Purpose This study aims to measure the effect of customers’ technology readiness and the quality of electronic services on customer satisfaction. Design/methodology/approach The statistical sample included 410 respondents from 24 branches of a private bank. The sampling method was questionnaire. Because of the structural and organizational similarity of private banks and the elimination of nuisance variables, a bank with the most branches and customers has been selected. To test the model, equation modeling was performed to test the hypotheses. Data were collected through a self-developed structured questionnaire, which served as the measurement tool as well. Findings The results of the study showed that technology readiness has a significant and positive effect on customer satisfaction through the quality of self-service. Moreover, the intermediate role of perceived value in this regard was confirmed; however, the role of trust was not confirmed. Originality/value Previous studies have considered technology readiness as an effective factor in the quality of self-service and customer satisfaction. In this study, apart from quality of service in self-service banking and customer satisfaction, two variables of trust and perceived value have been investigated. An attempt has also been made to address some questions, including “what the effect of customer technology readiness on perceived value of self-services as well as customer satisfaction is?” and “how it is possible to improve self-service quality in modern banking based on customer expectations?” or “what effects variables such as trust and perceived value have on customer satisfaction?” Having a glance at the studies done before, it can be understood that so far, there has been no study done using a mixture of these variables, yet societies’ demands for self-service operations grow day by day. It is, therefore, mandatory to study the prerequisites associated with any actions before one is taken. The paper contributes in the following way: trust and perceived value are added to the the study because of their role in customer satisfaction. In addition, for the first time, variables have been studied, which had never been under focus in any studies in developing countries before.

This paper presents a general review of intellectual capital literature, which includes definitions, components and indicators. We aim to gather a useful collection of indicators and definitions. After studying several related works from the literature, many definitions and indicators are identified and explain that choosing appropriate indicators depends on organizational targets. Every kind of organization can use this study to identify its more applicable and appropriate indicators to know about its intellectual capital. Identifying all of indicators in previous studies can help organization select right indicators for the organization.

No abstract

Predicting the performance of the new product development and selecting the strategy in the case of new product development failure is an issue that has drawn the attention of the many managers. Therefore, the goal of this study is to design an integrated system of prediction of product development success and selection of a proper market-product strategy by the method of artificial intelligence in companies working in the food industry. The population of this study was 250 companies of the food industries in Iran. The inputs and outputs of the success of the new product development were obtained from the research literature. Moreover, Ansoff matrix was applied to select the market-product strategy. A questionnaire was used to collect the data in this study. The adaptive neural-fuzzy network method and the fuzzy inference system are used to analyze the data. The results show that the Chief Executive Officers of companies working in the food industry may take action to predict a new product development success before developing the new product and use alternative strategies if needed.

Purpose The purpose of this paper is to apply fuzzy spectrum in order to collect the vague and imprecise data and to employ the fuzzy U control chart in variable sample size using fuzzy rules. This approach is improved and developed by providing some new rules. Design/methodology/approach The fuzzy operating characteristic (FOC) curve is applied to investigate the performance of the fuzzy U control chart. The application of FOC presents fuzzy bounds of operating characteristic (OC) curve whose width depends on the ambiguity parameter in control charts. Findings To illustrate the efficiency of the proposed approach, a practical example is provided. Comparing performances of control charts indicates that OC curve of the crisp chart has been located between the FOC bounds, near the upper bound; as a result, for the crisp control chart, the probability of the type II error is of significant level. Also, a comparison of the crisp OC curve with OCavg curve and FOCα curve approved that the probability of the type II error for the crisp chart is more than the same amount for the fuzzy chart. Finally, the efficiency of the fuzzy chart is more than the crisp chart, and also it timely gives essential alerts by means of linguistic terms. Consequently, it is more capable of detecting process shifts. Originality/value This research develops the fuzzy U control chart with variable sample size whose output is fuzzy. After creating control charts, performance evaluation in the industry is important. The main contribution of this paper is to employs the FOC curve for evaluating the performance of the fuzzy control chart, while in prior studies in this area, the performance of fuzzy control chart has not been evaluated.