Bibliometric Analysis of Accounting Literature on Artificial Intelligence (AI) Adoption in Organizational Functions
DOI:
https://doi.org/10.33003/fujafr-2024.v2i3.126.153-171Keywords:
Artificial Intelligence (AI), Co-Authorship, Keyword Co-occurrences, Bibliometric Analysis, Organizational FunctionAbstract
Artificial intelligence (AI) is a powerful technology with a high potentiality of transformative drive from traditional analog to digitalized organizational seamless decision processes efficiently and effectively. AI is an emerging area in organizational decision-making with limited number of studies across the globe. However, AI is now gaining considerable attention from the researcher, both at the local and international level. This study aims at providing a systematic review and biometric analysis on AI adoption in organizational functions using Google Scholar databases as the source of data. The study employs the steps of Prepare Reporting Items for Systematic Literature Review and Meta-Analysis Techniques PRISMA (2020) and bibliometric analysis techniques using VOS-View as a tool for analysis of publications performance over time with a view to determining the most influential articles, publication productivity, and direction of studies on AI Adoption in organizational functions for a period of ten years from 2015 to 2024. The analysis reveals that articles published in 2016 by Sage Journal recorded the highest citation of 2707, followed by MDPI Journal with total citations of 1922 in 2021, while Elsevier presents the lowest citation of 87 citations over the period of 10 years in the database used. These articles were written on more than 20 areas of application of AI in organizational functions.
References
Abidoye, R. B., & Chan, A. P. (2017). Critical review of hedonic pricing model application in property price appraisal: A case of Nigeria. International Journal of Sustainable Built Environment, 6(1), 250-259. DOI: https://doi.org/10.1016/j.ijsbe.2017.02.007
Abiodun, O. I., Jantan, A., Omolara, A. E., Dada, K. V., Umar, A. M., Linus, O. U., ... & Kiru, M. U. (2019). Comprehensive review of artificial neural network applications to pattern recognition. IEEE access, 7, 158820-158846. DOI: https://doi.org/10.1109/ACCESS.2019.2945545
Agbehadji, I. E., Awuzie, B. O., Ngowi, A. B., & Millham, R. C. (2020). Review of big data analytics, artificial intelligence and nature-inspired computing models towards accurate detection of COVID-19 pandemic cases and contact tracing. International Journal of Environmental Research and Public Health, 17(15), 5330. DOI: https://doi.org/10.3390/ijerph17155330
Allen, F., Gu, X., & Jagtiani, J. (2021). A survey of fintech research and policy discussion. Review of Corporate Finance, 1, 259-339. DOI: https://doi.org/10.1561/114.00000007
Almudhaiyan, T., Alhamzah, A., AlShareef, M., Alrasheed, A., Jaffar, R., Alluhidan, A., ... & Aldebasi, T. (2020). The prevalence of refractive errors among Saudi adults in Riyadh, Saudi Arabia. Saudi Journal of Ophthalmology, 34(1), 30-34. DOI: https://doi.org/10.4103/1319-4534.301297
Aman, A. H. M., Hassan, W. H., Sameen, S., Attarbashi, Z. S., Alizadeh, M., & Latiff, L. A. (2021). IoMT amid COVID-19 pandemic: Application, architecture, technology, and security. Journal of Network and Computer Applications, 174, 102886.
Aman, A. H. M., Hassan, W. H., Sameen, S., Attarbashi, Z. S., Alizadeh, M., & Latiff, L. A. (2021). IoMT amid COVID-19 pandemic: Application, architecture, technology, and security. Journal of Network and Computer Applications, 174, 102886. DOI: https://doi.org/10.1016/j.jnca.2020.102886
Åström, K. J. (2002). Control system design lecture notes for me 155a. Department of Mechanical and Environmental Engineering University of California Santa Barbara, 333.
