCA)    29
3.3 The DEMATEL Method    32
3.4 The DEMATEL base Network Process (DNP)    35
3.5 Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR)     40
3.6 Rough Set Theory (RST)     43
Chapter 4 emperical study    51
4.1 Criteria Definition by Modified Delphi Method    52
4.2 Empirical Study Results Based on Opinions by Middle Level Managers    53
4.3 Calculate the weight of perspective of site selection    63
4.4 Choose the preference scheme by VIKOR technology    67
4.5 Rough Set Theory    73
Chapter 5 Discussion    93
5.1 PCA result base on experts’ opinions    93
5.2 Dematel and DNP result    94
5.3 The advantage statement of Candidate countries implication based on compromise solutions by VIKOR    96
5.4 Using rough set theory to find out the decision rules of off-shoring or re-shore to the candidate countries based on the result of VIKOR    99
5.5 Strategies to Improve the Taiwan Site    102
Chapter 6 Conclusion    103
Reference    105





List of Tables
Table 1 The perspectives/criteria description list of site-selection factors for company    25
Table 2 PRINCIPLE FACTOR LOADING    31
Table 4-1 Questionnaire Collected which Experts' Background    52
Table 4-1-1 Questionnaire Collected of Experts' opinion about site selection    53
Table 4-2-1 Principal component Analysis    55
Table 4-2-2 The influence-Relation Matrix t of the Dimensions    56
Table 4-2-3 Effect Matrix (Criteria)    56
Table 4-2-4 Net correlation effect (dominat) matrix    57
Table 4-2-5 The influence-Relation Matrix t of The Cost Perspective    58
Table 4-2-6 Effect Table (cost-criteria)    58
Table 4-2-7 The Influence-Relation Matrix t of the Resources perspective    59
Table 4-2-8 Effect Table (resources-criteria)    59
Table 4-2-9 The Influence-Relation Matrix t of the government policies and laws perspective    60
Table 4-2-10 Effect Table (government policies and laws -criteria)    60
Table 4-2-11 The Influence-Relation Matrix t of risk perspective    61
Table 4-2-12 Effect Table (risk -criteria)    61
Table 4-2-13 The Influence-Relation Matrix t of market perspective    62
Table 4-2-14 Effect Table (market -criteria)    63
Table 4-3-1 The relativ weight of correlation matrix    65
Table 4-3-2 Un-weighted super matrix of site selection factors    66
Table 4-3-3 Weighted super matrix    66
Table 4-3-4 The limit super matrix    67
Table 4-3-5 The optimal weight    67
Table 4-4-1 The average score of each scheme    71
Table 4-4-2 Weighted score of each scheme    71
Table 4-4-3 Q_VK table in different v (the satisfaction of decision makers)    72
Table 4-4-4 The VSI in v=0.5 and Rank    72
Table 4-4-5 DMSI and average score of each scheme in v=0.5    72
Table 4-5-1 Attricbute specifivation for the personal analysis    75
Table 4-5-2 The Approximation of Five Classes    77
Table 4-5-3 The Frequency of Every Attribute    78
Table 4-5-4 The Decision Table    80
Table 4-5-5 Validation of Candidate Rules    88
Table 4-5-6 Rules being derived corresponding to the decision attribute 1    89
Table 4-5-7 Rules being derived corresponding to the decision attribute 2    89
Table 4-5-8 Rules being derived corresponding to the decision attribute 3    90
Table 4-5-9 Rules being derived corresponding to the decision attribute 5    90
Table 4-5-10 Rules being derived corresponding to the decision attribute 7    90




List of Figures
Fig. 1-1 Flow chart of research framework    6
Fig. 1-2 Flow Chart of this Study    8
Fig. 2-1 An example of the directed graph    33
Fig. 2-2 The control hierarchy    37
Fig. 2-3 Connections in a network    38
Fig. 2-4 A diagram of ideal and compromise solution    41
Fig. 4-2-1 The Total Dimension Influence Diagram    57
Fig. 4-2-2 Causal Relationship Structure of Total Dimension Influence Diagram    57
Fig. 4-2-3 Network structure of cost perspective    58
Fig. 4-2-4 Network structure of resources perspective    59
Fig. 4-2-5 Network structure of government policies and laws perspective    60
Fig. 4-2-6 Network structure of risk perspective    62
Fig. 4-2-7 Network structure of market perspective    63
Fig. 4-4-1 The competence of developing countries analysis    73
Fig. 4-5-1 Decision flow graph for rule-set of decision class 1    91
Fig. 4-5-2 Decision flow graph for rule-set of decision class 2    91
Fig. 4-5-3 Decision flow graph for rule-set of decision class 3    92
Fig. 4-5-4 Decision flow graph for rule-set of decision class 5    92
Fig. 4-5-5 Decision flow graph for rule-set of decision class 7    92
                                

References
GLOBALISATION AND GLOBAL TRANSFORMATIONS IN THE 21ST CENTURY. International Journal of Academic Research 5(6): 46.
