Evaluating and clustering the Iranian banks and financial institutions based on website traffic indicators

Todays, websites have great importance in the field of information and do a lot of services. In this regard, webometrics studies has been the attention of many researchers at various aspects. The aim of this study is to evaluate and cluster the Iranian banks and financial institutions based on website traffic indicators. In research process, 31 banks and financial institutions were evaluated in the form of 6 of the most important website traffic indicators include the average number of pages visited, average time to browse the site, the percentage of visitors within the country, the percentage of visitors from abroad, the number of links, and the speed of loading, based on the Alexa website and search engine. Then, the similar banks and institutions were classified in the form of homogeneous groups using by the Hierarchical Clustering Analysis (HCA). The quality and validity of each of the clusters created was confirmed by using Discriminant Analysis (DA) and finally, were discussed the characteristics of each of these clusters. The findings suggest that there is not a significant difference in terms of speed of loading between the clusters, but in other indexes, the difference between clusters is significant.