Intenção de adoção do mobile payment : uma análise à luz das teorias de aceitação e uso de tecnologia

Abstract

The technological improvement coupled with the growing use of smartphones has, amongst other functions, facilitated purchase transactions and payment by mobile phone. This phenomenon occurs worldwide and allows individuals more flexibility and convenience in carrying out their daily activities. This research aims to evaluate the relationship between background factors most used in adoption intention studies and the use of new technologies related to mobile payment services to current mobile phone customers. The low number of publications about this subject in Brazil, the generation of relevant information to industries in this sector and the development of technologies that benefit the general population justify the work. In this context, we applied the model UTAUT (Unified Theory of Acceptance and Use of Technology), which integrates elements of the eight models previously developed on prediction, acceptance and use of technology, set by Williams et al. (2011) and increased by additional factors (cost and perceived risk) to determine use intention (SHAFINAH et al., 2013). The resulting construct sought to improve the application of the original model to mobile services and consisted of the following variables: Performance Expectancy, Effort Expectancy, Social Influence, Perceived Cost, Perceived Risk and Behavioral Intention .A survey was carried out with mobile customers from a telecommunications company that operates in southeastern Brazil, providing a valid sample of 605 respondents. The Structural Equation Modeling has been used for the data analysis and validation of the research hypotheses. Four out of the five hypotheses developed in the work were confirmed from the proposed structural model, and the ratio of adopting intention (R²) indicated that 76.2% of the variation could be explained by the relation with the background factors under study. The Performance Expectation (ED) was the most important variable in explaining the variance of behavioral intention to use the service (47.1%). The Effort Expectancy (EE), the Social Influence (IS) and the Perceived Risk (PR) also contributed to a lesser extent for this explanation. On the other hand, the Perceived Cost (CP) was statistically insignificant. The findings contribute to the expansion of academic and managerial knowledge on the subject. In addition, the study presents its limitations and makes suggestions for future academic work.