Research Article
A Comparison of the Different Types of Risk Perceived by Users that Are Hindering the Adoption of Mobile Payment
@INPROCEEDINGS{10.1007/978-3-030-23943-5_14, author={Laure Pauchard}, title={A Comparison of the Different Types of Risk Perceived by Users that Are Hindering the Adoption of Mobile Payment}, proceedings={Emerging Technologies in Computing. Second International Conference, iCETiC 2019, London, UK, August 19--20, 2019, Proceedings}, proceedings_a={ICETIC}, year={2019}, month={7}, keywords={Mobile payment adoption User acceptance Hindering factors Perceived Risk}, doi={10.1007/978-3-030-23943-5_14} }
- Laure Pauchard
Year: 2019
A Comparison of the Different Types of Risk Perceived by Users that Are Hindering the Adoption of Mobile Payment
ICETIC
Springer
DOI: 10.1007/978-3-030-23943-5_14
Abstract
Recent research has established that the risk perceived by users is one of the main reasons why, despite offering numerous benefits, the worldwide adoption of mobile payment remains surprisingly low. This pilot study aims to establish more specifically what types of risk have a negative effect on the adoption of mobile payment by proposing a new research model solely focused on the risk dimension. The model is composed of 6 types of risk that were extracted from the existing literature investigating mobile payment adoption. A 5-point likert scale-based questionnaire was used to collect sample data to test the model. The data was subsequently analysed by conducting a reliability analysis of the scale and a regression analysis aiming to quantify the effect of the variables on the users’ intention to use mobile payment. The results of the study suggest that Security Risk is the highest deterrent, followed by Financial Risk, Social Risk, Privacy Risk and Time Risk while Psychological Risk was not found to have any negative effect on the users’ Intention of Use. These findings potentially have implications for stakeholders such as mobile phone manufacturers and banking organisations as testing the research model on a larger sample of data would identify more precisely what aspects of mobile payment should be improved to increase its appeal to consumers. Furthermore, the proposed model can assist further research aiming to identify what features could reduce the risk perceived by potential mobile payment users.