Digital transformation has emerged as a central imperative for organizations navigating the data-driven economy, fundamentally reshaping strategy, technology adoption, and organizational structures. This systematic and integrative review synthesizes peer-reviewed scholarship to examine how firms conceptualize digital transformation, pursue strategic renewal, implement digital technologies, and manage ensuing organizational changes. The analysis reveals that digital transformation is not merely technological upgrading but a multifaceted process involving strategic intent, capability reconfiguration, and structural redesign—often accompanied by significant tensions between legacy routines and emergent data-driven logics. Key insights trace the evolution of digital transformation research from early strategic framing toward more nuanced explorations of adoption barriers, managerial role shifts, and adaptive outcomes. Strategic drivers emphasize alignment with dynamic capabilities, while technology adoption processes underscore the interplay between implementation and business model innovation. Organizational change manifests in redesigned processes, cultures, and governance systems, yet persistent barriers such as cultural inertia and capability erosion hinder progress. To integrate these fragmented streams, this review introduces the Integrative Digital Transformation Framework, which maps interconnections across thematic layers and offers a structured lens for orchestrating sustainable transformation. By tracing temporal evolution and identifying theoretical gaps, this synthesis advances management scholarship and provides practitioners with actionable guidance for navigating digital transformation in data-driven enterprises.
Platform-based competition has fundamentally transformed competitive dynamics in digital markets by shifting the locus of rivalry from firm-level products to multi-sided ecosystems sustained by network effects and orchestrated participation. This integrative review synthesizes theoretical and empirical insights from peer-reviewed scholarship to examine how digital marketplaces, network externalities, and ecosystem strategies reshape value creation, competitive advantage, and strategic positioning. Early foundations in two-sided market theory established the centrality of cross-side and same-side network effects in driving platform scale and winner-take-most outcomes. Subsequent scholarship advanced understanding of platform envelopment, multihoming, complementor dynamics, and governance tensions between openness and control. The review identifies persistent strategic paradoxes: platforms must simultaneously encourage generativity to fuel innovation while safeguarding value appropriation and architectural integrity. By organizing the literature into a conceptual synthesis, the paper illuminates the interdependent layers through which platform leaders coordinate users and complementors, navigate openness-control trade-offs, and evolve in response to competitive feedback. Contributions include bridging fragmented perspectives across strategy, information systems, and economics, highlighting the temporal evolution from network effects to ecosystem orchestration, and delineating future research directions for platform evolution amid rapid technological change and regulatory scrutiny. The analysis underscores that sustainable competitive advantage in platform markets derives less from proprietary assets than from dynamic capabilities in governance, orchestration, and adaptive ecosystem design.
Artificial intelligence has emerged as a transformative force in business strategy research, reshaping how organizations conceptualize competitive advantage, reconfigure capabilities, and restructure decision architectures. This integrative review synthesizes peer-reviewed studies to map the evolving role of AI in strategic management. Drawing on literature from leading journals in strategy, information systems, and innovation, the analysis examines how AI is conceptualized—as both a decision-support tool and an autonomous strategic actor—and evaluates its organizational implications across adoption, governance, and transformation processes. Key findings reveal convergences around AI’s augmentation of dynamic capabilities and competitive positioning, yet persistent tensions exist regarding automation-augmentation paradoxes, managerial role erosion, and ethical governance challenges. The review introduces the AI Strategic Organizational Integration Model, a novel synthesis framework comprising five interconnected domains that organize prior research and highlight pathways toward emerging theoretical directions. By classifying studies along dimensions of strategic cognition, capability transformation, organizational redesign, governance tensions, and market-level outcomes, the model illuminates gaps in longitudinal evidence and cross-level theorizing. This work advances an integrative understanding of AI’s strategic significance while offering a structured foundation for future research on intelligent systems in dynamic business environments.
Digital ecosystems represent a fundamental shift in competitive dynamics, moving the unit of analysis from individual firms to interdependent networks organized around platform orchestrators. This review synthesizes contemporary research on how competitive strategy evolves in platform-centered markets, examining the transition from firm-centric to ecosystem-centric competition. We analyze how platform structures create new forms of interdependence, governance mechanisms, and power asymmetries that fundamentally reshape strategic positioning. The review identifies three core themes: ecosystem structure and platform-centered competition, governance and strategic asymmetry, and value dynamics between creation and capture. Our analysis reveals that competitive advantage in digital ecosystems increasingly derives from relational positioning, complementor management, and the ability to navigate tensions between openness and control. We identify critical gaps in the literature, particularly regarding complementor agency, dynamic governance evolution, and the strategic implications of generative AI platforms. The review concludes by proposing an integrated framework for understanding ecosystem competition and outlining priorities for future strategic management research.
Digital business and management research has expanded rapidly since 2017, reflecting the growing influence of digital transformation, platform ecosystems, analytics capabilities, and artificial intelligence in organizational settings. This expansion has produced a diverse and increasingly fragmented body of scholarship across strategy, information systems, innovation management, marketing, and organizational theory. Although several reviews have clarified specific subfields, the broader intellectual evolution of digital business research remains insufficiently mapped from a bibliometric perspective. This bibliometric review examines the evolution of digital business and management research. Its objective is to identify publication trends, intellectual foundations, thematic clusters, and emerging research fronts across four focal domains: digital strategy, platform-based business models, data analytics, and AI governance. By integrating performance analysis with co-citation and keyword-oriented interpretation, the article provides a structured view of how the field has developed. The analysis indicates that digital business research has moved from broad discussions of digital transformation toward more specialized debates on strategy formation, ecosystem governance, analytics-driven value creation, and responsible AI-enabled management. It also shows that the field is increasingly shaped by interdisciplinary connections between strategic management, information systems, innovation studies, and organizational governance. Five tables summarise the data source, publication trends, keyword clusters, leading contributors, and emerging research gaps. The review concludes that digital business and management research is becoming more mature, but also more complex. The next stage of scholarship requires stronger integration across platform strategy, analytics capabilities, organizational accountability, and AI governance. Future research should move beyond technological adoption narratives and examine how digital technologies reshape authority, coordination, value capture, and managerial responsibility.
Institute for Management, Business, and Accounting Studies