成功大學博碩士論文系統

簡易檢索 / 詳目顯示

回結果列表

研究生：	約書亞 Barnaby, Joshua
論文名稱：	The Efficiency of Canada’s Tertiary Educational Industry Utilizing Data Envelopment Analysis The Efficiency of Canada’s Tertiary Educational Industry Utilizing Data Envelopment Analysis
指導教授：	楊曉瑩 Yang, Ann Shawing
學位類別：	碩士 Master
系所名稱：	管理學院 - 國際經營管理研究所碩士班 Institute of International Management (IIMBA--Master)
論文出版年：	2009
畢業學年度：	97
語文別：	英文
論文頁數：	95
中文關鍵詞：	Performance indicators 、University efficiency 、Data Envelopment Analysis
外文關鍵詞：	Performance indicators, University efficiency, Data Envelopment Analysis
相關次數：	點閱：62 下載：2
分享至:	分享至facebook 分享至twitter

查詢本校圖書館目錄查詢臺灣博碩士論文知識加值系統勘誤回報

Educational budgets for universities are a substantial portion of national budgets. The nature of how they are funded has evolved substantially over time. In the last few decades there has been renewed scrutiny of how these institutions manage public money. This has only been exacerbated by the current international economic situation.
The application of data envelopment analysis (DEA) was applied in this study. DEA allows for the evaluation of multiple inputs and outputs to determine efficiency. DEA will also identify strengths and weaknesses of decision making units. The efficiency distribution of Canadian universities is the primary objective of this study. Forty-five of Canada’s leading universities were selected. They were then separated into three groups. The groups were medical-doctoral universities, comprehensive universities and finally undergraduate universities to ensure the homogeneous decision making units were being evaluated.
The study develops a framework to evaluate the efficiency of universities educational and research production using properly identified inputs and outputs. Secondly it evaluated the efficiency of universities relative to location to determine if different regional policies determine the level of operating efficiency. Finally it explored the relationship of operational efficiency relative to tuition prices to determine if there is a relationship between price liberalization and tuition cost.

ACKNOWLEDGEMENTS ........................................................................................... I
ABSTRACT .................................................................................................................. II
TABLE OF CONTENTS ............................................................................................. III
LIST OF TABLES ..................................................................................................... VII
LIST OF FIGURES ..................................................................................................... IX
CHAPTER ONE INTRODUCTION ............................................................................. 1
1 Research Background. ..................................................................................... 1
2 Research Motivation. ....................................................................................... 4
3 Research Objectives. ........................................................................................ 5
4 Research Structure. .......................................................................................... 6
5 Research Contribution. .................................................................................... 9
6 Scope and Limitation of this Study. ................................................................. 9
CHAPTER TWO LITERATURE REVIEW ............................................................... 10
1 A Conceptual Model of Education Production. ............................................. 10
2 Defining Efficiency and Productivity. ........................................................... 10
3 Types of Measured Efficiency. ....................................................................... 11
4 Approaches to Measuring Efficiency. ............................................................ 12
5 Principle Agent Theory. ................................................................................. 14
6 Market versus Government Governed Organizations Efficiency Trends. ..... 14
7 Data Envelopment Analysis. .......................................................................... 15
8 Homogenous Decision Making Units. ........................................................... 15
9 DEA Models. .................................................................................................. 16
10 Variable Selection. ....................................................................................... 17
11 The Conceptual Model. ................................................................................ 21
11.1 Educational Policy and Efficiency. .................................................... 21
11.2 Efficient Market Hypothesis. ............................................................. 22
11.4 Summary of Hypotheses. .................................................................... 23
12 A Summary. .................................................................................................. 24
CHAPTER THREE CANADA‟S TERTIARY EDUCATION FRAMEWORK ........ 25
1 Previous DEA Studies Applied in Canada. .................................................... 25
1.1 McMillan and Datta (1998). ............................................................... 25
1.2 McMillan and Chan (2006). ................................................................ 26
2 Canada‟s University Environment. ................................................................ 26
3 Unique DEA Opportunity............................................................................... 30
CHAPTER FOUR RESEARCH DESIGN AND METHODOLOGY ........................ 32
1 Research Framework. .................................................................................... 32
1.1 DEA Model. ......................................................................................... 32
1.2 CCR and VRS DEA Model. ................................................................. 33
1.3 Model Application. .............................................................................. 34
2 The Research Variables. ................................................................................. 35
