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

Abstract

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.

Total Quality Management Boosters and Blockers in a Humanitarian Setting: An Exploratory Investigation

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A decision framework proposal for customer order prioritization: A case study for a structural steel company

“…Due to dealing with a network model, fuzzy cognitive maps (FCMs) that allow dynamic modeling of a system in consideration of a complex network structure can be chosen but the main purpose of the FCM is to determine the causal relationships between factors and tries to find the effects of factors on others in the long run (Kutlu and Kadaifci, 2014;Yaman and Polat, 2009). On the other hand, System Dynamics that captures the causal relationships and interdependence of the factors (Tesfamariam and Lindberg, 2005) and The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method which is used for presenting the complex structure of causal relationships between factors (Jassbi et al, 2011) can also be used.…”

An Integrated Fuzzy Cognitive Map Approach in Modelling Factors of Management Quality in Banking Performance

“…An FCM was generated for the study by combining the fuzzy set theory and neural networks from the basic cognitive mapping method (Kosko, 1986). An FCM map can be used to represent the complex and dynamic behaviour of the elements within a system (Can Kutlu & Kadaifci, 2014). Because of its ability to model complex and ambiguous systems with fuzziness and uncertainty, researchers have used this tool Berger et al (2001), Gasbarro, Sadguna and Zumwalt (2002), Khalid (2006), Cooper (2009), Kumar et al, (2012) across various applications (Katiyar et al, 2018;Uzochukwu et al, 2016).…”

“…Applications of FCM can be seen in total quality management (TQM) and vendor selections as well. Can Kutlu and Kadaifci (2014) have used FCM to analyse the critical success factors of TQM in order to help the decision makers to better understand their interrelations. Hanafizadeh and Zadeh (2015) have used FCM to combine mental maps in order to design a solution for vendor selection.…”

“…Cognitive maps (CMs) are a diagrammatic and causative representation of complex systems (Can Kutlu & Kadaifci, 2014). The CM is a digraph composed of nodes and edges, where nodes represent variables or factors describing a real-world system, and edges represent the causal relationships that exist between them.…”