A bibliometric analysis of the economic effects of using artificial intelligence and ChatGPT tools in higher education institutions
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DOIhttp://dx.doi.org/10.21511/ppm.23(1).2025.08
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Article InfoVolume 23 2025, Issue #1, pp. 101-114
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One of the main challenges in higher education management is the complexity of resource optimization and increasing volumes of data, which limits the efficiency and accuracy of decision-making. The application of artificial intelligence can address these issues.
The present study aims to identify the key trends, knowledge gaps, and opportunities for further research into the economic effects of using artificial intelligence and ChatGPT tools in higher education. For this purpose, a systematic literature review was conducted to identify and screen the scientific articles related to the topic of this study indexed in Web of Science and Scopus from 1986 to 2024. A total of 234 articles were selected, all demonstrating positive growth both in scholarly output and citation count. The study identified the key contributors to scientific research on this topic by region (the United States, China, and India). It concluded that the relevant research centers are still at an early stage of their development. Based on bibliometric clusters formed by co-occurrence relations, three main areas of research were defined: 1) artificial intelligence in education for decision-making; 2) process automation and digital transformation in educational institutions; 3) artificial intelligence technologies and their application in education.
The study highlights the main areas of economic effects of artificial intelligence and ChatGPT tools in higher education, including reducing administrative costs, saving time for teachers and students, and improving the quality and accessibility of educational process.
Acknowledgments
The publication is part of the research topic “Economic Basics of Technology Diffusion into the National Economy of Ukraine Considering Best International Practices” (№0124U003482).
- Keywords
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JEL Classification (Paper profile tab)D24, I22, O33
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References71
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Tables4
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Figures5
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- Figure 1. PRISMA flow diagram
- Figure 2. Document and citation dynamics of selected publications
- Figure 3. Quantitative characteristics of the main keywords
- Figure 4. Bibliometric clusters of the main keywords
- Figure 5. Time-scale distribution of the main keywords
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- Table 1. Main keywords
- Table 2. Top five key contributors to scientific research by region, institution, and the number of publications in scientific journals from 2014 to 2024
- Table 3. Bibliometric cluster profiles defining research areas in economic effects of using AI and ChatGPT in higher education
- Table 4. Systematization of potential economic effects of using AI and ChatGPT in higher education
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- Asim, M., Arif, M., Rafiq, M., & Ahmad, R. (2023). Investigating applications of artificial intelligence in university libraries of Pakistan: An empirical study. Journal of Academic Librarianship, 49(6), Article 102803.
- Baksh, F., Zorec, M. B., & Kruusamäe, K. (2024). Open-source robotic study companion with multimodal human–robot interaction to improve the learning experience of university students. Applied Sciences, 14(13), Article 5644.
- Bearman, M., Ryan, J., & Ajjawi, R. (2023). Discourses of artificial intelligence in higher education: A critical literature review. Higher Education, 86(2), 369-385.
- Boddington, P. (2023). The rise of AI ethics. In AI ethics. Artificial intelligence: Foundations, theory, and algorithms (pp. 35-89). Singapore: Springer.
- Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Pham, P., Chong, S. W., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21(1), Article 4.
- Braun, D., Rogetzer, P., Stoica, E., & Kurzhals, H. (2023). Students’ perspective on AI-supported assessment of open-ended questions in higher education. In Proceedings of the 15th International Conference on Computer Supported Education (CSEDU 2023) (Vol. 2, pp. 73-78).
- Cavalcanti, A. P., Barbosa, A., Carvalho, R., Freitas, F., Tsai, Y.-S., Gašević, D., & Mello, R. F. (2021). Automatic feedback in online learning environments: A systematic literature review. Computers and Education: Artificial Intelligence, 2, Article 100027.
- Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66, 616-630.
- Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), Article 38.
- Chatterjee, S., & Bhattacharjee, K. K. (2020). Adoption of artificial intelligence in higher education: A quantitative analysis using structural equation modelling. Education and Information Technologies, 25, 3443-3463.
