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標題: Measuring Performance and Risk of Automotive Industry in Czech Republic
作者: 史雅柏
Selucky, Jakub
關鍵字: Automotive industry
Data Envelopment Analysis (DEA)
Return on Equity (ROE)
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. Drucker, P. F. (1977), An introductory view of management, Harper''s College Press, New York. 3. Freiberg, F.; Zraly, M. (2003), Enterprise Economics, Publ. CTU in Prague, Pages 106 4. Knight, F. H. (1921), Risk, Uncertainty and Profit, Boston, MA: Hart, Schaffner & Marx; Houghton Mifflin Co. 5. Lazonick, W. (2002), IEBM Handbook of Economics., Int. Thomson Business Press; 1st edition 6. MIT (2009), Panorama zpracovatelského průmyslu ČR 2008 (Panorama of the Czech manufacturing industry 2008). Prague: Czech Ministry of Industry and Trade, Pages 257 7. Pavlinek, P. (2008), A Successful Transformation? Restructuring of the Czech Automobile Industry, Physica-Verlag Heidelberg, series: Contributions to Economics, Pages 296 8. Ross, S. A.; Westerfield, R. W.; Bradford, J. D. (1999), Essentials of Corporate Finance, 2nd ed., USA, McGraw-Hill Companies, Inc. Journal Articles 1. Alizadeh, P. (2009), The Iranian auto industry in a comparative perspective, Conference on Iranian Economy at a Crossroads: Domestic and Global Challenges, Pages 1-38 2. Apicella, L. C.; Dreber, A.; Campbell, B.; Gray, B. P.; Hoffman, M.; Little, C. A., (2008), Testosterone and financial risk preferences., Evolution and Human Behavior, Vol. 29, No. 6, Pages 384-390 3. Asmild, M.; Paradi, J. C.; Reese, D. N.; Tam, F. (2007), Measuring overall efficiency and effectiveness using DEA, European journal of operational research, Vol. 178, No. 1, Pages 305-321 4. Banker, R.D., Charnes, A.; Cooper, W. (1984), Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis, Management Science, Vol. 30, No. 9, Pages 1078-1092 5. Barua, A.; Brockett, P.L.; Cooper, W.W.; Deng H. (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, Pages 233-253 6. Basso, A.; Funari, S. (2001), A data envelopment analysis approach to measure the mutual fund performance, European Journal of Operational Research, Vol. 135, No. 3, Pages 477-492. 7. Bernard, J.; Cantner, U.; Westermann, G. (1996), Technological leadership and variety: A Data Envelopment Analysis for the French machinery industry. Annals of Operations Research, Vol. 68, No. 1-4, Pages 361-377 8. Carlos, S.-C.; Fuertes-Callén, Y.; Mar-Molinero, C. (2005), Measuring DEA efficiency in Internet companies, Decision Support Systems, Vol.38, No. 4, Pages 557-573 9. Castro, C.; Cabrera-Ríos, M.; Lilly, B.; Castro, J.M.; Mount-Campbell, C. A. (2003), IDENTIFYING THE BEST COMPROMISES BETWEEN MULTIPLE PERFORMANCE MEASURES IN INJECTION MOLDING (IM) USING DATA ENVELOPMENT ANALYSIS (DEA)., Journal of Integrated Design & Process Science, Vol. 7, No. 1, Pages 1-10 10. Chang, H.; Majumdar, S. (1997), The optimal local exchange carrier size, Review of industrial organization, Vol. 13, No. 6, Pages 637-649 11. Chang, S. -Y.; Chen, T. -H. (2008), Performance ranking of Asian lead frame firms: a slack-based method in data envelopment analysis., International Journal of Production Research, Vol. 46 No. 14, Pages 3875-3885 12. Charnes, A.; Cooper, W. W. (1962), Programming with Linear Fractionals, Naval Res. Logistics Quarterly, Vol. 9, Pages 181-186. 13. Charnes, A.; Cooper, W.W.; Rhodes, E. (1978), Measuring the Efficiency of Decision Making Units, European Journal of Operational Research, Vol. 2, No. 6, Pages 429-444. 14. Chen, T. Y.; Yeh, T. L. (1998), A Study of Efficiency Evaluation in Taiwan's Banks, International Journal of Service Industry Management, Vol. 9, No. 5, 1-8 15. Chen, C. -J.; Wu, H.-L.; Lin, B.-W. (2006), Evaluating the development of high-tech industries: Taiwan's science park, Technological forecasting & social change, Vol. 73, No. 4, Pages 452-465 16. Chen, Z.; Lin, R.., (2006), Mutual fund performance evaluation using data envelopment analysis with new risk measures., OR Spectrum, Vol. 28, No. 3, Pages 375-398 17. Chiu, Y.-H.; Jan, C.; Shen, D.-B.; Wang, P.-C. (2008), Efficiency and capital adequacy in Taiwan banking: BCC and super-DEA estimation., Service Industries Journal, Vol. 28, No. 4, Pages 479-496 18. Chiu, Y.