摘要
为探寻存在搜寻成本情况下消费者购买可替代产品时的定价与库存问题,从消费者效用出发,对厂商收益构建了基于马尔可夫决策过程的优化模型。在消费者方面,分析了其购买与继续搜寻的条件,并分别在搜寻成本不变和搜寻成本边际递减的情况下研究了消费者保留效用的变化情况以及购买相应产品的概率。此外,与很多相关文献不同的是,由于搜寻成本的存在,该情形下的消费者并不一定会在完成购买之前搜寻完所有的产品。在厂商方面,根据实际情况构建不同搜寻顺序下的收益模型并求解出最优定价策略与库存策略,并将定价模型与库存策略扩展到了动态的环境,为厂商制定价格及库存方案提供相应的决策支持。
Aiming to solve a pricing and inventory problem which takes search cost into account,this paper constructs an optimization model based on Markov decision process from consumer's utility and companies' revenue perspective.As for consumers,we make an analysis of purchasing and searching conditions,and also study the changing tendency of consumers' reservation utility and the purchase probability of corresponding products under fixed search cost or decreasing marginal search cost respectively.Besides,different from many other researchers,we assume that it is not certain that consumers will complete all their products' search before they make a purchase due to research cost.In terms of companies,we build and solve revenue models and inventory model in different search order settings,then extend them to dynamic pricing environment,so as to provide better pricing and inventory decision support.
引文
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