Title :
Real Time Demand Learning-Based Q-learning Approach for Dynamic Pricing in E-retailing Setting
Author_Institution :
Bus. Sch., East China Univ. of Sci. & Technol., Shanghai, China
Abstract :
Information technology has given e-retailers new capability of learning demand in real time. This paper investigates how to integrate this real time learning technology with Q-learning algorithm for the optimization of dynamic pricing in e-retailing setting. Especially, this paper studies the optimal dynamic pricing problem for seasonal and style products in e-retailing setting, and validate our approach in simulated test.
Keywords :
electronic commerce; learning (artificial intelligence); pricing; real-time systems; retail data processing; Q-learning algorithm; e-retailing; optimal dynamic pricing problem; real time demand learning technology; seasonal product; style product; Computational modeling; Electronic commerce; Marketing and sales; Monitoring; Pricing; Stochastic processes; Technology management; Testing; Traffic control; Uncertainty; Q-learning; demand learning; e-commerce;
Conference_Titel :
Information Engineering and Electronic Commerce, 2009. IEEC '09. International Symposium on
Conference_Location :
Ternopil
Print_ISBN :
978-0-7695-3686-6
DOI :
10.1109/IEEC.2009.131