Attaran, M., & Deb, P. (2018). Machine learning: the new'big thing'for competitive advantage. International Journal of Knowledge Engineering and Data Mining, 5(4), 277-305. DOI: https://doi.org/10.1504/IJKEDM.2018.095523
Barrett, M., Boyne, J., Brandts, J., Brunner-La Rocca, H. P., De Maesschalck, L., De Wit, K., ... & Zippel-Schultz, B. (2019). Artificial intelligence supported patient self-care in chronic heart failure: a paradigm shifts from reactive to predictive, preventive and personalised care. Epma Journal, 10, 445-464. DOI: https://doi.org/10.1007/s13167-019-00188-9
Batistič, S., Černe, M., & Vogel, B. (2017). Just how multi-level is leadership research? A document co-citation analysis 1980–2013 on leadership constructs and outcomes. The Leadership Quarterly, 28(1), 86-103. DOI: https://doi.org/10.1016/j.leaqua.2016.10.007
Benckendorff, P., & Zehrer, A. (2013). A network analysis of tourism research. Annals of tourism research, 43, 121-149. DOI: https://doi.org/10.1016/j.annals.2013.04.005
Bichteler, J., & Eaton III, E. A. (1980). The combined use of bibliographic coupling and cocitation for document retrieval. Journal of the American Society for Information Science, 31(4), 278-282. DOI: https://doi.org/10.1002/asi.4630310408
Budhwar, P., Chowdhury, S., Wood, G., Aguinis, H., Bamber, G. J., Beltran, J. R., ... & Varma, A. (2023). Human resource management in the age of generative artificial intelligence: Perspectives and research directions on ChatGPT. Human Resource Management Journal, 33(3), 606-659. DOI: https://doi.org/10.1111/1748-8583.12524
Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big data & society, 3(1), 2053951715622512. DOI: https://doi.org/10.1177/2053951715622512
Callon, M., Courtial, J. P., & Laville, F. (1991). Co-word analysis as a tool for describing the network of interactions between basic and technological research: The case of polymer chemsitry. Scientometrics, 22, 155-205. DOI: https://doi.org/10.1007/BF02019280
Chaka, C. (2023). Fourth industrial revolution—a review of applications, prospects, and challenges for artificial intelligence, robotics and blockchain in higher education. Research and Practice in Technology Enhanced Learning, 18, 002-002. DOI: https://doi.org/10.58459/rptel.2023.18002
Chiluwa, I. E., & Samoilenko, S. A. (Eds.). (2019). Handbook of research on deception, fake news, and misinformation online. IGI Global. DOI: https://doi.org/10.4018/978-1-5225-8535-0
Cobo, A., & Diaz, C. (2011). Clinical application of oocyte vitrification: a systematic review and meta-analysis of randomized controlled trials. Fertility and sterility, 96(2), 277-285. DOI: https://doi.org/10.1016/j.fertnstert.2011.06.030
Cohen, G. Informed Consent and Medical Artificial Intelligence: What to Tell the Patient?’(2020). Georgetown Law Journal, 108, 1425-1451. DOI: https://doi.org/10.2139/ssrn.3529576
Culnan, M. J. (1987). Mapping the intellectual structure of MIS, 1980-1985: A co-citation analysis. Mis Quarterly, 341-353. DOI: https://doi.org/10.2307/248680
Debrah, C., Chan, A. P., & Darko, A. (2022). Artificial intelligence in green building. Automation in Construction, 137, 104192. DOI: https://doi.org/10.1016/j.autcon.2022.104192
Ding, Y. S., Fowler, J. S., Logan, J., Wang, G. J., Telang, F., Garza, V., ... & Vocci, F. (2004). 6-[18 F] Fluoro-A-85380, a new PET tracer for the nicotinic acetylcholine receptor: studies in the human brain and in vivo demonstration of specific binding in white matter. Synapse, 53(3), 184-189. DOI: https://doi.org/10.1002/syn.20051
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines? Journal of business research, 133, 285-296. DOI: https://doi.org/10.1016/j.jbusres.2021.04.070