2.1 Input Variables. ................................................................................... 35
2.2 Output Variables. ................................................................................. 35
3 Sampling Plan. ............................................................................................... 36
4 Data Collection. ............................................................................................. 38
5 Data Evaluation. ............................................................................................. 39
5.1 Descriptive Statistic Analysis. ............................................................. 39
5.2 Correlation Analysis of Variables. ....................................................... 40
5.3 Measuring the efficiency of Universities. ............................................ 40
5.4 Efficiency Scores.................................................................................. 40
5.5 Peer DMU Benchmarking. .................................................................. 40
5.6 Distribution of Technical Efficiency Scores. ....................................... 41
CHAPTER FIVE RESEARCH ANALYSIS AND DISCUSSIONS .......................... 42
1 Introduction. ................................................................................................... 42
2 Data. ............................................................................................................... 42
3 Variable Description. ...................................................................................... 44
3.1 Input Variable Description. ................................................................. 44
3.2 Output Variable Description. .............................................................. 44
4 Descriptive Statistics Table. ........................................................................... 45
5 Correlation Analysis. ...................................................................................... 48
6 Efficiency Scores. .......................................................................................... 51
5 Total Potential Improvements of CRSTE Technical Efficiency. .................... 54
7 The Efficiency Scores and Benchmarking Partners. ...................................... 56
8 Distribution of Efficiency Scores. .................................................................. 59
9 Regional Analysis. ......................................................................................... 61
10 Tuition Analysis. .......................................................................................... 66
CHAPTER SIX CONCLUSIONS AND SUGGESTIONS ......................................... 69
1 Introduction. ................................................................................................... 69
2 Conclusions. ................................................................................................... 69
2.1 Importance of Efficiency Analysis. ...................................................... 69
2.2 The Results of Data Envelopment Analysis. ........................................ 70
2.3 Applying Data Envelopment Analysis to Canadian Universities. ....... 71
2.4 In Relation to Previous Literature. ...................................................... 71
3 Suggestions. ................................................................................................... 73
3.1 Future DEA Model Adoption. .............................................................. 73
3.2 Isotopic Issues. .................................................................................... 73
3.3 Concluding Suggestions. ..................................................................... 74
REFERENCES ............................................................................................................ 78
APPENDICES ............................................................................................................. 87
Appendix 1: Data Tables for Medical-Doctorial Universities Auxiliary and Input Variables ........................................................................................................ 87
Appendix 2: Data Tables for Medical-Doctorial Universities Output Variables . 88
Appendix 3: Summary of Slacks for Medical-Doctorial Universities ................. 89
Appendix 4: Data Tables for Comprehensive Universities Auxiliary and Input Variables ........................................................................................................ 90
Appendix 5: Data Tables for Comprehensive Universities Output Variables ...... 91
Appendix 6: Summary of Slacks for Comprehensive Universities ..................... 92
Appendix 7: Data Tables for Undergraduate Universities Auxiliary and Input Variables ........................................................................................................ 93
Appendix 8: Data Tables for Undergraduate Universities Output Variables ....... 94
Appendix 9: Summary of Slacks for Undergraduate Universities ....................... 95
                                    

Abbott, M., & Doucouliagos, C. (2003). The efficiency of Australian universities: A data envelopment analysis. Economics of Education Review, 22(1), 89-97.
Aghion, P. (2007). Growth and the financing and governance of education. Keynote lecture of the 2007 Meeting of the German Economic Association.
Aghion, P., Dewatripont, M., Hoxby C., Mas-Colell, A. & Sapir, A. (2007). Why reform Europe‟s universities? Bruegel Policy Brief, 2007/04.
Ahn, T., Charnes, A., & Cooper, W.W. (1988). Some statistical and DEA evaluations of relative efficiencies of public and private institutions of higher learning. Socio-economic Planning Sciences 22(6), 259-269.
Ahn, T., Charnes, A., & Cooper, W. W. (1989). DEA and ratio efficiency analysis for public institutions of higher learning in Texas. Research in Governmental and Nonprofit Accounting, 5, 165-185.
Aidt, T. S. (2003). Economic analysis of corruption: A survey. The Economic Journal, 113(491), 632-652.
Asmild, M., Paradi, J. C., & Pastor, J. T. (2009). Centralized resource allocation BCC models. Omega, 37(1), 40-49.
