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مدلسازی ترکیبی Pareto/NBD و RFM موزون فازی بهمنظور بخشبندی مشتریان در روابط غیرقراردادی | ||
| مدیریت بازرگانی | ||
| مقاله 1، دوره 6، شماره 3، مهر 1393، صفحه 417-440 اصل مقاله (530.28 K) | ||
| نوع مقاله: مقاله علمی پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/jibm.2014.51381 | ||
| نویسندگان | ||
| امیر البدوی* 1؛ اشرف نوروزی2؛ محمدمهدی سپهری3؛ محمد رضا امین ناصری3 | ||
| 1استاد مهندسی صنایع، دانشکدۀ فنی و مهندسی، دانشگاه تربیت مدرس، تهران، ایران | ||
| 2دانشجوی دکتری مهندسی صنایع، دانشکدۀ فنی و مهندسی، دانشگاه تربیت مدرس، تهران، ایران | ||
| 3دانشیار مهندسی صنایع، دانشکدۀ فنی و مهندسی، دانشگاه تربیت مدرس، تهران، ایران | ||
| چکیده | ||
| درآمدسازی در شرکت‌ها از طریق ایجاد رابطه با مشتریان و حفظ این روابط در درازمدت صورت می‌پذیرد. از این رو توانایی پیشبینی مناسب روابط با مشتریان نکته‌ای اساسی در مدیریت رابطه با مشتریان است. بخشبندی روشی است که طی آن با تفکیک مشتریان به بخش‌های متجانس با رفتار خرید مشابه، تلاش می‌شود تا ارزش آتی رابطه با مشتریان پیشبینی شود. روش RFM یکی ازمتداول‌ترین روش‌های بخشبندی است که از تحلیل پایگاه دادۀ تراکنشی برای رده‌بندی ارزش مشتریان استفاده میکند. پژوهش حاضر تلاش دارد تا از ترکیب مدلسازی Pareto/NBD ـ که به مدلی قدرتمند در پیشبینی رفتار مشتریان مشهور است ـ با روش معمول RFM، کیفیت بخشبندی مشتریان را ارتقا بخشد. در این پژوهش از روش Pareto/NBD برای تخمین سه مؤلفۀ مقدار انتظار احتمال فعالیت آتی، تعداد تراکنش‌های آتی و متوسط ارزش پولی استفاده شده است. سپس نتایج بخشبندی مشتریان با استفاده از این مؤلفهها با کاربرد روش مرسوم RFM مقایسه شده است. نتایج حاصل بیانگر بهبود کیفیت بخشبندی در رده‌بندی ارزش آتی مشتریان، بهویژه در ردههای ارزشمند مشتری با کمک رویکرد پیشنهادی است. | ||
| کلیدواژه‌ها | ||
| روابط غیرقراردادی؛ فرایند تحلیل سلسلهمراتبی فازی؛ مدل RFM؛ مدلسازی Pareto/NBD | ||
| عنوان مقاله [English] | ||
| An Integrated Pareto/NBD- fuzzy weighted RFM model for customer segmentation in non-contractual setting | ||
| نویسندگان [English] | ||
| Amir Albadvi1؛ Ashraf Norouzi2؛ Mohammad Mehdi Sepehri3؛ Mohammad Reza Amin Naseri3 | ||
| 1Prof. Amir Albadvi, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran | ||
| 2PhD. Candidatein Industrial Engineering, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran | ||
| 3Associate Prof., Mohammad Mehdi Sepehri, Faculty of Engineering, Tarbiat Modares University, Tehran, Iran | ||
| چکیده [English] | ||
| Companies create revenue through creating customer relationships and sustenance of these relations in long-term. Therefore, an appropriate prediction of customer relationships is central for CRM. Segmentation divides the customer base into homogenous parts where every group of customers has similar characteristics of buying behavior and therefore has similar expected value. One of the most popular segmentation techniques is RFM analysis which uses transactional databases to provide predictions about customer lifetime value. This study aims to combine Pareto/NBD model, as a powerful tool in predicting customer’s future behavior with RFM analysis to improve the segmentation quality. The Pareto/NBD model is used to estimate the probability of customers’ activity in future periods, the expected number of transactions and the expected average monetary value. The result of this segmentation is being compared to the application of traditional RFM technique. Experimental results indicate that the proposed approach improves the quality of segmentation in order to estimate the customer’s future value, especially in the case of more valuable segments. | ||
| کلیدواژه‌ها [English] | ||
| Fuzzy Analytical Hierarchy Problem (FAHP), non-contractual setting, Pareto/NBD modeling, RFM Model | ||
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