How to cite this paper
Al-Mawalia, H., Allozia, Y., Nawaiseha, A., Zaidana, H., Natour, A & Alshurideh, M. (2025). AI-based audit acceptance and auditors’ technology readiness.International Journal of Data and Network Science, 9(3), 525-540.
Refrences
Abdullah, A. A. H., & Almaqtari, F. A. (2024). The impact of artificial intelligence and Industry 4.0 on transforming account-ing and auditing practices. Journal of Open Innovation: Technology, Market, and Complexity, 10(1), 100218. https://doi.org/10.1016/j.joitmc.2024.100218
Agustí, M. A., & Orta-Pérez, M. (2022). Big data and artificial intelligence in the fields of accounting and auditing: a biblio-metric analysis. Spanish Journal of Finance and Accounting, 52(3), 412–438. https://doi.org/10.1080/02102412.2022.2099675
Al-Sayyed, S., Al-Aroud, S., & Zayed, L. (2021). The effect of artificial intelligence technologies on audit evidence. Account-ing, 7(2), 281-288.
Al Natour, A. R., Al-Mawali, H., Zaidan, H., Meqbel, R., & Kawuq, S. (2024a). The readiness of Jordanian-listed firms toward CAATTs application in the post Covid-19 epidemic period. Discover Sustainability, 5. https://doi.org/10.1007/s43621-024-00313-3
Al Natour, A. R., Zaidan, H., Said, Y., & Al-Mawali, H. (2024b). The Role of Forensic Accounting Skills and CAATTs Applica-tion in Enhancing Firm's Cyber Resilience. In 2024 2nd International Conference on Cyber Resilience (ICCR) (pp. 1-5). IEEE.
Al Wael, H., Abdallah, W., Ghura, H., & Buallay, A. (2024). Factors influencing artificial intelligence adoption in the account-ing profession: the case of public sector in Kuwait. Competitiveness Review: An International Business Journal, 34(1), 3-27.
Alkhaffaf, H. H. K., Idris, K. M., Abdullah, A., & Al-Aidaros, A. H. (2018). The influence of technology readiness on infor-mation technology competencies and civil conflict environment. Indian-Pacific Journal of Accounting and Finance, 2(2), 51-64.
Al-Momani, K. (2020). Response rates in survey-based research in Jordan. Jordanian Journal of Business Administration, 16(1), 45-60.
Applegate, D., & Koenig, M. (2019). Framing AI audits. Internal Auditor, 76(6), 29-34.
Bhushan, U., Gujarathi, R., & Seetharaman, A. (2017). The Future of Accounting and Corporate Reporting-A View from the IT Perspective. International Journal of Business Management & Economic Research, 8(6).
Borrero, J. D., Yousafzai, S. Y., Javed, U., & Page, K. L. (2014). Expressive participation in Internet social movements: Testing the moderating effect of technology readiness and sex on student SNS use. Computers in Human Behavior, 30, 39-49.
Capa, R. L., Audiffren, M., & Ragot, S. (2008). The effects of achievement motivation, task difficulty, and goal difficulty on physiological, behavioral, and subjective effort. Psychophysiology, 45(5), 859-868.
Çabuk, A., & Aytaç, A. (2019). The transformation of auditing from traditional to continuous auditing in the era of big data. In Organizational Auditing and Assurance in the Digital Age (pp. 137-152). IGI Global.Chan and Kim, 2020
Chang, Y. W., & Chen, J. (2021). What motivates customers to shop in smart shops? The impacts of smart technology and technology readiness. Journal of Retailing and Consumer Services, 58, 102325.
Chao, C.-M., & Yu, T.-K. (2019). The moderating effect of technology optimism: How it affects students’ weblog learning. Online Information Review, 43(1), 161-180. https://doi.org/10.1108/OIR-11-2016-0316
Choung, H., David, P., & Ross, A. (2022). Trust in AI and Its Role in the Acceptance of AI Technologies. International Journal of Human–Computer Interaction, 39(9), 1727–1739. https://doi.org/10.1080/10447318.2022.2050543
Chukwuani, V. N., & Egiyi, M. A. (2020). Automation of accounting processes: impact of artificial intelligence. International Journal of Research and Innovation in Social Science (IJRISS), 4(8), 444-449.
