Examining the efficacy of self-classification approach in segmenting special-interest tourists: food tourism case

Tianyu Ying, Jun Wen, Rob Law, Liang Wang, William C. Norman

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)

Abstract

Self-classification is used as an a priori approach to tourist typology and market segmentation. However, skepticism still surrounds its ability to incorporate the multidimensionality of tourist behavior. This study seeks to empirically verify the efficacy of a single-item self-classification approach. The robustness of this self-classification measure is examined by comparing it to a data-driven multidimensional psychographic approach in terms of its ability to predict the behaviors of tourists toward food-related destination consumption. Results suggest that the single-item self-classification approach performs equally well as the psychographic approach in segmenting food-related consumption behaviors. The implications and limitations of this study are also discussed.

Original languageEnglish
Pages (from-to)961-974
Number of pages14
JournalAsia Pacific Journal of Tourism Research
Volume23
Issue number10
DOIs
Publication statusPublished - 3 Oct 2018

Keywords

  • food tourism
  • food-related destination consumption
  • market segmentation
  • psychographic segmentation
  • Self-classification
  • tourist typology

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Tourism, Leisure and Hospitality Management

Cite this