References
Abisoye, A., & Akerele, J. I. (2021b). A high-impact data-driven decision-making model for integrating cutting-edge cybersecurity strategies into public policy, governance, and organizational frameworks. International Journal of Multidisciplinary Research and Growth Evaluation, 2(1), 623–637. https://doi.org/10.54660/ijmrge.2021.2.1.623-637
Aithal, A., & Aithal, P. S. (2020). Development and validation of survey questionnaire and experimental data – A systematical review-based statistical approach. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3724105
Akudjedu, T. N., Torre, S., Khine, R., Katsifarakis, D., Newman, D., & Malamateniou, C. (2022). Knowledge, perceptions, and expectations of artificial intelligence in radiography practice: A global radiography workforce survey. Journal of Medical Imaging and Radiation Sciences, 54(1), 104–116. https://doi.org/10.1016/j.jmir.2022.11.016
Alcover, C., Guglielmi, D., Depolo, M., & Mazzetti, G. (2021). Aging-and-tech job vulnerability: A proposed framework on the dual impact of aging and AI, robotics, and automation among older workers. Organizational Psychology Review, 11(2), 175–201. https://doi.org/10.1177/2041386621992105
Almaiah, M. A., Alfaisal, R., Salloum, S. A., Hajjej, F., Shishakly, R., Lutfi, A., Alrawad, M., Mulhem, A. A., Alkhdour, T., & Al-Maroof, R. S. (2022). Measuring institutions’ adoption of artificial intelligence applications in online learning environments: Integrating the innovation diffusion theory with technology adoption rate. Electronics, 11(20), 3291. https://doi.org/10.3390/electronics11203291
Baburajan, V., De Abreu E Silva, J., & Pereira, F. C. (2020). Open-ended versus closed-ended responses: A comparison study using topic modeling and factor analysis. IEEE Transactions on Intelligent Transportation Systems, 22(4), 2123–2132. https://doi.org/10.1109/TITS.2020.3040904
Ban?a, V., Rînda?u, S., Tanasie, A., & Cojocaru, D. (2022). Artificial intelligence in the accounting of international businesses: A perception-based approach. Sustainability, 14(11), 6632. https://doi.org/10.3390/su14116632
Benbya, H., Davenport, T. H., & Pachidi, S. (2020). Artificial intelligence in organizations: Current state and future opportunities. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3741983
Blahušiaková, M. (2023). Business process automation: New challenges to increasing the efficiency and competitiveness of companies. Strategic Management, 28(3), 18–33. https://doi.org/10.5937/straman2300038b
Brocke, J. V., Maaß, W., Buxmann, P., Maedche, A., Leimeister, J. M., & Pecht, G. (2018). Future work and enterprise systems. Business & Information Systems Engineering, 60(4), 357–366. https://doi.org/10.1007/s12599-018-0544-2
Burla, L., Knierim, B., Barth, J., Liewald, K., Duetz, M., & Abel, T. (2008). From text to codings. Nursing Research, 57(2), 113–117. https://doi.org/10.1097/01.NNR.0000313482.33917.7D
Cardon, P., Fleischmann, C., Aritz, J., Logemann, M., & Heidewald, J. (2023). The challenges and opportunities of AI-assisted writing: Developing AI literacy for the AI age. Business and Professional Communication Quarterly, 86(3), 257–295. https://doi.org/10.1177/23294906231176517
Carnegie, G. D., & Napier, C. J. (2009). Traditional accountants and business professionals: Portraying the accounting profession after Enron. Accounting, Organizations and Society, 35(3), 360–376. https://doi.org/10.1016/j.aos.2009.09.002
English, P., De Villiers Scheepers, M. J., Fleischman, D., Burgess, J., & Crimmins, G. (2021). Developing professional networks: The missing link to graduate employability. Education + Training, 63(4), 647–661. https://doi.org/10.1108/ET-10-2020-0309
Ezeife, E., Kokogho, E., Odio, P. E., & Adeyanju, M. O. (2021). The future of tax technology in the United States: A conceptual framework for AI-driven tax transformation. International Journal of Multidisciplinary Research and Growth Evaluation, 2(1), 542–551. https://doi.org/10.54660/ijmrge.2021.2.1.542-551
Gelo, O., Braakmann, D., & Benetka, G. (2008). Quantitative and qualitative research: Beyond the debate. Integrative Psychological and Behavioral Science, 42(3), 266–290. https://doi.org/10.1007/s12124-008-9078-3
Giordano, J., O’Reilly, M., Taylor, H., & Dogra, N. (2007). Confidentiality and autonomy: The challenge(s) of offering research participants a choice of disclosing their identity. Qualitative Health Research, 17(2), 264–275. https://doi.org/10.1177/1049732306297884
Gonçalves, M. J. A., Da Silva, A. C. F., & Ferreira, C. G. (2022). The future of accounting: How will digital transformation impact the sector? Informatics, 9(1), 19. https://doi.org/10.3390/informatics9010019
Holmes, A. F., & Douglass, A. (2021). Artificial intelligence: Reshaping the accounting profession and the disruption to accounting education. Journal of Emerging Technologies in Accounting, 19(1), 53–68. https://doi.org/10.2308/JETA-2020-054
Kavanagh, M. H., & Drennan, L. (2008). What skills and attributes does an accounting graduate need? Evidence from student perceptions and employer expectations. Accounting and Finance, 48(2), 279–300. https://doi.org/10.1111/j.1467-629X.2007.00245.x
