Measuring the Academic Efficiency of the Four Campuses of the University for Development Studies Using Data Envelopment Analysis

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2012-06-15
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The purpose of this paper is to utilize data envelopment analysis (DEA) to measure academic efficiency of the four campuses of University for Development Studies. DEA has been recognized as a robust tool that is used for evaluating the performance of profit and non-profit institutions. The proposed approach is deployed based on empirical data collected from the four campuses. On an efficiency scale of 0–1.0, DEA analysis assesses the relative efficiency of every campus relative to the rest of the campuses in terms of academic performance. For inefficient campuses, DEA analysis provides quantitative guidance on how to make them efficient. The 2010/11 academic year data from the four campuses of University for Development Studies were used. Four input variables and five output variables were identified. The input variables were lecture to student ratio, cost per student, library facilities and academic staff to non-academic staff ratio. Output variables were estimated as: classes obtained (that is first class, second class upper, second class lower, third class and pass). Three campuses (Tamale, Nyankpala and Wa) formed the efficiency frontier and the fourth campus (Navrongo) was found inefficient for the academic year. There was an indication that reduction in academic staff to non-academic staff ratio as input has a larger effect on efficiency of Navrongo campus than does in input cost per student ratio. For Navrongo campus to be on the efficiency frontier , it is better for cost per student ratio as input to be reduced more than the library facilities. Keywords: Data Envelopment Analysis, efficiency frontier, quantitative guidance, relative efficiency, empirical data, inefficient and profit and non-profit institutions,
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A Thesis submitted to the Institute of Distance Learning, Kwame Nkrumah University of Science and Technology, Kumasi in partial fulfillment of the requirements for the degree of Master of Science in Industrial Mathematics, June-2012
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