EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 388 (2023) E3S Web of Conf., 388 (2023) 04058 References
Open Access
Issue
E3S Web of Conf.
Volume 388, 2023
The 4th International Conference of Biospheric Harmony Advanced Research (ICOBAR 2022)
Article Number 04058
Number of page(s) 9
Section Technological Influence on Society and Applied Social Sciences to Support Sustainable Society
DOI https://doi.org/10.1051/e3sconf/202338804058
Published online 17 May 2023
  1. N. Ahmed et al., “A Survey of COVID-19 Contact Tracing Apps,” IEEE Access, vol. 8. Institute of Electrical and Electronics Engineers Inc., pp. 134577–134601, 2020. doi:10.1109/ACCESS.2020.3010226. [CrossRef] [Google Scholar]
  2. J. Li and X. Guo, “COVID-19 Contact-tracing Apps: a Survey on the Global Deployment and Challenges.” [Google Scholar]
  3. D. N. Durrheim, J. K. Andrus, S. Tabassum, H. Bashour, D. Githanga, and G. Pfaff, “A dangerous measles future looms beyond the COVID-19 pandemic,” Nature Medicine, vol. 27, no. 3. Nature Research, pp. 360–361, Mar. 01, 2021.doi: 10.1038/s41591-021-01237-5. [CrossRef] [PubMed] [Google Scholar]
  4. A. A. Ali et al., “Contact Tracing Apps for COVID-19: Access Permission and User Adoption,” Proceedings of 2020 7th IEEE International Conference on Behavioural and Social Computing, BESC 2020, pp. 1–7, 2020,doi: 10.1109/BESC51023.2020.9348327. [Google Scholar]
  5. Iwan Supriyatna and Bagaskara Isdiansyah, “Data Pribadi Presiden Jokowi Bocor, DPR Singgung Tugas Polisi Siber”, Accessed: Mar. 22, 2022. [Online]. Available: https://www.suara.com/news/2021/09/04/130057/data-pribadi-presiden-jokowi-bocor-dprsinggung-tugas-polisi-siber [Google Scholar]
  6. U. Department of State, “Country Reports on Human Rights Practices for 2021 United States Department of State • Bureau of Democracy, Human Rights and Labor,” 2021. [Google Scholar]
  7. W. H. DeLone and E. R. McLean, “Information systems success: The quest for the dependent variable,” Information Systems Research, vol. 3, no. 1, pp. 60–95, 1992, doi: 10.1287/ISRE.3.1.60. [CrossRef] [Google Scholar]
  8. F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” Source: MIS Quarterly, vol. 13, no.3, pp. 319–340, 1989. [Google Scholar]
  9. W. H. DeLone and E. R. McLean, “The DeLone and McLean Model of Information Systems Success: A Ten-Year Update,” Journal of Management Information Systems, vol. 19, no. 4, pp. 9–30, 2003, doi:10.1080/07421222.2003.11045748. [CrossRef] [Google Scholar]
  10. N. Fortes, P. Rita, and M. Pagani, “The effects of privacy concerns, perceived risk and trust on online purchasing behaviour,” International Journal of Internet Marketing and Advertising, vol. 11, no. 4, pp. 307–329, 2017, doi:10.1504/IJIMA.2017.087269. [CrossRef] [Google Scholar]
  11. A. McLeod, S. Pippin, and R. Mason, “Individual Taxpayer Intention to Use Tax Preparation Software: Examining Experience, Trust, and Perceived Risk,” Journal of Information Science & Technology, vol. 6, no. 1, pp. 25–44, 2009,[Online]. Available: http://cdman2han.bib.unierlangen.de/han/BSCdirekt/web.ebscohost.com/ehost/pdfviewer/pdfviewer?hid=9&sid=b0ec4611-8c38-43e9-9c88-e064ea9f6dce@sessionmgr14&vid=1 [Google Scholar]
  12. A. A. C. Azmi, Y. Kamarulzaman, and N. H. A. Hamid, “Perceived risk and the adoption of tax efiling,” World Appl Sci J, vol. 20, no. 4, pp. 532–539, 2012, doi:10.5829/idosi.wasj.2012.20.04.2403. [Google Scholar]
  13. R. Schnall, T. Higgins, W. Brown, A. Carballo- Dieguez, and S. Bakken, “Trust, Perceived Risk, Perceived Ease of Use and Perceived Usefulness as Factors Related to mHealth Technology Use,” Studies in Health Technology and Informatics, vol. 216. pp. 467–471, 2015. doi: 10.3233/978-1-61499-564-7-467. [PubMed] [Google Scholar]
