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Tourist Choice Processing: Evaluating Decision Rules and Methods of Their Measurement

Li, Chunxiao; McCabe, Scott; Song, Haiyan

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Authors

Chunxiao Li

Scott McCabe

Haiyan Song



Abstract

A detailed understanding of decision rules is essential in order to better explain consumption behavior, yet the variety of decision rules used have been somewhat neglected in tourism research. This study adopts an innovative method, greedoid analysis, to estimate a noncompensatory type of decision rule known as lexicographic by aspect (LBA). It is quite different from the weighted additive (WADD) model commonly assumed in tourism studies. By utilizing an experimental research design, this study enables the evaluation of the two types of decision rules regarding their predictive and explanatory power. Additionally, we introduce a novel evaluation indicator (“cost”), which allows further investigation of the heterogeneity in the use of decision rules. The results suggest that although the out-of-sample accuracy is lower, the LBA model has a better explanatory performance on respondents’ preference order. Moreover, the different perspective provided by the LBA model is useful for obtaining managerial implications.

Citation

Li, C., McCabe, S., & Song, H. (2017). Tourist Choice Processing: Evaluating Decision Rules and Methods of Their Measurement. Journal of Travel Research, 56(6), 699-711. https://doi.org/10.1177/0047287516663651

Journal Article Type Article
Acceptance Date Jun 29, 2016
Online Publication Date Aug 23, 2016
Publication Date Jul 1, 2017
Deposit Date Jun 14, 2017
Publicly Available Date Mar 29, 2024
Journal Journal of Travel Research
Print ISSN 0047-2875
Electronic ISSN 1552-6763
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
Volume 56
Issue 6
Pages 699-711
DOI https://doi.org/10.1177/0047287516663651
Keywords tourist decision making, destination choice measurement, noncompensatory methods, greedoid analysis, China outbound market
Public URL https://nottingham-repository.worktribe.com/output/804776
Publisher URL http://journals.sagepub.com/doi/abs/10.1177/0047287516663651

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