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系統識別號 U0026-0202201517143900
論文名稱(中文) Bankruptcy Prediction Model for U.S Telecommunication Network Providers: Study of Financial Data
論文名稱(英文) Bankruptcy Prediction Model for U.S Telecommunication Network Providers: Study of Financial Data
校院名稱 成功大學
系所名稱(中) 國際經營管理研究所碩士班
系所名稱(英) Institute of International Management (IIMBA--Master)
學年度 103
學期 1
出版年 104
研究生(中文) 馬山杰
研究生(英文) Enkhbold Baasanjav
學號 RA6027162
學位類別 碩士
語文別 英文
論文頁數 50頁
口試委員 指導教授-楊曉瑩
召集委員-王鈿
口試委員-謝惠璟
口試委員-張巍勳
中文關鍵字 none 
英文關鍵字 Binary logistic regression  Binary quantile regression  Bankruptcy prediction  Telecommunication carriers 
學科別分類
中文摘要 none
英文摘要 In this study, binary logistic regression and binary quantile regression are used to come up with bankruptcy prediction model for telecommunication carriers’
bankruptcy illiquidity. The purpose of this research is to find out key determinants of regarding insolvency in telecommunication industry and to evaluate 2 different regressions’ performance. Operating margin, Receivables turnover, Average collection period and Total asset are included in proposed model. Research results show that proposed model with 4 explanatory variables are highly useful to classify and predict firms as bankrupted and survived. ROC and CAP curve indicates that model by binary logistic regression correctly discriminate 94% and 84% respectively and slightly better than binary quantile regression. But binary quantile regression demonstrates more complete estimates for different quantile levels and shows how explanatory variables’ estimations’ move in relative to probability of bankruptcy.
論文目次 TABLE OF CONTENTS
ABSTRACT I
ACKNOWLEDGEMENTS II
TABLE OF CONTENTS III
LIST OF TABLES V
LIST OF FIGURES VI
CHAPTER ONE INTRODUCTION 1
1.1 Research Background. 1
1.1.1 Contextual Background. 1
1.2 Motivation. 2
1.2.1 The Importance of Exploring Bankruptcy Prediction Model. 2
1.3 Research Objective. 3
1.4 Research Gap. 3
1.5 Telecommunication Network Providers’ in USA. 4
1.6 Procedure and Structure of Study. 5
CHAPTER TWO LITERATURE REVIEW 7
2.1 Telecommunication Industry and Driving Factors of Business Model. 7
2.1.1 Hypothesis Development. 10
2.2 Bankruptcy Prediction Model. 11
2.2.1 Accounting Based Approach. 13
2.2.2 Market Based Approach. 19
2.2.3 Hybrid Approach. 20
CHAPTER THREE RESEARCH DESIGN AND METHODOLOGY 22
3.1 Variables. 22
3.2 Logistic Regression Model. 24
3.3 Binary Quantile Regression Model. 25
3.4 Model Validation and Evaluation. 26
3.4.1 Cumulative Accuracy Profile. 26
3.4.2 Receiver Operating Curve. 27
3.5 Data and Samples. 28
CHAPTER FOUR RESEARCH RESULTS 30
4.1 Descriptive Statistics. 30
4.2 Pearson Correlation. 33
4.3 Variance Inflation Factor. 34
4.4 Binary Logistic Regression Result. 35
4.5 Binary Quantile Regression Result. 36
4.6 Model Validation and Evaluation. 39
4.6.1 Cumulative Accuracy Profile. 39
4.6.2 Receiver Operating Curve. 41
CHAPTER FIVE CONCLUSION AND SUGGESTIONS 42
5.1 Research Conclusion. 42
5.2 Managerial Implication 45
5.3 Research limitation and future caveat 45
REFERENCES 47
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