A study on understanding QR-based m-payment adoption intention and satisfaction among consumers in India

V Shunmugasundaram et al.

European Journal of Management Studies2025https://doi.org/10.1108/ejms-03-2025-0024article
ABDC C
Weight
0.37

What the paper says

Purpose Its goal is to determine the factors that affect consumers' intention to use and satisfaction with QR-based mobile payments by incorporating the constructs of the UTAUT2 model and adding one more construct from the diffusion of innovation theory. Design/methodology/approach The present study adopted a quantitative survey whereby data were gathered using a convenience sampling technique from QR-based m-payment users residing in New Delhi. Findings The findings suggest that habit, facilitating conditions, performance expectancy and relative advantage had a strong influence, while social influence does not affect users' satisfaction and intention to use. Research limitations/implications In this study, we used the UTAUT2 model to study the intention to use and satisfaction toward the adoption of QR-based m-payment, Further studies can use other established models for technology adoption to study the behavioral intention of the users toward technology adoption. Originality/value This study contributes to the mobile payment literature by going beyond the widely studied construct of technology adoption intention to also address user satisfaction, thereby linking pre- and post-adoption perspectives.

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https://doi.org/https://doi.org/10.1108/ejms-03-2025-0024

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@article{v2025,
  title        = {{A study on understanding QR-based m-payment adoption intention and satisfaction among consumers in India}},
  author       = {V Shunmugasundaram et al.},
  journal      = {European Journal of Management Studies},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1108/ejms-03-2025-0024},
}

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Evidence weight

0.37

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

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 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.