An Analytical Framework for Evaluating the Impact of Digital Transformation Technologies on Business Performance: A Natural Language Processing Approach

Document Type : Research Paper

Authors

1 Associate Prof., Department of Information Technology and Operations Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran.

2 Master of Information Technology Management, Advanced Information Systems, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran.

3 Prof., Department of Information Technology and Operations Management, Faculty of Management and Accounting, Allameh Tabataba'i University, Tehran, Iran.

Abstract

Extensive technological advancements have highlighted the importance of digital transformation in improving business performance. While prior research on this topic has been done in the information systems and business management domains, it has been limited to specific areas. Therefore, it is crucial to evaluate the impact of digital transformation comprehensively. This research aims to systematically identify critical themes, significant topics, main concepts, and trend priorities. The study involved the analysis of 474 research papers from 2015 to 2024 from reputable databases such as SCOPUS, Web of Science, and IEEE Xplore. First, thematic analysis identified the main themes and interpreted their relationships. Identified themes refer to technological changes at the operational and strategic levels through data analytics, digitalization, collaborative learning, and digital interaction. Realizing that digital transformation leads to value creation, improved service quality, customer experience, and long-term communication in digital ecosystems. These findings were related to dynamic capability theory concepts and compared with theory constructs like sensing, seizing, and transforming. Next, text mining techniques were used for deeper investigation, including word cloud, topic modeling (Latent Dirichlet Allocation), and text clustering (K-means). Findings were categorized into three perspectives: business, customer, and systemic, highlighting the influential role of digital technologies, particularly artificial intelligence (AI) capabilities. Moreover, trend analysis presented research priorities using VOSviewer. Finally, research innovation involved designing thematic networks and examining the relevance of significant topics as a research artifact with subtle differences compared to the conducted research. This novel approach provides five targeted propositions to audiences for future research.

Keywords

Main Subjects


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