R packages and tutorial for case 1 best–worst scaling

Hideo Aizaki and James Fogarty

Journal of choice modelling, 2023, vol. 46, issue C

Abstract: Case 1 best–worst scaling (BWS1) has been used in a wide variety of research fields. BWS1 is attractive, relative to discrete choice experiments, because individual’s preferences for items can be easily measured. Despite the relative ease of implementation, BWS1 analysis still requires the use of software packages. When used in conjunction with other packages, the new and revised functions in the package support.BWS allow BWS1 analysis to be conducted using either the counting approach or the modeling approach. Additionally, a new function that simulates responses to BWS1 questions allows discipline specific BWS1 examples to be created for teaching purposes. To make it easier for novice users to implement BWS1 analysis with R, the package RcmdrPlugin.BWS1, that integrates with R Commander has been developed. A free web tutorial for BWS1 in R has also been developed. This paper explains the features of the latest version of support.BWS, along with the new package RcmdrPlugin.BWS1, and illustrates how these packages work.

Keywords: Best worst scaling; Maxdiff; Object case; R package (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1755534522000513
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:eejocm:v:46:y:2023:i:c:s1755534522000513

DOI: 10.1016/j.jocm.2022.100394

Access Statistics for this article

Journal of choice modelling is currently edited by S. Hess and J.M. Rose

More articles in Journal of choice modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().