Technology and digitalization in accounting and auditing

Journal articles

Engström, J., Öhman, P. och Tagesson, T. (2026) 
Scrutinising the scrutiny: How do professional auditors approach digital ventures in municipal value for money audits?
Financial Accountability & Management, Vol. 42, No 1, pp. 90-102.
Kontakt: peter.ohman@miun.se

Svanberg, J., Öhman, P., Samsten, I., Neidermeyer, P., Rana, T. och Danielson, M. (2025) 
Addressing the exception prioritization problem in continuous auditing systems with thresholding,
Intelligent Systems in Accounting, Finance and Management, Vol. 32, No. 4, e70022.
Kontakt: peter.ohman@miun.se

Hedback, D. (2025)
Identifying going concern audit opinions using supervised machine learning, 
Intelligent Systems in Accounting, Finance and Management, Vol. 32 No. 4, e70020.
Kontakt: dennis.hedback@miun.se

Rahman, Md. J., Rana, T., Xu, Y. och Öhman, P. (2024) 
Bridging BI and AI enhancing operational efficiency in the Chinese financial sector,
Journal of Global Information Management, Vol. 32, No.1, pp. 1-27.
Kontakt: peter.ohman@miun.se

Maiga, A.S., Nilsson, A. och Jacobs, F.A. (2013)
Extent of managerial IT use, learning routines, and firm performance: A structural equation modeling of their relationship,
International Journal of Accounting Information Systems, Vol. 14, No. 4, pp. 297-320.
Kontakt: peter.ohman@miun.se

Maiga, A.S. och Jacobs, F.A. (2011)
Selection bias and endogeneity issues on the relationship between information technology and firm performance,
Advances in Management Accounting, Vol. 19, pp. 109-131.
Kontakt: peter.ohman@miun.se

Books and book chapters

Predictive machine learning in assessing materiality: The global reporting initiative standard and beyond,
In Walker, T., Wendt, S., Goubran, S. och Schwartz, T. (eds.), Artificial intelligence for sustainability innovations in business and financial services,
Cham: Palgrave MacMillan, pp. 105-131.

Kronblad, C., Rahnert, K. och Öhman, P. (2023)
Revision i en digital kontext,
I Rahnert, K. och Öhman, P. (red.), Revision – i går, i dag, i morgon,
Stockholm: Ekerlids Förlag, sid. 354-376.

Rana, T., Svanberg, J., Öhman, P. och Lowe, A. (eds.), (2023)
Handbook of big data and analytics in accounting and auditing,
Singapore: Springer.

Rana, T., Svanberg, J., Öhman, P. och Lowe, A. (2023)
Introduction,
In Rana, T., Svanberg, J., Öhman, P. och Lowe, A. (eds.), Handbook of big data and analytics in accounting and auditing,
Singapore: Springer, pp. 1-13.

Svanberg, J., Ardeshiri , T., Samsten, I., Öhman, P. och Neidermeyer, P. (2023)
Prediction of controversies and estimation of ESG performance: An experimental investigation using machine learning,
In Rana, T., Svanberg, J., Öhman, P. och Lowe, A. (eds.), Handbook of big data and analytics in accounting and auditing,
Singapore: Springer, pp. 65-88.

Debate articles

Stockenstrand, A-K. och Henriksson, H. (2018)
Vad är bra redovisning i en digital och global tid?, Organisation & Samhälle, Årgång 5, Nr 2, sid. 10-16.

Master theses

Hedback, D. (2019)
Time’s up! The impact of multi-year accounting data on bankruptcy prediction.
Handledare: Darush Yazdanfar