具有预期等待的离散选择模型下的产能、定价与分类管理

Ruxian Wang
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摘要

顾客在购买产品或服务时经常面临多种选择。在做出选择后,由于公司处理订单的能力有限,他们有时不得不等待一段时间才能收到所购买的商品。本文将预期等待接收购买的产品或服务纳入顾客的选择行为。所得到的选择模型与理性期望均衡具有相同的精神,并且捕获了由预期等待引起的负外部性的影响,因为所有的订单都可以由一个共同的设施处理。我们的分析表明,预期的等待可能会极大地改变替代模式。我们进一步研究了预期等待对产能投资决策、产品定价决策和分类计划决策的影响。我们建立了价格向量与选择概率向量的一对一映射关系,并证明了选择概率的等价利润函数是明确定义的,并且更易于处理。研究了带等待的MNL模型下的多产品价格优化问题。除了价格竞争,我们还研究了古诺竞争,其中决策是每个企业的选择概率,并证明存在纳什均衡。对于分类优化,我们确定了收益排序分类仍然保持最优性的条件。由于等待的分类问题通常是np困难的,我们开发了具有性能保证的有效近似,并提供了易于计算的紧上界。新模型有可能提高对顾客选择行为的预测精度,特别是当顾客面临多种选择时,他们知道他们购买的产品可能会等待。如果不考虑顾客购买行为中预期等待的影响,可能会给企业带来巨大的损失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Capacity, Pricing and Assortment Management under Discrete Choice Model with Anticipated Wait
Customers often face multiple choices when purchasing a product or service. After making a choice, they sometimes have to wait for a while before receiving their purchased item due to the firm’s limited capacity
to process orders. This paper incorporates the anticipated wait for receiving purchased products or services into customers’ choice behavior. The resulting choice model shares the same spirit of the rational expectation equilibrium, and captures the effects of negative externality caused by the anticipated wait, because all orders may be processed by a common facility. Our analysis shows that the anticipated wait may change the substitution patterns dramatically. We further investigate the effects of the anticipated wait on the decisions of capacity investment, product pricing and assortment planning. We establish the one-to-one mapping between the price vector and the choice probability vector, and show that the equivalent profit function of the choice probabilities is explicitly defined and more tractable. We characterize the multi-product price optimization problem under the MNL model with waiting. In addition to price competition, we also study the Cournot competition, in which the decision is the choice probability for each firm, and show that there exists a Nash equilibrium. For the assortment optimization, we identify the conditions under which the optimality of the revenue-ordered assortment still holds. Because the assortment problem with waiting is generally NP-hard, we develop efficient approximations with performance guarantee and also provide an easy-to-compute tight upper bound. The new model has the potential to increase prediction accuracy for customers’ choice behavior especially when customers faced with multiple choices are aware of the possible waiting for their purchased products. Failure to take into account the effects of the anticipated wait in customers’ purchase behavior may result in substantial losses to firms.
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