Please use this identifier to cite or link to this item:
|標題:||Measuring Performance and Risk of Biotechnology Industry in Taiwan
|關鍵字:||Performance;績效;Biotechnology industry, Data Envelopment Analysis (DEA);Risk;Return;生技產業;資料包絡分析法;風險;報酬||出版社:||科技管理研究所||引用:||Books 1. Black, F. (1995), Exploring General Equilibrium, Massachusetts Institute of Technology, Cambridge. 2. Cortwright, J. and H. Mayer (2002), Signs of Life: The Growth of Biotechnology Centers in the US, The Brookings Institution Center on Urban and Metropolitan Policy, Washington, DC. 3. Development Center for Biotechnology (2007), 2007 yearbook of Biotechnology Industry, Development Center for Biotechnology, Taipei. 4. Drucker, Peter F. (1977), An introductory view of management, Harper''s College Press, New York. 5. Industrial Development Bureau (2009), Biotechnology industry in Taiwan, Ministry of Economic Affairs R.O.C. 6. Knight, F. H. (1921), Risk, Uncertainty and Profit Boston, MA: Hart, Schaffner & Marx; Houghton Mifflin Co. 7. Ross, S. A, Randolph W. Westerfield and Bradford D. Jordan (1999), Essentials of Corporate Finance, 2nd ed., USA, McGraw-Hill Companies, Inc. 8. Shieh, C. P. (2009), Financial Management: New Concepts with Unique Domestic Examples, 5th ed., Taiwan, Bestwise Companies, Inc. Journal Articles 1. Asmild, M., J. C. Paradi, D. N. Reese and F. Tam (2007), Measuring overall efficiency and effectiveness using DEA, European journal of operational research, Volume 178, Issue 1, 305-321 2. Appiah, H.K., A. Ranchhood (1998), Market orientation and performance in the biotechnology industry: an exploratory empirical analysis, Technology Analysis & Strategic Management, Vol. 10, No.20, 197-211 3. Banker, R.D., A. Charnes, and W. Cooper (1984), Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis, Management Science, Vol. 30, No. 9, 1078-1092 4. Barua, Anitesh, P.L. Brockett, W.W. Cooper and Honghui Deng (2004), DEA evaluations of long- and short-run efficiencies of digital vs. physical product “dot com” companies, Socio-Economic Planning Sciences, Vol. 38, No. 4, 233-253 5. Basso, Antonella and Stefania Funari (2001), A data envelopment analysis approach to measure the mutual fund performance, European Journal of Operational Research, Vol. 135, Issue 3, 477-492. 6. Carlos, Serrano-Cinca, Fuertes-Callen Yolanda and Mar-Molinero Cecilio (2005), Measuring DEA efficiency in Internet companies, Decision Support Systems, Vol.38, Issue 4, 557-573 7. Chang, D.S., and Jen-Gu Liau (2003), Dynamic Analysis of Relative Efficiency for the Biotechnology and Pharmaceutical Industry in Taiwan, Industrial Forum, Vol. 5, No. 2, 285-302 8. Chang, H., and S. Majumdar (1997), The optimal local exchange carrier size, Review of industrial organization, Vol. 13, No. 6, 637-649 9. Charnes, A. and W. W. Cooper (1962), Programming with Linear Fractionals, Naval Res. Logistics Quarterly, Vol. 9, 181-186. 10. Charnes, A., W.W. Cooper and E. Rhodes (1978), Measuring the Efficiency of Decision Making Units, European Journal of Operational Research, Vol. 2, Issue 6, 429-444. 11. Chen, T. Y. and T. L. Yeh (1998), A Study of Efficiency Evaluation in Taiwan's Banks, International Journal of Service Industry Management, Vol. 9, No. 5, 1-8 12. Chen, Chung-Jen, Hsueh-Liang Wu, Bou-Wen Lin (2006), Evaluating the development of high-tech industries: Taiwan's science park, Technological forecasting & social change, Vol. 73, Issue 4, 452-465 13. Chiu, Yung-Ho, Yu-Chuan Chen and Chia-Lin Tsao (2005), The estimation of Taiwan biotechnology industry's productivity and efficiency, THJLTP, Vol.2 No.2, 93-120. 14. Daft, R. L. (1982), Bureaucratic versus Non-bureaucratic Structure and the Process of Innovation and Change, Research in the Sociology of Organisation, Vol. 1 pp.129-66. 15. Donthu, N. and Boonghee Yoo (1998), Retail productivity assessment using Data envelopment analysis, Journal of retailing, Vol. 74, Issue 1, 89-105 16. Farrell, M.J. (1957), The Measurement of Productive Efficiency, Journal of the Royal Statistical Society, Vol. 120, 253-290 17. Galagedera, Don U. A. and Param Silvapulle (2002), Australian mutual fund performance appraisal using data envelopment analysis, Managerial Finance, Vol. 28, Issue 9, 60-73. 