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One of the salient challenges in customer-oriented organizations is to recognize, segment and rank customers. Customer segmentation is usually based on customer lifetime value (CLV) measured by three purchase variables: “Recency,” “Frequency” and “Monetary.” However, due to the ambiguity of these variables, using deterministic approach is not appropriate. For tackling this matter, the purpose of this paper is to propose a new method of customer segmentation and ranking by combining fuzzy clustering (as a segmentation method) and fuzzy AHP (as a ranking method).

First, customers are classified based on purchase variables using fuzzy c-means clustering algorithm. Second, the variables are weighed applying an optimized version of AHP method. Considering the derived weights and customer groups, this paper follows to ranks segments based on CLV. The developed methodology has been implemented for a large IT company in Iran.

The results show a tremendous capability to the company to evaluate his customers by dividing them into nine ranked segments. The validity of clusters has been submitted.

For researchers, this study provides a useful literature by combining FCM and an optimized version of fuzzy AHP in order to cover the limitations of previous methodologies. For organizations, this study clarifies the procedure of customer segmentation by which they can improve their marketing activities.

Managers can consider the proposed CLV calculation methodology for selling the next best services/products to the group of customers that are more valuable, by calculating the entire lifetime value of the customers.

This study contributes to the process of customer segmentation based on CLV, proposing a new method which covers the limitations of previous customer segmentation methods.

The purpose of this paper is first to construct an e‐publishing model and then to implement the model in Iranian publishers.

This article critically tries to evaluate Iranian publishing companies involved in e‐publishing based on a new model which is made in this paper. Moreover, it has tried to investigate the readiness of the society and the Ministry of Culture and Islamic Guidance as a legislator toward e‐publishing. Furthermore, some suggestions to remove challenges toward e‐publishing based on the findings will be made.

A new e‐publishing readiness model is made based on e‐readiness prior models. Based on the new model, the e‐publishing readiness level of Iranian publishing companies is evaluated. It was found that, to improve e‐publishing, it is necessary to have a holistic view toward the model in a way that considers all dimensions of e‐publishing. Furthermore, it was found that in some constructs like technical infrastructure, social, and economical and financial constructs, Iranian publishers did not enjoy a good status, while in other factors this was better. Consequently, based on these finding, some suggestions are made toward improving the e‐publishing readiness level of Iranian publishers.

This research is probably the first to support the perspective of critical issues regarding e‐readiness assessment in publishing companies based on macro models. It will give a good insight which it is expected could be helpful for managers to consider the critical issues with respect to e‐readiness assessment of their organization in an effective way.

This study aimed to Simultaneous matching of color and antimicrobial properties of silk fabric treated with silver nanoparticle. The antimicrobial finishing using silver nanoparticles (AgNPs) is one of the most important finishing processes in the textile industry. Color matching is widely applied in the textile industry, but there has been a need for the prediction of AgNPs concentration for the matching of dyed silver-treated samples.

In this research, the silk fabrics were dyed with various concentrations of C.I. Acid Red 359 dye at 0.5, 1, 1.5 and 2 per cent (w/w). The dyed fabrics were then coated with AgNPs in several concentrations at 0.015, 0.030, 0.050, 0.100 and 0.250 ml/l. The prediction of dye and AgNPs concentrations were evaluated using single constant color matching and artificial neural network techniques.

The obtained results indicate that the accuracy of dye concentration prediction, as well as AgNPs concentration prediction, was improved by using a neural network method. Also, the correlation between actual and predicted dye and AgNPs concentrations in the best neural networks is more than the single constant color matching method.

Simultaneous antibacterial and color matching of nanosilver-treated fabric is novel. This method achieved acceptable accuracy for antibacterial and color matching.