carconf: Data (partial rankings): Car Configurator

Description Usage Format Source Examples

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

1

Format

A data frame with 435 observations on the following 9 variables.

price

rank (1 highest preference)

exterior

rank

brand

rank

tech.equip

rank

country

rank

interior

rank

sex

1 female 2 male

age

1 17–29 years, 2 30–49 years, 3 50+ years

segment

preferred 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

1

prefmod documentation built on May 2, 2019, 4:59 p.m.