电子商务零售商多项Logit模型下的联合产品框架(陈列、排序、定价)与订单履行

Y. Lei, Stefanus Jasin, J. Uichanco, A. Vakhutinsky
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引用次数: 10

摘要

问题定义:我们研究了一个电子商务零售商所面临的具有库存和基数约束的联合产品框架和订单履行问题。销售周期有限,没有补货机会。在每个时期,零售商需要决定如何在他或她的网站上“框架”(即,展示,排名,价格)每种产品以及如何满足新的需求。学术/实践相关性:众所周知,电子商务零售的利润率很低。利用美国一家大型零售商的数据,我们表明,共同规划产品框架和订单履行可以对在线零售商的盈利能力产生重大影响。这是一个具有技术挑战性的问题,因为它涉及库存和基数约束。在本文中,我们在解决这一挑战方面取得了进展。方法:我们使用随机算法和基于图的算法等技术来提供一个易于处理的启发式解决方案,我们通过渐近分析进行分析。结果:我们提出的随机启发式策略是基于随机控制问题的确定性近似解。关键的挑战是构建一个易于实现的随机化方案,并保证结果策略是渐近最优的。基于矩阵分解的思想,提出了一种新的两步随机化方案。管理意义:我们的数值测试表明,所提出的策略非常接近最优,可以应用于实践中的大规模问题,并突出了共同优化产品框架和订单履行决策的价值。当整个网络的库存不平衡时,规划产品框架而不考虑其对履行的影响的普遍做法可能导致高运输成本,无论使用的履行政策如何。我们提出的策略通过使用产品框架来管理需求,从而使其发生在靠近库存位置的地方,从而大大降低了运输成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Joint Product Framing (Display, Ranking, Pricing) and Order Fulfillment Under the Multinomial Logit Model for E-Commerce Retailers
Problem definition: We study a joint product framing and order fulfillment problem with both inventory and cardinality constraints faced by an e-commerce retailer. There is a finite selling horizon and no replenishment opportunity. In each period, the retailer needs to decide how to “frame” (i.e., display, rank, price) each product on his or her website as well as how to fulfill a new demand. Academic/practical relevance: E-commerce retail is known to suffer from thin profit margins. Using the data from a major U.S. retailer, we show that jointly planning product framing and order fulfillment can have a significant impact on online retailers’ profitability. This is a technically challenging problem as it involves both inventory and cardinality constraints. In this paper, we make progress toward resolving this challenge. Methodology: We use techniques such as randomized algorithms and graph-based algorithms to provide a tractable solution heuristic that we analyze through asymptotic analysis. Results: Our proposed randomized heuristic policy is based on the solution of a deterministic approximation to the stochastic control problem. The key challenge is in constructing a randomization scheme that is easy to implement and that guarantees the resulting policy is asymptotically optimal. We propose a novel two-step randomization scheme based on the idea of matrix decomposition and a rescaling argument. Managerial implications: Our numerical tests show that the proposed policy is very close to optimal, can be applied to large-scale problems in practice, and highlights the value of jointly optimizing product framing and order fulfillment decisions. When inventory across the network is imbalanced, the widespread practice of planning product framing without considering its impact on fulfillment can result in high shipping costs, regardless of the fulfillment policy used. Our proposed policy significantly reduces shipping costs by using product framing to manage demand so that it occurs close to the location of the inventory.
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