考虑商品促销关联效应的网络零售商动态定价模型

doi:10.12066/j.issn.1007-2861.2190

Abstract

Abstract:

In addition to the rapid development of e-commerce business, helping enterprises obtain optimal profits through dynamic pricing decisions has become a critical research direction of operations management for online retailers. With the increase in the frequency and variety of promotional activities, there are increasingly strong promotional correlation effects amid products. Therefore, different promotional strategies impact sales at the inter- and intra-category level. This study first applies the Granger-LASSO (least absolute shrinkage and selection operator) test to identify promotional correlation effects. The ADL (advanced distributed learning)-LASSO multi-stage regression is then used to establish a demand forecast model. Finally, the demand model is integrated into the profit function to establish a dynamic pricing model that considers promotional correlation effects. The experimental simulation results indicate that the proposed model can improve the total online profit of Brand U by 13.46%, which is proven to be an effective solution to dynamic pricing decisions for online retailers.

Key words: online retailer, dynamic pricing, promotional correlation effect, demand forecast

CLC Number:

F273

GAO Junjun, GUO Peng. Dynamic pricing model based on correlation effect of product promotion for an online retailer[J]. Journal of Shanghai University（Natural Science Edition）, 2021, 27(5): 959-971.

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References 17

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Dynamic pricing model based on correlation effect of product promotion for an online retailer

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