کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
386542 660885 2010 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A two-stage clustering approach for multi-region segmentation
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A two-stage clustering approach for multi-region segmentation
چکیده انگلیسی

Previous research in multi-region segmentation has found that the customer segmentation derived based on the customer attributes from one region (i.e., city or country) cannot be directly adopted by another region. As a result, for a firm that operates in multiple regions, a market segmentation method that can integrate data from different regions to obtain a set of generalized segmentation rules can greatly enhance the competitiveness of the company. In this research, we applied self-organizing map (SOM) network, an unsupervised neural networks technique as both a dimension reduction and a clustering tool to market segmentation. A two-stage clustering approach, which first groups similar regions together then finds customer segmentation for each region-group, is proposed. Empirical data from one of the largest credit card issuing banks in China was collected. The data, that includes surveys of customer satisfaction attributes and credit card transaction history, is used to validate the proposed model. The results show that the two-stage clustering approach based on SOM for multi-region segmentation is an effective and efficient method compared to other approaches.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 37, Issue 10, October 2010, Pages 7120–7131
نویسندگان
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