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Cited by 197

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

An Application of Travel Blog Narratives to Explore Memorable Tourism Experiences

Chandralal, Lalith, Rindfleish, Jennifer, Valenzuela, Fredy·2015·Asia Pacific Journal of Tourism Research

Abstract

This paper is based on a netnography investigation into the likely components of memorable tourism experiences (MTEs) using travel blog narratives by travellers. One hundred travel blog narratives published by travellers in two reputable travel blogs were used for the study. The results revealed two major findings: (a) bloggers mostly report positive MTEs in their experiential narratives and (b) such positive MTEs are often associated with seven experiential themes: (1) local people, life and culture (2) personally significant experiences (3) shared experiences (4) perceived novelty (5) perceived serendipity (6) professional guides and tour operator services and (7) affective emotions associated with memorable experiences. The findings provide important theoretical and managerial implications.

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Registry

Crossref · 10.1080/10941665.2014.925944

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Metadata

Authors
Chandralal, L., Rindfleish, J., & Valenzuela, F.
Venue
Asia Pacific Journal of Tourism Research
Published
2014-06-16
Volume
20
Issue
6
Pages
680-693
ISSN
  • 1094-1665 (ISSN-L)
  • 1741-6507
OpenAlex
W2044815232
Cited by
197
References
3
FWCI
17.30
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: An Application of Travel Blog Narratives to Explore Memorable Tourism Experiences. https://app.cochat.ai/papers/10.1080/10941665.2014.925944
The paper
Chandralal, L., Rindfleish, J., & Valenzuela, F. (2015). An Application of Travel Blog Narratives to Explore Memorable Tourism Experiences. Asia Pacific Journal of Tourism Research. https://doi.org/10.1080/10941665.2014.925944

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.