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MEASUREMENT OF MUSIC STREAMERS’ PREFERENCES USING BEST-WORST SCALING AND CONJOINT ANALYSIS METHODS.

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Titel: MEASUREMENT OF MUSIC STREAMERS’ PREFERENCES USING BEST-WORST SCALING AND CONJOINT ANALYSIS METHODS.
Autoren: BARTŁOMOWICZ, Tomasz1 tomasz.bartlomowicz@ue.wroc.pl
Quelle: Scientific Papers of Silesian University of Technology. Organization & Management / Zeszyty Naukowe Politechniki Slaskiej. Seria Organizacji i Zarzadzanie. 2025, Issue 218, p39-67. 29p.
Schlagwörter: *CONJOINT analysis, *SOCIAL impact, PACKAGING waste, LOGISTIC regression analysis, AREA measurement
Abstract: Purpose: The main aim of the research was to measure the music streamers’ preferences using Best-Worst Scaling and conjoint analysis methods. The additional purpose is to compare the results obtained from both used methods, which should get similar conclusions. Finally, the cooperation of the support.BWS3 and conjoint R packages as the one common tool for measurement of stated preferences was also examined. Design/methodology/approach: Multi-profile Best-Worst Scaling method uses a modeling approach based on the conditional logit model, whereas traditional conjoint analysis method applies a linear regression model. Therefore, comparing the results of both methods was even more interesting. Findings: In the paper, the results of measurement and analysis of music streamers’ preferences were presented, calculations from different preference models were confronted and the correct use of R packages in the form of completed scripts was demonstrated. Research limitations/implications: The limitations of one used method were compensated by the second one. The cooperation of both methods and used R packages was not only confirmed but also led to complete the research results. Practical implications: The research results, as well as the combined use of some R packages may interest practitioners, researchers and students in the fields of marketing research, in the area of measurement of consumers’ preferences. Streaming companies, manufacturers of playback equipment, artist and record labels as well as marketers should be interested in the research results. Social implications: One of the used packages – authoring conjoint R package implements the traditional conjoint analysis method similarly to the module Conjoint IBM SPSS program. The statistics (over a half million of downloads) indicate that the non-commercial conjoint package is popular among R users. Originality/value: In addition to the benefits in form of conclusions drawn from the research, the paper presents one more example confirming results of both used methods. There are no similar studies confirming the results of multi-profile Best-Worst Scaling (Case 3 BWS) and traditional conjoint analysis methods based on measurement of music streamers’ preferences. [ABSTRACT FROM AUTHOR]
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Datenbank: Business Source Index
Beschreibung
Abstract:Purpose: The main aim of the research was to measure the music streamers’ preferences using Best-Worst Scaling and conjoint analysis methods. The additional purpose is to compare the results obtained from both used methods, which should get similar conclusions. Finally, the cooperation of the support.BWS3 and conjoint R packages as the one common tool for measurement of stated preferences was also examined. Design/methodology/approach: Multi-profile Best-Worst Scaling method uses a modeling approach based on the conditional logit model, whereas traditional conjoint analysis method applies a linear regression model. Therefore, comparing the results of both methods was even more interesting. Findings: In the paper, the results of measurement and analysis of music streamers’ preferences were presented, calculations from different preference models were confronted and the correct use of R packages in the form of completed scripts was demonstrated. Research limitations/implications: The limitations of one used method were compensated by the second one. The cooperation of both methods and used R packages was not only confirmed but also led to complete the research results. Practical implications: The research results, as well as the combined use of some R packages may interest practitioners, researchers and students in the fields of marketing research, in the area of measurement of consumers’ preferences. Streaming companies, manufacturers of playback equipment, artist and record labels as well as marketers should be interested in the research results. Social implications: One of the used packages – authoring conjoint R package implements the traditional conjoint analysis method similarly to the module Conjoint IBM SPSS program. The statistics (over a half million of downloads) indicate that the non-commercial conjoint package is popular among R users. Originality/value: In addition to the benefits in form of conclusions drawn from the research, the paper presents one more example confirming results of both used methods. There are no similar studies confirming the results of multi-profile Best-Worst Scaling (Case 3 BWS) and traditional conjoint analysis methods based on measurement of music streamers’ preferences. [ABSTRACT FROM AUTHOR]
ISSN:16413466
DOI:10.29119/1641-3466.2025.218.2