Cho, G., Hwang, H., Sarstedt, M., & Ringle, C. M. (2020). Cutoff criteria for overall model fit indexes in generalized struc-tured component analysis. Journal of marketing analytics, 8(4), 189-202. https://doi.org/10.1057/s41270-020-00089-1
Collins, C., Landivar, L. C., Ruppanner, L., & Scarborough, W. J. (2021). COVID‐19 and the gender gap in work hours. Gen-der, Work & Organization, 28, 101-112.
Commerford, B. P., Dennis, S. A., Joe, J. R., & Ulla, J. W. (2022). Man versus machine: Complex estimates and auditor reli-ance on artificial intelligence. Journal of Accounting Research, 60(1), 171-201.
Damerji, H., & Salimi, A. (2021). Mediating effect of use perceptions on technology readiness and adoption of artificial intel-ligence in accounting. Accounting Education, 30(2), 107-130. https://doi.org/10.1080/09639284.2021.1872035
Davis, F. D. (1985). A technology acceptance model for empirically testing new end-user information systems: Theory and re-sults (Doctoral dissertation, Massachusetts Institute of Technology).
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarter-ly, 13(3), 319-340.
Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of ac-ceptance and use of technology (UTAUT): Towards a revised theoretical model. Information systems frontiers, 21, 719-734. https://doi.org/10.1007/s10796-017-9774-y
Erasmus, W., & Marnewick, C. (2021). An IT governance framework for IS portfolio management. International Journal of Managing Projects in Business, 14(3), 721-742. https://doi.org/10.1108/IJMPB-04-2020-0110
Fedyk, A., Hodson, J., Khimich, N., & Fedyk, T. (2022). Is artificial intelligence improving the audit process?. Review of Ac-counting Studies, 27(3), 938-985. https://doi.org/10.1007/s11142-022-09697-x
Ajzen, I., & Fishbein, M. (1975). A Bayesian analysis of attribution processes. Psychological bulletin, 82(2), 261.
Fryer, L. K., Ainley, M., Thompson, A., Gibson, A., & Sherlock, Z. (2017). Stimulating and sustaining interest in a language course: An experimental comparison of Chatbot and Human task partners. Computers in Human Behavior, 75, 461-468.
Ghura, H., & Harraf, A. (2021). How will artificial intelligence reshape the future of entrepreneurship and economic growth? Applications of Artificial Intelligence in Business, Education and Healthcare, 69-79. https://doi.org/10.1007/978-3-030-72080-3_4
Goto, M. (2023). Anticipatory innovation of professional services: The case of auditing and artificial intelligence. Research Policy, 52(8), 104828. https://doi.org/10.1016/j.respol.2023.104828
Goudey, A., & Bonnin, G. (2016). Must smart objects look human? Study of the impact of anthropomorphism on the ac-ceptance of companion robots. Recherche et Applications in Marketing (English Edition), 31(2), 2-20.
Greenman, C. (2017). Exploring the impact of artificial intelligence on the accounting profession. Journal of Research in Business, Economics and Management, 8(3), 1451.
Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169. https://doi.org/10.1016/j.ijinfomgt.2019.03.008
Hair, J. F., Astrachan, C. B., Moisescu, O. I., Radomir, L., Sarstedt, M., Vaithilingam, S., & Ringle, C. M. (2021). Executing and interpreting applications of PLS-SEM: Updates for family business researchers. Journal of Family Business Strategy, 12(3), 100392. https://doi.org/10.1016/j.jfbs.2020.100392
Hall, B., & Henningsen, D. D. (2008). Social facilitation and human–computer interaction. Computers in human behavior, 24(6), 2965-2971. https://doi.org/10.1016/j.chb.2008.05.003
Han, H., Shiwakoti, R. K., Jarvis, R., Mordi, C., & Botchie, D. (2023). Accounting and auditing with blockchain technology and artificial Intelligence: A literature review. International Journal of Accounting Information Systems, 48, 100598. https://doi.org/10.1016/j.accinf.2022.100598
Holt, D. T., Armenakis, A. A., Feild, H. S., & Harris, S. G. (2007). Readiness for organizational change: The systematic devel-opment of a scale. The Journal of applied behavioral science, 43(2), 232-255. https://doi.org/10.1177/0021886306295
Ilias, A., Baidi, N. B., & Rahman, R. A. (2020). Are you ready to embrace new technology? Accounting practitioners in Malay-sia. Science International, 32(2), 199-203.
