Open Access
Issue
E3S Web of Conf.
Volume 388, 2023
The 4th International Conference of Biospheric Harmony Advanced Research (ICOBAR 2022)
Article Number 04055
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/202338804055
Published online 17 May 2023
  1. A. Majchrzak, M. L. Markus, and J. Wareham, “Designing for digital transformation,” MIS Q., vol. 40, no. 2, pp. 267–278, 2016. [CrossRef] [Google Scholar]
  2. J. Eicher, “How AI is Changing the Accounting Landscape,” Accounting Today, 2021. [Online]. Available: https://www.accountingtoday.com/opinion/how-ai-is-changing-the-accounting-landscape. [Google Scholar]
  3. Y. Li, “Artificial intelligence in accounting and auditing: A review of the literature,” Journal of Applied Accounting Research, vol. 21, no. 2, pp. 256–274, 2020, doi: 10.1108/JAAR-09-2019-0149. [Google Scholar]
  4. K. Assenova, “Development of Artificial Intelligence and Effects on High Education in Finance, Accounting, and Auditing, 9th,” Proc. Univ. Vol., 2020. [Google Scholar]
  5. E. Petrova, Accounting Educator and Practitioners on Alert the Time for Bigger and Constant Changes has Come. Varna: Varna University of Economics book, 2019. [Google Scholar]
  6. E. Johnson, M. Petersen, J. Sloan, and A. Valencia, “The Interest, Knowledge, and Usage of Artificial Intelligence in Accounting: Evidence from Accounting Professionals,” Account. Tax., vol. 13, no. 1, pp. 45–58, 2021. [Google Scholar]
  7. S. J. Mohammad, A. K. Hamad, H. Borgi, P. A. Thu, M. S. Sial, and A. A. Alhadidi, “How Artificial Intelligence Changes the Future of Accounting Industry,” Int. J. Econ. Bus. Adm., vol. 8, no. 3, pp. 478–488, 2020. [Google Scholar]
  8. M. Bowles, S. Ghosh, and L. Thomas, “Futureproofing accounting professionals: Ensuring graduate employability and future readiness,” J. Teach. Learn. Grad. Employab., vol. 13, no. 1, pp. 1–21, 2020. [Google Scholar]
  9. Z. Ismail, A. S. Ahmad, and A. Ahmi,“Perceived Employability Skills of Accounting Graduates: The Insight from Employers,” Elem. Educ. Online, vol. 19, no. 4, pp. 36–41, 2020. [Google Scholar]
  10. K. Gašová, T. Mišík, and Z. ŠTofková, “Employers Demands on E-Skills of University Students in Conditions of Digital Economy,” CBU Int. Conf. Proc., vol. 6, pp. 146–151, 2018. [CrossRef] [Google Scholar]
  11. R. Priyahita, “The Utilization of E-Learning and Artificial Intelligence in the Development of Education System in Indonesia, Advances in Social Science,” Educ. Humanit. Res., vol. 459, 2020. [Google Scholar]
  12. A. Parasuraman, “Technology Readiness Index (Tri): A Multiple-Item Scale to Measure Readiness to Embrace New Technologies,” J. Serv. Res., vol. 2, no. 4, pp. 307–320, 2000. [CrossRef] [Google Scholar]
  13. A. Parasuraman and C. L. Colby, “An Updated and Streamlined Technology Readiness Index: TRI 2.0,” J. Serv. Res., vol. 18, no. 1, pp. 59– 74, 2015. [CrossRef] [Google Scholar]
  14. H. Damerji and A. Salimi, “Mediating effect of use perceptions on technology readiness and adoption of artificial intelligence in accounting,” Account. Educ., vol. 30, no. 2, pp. 107–130, 2021. [CrossRef] [Google Scholar]
  15. L. W. Wong, G. W. H. Tan, V. H. Lee, K. B. Ooi, and A. Sohal, “Unearthing the determinants of Blockchain adoption in supply chain management,” Int. J. Prod. Res., vol. 58, no. 7, pp. 2100–2123, 2020. [CrossRef] [Google Scholar]
  16. P. Godoe and T. S. Johansen, “Understanding adoption of new technologies: Technology readiness and technology acceptance as an integrated concept,” J. Eur. Psychol. Students, vol. 3, no. 1, pp. 38–52, 2012. [CrossRef] [Google Scholar]
