The conjoint R package as a tool for measuring stated preferences

Abstract

Two groups of research methods are used in the decompositional approach to stated preferences-conjoint analysis methods and discrete choice methods. The most commonly applied traditional conjoint analysis method is an example of the first group. Because of its computational complexity, its practical application requires using appropriate commercial or non-commercial computer software. The purpose of the article is to present the traditional conjoint analysis method and discuss its implementation in the form of the conjoint package for R program, which with CRAN packages is currently one of the most important non-commercial computing environments for statistical data analysis. In addition to the detailed characteristics of the individual conjoint R package functions, the paper also presents the application of the conjoint package in marketing research, along with the interpretation of the selected results, based on the example of measuring and analysing stated preferences of beer consumers.

Segmentation of e-customers in terms of sustainable last-mile delivery

“…The last stage in the conjoint analysis is segmentation, which was performed in the R program using the classification method of k-medoids, which enables the division of the data set into classes (from 2 to 10 classes). The gap index programmed in the clusterSIM package was used (Bartłomowicz, & Bąk, 2019) to select the number of classes. When determining the number of classes, the value of diffu was considered.…”