Management Modeling of Financial Reporting in the Cloud Accounting Context: A Text Mining-Based Approach Towards Sustainable Development

Background and Objectives: Advances in information technology and the widespread use of cloud computing have significantly transformed accounting systems and financial reporting, giving rise to cloud accounting. By enabling real-time data processing, online accessibility, cost efficiency, and greater transparency, cloud accounting enhances the quality of financial reporting. However, despite its increasing adoption, existing studies lack a comprehensive conceptual framework that clearly defines its key dimensions in financial reporting. Moreover, prior research has largely relied on quantitative methods, with limited use of qualitative data-driven approaches such as text mining. Therefore, this study aims to develop a comprehensive conceptual framework for cloud accounting in financial reporting through a systematic literature review and text mining analysis.
Materials and Methods: This applied study employs a qualitative, exploratory design. Using the PRISMA protocol, a systematic literature review was conducted, initially identifying over 5,000 articles (2015–2025) from major databases such as Scopus, Web of Science, Springer, and Google Scholar. After removing duplicates and screening titles, abstracts, and full texts, 96 eligible English-language articles related to cloud accounting and financial reporting were selected for analysis. In the second stage, a text mining analysis was performed using RapidMiner software. The selected texts were subjected to a preprocessing procedure comprising normalization, tokenization, stop-word removal, and stemming. Subsequently, term weighting was carried out using the TF–IDF method to identify the most informative and representative keywords. Based on a weighting threshold of 0.019, key terms were extracted and transformed into a vector space model. Document clustering was then conducted using the K-means algorithm. The optimal number of clusters was determined through visual inspection of clustering outputs, and five clusters (K = 5) were identified as the most appropriate solution. To enhance the robustness of the results, the algorithm was executed with ten repeated runs (Max Runs = 10). Cluster quality was evaluated using intra-cluster distance measures and the Davies–Bouldin index, confirming satisfactory internal cohesion and clear separation among clusters.
Results: The findings of the study revealed five core dimensions of cloud accounting in financial reporting. These dimensions include: (1) Foundations and infrastructure of cloud-based accounting systems, emphasizing information technology infrastructure, data security, accounting software, and integrated information systems; (2) Efficiency, performance, and financial reporting, focusing on improvements in timeliness, accuracy, transparency, and operational cost reduction in financial reporting processes; (3) Adoption of cloud accounting, sustainability, and financial outcomes, highlighting the relationship between cloud technology adoption, financial performance, profitability, and organizational sustainability; (4) Advanced accounting systems, artificial intelligence integration, and digital transformation, underscoring the role of emerging technologies such as artificial intelligence and cloud-based enterprise resource planning (cloud-based ERP) systems in reshaping accounting practices and the professional role of accountants; and (5) Governance, quality, and risk management, which stresses the importance of governance frameworks, internal controls, regulatory compliance, and information technology risk management in cloud-based environments.
Conclusion: Overall, the results demonstrate that the application of text mining techniques significantly reduces researcher subjectivity and enables a systematic, comprehensive, and data-driven identification of emerging dimensions of cloud accounting. The proposed conceptual framework provides valuable theoretical and practical insights for financial managers, accountants, auditors, and regulatory bodies seeking to enhance financial reporting quality in cloud-based settings. Moreover, the findings offer a solid foundation for future empirical research aimed at testing the identified dimensions and examining their effects on financial reporting quality, transparency, and organizational sustainability.