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Of all publications in the section: 4
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Article
Antipov E. A., Pokryshevskaya E. B. Journal of Targeting, Measurement and Analysis for Marketing. 2011. Vol. 19. No. 1. P. 3-10.

This article addresses the issue of unobserved heterogeneity in film characteristics influence on box-office. We argue that the analysis of pooled samples, most common among researchers, does not shed light on underlying segmentations and leads to significantly different estimates obtained by researchers running similar regressions for movie success modeling. For instance, it may be expected that a restrictive MPAA rating is a box office poison for a family comedy, whereas it insignificantly influences an action movie’s revenues. Using a finite mixture model we extract two latent groups, the differences between that can be explained in part by the movie genre, the source, the creative type and the production method. On the basis of this result, the authors recommend developing separate movie success models for different segments, rather than adopting an approach, that was commonly used in previous research, when one explanatory or predictive model is developed for the whole sample of movies.

Added: Oct 4, 2012
Article
Antipov E. A., Pokryshevskaya E. B. Journal of Targeting, Measurement and Analysis for Marketing. 2010. Vol. 18. No. 2. P. 109-117.

In this study a CHAID-based approach to detecting classification accuracy heterogeneity across segments of observations is proposed. This helps to solve some important problems, facing a model-builder: (1) How to automatically detect segments in which the model significantly underperforms? and (2) How to incorporate the knowledge about classification accuracy heterogeneity across segments to partition observations in order to achieve better predictive accuracy? The approach was applied to churn data from the UCI Repository of Machine Learning Databases. By splitting the data set into four parts, which are based on the decision tree, and building a separate logistic regression scoring model for each segment we increased the accuracy by more than 7 percentage points on the test sample. Significant increase in recall and precision was also observed. It was shown that different segments may have absolutely different churn predictors. Therefore such a partitioning gives a better insight into factors influencing customer behavior.

Added: Oct 4, 2012
Article
Pokryshevskaya E. B., Antipov E. A. Journal of Targeting, Measurement and Analysis for Marketing. 2012. Vol. 20. No. 3-4. P. 203-211.

Measuring indirect importance of various attributes is a very common task in marketing analysis for which researchers use correlation and regression techniques. We have listed and illustrated some common problems with widely used latent importance measures. A more theoretically sound approach - the Shapley Value decomposition - was applied to a rich data set of US internet stores. The use of store-level data instead of respondent-level data allowed us to reveal the factors, which are powerful in explaining, why some stores have higher rates of willingness to make repeat purchases than the others. By confronting the indirect importance and performance measures for three different internet stores, we have revealed strengths, weaknesses, attributes that the company should bring customers' attention to and attributes that do not require immediate improvement.

Added: Feb 4, 2013
Article
Pokryshevskaya E. B., Antipov E. A. Journal of Targeting, Measurement and Analysis for Marketing. 2012.

Measuring indirect importance of various attributes is a very common task in marketing analysis for which researchers use correlation and regression techniques. We have listed and illustrated some common problems with widely used latent importance measures. A more theoretically sound approach – the Shapley Value decomposition – was applied to a rich data set of US internet stores. The use of store-level data instead of respondent-level data allowed us to reveal the factors, which are powerful in explaining, why some stores have higher rates of willingness to make repeat purchases than the others. By confronting the indirect importance and performance measures for three different internet stores, we have revealed strengths, weaknesses, attributes that the company should bring customers’ attention to and attributes improvement of which is not of a high priority.

Added: Oct 4, 2012