Competitive Intelligence–Enabled Digital Transformation: A Sustainable Optimization Model with Evidence from China and Spain

Purpose: This study conceptualizes Competitive Intelligence (CI) as an intelligence-based decision governance capability that structures how organizations select, sequence, and govern digital transformation initiatives under conditions of competitive and sustainability uncertainty. Rather than modeling CI as a technological antecedent, the article positions CI as the decisional infrastructure through which digital transformation contributes to sustainable optimization outcomes. Methodology/approach: Drawing on Dynamic Capabilities Theory and the Resource-Based View, the study develops an intelligence-centered CI–DT–SOO framework and tests it using survey data from 200 firms in China and Spain. Partial Least Squares Structural Equation Modeling (PLS-SEM) and multi-group analysis are employed to examine intelligence-driven decision pathways across institutional contexts. Originality/Relevance: Responding directly to the epistemological standards of the Journal of Sustainable Competitive Intelligence, this study advances CI as a structured intelligence system that reduces information asymmetry and governs executive decision-making. It moves beyond techno-causal models by empirically demonstrating CI’s role as a strategic decision architecture rather than a descriptive scanning activity. Key findings: Results show that CI significantly structures digital transformation decisions, which in turn enable sustainable optimization outcomes. Digital transformation operates as a governed execution mechanism rather than an autonomous driver. Stronger intelligence-to-decision effects are observed in Chinese firms, highlighting institutional differences in intelligence utilization regimes. Theoretical/methodological contributions: The study integrates RBV and DCT perspectives to demonstrate that sustainable competitiveness emerges from the joint development of intelligence and digital capabilities. It contributes to theory and practice by presenting a sustainable optimization model applicable across different economic contexts and offering managerial implications for integrating CI into digital strategies and aligning DT with economic, environmental, and social goals.