Abstract
In the last decades the use of regression-like preference models has found widespread application in marketing research. The Conjoint Analysis models have even more been used to analyze consumer preferences and simulate product positioning. The typical data structure of this kind of models can be enriched by the presence of supplementary information observed on respondents. We suppose that relational data observed on pairs of consumers are available. In such a case, the existence of a consumer network is introduced in the Conjoint model as a set of contiguous constraints among the respondents. The proposed approach will allow to bring together the theoretical framework of Social Network Analysis with the explicative power of Conjoint Analysis models. The combined use of relational and choice data could be usefully exploited in the framework of relational and tribal marketing strategies.
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Giordano, G., Scepi, G. (2012). Network Data as Contiguity Constraints in Modeling Preference Data. In: Gaul, W., Geyer-Schulz, A., Schmidt-Thieme, L., Kunze, J. (eds) Challenges at the Interface of Data Analysis, Computer Science, and Optimization. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24466-7_24
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DOI: https://doi.org/10.1007/978-3-642-24466-7_24
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