Individuals’ adoption of smart technologies for preventive health care: a structural equation modeling approach
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DOI: 10.1007/s10729-019-09468-2
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- Salem Ahmed Alabdali & Salvatore Flavio Pileggi & Dilek Cetindamar, 2023. "Influential Factors, Enablers, and Barriers to Adopting Smart Technology in Rural Regions: A Literature Review," Sustainability, MDPI, vol. 15(10), pages 1-38, May.
- Liyuan Liu & Yen Hsu, 2022. "Motivating factors behind the public’s use of smart recycling systems: perceived playfulness and environmental concern," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-13, December.
- Jiaxin Chen & Ting Li & Hua You & Jingyu Wang & Xueqing Peng & Baoyi Chen, 2023. "Behavioral Interpretation of Willingness to Use Wearable Health Devices in Community Residents: A Cross-Sectional Study," IJERPH, MDPI, vol. 20(4), pages 1-11, February.
- Gerli, Paolo & Clement, Jessica & Esposito, Giovanni & Mora, Luca & Crutzen, Nathalie, 2022. "The hidden power of emotions: How psychological factors influence skill development in smart technology adoption," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
- Pal, Debajyoti & Vanijja, Vajirasak, 2020. "Perceived usability evaluation of Microsoft Teams as an online learning platform during COVID-19 using system usability scale and technology acceptance model in India," Children and Youth Services Review, Elsevier, vol. 119(C).
- Fuyong Lu & Xian Huang & Xintao Wang, 2022. "Willingness to Pay for Mobile Health Live Streaming during the COVID-19 Pandemic: Integrating TPB with Compatibility," Sustainability, MDPI, vol. 14(23), pages 1-22, November.
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Keywords
Preventive health; Mobile health care; Smart technologies; Technology acceptance model; Structural equation modeling;All these keywords.
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