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Article
Publication date: 9 April 2018

Lishan Xie, Xiaoyun Han and Hui Fu

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International Journal of Contemporary Hospitality Management, vol. 30 no. 4
Type: Research Article
ISSN: 0959-6119

Open Access
Article
Publication date: 15 February 2022

Kyrie Eleison Munoz

This paper determines how travel intentions can be predicted using self-disclosure behaviour, trust and intimacy. This case study focuses on Tinder users who utilised the…

2192

Abstract

Purpose

This paper determines how travel intentions can be predicted using self-disclosure behaviour, trust and intimacy. This case study focuses on Tinder users who utilised the application's Passport feature which allowed them to travel virtually and interact with other users around the globe amid global travel restrictions.

Design/methodology/approach

This quantitative research conveniently sampled 294 Tinder users who used the Passport feature during COVID-19 pandemic lockdowns. Data were analysed using PLS-SEM.

Findings

This study revealed that self-disclosure had a significant influence towards future travel intentions. Findings show that the more users self-disclose, the more their intent to travel increase. Trust and intimacy also had significant relationship on travel intentions while intimacy had a mediating effect between self-disclosure and travel intentions.

Practical implications

Tourism-oriented establishments and destination marketers should consider Tinder users as a market segment of future tourists. These users have developed travel intentions through in-app interactions and thus comprise an untapped market of potential tourists seeking for meet-ups and niche experiences in a post-pandemic era.

Originality/value

This study provides novelty in showing the predictive relationship of self-disclosure, trust and intimacy towards travel intentions. A model consisting of these constructs in the context of online interactions was also empirically tested and found adequate to predict travel intentions.

Details

Journal of Tourism Futures, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2055-5911

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