  17. J. C. Oh, S. J. Yoon, and N. Chung, “The role of technology readiness in consumers’ adoption of mobile internet services between South Korea and China,” Int. J. Mob. Commun., vol. 12, no. 3, p. 229, 2014. [CrossRef] [Google Scholar]
  18. V. Liljander, F. Gillberg, J. Gummerus, and A. van Riel, “Technology readiness and the evaluation and adoption of self-service technologies,” J. Retail. Consum. Serv., vol. 13, no. 3, pp. 177–191, 2006. [CrossRef] [Google Scholar]
  19. R. Walczuch, J. Lemmink, and S. Streukens, “The effect of service employees’ technology readiness on technology acceptance,” Inf. Manag., vol. 44, no. 2, pp. 206–215, 2007. [CrossRef] [Google Scholar]
  20. C. J. Gelderman, P. W. Ghijsen, and R. van Diemen, “Choosing self-service technologies or interpersonal services—The impact of situational factors and technology-related attitudes,” J. Retail. Consum. Serv., vol. 18, no. 5, pp. 414–421, 2011. [CrossRef] [Google Scholar]
  21. UNESCO, “UNESCO,” 2018. [Online]. Available: https://www.google.com/search?q=What+is+webpage+name+in+research&sxsrf=APq-WBt3KmPai6f95jgvM9Rz9Ldt1_XHLQ%3A1648903666282&ei=8kVIYt3lEMfseMPyKmmAE&ved=0ahUKEwjdprDqtPX2AhXPT2wGHciUCR8Q4dUDCA4&uact=5&oq=What+is+webpage+name+in+research&gs_lcp=Cgdnd3Mtd2 l. [Accessed: 20-Apr–2022]. [Google Scholar]
  22. CGMA, “Digital competencies for finance professionals,” 2019. [Online]. Available: https://www.cgma.org/content/dam/cgma/resources/reports/downloadabledocuments/digitalcompetency-model-for-financeprofessionals.pdf. [Google Scholar]
  23. M. Jang, M. Aavakare, S. Nikou, and S. Kim, “The impact of literacy on intention to use digital technology for learning: A comparative study of Korea and Finland,” Telecomm. Policy, vol. 45, no. 7, p. 102154, 2021. [CrossRef] [Google Scholar]
  24. S. Kinkel, M. Baumgartner, and E. Cherubini, “Prerequisites for the adoption of AI technologies in manufacturing – Evidence from a worldwide sample of manufacturing companies,” Technovation, vol. 110, p.102375, 2022. [CrossRef] [Google Scholar]
  25. N. Bergdahl, J. Nouri, and U. Fors, “Disengagement, engagement, and digital skills in technology-enhanced learning,” Educ. Inf. Technol., vol. 25, no. 2, pp. 957–983, 2019. [Google Scholar]
  26. S. Lissitsa and T. Laor, “Baby Boomers, Generation X and Generation Y: Identifying generational differences in effects of personality traits in on-demand radio use,” Technol. Soc., vol. 64, p. 101526, 2021. [CrossRef] [Google Scholar]
  27. Y. Zhao, A. M. Pinto Llorente, and M. C. Sánchez Gómez, “Digital competence in higher education research: A systematic literature review,” Comput. Educ., vol. 168, 2021. [Google Scholar]
  28. J. Portillo, U. Garay, E. Tejada, and N. Bilbao, “Self-Perception of the Digital Competence of Educators during the COVID-19 Pandemic: A Cross-Analysis of Different Educational Stages,” Sustainability, vol. 12, no. 23, p. 10128, 2020. [CrossRef] [Google Scholar]
  29. F. D. Davis, “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Q., vol. 13, no. 3, p. 319, 1989. [CrossRef] [Google Scholar]
  30. Y. J. Joo, S. Park, and E. K. Shin, “Students’expectation, satisfaction, and continuance intention to use digital textbooks,” Comput. Human Behav., vol. 69, pp. 83–90, 2017. [CrossRef] [Google Scholar]
  31. M. M. Alamri et al., “Towards Adaptive ELearningamong University Students: by Applying Technology Acceptance Model (TAM),” Int. J. Eng. Adv. Technol., vol. 8, no. 6, 2019. [Google Scholar]
  32. I. M. Lazar, G. Panisoara, and I. O. Panisoara, “Digital technology adoption scale in the blended learning context in higher education: Development, validation, and testing of a specific tool,” PLoS One, vol. 15, no. 7, 2020. [Google Scholar]