  14. W. Munyoka and M. S. Maharaj, “Privacy, security, trust, risk and optimism bias in egovernment use: The case of two Southern African Development Community countries,” SA Journal of Information Management, vol. 21, no. 1, pp. 1–9, 2019, doi: 10.4102/sajim.v21i1.983. [CrossRef] [Google Scholar]
  15. A. Lodders and J. M. Paterson, “Scrutinising COVIDSafe: Frameworks for evaluating digital contact tracing technologies,” Alternative Law Journal, vol. 45, no. 3, pp. 153–161, 2020, doi: 10.1177/1037969X20948262. [CrossRef] [Google Scholar]
  16. K. Rout and S. Sahu, “Exploring Factors Influencing the Users’ Intention to Use Aarogya Setu Contact Tracing Mobile Health Application during COVID-19 Pandemic,” Journal of Humanities and Social Sciences Research, vol. 2, no. (S), pp. 29–36, 2020, doi:10.37534/bp.jhssr.2020.v2.ns.id1068.p29. [CrossRef] [Google Scholar]
  17. A. T.-Y. Chen and K. W. Thio, “Exploring the drivers and barriers to uptake for digital contact tracing,” Social Sciences & Humanities Open, vol. 4, no. 1, p. 100212, 2021, doi: 10.1016/j.ssaho.2021.100212. [CrossRef] [PubMed] [Google Scholar]
  18. M. Dimodugno, S. Hallman, M. Plaisent, and P. Bernard, “The effect of privacy concerns, risk, control, and trust on individuals’ decisions to share personal information: A game theory-based approach,” J Phys Conf Ser, vol. 2090, no. 1, 2021, doi: 10.1088/1742-6596/2090/1/012017. [CrossRef] [Google Scholar]
  19. S. L. Zhou, X. Jia, S. P. Skinner, W. Yang, and I. Claude, “Lessons on mobile apps for COVID-19 from China,” Journal of Safety Science and Resilience, vol. 2, no. 2, pp. 40–49, 2021, doi: 10.1016/j.jnlssr.2021.04.002. [CrossRef] [Google Scholar]
  20. J. Lin, L. Carter, and D. Liu, “Privacy concerns and digital government: exploring citizen willingness to adopt the COVIDSafe app,” European Journal of Information Systems, vol. 30, no. 4, pp. 389–402, 2021, doi: 10.1080/0960085X.2021.1920857. [CrossRef] [Google Scholar]
  21. B. Zarouali, J. Strycharz, N. Helberger, and C. de Vreese, “Exploring people’s perceptions and support of data-driven technology in times of COVID-19: the role of trust, risk, and privacy concerns,” Behaviour and Information Technology, pp. 1–12, 2022, doi: 10.1080/0144929X.2021.2022208. [Google Scholar]
  22. W. Sardjono, D. M. Kristin, G. R. Putra, G. Salim, and S. Subiyantoro, “EVALUATION MODEL OF YACHTERS INFORMATION SYSTEM IMPLEMENTATION SUCCESS USING DELONE AND MCLEAN TO INCREASE ORGANIZATION PERFORMANCE,” ICIC Express Letters, vol. 16, no. 2, pp. 205–213, Feb. 2022, doi: 10.24507/ICICEL.16.02.205. [Google Scholar]
  23. MD. Aminul Islam, “Factors affecting user satisfaction in the Malaysian income tax e-filing system,” African Journal of Business Management, vol. 6, no. 21, pp. 6447–6455, 2012, doi: 10.5897/ajbm11.1689. [CrossRef] [Google Scholar]
  24. Y. H. Lai, “Factors Influencing the Intention to Use the Online Face Mask Information System during the COVID-19 Pandemic,” Electronic Journal of General Medicine, vol. 19, no. 2, Apr. 2022, doi: 10.29333/EJGM/11547. [Google Scholar]
  25. N. Veeramootoo, R. Nunkoo, and Y. K. Dwivedi, “What determines success of an e-government service? Validation of an integrative model of efiling continuance usage,” Gov Inf Q, vol. 35, no. 2, pp. 161–174, 2018, doi: 10.1016/j.giq.2018.03.004. [CrossRef] [Google Scholar]
  26. D. Ariyanto, A. A. Dewi, H. T. Hasibuan, and R. B. Paramadani, “The Success of Information Systems and Sustainable Information Society: Measuring the Implementation of a Village Financial System,” Sustainability, vol. 14, no. 7, p. 3851, Mar. 2022, doi: 10.3390/SU14073851. [CrossRef] [Google Scholar]
  27. S. I. A. SUSANTI and T. Mauritsius, “UNDERSTANDING USER SATISFACTION IN USING MOBILE-BASED BEAUTY AND SKINCARE E-COMMERCE APPLICATION IN INDONESIA 1 SHANIA IRENE APPOLITA SUSANTI, 2 TUGA MAURITSIUS,” J Theor Appl Inf Technol, vol. 100, no. 7, 2022, [Online].Available: www.jatit.org [Google Scholar]
