References
Aldeen, Y. a. a. S., Salleh, M., & Razzaque, M. A. (2015). A comprehensive review on privacy preserving data mining. SpringerPlus, 4(1). https://doi.org/10.1186/s40064-015-1481-x
Alzoubi, H. M., & Aziz, R. (2021). Does emotional intelligence contribute to quality of strategic decisions? The mediating role of open innovation. Journal of Open Innovation Technology Market and Complexity, 7(2), 130. https://doi.org/10.3390/joitmc7020130
Behl, A., Dutta, P., Luo, Z., & Sheorey, P. (2021). Enabling artificial intelligence on a donation-based crowdfunding platform: a theoretical approach. Annals of Operations Research, 319(1), 761–789. https://doi.org/10.1007/s10479-020-03906-z
Bhargava, A., Bester, M., & Bolton, L. (2020). Employees’ perceptions of the implementation of robotics, Artificial intelligence, and Automation (RAIA) on job satisfaction, job security, and employability. Journal of Technology in Behavioral Science, 6(1), 106–113. https://doi.org/10.1007/s41347-020-00153-8
Budhwar, P., Malik, A., De Silva, M. T. T., & Thevisuthan, P. (2022). Artificial intelligence – challenges and opportunities for international HRM: a review and research agenda. The International Journal of Human Resource Management, 33(6), 1065–1097. https://doi.org/10.1080/09585192.2022.2035161
Busuioc, M. (2020). Accountable Artificial intelligence: holding algorithms to account. Public Administration Review, 81(5), 825–836. https://doi.org/10.1111/puar.13293
De Almeida, P. G. R., Santos, C. D. D., & Farias, J. S. (2021). Artificial Intelligence Regulation: a framework for governance. Ethics and Information Technology, 23(3), 505–525. https://doi.org/10.1007/s10676-021-09593-z
Drydakis, N. (2022). Artificial intelligence and reduced SMEs’ business risks. A Dynamic Capabilities Analysis during the COVID-19 pandemic. Information Systems Frontiers, 24(4), 1223–1247. https://doi.org/10.1007/s10796-022-10249-6
Elliott, K., Price, R., Shaw, P., Spiliotopoulos, T., Ng, M., Coopamootoo, K., & Van Moorsel, A. (2021). Towards an equitable digital society: artificial intelligence (AI) and Corporate Digital Responsibility (CDR). Society, 58(3), 179–188. https://doi.org/10.1007/s12115-021-00594-8
Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022). Is artificial intelligence improving the audit process? Review of Accounting Studies, 27(3), 938–985. https://doi.org/10.1007/s11142-022-09697-x
Fenwick, M., Vermeulen, E. P. M., & Corrales, M. (2018). Business and Regulatory responses to artificial intelligence: dynamic regulation, innovation ecosystems and the strategic management of disruptive technology. In Perspectives in law, business and innovation (pp. 81–103). https://doi.org/10.1007/978-981-13-2874-9_4
Haneef, R., Delnord, M., Vernay, M., Bauchet, E., Gaidelyte, R., Van Oyen, H., Or, Z., Pérez-Gómez, B., Palmieri, L., Achterberg, P., Tijhuis, M., Zaletel, M., Mathis-Edenhofer, S., Májek, O., Haaheim, H., Tolonen, H., & Gallay, A. (2020). Innovative use of data sources: a cross-sectional study of data linkage and artificial intelligence practices across European countries. Archives of Public Health, 78(1). https://doi.org/10.1186/s13690-020-00436-9
Holmström, J. (2021). From AI to digital transformation: The AI readiness framework. Business Horizons, 65(3), 329–339. https://doi.org/10.1016/j.bushor.2021.03.006
Horsfall, H. L., Palmisciano, P., Khan, D. Z., Muirhead, W., Koh, C. H., Stoyanov, D., & Marcus, H. J. (2020). Attitudes of the surgical team toward Artificial intelligence in Neurosurgery: International 2-Stage Cross-Sectional Survey. World Neurosurgery, 146, e724–e730. https://doi.org/10.1016/j.wneu.2020.10.171
Issa, W. B., Akour, I. A., Ibrahim, A., Almarzouqi, A., Abbas, S., Hisham, F., & Griffiths, J. (2020). Privacy, confidentiality, security and patient safety concerns about electronic health records. International Nursing Review, 67(2), 218–230. https://doi.org/10.1111/inr.12585