-H.; Chen, Y.-C.; Tsao, C.-L. (2005), The estimation of Taiwan biotechnology industry's productivity and efficiency, THJLTP, Vol.2, No.2, Pages 93-120 19. Co, H. C.; Chew, K. S., (1997), Performance and R&D expenditures in American and Japanese manufacturing firms., International Journal of Production Research, Vol. 35, No. 12, Pages 3333-3348 20. CzechInvest (March 2009), “Automotive industry in the Czech Republic” 21. CzechInvest, (2010), Promised Incentives from 1998 to 2010. Prague: CzechInvest. 22. Daft, R. L. (1982), Bureaucratic versus Non-bureaucratic Structure and the Process of Innovation and Change, Research in the Sociology of Organisation, Vol. 1, Pages 129-166. 23. Doner,R.F.; Noble, G. W.; Ravenhill, J., (2006), Industrial competitiveness of the auto parts industries in four Asian countries, World Bank Policy Research Working paper, No. 4106, Pages 1-76 24. Donthu, N.; Yoo, B. (1998), Retail productivity assessment using Data envelopment analysis, Journal of retailing, Vol. 74, No. 1, Pages 89-105 25. Farrell, M.J. (1957), The Measurement of Productive Efficiency, Journal of the Royal Statistical Society, Vol. 120, Pages 253-290 26. Galagedera, Don U. A.; Silvapulle P. (2002), Australian mutual fund performance appraisal using data envelopment analysis, Managerial Finance, Vol. 28, No. 9, Pages 60-73. 27. Grosskopf, S.; Valdmanis, V. (1987), Measuring hospital performance : A non-parametric approach, Journal of Health Economics, Vol. 6, No. 2, Pages 89-107 28. Ho, C.-T. B.; Zhu, D.-S. (2004), Performance Measurement of Taiwan's Commercial Banks, International Journal of Productivity & Performance Management, Emerald Publisher, Vol. 53, No. 5, Pages 425-434. 29. Ho, C.-T. B.; Oh, K.B. (2008), Measuring online stockbroking performance, Industrial Management & Data Systems, Vol. 108, No.7, Pages 988-1004 30. Ho, C.-T.; Wu, D. (2008), Online banking performance evaluation using data envelopment analysis and principal component analysis, Computers & Operations Research, Elsevier Publisher, Vol. 36, No. 6, Pages 1835-1842. 31. Ho, C.-T. B.; Wu, D. D.; Chou, C.S.; Olson, D. L. (2009), A risk scoring model and application to measuring internet stock performance, International journal of information technology & decision making, Vol. 8, No. 1, Pages 133-149 32. Ho, C.-T.; Wu Y.-S. (2006), Benchmarking Performance Indicators for Banks, Benchmarking - An International Journal, Vol. 13, No. 1/2, Pages 147-159. 33. Humphery, J.; Memedovic, O. (2003), “ The global automotive industry value chain: what prospects for upgrading by developing countries?, Sectoral studies series, United Nations Industrial development Organization (UNIDO), Vienna. 34. Hung, W.-T., Chu, Y.-W.; Yao, C.-W. (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 35. Izadbakhsh, H.; Ali, M. H.; Amirkhani, A.; Montazeri, A.; Saberi, M. (2009), Performance Assessment and Optimization of the After-Sale Networks., Proceedings of World Academy of Science: Engineering & Technology, Vol. 49, Pages 910-914 36. Jaklic, M.; Svetina, A.C.; Zagorsek, H. (2004), SPECIFIC RESPONSES TO UNIVERSAL PRESSURES IN THE INDUSTRY - COMPARING EUROPEAN AUTOMOTIVE CLUSTERS, University of Ljubljana, Faculty of Economics, Pages 25 37. Jenkins, L.; Anderson, M. (2003), A multivariate statistical approach to reducing the number of variables in data envelopment analysis, European Journal of operational research, Vol. 147, No.1, Pages 51-61. 38. Jiang, P. (2009), Exploring the price efficiency within automotive markets., International Journal of Market Research, Vol. 51, No. 3, Pages 403-426 39. Johnes, J.; Jones, G. (1995), Research Funding and Performance in U.K. University Department of Economics: A Frontier Analysis, Economics of Education Review, Vol. 14, No. 3, Pages 310-314 40. Kane, J. S. (1996), The conceptualization and representation of total performance effectiveness, Human resource management review, Vol. 6, No. 2 , Pages 123-145 41. Kuosmanen, T. (2007), Performance measurement and best-practice benchmarking of mutual funds: combining stochastic dominance criteria with data envelopment analysis., Journal of Productivity Analysis, Vol. 28, No. 1/2, Pages 71-86 42. Kravtsova, V. (2008), Foreign presence and efficiency in transition economies., Journal of Productivity Analysis, Vol. 29, No. 2, Pages 91-102 43. Liang, S.