Exploring Tourists’ Behavioural Intentions Towards Use of Select Mobile Wallets for Digital Payments

Abstract

The present study goal is to identify assorted factors and also to investigate their influence on tourists’ behavioural intentions about their usage patterns with respect to M-wallet payment. A conceptual model has been anticipated and authenticated and 600 questionnaires were distributed and 482 were usable. Structural equation modelling was employed to assess research hypotheses. The result shows that the behavioural intention is significantly influenced by perceived value, trust, compatibility and social influence while tourists’ is less optimistic when it comes to use M-wallet with regard to perceived enjoyment. The study also showed that trust followed by compatibility has a more powerful influence on the behavioural intention of tourists in the context of M-payment. The present study is limited to only six M-wallet and that too limited to the certain age category, namely 18–25 in Gwalior city of India. Understanding the different dimensions of behavioural intentions can help M-wallet players to win the trust of tourists and enhance the frequency to use M-wallet for M-payment. The results indicate that M-wallet service providers should consider and manage all affecting factors proactively as mechanisms for intention to use M-wallet. It will establish a behavioural intention model of M-wallet users that can help organizations to manage the formation of behavioural intentions of their users.

Understanding intentions and actual use of mobile wallets by millennial: an extended TAM model perspective

“…Additionally, previous studies found trust as essential driver of technology adoption in context of mobile banking (Alalwan et al, 2017) and mobile learning (Chao, 2019). Recent studies in the context of mobile wallet found significant influence of trust on BIs (Chawla and Joshi, 2020;Hasan and Gupta, 2020).…”

“…Extant studies examined the intentions of millennial generation to use the mobile wallets using TAM (Pertiwi et al, 2020). However, Hasan and Gupta (2020) posited that in India there are 135 million e-wallet users, and they have conducted a study with the objective to recognize the determinants of tourists' behavioral intentions to use m-wallet payment with extended TAM model. In the present study, we have applied the TAM model in context of developing nation.…”

Assessing Antecedents of Behavioral Intention to Use Mobile Technologies in E-Commerce

“…Ngubelanga and Duffett [30] investigated the antecedents of customer satisfaction following the use of m-commerce applications by consumers; showing that confidence, social influence, mobility, involvement, and innovation positively influence usefulness and ease of use. Other research has shown that social influence is the main factor in adopting mobile devices and their use as an e-commerce channel [31][32][33][34][35][36][37].…”

“…Depending on the domain in which the TAM model is applied, these two main variables are influenced by domain-specific external variables. Our research used the external variables (antecedents) of trust, convenience, customization, innovativeness, rapidity, accessibility, mobility, and enjoyment; variables identified and used in multiple other studies [10,11,[29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][66][67][68][69][70][71][72][73][74][75][76][77][78]. Our theoretical model defines PEU and PU as latent variables influenced by external variables.…”

“…Conceptual structural model. Source: own construction based on[10,11,[29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44][45][66][67][68][69][70][71][72][73][74][75][76][77][78].…”