Abstract
Purpose: This study investigates how digital transformation contributes to organizational competitive intelligence by examining the relationships among Information Technology (IT) application maturity, Business Process Optimization (BPO), and Management Model Innovation (MMI). The objective is to explain how digital capabilities evolve from operational improvements into decision-relevant intelligence that supports strategic management.
Methodology/approach: A quantitative-dominant mixed-methods design was adopted, combining survey data and objective system-level performance indicators from 362 firms operating in manufacturing, finance, healthcare, and logistics sectors. Partial Least Squares Structural Equation Modeling (PLS-SEM), multi-group analysis, and mediation testing were employed to assess causal relationships. Process mining techniques were used to validate operational performance improvements based on ERP and BPM system data.
Originality/Relevance: The study advances digital transformation research by explicitly conceptualizing it as a competitive intelligence capability rather than a purely technological or efficiency-oriented phenomenon. By integrating IT maturity, process optimization, and management innovation within a unified analytical framework, the research addresses critical gaps in empirical and methodological literature.
Key findings: Results indicate that IT application maturity has a strong positive effect on business process optimization and a moderate direct effect on management model innovation. Business process optimization partially mediates this relationship, confirming that structured and traceable processes are central to transforming digital capabilities into managerial intelligence. Sectoral differences were also identified.
Theoretical/methodological contributions: The study provides an empirically validated framework linking digital transformation to competitive intelligence through sequential capability building. Methodologically, it strengthens rigor by integrating PLS-SEM, multi-group analysis, and process mining to bridge operational data with strategic decision-making.
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