-K.; Jiang, J.-L.; Lai, C.-T. (2008), Effects of integrative strategies on the production efficiency of biotech firms: A data envelopment analysis, International journal of management, Vol. 25, No. 1, Pages 140-148 44. Lin, L.; Huang, C.-Y. (2009), Optimal size of the financial services industry in Taiwan: a new DEA-option-based merger simulation approach., Service Industries Journal, Vol. 29, No. 4, Pages 523-537 45. Lin, R.; Chen, Z. (2008), NEW DEA PERFORMANCE EVALUATION INDICES AND THEIR APPLICATIONS IN THE AMERICAN FUND MARKET., Asia-Pacific Journal of Operational Research, Vol. 25, No. 4, Pages 421-450 46. Liu, H.-H., Chu, P.-H. (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. 47. Lo, S.-F.; Lu, W.-M. (2006), Does Size Matter? Finding The Profitability And Marketability Benchmark Of Financial Holding Companies, Asia - Pacific Journal of Operational Research , Vol. 23, No. 2, Pages 229-246 48. Luo, X. (2003), Evaluating the profitability and marketability efficiency of large banks: An application of data envelopment analysis, Journal of Business Research, Vol. 56, No. 8, Pages 627-635 49. Mahajan, J. (1991), A data envelopment analytic model for assessing the relative efficiency of the selling function, European Journal of operational research, Vol. 53, No. 2, Pages 189-205 50. McKinsey''s Automotive & Assembly Practice, (2004), HAWK 2015 - Knowledge-based changes in the automotive value chain, McKinsey Brochures 51. McMullen, P. R.; Strong, R. A. (1998), Selection of Mutual Funds Using Data Envelopment Analysis, Journal of Business and Economics Studies, Vol. 4, No.1, Pages 1-12. 52. Memedovic, O. (2007), Links between Local Clusters and Global Value Chains, Expert Meeting on "ENHANCING THE PARTICIPATION OF SMALL AND MEDIUMSIZED ENTERPRISES IN GLOBAL VALUE CHAINS", UNIDO Private Sector Development Branch, Geneva 53. Meric, G.; Meric, I. (2001), Risk and Return in the World''s Major Stock Markets, Journal of Investing, Vol. 10, No. 1, Pages 62-66 54. 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, Pages 751-758 55. Mok, V.; Yeung, G.; Han, Z.; Li, Z. (2007), Leverage, Technical Efficiency and Profitability: an application of DEA to foreign-invested toy manufacturing firms in China., Journal of Contemporary China, Vol. 16, No. 51, Pages 259-274 56. Mouzas, S. (2006), Efficiency versus effectiveness in business networks, Journal of business research, Vol. 59, No. 10-11, Pages 1124-1132 57. Murthi, B. P. S.; Choi, Y. K.; Desai, P. (1997), Efficiency of mutual funds and portfolio performance measurement: A non-parametric approach, European Journal of Operational Research, Vol. 98, No. 2, Pages 408-418 58. Nag, B.; Banerjee, S.; Chatterjee, R., (2007), Changing features of the automobile industry in Asia, Asia-pacific research and training network on trade, Working Paper Series, No. 37, Pages 1-48 59. Nagadevara, V.; Ramanayya, T. V. (2010), INTER-TEMPORAL SHIFTS IN EFFICIENCY IN A ROAD TRANSPORT ORGANIZATION., Journal of the Academy of Business & Economics, Vol. 10, No. 1, Pages 139-144 60. OECD (2009), "Automotive Components", in OECD, Sector Specific Sources of Competitiveness in the Western Balkans: Recommendation for a Regional Investment Strategy, OECD Publishing 61. Papahristodoulou, C. (1997), A DEA model to evaluate car efficiency. Applied Economics, Vol. 29, No. 11, Pages 1493-1508 62. Paradi, J. C.; Schaffnit, C. (2004), Commercial branch performance evaluation and results communication in a Canadian bank- a DEA application, European Journal of operational research, Vol. 156, No. 3, Pages 719-735 63. Parkan, C. (1987), Measuring the efficiency of service operations: An application to bank branches, Engineering Costs and Production Economics, Vol. 12, No. 1-4, Pages 237-242 64. Pavlinek, P.; Zenka, J., (2010), Upgrading in the automotive industry: firm-level evidence from Central Europe, Journal of Economic Geography, Pages 1-28 65. Poli, P. M.; Scheraga, C. A. (2001), A