Astin, A. W., & Inouye, C. J. (1988). How public policy at the state level affects private higher education institutions. Economics of Education Review, 7(1), 47-63.
Athanassopoulos, A.D, & Shale, E. (1997). Assessing the comparative efficiency of higher education institutions in the UK by means of data envelopment analysis. Education Economics, 5(2), 117-134.
Avkiran, N. K. (2001). Investigating technical and scale efficiencies of Australian Universities through data envelopment analysis. Socio-Economic Planning Sciences, 35(1), 57-80.
Bal, H., Örkcü, H. H., & Çelebioglu, S. (2008). A new method based on the dispersion of weights in data envelopment analysis. Computers & Industrial Engineering, 54(3), 502-512.
Banker, R. D. (1984). Estimating most productive scale size using data envelopment analysis. European Journal of Operational Research, 17(1), 35-44.
79
Belfield, C. R., & Fielding, A. (2001). Measuring the relationship between resources and outcomes in higher education in the UK. Economics of Education Review, 20(6), 589-602.
Blaug, M. (1982). The costs of higher education. How much do colleges and universities spend per student and how much should they spend? International Journal of Educational Development, 2(1), 91-92.
Bolton, P., & Mehran, H. (2006). An introduction to the governance and taxation of not-for-profit organizations. Journal of Accounting & Economics, 41(3), 293-305.
Brinkman, P. T. (1990). Higher education cost functions. In S.A. Hoenack & E.I. Collins (Eds.). The economics of American universities. Buffalo, NY: State University of New York Press.
Brown, K. W. (1994). Private-college financial results and their effect on tuition-rate policies. Journal of Accounting & Public Policy, 13(1), 1-29.
Caballero, R., Galache, T., Gómez, T., Molina, J., & Torrico, A. (2004). Budgetary allocations and efficiency in the human resources policy of a university following multiple criteria. Economics of Education Review, 23(1), 67-74.
Cameron, D. (2000). Equity and purpose in financing universities: The case of Nova Scotia. Canadian Public Administration, 43(3), Fall.
Cameron, D. (2005). Post-secondary education and research: Whither Canadian federalism. Taking public universities seriously. Toronto: University of Toronto Press.
Charnes, A., & Cooper, W. W. (1985). Preface to topics in Data Envelopment Analysis. Annals of Operations Research, 2, 59-94.
Charnes, A., & Cooper, W. W. (1978). Managerial economics: Past, present and future. Journal of Enterprise Management, 1(1), 5-23.
Charnes, A., & Cooper, W. W. (1959). Chance-constrained programming. Management Science, 6(1), 73-79.
Charnes, A., Cooper, W. W., Lewin, A. Y., Morey, R. C., & Rousseau, J. (1985). Sensitivity and stability analysis in DEA. Annals of Operations Research, 2, 139-156.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Charnes, A., Cooper, W. W., Seiford, L., & Stutz, J. (1982). A multiplicative model for efficiency analysis. Socio- Economic Planning Sciences, 16, 223-224.
80
Charnes, A., Cooper, W. W., Seiford, L., & Stutz, J. (1983). Invariant multiplicative efficiency and piecewise Cobb-Douglas envelopments. Operations Research Letters, 2(3), 101-103.
Chen, Y. (2004). Ranking efficient units in DEA. Omega, 32(3), 213-219.
Coelli, T. (1996). Assessing the performance of Australian universities using data envelopment analysis. Internal report, Centre for Efficiency and Productivity Analysis, University of New England.
Conceição, P., Heitor, M. V., Sirilli, G., & Wilson, R. (2004). The "swing of the pendulum" from public to market support for science and technology: Is the U.S. leading the way? Technological Forecasting and Social Change, 71(6), 553-578.
Cooper, W.W., Seiford, L.M., & Tone, K. (2000). Data Envelopment Analysis: A comprehensive text with models, applications, references and DEA-solver software. Kluwer, Norwell, MA.
Dorfman, J. H., & Koop, G. (2005). Current developments in productivity and efficiency measurement. Journal of Econometrics, 126(2), 233-240.
Dyson, R. G., Allen, R., Camanho, A. S., Podinovski, V. V., Sarrico, C. S., & Shale, E. A. (2001). Pitfalls and protocols in DEA. European Journal of Operational Research, 132(2), 245-259.
Emrouznejad, A., Parker, B. R., & Tavares, G. (2008). Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA. Socio-Economic Planning Sciences, 42(3), 151-157.
