Trim: 229mm × 152mm vi CONTENTS 2.5 Extensions of AHP 2.5.1 Analytic hierarchy process ordering 2.5.2 Group analytic hierarchy process 2.5.3 Clusters and pivots for a large number of alternatives 2.5.4 AHPSort References 3 Analytic network process 3.1 Introduction 3.2 Essential concepts of ANP 3.2.1 Inner dependency in the criteria cluster 3.2.2 Inner dependency in the alternative cluster 3.2.3 Outer dependency 3.2.4 Influence matrix 3.3 ANP software: Super Decisions 3.3.1 Problem structuring 3.3.2 Assessment of pairwise comparison 3.3.3 Results 3.3.4 Sensitivity analysis 3.4 In the black box of ANP 3.4.1 Markov chain 3.4.2 Supermatrix References 4 Multi-attribute utility theory 4.1 Introduction 4.2 Essential concepts of MAUT 4.2.1 The additive model 4.3 RightChoice 4.3.1 Data input and utility functions 4.3.2 Results 4.3.3 Sensitivity analysis 4.3.4 Group decision and multi-scenario analysis 4.4 In the black box of MAUT 4.5 Extensions of the MAUT method 4.5.1 The UTA method 4.
Purpose
– The purpose of this paper is: to measure school technical efficiency and to identify the determinants of primary school performance.
Design/methodology/approach
– A two-stage data envelopment analysis (DEA) of school efficiency is conducted. At the first stage, DEA is employed to calculate an individual efficiency score for each school. At the second stage, efficiency is regressed on school characteristics and environmental variables.
Findings
– The mean technical efficiency of schools in the State of Geneva is equal to 93 per cent. By improving the operation of schools, 7 per cent (100−93) of inputs could be saved, representing 17,744,656 Swiss francs in 2010. School efficiency is negatively influenced by: operations being held on multiple sites, the proportion of disadvantaged pupils enroled at the school and the provision of special education, but positively influenced by school size (captured by the number of pupils).
Practical implications
– Technically, the determinants of school efficiency are outside of the control of headteachers. However, it is still possible to either boost the positive impact or curb the negative impact. In the context of the State of Geneva, the policy-related implications of the current study could be summarized as follows. New schools or existing multi-site schools should be concentrated on common sites; if this is not possible, the use of information and communication technology in school management and teaching should be developed and encouraged. In order to correct the negative influence of disadvantaged pupils on school performance, policymakers should focus on related social policies, such as pre-school, health, housing and benefits policies, rather than on allocating additional resources to schools. Finally, with an average of 381 pupils per school, school size could be increased to maximize school efficiency.
Originality/value
– Unlike most similar studies, the model in this study is tested for multicollinearity, heteroskedasticity and endogeneity. It is therefore robust. Moreover, one explanatory variable of school efficiency (operations being held on multiple sites) is a truly original variable as it has never been tested so far.
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