carconf: Data (partial rankings): Car Configurator
In prefmod: Utilities to Fit Paired Comparison Models for Preferences
carconf R Documentation
Data (partial rankings): Car Configurator
Description
Online configuration systems allow customers to actively participate in the creation of products and become increasingly important in various market sectors.
Dabic and Hatzinger report a study on car configurators that aimed at investigating the effects of certain person characteristics (such as gender) on the configuration process.
Subjects were asked to configure a car according to their preferences.
They could choose freely from several modules: such as exterior and interior design, technical equipment, brand, price, and producing country.
The order of module choice was recorded as ranks.
Since not all modules had to be chosen the response format was partial rankings.
Usage
carconf
Format
A data frame with 435 observations on the following 9 variables.
pricerank (1 highest preference)
exteriorrank
brandrank
tech.equiprank
countryrank
interiorrank
sex1 female 2 male
age1 17–29 years, 2 30–49 years, 3 50+ years
segmentpreferred car type: 1 premium-class, 2 medium-class, 3 low-budget
Source
Dabic, M., & Hatzinger, R. (2009). Zielgruppenadäquate Abläufe in Konfigurationssystemen – eine empirische Studie im Automobilmarkt: Das Paarvergleichs-Pattern-Modell für Partial Rankings. In R. Hatzinger, R. Dittrich, & T. Salzberger (Eds.), Präferenzanalyse mit R: Anwendungen aus Marketing, Behavioural Finance und Human Resource Management (pp. 119–150). Wien: Facultas.
Examples
head(carconf)
prefmod documentation built on June 11, 2022, 3 p.m.
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| carconf | R Documentation |
Data (partial rankings): Car Configurator
Description
Online configuration systems allow customers to actively participate in the creation of products and become increasingly important in various market sectors. Dabic and Hatzinger report a study on car configurators that aimed at investigating the effects of certain person characteristics (such as gender) on the configuration process. Subjects were asked to configure a car according to their preferences. They could choose freely from several modules: such as exterior and interior design, technical equipment, brand, price, and producing country. The order of module choice was recorded as ranks. Since not all modules had to be chosen the response format was partial rankings.
Usage
carconf
Format
A data frame with 435 observations on the following 9 variables.
pricerank (1 highest preference)
exteriorrank
brandrank
tech.equiprank
countryrank
interiorrank
sex1 female 2 male
age1 17–29 years, 2 30–49 years, 3 50+ years
segmentpreferred car type: 1 premium-class, 2 medium-class, 3 low-budget
Source
Dabic, M., & Hatzinger, R. (2009). Zielgruppenadäquate Abläufe in Konfigurationssystemen – eine empirische Studie im Automobilmarkt: Das Paarvergleichs-Pattern-Modell für Partial Rankings. In R. Hatzinger, R. Dittrich, & T. Salzberger (Eds.), Präferenzanalyse mit R: Anwendungen aus Marketing, Behavioural Finance und Human Resource Management (pp. 119–150). Wien: Facultas.
Examples
head(carconf)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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