Quality Assessment of Motor Carrier Maintenance Strategies: An Application of Data Envelopment Analysis., Quarterly Journal of Business & Economics, Vol. 40, No. 1, Pages 1-25 66. Porter, M. E. (2000), “Location, Competition and Economic Development: Local Clusters in a Global Economy”, Economic Development Quarterly, Vol.14, No. 1, Pages 15-34 67. Reddy, K. R.; Reddy, C. S. R.; Sarojamma, B.; Subramanyam, T. (2009), Controlling Input -- Output Weights, Ranking of DMUs in DEA., International Journal of Statistics & Systems, Vol. 4, No. 2, Pages 149-166 68. Reiner, G.; Hofmann, P., (2006), Efficiency analysis of supply chain processes., International Journal of Production Research, Vol. 44, No. 23, Pages 5065-5087 69. Rhys D. G. O., (2004), The Motor Industry in an Enlarged EU, The World Economy, Vol. 27, No. 6, Pages 877-900 70. SAE - Society of Automotive Engineers, (2000), World Congress, Detroit, Michigan 71. Sapienza, P.; Zingalesb, L.; Maestripieric, D., (2009), Gender differences in financial risk aversion and career choices are affected by testosterone, PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, Vol. 106, No. 36, Pages 15268-15273 72. Seiford, L. M.; Zhu, J. (1999), Profitability and Marketability of the top 55 U.S. Commercial Banks, Management Science, Vol. 45, No. 9, Pages 1270-1288. 73. Sinha, K. K. (1997), Moving frontier analysis: An application of Data Envelopment Analysis for competitive analysis of a high-technology manufacturing plant., Annals of Operations Research, Vol. 73, No. 1-4, Pages 197-218 74. Spronk, J.; Vermeulen, E. M. (2003), Comparative performance evaluation under uncertainty, European Journal of Operational Research, Vol. 150, No. 3, Pages 482-495 75. Sturgeon, T. J.; Memedovic, O.; Biesebroeck, J. V.; Gereffi, G. (2009), Globalisation of the automotive industry: main features and trends, Int. J. Technological Learning, Innovation and Development, Vol. 2, No. 1/2, Pages 1-18 76. Sufian, F. (2010), The Impact of Risk on Banks'' Technical and Scale Efficiency: Empirical Evidence from the Chinese Banking Sector. IUP Journal of Financial Economics, Vol. 8, No. 1/2, Pages 82-102 77. Talluri, S.; Vickery, S. K.; Droge, C. L. (2003), Transmuting performance on manufacturing dimensions into business performance: an exploratory analysis of efficiency using DEA. International Journal of Production Research, Vol. 41, No. 10, Pages 2107-2123 78. Tsai, H.-C., Chen, C.-M.; Tzeng, G.-H. (2006), The comparative productivity efficiency for global telecoms, International Journal of Production Economics, Vol. 103, No. 2, Pages 509-526 79. Zhao, X.-J.; Wang, S.-Y. (2007), Empirical Study on Chinese Mutual Funds' Performance, Systems Engineering - Theory & Practice, Vol. 27, No. 3, Pages 1-11 80. Zhu, D.-S., Ho, C.-T.; Lin, L.-H. (2005), A Study on the Performance Evaluation of Taiwan's Newly Reorganized Banks, Sun Yat-Sen Management Review, Vol. 13, No. 5, Pages 125-157. 81. Zhu, J. (2000), Multi-factor performance measure model with an application to Fortune 500 companies, European Journal of Operational Research, Vol. 123, No. 1, Pages 105-124 WWW sources: 1. AI - Automotive industries - Automotive Industries magazine, founded in 1895 2. AIA, (2010), Přehled výroby a odbytu vozidel domácích značek (Production and sale of domestically produced vehicles). Prague: Czech Automotive Industry Association. 3. "Automobile industry. “, The Columbia Encyclopedia, Sixth Edition, (2008), 4. Centre for automotive industry research (CAIR) 5. CzechInvest - Government organization under the Czech Ministry of the Industry and Trade 6. Czech Statistical Office (CSO) 7. Ministry of the Environment of the Czech Republic (MoE) 8. Ministry of the Industry and Trade of the Czech Republic (MIT) 9. Ministry of Justice of the Czech Republic (MoJ) 10. NACE International - is a professional organization for the corrosion control industry established in 1943. 11. OICA, (2010) World Motor Vehicle Production by Country and Type, 1997-2008. Paris: Organisation Internationale des Constructeurs d'Automobile. Data sources: 1. The data used to compare companies come from the annual reports of companies for the years 2004-2008.