Eboigbe, E. O., Farayola, O. A., Olatoye, F. O., Nnabugwu, O. C., & Daraojimba, C. (2023). Business intelligence transformation through AI and data analytics. Engineering Science & Technology Journal, 4(5), 285-307. DOI: https://doi.org/10.51594/estj.v4i5.616
Farzaneh, H., Malehmirchegini, L., Bejan, A., Afolabi, T., Mulumba, A., & Daka, P. P. (2021). Artificial intelligence evolution in smart buildings for energy efficiency. Applied Sciences, 11(2), 763. DOI: https://doi.org/10.3390/app11020763
Ferrero Bermejo, J., Gómez Fernández, J. F., Olivencia Polo, F., & Crespo Márquez, A. (2019). A review of the use of artificial neural network models for energy and reliability prediction. A study of the solar PV, hydraulic and wind energy sources. Applied Sciences, 9(9), 1844. DOI: https://doi.org/10.3390/app9091844
Goodell, J. W., Kumar, S., Lim, W. M., & Pattnaik, D. (2021). Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis. Journal of Behavioral and Experimental Finance, 32, 100577. DOI: https://doi.org/10.1016/j.jbef.2021.100577
Guembe, B., Azeta, A., Misra, S., Osamor, V. C., Fernandez-Sanz, L., & Pospelova, V. (2022). The emerging threat of ai-driven cyber-attacks: A review. Applied Artificial Intelligence, 36(1), 2037254. DOI: https://doi.org/10.1080/08839514.2022.2037254
Hanga, K. M., & Kovalchuk, Y. (2019). Machine learning and multi-agent systems in oil and gas industry applications: A survey. Computer Science Review, 34, 100191. DOI: https://doi.org/10.1016/j.cosrev.2019.08.002
Hasan, A. R. (2021). Artificial Intelligence (AI) in accounting & auditing: A Literature review. Open Journal of Business and Management, 10(1), 440-465. DOI: https://doi.org/10.4236/ojbm.2022.101026
Hassan, A. O., Ewuga, S. K., Abdul, A. A., Abrahams, T. O., Oladeinde, M., & Dawodu, S. O. (2024). Cybersecurity in banking: a global perspective with a focus on Nigerian practices. Computer Science & IT Research Journal, 5(1), 41-59. DOI: https://doi.org/10.51594/csitrj.v5i1.701
Hassani, H., Huang, X., & Silva, E. (2018). Digitalization and big data mining in banking. Big Data and Cognitive Computing, 2 (3), 1-13. DOI: https://doi.org/10.3390/bdcc2030018
Hentzen, J. K., Hoffmann, A., Dolan, R., & Pala, E. (2022). Artificial intelligence in customer-facing financial services: a systematic literature review and agenda for future research. International Journal of Bank Marketing, 40(6), 1299-1336. DOI: https://doi.org/10.1108/IJBM-09-2021-0417
Huang, J., Saleh, S., & Liu, Y. (2021). A review on artificial intelligence in education. Academic Journal of Interdisciplinary Studies, 10(3). DOI: https://doi.org/10.36941/ajis-2021-0077
Hughes, K., Bellis, M. A., Hardcastle, K. A., Sethi, D., Butchart, A., Mikton, C., ... & Dunne, M. P. (2017). The effect of multiple adverse childhood experiences on health: a systematic review and meta-analysis. The Lancet public health, 2(8), e356-e366. DOI: https://doi.org/10.1016/S2468-2667(17)30118-4
Khang, A. (Ed.). (2023). AI and IoT-based technologies for precision medicine. IGI Global. DOI: https://doi.org/10.4018/979-8-3693-0876-9
Latif, S., Usman, M., Manzoor, S., Iqbal, W., Qadir, J., Tyson, G., ... & Crowcroft, J. (2020). Leveraging data science to combat COVID-19: A comprehensive review. IEEE Transactions on Artificial Intelligence, 1(1), 85-103. DOI: https://doi.org/10.1109/TAI.2020.3020521
Lee, C. S., & Tajudeen, F. P. (2020). Usage and impact of artificial intelligence on accounting: Evidence from Malaysian organisations. Asian Journal of Business and Accounting, 13(1). DOI: https://doi.org/10.22452/ajba.vol13no1.8
Lee, M. C. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model. Computers & education, 54(2), 506-516. DOI: https://doi.org/10.1016/j.compedu.2009.09.002
