Retail pricing decisions and product category competitive structure

被引:16
|
作者
Gonzalez-Benito, Oscar [1 ]
Pilar Martinez-Ruiz, Maria [2 ]
Molla-Descals, Alejandro [3 ]
机构
[1] Univ Salamanca, Dpto Adm & Econ Empresa, Salamanca 37007, Spain
[2] Univ Castilla La Mancha, Area Comercializac & Invest Mercados, Cuenca 16002, Spain
[3] Univ Valencia, Dpto Comercializac & Invest Mercados, Valencia 46022, Spain
关键词
Retail pricing decision model; Demand forecasting; Market share models; Category management; Competitive structure; Store-level scanner data; IMPACT; PROMOTIONS; ELASTICITIES; STRATEGIES; MANAGEMENT; BEHAVIOR; CHOICES; MODEL;
D O I
10.1016/j.dss.2010.01.009
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This study addresses the use of demand forecasting techniques by retailers to support their decision making. Specifically, the authors propose a pricing decision support model for retailers to estimate optimal prices, whose output depends on the configuration of a supporting measurement model. The measurement model is a demand function that relates sales and prices within the category: optimal prices are those whose effects on demand and retail margins maximize the category's profitability. This investigation focuses particularly on the role of competitive structure, such that the authors consider two types of price competition asymmetries for demand forecasting: those depending on the brand (differential price effects) and those dealing with demand for competing brands (cross-price effects). By explicitly modeling competitive asymmetries in the demand function that underlies the decision support model, the authors assess implications for pricing decisions, sales, and profitability. The empirical application of the model to store-level, aggregated scanner data for two frequently purchased categories reveals the impact of an asymmetric competitive structure on demand forecasting and optimal pricing decisions. Furthermore, this article quantifies the costs of ignoring asymmetric competitive interactions in retailers' decision making. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:110 / 119
页数:10
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