Two of a kind: Similarities between ranking and rating data in measuring work values

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
42 Downloads (Pure)

Abstract

The key research question asked in this research is to what extent the respondents’ answers to ranking a set of items is mirrored in the response pattern when using rating questions. For example: Do respondents who prefer intrinsic over extrinsic work values in a ranking questionnaire also rate intrinsic values higher than extrinsic values when ratings are used? We adopt a modified version of the form-resistant hypothesis, arguing that each questionnaire mode yields unique features that prevent it from establishing a perfect match between both modes. By adopting a unified latent class model that allows identifying latent class profiles that share a particular preference structure in both question modes, we show that a large portion of respondents tend to identify similar preferences structures in work values regardless of the questionnaire mode used. At the same time the within-subjects design we use is able to answer questions regarding how non-differentiators in a rating assignment react to a ranking assignment in which non-differentiation is excluded by design. Our findings are important since – contrary to popular belief – ranking and ratings do produce results that are more similar than often thought. The practical relevance of our study for secondary data analysts is that our approach provides them with a tool to identify relative preference structures in a given dataset that was asked by rating questions and hence not directly designed to reveal such preferences.
Keywords: Rating and Ranking questions, Survey methodology, Measuring attitudes and values, Latent class analysis, Questionnaire modes
Original languageEnglish
Pages (from-to)15-33
JournalSurvey Research Methods
Volume10
Issue number1
DOIs
Publication statusPublished - 2016

Fingerprint Dive into the research topics of 'Two of a kind: Similarities between ranking and rating data in measuring work values'. Together they form a unique fingerprint.

  • Cite this