Lehner, O. M., Ittonen, K., Silvola, H., Ström, E., & Wührleitner, A. (2022). Artificial intelligence based decision-making in accounting and auditing: ethical challenges and normative thinking. Accounting, Auditing & Accountability Journal, 35(9), 109-135. DOI: https://doi.org/10.1108/AAAJ-09-2020-4934
Leydesdorff, L. (1997). Why words and co‐words cannot map the development of the sciences. Journal of the American society for information science, 48(5), 418-427. DOI: https://doi.org/10.1002/(SICI)1097-4571(199705)48:5<418::AID-ASI4>3.0.CO;2-Y
Mhlanga, D. (2020). Industry 4.0 in finance: the impact of artificial intelligence (ai) on digital financial inclusion. International Journal of Financial Studies, 8(3), 45. DOI: https://doi.org/10.3390/ijfs8030045
Mhlanga, D. (2021). Financial inclusion in emerging economies: The application of machine learning and artificial intelligence in credit risk assessment. International journal of financial studies, 9(3), 39. DOI: https://doi.org/10.3390/ijfs9030039
Mogaji, E., & Nguyen, N. P. (2022). Managers' understanding of artificial intelligence in relation to marketing financial services: insights from a cross-country study. International Journal of Bank Marketing, 40(6), 1272-1298. DOI: https://doi.org/10.1108/IJBM-09-2021-0440
Mogaji, E., Soetan, T. O., & Kieu, T. A. (2020). The implications of artificial intelligence on the digital marketing of financial services to vulnerable customers. Australasian Marketing Journal, j-ausmj. DOI: https://doi.org/10.1016/j.ausmj.2020.05.003
Mustapha, U. F., Alhassan, A. W., Jiang, D. N., & Li, G. L. (2021). Sustainable aquaculture development: a review on the roles of cloud computing, internet of things and artificial intelligence (CIA). Reviews in Aquaculture, 13(4), 2076-2091. DOI: https://doi.org/10.1111/raq.12559
Ndung’u, N., & Signé, L. (2020). The Fourth Industrial Revolution and digitization will transform Africa into a global powerhouse. Foresight Africa Report, 5(1), 1-177.
Odoh, L. C., Echefu, S. C., Ugwuanyi, U. B., & Chukwuani, N. V. (2018). Effect of artificial intelligence on the performance of accounting operations among accounting firms in South East Nigeria. Asian Journal of Economics, Business and Accounting, 7(2), 1-11. DOI: https://doi.org/10.9734/AJEBA/2018/41641
Ooi, K. B., Tan, G. W. H., Al-Emran, M., Al-Sharafi, M. A., Capatina, A., Chakraborty, A., ... & Wong, L. (2023). The potential of generative artificial intelligence across disciplines: Perspectives and future directions. Journal of Computer Information Systems, 1-32. DOI: https://doi.org/10.1080/08874417.2023.2261010
Owan, V. J., Abang, K. B., Idika, D. O., Etta, E. O., & Bassey, B. A. (2023). Exploring the potential of artificial intelligence tools in educational measurement and assessment. Eurasia Journal of Mathematics, Science and Technology Education, 19(8), em2307. DOI: https://doi.org/10.29333/ejmste/13428
Owoc, M. L., Sawicka, A., & Weichbroth, P. (2019, August). Artificial intelligence technologies in education: benefits, challenges and strategies of implementation. In IFIP International Workshop on Artificial Intelligence for Knowledge Management (pp. 37-58). Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-85001-2_4
Pasadeos, Y., Phelps, J., & Kim, B. H. (1998). Disciplinary impact of advertising scholars: Temporal comparisons of influential authors, works and research networks. Journal of Advertising, 27(4), 53-70. DOI: https://doi.org/10.1080/00913367.1998.10673569
Pritchard, W. G. (1970). Solitary waves in rotating fluids. Journal of Fluid Mechanics, 42(1), 61-83. DOI: https://doi.org/10.1017/S0022112070001076
Renda, A. (2019). Artificial Intelligence. Ethics, governance and policy challenges. CEPS Centre for European Policy Studies.
