عنوان مقاله :
مدل بيزين ريسك مشتري بر پايه‌ي مشخصه‌هاي عملكردي: يك استراتژي موفق در حفظ مشتري
عنوان به زبان ديگر :
BAYESIAN CUSTOMER RISK MODEL BASED ON THEIR OPERATIONAL CHARACTERISTICS IN ORDER TO FORMULATE A SUCCESSFUL STRATEGY FOR KEEPING CUSTOMERS
پديد آورندگان :
بازدار، علي اصغر دانشكده‌ي فني و مهندسي گلپايگان - گروه مهندسي صنايع , طاهري، نرگس دانشكده‌ي فني و مهندسي گلپايگان - گروه مهندسي صنايع
كليدواژه :
تحليل ريسك , دسته‌بندي , پيش‌بيني , مدل بيز , درخت تصميم
چكيده فارسي :
بهره‌برداري از اطلاعات مشتري نقش مهمي در تحليل رفتار آن و بررسي ريسك خريد دارد و امروزه در مقابله با بازار رقبا و حفظ و سيانت از مشتري پايدار مورد توجه قرار گرفته است. در اين پژوهش با در نظر گرفتن متغيرهاي توصيفي مشتري از جمله سن و شغل به تعيين مدلي براي تحليل ريسك آينده‌ي مشتري پرداخته شده و رفتار آينده‌ي مشتري پيش‌بيني مي‌شود. ابتدا ميزان ريسك‌پذيري برحسب برخي مشخصه‌هاي مشتري به‌طور تجربي ارزيابي مي‌شود؛ سپس با توجه به اطلاعات پيشين، ريسك بيزي مشتري تحليل شده و از آن در دسته‌بندي مشتري و پيش‌بيني رفتار خريد آن استفاده شده است. رويكرد نشان داده شده در اين تحقيق، در خصوص
محصولات شركت صندوق نسوز كاوه به‌صورت يك مطالعه‌ي موردي به كار گرفته شده تا كاربرد پژوهش بر خواننده هرچه بيشتر محقق شود.
چكيده لاتين :
Costumer information can be take an important basis in the analysis of costumer
behavior. It's obvious that one of the most essential characteristics of the customer behavior is the customer risk modelling in order to the customer risk assessment. Today, it's very important to keep up stable costumers to confront with the rival market and get it. In this research, at the first we introduced introduction in order to survey prior research about risk modelling and assessment in work field. There are a lot of procedure to risk modelling because the usage of this methodology is very comprehensive whiles there is not any distinctive structure to risk assessment and modelling. In section two, we are considered descriptive variables of customer such as age, weight, usage, prehistory and occupation to analyze past behavior of customer with respect to the future behavior by definition experimental function from determinative historical data. It approach used to model customer future behavior. Then we are assessed purchase risk in order to predict the future behavior of customer. At first, according to the many characteristics that driven from the specific sample of new strongbox company customers, experimental functions generated and are compared to gather with the information that gains from the descriptive statistics and distribution diagrams on this data and then, purchase risk is evaluated experimentally. In the next section, the Bayes risk of customer is analyzed and used to classify customers according to the prior data. After it, we proposed guidance for improve the production programing and sale management decision tree technique. The approach mentioned in this research is used as a case study about the products of Kaveh strongbox company that readers can be realize the practical usage of this research as much. All data in this research that obtains from thoroughbred replier is done by expert questioner. The
software that we used in this research are MINITAB and Expert Choice.
عنوان نشريه :
مهندسي صنايع و مديريت شريف