- Chaudhry, M. A., & Kazim, E. (2022). Artificial Intelligence in Education (AIEd): A high-level academic and industry note 2021. AI and Ethics, 2, 157-165.
- Chen, K., Tallant, A. C., & Selig, I. (2024). Exploring generative AI literacy in higher education: Student adoption, interaction, evaluation and ethical perceptions. Information and Learning Sciences.
- Chu, H., Tu, Y., & Yang, K. (2022). Roles and research trends of artificial intelligence in higher education: A systematic review of the top 50 most-cited articles. Australasian Journal of Educational Technology, 38(3), 22-42.
- Corea, F., Fossa, F., Loreggia, A., Quintarelli, S., & Sapienza, S. (2022). A principle-based approach to AI: The case for European Union and Italy. AI & SOCIETY, 38, 521-535.
- Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20, Article 22.
- Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
- Driessens, O., & Pischetola, M. (2024). Danish university policies on generative AI: Problems, assumptions, and sustainability blind spots. MedieKultur: Journal of Media and Communication Research, 40(76), 31-52.
- Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, Article 102642.
- Fahd, K., Venkatraman, S., Miah, S. J., & Ahmed, K. (2022). Application of machine learning in higher education to assess student academic performance, at-risk, and attrition: A meta-analysis of literature. Education and Information Technologies, 3, 3743-3775.
- Ferrara, E. (2023). Should ChatGPT be biased? Challenges and risks of bias in large language models. First Monday, 28(11).
- Gallastegui, L. M. G., & Forradellas, R. R. (2024). Optimization of the educational experience in higher education using predictive artificial intelligence models. Revista de Gestão Social e Ambiental, 18(5), Article e07111.
- Guerrero-Roldán, A.-E., Rodríguez-González, M. E., Bañeres, D., Elasri-Ejjaberi, A., & Cortadas, P. (2021). Experiences in the use of an adaptive intelligent system to enhance online learners’ performance: A case study in Economics and Business courses. International Journal of Educational Technology in Higher Education, 18(1), Article 36.
- Haddaway, N. R., Page, M. J., Pritchard, C. C., & McGuinness, L. A. (2022). PRISMA2020: An R package and Shiny app for producing PRISMA 2020-compliant flow diagrams, with interactivity for optimised digital transparency and Open Synthesis. Campbell Systematic Reviews, 18(2), Article e1230.
- Han, X., Xiao, S., Sheng, J., & Zhang, G. (2024). Enhancing efficiency and decision-making in higher education through intelligent commercial integration: Leveraging artificial intelligence. Journal of the Knowledge Economy.
- Johnstone, D. B. (2004). The economics and politics of cost sharing in higher education: Comparative perspectives. Economics of Education Review, 23(4), 403-441.
- Kaczorowska-Spychalska, D., Kotula, N., Mazurek, G., & Sułkowski, Ł. (2024). Generative AI as source of change of knowledge management paradigm. Human Technology, 20(1), 131-154.
- Kamalov, F., Calonge, D. S., & Gurrib, I. (2023). New era of artificial intelligence in education: Towards a sustainable multifaceted revolution. Sustainability, 15(16), Article 12451.
- Karam, J. (2023). Reforming higher education through AI. In N. Azoury & G. Yahchouchi (Eds.), Governance in Higher Education: Global Reform and Trends in the MENA Region (pp. 275-306). Cham: Palgrave Macmillan.
- Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274.
- Kejriwal, M. (2023). AI in practice and implementation: Issues and costs. In Artificial Intelligence for Industries of the Future. Future of Business and Finance (pp. 25-45). Cham: Springer.
- Krenn, M., Pollice, R., Guo, S. Y., Aldeghi, M., Friederich, P., Häse, F., Jinich, A., Nigam, A., & Yao, Z. (2022). On scientific understanding with artificial intelligence. Nature Reviews Physics, 4(12), 761-769.
