Predicting travel intentions using self-disclosure, trust and intimacy: the case of Tinder users during COVID-19

Abstract

PurposeThis 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/approachThis quantitative research conveniently sampled 294 Tinder users who used the Passport feature during COVID-19 pandemic lockdowns. Data were analysed using PLS-SEM.FindingsThis 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 implicationsTourism-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/valueThis 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.