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Cited by 170

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Understanding memorable tourism experiences as the determinants of tourists' behaviour

Sharma, Pramod, Nayak, Jogendra Kumar·2019·International Journal of Tourism Research

Abstract

This study empirically investigated a theoretical model predicting the direct and indirect effects of memorable tourism experiences (MTEs) on behavioural intentions via destination image and tourists' satisfaction in yoga tourism. This research was conducted using data collected from 502 tourists visiting Rishikesh in India. Using confirmatory factor analysis and SPSS macro (PROCESS), findings confirmed that MTEs influenced behavioural intentions both directly and indirectly via destination image and tourists' satisfaction. MTEs were found as the strongest influencer of behavioural intentions in yoga tourism. This study opposes those researchers and practitioners who argued tourists' satisfaction alone as the most significant influencer of destination performance.

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Crossref · 10.1002/jtr.2278This paper is marked retracted.

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Metadata

Authors
Sharma, P., & Nayak, J. K.
Venue
International Journal of Tourism Research
Publisher
Wiley
Published
2019-05-02
Volume
21
Issue
4
Pages
504-518
ISSN
  • 1099-2340 (ISSN-L)
  • 1522-1970
OpenAlex
W2942683073
Cited by
170
References
9
FWCI
32.31
Type
journal article
Language
en
Status
Retracted
Open access
closed

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CoChat. (2026). Citation check: Understanding memorable tourism experiences as the determinants of tourists' behaviour. https://app.cochat.ai/papers/10.1002/jtr.2278
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Sharma, P., & Nayak, J. K. (2019). Understanding memorable tourism experiences as the determinants of tourists' behaviour. International Journal of Tourism Research. https://doi.org/10.1002/jtr.2278

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.