Hi, Tarcza:

Researchers have recently introduced a finite mixture Bayesian regression model to simultaneously identify consumer market segments (heterogeneity) and determine how such segments differ with respect to active regression coefficients (variable selection). In this study ( Sughoon, Blanchard, Desarbo & Fong, 2013) introduced three extensions of this model to incorporate managerial restrictions (constraints).

The authors demonstrate with synthetic data that the new constrained finite mixture Bayesian regression models can be used to identify and represent several constrained heterogeneous response patterns commonly encountered in practice. In addition, they show that the proposed models are more robust against multicollinearity than traditional methods. Finally, to illustrate the proposed models' usefulness, the authors apply the proposed constrained models in the context of a service quality (SERVPERF) survey of National Insurance Company's customers.

• SUNGHOON, K., BLANCHARD, S. J., DESARBO, W. S., & FONG, D. H. (2013). Implementing Managerial Constraints in Model-Based Segmentation: Extensions of Kim, Fong, and DeSarbo (2012) with an Application to Heterogeneous Perceptions of Service Quality. Journal Of Marketing Research (JMR), 50(5), 664-673.

Hope this helps!

Nadeem

Dear Tarcsa Teodora:

Indicator Consumer Satisfaction. It is correct.

Thank you

Do you mean theoretical models or for data analysis?

Theoretical:

Attitude-based segmentation, Motives-based segmentation, Buying intensity

Psichographic/Lifestyle: AIO, attitudes, interests, opinion, VALS, social milieu, e.g. SINUS milieu

Food related: FCQ (Steptoe et al. 1995), FRL (food-related lifestyle, famous are Grunert's versions)

Data analysis:

Cluster analysis (Ward, k-means; latent-class e.g. probability based)

Hello Tarzca,

Clustering- Moving k-means- especially for data redundancy.

Dear Teodora,

From my point of view I can recommend  you a standard.

Namely ISO 10002:2004 ”Quality management -- Customer satisfaction -- Guidelines for complaints handling in organizations”

Thank you for all your answers.