摘要
电子商务竞争环境下,耐用品的动态定价中考虑成本和顾客期望,采用多个周期两阶段定价的方法,两个阶段分别选取成本加成和顾客期望定价模型,并组合在一起形成一个周期的定价策略。以电子商务运营商的在线销售利润和销售额为算法的性能衡量指标,采用PSO算法,寻找最优降价时间和两阶段的最优价格。实验结果证实该方法在收敛速度上和计算效率上是可行的,性能也优于多周期只考虑成本的单阶段定价方法。
In competitive environment of electronic commerce, durable products were priced dynamically, considering not only cost, but also customer expectation in every period. Multi-period two stages pricing is adopted. Cost-plus model and customer-expectation model were selected for each stage respectively, and integrated for one pricing period. To find the optimal price and time length of two stages, particle swarm optimization was selected for the sake of maximizing the profit and sale number of an online marketing site, The results of experimentation verify that the method is practical in terms of the speed of convergence to the optimal price and computational efficiency, and is better than multi-period only considering cost one stage pricing.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2006年第11期3046-3049,3054,共5页
Journal of System Simulation
基金
国家自然科学基金重点资助项目(70431003)
教育部高等学校博士学科点专项科研基金(20040145009)。
关键词
电子商务
竞争
PSO算法
耐用品
动态定价
electronic commerce
competition
particle swarm optimization
durable products
dynamic pricing