Kilpatrick, K., Tchouaket, É., Paquette, L., Guillemette, C., Jabbour, M., Desmeules, F., Landry, V., & Fernandez, N. (2019). Measuring patient and family perceptions of team processes and outcomes in healthcare teams: Questionnaire development and psychometric evaluation. BMC Health Services Research, 19(1), 1–10. https://doi.org/10.1186/s12913-018-3808-0
Leitner-Hanetseder, S., Lehner, O. M., Eisl, C., & Forstenlechner, C. (2021). A profession in transition: Actors, tasks and roles in AI-based accounting. Journal of Applied Accounting Research, 22(3), 539–556. https://doi.org/10.1108/JAAR-10-2020-0201
Leonard, V. M., Bélanger, C. H., & Wardley, L. J. (2016). Examining the ethical behavior of Ontario chartered accountants: A longitudinal review of the disciplinary process. Accounting Perspectives, 15(3), 169–199. https://doi.org/10.1111/1911-3838.12095
Martino, S. C., Shaller, D., Schlesinger, M., Parker, A. M., Rybowski, L., Grob, R., Cerully, J. L., & Finucane, M. L. (2017). CAHPS and comments. Journal of Patient Experience, 4(1), 37–45. https://doi.org/10.1177/2374373516685940
Mathew, D., Brintha, N. C., & Jappes, J. T. W. (2023). Artificial intelligence powered automation for industry 4.0. Springer eBooks, 1–28. https://doi.org/10.1007/978-3-031-20443-2_1
Moore, P. V. (2019). OSH and the future of work: Benefits and risks of artificial intelligence tools in workplaces. Lecture Notes in Computer Science, 292–315. https://doi.org/10.1007/978-3-030-22216-1_22
Morandini, S., Fraboni, F., De Angelis, M., Puzzo, G., Giusino, D., & Pietrantoni, L. (2023). The impact of artificial intelligence on workers’ skills: Upskilling and reskilling in organisations. Informing Science: The International Journal of an Emerging Transdiscipline, 26, 39–68. https://doi.org/10.28945/5078
Musselin, C. (2013). How peer review empowers the academic profession and university managers: Changes in relationships between the state, universities and the professoriate. Research Policy, 42(5), 1165–1173. https://doi.org/10.1016/j.respol.2013.02.002
Nicolò, A., Sacchetti, M., Girardi, M., McCormick, A., Angius, L., Bazzucchi, I., & Marcora, S. M. (2019). A comparison of different methods to analyse data collected during time-to-exhaustion tests. Sport Sciences for Health, 15(3), 667–679. https://doi.org/10.1007/s11332-019-00585-7
Olan, F., Arakpogun, E. O., Suklan, J., Nakpodia, F., Damij, N., & Jayawickrama, U. (2022). Artificial intelligence and knowledge sharing: Contributing factors to organizational performance. Journal of Business Research, 145, 605–615. https://doi.org/10.1016/j.jbusres.2022.03.008
Pan, G., & Seow, P. (2016). Preparing accounting graduates for the digital revolution: A critical review of information technology competencies and skills development. Journal of Education for Business, 91(3), 166–175. https://doi.org/10.1080/08832323.2016.1145622
Pedro, F., Subosa, M., Rivas, A., & Valverde, P. (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. UNESCO. https://hdl.handle.net/20.500.12799/6533
Popping, R. (2015). Analyzing open-ended questions by means of text analysis procedures. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 128(1), 23–39. https://doi.org/10.1177/0759106315597389
Raso, F. A., Hilligoss, H., Krishnamurthy, V., Bavitz, C., & Kim, L. (2018). Artificial intelligence and human rights: Opportunities and risks. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3259344
Roszkowska, P. (2020). Fintech in financial reporting and audit for fraud prevention and safeguarding equity investments. Journal of Accounting & Organizational Change, 17(2), 164–196. https://doi.org/10.1108/JAOC-09-2019-0098
Sheela, S., Alsmady, A. A., Tanaraj, K., & Izani, I. (2023). Navigating the future: Blockchain’s impact on accounting and auditing practices. Sustainability, 15(24), 16887. https://doi.org/10.3390/su152416887
Spring, M., Faulconbridge, J., & Sarwar, A. (2022). How information technology automates and augments processes: Insights from artificial-intelligence-based systems in professional service operations. Journal of Operations Management, 68(6–7), 592–618. https://doi.org/10.1002/joom.1215
Strich, F., Mayer, A., & Fiedler, M. (2021). What do I do in a world of artificial intelligence? Investigating the impact of substitutive decision-making AI systems on employees’ professional role identity. Journal of the Association for Information Systems, 22(2), 304–324. https://doi.org/10.17705/1JAIS.00663
Sutton, S. G., Arnold, V., & Holt, M. (2018). How much automation is too much? Keeping the human relevant in knowledge work. Journal of Emerging Technologies in Accounting, 15(2), 15–25. https://doi.org/10.2308/JETA-52311
Sutton, S. G., Holt, M., & Arnold, V. (2016). “The reports of my death are greatly exaggerated”—Artificial intelligence research in accounting. International Journal of Accounting Information Systems, 22, 60–73. https://doi.org/10.1016/j.accinf.2016.07.005
Vudugula, S., Chebrolu, S. K., Bhuiyan, M., & Rozony, F. Z. (2023b). Integrating artificial intelligence in strategic business decision-making: A systematic review of predictive models. International Journal of Scientific Interdisciplinary Research, 4(1), 1–26. https://doi.org/10.63125/s5skge53
Zaripova, R., Kosulin, V., Shkinderov, M., & Rakhmatullin, I. (2023). Unlocking the potential of artificial intelligence for big data analytics. E3S Web of Conferences, 460, 04011. https://doi.org/10.1051/e3sconf/202346004011