Esping-Andersen, G. (2001). Social welfare policy: Comparisons. In International Encyclopedia of the Social & Behavioral Sciences (pp. 14481-14485). Oxford: Pergamon.
Fandel, G. (2007). On the performance of universities in North Rhine-Westphalia, Germany: Government's redistribution of funds judged using DEA efficiency measures. European Journal of Operational Research, 176(1), 521-533.
Finnie, R. & Schwartz, S. (1996). Student loans in Canada: Past, present, and future. Toronto, ON: C.D. Howe Institute.
Foot, D. K. (1996). Boom bust echo 2000. Toronto: Macfarlane, Walter and Ross.
Garcia-Aracil, A., Gracia, A. G., & Perez-Martin, M. (2006). Analysis of the evaluation process of the research performance: An empirical case. Scientometrics, 67, 213-230.
Garrett-Jones, S., & Aylward, D. (2000). Some recent developments in the evaluation of university research outcomes in the United Kingdom. Research Evaluation, 9, 69-75.
81
Geuna, A., & Martin, B. R. (2003). University research evaluation and funding: An international comparison, Minerva, 41, 277-304.
Glass, J. C., McCallion, G., McKillop, D. G., & Stringer, K. (2006). A technically level playing-field' profit efficiency analysis of enforced competition between publicly funded institutions. European Economic Review, 50(6), 1601-1626.
Gordon, T., Fischer, M., Malone, D., & Tower, G. (2002). A comparative empirical examination of extent of disclosure by private and public colleges and universities in the United States. Journal of Accounting and Public Policy, 21(3), 235-275.
Grob, U., & Wolter, S. C. (2007). Demographic change and public education spending – A conflict between young and old. Education Economics, 15, 277-292.
Hanushek, E. (1989). The impact of differential expenditures on school performance. Educational Research, 18(4), 45-62.
Hanushek E. (1986). The economics of schooling: Production and efficiency in public schools. Journal of Economic Literature, 24(3), 1141-1171.
Harris, A. R., Evans, W. N., & Schwab, R. M. (2001). Education spending in an aging America. Journal of Public Economics, 81(3), 449-472.
Harris, M., & Raviv, A. (1978). Some results on incentive contacts with applications to education and employment, health insurance, and law enforcement. American Economic Review, 68, 20-30.
Heidenheimer, A. J., Neil, J. S., & Paul, B. B. (2001). Educational policy: Comparative perspective. In International Encyclopedia of the Social & Behavioral Sciences (pp. 4296-4302). Oxford: Pergamon.
Higgins, J. C. (1989). Performance measurement in universities. European Journal of Operational Research, 38, 358-368.
Huff, W. D. (2000). Colleges and universities: survival in the information age. Computers & Geosciences, 26(6), 635-640.
Izadi, H., Johnes, G., Oskrochi, R., & Crouchley, R. (2002). Stochastic frontier estimation of a CES cost function: The case of higher education in Britain. Economics of Education Review, 21, 63-71.
Jensen, M. C., & Meckling, W. H. (1976). Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of Financial Economics, 3, 303-360.
Johnes, J. (2006a). Data envelopment analysis and its application to the measurement of efficiency in higher education. Economics of Education Review, 25(3), 273-288.
82
Johnes, J. (2006b). Measuring teaching efficiency in higher education: An application of data envelopment analysis to economics graduates from UK Universities 1993. European Journal of Operational Research, 174(1), 443-456.
Johnes, G., & Johnes, J. (2009). Higher education institutions' costs and efficiency: Taking the decomposition a further step. Economics of Education Review, 28(1), 107-113.
Johnes, J., & Johnes, G. (1995). Research funding and performance in U.K. university departments of economics: A frontier analysis. Economics of Education Review, 14, 301-14.
Jongbloed, B. W. A., Koelman, J. B. J., Goudriaan, R., de Groot, H., Haring, H. M. M. & van Ingen, D. C. (1994). Kosten en Doelmatigheid van het Hoger Onderwijs in Nederland, Duitsland en Groot- Brittannië. Beleidsgerichte Studies Hoger Onderwijs en Wetenschappelijk Onderzoek 35, Ministerie van Onderwijs, Cultuur en Wetenschappen. Den Haag: SDU.
Jongbloed, B. W. A., & Koelman, J. B. J. (1996). Universiteiten en Hogescholen vergeleken, Beleidsgerichte Studies Hoger Onderwijs en Wetenschappelijk Onderzoek 38, Ministerie van Onderwijs, Cultuur en Wetenschappen. Den Haag: SDU.