Satish, T., Cummings, M. J., Wolf, A., & O’Donnel, M. A. X. (2022). Investigating Heterogeneity of Treatment Effect for Convalescent Plasma in Severe Covid-19: Secondary Analysis of A Randomized Controlled Trial. Chest, 162(4), A679. DOI: https://doi.org/10.1016/j.chest.2022.08.532
Small, H. (1973). Co‐citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for information Science, 24(4), 265-269. DOI: https://doi.org/10.1002/asi.4630240406
Soetan, T. O., Mogaji, E., & Nguyen, N. P. (2021). Financial services experience and consumption in Nigeria. Journal of Services Marketing, 35(7), 947-961. DOI: https://doi.org/10.1108/JSM-07-2020-0280
Strusani, D., & Houngbonon, G. V. (2019). The role of artificial intelligence in supporting development in emerging markets. International Finance Corporation, Washington, DC. DOI: https://doi.org/10.1596/32365
Van Eck, N. J., & Waltman, L. (2014). Visualizing bibliometric networks. In Measuring scholarly impact: Methods and practice (pp. 285-320). Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-10377-8_13
Van Raan, A. F. (2005). For your citations only? Hot topics in bibliometric analysis. Measurement: interdisciplinary research and perspectives, 3(1), 50-62. DOI: https://doi.org/10.1207/s15366359mea0301_7
Varma, P., Nijjer, S., Sood, K., Grima, S., & Rupeika-Apoga, R. (2022). Thematic analysis of financial technology (Fintech) influence on the banking industry. Risks, 10(10), 186. DOI: https://doi.org/10.3390/risks10100186
Wang, V., Nnaji, H., & Jung, J. (2020). Internet banking in Nigeria: Cyber security breaches, practices and capability. International Journal of Law, Crime and Justice, 62, 100415. DOI: https://doi.org/10.1016/j.ijlcj.2020.100415
Whittaker, R. J., Bush, M. B., & Richards, K. J. E. M. (1989). Plant recolonization and vegetation succession on the Krakatau Islands, Indonesia. Ecological Monographs, 59(2), 59-123. DOI: https://doi.org/10.2307/2937282
Wiafe, I., Koranteng, F. N., Obeng, E. N., Assyne, N., Wiafe, A., & Gulliver, S. R. (2020). Artificial intelligence for cybersecurity: a systematic mapping of literature. IEEE Access, 8, 146598-146612. DOI: https://doi.org/10.1109/ACCESS.2020.3013145
Yaacoub, J. P. A., Noura, H. N., Salman, O., & Chehab, A. (2022). Robotics cyber security: Vulnerabilities, attacks, countermeasures, and recommendations. International Journal of Information Security, 21(1), 115-158. DOI: https://doi.org/10.1007/s10207-021-00545-8
Yasir, A., Ahmad, A., Abbas, S., Inairat, M., Al-Kassem, A. H., & Rasool, A. (2022, February). How Artificial Intelligence Is Promoting Financial Inclusion? A Study On Barriers of Financial Inclusion. In 2022 International Conference on Business Analytics for Technology and Security (ICBATS) (pp. 1-6). IEEE. DOI: https://doi.org/10.1109/ICBATS54253.2022.9759038
Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational research methods, 18(3), 429-472. DOI: https://doi.org/10.1177/1094428114562629
Downloads
Published
Issue
Section
License
Copyright (c) 2024 FUDMA Journal of Accounting and Finance Research [FUJAFR]
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The FUDMA Journal of Accounting and Finance Research (FUJAFR) operates a copyright policy that ensures a balance between author rights and wide dissemination of scholarly work.
1. Author Copyright Retention
Authors retain full copyright of their published work without restriction. Submission to FUJAFR does not transfer ownership of copyright to the journal.
2. License to Publish
By submitting a manuscript and upon acceptance, authors grant FUJAFR:
- The right to publish, reproduce, and distribute the article
- The right to identify itself as the original publisher of the work
This grant is non-exclusive, meaning authors are free to reuse their work in other contexts, provided proper acknowledgment of the original publication in FUJAFR is made.
3. Licensing of Published Content
All articles are published under the:
Creative Commons Attribution-NonCommercial License (CC BY-NC 4.0)
Under this license:
- Users may share and adapt the work for non-commercial purposes only
- Proper attribution to the author(s) and the journal is required
- Any commercial use requires explicit permission from the copyright holder
4. Author Reuse Rights
Authors are permitted to:
- Archive their published articles in institutional repositories or personal websites
- Share their work for educational and research purposes
- Reuse portions of their work in future publications (e.g., books or other articles), provided proper citation of the original publication is included
5. Third-Party Content
Authors are responsible for obtaining permission to use any third-party copyrighted material (e.g., images, tables, datasets) included in their manuscripts. Proper acknowledgment must be provided where required.
6. Attribution Requirement
All users of FUJAFR content must provide appropriate credit, including:
- Author name(s)
- Article title
- Journal name (FUJAFR)
- Year of publication
