Identifying demand effects in a large network of product categories
By Sarah Gelper, Ines Wilms, Christophe Croux. 2015
48 citations recorded by the source corpus.
Planning marketing mix strategies requires retailers to understand within- as well as cross-category demand effects. Most retailers carry products in a large variety of categories, leading to a high number of such demand effects to be estimated. At the same time, we do not expect cross-category effects between all categories. This paper outlines a methodology to estimate a parsimonious product category network without prior constraints on its structure. To do so, sparse estimation of the Vector AutoRegressive Market Response Model is presented. We find that cross-category effects go beyond substitutes and complements, and that categories have asymmetric roles in the product category network. Destination categories are most influential for other product categories, while convenience and occasional categories are most responsive. Routine categories are moderately influential and moderately responsive.
Subfields: Marketing, Tourism, Leisure and Hospitality Management
View Paper: https://www.semanticscholar.org/paper/91865c69d12a35540d906f45ba3f946c8fd99704
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In Tourism, Leisure and Hospitality Management
Citations in the corpus
- A network analysis of the volatility of high dimensional financial series (2017, methodology): “…n data sets, is based on sparsity assumptions allowing for the application of penalized regression techniques (Hsu et al., 2008; Abegaz and Wit, 2013; Nicholson et al., 2014; Basu and Michailidis, 2015; Davis et al., 2015; Kock and Callot, 2015; Barigozzi and Brownless, 2016; Gelper et al., 2016).”