臺灣博碩士論文加值系統

台灣的保險市場逐漸趨於成熟和飽和的狀態，2013年保險滲透度更達世界第一，消費者的行為模式隨著科技和網路的發展演變為過去被動到現今主動的角色。過去對於公司績效評估的研究主要著重在公司內部的資源配置和經營管理，由於消費行為模式的改變，本研究旨在探討外部消費面因素對於壽險公司經營管理的效率影響。研究採用Battese and Coelli (1995) 提出的一階段聯立隨機生產邊界與無效率方程式的方式以估計台灣24家壽險公司，時間範圍為2011到2013三年的經營效率，生產函數變數選擇為員工數、股東權益與負債作為生產函數的投入變數，產出變數則選擇保費收入，無效率方程式的環境變數選擇為：公司知名度、聲譽、兼職員工比例與公司規模。研究結果顯示公司知名度對於經營效率有顯著負向影響，公司聲譽與規模大小對於經營效率有顯著正向影響，兼職員工的比例則對公司經營效率則無顯著影響。

The insurance market in Taiwan has become mature and saturated. Market penetration even ranked the first in the world in 2013. Along with the development of technology and prevalence of Internet, the role of consumers has also evolved from the passive role in the past to the proactive role nowadays. Looking into past studies, researches were more focusing on the internal factors in companies, for example, allocation of resources or operation management. As the role of consumers has changed, this study aims to investigate the impact of factors of consumer side on the company operation efficiency. The one-stage SFA model of Battese and Coelli (1995) is adopted in this study to estimate the operation efficiency for the twenty-four life insurance firms in Taiwan from 2011 to 2013. The input factors are labor, equity and liability and the output factor is premium income. Moreover, the selected environmental factors are visibility, reputation, part-time workforce and firm scale. The results show that visibility has significantly negative impact on the firm efficiency. Reputation and scale have significantly positive relationship with firm efficiency. Part-time workforce does not have significant impact on the firm efficiency.

Chinese Abstract i
English Abstract ii
Acknowledgements iii
Table of Contents iv
List of Tables v
List of Figures vi
I. Introduction 1
1.1 Background and Purpose of Study 1
1.2 Objective and Scope of Study 6
1.3 Study Process 6
II. Literature Review 8
2.1 Current Life Insurance Market in Taiwan 8
2.2 Literature Review for the Performance Evaluation Model 11
2.2.1 Data Envelopment Analysis (DEA) 11
2.2.2 Stochastic Frontier Analysis (SFA) 12
2.2.3 Life Insurance Industry Performance Evaluation 13
III. Research Methodology 17
3.1 Data Sources 17
3.2 Variable Definitions and Research Hypothesis 17
3.3 Methodology – One-Stage Stochastic Frontier Analysis (SFA) Model 21
IV. Results and Discussion 23
V. Conclusions 29
5.1 Conclusions 29
5.2 Limitation and Recommendation 30
References 31

Aigner, D., Lovell, C. K., &; Schmidt, P. (1977). Formulation and estimation of stochastic frontier production function models. Journal of Econometrics, 6(1), 21-37.
Banker, R. D., Charnes, A., &; Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078-1092.
Battese, G., &; Coelli, T. (1992). Frontier production functions, technical efficiency and panel data: With application to paddy farmers in India. Journal of Productivity Analysis, 3(1), 153-169.
Battese, G. E., &; Coelli, T. J. (1995). A model for technical inefficiency effects in a stochastic frontier production function for panel data. Empirical Economics, 20(2), 325-332.
Charnes, A., Cooper, W. W., &; Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Cuesta, R. A. (2000). A production model with firm-specific temporal variation in technical inefficiency: with application to Spanish dairy farms. Journal of Productivity Analysis, 13(2), 139-158.
Cummins, J. D., Weiss, M. A., Xie, X., &; Zi, H. (2010). Economies of scope in financial services: A DEA efficiency analysis of the US insurance industry. Journal of Banking &; Finance, 34(7), 1525-1539.
Eling, M., &; Luhnen, M. (2010). Efficiency in the international insurance industry: A cross-country comparison. Journal of Banking &; Finance, 34(7), 1497-1509.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, Series A (General), 120(3), 253-290.
Fenn, P., Vencappa, D., Diacon, S., Klumpes, P., &; O’Brien, C. (2008). Market structure and the efficiency of European insurance companies: A stochastic frontier analysis. Journal of Banking &; Finance, 32(1), 86-100.
Fukuyama, H. (1997). Investigating productive efficiency and productivity changes of Japanese life insurance companies. Pacific-Basin Finance Journal, 5(4), 481-509.
Greene, W. H., &; Segal, D. (2004). Profitability and efficiency in the US life insurance industry. Journal of Productivity Analysis, 21(3), 229-247.
Hardwick, P. (1997). Measuring cost inefficiency in the UK life insurance industry. Applied Financial Economics, 7(1), 37-44.
Hu, J. L., Tang, C. T., &; Lin, C. H. (2014). Determinants of reputation evaluation of life insurance companies in Taiwan. Taiwan Insurance Review, 30(1), 35-56.
Klumpes, P. J. M. (2004). Performance benchmarking in financial services: Evidence from the UK life insurance industry. Journal of Business, 77(2), 257-273.
Md Saad, N., Idris, H., &; Edzalina, N. (2011). Efficiency of life insurance companies in Malaysia and Brunei: A comparative analysis. International Journal of Humanities and Social Science, 1(3), 111-122.
Meeusen, W., &; van den Broeck, J. (1977). Efficiency estimation from Cobb-Douglas production functions with composed error. International Economic Review, 18(2), 435-444.
Schmidt, P., &; Sickles, R. C. (1984). Production frontiers and panel data. Journal of Business &; Economic Statistics, 2(4), 367-374.
Yang, Z. (2006). A two-stage DEA model to evaluate the overall performance of Canadian life and health insurance companies. Mathematical and Computer Modelling, 43(7), 910-919.
Zhi, Y., &; Hu, J. L. (2011). A cross-strait comparative study of efficiency of life insurance companies: An application of the input slack adjustment approach. African Journal of Business Management, 5(14), 5746-5752.