2017
DOI: 10.1007/978-3-319-71225-3_20
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Determinants of Mobile Banking Use: An Extended TAM with Perceived Risk, Mobility Access, Compatibility, Perceived Self-efficacy and Subjective Norms

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Cited by 56 publications
(59 citation statements)
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“…Various perspectives and models have been used to study technology adoption. One of the most widespread models in technology adoption for payment methods and e-banking is TAM (technology acceptance model) [21], which numerous researchers have applied to related technologies such as cloud computing [29] (Palos-Sanchez et al, 2017) and mobile banking [30,31].…”
Section: Conceptual Framework and Hypotheses Developmentmentioning
confidence: 99%
“…Various perspectives and models have been used to study technology adoption. One of the most widespread models in technology adoption for payment methods and e-banking is TAM (technology acceptance model) [21], which numerous researchers have applied to related technologies such as cloud computing [29] (Palos-Sanchez et al, 2017) and mobile banking [30,31].…”
Section: Conceptual Framework and Hypotheses Developmentmentioning
confidence: 99%
“…Kim et al (2009) suggested that a person often evaluates the consequences of their actions and then establishes a selection reliant on the favourability of perceived USF. Accordingly, USF would impact an individual's intention to use m-banking as a technological service (Dwivedi, Rana, Janssen, Lal, Williams and Clement, 2017;Gumussoy et al, 2018;Williams et al, 2015). Within the domain of m-banking, people tend to adopt it when perceiving the usefulness of the service for their financial transactions as well as saving their time (Gu et al, 2009;Shaikh and Karjaluoto, 2015;Zhou, 2012).…”
Section: Perceived Usefulness (Usf)continued Intention (Ci)mentioning
confidence: 99%
“…Several studies also have utilized an extended version of TAM to investigate the adoption behavior of mobile banking systems (Aboelmaged & Gebba, 2013;Govender & Sihlali, 2014). In particular, Gumussoy, Kaya, and Ozlu (2018) introduced compatibility, mobility access, and perceived self-efficacy to predict perceived usefulness and perceived ease of use of mobile banking systems. Then they used these TAM constructs, along with subjective norm and perceived risk, to predict intention to use this type of banking system.…”
Section: Technology Acceptance Modelmentioning
confidence: 99%