摘要: 股東權益報酬率能反應出公司的經營績效,因此是投資人選股時的重要考量,而績效可視為由效能和效率所組成; 除此之外,風險也是投資時參考的重要指標。因此,本研究目的是探討捷克汽車公司的效能、效率、績效和風險之間的關係。 汽車產業做為捷克的重要產業行之有年,學界和業界的緊密聯結加上實力深厚的工業傳承為捷克創造出超越其他中東歐國家、具競爭力的創新優勢。捷克是汽車製造及設計相關活動密集度極高的國家之一,而且在汽車方面的研發計畫為全歐之冠。作為具有容納三個大車廠能力和資源並賦予供應商極佳商機的國家,捷克試圖鞏固其做為歐洲汽車相關設計及研發中心之一的領導地位。 大部分關於評估公司績效的研究只著重在經營效率。然而,適當地處理經營效能會對公司收益產生重要影響。不幸的是,這部分常被忽略。本研究運用兩階段的資料包絡分析法(Data Envelopment Analysis, DEA),就捷克汽車產業的31家公司分別進行績效的評估。第一階段分別就效率和效能進行公司經營績效評估,第二階段使用權益乘數(Equity Multiplier, EM)進行財務風險評估。 此基於報酬的模式對管理者和投資人都有用。對管理者而言,本模式提供校正報酬之公司績效評估方式。對投資人而言,則提供了選股新策略。 本研究從實證結果得知,對於捷克汽車工業而言,有較好效率的公司,不必然效能較高。兩者之間並無相關。就報酬而言,公司效能比經營效率更重要。公司的經營績效和資本結構對報酬有直接影響。
Return on equity correspondents to company performance and represents important concern for investors while making stock selections. Performance itself can be understood as mutual participation of effectiveness and efficiency. Another but not less important indicator for investors is risk. Hence, the goal of this study is to examine the relationship between effectiveness, efficiency, performance and risk of automotive companies in Czech Republic. Automotive has been a key industry in Czech Republic for years. The interrelationship between very strong academic and institutional base and deep-rooted engineering tradition creates a culture of competitive innovation advantage that puts the country apart from others, exceedingly in Central and Eastern Europe. The Czech Republic hosts one of the highest concentrations of automotive-related manufacturing and design activity in the world and secured more automotive R&D projects than any other country in Europe. While the country has the capacity and resources to accommodate three major vehicle plants and holds excellent business opportunities for suppliers, the Czech Republic is poised to consolidate its position as one of the leading European centers for automotive-related design and R&D activity. Most of the previous studies concern companies' performance evaluation solely on operational efficiency. Nevertheless, properly handle the operational effectiveness importantly influences the companies' return. Unfortunately, this factor is usually ignored. As a result, this study proposes Data Envelopment Analysis (DEA) model with two processes to measure performance of 31 listed automotive companies in Czech Republic; Process (I) that separates efficiency and effectiveness to assess a companies'' operational performance, and Process (II) measures the degree of financial risk based on an equity multiplier perspective. This return based model is useful for both managers and investors. For managers, it provides return-adjusted performance evaluation process. For investors, it provides a new strategy to stock selection. Empirical results of this study shows that for the Automotive industry in Czech Republic, the companies with better efficiency, not necessary has better effectiveness. There is no correlation between these two indicators. The effectiveness of a company is more important than operating efficiency in term of return. Operational performance and Capital structure of the company has direct effect on its return.
其他識別: U0005-1001201110532200
Appears in Collections:科技管理研究所



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