Using dummy regression to explore asymmetric effects in tourist satisfaction: A cautionary note
Josip Mikulic and
Darko Prebežac
Tourism Management, 2012, vol. 33, issue 3, 713-716
Abstract:
This research note addresses the misuse of standardized weights as measures of effect in dummy regression, which is the most frequently used technique for assessing asymmetric effects in the formation of tourist satisfaction. Unlike in regular regressions, standardized weights have no straightforward interpretation in dummy regressions, but they only carry the risk of providing misleading implications in theory building and guiding managerial action. To empirically underpin the arguments put forward in this note, an illustrative case example is used that provides insight into the underlying statistical mechanisms that cause unstandardized and standardized weights to provide significantly different implications in dummy regressions. The findings of this note should help to prevent bad practice in future studies that make use of the technique in assessments of asymmetric effects in customer satisfaction and/or the three-factor structure of customer satisfaction. However, the points put forward hold for dummy regressions in general.
Keywords: Tourist satisfaction; Asymmetric effects; Three-factor theory; Dummy regression; Penalty–reward-contrast analysis (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0261517711001580
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:touman:v:33:y:2012:i:3:p:713-716
DOI: 10.1016/j.tourman.2011.08.005
Access Statistics for this article
Tourism Management is currently edited by Chris Ryan
More articles in Tourism Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().