臺灣博碩士論文加值系統

This study analyzes the factors that determine and shape output generation in Japan. These factors are being examined in pursuance to have the understanding of growth and downfall of output. It is hypothesized that R＆D activities, labor, non IT capital stock and IT capital stock contribute to the development of output growth in Japanese industries. In addition to that, moderator variables which are represented by numbers of aging labor and industry competition are hypothesized can either stimulate or weaken the output generation. Hypotheses are tested using the data obtained from Research Institute of Economy, Trade and Industry (RIETI) Japan Industrial Output (JIP) Database 2011 and Japan Statistics Official within period 1970 to 2008. A multiple regression analysis, a manova analysis and a hierarchical multiple regression analysis are conducted. Results indicate that as hypothesized, but the expected significant coefficients only appeared in several industries, hence all hypotheses can be apprehended as partially supported. Similar to expectations, labor aging has negative moderating effect to labor-intensive industry, meanwhile labor aging has positive moderating effect to capital intensive industry. Concurrently, it is found that industry competition discourage the investment towards factor inputs, but it only has relatively weak power in affecting R＆D expenditure per researcher to output.

ABSTRACT III
ACKNOWLEDGEMENTS IV
TABLE OF CONTENTS VII
LIST OF TABLES XIV
LIST OF FIGURES XVI
CHAPTER ONE INTRODUCTION 1
1.1 Research Background. 1
1.1.1 Economic History of Japan and Output Growth. 1
1.1.2 Concerns over Japan’s Economy: Some Insights from Japan’s External Determinants. 3
1.1.3 Case Study Overview: Japanese Industries. 6
1.2 Research Objectives and Contribution. 8
1.3 Research Procedure. 14
CHAPTER TWO LITERATURE REVIEW 16
2.1 Background. 16
2.1.1 Output Management. 16
2.1.2 The Application of Cobb Douglas in Industry Level. 18
2.1.3 Output and External Determinants: Competition and Aging Labor. 18
2.2 Theoretical Foundation. 21
2.2.1 Output Growth Theory: Neoclassical Growth Theory and New Growth Theory. 21
2.2.2 The Application of Neoclassical and New Growth Theory to Production Function Model. 23
2.3 Definition of Relevant Research Variables. 26
2.3.1 Number of Researchers. 26
2.3.2 R＆D Expenditure. 27
2.3.3 Labor Input. 27
2.3.4 Non-IT Capital Stock. 28
2.3.5 IT Capital Stock. 28
2.3.6 Competition. 29
2.3.7 Aging Labor. 29
2.3.8 Output. 30
2.4 Development of Research Hypotheses. 31
2.4.1 Interrelationship between Numbers of Researcher to Output. 31
2.4.2 Interrelationship between R＆D Expenditure to Output. 32
2.4.3 Interrelationship between Labor Input to Output. 33
2.4.4 Interrelationship between Non-IT Capital Stock to Output. 33
2.4.5 Interrelationship between IT Capital Stock and Output. 34
2.4.6 Interrelationship among Aging Labor, Labor Input and Output. 35
2.4.7 Interrelationship among Competition, Output, Research and Development, Non-IT Capital Stock and IT Capital Stock. 36
CHAPTER THREE RESEARCH DESIGN AND METHODOLOGY 40
3.1 Conceptual Model. 40
3.2 Definition Variables. 41
3.3 Summary of Hypotheses. 42
3.4 Industry Coverage and Time Data. 43
3.5 Definition and Measurement of Variables. 44
3.5.1 Dependent Variables. 45
3.5.2 Independent Variables. 46
3.6 Data Sources. 50
3.7 Data Analysis. 51
3.7.1 Interpolation. 51
3.7.2 Ratio to Number. 52
3.7.3 Natural Logarithm. 52
3.7.4 Depreciation of Capital Stock. 53
3.7.5 Correlation Coefficients Analysis. 53
3.7.6 Multiple Regression Analysis. 53
3.7.7 Hierarchical Multiple Regression. 54
3.7.8 The Model Fitness. 54
3.7.9 Multivariate Analysis Variance (Manova). 55
CHAPTER FOUR RESEARCH RESULTS 56
4.1 Hypothesis Testing. 56
4.2 Each Hypothesis Testing 63
4.2.1 Hypothesis 1: The Numbers of Researcher is Positively Related to Output. 63
4.2.2 Hypothesis 2: R＆D Expenditure per Researcher is Positively Related to Output. 71
4.2.3 Hypothesis 3 and 4: Labor Input and Output. 80
