Consumer acceptance of mobile wallet in the hospitality industry

Salman Khan & Qingyu Zhang

International Hospitality Review2025https://doi.org/10.1108/ihr-07-2023-0038article
AJG 1
Weight
0.41

What the paper says

Purpose This study examines the drivers of consumers’ intentions to adopt mobile wallets in Pakistan’s hospitality industry. Specifically, it proposes and tests a model of non-user consumer intention to adopt mobile wallets for hospitality in Pakistan. Design/methodology/approach A conceptual framework grounded in the mobile technology acceptance model (MTAM) integrating personal innovativeness in IT, mobile perceived compatibility, perceived critical mass, perceived enjoyment, mobile perceived risk and mobile perceived wireless trust was used as a theoretical model of the study. Using structural equation modeling, we tested the research model and its relevant hypotheses on a sample of 310 mobile wallet nonusers. Findings Findings from the expanded model demonstrate that only four of the suggested hypotheses were insignificant in this study and require additional examination. Overall, the modified model explained 63% of the variance in the behavioral intention to adopt mobile wallets. This paper concludes with key implications and directions for future work concerning the limitations of this study. Originality/value This study contributes to a theoretical understanding of the factors that explain nonusers’ behavioral intention to use a mobile wallet in the hospitality context.

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https://doi.org/https://doi.org/10.1108/ihr-07-2023-0038

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@article{salman2025,
  title        = {{Consumer acceptance of mobile wallet in the hospitality industry}},
  author       = {Salman Khan & Qingyu Zhang},
  journal      = {International Hospitality Review},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1108/ihr-07-2023-0038},
}

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.