顾客策略行为与贝叶斯需求学习下的易逝品定价

Pricing for perishable products with strategic customers and Bayesian demand learning

面对策略型消费者,为了制定更合适的定价策略,构建了引入贝叶斯需求学习的垄断厂商两期定价模型.首先分析了策略型顾客的最优购买决策,在此基础上运用贝叶斯更新法则建立并分析潜在需求模型和实际购买需求模型;其次建立了需求学习、未进行需求学习和完全信息下厂商的收益最大化模型,得出了相应的最优价格策略,证明了最优价格策略是一条降价路径.研究表明,面对策略型消费者,厂商引入需求学习能明显改善收益,特别是产品上市后受消费者青睐时,厂商引入需求学习的效果更为明显;随着厂商学习主动性的增强,厂商进行需求学习所增加的收益百分数呈递增趋势.

To optimize pricing strategies with strategic customers, a two-stage pricing model for mo- nopolist manufacturer is established using Bayesian demand learning. First, after analyzing the opti- mal decision-making of strategic customers, a potential demand model and a real demand model are established and analyzed using Bayesian rule. Then, a revenue maximization model is built to obtain the optimal price strategies based on the demand learning, non-demand learning and perfect informa- tion, respectively. It is proved that the optimal price strategy is a price reduction path. This research shows that the manufacturer can significantly improve profits when using demand learning under the strategic behavior of the customer. Especially when products are welcome among consumers, the effect of demand learning is more obvious. With the increase of motivation to demand learning, the percentage of increased revenue increases progressively.