Analysis of Technology Readiness of Generation Z Accountants with the Technology Acceptance Model in Adopting Artificial Intelligence Technology
DOI:
https://doi.org/10.59188/eduvest.v4i11.44756Keywords:
Technology readiness, perceived ease of use, perceived usefulness, AI adoption, Generation Z accountantsAbstract
Everything related to Artificial Intelligence (AI) technology has a crucial role to play in helping to improve efficiency, lowering expenses, and optimizing decision-making across numerous industries, including accounting, where Generation Z accountants, particularly in Batam, must continuously develop their skills and readiness to leverage AI despite challenges related to data privacy and security. This research seeks to evaluate the readiness of a Generation Z accountant to embrace artificial intelligence (AI) technology by applying the Technology Acceptance Model (TAM). In the context of the fourth industrial revolution, AI adoption is crucial for improving efficiency and effectiveness in accounting practices. The study employs a quantitative approach with purposive sampling, involving 220 Generation Z accountant participants from Batam City. The analysis, conducted using the PLS-PM method in R programming and data processing with Google Colab statistics, reveals that the Technology Readiness (TR) variable significantly influences the interest of Generation Z accountants in adopting AI technology. While the perceived ease of use (PEOU) variable showed no significant effect, perceived usefulness (PU) emerged as the dominant factor in technology adoption. The R-Squared value of 0.920 indicates that 92% of the variables influencing AI technology adoption are explained by TR and PU. This study highlights the importance of technology readiness in helping Generation Z accountants adapt to technological advancements and offers recommendations for enhancing education, training, and technology development within the accounting profession.
References
Abdullah, Abdulwahid Ahmad Hashed, & Almaqtari, Faozi A. (2024). The impact of artificial intelligence and Industry 4.0 on transforming accounting and auditing practices. Journal of Open Innovation: Technology, Market, and Complexity, 10(1), 100218.
Anh, Nguyen Thi Mai, Hoa, Le Thi Khanh, Thao, Lai Phuong, Nhi, Duong Anh, Long, Nguyen Thanh, Truc, Nguyen Thanh, & Ngoc Xuan, Vu. (2024). The effect of technology readiness on adopting artificial intelligence in accounting and auditing in Vietnam. Journal of Risk and Financial Management, 17(1), 27.
Bogdan, Victoria, Rus, Luminita, Gherai, Dana Simona, Florea, Adrian Gheorghe, & Bugnar, Nicoleta Georgeta. (2023). A Streamline Sustainable Business Performance Reporting Model by an Integrated FinESG Approach. Sustainability, 15(24), 16860.
Damerji, Hassan, & Salimi, Anwar. (2021). Mediating effect of use perceptions on technology readiness and adoption of artificial intelligence in accounting. Accounting Education, 30(2), 107–130.
Firoiu, Daniela, Ionescu, George H., Cismaș, Laura Mariana, Vochița, Luminița, Cojocaru, Teodor Marian, & Bratu, Răducu Ștefan. (2023). Can Europe Reach Its Environmental Sustainability Targets by 2030? A Critical Mid-Term Assessment of the Implementation of the 2030 Agenda. Sustainability, 15(24), 16650.
Gulliford, Fred, & Dixon, Amy Parker. (2019). AI: the HR revolution. Strategic HR Review, 18(2), 52–55.
Hair, Joseph, & Alamer, Abdullah. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027.
Hasan, Ahmed Rizvan. (2021). Artificial Intelligence (AI) in accounting & auditing: A Literature review. Open Journal of Business and Management, 10(1), 440–465.
Kholilah, Kholilah, Kawulur, Hisky Ryan, & Subekti, Imam. (2022). Perceived usefulness, perceived ease of use, facilitating condition, social influence, and personal innovativeness of accounting students cloud computing adoption. Organum: Jurnal Saintifik Manajemen Dan Akuntansi, 5(2), 141–151.
Leitner-Hanetseder, Susanne, Lehner, Othmar M., Eisl, Christoph, & Forstenlechner, Carina. (2021). A profession in transition: actors, tasks and roles in AI-based accounting. Journal of Applied Accounting Research, 22(3), 539–556.
Liu, L. L., Su, Y. J., & Chiang, C. H. (2023). Research from RPA Advancement to AI Intelligent Automation Development: Taking the Accounting Service Industry in Taiwan as an Example. Advances in Management and Applied Economics, 55–91.
Moron, Camille E., & Diokno, Chester Owen B. (2023). Level of readiness and adoption on the use of artificial intelligence technologies in the accounting profession. Open Journal of Accounting, 12(3), 37–54.
Năstasă, Anamaria, Dumitra, Teodora Cătălina, & Grigorescu, Adriana. (2024). Artificial intelligence and sustainable development during the pandemic: An overview of the scientific debates. Heliyon.
Nga, Ngo Thi Viet, Xuan, Vu Ngoc, Trong, Vu Anh, Thao, Pham Huong, & Doanh, Duong Cong. (2023). Perceived barriers and intentions to receive COVID-19 vaccines: psychological distress as a moderator. Vaccines, 11(2), 289.
Nouraldeen, Rasha Mohammad. (2023). The impact of technology readiness and use perceptions on students’ adoption of artificial intelligence: the moderating role of gender. Development and Learning in Organizations: An International Journal, 37(3), 7–10.
Parasuraman, Ananthanarayanan, & Colby, Charles L. (2015). An updated and streamlined technology readiness index: TRI 2.0. Journal of Service Research, 18(1), 59–74.
Paudel, Gokul P., Gartaula, Hom, Justice, Scott E., Krupnik, Timothy J., & McDonald, Andrew J. (2023). The contributions of scale-appropriate farm mechanization to hunger and poverty reduction: evidence from smallholder systems in Nepal. Journal of Economics and Development, 25(1), 37–61.
Salman, Doaa, & Ismael, Doaa. (2023). The effect of digital financial inclusion on the green economy: the case of Egypt. Journal of Economics and Development, 25(2), 120–133.
Sudaryanto, Miftah Rizqullah, Hendrawan, Muhammad Aditya, & Andrian, Tommy. (2023). The Effect of Technology Readiness, Digital Competence, Perceived Usefulness, and Ease of Use on Accounting Students Artificial Intelligence Technology Adoption. E3S Web of Conferences, 388, 4055. EDP Sciences.
Sugiyono. (2019). Metode Penelitian Kuantitatif Kualitatif dan R&D. Yogyakarta: Alfabeta.
Vărzaru, Anca Antoaneta. (2022). Assessing artificial intelligence technology acceptance in managerial accounting. Electronics, 11(14), 2256.
Wang, Jianwang, Luo, Lan, Sa, Rina, Zhou, Wei, & Yu, Zihan. (2023). A Quantitative Analysis of Decision-Making Risk Factors for Mega Infrastructure Projects in China. Sustainability, 15(21), 15301.
Zhang, Yongming, Imeni, Mohsen, & Edalatpanah, Seyyed Ahmad. (2023). Environmental dimension of corporate social responsibility and earnings persistence: an exploration of the moderator roles of operating efficiency and financing cost. Sustainability, 15(20), 14814.
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