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Cited by 1,054

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Developing the Travel Career Approach to Tourist Motivation

Pearce, Philip L., Lee, Uk-Il·2005·Journal of Travel Research

Abstract

The purpose of this study lies in the conceptual adjustment of the travel career ladder (TCL) approach to travel motivation. In this context, the study examined the relationship between patterns of travel motivation and travel experience. This research was conducted through two studies: an interview phase to guide the further conceptual development of the travel career approach and a major survey phase for further empirical exploration of the ideas. Overall results suggested that host-site-involvement motivation (e.g., experiencing different cultures) and nature-related motivation (e.g., being close to nature) were more important factors to the more experienced travelers, whereas motivations such as stimulation, personal development, relationship (security), self-actualization, nostalgia, romance, and recognition had a higher priority for the less experienced ones. Importantly, a core of travel motivation factors including escape, relaxation, relationship enhancement, and self-development seem to comprise the central backbone of motivation for all travelers.

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Crossref · 10.1177/0047287504272020

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Metadata

Authors
Pearce, P. L., & Lee, U.-I.
Venue
Journal of Travel Research
Published
2005-02
Volume
43
Issue
3
Pages
226-237
ISSN
  • 0047-2875 (ISSN-L)
  • 1552-6763
OpenAlex
W2156480840
Cited by
1,054
References
1
FWCI
50.84
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Developing the Travel Career Approach to Tourist Motivation. https://app.cochat.ai/papers/10.1177/0047287504272020
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Pearce, P. L., & Lee, U.-I. (2005). Developing the Travel Career Approach to Tourist Motivation. Journal of Travel Research. https://doi.org/10.1177/0047287504272020

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.