18. Hall, Linda A. and Bagchi-Sen Sharmistha (2007), An analysis of firm-level innovation strategies in the US biotechnology industry, Technovation, Vol. 27, Issues 1-2, 4-14 19. Ho, Chien-Ta Bruce and Dauw-Song Zhu (2004), Performance Measurement of Taiwan's Commercial Banks, International Journal of Productivity & Performance Management, Emerald Publisher, Vol. 53, No. 5, 425-434. 20. Ho, Chien-Ta Bruce, Desheng Dash Wu, Chris Chou and David L. Olson (2009), A risk scoring model and application to measuring internet stock performance, International journal of information technology & decision making, Vol.8, No.1, 133-149 21. Ho, Chien-Ta and D. Wu (2008), Online banking performance evaluation using data envelopment analysis and principal component analysis, Computers & Operations Research, Elsevier Publisher, Vol. 36, No. 6, 1835-1842. 22. Ho, Chien-Ta Bruce and Oh, K.B. (2008), Measuring online stockbroking performance, Industrial Management & Data Systems, Vol. 108, No.7, 988-1004 23. Ho, C. T. and Y. C. Wang (2004), Performance evaluation for trust firms reorganizing into commercial banks in Taiwan, Euro Asia Journal of Management, Vol. 14, No. 28, pp 113-134 24. Ho, Chien-Ta and Yun-Shan Wu (2006), Benchmarking Performance Indicators for Banks, Benchmarking - An International Journal, Vol. 13, No. 1/2, 147-159. 25. Hu, Jin-Li and Ming-Chao Tsou (2003), Productivities of Biotech Firms in Mainland China and Taiwan, Master thesis, Institute of Business and management, National Chiao Tung University, Taiwan 26. Hung, Wei-Tien, Yi-Wei Chu and Cheng-Wen Yao (2009), Using data envelopment analysis approach to evaluate the operation efficiency of biotechnology firms in Taiwan, 2009 Cross-Strait Symposium on Innovation and sustainable management and management innovation and interdisciplinary symposium 27. Jenkins, L., M. Anderson (2003), A multivariate statistical approach to reducing the number of variables in data envelopment analysis, European Journal of operational research, Vol. 147, No.1, 51-61. 28. Johnes, J. and G. Jones (1995), Research Funding and Performance in U.K. University Department of Economics: A Frontier Analysis, Economics of Education Review, Vol. 14, No. 3, 310-314 29. Kane, Jeffrey S. (1996), The conceptualization and representation of total performance effectiveness, Human resource management review, Vol. 6, Issue 2 , 123-145 30. Lai, Shih-Pao, Sung-Po Cheng, Kuan-Chia Lu (2004), Operation Efficiency Analysis of Biotech Companies in Taiwan─Applications of Data Envelopment Analysis, Journal of management and information, Vol. 9, 63-88 31. Liang, Shing-Ko, Jyun-Lin Jiang, Chia-Te Lai (2008), Effects of integrative strategies on the production efficiency of biotech firms: A data envelopment analysis, International journal of management, Vol. 25, No. 1, 140-148 32. Liu, Hsiang-His, Pei-Hung Chu (2004), A study on the operational efficiency of Taiwan Biotechnology industry: An application of DEA and Malmquist Productivity index, The 5th annual conference of Taiwan's economic empirics. 33. Lo, Shih-Fang and Wen-Min Lu (2006), Does Size Matter? Finding The Profitability And Marketability Benchmark Of Financial Holding Companies, Asia - Pacific Journal of Operational Research , Vol. 23, No. 2, 229-246 34. Luo, Xueming (2003), Evaluating the profitability and marketability efficiency of large banks: An application of data envelopment analysis, Journal of Business Research, Vol. 56, Issue 8, 627-635. 35. Mahajan, J. (1991), A data envelopment analytic model for assessing the relative efficiency of the selling function, European Journal of operational research, Vol. 53, Issue 2, 189-205 36. Mass, NJ.(2005), The relative value of growth, Harvard business review, Vol. 83, No 4, 102-12 37. McMullen, P. R., R. A. Strong (1998), Selection of Mutual Funds Using Data Envelopment Analysis, Journal of Business and Economics Studies, Vol. 4, No.1, 1-12. 