مدل سازی فروش محصولات مصرفی با استفاده از سیستم استنتاج عصبی-فازی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مدیریت بازرگانی و اجرایی، دانشکده مدیریت و حسابداری، پردیس فارابی دانشگاه تهران، قم، ایران

2 گروه مدیریت کسب و کار، دانشکده مدیریت و حسابداری پردیس فارابی، دانشگاه تهران، قم، ایران

3 گروه مدیریت صنعتی و تکنولوژی، دانشکده مدیریت و حسابداری، پردیس فارابی دانشگاه تهران، قم، ایران

4 مدرس دوره های آزاد دانشگاه تهران

چکیده

مدل سازی فروش در این فضای بسیار رقابتی برای هر کسب و کاری نقش اساسی دارد. پیش بینی فروش محصولات در گونه های مختلف خرده فروشی به نگرانی اصلی شرکت ها برای ارزیابی گردش و توان رقابتی محصولات تبدیل شده است. مدل سازی فروش در صنعت محصولات مصرفی به دلیل وجود طیف گسترده ای از ویژگی های متغیر محصول، بسیار پیچیده است. هدف این پژوهش، طراحی یک سیستم استنتاج عصبی-فازی جهت مدل سازی فروش محصولات مصرفی در گونه‌های مختلف خرده‌فروشی است. در این پژوهش، فروش از نظر خبرگان صنعت محصولات مصرفی و با استفاده از تکنیک انفیس بررسی شده است. انفیس، یک تکنیک جدید برای تخمین فروش است که ترکیبی از قابلیت یادگیری شبکه های عصبی و قابلیت تعمیم منطق فازی را دارا است. معیارهای ورودی و خروجی پژوهش از طریق مصاحبه عمیق با 12 نفر از صاحب‌نظران و مدیران فروشگاهی و همچنین جمع‌آوری داده‌های میانگین فروش یک سال 336 محصول مختلف (1398) تعیین شده است. نتایج پژوهش نشان داد که مدل سازی فروش بر اساس سیستم انفیس می تواند به تولیدکنندگان محصولات مصرفی کمک کند تا تقاضای گونه های خرده فروشی را با دقت بالاتر پیش بینی کنند. در نهایت، کارآئی آموزش و آزمون مدل فازی طراحی شده با استفاده از شاخص های جذر میانگین مربعات خطا، میانگین قدر مطلق خطا، میانگین خطای استاندارد و خطای مطلق نسبی مورد ارزیابی قرار گرفت.

کلیدواژه‌ها


عنوان مقاله [English]

Modeling of Consumer Product Sales using an Adaptive Neuro-Fuzzy Inference System

نویسندگان [English]

  • Hamidreza Nezhadali Lafmejani 1
  • Hamidreza irani 2
  • touraj karimi 3
  • Morteza Soltani 1
  • ahmad saffar 4
1 Department of Business Management, Faculty of management and accounting, Tehran University, Farabi College, Qom, Iran
2 Department of Business Management, Farabi Campus School of Management and Accounting, University of Tehran, Qom, Iran
3 Department of Industrial and technology Management, Faculty of Management and Accounting, Tehran University, Farabi College, Qom, Iran
4 lecturer of Tehran University Open Courses
چکیده [English]

Sales modeling is essential for businesses in today’s strongly competitive world. The sales forecasting of products under different retail format has become a major concern of companies for evaluating the circulation and competitiveness of their products. Due to the presence of a wide range of variable product characteristics, it is very complicated to model the sales of consumer products. The present study aims to design an adaptive neuro-fuzzy inference system (ANFIS) to model the sales of consumer products under different retail format. Sales were investigated based on the views of consumer product experts through the ANFIS technique. As a new technique for sales estimation, ANFIS is a combination of neural network learning and fuzzy logic generalization. The input and output criteria were determined by performing in-depth interviews with twelve sales experts and managers and collecting the average sales data of 336 products in 2019. The results indicated that ANFIS-based sales modeling could help manufacturers of consumer products more accurately forecast retail type demands. Finally, the training and testing efficiency of the proposed model was evaluated using the root mean square error (RMSE), mean absolute error (MAE), standard error of the mean (MSE), and relative absolute error (RAE).

کلیدواژه‌ها [English]

  • Sales forecasting
  • Sales modeling
  • Adaptive neuro-fuzzy inference system
 
ترابی، فاطمه؛ رحیمی نیک، اعظم؛ ودادی، احمد و اسماعیل پور، حسن. (1398). تبیین مدل رفتار خرید مصرف کننده در انتخاب محصولات لذت بخش با رویکرد آمیخته (مورد مطالعه: فروشگاه های زنجیره ای همواره تخفیف(. مطالعات رفتار مصرف کننده، 6(1)، 81-104.
مهدیه، امید و سلیمانی، چیمه. (1397). رابطه بین اطلاعات مندرج بر بسته بندی و رفتار خرید مصرف کننده. مطالعات رفتار مصرف کننده، 5(1)، 81-99.
 
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