臺灣博碩士論文加值系統

本論文主要採用Hansen(2000)所提出之多重狀態模型(multiple regimes model)分析2005年至2013年台灣上市公司無形資產、公司成長與企業風險關係，並進一步選用Pantzalis and Park (2009)超額人力資本指標(Excess Value of Human Capital, EVHC)，探討不同人力資源投入程度下是否對企業風險有不同的影響。
實證結果顯示多重狀態模型檢測出人力資源與企業風險間，具有上下不對稱之非線性關係。公司規模與公司成長具有門檻效果，在單一門檻效果且門檻變數為公司規模之檢測下，區分大規模與小規模公司區間，發現大規模公司風險與人力資源投入為顯著負相關，大規模公司擁有較多資源優勢與經驗，降低公司成本與人為疏失，進而降低風險。在多重門檻效果且門檻變數為公司規模與公司成長之檢測下，大規模公司區分為高成長與低成長公司區間，規模較大且高成長公司之人力資源投入與公司風險呈現顯著負相關，小規模則無門檻效果；相對於大規模且低成長公司，人力資源投入更能降低企業風險。在大規模且高成長區間下，研發支出為顯著正相關，推論原因為大規模公司應透過併購、投資與購買專利來提升效率、降低成本，增加研發支出投入並不符合效益。而在營運現金流量方面，為顯著正相關，由於公司擁有高現金流量不僅可提高公司償債能力且有能力投資潛力計畫，降低風險。

This dissertation adopts the multiple regimes model to analyze the relations among intangible assets, firm growth and enterprise risk in Taiwan-listed companies from 1998 to 2013. In contrast with previous studies, this dissertation calculates an indicator of human capital’s excess value to examine whether the human resource input difference influences enterprise risk in accordance with Pantzalis and Park (2009).
The results show that there is a significant asymmetric non-linear relation between human resource and enterprise risk. It is found that firm size and firm growth exhibit a threshold effect with enterprise risk. When firm size was selected the threshold variable with a single threshold effect was used to test the relationship, and the large group could be divided into a high firm growth regime and a low firm growth regime. A large firm regime has a negative significant link between human resource and enterprise risk; a large company owns more advantageous resources and unique experience to reduce costs and humor error which decreases risk. When firm size and firm growth were selected as threshold variables with multiple threshold effects, the large group could be divided into high firm a growth regime and a low firm growth regime. There is a negative significant link between human resource and enterprise risk in large firms with high growth, but the threshold effect does not exist in small firms; human resource input can decrease more risk than in large firms with high growth. Under a large size and high firm growth regime, the research and development expenditure has a significantly positive correlation with risk; our inference is that firms should merge, invest equity, and purchase patents to enhance efficient and reduce cost; higher research and development expenditures do not enhance the benefit assessment. Operating cash flow has a significantly negative correlation with risk; high cash flow is helpful for a firm’s debt-payment ability and increasing cash holdings to invest in potential projects.

ACKNOWLEDGEMENT I
ABSTRACT IN CHINESE II
ABSTRACT IN ENGLISH III
CONTENTS V
LIST OF TABLES VII
LIST OF FIGURES VIII
CHAPTER 1 INTRODUCTION 1
1.1 Study Process 7
CHAPTER 2 LITERATURE REVIEW 8
2.1 Effect of Human Resource on Firm Performance 8
2.2 Relation between Enterprise Risk
and Firm Performance 11
2.3 Interactions among Enterprise Risk,
Human Resource and Firm Performance 13
CHAPTER 3 VARIABLES AND METHODOLOGY 16
3.1 Variable Measurement 16
3.1.1 Expected default risk 16
3.1.2 Human resource 18
3.1.3 Control variables 19
3.2 Methodology 22
3.3 Threshold Estimate and Slope Parameters 26
CHAPTER 4 DATA 28
4.1 Data 28
4.2 Descriptive Statistics 29
CHAPTER 5 EMPIRICAL RESULTS AND ANALYSIS 35
5.1 Pooled Regression Results 35
5.2 Threshold Effects 38
5.3 Threshold Variable of
the M/B Ratio in Multiple Regimes 42
CHAPTER 6 CONCLUSIONS 47
REFERENCES 49


LIST OF TABLES
Table 1 Descriptive statistics from relevant variables 31
Table 2 Empirical results from the pooled regression model without the threshold effect 37
Table 3 Test for the threshold effect 39
Table 4 Threshold model for the single threshold variable 41
Table 5 Threshold estimation for a single threshold variable and multiple threshold variables 43
Table 6 Threshold model for multiple threshold variables 46

LIST OF TABLES
Table 1 Descriptive statistics from relevant variables 31
Table 2 Empirical results from the pooled regression model without the threshold effect 37
Table 3 Test for the threshold effect 39
Table 4 Threshold model for the single threshold variable 41
Table 5 Threshold estimation for a single threshold variable and multiple threshold variables 43
Table 6 Threshold model for multiple threshold variables 46

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