Artificial Intelligence (AI) is the way forward in accounting and auditing. The purpose of this study was to examine the relationship between accounting students’ level of technology readiness (TR) and AI technology adoption (TA). This quantitative study examined the independent variables of TR, perceived ease of use (PEOU), and perceived usefulness (PU) and the dependent variable of TA. Moreover, the present study examined the mediating effect of PEOU and PU on the relationship between TR and TA.
The present study was related to individual accounting students’ perceptions of TR and TA. Student participants (n = 101) recruited for this study were randomly sampled from 2 universities in Southern California, the United States. An online questionnaire consisting of 30 items regarding perceptions of TR, PEOU, PU, and TA was administered.
The bivariate correlation and regression between variables showed that TR, PEOU, and PU positively influence TA; TR positively influences PEOU and PU; and PEOU positively influences PU. Mediation analysis showed that both PEOU and PU mediate the relationship between TR and TA. Because of the significant relationships among variables, the model met the criteria for technology readiness and acceptance model (TRAM) and Model 6 of process mediation.
This study adds to the empirical research regarding the relationships between the constructs of TR and TA of AI within higher education, in which there is a gap in the literature. The study contributed by applying the TRAM construct to the use and adoption of AI. TR, PEOU, and PU are important constructs within higher education and predict AI TA by accounting students. Additionally, TR is a precursor to PEOU and PU of AI for this population.
For practice, universities should enhance use perceptions by creating opportunities for accounting students to interact with AI. Effective adoption of AI in accounting curricula aimed at enhancing students’ perceptions is essential to increase their adoption of AI and overall career readiness. For research, replicating the study at other universities, examining other factors that influence students’ adoption of AI, and exploring other AI topics in higher education could expand the literature on technology readiness and TA of AI.
|Advisor:||Haque, Md. Mahbubul|
|Commitee:||Helou, Ibrahim, Salimi, Anwar|
|School:||University of La Verne|
|Department:||LaFetra College of Education|
|School Location:||United States -- California|
|Source:||DAI-A 81/5(E), Dissertation Abstracts International|
|Subjects:||Accounting, Business education, Artificial intelligence, Educational technology|
|Keywords:||Accounting, AI, Artificial intelligence, Auditing, Technology adoption, Technology readiness|
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