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The digital transformation of business has given rise to data-intensive firms in which competitive advantage and strategic positioning are no longer adequately explained by traditional resource-based or dynamic-capability theories. This conceptual theory-development paper reconceptualizes competitive advantage as the outcome of three interdependent mechanisms—digital infrastructure, algorithmic learning, and organizational data accumulation. Digital infrastructure functions as the enabling platform for seamless data flows; organizational data accumulation converts raw information into strategic capabilities; and algorithmic learning provides the adaptive engine that translates accumulated data into real-time repositioning. Synthesizing peer-reviewed studies published across leading outlets, the paper identifies critical theoretical gaps in isolated treatments of these constructs. Six formal propositions articulate causal, moderating, and synergistic relationships that produce a novel competitive logic unique to data-intensive environments. The resulting framework advances digital business theory by demonstrating how these elements collectively generate dynamic, ecosystem-level strategic positioning that traditional models cannot capture. Contributions extend to both scholarly understanding of data-driven strategy and managerial imperatives for sustained advantage in hyper-competitive markets.

In digitally networked economies, competitive advantage has shifted from firm-level resources to ecosystem-level orchestration, where platform leaders and complementors navigate interdependent value creation and capture. This theory-development article synthesizes recent advances in platform research to propose an evolutionary framework that explains how competitive advantage emerges, sustains, and erodes across three stages: firm-centric, platform-centric, and ecosystem-centric competition. Drawing on network effects, multi-sided market dynamics, and governance mechanisms, the framework highlights strategic positioning within platform hierarchies as the central driver of sustained advantage. Five core propositions articulate causal relationships between network intensity, complementor dependence, data-driven feedback loops, and value-capture asymmetry. The analysis reveals that platform leaders maintain dominance not through ownership of scarce resources but through selective promotion of complements, ecosystem governance, and orchestration of indirect network effects. Complementors, in turn, secure advantage by exploiting platform openness while mitigating lock-in risks. By integrating insights from peer-reviewed studies, this article advances a novel theory of ecosystem-driven competitive advantage that accounts for the dynamic interplay of technological affordances, strategic interdependence, and regulatory pressures. The resulting framework offers actionable guidance for platform leaders and complementors seeking to reposition within rapidly evolving digital markets.