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The digital economy has fundamentally altered the foundations of competitive strategy, shifting firms from reliance on scarce physical and intangible resources toward data-rich environments where advantage stems from continuous data accumulation, analytics, and platform-mediated interactions. This theory-development article synthesizes recent literature on digital platforms, big data analytics, and ecosystem dynamics to propose new logics of competitive advantage characterized by speed, scale, learning, and connectivity. Traditional resource-based and positioning views are transformed as firms leverage data as a generative resource, platforms as coordination mechanisms, and algorithms for real-time adaptation. The article identifies key mechanisms driving this shift: data-driven resource reconfiguration, network effects amplifying scale advantages, algorithmic competition enabling dynamic strategic adjustment, and ecosystem positioning fostering connectivity. Five theoretical propositions articulate these relationships, culminating in a conceptual model illustrating the evolutionary trajectory from traditional to data-driven strategies. By highlighting feedback loops of continuous learning and adaptation, the framework explains how firms sustain advantage in volatile, data-intensive markets. Contributions include a reconceptualization of competitive logics in the digital era and implications for strategic management in platform-dominated ecosystems.

Firms have invested heavily in digital transformation through cloud infrastructure, process digitisation, data platforms, automation, and digitally enabled customer interfaces. Yet many organisations discover that becoming more digital does not automatically produce durable competitive advantage, stronger margins, or defensible market positions. The central problem is that digital transformation is often treated as a strategic endpoint rather than as a foundation for deeper business model change. Firms may modernise systems, accelerate operations, and improve data visibility while leaving their revenue logic, value proposition, customer relationship, and ecosystem role largely unchanged. This perspective argues that digital transformation becomes strategically meaningful only when it triggers business model reinvention. The article focuses on three critical dimensions of post-transformation business models: revenue logic, customer data as a strategic resource, and ecosystem positioning. The article develops an evidence-based perspective using peer-reviewed research on business model innovation, digital transformation, platform strategy, data-driven innovation, and ecosystem competition. It does not present new empirical data; instead, it offers a critical synthesis and strategic argument for managers and scholars. The perspective concludes that the central managerial challenge is no longer simply how to become digital, but how to reinvent the business after digital foundations are in place. Firms that fail to make this transition risk becoming digitally efficient but strategically stagnant.