Examining the factors affecting users’ cybersecurity behaviour in mobile payment contactless technologies: A hybrid SEM-ANN approach

dc.SupervisorProfessor Khaled Shaalan
dc.contributor.authorZAINAL, HANA YOUSUF
dc.description.abstractModern businesses have adopted a plethora of advancements due to the emergence of digital transformation where the recent lifestyle requires to have a robust platform to process all the communication in an effective and secure way. Advanced technologies adopted by the society purely concentrated on the software and cybersecurity enhancements from the software perspective ignoring the fact that a human behaviour can be the most major and severe threat for these advanced technologies. The adoption of any new technology in the society has been turned into a must rather than a complimentary due to the rapid growth of the technology advancements and people curiosity to investigate new trends. Technology adoption depends on the behaviour of the end users in dealing with the technology. Mobile payment contactless technologies are one of the fast-growing technologies specially after the appearance of the COVID-19 where all the payments and transactions are performed using RFID (Radio-Frequency Identification) or NFC (Near Field Communication) techniques. The individual’s cybersecurity behaviour is a major concern in these technologies. A quick review of literature showed that none of the studies discussed the individual’s cybersecurity behaviour toward this technology. Therefore, this research has three main objectives. First, conducting a systematic of systematic reviews on cybersecurity through a multidisciplinary perspective to address the research gaps in the existing literature of human cybersecurity behaviour. The systematic review of systematic review included empirical studies published between January 2015 and February 2022 on the topic of cybersecurity. A total of 794 studies have been reviewed, and 60 studies were found qualified and considered in the analysis. Through the analysis, little attention has been paid to cybersecurity behaviour in general and mobile payment contactless technologies in specific. Moreover, the existing literature discussed the utilization of mobile payment contactless technologies in terms of adoption and use in a certain criteria or environment and do not measure or explore the cybersecurity behaviour towards this technology. To bridge this literature gap, this research builds an integrated theoretical model by combining factors from the Protection Motivation Theory (PMT), Technology Threat Avoidance Theory (TTAT), Theory of Planned Behaviour (TPB), along with cybersecurity awareness to measure the cybersecurity behaviour in mobile payment contactless technologies. The model was then empirically validated using a hybrid Structural Equation Modelling-Artificial Neural Network (SEM-ANN) approach based on data collected through questionnaire surveys from mobile payment contactless technologies users in the UAE. The results indicated that the attitude, subjective norm, cybersecurity awareness, perceived behavioural control and response efficacy have a significant influence on cybersecurity behaviour. On the other side, the results indicated that perceived threat, response cost, and self-efficacy have insignificant influence on cybersecurity behaviour. The model explained 53% of the total variance in cybersecurity behaviour. Additionally, the ANN results showed that cybersecurity awareness is the most important factor affecting cybersecurity behaviour, with a normalized importance of 100%. Theoretical contributions, practical implications, and limitations and future research were also discussed.en_US
dc.publisherThe British University in Dubai (BUiD)en_US
dc.subjectmobile paymenten_US
dc.subjectdigital transformationen_US
dc.subjectadvanced technologiesen_US
dc.subjectcybersecurity behaviouren_US
dc.subjectcontactless technologiesen_US
dc.subjectUnited Arab Emirates (UAE)en_US
dc.subjectcybersecurity awarenessen_US
dc.titleExamining the factors affecting users’ cybersecurity behaviour in mobile payment contactless technologies: A hybrid SEM-ANN approachen_US
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