Jarrett, A., & Choo, K. R. (2021). The impact of automation and artificial intelligence on digital forensics. Wiley Interdisciplinary Reviews Forensic Science, 3(6). https://doi.org/10.1002/wfs2.1418
Kelley, K. H., Fontanetta, L. M., Heintzman, M., & Pereira, N. (2018). Artificial intelligence: Implications for social inflation and insurance. Risk Management and Insurance Review, 21(3), 373–387. https://doi.org/10.1111/rmir.12111
Khan, H. U., Malik, M. Z., Alomari, M. K. B., Khan, S., Al-Maadid, A. a. S. A., Hassan, M. K., & Khan, K. (2022). Transforming the Capabilities of Artificial intelligence in GCC Financial Sector: A Systematic literature review. Wireless Communications and Mobile Computing, 2022, 1–17. https://doi.org/10.1155/2022/8725767
Kokina, J., & Blanchette, S. (2019). Early evidence of digital labor in accounting: Innovation with Robotic Process Automation. International Journal of Accounting Information Systems, 35, 100431. https://doi.org/10.1016/j.accinf.2019.100431
Mahalakshmi, V., Kulkarni, N., Kumar, K. P., Kumar, K. S., Sree, D. N., & Durga, S. (2021). The Role of implementing Artificial Intelligence and Machine Learning Technologies in the financial services Industry for creating Competitive Intelligence. Materials Today Proceedings, 56, 2252–2255. https://doi.org/10.1016/j.matpr.2021.11.577
Milana, C., & Ashta, A. (2021). Artificial intelligence techniques in finance and financial markets: A survey of the literature. Strategic Change, 30(3), 189–209. https://doi.org/10.1002/jsc.2403
Munoko, I., Brown-Liburd, H. L., & Vasarhelyi, M. (2020). The ethical implications of using artificial intelligence in auditing. Journal of Business Ethics, 167(2), 209–234. https://doi.org/10.1007/s10551-019-04407-1
Omoteso, K. (2012). The application of artificial intelligence in auditing: Looking back to the future. Expert Systems With Applications, 39(9), 8490–8495. https://doi.org/10.1016/j.eswa.2012.01.098
Ramachandran, K., Mary, A. a. S., Hawladar, S., Asokk, D., Bhaskar, B., & Pitroda, J. (2021). Machine learning and role of artificial intelligence in optimizing work performance and employee behavior. Materials Today Proceedings, 51, 2327–2331. https://doi.org/10.1016/j.matpr.2021.11.544
Rana, N. P., Chatterjee, S., Dwivedi, Y. K., & Akter, S. (2021). Understanding dark side of artificial intelligence (AI) integrated business analytics: assessing firm’s operational inefficiency and competitiveness. European Journal of Information Systems, 31(3), 364–387. https://doi.org/10.1080/0960085x.2021.1955628
Svanberg, J., Ardeshiri, T., Samsten, I., Öhman, P., Neidermeyer, P. E., Rana, T., Semenova, N., & Danielson, M. (2022). Corporate governance performance ratings with machine learning. Intelligent Systems in Accounting Finance & Management, 29(1), 50–68. https://doi.org/10.1002/isaf.1505
Truby, J., Brown, R., & Dahdal, A. (2020). Banking on AI: mandating a proactive approach to AI regulation in the financial sector. Law And Financial Markets Review, 14(2), 110–120. https://doi.org/10.1080/17521440.2020.1760454
Van Noordt, C., & Misuraca, G. (2022). Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union. Government Information Quarterly, 39(3), 101714. https://doi.org/10.1016/j.giq.2022.101714
Weber-Lewerenz, B. (2021). Corporate digital responsibility (CDR) in construction engineering—ethical guidelines for the application of digital transformation and artificial intelligence (AI) in user practice. SN Applied Sciences, 3(10). https://doi.org/10.1007/s42452-021-04776-1
Wirtz, B. W., Weyerer, J. C., & Sturm, B. J. (2020). The Dark Sides of Artificial Intelligence: An Integrated AI Governance Framework for Public Administration. International Journal of Public Administration, 43(9), 818–829. https://doi.org/10.1080/01900692.2020.1749851