Presenting a model for using business intelligence to improve the quality of management accounting reports based on grounded theory

Articles in Press

Document Type : Original Article

Authors
maryam صارمی 1
Ali Rahmani 2
mohammah mahmoodi 3
1 PhD Student, Department of Accounting, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
2 Professor, Department of Accounting, Faculty of Social Sciences & Economics, Alzahra University, Tehran, Iran
3 Associate Professor, Department of Accounting, Firoozkooh Branch, Islamic Azad university, Firoozkooh, Iran
10.22034/jmaak.2026.79457.4821
Abstract
Business Intelligence (BI), as one of the modern information management technologies, facilitates the generation of accurate, timely, and reliable information for managerial decision-making through the integration, processing, and analysis of organizational data. The present study was conducted with the aim of developing a model for the application of Business Intelligence to enhance the quality of management accounting reports. In terms of purpose, this research is applied, and in terms of methodology, it is qualitative and based on the Grounded Theory approach proposed by Strauss and Corbin. Data were collected through semi-structured interviews with ten experts in the fields of management accounting, business intelligence, and information technology, and were analyzed using open, axial, and selective coding. The findings revealed that the application of Business Intelligence is influenced by causal, contextual, and intervening conditions and, through strategies such as the implementation of Business Intelligence systems, data integration, the design of interactive managerial dashboards, the development of reporting standards, and the empowerment of human resources, leads to the enhancement of the quality of management accounting reports. Furthermore, the implementation of these strategies results in outcomes including increased reporting speed and accuracy, reduced human errors, improved managerial decision-making quality, enhanced financial information transparency, reduced operational and financial risks, the development of data-driven decision-making, and improved organizational financial performance. The proposed model can serve as a practical framework for the implementation of Business Intelligence systems and the enhancement of management accounting reporting quality, providing valuable guidance for managers and policymakers.
Business Intelligence, Management Accounting, Quality of Management Accounting Reports, Grounded Theory, Data-Driven Decision-Making.
Keywords
Business Intelligence
Management Accounting
Quality of Management Accounting Reports
Grounded Theory
Data-Driven Decision-Making
  1. انصاریان، رامین ، رهنمای رودپشتی، فریدون ، زمردیان، غلامرضا ، نیکومرام، هاشم. (1404). طراحی مدل هوش تجاری با لحاظ تصمیم گیری اخلاقی در کسب و کارهای حسابداری. دانش سرمایه گذاری 53. 575-596.
  2. سرور، ماکان، فرهادی عدل، آیدین. (1395). موفقیت در سیستم های هوش تجاری با رویکرد تحلیل سازمان . کنفرانس بین المللی پژوهش در علوم و تکنولوژی.
  3. شاهواروقی فراهانی، علیرضا ، پوربهرامی، بابک (1403). نقش میانجی سرمایه فکری حسابرسان در تاثیر هوش تجاری بر تجاری سازی موسسات حسابرسی. نشریه پژوهش های حسابرسی حرفه ای 17. 144-161.
  4. فانی، مجید. (1401). تاثیر هوش تجاری بر کیفیت تصمیم گیری کارآفرینان با متغیر میانجی کیفیت اطلاعات، کیفیت داده و نوآوری. پژوهشنامه مدیریت اجرایی 28. 229-253.
  5. Appelbaum, D., Kogan, A., Vasarhelyi, M. A., & Yan, Z. (2017). Impact of business analytics and enterprise systems on managerial accounting. International Journal of Accounting Information Systems, 25, 29–44. https://doi.org/10.1016/j.accinf.2017.03.003
  6. Burns, J., Quinn, M., Warren, L., & Oliveira, J. (2019). Management Accounting. McGraw-Hill Education.
  7. Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). An overview of business intelligence technology. Communications of the ACM, 54(8), 88–98. https://doi.org/10.1145/1978542.1978562
  8. Cockcroft, S., & Russell, M. (2018). Big Data opportunities for accounting and finance practice and research. Australian Accounting Review, 28(3), 323–333. https://doi.org/10.1111/auar.12218
  9. Divatia, A. S., Tikoria, J., & Lakdawala, S. (2021). Emerging trends and impact of business intelligence & analytics in organizations: Case studies from India. Business Information Review, 38(1), 40–52. https://doi.org/10.1177/0266382120969265
  10. Drury, C. (2021). Management and Cost Accounting (11th ed.). Cengage Learning.
  11. Elbashir, M. Z., Sutton, S. G., Mahama, H., & Arnold, V. (2021). Unravelling the integrated information systems and management control paradox: Enhancing dynamic capability through business intelligence. Accounting & Finance, 61(S1), 1775–1814. https://doi.org/10.1111/acfi.12644
  12. Hansen, D. R., Mowen, M. M., & Heitger, D. L. (2022). Cornerstones of Cost Management (5th ed.). Cengage Learning.
  13. Horngren, C. T., Datar, S. M., & Rajan, M. V. (2021). Cost Accounting: A Managerial Emphasis (17th ed.). Pearson.
  14. IFAC. (2023). International Good Practice Guidance: Technology and the Future of Finance. International Federation of Accountants.
  15. IFRS Foundation. (2023). Conceptual Framework for Financial Reporting. London: IFRS Foundation.
  16. Isik, O., Jones, M. C., & Sidorova, A. (2011). Business intelligence success and the role of BI capabilities. Intelligent Systems in Accounting, Finance and Management, 18(4), 161–176. https://doi.org/10.1002/isaf.329
  17. Kaplan, R. S., & Atkinson, A. A. (2015). Advanced Management Accounting (3rd ed.). Pearson.
  18. Oesterreich, T. D., & Teuteberg, F. (2019). The role of business analytics in management accounting. Journal of Accounting & Organizational Change, 15(2), 180–206. https://doi.org/10.1108/JAOC-10-2017-0097
  19. Paradza, D., & Daramola, O. (2021). Business intelligence and business value in organisations: A systematic literature review. Sustainability, 13(20), 11382. https://doi.org/10.3390/su132011382
  20. Quinn, M., Strauss, E., & Kristandl, G. (2018). The Routledge Companion to Accounting Information Systems. Routledge.
  21. Rikhardsson, P., & Yigitbasioglu, O. (2018). Business intelligence & analytics in management accounting research: Status and future focus. International Journal of Accounting Information Systems, 29, 37–58. https://doi.org/10.1016/j.accinf.2018.03.001
  22. Srivastava, G., Muneeswari, S., Venkataraman, R., Kavitha, V., & Parthiban, N. (2022). A review of the state of the art in business intelligence software. Enterprise Information Systems, 16(1). https://doi.org/10.1080/17517575.2021.1872107