  28. Y. H. Fang, C. M. Chiu, and E. T. G. Wang, “Understanding customers’ satisfaction and repurchase intentions: An integration of IS success model, trust, and justice,” Internet Research, vol. 21, no. 4, pp. 479–503, Jan. 2011, doi: 10.1108/10662241111158335. [CrossRef] [Google Scholar]
  29. MD. Aminul Islam, “Factors affecting user satisfaction in the Malaysian income tax e-filing system,” African Journal of Business Management, vol. 6, no. 21, pp. 6447–6455, 2012, doi: 10.5897/ajbm11.1689. [CrossRef] [Google Scholar]
  30. A. Lodders and J. M. Paterson, “Scrutinising COVIDSafe: Frameworks for evaluating digital contact tracing technologies,” Alternative Law Journal, vol. 45, no. 3, pp. 153–161, 2020, doi: 10.1177/1037969X20948262. [CrossRef] [Google Scholar]
  31. N. Veeramootoo, R. Nunkoo, and Y. K. Dwivedi, “What determines success of an e-government service? Validation of an integrative model of efiling continuance usage,” Gov Inf Q, vol. 35, no. 2, pp. 161–174, 2018, doi: 10.1016/j.giq.2018.03.004. [CrossRef] [Google Scholar]
  32. W. S. Jian et al., “Voice-based control system for smart hospital wards: a pilot study of patient acceptance,” BMC Health Serv Res, vol. 22, no. 1, Dec. 2022, doi: 10.1186/S12913-022-07668-1. [Google Scholar]
  33. S. Nezamdoust, M. Abdekhoda, and A. Rahmani, “Determinant factors in adopting mobile health application in healthcare by nurses,” BMC Med Inform Decis Mak, vol. 22, no. 1, Dec. 2022, doi: 10.1186/S12911-022-01784-Y. [CrossRef] [Google Scholar]
  34. H. Wibowo and T. Mauritsius, “FACTORS THAT AFFECT THE E-FILLING USAGE IN INDONESIA: AN EXTENSION OF TECHNOLOGY ACCEPTANCE MODEL AND THEORY OF PLANNED BEHAVIOR,” J Theor Appl Inf Technol, vol. 15, no. 7, 2022, [Online]. Available: www.jatit.org [Google Scholar]
  35. Stefanus and T. Mauritsius, “A study on senior high school students’ acceptance of mobile learning management system,” J Theor Appl Inf Technol, vol. 97, no. 13, pp. 3638–3649, Jun. 2019. [Google Scholar]
  36. N. Shahidi, V. Tossan, S. Bourliataux-Lajoinie, and S. Cacho-Elizondo, “Behavioural intention to use a contact tracing application: The case of StopCovid in France,” Journal of Retailing and Consumer Services, vol. 68, p. 102998, Sep. 2022, doi:10.1016/J.JRETCONSER.2022.102998. [CrossRef] [Google Scholar]
  37. K. Rivo, and M. Zumer,” Academic Libraries and Use of Mobile Devices: Case Study of Slovenia,” Journal of Academic Librarianship, vol. 48, no. 3, May 2022, doi: 10.1016/J.ACALIB.2022.102507. [CrossRef] [Google Scholar]
  38. R. Schnall, T. Higgins, W. Brown, A. Carballo- Dieguez, and S. Bakken, “Trust, Perceived Risk, Perceived Ease of Use and Perceived Usefulness as Factors Related to mHealth Technology Use,” Studies in Health Technology and Informatics, vol. 216. pp. 467–471, 2015. doi: 10.3233/978-1-61499–564–7–467. [PubMed] [Google Scholar]
  39. N. Fortes, P. Rita, and M. Pagani, “The effects of privacy concerns, perceived risk and trust on online purchasing behaviour,” International Journal of Internet Marketing and Advertising, vol. 11, no. 4, pp. 307–329, 2017, doi: 10.1504/IJIMA.2017.087269. [CrossRef] [Google Scholar]
  40. P. Kotler and K. L. (2006).g Keller, Marketing management 12e. New Jersey, 2006. [Google Scholar]
  41. F. D. Davis, “Perceived Usefulness, Perceived Ease Of Use, And User Acceptance Of Information Technology,” MIS Quarterly, vol.13, no. 3, 1989. [Google Scholar]
  42. J. Christopher Westland, “Lower bounds on sample size in structural equation modeling,” Electron Commer Res Appl, vol. 9, no. 6, pp. 476– 487, Nov. 2010, doi: 10.1016/j.elerap.2010.07.003. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.