Jongbloed, B. W. A., & Salerno, C. (2003). Funding and recognition: A comparative study of funded versus non-funded higher education in eight countries. The Netherlands: Cheps, Center for Higher Education Policy Studies University of Twente.
Kao, C. (2006). Interval efficiency measures in data envelopment analysis with imprecise data. European Journal of Operational Research, 174(2), 1087-1099.
Kao, C., & Hung, H.T. (2008). Efficiency analysis of university departments: An empirical study. Omega, 36(4), 653-664.
Kao, C., & Pao, H. T. (2009). An evaluation of research performance in management of 168 Taiwan universities. Scientometrics, 78(2), 261-277.
Kells, H. R., ed. (1993). The development of performance indicators for higher education. Paris: OECD.
Kedrosky, P. (2003). Elementary math: The best universities have the most money. Financial Post, FP13.
King, W. D. (1997). Input and output substitution in higher education. Economic Letters, 57, 107-111.
Kokkelenberg, E. C., Dillon, M., & Christy, S. M. (2008). The effects of class size on student grades at a public university. Economics of Education Review, 27(2), 221-233.
83
Kuo, J.-S., & Ho, Y.-C. (2007). The cost efficiency impact of the university operation fund on public universities in Taiwan. Economics of Education Review, 27(5), 603-612.
Lewis, H. F., & Sexton, T. R. (2004). Data envelopment analysis with reverse inputs and outputs. Forthcoming in Journal of Productivity Analysis, 21, 113-132.
Mar Molinero, C. (1996). On the joint determination of efficiencies in a data envelopment analysis context. Journal of the Operational Research Society, 47(10), 1273-79.
Marinova, D., & Newman, P. (2008). The changing research funding regime in Australia and academic productivity. Mathematics and Computers in Simulation, 78(2-3), 283-291.
Massow, V. (1983). The role of universities in economic development: National, regional, and international. Technology in Society, 5(3-4), 261-267.
Massy, W. (1989). Productivity improvement strategies for college and university administration and support services. Paper presented at the Forum for College Financing.
McMillian, M., & Chan, W. (2006). University efficiency: A comparison and consolidation of results from stochastic and non-stochastic methods. Education Economics, 14(1), 1-30.
McMillan, M.L., & Datta, D. (1998). The relative efficiency of Canadian universities. Canadian Public Policy, 24(4), 485-511.
Munroe-Blum, H. (2005). Funding Canada‟s universities: Research thrives in a culture of excellence. Institute for Research on Public Policy.
McPherson, M. S., Schapiro, M. O., Hanushek, E., & Welch, F. (2006). Chapter 24 US Higher Education Finance. In Handbook of the Economics of Education 2, 1403-1434.
Nelson, R. R. (2004). The market economy, and the scientific commons. Research Policy, 33(3), 455-471.
Nelson, R., & Hevert, K. T. (1992). Effect of class size on economies of scale and marginal costs in higher education. Applied Economics, 24, 473-482.
Nunamaker, T. R. (1985). Using data envelopment analysis to measure the efficiency of non-profit organizations: A critical evaluation. Managerial and Decision Economics, 6(1), 50-58.
Nicholson, W. (1995). Microeconomic theory: Basic principles and extensions. New York: The Dryden Press.
Parpala, A., & Lindblom-Ylänne, S. (2007). University teachers‟ conception of good teaching in the units of high-quality education. Studies in Educational Evaluation, 33(3-4), 355-370.
84
Pedraja-Chaparro, F., Salinas-Jimenez, J., Smith, P. (1997). On the role of weight restrictions in data envelopment analysis. Journal of Productivity Analysis, 8, 215-30.
Phelan, T. J. (2000). Bibliometrics and the evaluation of Australian sociology, Journal of Sociology, 36, 345–363.
Post, T., & Spronk, J. (1999). Performance benchmarking using interactive data envelopment analysis. European Journal of Operational Research, 115, 472-87.
Poterba, J. M. (1997). Demographic structure and the political economy of public education. Journal of Policy Analysis and Management, 16, 48-66.
Robst, J. (2001). Cost efficiency in public higher education institutions. Journal of Higher Education, 72(6), 730-750.
Ross, S. (1973). The economic theory of agency: The principal‟s problem. American Economic Review, 63(2), 134-139.
