Accounting Information Systems: A Bibliometric Analysis of Research Domains and Methods (2000–2026)
DOI:
https://doi.org/10.58812/wsaf.v4i01.2752Keywords:
Career Adaptability, Bibliometric Analysis, Research Trends, Career DevelopmentAbstract
This study aims to map the intellectual structure, thematic evolution, and research trends in career adaptability and related domains through a comprehensive bibliometric analysis. Data were collected from the Scopus database, covering publications from 2000 to 2026, and analyzed using VOSviewer to generate co-occurrence, overlay, and density visualizations. The findings reveal that career adaptability has emerged as a central and integrative concept, connecting key research domains such as psychological factors, career guidance, employability, and educational systems. The network analysis identifies several major clusters, reflecting the multidisciplinary nature of the field, while the overlay visualization indicates a clear shift from early theoretical foundations—such as self-efficacy and career construction—toward more applied themes including employment readiness, professional development, and learning systems. Additionally, the density analysis highlights a strong concentration of research around core topics, alongside emerging but underexplored areas, particularly in the integration of digital technologies and innovative learning environments. The results suggest that the field is evolving toward a more practical and outcome-oriented direction, driven by global labor market changes and technological advancements. This study contributes by providing a systematic overview of research domains and methodological trends, offering valuable insights for scholars and practitioners, and identifying future research opportunities to enhance the relevance and impact of career development studies in a rapidly changing world.
References
[1] M. Z. K. Md Zillul Karim, “Accounting Information System Quality and Management Information Systems Integration: A Pathway to Enhanced Financial Risk Management,” Account. Inf. Syst. Qual. Manag. Inf. Syst. Integr. A Pathw. to Enhanc. Financ. Risk Manag., vol. 3, no. 1, pp. 128–142, 2025.
[2] H. Balicka, “Digital technologies in the accounting information system supporting decision-making processes,” Zesz. Nauk. Organ. i Zarządzanie/Politechnika Śląska, 2023.
[3] A. P. Noviyanti, “The Evolution of Accounting Information Systems: Recent Trends and Future Directions,” Account. Res. J., vol. 1, no. 1, pp. 24–38, 2025.
[4] A. Monteiro and C. Cepêda, “Accounting information systems: scientific production and trends in research,” Systems, vol. 9, no. 3, p. 67, 2021.
[5] N. Donthu, S. Kumar, D. Mukherjee, N. Pandey, and W. M. Lim, “How to conduct a bibliometric analysis: An overview and guidelines,” J. Bus. Res., vol. 133, pp. 285–296, 2021.
[6] V. Venkatesh and F. D. Davis, “A theoretical extension of the technology acceptance model: Four longitudinal field studies,” Manage. Sci., vol. 46, no. 2, pp. 186–204, 2000.
[7] G. Vial, “Understanding digital transformation: A review and a research agenda,” Manag. Digit. Transform., pp. 13–66, 2021.
[8] M. Schmidt, S. A. J. Schmidt, J. L. Sandegaard, V. Ehrenstein, L. Pedersen, and H. T. Sørensen, “The Danish National Patient Registry: a review of content, data quality, and research potential,” Clin. Epidemiol., pp. 449–490, 2015.
[9] N. K. Malhotra, S. S. Kim, and A. Patil, “Common method variance in IS research: A comparison of alternative approaches and a reanalysis of past research,” Manage. Sci., vol. 52, no. 12, pp. 1865–1883, 2006.
[10] D. C. Donato, J. B. Kauffman, D. Murdiyarso, S. Kurnianto, M. Stidham, and M. Kanninen, “Mangroves among the most carbon-rich forests in the tropics,” Nat. Geosci., vol. 4, no. 5, pp. 293–297, 2011.
[11] J.-M. Raimond, M. Brune, and S. Haroche, “Manipulating quantum entanglement with atoms and photons in a cavity,” Rev. Mod. Phys., vol. 73, no. 3, p. 565, 2001.
[12] S. Whitmee et al., “Safeguarding human health in the Anthropocene epoch: report of The Rockefeller Foundation–Lancet Commission on planetary health,” Lancet, vol. 386, no. 10007, pp. 1973–2028, 2015.
[13] M. Usher and J. L. McClelland, “The time course of perceptual choice: the leaky, competing accumulator model.,” Psychol. Rev., vol. 108, no. 3, p. 550, 2001.
[14] H. K. Finucane et al., “Partitioning heritability by functional annotation using genome-wide association summary statistics,” Nat. Genet., vol. 47, no. 11, pp. 1228–1235, 2015.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Loso Judijanto

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.












