A Model for Promoting Lean Accounting Based on Emerging Technologies Using an Interpretive Structural Modeling Approach
Keywords:
Lean Accounting, New Technologies, Artificial IntelligenceAbstract
Objective: This study aimed to develop a model for promoting lean accounting based on emerging technologies, with emphasis on blockchain infrastructure and artificial intelligence-driven smartization, using the interpretive structural modeling approach.
Methodology: This applied study adopted a mixed-method, exploratory, inductive, and cross-sectional design. The research population consisted of academic and professional experts familiar with lean accounting and emerging technologies. The sample included 15 experts selected through purposive and snowball sampling, and data collection continued until theoretical saturation was reached. The identified components were validated using expert judgment and content validity ratio. Interpretive Structural Modeling was then used to determine the hierarchical relationships among the components and to construct the final model. In addition, MICMAC analysis was applied to assess the driving power and dependence of the components.
Findings: The content validity results indicated that all identified components were confirmed, with a CVR value of 1, exceeding the acceptable threshold of 0.42. The ISM results showed that the lean accounting improvement components, including waste elimination, cost management, value creation, and continuous improvement, were positioned at the first level of the model and represented the most dependent outcomes. The artificial intelligence smartization components, including fraud and risk detection, advanced data analytics, intelligent automation, and prediction and optimization, were placed at the second level and functioned as intermediate factors affecting lean accounting improvement. The blockchain infrastructure components, including transparency and traceability, data security, smart contracts, and regulatory compliance, were positioned at the third and foundational level and were identified as the most influential drivers of the model. MICMAC analysis further showed that blockchain-related components were located in the driving area, AI-based components played an intermediary role, and lean accounting improvement components were classified as dependent variables.
Conclusion: The findings indicate that the promotion of lean accounting depends fundamentally on the establishment of technological infrastructure, particularly blockchain, while artificial intelligence serves as a mediating mechanism that converts data-driven, predictive, and automated capabilities into practical lean accounting outcomes such as waste reduction, cost control, value creation, and continuous improvement.
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Copyright (c) 1404 Mehrnaz Hakami, Donya Ahadian Pour Parvin, Seyedeh Atefeh Hosseini, Sina Abouei Mehrizi (Author)
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