Analyzing critical success factors of total quality management by using fuzzy cognitive mapping

Purpose – Total quality management (TQM) is a process and philosophy to achieve customer satisfaction in long term by improving the products, processes and services effectively and efficiently. TQM implementation is turning into a complex practice due to the increasing number of effective factors and key elements labelled as critical success factors (CSFs). The purpose of this paper is to analyse the relations between CSFs of TQM and to provide decision makers has a clear picture of relations by determining the most affecting – both the number of CSFs which this factor affects and the its effect degree on relevant CSFs are higher comparing to other factors – of this factors affected factors – both the number of CSFs and their effect degree on these factors are higher – that influences a successful TQM implementation. Design/methodology/approach – The paper refers to fuzzy cognitive maps (FCMs) that allow dynamic modelling of a system in consideration of a complex network structure and the effects of factors to each other. The method demonstrates causal representations between CSFs under uncertainty to represent the relations and interaction between them and performs qualitative simulations to analyse the factors that have the highest impact on continuous improvement of quality management process. The evaluations are performed by five academicians whose professions are on both the areas of TQM and FCM. Findings – FCM analysis shows how the most affecting and affected factors influence the other CSF in order to manage a successful TQM implementation. Originality/value – The critical factors of TQM implementation are in the focus of most of the empirical studies in the literature. However, none of them considers the dynamic interactions between the factors. This study employs FCM to explore the CSFs that influence the TQM implementation process considering the relations among them to observe the most affecting and affected factors based on the changes of determined CSFs.