4.2.4 Hypothesis 5: Non-IT Capital Stock is Positively Related to Output. 90
4.2.5 Hypothesis 6: IT Capital Stock is Positively Related to Output. 97
4.2.6 Hypothesis 7 and 8: Aging Labor and Output. 105
4.2.7 Hypothesis 9: Industry Competition Has Negative Moderating Effect on Relationship Between Number of Researcher and Output. 114
4.2.8 Hypothesis 10: Industry Competition Has Negative Moderating Effect on Relationship Between Intramural R＆D Expenditure Per Researcher and Output. 122
4.2.9 Hypothesis 11: Industry Competition Has Negative Moderating Effect on Relationship between Non-It Capital Stock and Output. 129
4.2.10 Hypothesis 12: Industry Competition Has Negative Moderating Effect on Relationship between IT Capital Stock and Output. 137
4.3 Multivariate Analysis Variance (Manova) Test. 144
4.4 The Model Fitness. 144
CHAPTER FIVE CONCLUSION AND SUGGESTIONS 148
5.1 Overview of Japan Situation. 148
5.2 Brief Explanation of Hypotheses Results. 149
5.2.1 Number of Researchers and Output. 152
5.2.2 R＆D Expenditure per Researcher and Output. 159
5.2.3 Labor Intensive Industry: Labor Input and Output. 160
5.2.4 Capital Intensive Industry: Labor Input and Output. 162
5.2.5 Non-IT Capital Stock and Output. 164
5.2.6 IT Capital Stock and Output. 166
5.2.7 Labor Intensive Industry: Aging Labor, Labor Input and Output. 169
5.2.8 Capital Intensive Industry: Aging Labor, Labor Input and Output. 172
5.2.9 Competition in Japan and Its Impacts toward Japanese Industries. 173
5.3 Multivariate Analysis Variance (Manova). 189
5.4 Limitations of Research and Future Work. 190
5.4.1 Model Fitness and Future Research. 190
5.4.2 Limitations of Data Availability and Future Research. 190
5.5 Contribution to Management Field. 191
5.6 Contribution to Academia and Thereotical Implications. 193
5.7 What Lessons can be Obtained? Lesson Learned for Indonesia. 195
REFERENCES 198
APPENDICES 220
Appendix 6.1 Production Function Input Results. 220
6.1.1 Transport and Telecommunication Service Industry. 220
6.1.2 Chemical Products Industry. 221
6.1.3 Petroleum and Coal Products Industry. 221
6.1.4 Construction Industry. 222
6.1.5 Rubber Products Industry. 223
6.1.6 Pharmaceutical Products Industry. 223
6.1.7 Iron and Steel Products Industry. 224
6.1.8 Mining Industry. 225
6.1.9 Motor Vehicles Industry. 225
6.1.10 Other Transport Equipment Products Industry. 226
6.1.11 Pulp and Paper Products Industry. 226
6.1.12 Fabricated Metal Products Industry. 227
6.1.13 Agriculture Forestry Fisheries Industry. 228
Appendix 6.2 Moderating Effect: Aging Labor. 228
6.2.1. Transport and Telecommunication Service Industry. 228
6.2.2 Chemical Products Industry. 229
6.2.3 Petroleum and Coal Products Industry. 229
6.2.4 Construction Industry. 230
6.2.5 Rubber Products Industry. 231
6.2.6 Pharmaceutical Products Industry. 231
6.2.7 Iron and Steel Products Industry. 232
6.2.8 Mining Industry. 232
6.2.9 Motor Vehicles Products Industry. 233
6.2.10 Other Transport Equipment Products Industry. 233
6.2.11 Pulp and Paper Products Industry. 234
6.2.12 Fabricated Metal Products Industry. 234
6.2.13 Agriculture Forestry Fisheries Industry. 235
Appendix 6.3 Moderating Effect: Industry Competition. 235
6.3.1. Transport and Telecommunication Service Industry. 235
6.3.2 Chemical Products Industry. 238
6.3.3 Petroleum and Coal Products Industry. 240
6.3.4 Construction Industry. 243
6.3.5 Rubber Products Industry. 246
6.3.6 Pharmaceutical Products Industry. 249
6.3.7 Iron and Steel Products Industry. 251
6.3.8 Mining Industry. 253
6.3.9 Motor Vehicles Products Industry. 255
6.3.10 Other Transport and Equipment Products Industry. 257
6.3.11 Pulp and Paper Products Industry. 259
6.3.12 Fabricated Metal Products Industry. 261
6.3.13 Agriculture Forestry Fisheries Industry. 263
Appendix 6.4 Manova Regression Analysis. 265
6.4.1 Manova Regression Analysis Result. 265
Appendix 6.5 Summary of Hypothesis Results (All Industries). 266

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