Mohammad Ali Faezi-Rad; Alireza Pooya
Abstract
By developing information technology and emerging online markets,Planning for these markets and analyzing their details has been became a priority for beneficiary organizations. One of most important online markets in Iran is SIM card credit services that are considered as online stores. Regarding to ...
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By developing information technology and emerging online markets,Planning for these markets and analyzing their details has been became a priority for beneficiary organizations. One of most important online markets in Iran is SIM card credit services that are considered as online stores. Regarding to numerous and increasing number of online malls, grouping and classification of online malls from supplier's point of view in order to forecasting cooperation is essential. In this paper, around three thousand online stores has been studied and analyzed by using one of famous supplier data and it has been clustered according to supplier's indexes. Clustering process has been done by using SOM Neural Network in two levels by K-means algorithm since it facilitates analyzing of clusters. Although various validation indicators has been developed to determine the best number of clusters but in this paper, an optimizing model of compensatory approach to indexes is presented by using combination multi criteria decision making and aggregation of various indexes