IFAC (2018), Is Your Business Ready to Adapt to Demographic and Technology Changes? available at: https://www.ifac.org/search?sort_by=search_api_relevance&field_source[4]=4&keys=technology%20readiness%20 (ac-cessed 23 February 2024).
Issa, H., Sun, T., & Vasarhelyi, M. A. (2016). Research ideas for artificial intelligence in auditing: The formalization of audit and workforce supplementation. Journal of emerging technologies in accounting, 13(2), 1-20. https://doi.org/10.2308/jeta-10511
JACPA (2024). A list of Jordanian Certified Public Accountants inside Jordan. available at: https://jacpa.org.jo/Portals/0/a1_1.pdf (accessed 26 January 2024).
Jaffar, N., Ahmad, A.A.A., & Sulaiman, N.A. (2022). Technology readiness and data analytics competencies of the Muslim and non-Muslim external auditors: a comparative analysis. Journal of Islamic Accounting and Business Research, 13(6), 920-941. https://doi.org/10.1108/JIABR-11-2020-0341
Kashive, N., Powale, L., & Kashive, K. (2021). Understanding user perception toward artificial intelligence (AI) enabled e-learning. International Journal of Information and Learning Technology, 38(1), 1-19. https://doi.org/10.1108/IJILT-05-2020-0090
Kelly, S., Kaye, S. A., & Oviedo-Trespalacios, O. (2023). What factors contribute to the acceptance of artificial intelligence? A systematic review. Telematics and Informatics, 77, 101925. https://doi.org/10.1016/j.tele.2022.101925
Kim, H. Y., & McGill, A. L. (2018). Minions for the rich? Financial status changes how consumers see products with anthro-pomorphic features. Journal of Consumer Research, 45(2), 429-450. https://doi.org/10.1093/jcr/ucy006
Khan, R., Adi, E., & Hussain, O. (2021). AI-based audit of fuzzy front-end innovation using ISO56002. Managerial Auditing Journal, 36(4), 564-590. https://doi.org/10.1108/MAJ-03-2020-2588
Kock, N., & Lynn, G. (2012). Lateral collinearity and misleading results in variance-based SEM: An illustration and recom-mendations. Journal of the Association for information Systems, 13(7).
Kock, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1-10.
Kommunuri, J. (2022). Artificial intelligence and the changing landscape of accounting: a viewpoint. Pacific Accounting Re-view, 34(4), 585-594. https://doi.org/10.1108/PAR-06-2021-0107
Kokina, J., & Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of emerging technologies in accounting, 14(1), 115-122. https://doi.org/10.2308/jeta-51730
Lai, M. T., & Chen, Y. C. (2008). Optimal replacement period of a two-unit system with failure rate interaction and external shocks. International Journal of Systems Science, 39(1), 71-79. https://doi.org/10.1080/00207720701669479
Latané, B. (1981). The psychology of social impact. American psychologist, 36(4), 343.
Law, R., Chan, I. C. C., & Wang, L. (2018). A comprehensive review of mobile technology use in hospitality and tourism. Journal of Hospitality Marketing & Management, 27(6), 626-648. https://doi.org/10.1080/19368623.2018.1423251
Lehner, O. M., Leitner-Hanetseder, S., Eisl, C., & Knoll, C. (2022). Artificial Intelligence-driven Accounting (AIDA): Future Insights and Organisational Implications. In Artificial Intelligence in Accounting (pp. 6-34). Routledge.