Tate, W. L., Ellram, L. M., Schoenherr, T., & Petersen, K. J. (2014). Global competitive conditions driving the manufacturing location decision. Business Horizons, 57(3), 381-390.
Wahlen, J. R. (2013). Bringing back jobs: the factors that influence decisions to offshore and reshore jobs back to the US.
Sarder, M. D., Miller, C., & ZIAUL, A. (2014, January). Understanding the Reshoring Decision-Making Process Using AHP Approach. In Proceedings of the 2014 Industrial and Systems Engineering Research Conference. Downloaded from XCDsystem. com. August (Vol. 12).
Garza, F. A. (2013). International Business Locations: A Framework and Model for Entrepreneurial Reshoring. ACADEMY OF INTERNATIONAL BUSINESS–US NORTH EAST CHAPTER OCTOBER 11–OCTOBER 12, 2013, 61.
Freidman, T. (2005). The world is flat. New York: Farrar, Straus and Giroux.
Setili, A. (2014). The Agility Advantage: How to Identify and Act on Opportunities in a Fast-Changing World. John Wiley & Sons.
Cowell, M., & Provo, J. (2015). 5. Reshoring and the manufacturing moment. Handbook of Manufacturing Industries in the World Economy, 71.
Adler, M. and E. Ziglio (1996). Gazing into the oracle: the Delphi method and its application to social policy and public health, Jessica Kingsley Publishers.
Armon, K., T. Stephenson, R. MacFaul, P. Eccleston and U. Werneke (2001). An evidence and consensus based guideline for acute diarrhoea management. Archives of Disease in Childhood 85(2): 132-142.
Behrens, A., J. J. Doyle, L. Stern, R. S. Chuck, P. J. McDonnell, D. T. Azar, H. S. Dua, M. Hom, P. M. Karpecki and P. R. Laibson (2006). Dysfunctional tear syndrome: a Delphi approach to treatment recommendations. Cornea 25(8): 900-907.
Carmel, E. and P. Tjia (2005). Offshoring Information Technology: Sourcing and Outsourcing to a Global Workforce, Cambridge University Press.
Carnes, D., B. Mullinger and M. Underwood (2010). Defining adverse events in manual therapies: a modified Delphi consensus study. Manual therapy 15(1): 2-6.
Chakravarti, A., B. Vasanta, A. Krishnan and R. Dubash (1998). Modified Delphi methodology for technology forecasting case study of electronics and information technology in India. Technological Forecasting and Social Change 58(1): 155-165.
Clayton, M. J. (1997). Delphi: a technique to harness expert opinion for critical decision‐making tasks in education. Educational Psychology 17(4): 373-386.
Ellram, L. M. (2013). Offshoring, Reshoring and the Manufacturing Location Decision." Journal of Supply Chain Management 49(2): 3-5.
Fine, C. (2013). Intelli‐Sourcing to Replace Offshoring as Supply Chain Transparency Increases. Journal of Supply Chain Management 49(2): 6-7.
Gordon, T. J. (1994). The delphi method. Futures research methodology: 1-33.
Hill, W. (2013). International Business: Competing in the Global Marketplace. New York, N.Y., McGraw Hill.
Jeste, D. V., M. Ardelt, D. Blazer, H. C. Kraemer, G. Vaillant and T. W. Meeks (2010). Expert consensus on characteristics of wisdom: A Delphi method study. The Gerontologist 50(5): 668-680.
Knol, A. B., P. Slottje, J. P. van der Sluijs and E. Lebret (2010). The use of expert elicitation in environmental health impact assessment: a seven step procedure. Environmental Health 9(1): 19.
Opricovic, S. and G. H. Tzeng (2002). Multicriteria planning of post-earthquake sustainable reconstruction. Computer-Aided Civil and Infrastructure Engineering 17(3): 211-220.
Opricovic, S. and G. H. Tzeng (2003). Defuzzification within a multicriteria decision model. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems 11(5): 635-652.
