Research on the correlation between information technology applications driven by digital transformation and enterprise business process optimization and management model innovation

Bin Zhang (), Xiuzhi Han (), Jing Yang (), Nelli Akylbekova (), Biibosunov Bolotbek Ilyasovich () and Saida Ibraimova ()

Edelweiss Applied Science and Technology, 2025, vol. 9, issue 8, 1413-1437

Abstract: This study examines the correlation between IT application maturity, Business Process Optimization (BPO), and Management Model Innovation (MMI) in the context of enterprise Digital Transformation (DT). Despite widespread DT adoption, organizations often treat BPO and MMI as separate outcomes, limiting strategic coherence. Using a quantitative-dominant mixed-methods approach, data were collected from 362 enterprises across manufacturing, finance, logistics, and healthcare sectors through structured surveys and KPI extractions from ERP/BPM systems. Partial Least Squares Structural Equation Modeling (PLS-SEM) and Multi-Group Analysis (MGA) were employed to test hypotheses, with process mining used for validation. Results reveal a strong direct effect of IT maturity on BPO (β = 0.69, p < 0.001) and a moderate direct effect on MMI (β = 0.31, p < 0.001), with BPO partially mediating the relationship (indirect β = 0.28, p < 0.001). Sector-wise, manufacturing and finance showed stronger effects compared to healthcare and logistics. Large enterprises outperformed SMEs, attributed to greater digital capabilities and resources. Process mining confirmed significant post-DT improvements, including 19.7% cycle time reduction and 28.9% error rate reduction. This study offers a validated model linking digital capabilities to process and management innovation, emphasizing the importance of aligning IT adoption with operational excellence and organizational readiness in digital transformation initiatives.

Keywords: Business process optimization; Digital transformation; Information technology applications; Management model innovation; PLS-SEM; Multi-Group analysis; Process mining. (search for similar items in EconPapers)
Date: 2025
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