PRICING OPTIMIZATION BASED ON INTELLIGENT DATA ANALYSIS MODEL
Journal Title: Вісник Київського національного університету імені Тараса Шевченка. Економіка. - Year 2015, Vol 7, Issue 172
Abstract
Determination of the optimal prices for goods is one of the important business management tasks in retailing. The new effective enterprises reality demonstrate the need to focus on the customers behavior and preferences. Traditional approaches to the pricing problem associated with solving an optimization problem, where the optimality criterion considering the company revenue maximization. The purpose of this study is to develop and implement an approach for solving the optimization problem in the retailers goods market and different consumers groups based on a hybrid model of intelligent data analysis. For each consumer type product information array formed consisting of the factors values that affect the company revenue. An example of the optimal prices hybrid model synthesis in the product (beer) market and grocery stores network were considered. Solving the problem of optimizing product prices by consumer groups was implemented in two stages: first constructed interpolation function of consumer demand each group, and then solve the problem of optimizing implicitly given function. Demand function obtained by artificial neural networks.
Authors and Affiliations
Galyna Chornous, Sergii Rybalchenko
Keywords
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- EP ID EP401119
- DOI 10.17721/1728-2667.2015/172-7/7
- Views 72
- Downloads 0
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