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Ultra Innovative Approach to Integrate Cellphone Customer Market Segmentation Model Using Self Organizing Maps and K-Means Methodology | ||
| Journal of Information Technology Management | ||
| مقاله 73، دوره 8، شماره 2، مهر 2016، صفحه 351-372 اصل مقاله (1.55 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jitm.2016.57233 | ||
| نویسندگان | ||
| Mohammad Reza karimi Alavijeh* 1؛ Saeed Khadangi2؛ Mohammad Saleh Torkestani1 | ||
| 1Associate Prof., Faculty of Management, Allameh Tabatabaei University, Tehran, Iran | ||
| 2MSc. Student in Marketing Management, Faculty of Management Allameh Tabatabaei University , Iran | ||
| چکیده | ||
| The utilization of 3G and 4G is rapidly increasing and also cellphone users are briskly changing their consumption behavior, using preferences and shopping manner. Accordingly, cellphone manufacturers should create an accurate insight of their target market and provide a “special offer” to their target consumers. In order to reach a correct understanding of the target market, consumption behavior and lifestyle of the submarkets we found the appropriate number of community clusters after criticizing the traditional methods and introducing market segmentation techniques which were based on neural networks. By utilizing the fuzzy Delphi technique, variables of target market segmentation were found. Finally, the obtained clusters and segmentations of the market were refined by using the techniques of K-means and aggregation (Agglomerative). The population of this research included the consumers of mobile in Tehran with a sample of 130 specimens after collecting data through questionnaires, results demonstrated that the Tehran cellphone market was comprised of 5 Clusters, each one are capable of implementing marketing strategy and marketing mix separately with taking into account the competitive advantages of ICT companies to maximize their demand and margin. | ||
| کلیدواژهها | ||
| Market segmentation؛ Self-organizing Maps؛ Neural Networks؛ Data Mining؛ Delphi-fuzzy method؛ Clustering | ||
| مراجع | ||
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