Purpose -The aim of the present research is firstly to examine and recognize the quality elements of services in the banks by SERVQUAL instrument and some Islamic banking factors. Secondly, the aim is to prioritize these factors based on fuzzy TOPSIS. Fuzzy logic provides a useful tool for dealing with decisions in which the phenomena are vague. Design/methodology/approach -The present research was performed among bank customers. The required information was gathered through a designed questionnaire. Using fuzzy set theory, customers' perceptions of service quality are generally expressed subjectively in vague linguistic terms, and this paper tries to apply a fuzzy approach to service quality. Findings -The result of this study shows that "short and suitable queue" and "confident and reliable staff" are the most important quality factors in bank service and on the other hand, "being equal with Islamic doctrines" and "accessible branches" are the least significant factors of service quality in the view of Iranian bank customers. Practical implications -The results of the present research will be useful for bank decision makers to pay particular attention to indicators of most or least importance. Originality/value -The concept of ranking quality factors in banking service using fuzzy TOPSIS is a new approach, especially in the field of Islamic banking. Banks have huge budgets, which can then be allocated for indicators of higher importance when the importance of each factor is determined.

The growth of market capitalisation and the number of altcoins (cryptocurrencies other than Bitcoin) provide investment opportunities and complicate the prediction of their price movements. A significant challenge in this volatile and relatively immature market is the problem of predicting cryptocurrency prices

AbstractIn this paper, using a family of confidence intervals, we construct a triangular shaped fuzzy number as the estimator for mean lifetime as well as the estimator for reliability function of a component. We derive the explicit and unique membership functions of these fuzzy estimators. Our attention is on the case where the lifetime has an exponential distribution. Numerical examples are given to show the performance of the method.

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