A fuzzy-logic-based approach to the EFQM model for performance enhancement

Abstract

Institutions could be longstanding if they are consistent with well-defined strategies. Self-assessment activities are among the significant ways to identify the level of reaching strategic objectives of institutions. In recent studies, different TQM models were presented to evaluate organizational performance. The European Foundation for Quality Management (EFQM) excellence model is a commonly used model for self-assessment. In this study, Fuzzy EFQM (FEFQM) model is proposed in order to minimize the calculation deviation of expert opinions and to measure the level of institutionalization more consistently. 'If- then' the rules were produced by utilizing the CN2 induction algorithm in accordance with the current rule base, due to the implementation of Matlab fuzzy logic toolbox takes long time and it has some reliability issues. Two various Fuzzy EFQM models have been established on the basis of the CN2 algorithm with various aggregation methods such as max and sum, in other words, FEFQM(CN2/max) and FEFQM(CN2/sum). The models were applied to 10 institutions and comparisons were made with classical EFQM and FEFQM models. As a result, the FEFQM(CN2/sum) model and the classical EFQM excellence model score were found by the Mean Absolute Percentage Error as 2.33%. In accordance with the experimental findings, it is thought the model can be used as a guide for EFQM assessors and policy makers.