Liengaard, B. D., Sharma, P. N., Hult, G. T. M., Jensen, M. B., Sarstedt, M., Hair, J. F., & Ringle, C. M. (2021). Prediction: coveted, yet forsaken? Introducing a cross‐validated predictive ability test in partial least squares path modeling. Decision Sciences, 52(2), 362-392.https://doi.org/10.1111/deci.12445
Lin, C. Y., & Xu, N. (2022). Extended TAM model to explore the factors that affect intention to use AI robotic architects for architectural design. Technology Analysis & Strategic Management, 34(3), 349-362. https://doi.org/10.1080/09537325.2021.1900808
Lu, L., Cai, R., & Gursoy, D. (2019). Developing and validating a service robot integration willingness scale. International Journal of Hospitality Management, 80, 36-51. https://doi.org/10.1016/j.ijhm.2019.01.005
Mancini, D., Lombardi, R., & Tavana, M. (2021). Four research pathways for understanding the role of smart technologies in accounting. Meditari Accountancy Research, 29(5), 1041-1062. https://doi.org/10.1108/MEDAR-03-2021-1258
McLean, G., & Osei-Frimpong, K. (2019). Hey Alexa… examine the variables influencing the use of artificial intelligent in-home voice assistants. Computers in Human Behavior, 99, 28-37. https://doi.org/10.1016/j.chb.2019.05.009
Meyer-Waarden, L., & Cloarec, J. (2022). “Baby, you can drive my car”: Psychological antecedents that drive consumers’ adoption of AI-powered autonomous vehicles. Technovation, 109, 102348. https://doi.org/10.1016/j.technovation.2021.102348
Ming Ling, L., & Muhammad, I. (2006). Taxation and Technology: Technology Readiness of Malaysian Tax Officers in Petal-ing Jaya Branch. Journal of Financial Reporting and Accounting, 4(1), 147-163. https://doi.org/10.1108/19852510680001587
Mohammad, S. J., Hamad, A. K., Borgi, H., Thu, P. A., Sial, M. S., & Alhadidi, A. A. (2020). How artificial intelligence chang-es the future of accounting industry. International Journal of Economics and Business Administration, 8(3), 478-488.
Moll, J., & Yigitbasioglu, O. (2019). The role of internet-related technologies in shaping the work of accountants: New direc-tions for accounting research. The British accounting review, 51(6), 100833.
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.
Nugroho, M. A., & Fajar, M. A. (2017). Effects of technology readiness towards acceptance of mandatory web-based attend-ance system. Procedia Computer Science, 124, 319-328.
Oduwole, F. R., & Olukunle, I. (2023). Artificial intelligence and accounting practice in Nigerian banking industry. BOHR In-ternational Journal of Finance and Market Research, 2(1), 61-69.
Truong, Y., & Papagiannidis, S. (2022). Artificial intelligence as an enabler for innovation: A review and future research agen-da. Technological Forecasting and Social Change, 183, 121852. https://doi.org/10.1016/j.techfore.2022.121852
Parasuraman, A., & Colby, C. L. (2015). An updated and streamlined technology readiness index: TRI 2.0. Journal of service research, 18(1), 59-74.
Parasuraman, A. (2000). Technology readiness index (TRI) factors as differentiating elements between users and non users of internet banking, and as antecedents of the technology acceptance model (TAM). Journal Of Service Research, 2, 307-320.
Peng, D. X., & Lai, F. (2012). Using partial least squares in operations management research: A practical guideline and sum-mary of past research. Journal of operations management, 30(6), 467-480.
Ramayah, T. J. F. H., Cheah, J., Chuah, F., Ting, H., & Memon, M. A. (2018). Partial least squares structural equation model-ing (PLS-SEM) using smartPLS 3.0. An updated guide and practical guide to statistical analysis, 978-967.
Rather, R. A., & Hollebeek, L. D. (2019). Exploring and validating social identification and social exchange-based drivers of hospitality customer loyalty. International Journal of Contemporary Hospitality Management, 31(3), 1432-1451.
Raghunathan, R., & Pham, M. T. (1999). All negative moods are not equal: Motivational influences of anxiety and sadness on decision making. Organizational behavior and human decision processes, 79(1), 56-77.