Rhodes, E. L., & Southwick, L., Jr. (1993). Variations in public and private university efficiency. Applications of management science, Greenwich, Connecticut: JAI Press, Inc.
Rosser, J. J. B. (2005). The road to serfdom and the world economy: 60 years later. European Journal of Political Economy, 21(4), 1012-1025.
Ruggiero, J., Miner, J., & Blanchard, L. (2002). Measuring equity of educational outcomes in the presence of inefficiency. European Journal of Operational Research, 142(3), 642-652.
Salerno, C. S. (2002). On the technical and allocative efficiency of research-intensive higher education institutions. Unpublished doctoral dissertation. The Pennsylvania State University: University Park, PA.
Scheel, (2001). Undesirable outputs in efficiency valuations. European Journal of Operational Research, 132, 400-410.
Sengupta, J. K. (1996). Economic theory and DEA models: A critical review. International Journal of Systems Science, 27(1), 77-85.
Sexton, T. R. (1986). The methodology of data envelopment analysis‟. In R. H. Silkman, Measuring Efficiency: An Assessment of Data Envelopment Analysis, Jossey-Bass Publishers, San Francisco.
Siegfried, J. J., Sanderson, A. R., & McHenry, P. (2007). The economic impact of colleges and universities. Economics of Education Review, 26(5), 546-558.
Sinuany-Stern, Z., Mehrez, A., & Barboy, A. (1994). Academic departments efficiency via DEA. Computers & Operations Research, 21(5), 543-556.
Schloegl, C., Gorraiz, J., Bart, C., Bargmann, M. (2003). Evaluating two Austrian university departments: Lessons learned. Scientometrics, 56, 287-299.
85
Skinner, J. (1994). What do stochastic frontier cost functions tell us about inefficiency? Journal of Health Economics, 13(3), 323-328.
Smith, S. L. (1991) Report of the Commission of Inquiry on Canadian University Education. Ottawa: AUCC.
Spence, M., & Zeckhauser, R. (1971). Insurance, information and individual action. American Economic Review, 61(2), 380-387.
Statistics Canada. (2004). Average undergraduate tuition fees for full-time students, by discipline, by province (table). Canadian Statistics. Last updated September 1st, 2004. http://www40.statcan.gc.ca/l01/cst01/educ50a-eng.htm (accessed December 20th, 2008).
Statistics Canada. (2008). Provincial and territorial general government revenue and expenditure, Canada (table). Canadian Statistics. Last updated June 25th, 2008. http://www40.statcan.gc.ca/l01/cst01/govt04a-eng.htm (accessed December 20th, 2008).
Statistics Canada. (2008). Universities and colleges revenue and expenditures, by province and territory (table). Canadian Statistics. Last updated June 25th, 2008. http://www40.statcan.gc.ca/l01/cst01/govt41a-eng.htm (accessed December 20th, 2008).
Statistics Canada. (2006). University enrolments by program level and instructional program (table). Canadian Statistics. Last updated April 23rd, 2008. http://www40.statcan.gc.ca/l01/cst01/educ54a-eng.htm(accessed December 20th, 2008).
Stevens, P.A. (2001). The determinants of economic efficiency in English and Welsh universities. National Institute of Economic and Social Research, Discussion paper number 185.
Stevens, P.A. (2005): A stochastic frontier analysis of English and Welsh universities, Education Economics, 13, 355-374.
Tanzi, V. (2008). The future of fiscal federalism. European Journal of Political Economy, 24(3), 705-712.
Tomkins, C., & Green, R. (1988). An experiment in the use of data envelopment for evaluating the efficiency of UK university departments of accounting. Financial Accountability and Management, 44, 147-64.
Vink, M. J. C. (1997). Efficiency in higher education: A comparative analysis on sectoral and institutional level. Twente, The Netherlands: Universiteit Twente.
Weir, M., Neil, J. S., & Paul, B. B. (2001). Welfare State. In International Encyclopedia of the Social & Behavioral Sciences, 16432-16435
West, E. G. (1993). Ending the squeeze on universities. Montreal, PQ: The Institute for Research on Public Policy.
86
Zhu, J. (1996). Robustness of the efficient DMUs in data envelopment analysis. European Journal of Operational Research, 90(3), 451-460.

校內：2014-07-24公開
校外：2014-07-24公開

簡易檢索 / 詳目顯示

相關論文