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The main goal of our research is to analyze users' acceptance of mobile payment systems, considering the population's widespread use of mobile devices. In order to explain acceptance, we have added trust and perceived risk to the traditional variables. To this end, we have carried out a study through an online survey to a national panel of Internet users. The results of this survey check the implications considered on the basis of the Technological Acceptance Model, the Theory of Reasoned Action and the trust building principles for a given system. The conclusions and implications for management provide alternatives for companies to promote this new business by means of the new technical developments.

Amid the pandemic infection, people are bound to use contactless mobile payment (M-Payment) services. M-Payment is a payment method using an application in a mobile device, such as a mobile phone, and gadget. Owing to the convenience, reliability and contact-free feature of M-Payment, it has been diffusely adopted to reduce the direct and indirect contacts in transactions, allowing social distancing to be maintained and facilitating the stabilization of the social economy. Consequently, it has become one of the day’s most important topics. Therefore, the purpose of this study is to provide a systematic literature review (SLR) on the applications of M-payment services in financial strategies, focusing on the pandemic crisis. 19 papers were collected and divided into three groups for further analysis. The results showed that M-Payments applications in financial strategies during the pandemic crisis could help reduce the spread of infection risks by hastening the transition to touchless habits.

The acceptance of mobile payments has been limited. This paper, therefore, attempts to investigate the determinants of mobile payment adoption. To this end, it examines the relationships between the personality trait dimensions of the Technology Readiness Index 2.0 and the system-specific dimensions of the Technology Acceptance Model in Germany and South Africa. The model was tested using structural equation modeling. Results show that some, but not all, of the Technology Readiness Index 2.0 variables had a significant influence on the dimensions of the Technology Acceptance Model. Perceived Usefulness was the strongest predictor of the intention to use mobile payments. The factor “country” did not moderate the structural relationships.