d_carconf {PLMIX} | R Documentation |
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.
Usage
data(d_carconf)
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)