38. Meric, Gulser and Ilhan Meric (2001), Risk and Return in the World''s Major Stock Markets, Journal of Investing, Vol. 10, No. 1, 62-6 39. Michalska, J. (2005), The usage of The Balanced Scorecard for the estimation of the enterprise''s effectiveness, Journal of Materials Processing Technology, Vol. 162-163, No. 15, 751-758 40. Mouzas, Stefanos (2006), Efficiency versus effectiveness in business networks, Journal of business research, Vol. 59, Issues 10-11 , 1124-1132 41. Murthi, B. P. S., Yoon K. Choi and Preyas Desai (1997), Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach, European Journal of Operational Research, Vol. 98, Issue 2, 408-418 42. Paradi, J. C. and C. Schaffnit (2004), Commercial branch performance evaluation and results communication in a Canadian bank- a DEA application, European Journal of operational research, Vol. 156, Issue 3, 719-735 43. Seiford, Lawrence. M., Joe. Zhu (1999), Profitability and Marketability of the top 55 U.S. Commercial Banks, Management Science, Vol. 45, No. 9, 1270-1288. 44. Spronk, Jaap and Erik M. Vermeulen (2003), Comparative performance evaluation under uncertainty, European Journal of Operational Research, Vol. 150, Issue 3, 482-495 45. Tsai, Hsiang-Chih, Chun-Mei Chen and Gwo-Hshiung Tzeng (2006), The comparative productivity efficiency for global telecoms, International Journal of Production Economics, Vol. 103, Issue 2, 509-526 46. Wu, Jia-Yuan(2004), A Study on the Operational Efficiency of Taiwan Biotechnological Industry : An Application of DEA and Malmquist Productivity index , unpublished master thesis, Department of Economic, Soochow University, Taiwan 47. Zhao, Xiu-juan and Shou-yang Wang (2007), Empirical Study on Chinese Mutual Funds' Performance, Systems Engineering - Theory & Practice, Vol. 27, Issue 3, 1-11. 48. Zhu, Joe (2000), Multi-factor performance measure model with an application to Fortune 500 companies, European Journal of Operational Research, Vol. 123, Issue 1, 105-124 49. Zhu, Dauw-Song, Ho, Chien-Ta and Li-Hsia Lin (2005), A Study on the Performance Evaluation of Taiwan's Newly Reorganized Banks, Sun Yat-Sen Management Review, Vol. 13, No. 5, 125-157. Website Reference 1. Organization for Economic Cooperation and Development (2005): http://www.oecd.org/dataoecd/4/23/42833898.pdf 2. UN convention in Biological Diversity: http://www.cbd.int/convention/convention.shtml 3. Science and Technology Advisory Group of Executive Yuan R. O. C. (2001): http://www.stag.gov.tw/index.php||摘要:||
For investors, considering return when they make stock selections is an important concern. Besides company performance, risk is another important indicator for determining investing. The aim of this study is to examine the relationships among performance, risk and return. Biotechnology has been a key development industry in many countries; its innovative R&D technology not only can solve environmental problems but also help to cure human diseases. Moreover, from a financial point of view, in spite of the global financial crisis in 2008, the biotechnology industry is still in its growth phase, and biotechnology stocks have become a popular target for investors. As a result, the biotechnology industry is considered a valuable research target. This study uses the concept of return on equity (ROE) and applies a Data Envelopment Analysis (DEA) approach to measure operating efficiency, operating effectiveness and risk. There are two evaluation processes; process 1 measures the operating performance of a company and this study separates performance from operating efficiency and operating effectiveness. In process 2, this study measures the degree of financial risk based on an equity multiplier perspective.
The empirical result shows there is no significant relationship between operating efficiency and operating effectiveness. Also, operating effectiveness affects performance more than operating efficiency does in Taiwan's biotechnology industry. Moreover, there is a relationship, not only between performance and return, but also between risk and return.
投資人在選擇投資標的時，未來可獲得的報酬為其主要投資動機，而公司的績效為評估報酬之重要考量因子。然而除了公司績效表現外，風險為隱含在報酬中的重要因子，因此本研究主要探討「績效、報酬與風險的關係」。生物科技產業在許多國家皆已被視為重點發展產業，除了其創新研發技術可能解決未來環境問題及人類疾病外，在歷經2008年全球金融海嘯後，生物科技產業仍維持成長幅度，使得生技股在股票市場上亦為活躍的明星股，因此本研究認為生物科技產業為一值得研究對象。本研究應用股東權益報酬率(ROE)的概念，以資料包絡分析法(DEA)衡量台灣15家上市櫃生物科技公司之報酬 (Return)、績效 (Performance)及風險 (Risk)的關係。本研究分為兩步驟衡量，第一步驟衡量公司績效，應用資產報酬率(ROA)的概念，以營運效率(operating efficiency)及營運效果(operating effectiveness) 衡量公司績效；第二步驟運用公司之權益乘數程度的概念衡量公司之財務風險 。
|Appears in Collections:||科技管理研究所|
Show full item record
TAIR Related Article
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.