Fuzzy Multiple Criteria Decision Making Model for Risk Assessment of Enterprise Overseas Projects Investment

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姓名

呂世通(Shih-Tong Lu) 查詢紙本館藏

畢業系所

企業管理學系

論文名稱

(Fuzzy Multiple Criteria Decision Making Model for Risk Assessment of Enterprise Overseas Projects Investment)

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摘要(中)

在全球化的大趨勢下企業為了謀求永續發展，逐步開拓海外的機會是提高國際競爭力的必然選擇，而開拓海外的機會，可以由一些海外專案投資開始，例如，在海外設立工廠並遷移一部分的生產線，或者發現國外一些有利的資源而可以進行一項投資專案。然而，海外專案投資必須面對與國內不同的經濟條件和風險因素。因此，選擇合適的海外專案投資國家，應是海外專案投資成功的第一步。而在實施海外專案投資之前，必須進行風險評估過程，才能有助於該項專案投資成功的機會。本研究運用Fuzzy LinPreRa 和Fuzzy VIKOR方法，建立了以風險分析與評價為基礎的混合式模糊多準則決策(Fuzzy MCDM) 模型，來分析其風險因素影響程度和選擇合適的海外投資國家。本研究根據某科技公司的案例模擬，結果顯示5項風險層面的相對影響排序是「財務條件面風險」、「政治社會面風險」、「市場特性面風險」、「總體經濟面風險」和「營運作業面風險」;對於20項風險因素而言，「營業收入不如預期」在所有風險因素相對影響最大，其次是「投資國政府態度轉變」，第三名為「市場條件不穩定」。這結果反映出，想要投資海外專案的企業應具備一定的財務能力會比較穩當，並以獲得投資國較好的融資條件和租稅優惠為較可能的誘因，但也相當擔心投資國政府的政策轉彎，市場狀況不穩定而造成的營收下降是一大風險變數。本研究所建立的混合式Fuzzy MCDM模式使得風險評估方法比傳統的統計方法易於實務上之應用外，也具有相當可靠的理論基礎，並嘗試將一般用於正向值的績效評估之Fuzzy VIKOR方法應用於負向值的風險評估，期望本研究所建立的模式能協助有意進行海外專案投資的企業，提高決策的有效性。

摘要(英)

Under the trend of globalization, enterprises, in order to seek sustainable development of their business, gradually explore overseas opportunities, is the inevitable choice for them to improve the international competitiveness. Explore overseas opportunities can start projects with some overseas investments. For example, set up the factory overseas and move a certain production line, or found some advantageous resources overseas can make an investment project. However, overseas investment must face different economic conditions and risk factors from domestic. Therefore, selecting the appropriate country for overseas project investment (OPI) should be the first step to success overseas investment and it is necessary to perform the risk assessment process before implementing an OPI. This paper constructs a hybrid fuzzy multiple criteria decision making (Fuzzy MCDM) model to analyze and select an appropriate overseas investment location based on the risk analysis and evaluation by the Fuzzy LinPreRa and Fuzzy VIKOR approach. According to the case simulation of a technology company, the results show that the ranking of the relative impact of 5 risk dimension is “Financial risk”, “Politics and social risk”, “Market characteristics risk”, “Macroeconomic risk” and “Operational risk”. For the 20 risk factors, “Operational revenue underperforming” have the greatest impact among all risk factors, the “Host government attitude adjusting” is the second impact of all risk factors and “Market conditions instability” ranking at all risk of the third. This result fully reflects that enterprises that want to invest in overseas projects should have a basic level of financial capacity and are likely to receive better financing conditions and tax concessions from investment countries. The hybrid Fuzzy MCDM model established in this research makes the risk assessment method easier to practice than the traditional statistical method, and also has a fairly reliable theoretical basis. Besides, attempting to apply the Fuzzy VIKOR approach, which is generally used for positive value performance evaluation, to risk assessment of negative value. It is expected that the model established in this study can assist enterprises interested in investing in overseas projects to improve the effectiveness of decision making.

關鍵字(中)

★ 海外專案投資
★ 風險評估
★ 投資國選擇
★ 模糊語意偏好關係法
★ 模糊多準則妥協解排序法

關鍵字(英)

★ Overseas Project Investment
★ Risk Assessment
★ Investment Country Selection
★ Fuzzy LinPreRa
★ Fuzzy VIKOR

論文目次

中文摘要 i
Abstract ii
謝誌 iii
Chapter 1 Introduction 1
1-1 Background and motivation 1
1-2 Research questions and purposes 2
1-3 Organization of the dissertation 4
Chapter 2 Literature Review 6
2-1 Risk 6
2-2 Risk of overseas project investment 7
2-3 Identification risk of overseas project investment 8
2-4 Brief descriptions for risk dimensions and factors 9
Chapter 3 Research Methodology 15
3-1 Fuzzy numbers 16
3-2 Linguistic variables 17
3-3 Defuzzification 20
3-4 Consistent Fuzzy Preference Relation (CFPR) 21
3-4-1 Multiplication preference relation 21
3-4-2 Fuzzy preference relation 22
3-4-3 Consistent fuzzy preference relation matrix 22
3-5 Fuzzy linguistic preference relation (Fuzzy LinPreRa) 23
3-6 Determination of aggregative weights 25
3-7 Fuzzy VIKOR 25
Chapter4 Case Simulation 31
4-1 Relative impact for risk dimensions and risk factors 32
4-2 Ranking for the comprehensive risk degree of investment countries 44
Chapter 5 Conclusion 50
5-1 Suggestions and management implications 51
5-2 Research limitations and further research 53
References 55
Appendix Questionnaire 61

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指導教授

張東生(Dong-Shang Chang)

審核日期

2018-1-11

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