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1 – 3 of 3Saliha Karadayi-Usta and Cigdem Kadaifci
The purpose of this study is to extract factors enabling the digital car sharing enterprises' supply chain resilience (SCR), to interpret different factor prioritizations in terms…
Abstract
Purpose
The purpose of this study is to extract factors enabling the digital car sharing enterprises' supply chain resilience (SCR), to interpret different factor prioritizations in terms of industry representatives’ assessments and specialties, and to discuss the results by applying and comparing different ranking techniques.
Design/methodology/approach
To achieve the purpose, the factors were identified via an in-depth systematic literature review, and next, these factors were examined by industry representatives to gather the decision matrices, then analytic hierarchy process (AHP) and measuring attractiveness by a categorical based evaluation technique (MACBETH) were applied separately to model the decision problem, and finally the findings were interpreted with different participants’ perspectives.
Findings
The findings revealed that the AHP and MACBETH provide nearly identical rankings in terms of main factors by implying the significance of the triple bottom line of sustainability. Therefore, the economic, social, and environmental dimensions of sustainability should be accomplished to obtain a resilient digital car sharing enterprise supply chain. In addition, readiness and agility are the other important factors affecting the enterprises’ resilience, and finally, although digitalization seemed to be the least important one, its sub-factor emerged at the top of the ranking list.
Originality/value
Up to the authors’ knowledge, this is the first study in the literature that focuses on the SCR of car sharing companies, a particular type of digital enterprise, and uses AHP and MACBETH to examine the important factors that might affect the SCR of these companies. Practitioners should take the findings of both methods into account when evaluating the results and determine the short- and long-term strategies accordingly.
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Ahmet Can Kutlu and Cigdem Kadaifci
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…
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.
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