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Exploring the efficiency of Mexican universities: Integrating Data Envelopment Analysis and Multidimensional Scaling
Affiliation:1. ETH Zurich, KOF Swiss Economic Institute, Leonhardstrasse 21, CH-8092 Zurich, Switzerland;2. University of Zurich, Department of Business Administration, Plattenstrasse 14, CH-8032 Zurich, Switzerland;3. University of Pisa, Dipartimento di Ingegneria dell’Energia, dei Sistemi, del Territorio e delle Costruzioni, Pisa, Italy;4. Sapienza University of Rome, Department of Computer, Control and Management Engineering, via Ariosto, 25 Rome, I-00185, Italy;5. Universitat Politècnica de València, ingenio CSIC-UPV, s/n 46022, Valencia, Spain;6. Università della Svizzera italiana, via Lambertenghi 10a, Lugano 6904, Switzerland
Abstract:National policy initiatives require the expenditure of large amounts of resources over several years. It is common for these initiatives to generate large amounts of data that are needed in order to assess their success. Educational policies are an obvious example. Here we concentrate on Mexico׳s “Educational Modernisation Programme” and try to see how this plan has affected efficiency in teaching and research at Mexico׳s universities. We use a combined approach that includes traditional ratios together with Data Envelopment Analysis models. This mixture allows us to assess changes in efficiency at each individual university and explore if these changes are related to teaching, to research, or to both. Using official statistics for 55 universities over a six year period (2007–2012), we have generated 12 ratios and estimated 21 DEA models under different definitions of efficiency. In order to make the results of the analysis accessible to the non-specialist we use models that visualise the main characteristics of the data, in particular scaling models of multivariate statistical analysis. Scaling models highlight the important aspects of the information contained in the data. Because the data is three-way (variables, universities, and years) we have chosen the Individual Differences Scaling model of Carroll and Chang. We complete the paper with a discussion of efficiency evolution in three universities.
Keywords:Performance evaluation  Benchmarking  Efficiency  Data Envelopment Analysis (DEA)  Multidimensional Scaling (MDS)  Higher education
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