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論文名稱 Title |
基於奇異空間之併購預測支援模型 Singular-Space-Based Support model for M&A Prediction |
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系所名稱 Department |
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畢業學年期 Year, semester |
語文別 Language |
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學位類別 Degree |
頁數 Number of pages |
75 |
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研究生 Author |
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指導教授 Advisor |
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召集委員 Convenor |
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口試委員 Advisory Committee |
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口試日期 Date of Exam |
2018-07-27 |
繳交日期 Date of Submission |
2018-07-24 |
關鍵字 Keywords |
併購、企業環境分析、併購策略、文字探勘、奇異值分解、交叉驗證、決策支援模型 Cross verification, SVD, Decision model, Singular Space, M&A, Business environmental analysis, Text mining, M&A strategy |
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統計 Statistics |
本論文已被瀏覽 5979 次,被下載 2 次 The thesis/dissertation has been browsed 5979 times, has been downloaded 2 times. |
中文摘要 |
自1980年開始,在全球競爭環境下,併購漸漸的被企業重視。併購是為了增加企業自身的核心能力所採用的策略之一,企業併購活動如同滾雪球般的發展。然而數據顯示併購案例逐年上升但失敗的機率卻高達70%~90%。 併購失敗的原因可能存在企業的內部與外部中,許多文獻指出要增加併購成功率必須要選擇一個與自身公司策略符合的目標。研究指出過往併購案太過於依賴財務指標,而忽略了其他非財務指標(例如文化、科技、環境等等),這導致了財務指標決定了大部分的併購案。有鑑於此,本文定義了企業環境指標,我們希望透過加入非財務指標能對預測目標有所改善,並且證明非財務指標對於併購目標選擇的影響。 然而我們希望能夠將併購準確性提升,我們採用SVD幫助我們去除雜訊值並且降維,結果顯示透過此方法準確率因此而改善。而當SVD對於併購有所幫助時,我們試圖解釋對於併購那些是更為重要的因素在奇異空間中。 我們分析與歸納了本次實驗的管理意涵。最後我們找出對於併購較為重要因素,這表示在併購決策中這些因素以及因素之間的關係應該要被重視 |
Abstract |
Since 1980, in the global competitive environment, M&A has gradually been valued by enterprises. M&A is one of the strategies used to increase the core competence of enterprises. M&A activities are like snowball development. However, data shows that M&A cases have risen year by year, but the failure is as high as 70% to 90%. The reasons for the failure of M&A may exist in the internal and external environment of the enterprise. Many researches pointed out that to increase the success rate of M&A, it is necessary to choose the target that is consistent with its own company strategy. Research indicates that past mergers and acquisitions are too dependent on financial variables while ignoring other non-financial variables (i.e. culture, technology, environment) which led to financial variables that determine most of the mergers and acquisitions. In view of this, this paper defines the business environmental variables. When we add the business environmental variables to the financial variables, we calculate the scores of real M&A cases. We hope that by adding non-financial variables, we can improve the score of the forecast target and demonstrate the impact of non-financial variables on M&A target selection. In order to reduce the high failure rate of mergers and acquisitions, we use SVD to help us remove the noise value and reduce the dimension. The results show that the method affects the results of the merger. The study analyzed the cases of mergers and acquisitions in Taiwan from 2014 to 2016 and verified them through leave-one-out cross verification. And when SVD is helpful for mergers and acquisitions, we try to explain the factors that are more important for mergers and acquisitions in the singular space. We analyzed and summarized the managerial implications of this experiment. Finally, we identify the more important factors for M&A, which means that the relationship between these factors and factors in M&A decisions should be taken seriously. |
目次 Table of Contents |
論文審定書 i 誌謝 ii 摘要 iii Abstract iv TABLE OF CONTENTS vi LIST OF FIGURES viii LIST OF TABLES ix CHAPTER 1 Introduction 1 1.1 Background and Objective of the research 1 1.2 The goal and purpose of research 5 1.3 Organization of the research 6 CHAPTER 2 Literature Review 7 2.1 The step of M&A 7 2.2 The type of M&A 8 2.3 Business Environmental Indicators 11 2.4 Financial Variables 16 2.5 SVD 19 CHAPTER 3 Research Procedure 21 Step 1:Collect the M&A deal cases and data preprocess 23 Step 2:Collect the financial indicators 24 Step 3:Collect the business environmental indicators through annual reports 25 Step 4:Examine the impact of the business environmental indicators 28 Step 5:Investigate the impact of SVD 29 CHAPTER 4 Experiments and Results 31 4.1 Experiment Design 31 4.2 Feasibility Evaluation with business environmental variables 36 4.3 Feasibility Evaluation on SVD Applications 37 4.4 Managerial Implications on SVD Applications 43 CHAPTER 5 Conclusions 52 5.1 Concluding Remarks 52 5.2 Research Limitations 53 5.3 Future work 53 References 55 |
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