05 اردیبهشت 1403
سيد يعقوب حسيني

سید یعقوب حسینی

مرتبه علمی: دانشیار
نشانی: دانشکده کسب و کار و اقتصاد - گروه مدیریت بازرگانی
تحصیلات: دکترای تخصصی / مدیریت
تلفن: 07731222124
دانشکده: دانشکده کسب و کار و اقتصاد

مشخصات پژوهش

عنوان A Data Mining Approach for Segmentation Based Importance-Performance Analysis (SOM-BPNN-IPA): A New Framework for Developing Customer Retention Strategies
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
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مجله Service Business
شناسه DOI
پژوهشگران سید یعقوب حسینی (نفر اول) ، علیرضا ضیایی بیده (نفر دوم)

چکیده

Importance-performance analysis (IPA) is a simple but effective means of assisting practitioners in prioritizing service attributes when attempting to enhance service quality and customer satisfaction. The purpose of this study was to demonstrate how IPA can be used with market segmentation to develop customer retention strategies for different market segments. For this purpose, a new framework have been proposed that uses self-organizing maps for customers’ segmentation and back-propagation neural network (BPNN) for implicity drive the importance of service attributes based on their effect on customers’ loyalty in each segment. Then, individual IPA matrixes are developed for each market segment. Also, an example case is presented to demonstrate the implementation and application of the proposed framework. The results of the proposed framework compared with a conventional BPNN-IPA approach indicated that it can increase reliability and applicability of IPA results.