Rai, A. (2020). Explainable AI: From black box to glass box. Journal of the Academy of Marketing Science, 48, 137-141.
Ramen, M., Jugurnath, B., & Ramhit, P. (2015). UTR-CTOE: a new paradigm explaining CAATs adoption. Journal of Modern Accounting and Auditing, 11(12), 615-631.
Rikhardsson, P., Kristinn, T., Bergthorsson, G., & Batt, C. (2022). Artificial intelligence and auditing in small-and medium-sized firms: Expectations and applications. AI Magazine, 43(3), 323-336.
Rosenthal-von der Pütten, A. M., & Krämer, N. C. (2015). Individuals’ evaluations of and attitudes towards potentially uncan-ny robots. International Journal of Social Robotics, 7, 799-824.
Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Pearson.
Rucker, D. D., & Petty, R. E. (2004). When resistance is futile: Consequences of failed counterarguing for attitude certain-ty. Journal of personality and social psychology, 86(2), 219.
Seethamraju, R., & Hecimovic, A. (2023). Adoption of artificial intelligence in auditing: An exploratory study. Australian Journal of Management, 48(4), 780-800.
Sharma, P.N., Liengaard, B.D., Hair, J.F., Sarstedt, M., & Ringle, C.M. (2023). Predictive model assessment and selection in composite-based modeling using PLS-SEM: extensions and guidelines for using CVPAT. European Journal of Marketing, 57(6), 1662-1677. https://doi.org/10.1108/EJM-08-2020-0636
Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model as-sessment in PLS-SEM: guidelines for using PLSpredict. European journal of marketing, 53(11), 2322-2347.
Sohn, K., & Kwon, O. (2020). Technology acceptance theories and factors influencing artificial Intelligence-based intelligent products. Telematics and Informatics, 47, 101324. https://doi.org/10.1016/j.tele.2019.101324
Thomas, T., Singh, L., & Gaffar, K. (2013). The utility of the UTAUT model in explaining mobile learning adoption in higher education in Guyana. International Journal of Education and Development using ICT, 9(3).
Thottoli, M.M., Ahmed, E.R., & Thomas, K.V. (2022). Emerging technology and auditing practice: analysis for future direc-tions. European Journal of Management Studies, 27(1), 99-119. https://doi.org/10.1108/EJMS-06-2021-0058
Thottoli, M.M. (2024). Leveraging information communication technology (ICT) and artificial intelligence (AI) to enhance auditing practices. Accounting Research Journal, 37(2), 134-150. https://doi.org/10.1108/ARJ-09-2023-0269
Tiron-Tudor, A., & Deliu, D. (2022). Reflections on the human-algorithm complex duality perspectives in the auditing pro-cess. Qualitative Research in Accounting & Management, 19(3), 255-285.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a uni-fied view. MIS quarterly, 27(3), 425-478.
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 36(1), 157-178.
Wang, Y., So, K. K. F., & Sparks, B. A. (2017). Technology readiness and customer satisfaction with travel technologies: A cross-country investigation. Journal of Travel Research, 56(5), 563-577.
Watson, L., & Spence, M. T. (2007). Causes and consequences of emotions on consumer behaviour: A review and integrative cognitive appraisal theory. European Journal of Marketing, 41(5/6), 487-511.
Wirtz, B. W., Weyerer, J. C., & Kehl, I. (2018). Governance of artificial intelligence: A risk and guideline-based integrative framework. Government Information Quarterly, 39(4), 101685.
Wright, R. A., & Kirby, L. D. (2001). Effort determination of cardiovascular response: An integrative analysis with applica-tions in social psychology. Advances in experimental social psychology, 33, 255-307.
Xian, F. (2022). Quantifying the impact of artificial intelligence technology on China's manufacturing employment. In International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2022) (Vol. 12288, pp. 267-270). SPIE.
Zhang, C. A., Cho, S., & Vasarhelyi, M. (2022). Explainable artificial intelligence (xai) in auditing. International Journal of Accounting Information Systems, 46, 100572. https://doi.org/10.1016/j.accinf.2022.100572