- Kuleto, V., Ilić, M., Dumangiu, M., Ranković, M., Martins, O. M., Păun, D., & Mihoreanu, L. (2021). Exploring opportunities and challenges of artificial intelligence and machine learning in higher education institutions. Sustainability, 13(18), Article 10424.
- Kumar, S., Rao, P., Singhania, S., Verma, S., & Kheterpal, M. (2024). Will artificial intelligence drive the advancements in higher education? A tri-phased exploration. Technological Forecasting and Social Change, 201, Article 123258.
- Kumari, R. K., & Snehalatha, M. (2024). AI and OpenAI in education: Unveiling the future of learning and teaching. In Ş. Demir & M. Demir (Eds.), Enhancing Higher Education and Research With OpenAI Models (pp. 176-205). IGI Global Scientific Publishing.
- Kurban, C. F., & Şahin, M. (2024). The impact of ChatGPT on higher education: Exploring the AI revolution. Emerald Group Publishing.
- Lee, D., Arnold, M., Srivastava, A., Plastow, K., Strelan, P., Ploeckl, F., Lekkas, D., & Palmer, E. (2024). The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives. Computers and Education: Artificial Intelligence, 6, Article 100221.
- Lindqvist, M. H., Mozelius, P., Jaldemark, J., & Innes, M. C. (2023). Higher education transformation towards lifelong learning in a digital era – A scoping literature review. International Journal of Lifelong Education, 43(1), 24-38.
- Lu, K., Pang, F., & Shadiev, R. (2023). Understanding college students’ continuous usage intention of asynchronous online courses through extended technology acceptance model. Education and Information Technologies, 28, 9747-9765.
- Mambile, C., & Mwogosi, A. (2025). Transforming higher education in Tanzania: Unleashing the true potential of AI as a transformative learning tool. Technological Sustainability, 4(1), 51-76.
- Markauskaite, L., Marrone, R., Poquet, O., Knight, S., Martinez-Maldonado, R., Howard, S., Tondeur, J., De Laat, M., Buckingham Shum, S., Gašević, D., & Siemens, G. (2022). Rethinking the entwinement between artificial intelligence and human learning: What capabilities do learners need for a world with AI? Computers and Education: Artificial Intelligence, 3, Article 100056.
- McGrath, C., Cerratto Pargman, T., Juth, N., & Palmgren, P. J. (2023). University teachers’ perceptions of responsibility and artificial intelligence in higher education – An experimental philosophical study. Computers and Education: Artificial Intelligence, 4, Article 100139.
- Meakin, L. (2024). Exploring the impact of generative artificial intelligence on higher education students’ utilization of library resources: A critical examination. Information Technology and Libraries, 43(3).
- Naseer, F., Khan, M. N., Tahir, M., Addas, A., & Aejaz, S. M. H. (2024). Integrating deep learning techniques for personalized learning pathways in higher education. Heliyon, 10(11), Article e32628.
- Ng, D. T. K., Lee, M., Tan, R. J. Y., Hu, X., Downie, J. S., & Chu, S. K. W. (2023). A review of AI teaching and learning from 2000 to 2020. Education and Information Technologies, 28(7), 8445-8501.
- Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381(6654), 187-192.
- Nyale, D., Karume, S., & Kipkebut, A. (2024). A comprehensive analysis of the role of artificial intelligence in aligning tertiary institutions academic programs to the emerging digital enterprise. Education and Information Technologies, 29, 22407-22426.
- Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, Article 100020.
- Pantelimon, F.-V., Bologa, R., Toma, A., & Posedaru, B.-S. (2021). The evolution of AI-driven educational systems during the COVID-19 pandemic. Sustainability, 13(23), Article 13501.
- Pearce, J., & Chiavaroli, N. (2023). Rethinking assessment in response to generative artificial intelligence. Medical Education, 57(10), 889-891.
- Pelletier, K., McCormack, M., Muscanell, N., Reeves, J., Robert, J., & Arbino, N. (2024). 2024 EDUCAUSE Horizon Report, teaching and learning edition. EDUCAUSE.