Opricovic, S. and G. H. Tzeng (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research 156(2): 445-455.
Opricovic, S. and G. H. Tzeng (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research 178(2): 514-529.
Tzeng, G.-H., C.-W. Lin and S. Opricovic (2005). Multi-criteria analysis of alternative-fuel buses for public transportation. Energy Policy 33(11): 1373-1383.
Tzeng, G.-H., M.-H. Teng, J.-J. Chen and S. Opricovic (2002). Multicriteria selection for a restaurant location in Taipei. International Journal of Hospitality Management 21(2): 171-187.
Tzeng, G.-H., S.-H. Tsaur, Y.-D. Laiw and S. Opricovic (2002). Multicriteria analysis of environmental quality in Taipei: public preferences and improvement strategies. Journal of Environmental Management 65(2): 109-120.
Woods, D. and T. Mattern (2006). Enterprise SOA: Designing IT for Business Innovation, O'Reilly Media.
Yu, P. L. (1973). A class of solutions for group decision problems. Management Science (pre-1986) 19(8): 936.
Zeleny, M. (1982). Multiple Criteria Decision Making. McGraw-Hill. New York.
Carlson, C. (2012). Effective FMEAs: Achieving Safe, Reliable, and Economical Products and Processes using Failure Mode and Effects Analysis, Wiley.
Ellram, L. M. (2013). Offshoring, Reshoring and the Manufacturing Location Decision. Journal of Supply Chain Management 49(2): 3-5.
Fine, C. (2013). Intelli‐Sourcing to Replace Offshoring as Supply Chain Transparency Increases. Journal of Supply Chain Management 49(2): 6-7.
Hill, W. (2013). International Business: Competing in the Global Marketplace. New York, N.Y., McGraw Hill.
Woods, D. and T. Mattern (2006). Enterprise SOA: Designing IT for Business Innovation, O'Reilly Media.
Ellram, L. M. (2013). Offshoring, Reshoring and the Manufacturing Location Decision. Journal of Supply Chain Management 49(2): 3-5.
Fine, C. (2013). Intelli‐Sourcing to Replace Offshoring as Supply Chain Transparency Increases. Journal of Supply Chain Management 49(2): 6-7.
Carlson, C. (2012). Effective FMEAs: Achieving Safe, Reliable, and Economical Products and Processes using Failure Mode and Effects Analysis, Wiley.
Carmel, E. and P. Tjia (2005). Offshoring Information Technology: Sourcing and Outsourcing to a Global Workforce, Cambridge University Press.
Ellram, L. M. (2013). Offshoring, Reshoring and the Manufacturing Location Decision. Journal of Supply Chain Management 49(2): 3-5.
Fine, C. (2013). Intelli‐Sourcing to Replace Offshoring as Supply Chain Transparency Increases. Journal of Supply Chain Management 49(2): 6-7.
Ellram, L. M. (2013). Offshoring, Reshoring and the Manufacturing Location Decision. Journal of Supply Chain Management 49(2): 3-5.
Gordon, T. J. (1994). The delphi method. Futures research methodology: 1-33.
Hill, C. W. and A. K. Jain (2007). International business: Competing in the global marketplace, McGraw-Hill/Irwin New York, NY.
Knol, A. B., P. Slottje, J. P. van der Sluijs and E. Lebret (2010). The use of expert elicitation in environmental health impact assessment: a seven step procedure.Environmental Health 9(1): 19.
Walczak, B., & Massart, D. L. (1999). Rough set theory, Chemometrics and Intelligent Laboratory Systems, 47(1), 1-16.
Komorowski, J., Pawlak, Z., Polkowski, L., & Skowron, A. (1999). Rough sets: A tutorial. Rough fuzzy hybridization: A new trend in decision-making, 3-98.
Shyng, J. Y., Wang, F. K., Tzeng, G. H., & Wu, K. S. (2007). Rough set theory in analyzing the attributes of combination values for the insurance market.Expert Systems with Applications, 32(1), 56-64.
Wang, C. H., Chin, Y. C., & Tzeng, G. H. (2010). Mining the R&D innovation performance processes for high-tech firms based on rough set theory.Technovation, 30(7), 447-458.
Liou, J. J., Yen, L., & Tzeng, G. H. (2010). Using decision rules to achieve mass customization of airline services. European Journal of Operational Research, 205(3), 680-686.
Shen, K. Y., & Tzeng, G. H. (2015). A new approach and insightful financial diagnoses for the IT industry based on a hybrid MADM model. Knowledge-Based Systems.

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