0000000001091363
AUTHOR
ÓScar González-benito
Spatial mapping of price competition using logit-type market share models and store-level scanner-data
This paper proposes a methodology to obtain reliable spatial maps of price competition using store-level scanner data. Specifically, a procedure to obtain a symmetric matrix of similarities between brands considering their substitutability depending on price variations is proposed. The matrix is derived from a market response model where price cross-effects are split into two components. The first component accounts for the fact that price variation in one brand can have different effects to price variation in other brands (ie j → j′≠j′ → j). The second component accounts for the fact that the price of each brand can have different effects across competing brands (ie j → j′≠j → j ″). The ma…
Using store level scanner data to improve category management decisions: Developing positioning maps
This paper provides evidence of the usefulness of aggregated point-of-sale scanner data to infer the positioning of competing brands, providing valuable information for category management and hence facilitating decision making. Specifically, the authors propose a methodology to study the internal market structure based on market share models with latent heterogeneity when only macro-level time series data (not individual choices) are available. The proposed approach assumes a multidimensional decomposition, latent in the preference structure that is implicit to these types of models. By empirically applying this approach, the authors (1) simultaneously identify both latent dimensions of co…