Abstract
Based on the analysis of previous research in the field of technological acceptance models, the aim of this study is to clarify the significance of individual social media factors in connection with the use of electronic banking in the light of unified theory of acceptance and use of technology. The aim of the article is to describe a model that identifies the influence of social media use factors on the use of electronic banking. The purpose of this model is to explain how these factors influence user behavior in the context of using electronic banking. To obtain primary data sources, we used the exploratory method through a questionnaire survey, which was attended by 948 respondents who are Internet users and users of banking services in an electronic environment. We verified the adequacy of the composition of the research sample with Cronbach alpha. We solved the verification of hypotheses through confirmatory factor analysis and modeling of structural equations. The results, using the WLSMV estimation method, found a negative significant impact (negative linear dependence) of the social media factor on the expected efforts, which are further related to the use of electronic banking.
Highlights
New technologies and the big expansion of social media websites have transformed interaction in the online space, and many online retailers and industries have provided new opportunities to reach their audiences, including the field of Internet banking (Małkowska et al 2021).The coverage of social networks worldwide is still growing
Testing of ordinal variables as if they were continuous variables, the accuracy and precision of parametric model estimates, standard errors, and goodness-offit tests may be compromised, leading to misinterpreted statistical conclusions. Robust estimates such as WLSMV method, have been addressed in the literature in recent decades and are considered more applicable than the current Maximum Likelihood (ML) theory when ordinal variables are being analyzed (Cheng-Hsien, 2014)
In the context of the hypothesis, we focused on the social media factor and its impact on the effort expectancy
Summary
The coverage of social networks worldwide is still growing. The global digital population is 4.66 billion active Internet users in January 2021, of which 4.2 billion are active social media users, which represents about 90% (Johnson, 2021). In 2012, 63.1% of Internet users used social networking services. The worldwide increase in the use of smartphones and other mobile devices, such as tablets, opened up the possibilities of social networks with extended functions. Most social networks are available as mobile applications, while some networks are optimized for Internet browsers. Facebook is currently the market leader in terms of size and reach. This social network has been shaping the social media market since its launch and has faced various discussions on user privacy (American Marketing Association, 2014)
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