  33. K. Cicha, M. Rizun, P. Rutecka, and A. Strzelecki, “COVID-19 and Higher Education: Distance Learning,” Sustainability, vol. 13, no. 4, p. 1889, 2021. [CrossRef] [Google Scholar]
  34. M. Blut and C. Wang, “Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage,” J. Acad. Mark. Sci., vol. 48, no. 4, pp. 649– 669, 2019. [Google Scholar]
  35. L. Pham, S. Williamson, P. Lane, Y. Limbu, P. T. H. Nguyen, and T. Coomer, “Technology readiness and purchase intention: role of perceived value and online satisfaction in the context of luxury hotels,” Int. J. Manag. Decis. Mak., vol. 19, no. 1, pp. 91–117, 2020. [Google Scholar]
  36. C. Smit, M. Roberts-Lombard, and M. Mpinganjira, “Technology readiness and mobile self-service technology adoption in the airline industry: An emerging market perspective,” Acta Commer., vol. 18, no. 1, 2018. [CrossRef] [Google Scholar]
  37. M. A. Nugroho and M. A. Fajar, “Effects of Technology Readiness Towards Acceptance of Mandatory Web-Based Attendance System,” Procedia Comput. Sci., vol. 124, pp. 319–328, 2017. [CrossRef] [Google Scholar]
  38. O. E. Hatlevik and K. A. Christophersen, “Digital competence at the beginning of upper secondary school: Identifying factors explaining digital inclusion,” Comput. Educ., vol. 63, pp. 240–247, 2013. [CrossRef] [Google Scholar]
  39. X. He and Y. Li, “An empirical study of accounting professionals’ digital competence and its effect on job performance,” Journal of Business and Psychology, vol. 34, no. 6, pp. 791–807, 2019, doi: 10.1007/s10869-019-09620-5. [CrossRef] [Google Scholar]
  40. Y. Li, W. Wu, Y. Huang, and J. Zhang, “The influence of social media on accounting professionals’ digital competence and job performance,” The Journal of Social Media in Society, vol. 10, no. 1, pp. 179–202, 2021.[Online]. Available: https://thejsms.org/index.php/TSMRI/article/view/900/552. [Google Scholar]
  41. I. Schiffl, “How Information Literate Are Junior and Senior Class Biology Students?,” Res. Sci. Educ., vol. 50, no. 2, pp. 773–789, 2018. [Google Scholar]
  42. N. A. Buzzetto-Hollywood, H. C. Wang, M. Elobeid, and M. E. Elobaid, “Addressing Information Literacy and the Digital Divide in Higher Education,” Interdiscip. J. E-Skills Lifelong Learn., vol. 14, pp. 077–093, 2018. [CrossRef] [Google Scholar]
  43. A. Lawson-Body, L. Willoughby, L. Lawson- Body, and E. M. Tamandja, “Students’ acceptance of E-books: An application of UTAUT,” J. Comput. Inf. Syst., vol. 60, no. 3, pp. 256–267, 2018. [Google Scholar]
  44. A. Wicaksono and A. Maharani, “The Effect of Perceived Usefulness and Perceived Ease of Use on the Technology Acceptance Model to Use Online Travel Agency,” J. Bus. Manag. Rev., vol. 1, no. 5, pp. 313–328, 2020. [CrossRef] [Google Scholar]
  45. K. Martzoukou, C. Fulton, P. Kostagiolas, and C. Lavranos, “A study of higher education students’ self-perceived digital competences for learning and everyday life online participation,” J. Doc., vol. 76, no. 6, pp. 1413–1458, 2020. [CrossRef] [Google Scholar]
  46. J. F. Hair, W. C. Black, B. J. Babin, and R. E. Anderson, “Multivariate Data Analysis, 8th edition,“ Cengage Learning, 2019, p. 143. [Google Scholar]
  47. J. Henseler, C. M. Ringle, and M. Sarstedt, “A new criterion for assessing discriminant validity in variance-based structural equation modeling,” J. Acad. Mark. Sci., vol. 43, no. 1, pp. 115–135, 2014. [Google Scholar]
  48. M. A. Rouf and M. Akhtaruddin, “Factors affecting the voluntary disclosure: a study by using smart PLS-SEM approach,” Int. J. Law Manag., 2018. [Google Scholar]

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