PLMIX (version 2.2.0)

d_carconf: Car Configurator Data (partial orderings)

Description

The Car Configurator dataset (d_carconf) came up from a marketing study aimed at investigating customer preferences toward different car features. A sample of \(N=435\) customers were asked to construct their car by using an online configurator system and choose among \(K=6\) car modules in order of preference. The car features are labeled as: 1 = price, 2 = exterior design, 3 = brand, 4 = technical equipment, 5 = producing country and 6 = interior design. The survey did not require a complete ranking elicitation, therefore the dataset is composed of partial top orderings of varying lengths. Missing positions are denoted with zero entries.

Format

Object of S3 class c("top_ordering","matrix") gathering a matrix of partial orderings with \(N=435\) rows and \(K=6\) columns. Each row lists the car features from the most important (Rank_1) to the least important (Rank_6) for a given customer.

References

Mollica, C. and Tardella, L. (2017). Bayesian Plackett-Luce mixture models for partially ranked data. Psychometrika, 82(2), pages 442--458, ISSN: 0033-3123, <doi: 10.1007/s11336-016-9530-0>.

Hatzinger, R. and Dittrich, R. (2012). Prefmod: An R package for modeling preferences based on paired comparisons, rankings, or ratings. Journal of Statistical Software, 48(10), pages 1--31.

Dabic, M. and Hatzinger, R. (2009). Zielgruppenadaequate Ablaeufe in Konfigurationssystemen - eine empirische Studie im Automobilmarkt - Partial Rankings. In Hatzinger, R., Dittrich, R. and Salzberger, T. (eds), Praeferenzanalyse mit R: Anwendungen aus Marketing, Behavioural Finance und Human Resource Management. Wien: Facultas.

Examples

data(d_carconf)
head(d_carconf)

## Subset of complete sequences
d_carconf_compl=d_carconf[rowSums(d_carconf!=0)>=(ncol(d_carconf)-1),]
head(d_carconf_compl)