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The Research Future of Management Accounting Based on Data-Based Systems

Document Type : Original Research Manuscripts

Authors

1 1. Ph.D. Student in Accounting, Department of Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran.

2 Assistant Professor of Accounting, Department of Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran

3 Associate Professor of Accounting, Department of Accounting, Qazvin Branch, Islamic Azad University, Qazvin, Iran

4 Associate Professor of Industrial Management, Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Abstract

The purpose of this research was to explore the future of management accounting, specifically focusing on data-based systems, using a structural analysis approach. The study aimed to provide insights into the field by projecting trends and developments up to the year 2030.
This research is exploratory in terms of its purpose and application. The participants were 20 experts in the accounting profession who were selected using purposive judgmental sampling. The data processing involved the use of the structural interaction analysis method and the MICMAC software. According to the findings of the structural analysis of business globalization, the key drivers include the convergence of accounting and business, the relationship between industry and university in management accounting, the increase of academic experts, and the rapid pace of technological and business intelligence changes. They have an impact on improving the quality and quantity of companies' profits in the future of the management accounting profession by 2030. The results show that these drivers play a crucial and highly effective role in enhancing the future profitability of companies in various sectors within the management accounting profession.
This finding can be valuable for management accounting policymakers to anticipate future developments in this profession and avoid being caught off guard.

Keywords

Main Subjects

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International Journal of Knowledge Processing Studies
Volume 4, Issue 1
December 2023
Pages 91-106
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History
  • Receive Date: 27 March 2023
  • Revise Date: 04 April 2023
  • Accept Date: 27 June 2023
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