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پیشبینی ارزش طول عمر مشتریان بانکی با استفاده از تکنیک دستهبندی گروهی دادهها (GMDH) در شبکۀ عصبی | ||
مدیریت بازرگانی | ||
مقاله 8، دوره 8، شماره 4، 1395، صفحه 833-860 اصل مقاله (663.65 K) | ||
نوع مقاله: مقاله علمی پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/jibm.2017.61302 | ||
نویسندگان | ||
امیر خانلری* 1؛ مهدی احراری2؛ سمیه میرپور3 | ||
1استادیار/ گروه مدیریت MBA دانشکده مدیریت دانشگاه تهران | ||
2دانشجوی دکتری اقتصاد نفت و گاز، بازار و مالیه / دانشگاه علامه طباطبایی | ||
3مدیر توسعه کسب و کار / تجهیزات مخابراتی نت کالا | ||
چکیده | ||
امروزه نقش مدیریت ارتباط با مشتری بهعنوان ابزار راهبردی در توسعۀ سازمانهای تولیدی و خدماتی و همچنین جذب و نگهداری مشتریان در صنایع رقابتی، انکارناپذیر است. شناسایی، ارزشگذاری و دستهبندی مشتریان و تخصیص بهینۀ منابع به آنها با توجه به ارزشی که برای سازمانها دارند، از دغدغههای اصلیِ حوزۀ مدیریت ارتباط با مشتری است. در این مقاله با استفاده از شبکۀ عصبی GMDH به محاسبه و پیشبینی ارزش طول عمر مشتریان، بهعنوان ابزاری کلیدی در تحقق نقش مدیریت ارتباط با مشتری در صنعت بانکداری پرداخته شده است. برای این منظور، اطلاعات جمعیتشناختی و مالی 5000 مشتری حقیقی ارزندۀ یکی از بانکهای خصوصی کشور با شرط میانگین موجودی بیش از 500 میلیون ریال در حداقل یکی از حسابها، وارد شبکه شد. نتایج نشان داد بهکمک این روش میتوان با دقت بالای 90 درصد ارزش طول عمر مشتریان را پیشبینی کرد که به نسبت روشهای آماری متعارف، دقت بیشتری دارد. پس از حذف متغیرهای مؤثر و مضاعف، شبکه بار دیگر آزمایش شد که در این حالت نیز پیشبینی با دقت بیش از 85 درصد بود | ||
کلیدواژهها | ||
: ارزش طول عمر مشتری؛ پیشبینی؛ شبکۀ عصبی GMDH؛ مدیریت ارتباط با مشتری | ||
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