NFC Technology Acceptance Factors in Tourism

Platov, Alexey V.; Tarchokov, S.K.; Zikirova, Shakhlo; Litvinova, Olga Igorevna; Удалов, Д.Э.

doi:10.1145/3487757.3490928

Cited by 4 publications

(4 citation statements)

References 20 publications

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“…This can be attributed to the inherent risks associated with these applications as they may be vulnerable to attacks by hackers, impacting users' trust. These results aligned with the findings of previous studies [100][101][102][103][104][105][106][107]. Moreover, this study established a significant link between perceived risk and user trust.…”

Section: Discussionsupporting

confidence: 92%

“…(3) Sustainability and environmental management: environmental sustainability is a central element of smart cities. Green infrastructure, energy-efficient buildings, and waste recycling programs are common features of smart urban planning [107]. They aim to reduce carbon emissions, minimize energy consumption, and promote the use of renewable energy sources.…”

Section: Smart Citiesmentioning

confidence: 99%

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Exploring the Success Factors of Smart City Adoption via Structural Equation Modeling

Alkdour,

Almaiah,

Shishakly

et al. 2023

Sustainability

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This study investigated the roles of security and technological factors in the adoption of smart cities, with the aim of developing a deeper understanding of the key aspects of the successful adoption of smart cities in Jordanian traditional cities. This study developed a conceptual model to investigate the importance of security and technological factors in the adoption of smart cities. The proposed model was tested using the structural equation modeling method after collecting data from ICT experts. The findings of the study revealed that perceived security, perceived trust, and service quality play pivotal roles in enhancing the adoption of smart city services. Moreover, the results indicated that information security and information privacy positively impact intentions toward adopting smart city services. These research findings provide valuable insights into the critical factors that can drive the adoption of smart city services. Policymakers and academics could utilize this knowledge to devise and implement new strategies aimed at increasing the adoption of smart city services.

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Section: Discussionsupporting

confidence: 92%

Section: Smart Citiesmentioning

confidence: 99%

Exploring the Success Factors of Smart City Adoption via Structural Equation Modeling

Alkdour,

Almaiah,

Shishakly

et al. 2023

Sustainability

View full text Add to dashboard Cite

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“…Consequently, this negative result significantly influences students' trust in m-learning apps. Our findings align with previous studies in the context of e-learning systems [100][101][102][103][104][105][106][107]. Furthermore, this research provides evidence of a connection between perceived risk and students' trust.…”

Section: Discussionsupporting

confidence: 91%

A New Technological Model on Investigating the Utilization of Mobile Learning Applications: Extending the TAM

Shishakly,

Almaiah,

Al-Otaibi

et al. 2023

MTI

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Mobile learning has become increasingly important for higher education due to its numerous advantages and transformative potential. The aim of this study is to investigate how students perceive and utilize mobile learning (m-learning) services in universities. To achieve this objective, a conceptual model was developed, combining the TAM with additional new determinants, including perceived security, perceived trust, perceived risk, and service quality. The primary goal of this model is to assess the adoption of m-learning apps among users in university settings. To evaluate the proposed model, SEM was utilized to test the research model. The findings of the study highlight the critical roles of perceived security, perceived trust, and service quality in promoting the adoption of m-learning apps. Moreover, the results indicate that perceived risk negatively impacts both students’ trust and their attitudes towards using mobile learning services. The study reveals that the perceived trust, and service quality factors positively influence students’ attitudes towards adopting m-learning apps. These research findings hold significant implications for universities and academia, offering valuable insights to devise effective strategies for increasing the utilization of m- learning services among students. By gaining a deeper understanding of students’ perceptions and acceptance, universities can optimize their m-learning offerings to cater to students’ needs and preferences more effectively.

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“…Attitude toward use is one of the most important predictors in the TAM model and in other technology acceptance models, like UTAUT, TRA and others. Studies on e-banking [85][86][87][88] have confirmed that attitude toward use has a positive relationship with intention to use e-banking systems. Accordingly, in our study, attitude toward use will play an important role in predicting the adoption by clients of mobile banking applications.…”

Section: Attitude Toward Usementioning

confidence: 96%

Investigating the Role of Perceived Risk, Perceived Security and Perceived Trust on Smart m-Banking Application Using SEM

et al. 2023

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Effective security support remains a challenge, even for mobile banking applications; this is leading to the loss of many customers due to limited protection of customer data and privacy. Cyber threats include everything from identity theft to malware threats and email and online fraud. Thus, businesses and individuals should use risk assessment methods and countermeasures to protect their m-banking apps. With this in mind, a new model using the Technology Acceptance Model (TAM) has been proposed. The model has been broken down into six main countermeasure categories, namely: perceived risk, perceived security, perceived trust, ease of use, usefulness and service quality. To test this model, structural equation modelling (SEM) was used. Our findings reveal that perceived security, perceived trust and service quality play key roles in improving the adoption of mobile banking apps. In addition, the findings indicate that perceived risk had a negative impact on both clients’ trust and their attitudes toward the use of mobile banking services. The proposed model could increase the adoption of m-banking apps by enhancing their defenses against security risk issues. The model enhances the risk reduction (63.0%), data protection (75.0%), trust (32.1%), quality of service (74.0%), ease of use (44.0%) and usefulness (45.3%) ratios.

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NFC Technology Acceptance Factors in Tourism

Cited by 4 publications

References 20 publications

Exploring the Success Factors of Smart City Adoption via Structural Equation Modeling

Exploring the Success Factors of Smart City Adoption via Structural Equation Modeling

A New Technological Model on Investigating the Utilization of Mobile Learning Applications: Extending the TAM

Investigating the Role of Perceived Risk, Perceived Security and Perceived Trust on Smart m-Banking Application Using SEM

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