DocumentCode :
2560644
Title :
Multi-product pricing method based on the customer buying behavior
Author :
Fucai, Wan ; Jia, E. ; Wei, Wang
Author_Institution :
Coll. of Inf. Eng., Shenyang Univ., Shenyang
fYear :
2008
fDate :
2-4 July 2008
Firstpage :
2126
Lastpage :
2130
Abstract :
Through interaction with online consumers, e-commerce Web sites can gather data reflecting consumer preferences. The available data on consumer preferences together with sophisticated analytical tools enables companiespsila increases in profit through optimization of prices. We can study for the multi-product pricing problem based on this available data. Where, given consumer preferences among products, their budgets, and the order list of production, the goal is to set prices of multiple products from a single company, so as to maximize the overall revenue of the company. To address this problem, based on the customer-buying-behavior, a non-linear programming model of multi-product pricing was presented. The model was solved through genetic algorithms. Optimal solution of the given example shows that this model is effective for enterprises.
Keywords :
Web sites; consumer behaviour; electronic commerce; genetic algorithms; nonlinear programming; pricing; profitability; retail data processing; company profitability; company revenue maximization; consumer preferences; customer buying behavior; e-commerce Web site; genetic algorithm; multiproduct pricing method; nonlinear programming model; online consumer interaction; Companies; Data engineering; Design methodology; Educational institutions; Electronic commerce; Genetic algorithms; Genetic mutations; Internet; Pricing; Production; Customer Buying Behavior; Electronic Commerce; Genetic Algorithms; Multi-Product Pricing; Substitutable Products;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
Type :
conf
DOI :
10.1109/CCDC.2008.4597700
Filename :
4597700
Link To Document :
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