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  • 标题:A Comparative Study of Users versus Non-Users’ Behavioral Intention towards M-Banking Apps’ Adoption
  • 本地全文:下载
  • 作者:Vaggelis Saprikis ; Giorgos Avlogiaris ; Androniki Katarachia
  • 期刊名称:Information
  • 电子版ISSN:2078-2489
  • 出版年度:2022
  • 卷号:13
  • 期号:1
  • 页码:30
  • DOI:10.3390/info13010030
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:The banking sector has been considered as one of the primary adopters of Information and Communications Technologies. Especially during the last years, they have invested a lot into the digital transformation of their business process. Concerning their retail customers, banks realized very early the great potential abilities to provide value added self-services functions via mobile devices, mainly smartphones to them; thus, they have invested a lot into m-banking apps’ functionality. Furthermore, the COVID-19 pandemic has brought out different ways for financial transactions and even more mobile users have taken advantage of m-banking app services. Thus, the purpose of this empirical paper is to investigate the determinants that impact individuals on adopting or not m-banking apps. Specifically, it examines two groups of individuals, users (adopters) and non-users (non-adopters) of m-banking apps, and aims to reveal if there are differences and similarities between the factors that impact them on adopting or not this type of m-banking services. To our knowledge, this is the second scientific attempt where these two groups of individuals have been compared on this topic. The paper proposes a comprehensive conceptual model by extending Venkatech’s et al. (2003) Unified Theory of Acceptance and Use of Technology (UTAUT) with ICT facilitators (i.e., reward and security) and ICT inhibitors (i.e., risk and anxiety), as well as the recommendation factor. However, this study intends to fill the research gap by investigating and proving for the first time the impact of social influence, reward and anxiety factors on behavioral intention, the relationship between risk and anxiety and the impact of behavioral intention on recommendation via the application of Confirmatory Factor Analysis and Structural Equation Modeling (SEM) statistical techniques. The results reveal a number of differences regarding the factors that impact or not these two groups towards m-banking app adoption; thus, it provides new insights regarding m-banking app adoption in a slightly examined scientific field. Thus, the study intends to assist the banking sector in better understanding their customers with the aim to formulate and apply customized m-business strategies and increase not only the adoption of m-banking apps but also the level of their further use.
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