- Popenici, S. A. D., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), Article 22.
- Ranoliya, B.R., Raghuwanshi, N., & Singh, S. (2017). Chatbot for university related FAQs. 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (pp. 1525-1530).
- Renz, A., & Hilbig, R. (2020). Prerequisites for artificial intelligence in further education: Identification of drivers, barriers, and business models of educational technology companies. International Journal of Educational Technology in Higher Education, 17(1), Article 14.
- Rogers, E.M. (2003). Diffusion of innovations (5th ed.). New York: The Free Press.
- Saúde, S., Barros, J. P., & Almeida, I. (2024). Impacts of generative artificial intelligence in higher education: Research trends and students’ perceptions. Social Sciences, 13(8), Article 410.
- Schemmer, M., Kuehl, N., Benz, C., Bartos, A., & Satzger, G. (2023). Appropriate reliance on AI advice: Conceptualization and the effect of explanations. Proceedings of the 28th International Conference on Intelligent User Interfaces, 410-22.
- Schön, E.M., Neumann, M., Hofmann-Stölting, C., Baeza-Yates, R., & Rauschenberger, M. (2023). How are AI assistants changing higher education? Frontiers in Computer Science, 5, Article 1208550.
- Segovia-García, N. (2024). Optimización de la atención estudiantil: una revisión del uso de chatbots de IA en la educación superior [Optimizing student support: A review of the use of AI chatbots in higher education]. European Public and Social Innovation Review, 9, 1-20. (In Spanish).
- Seo, K., Tang, J., Roll, I., Fels, S., & Yoon, D. (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. International Journal of Educational Technology in Higher Education, 18(54), Article 54.
- Shahzad, M.F., Xu, S., & Zahid, H. (2024). Exploring the impact of generative AI-based technologies on learning performance through self-efficacy, fairness & ethics, creativity, and trust in higher education. Education and Information Technologies.
- Shaw, D. E. (1987). On the range of applicability of an artificial intelligence machine. Artificial Intelligence, 32(2), 151-172.
- Singh, H., & Singh, A. (2023). ChatGPT: Systematic review, applications, and agenda for multidisciplinary research. Journal of Chinese Economic and Business Studies, 21(2), 193-212.
- Slimi, Z. (2021). The impact of AI implementation in higher education on educational process future: A systematic review. Research Square.
- Smerdon, D. (2024). AI in essay-based assessment: Student adoption, usage, and performance. Computers and Education: Artificial Intelligence, 7, Article 100288.
- Stahl, B. C. (2023). Embedding responsibility in intelligent systems: From AI ethics to responsible AI ecosystems. Scientific Reports, 13, Article 7586.
- van As, J., & Cooke, R. (2024). Immersive virtual community engagement: Unleashing the potential of AI avatars and virtual reality in education to enhance learning excellence. In K. Chee & M. Sanmugam (Eds.), Integrating cutting-edge technology into the classroom (pp. 162-183). IGI Global Scientific Publishing.
- Williams, N. (1992). The artificial intelligence applications to learning programme. Computers & Education, 18(1-3), 101-107.
- Wirtz, B. W., Weyerer, J. C., & Kehl, I. (2022). Governance of artificial intelligence: A risk and guideline-based integrative framework. Government Information Quarterly, 39(4), Article 101685.
- Xu, Y., Liu, X., Cao, X., Huang, C., Liu, E., Qian, S., Liu, X., Wu, Y., Dong, F., Qiu, C-W., Qiu, J., Hua, K., Su, W., Wu, J., Xu, H., Han, Y., Fu, C., Yin, Z., Liu, M., … Zhang, J. (2021). Artificial intelligence: A powerful paradigm for scientific research. The Innovation, 2(4).
- Zagoruiko, I., & Petkova, L. (2022). Model of world technological and economic efficiency frontiers. Journal of International Studies, 15(2), 174-198.
- Zawacki-Richter, O., Marín, V.I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education 16(1), Article 39.