The digital transformation of the economy has fundamentally altered the logic of business models, shifting the focus from linear, firm-centric value chains to complex, networked architectures. This narrative review synthesizes contemporary literature to conceptualize digital business models, framing the interplay between digitalization and business model design. We explore how platforms, data, and ecosystem-based value creation have become the central pillars of modern business strategy. The review identifies three core architectural shifts: the emergence of platform-based models that orchestrate value exchange, the rise of data as a primary resource for value propositions and monetization, and the transition from dyadic firm-customer relationships to multi-actor ecosystems. We analyze inherent tensions in these models, such as balancing openness with control and scalability with value capture, which present novel strategic challenges. By integrating findings from key references, this article clarifies the conceptual landscape of digital business models and highlights a departure from traditional configurations. We conclude by outlining implications for strategic management and proposing future research directions to address conceptual fragmentation and dynamic governance issues in digital business model innovation.
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.
Modern firms increasingly rely on external digital ecosystems to access infrastructure, artificial intelligence, data, and analytical capabilities that are difficult to build entirely in house. Cloud platforms, AI vendors, and data intermediaries now support core business operations rather than peripheral technical functions. This shift has expanded firm capabilities, but it has also created new forms of dependence. The central problem addressed in this article is that digital ecosystem dependence is often governed through fragmented IT, procurement, compliance, and legal processes. These arrangements can manage service delivery and contractual performance, but they are less suited to strategic vulnerabilities such as lock-in, opacity, bargaining asymmetry, data control loss, and exit difficulty. As a result, firms may become operationally efficient while becoming strategically constrained. The objective of this article is to develop a Digital Ecosystem Governance Framework for firms that depend on cloud platforms, AI vendors, and data intermediaries. The framework identifies the distinct dependence risks associated with each ecosystem partner type and integrates them into a unified governance logic. It treats dependence as a strategic management issue rather than a narrow technology sourcing problem. The proposed framework shows that effective governance of digital ecosystem dependence requires three interrelated capabilities: dependency risk assessment, protective governance mechanisms, and strategic governance oversight. Firms need contractual safeguards, technical portability, internal capability building, vendor diversification, data control mechanisms, and board-level visibility over dependence thresholds. The article contributes a governance-oriented perspective on how firms can use external digital ecosystems without becoming strategically captured by them.
Trust has become a central strategic condition of participation in the digital economy. Data-driven firms depend on customers who share personal information, employees who accept digital systems at work, platforms that coordinate ecosystem participation, and regulators who evaluate organizational credibility. When trust weakens in any of these domains, the consequences can extend beyond the original stakeholder group. Existing research has produced valuable insights into customer privacy, algorithmic fairness, employee surveillance, platform dependence, and governance. However, these domains are often treated separately, which limits the ability of managers to understand how digital trust crises unfold across stakeholder boundaries. A data breach, opaque algorithmic decision, or platform governance failure can simultaneously damage market confidence, employee morale, ecosystem relationships, and regulatory legitimacy. This article develops a unified Digital Trust Management Framework for data-driven business ecosystems. The framework treats digital trust as a systemic managerial capability rather than as a set of isolated stakeholder concerns. It integrates trust-building, trust-maintenance, and trust-repair mechanisms across customers, employees, platforms, and regulators. The article is based on a conceptual synthesis of peer-reviewed articles published. These studies are integrated across strategic management, organizational trust, digital business, information systems, platform ecosystems, data privacy, artificial intelligence governance, and stakeholder management. The synthesis supports a framework that links stakeholder-specific trust drivers with shared managerial mechanisms such as transparency, accountability, participation, security, fairness, and governance credibility. The framework shows that digital trust must be managed as an interconnected ecosystem property. It identifies how trust erosion cascades across stakeholder groups and how integrated trust governance can help firms prevent, contain, and repair digital trust failures. The article contributes a practical roadmap for managers seeking to sustain legitimacy and performance in data-driven business ecosystems.
Modern businesses increasingly depend on a wide array of digital vendors, including SaaS applications, payment gateways, analytics platforms, and outsourced digital services. These vendors no longer sit at the periphery of operations; they shape how firms sell, serve, analyse, automate, and innovate. As digital transformation deepens, the vendor landscape becomes more complex, distributed, and strategically consequential. Many firms still manage digital vendors through fragmented ownership structures, with procurement, IT, finance, marketing, operations, and business units each controlling different vendor relationships. This siloed approach produces integration debt, uncontrolled spending, duplicated functionality, weak renewal discipline, and fragmented data flows. It also increases dependency on external platforms and service providers whose pricing, APIs, data policies, and continuity risks can directly affect firm performance. The objective of this article is to develop a Digital Vendor Portfolio Framework that enables firms to coordinate and govern all digital vendors as an integrated strategic portfolio. The framework treats digital vendors not as isolated contracts but as interdependent assets, risks, and capabilities. It provides a governance logic for mapping vendor roles, identifying dependencies, monitoring performance, and aligning external digital resources with business strategy. The proposed framework addresses coordination for SaaS providers, payment platforms, analytics tools, and outsourced digital services. It identifies governance mechanisms for each vendor category and outlines how portfolio mapping, contractual safeguards, technical integration, relational governance, and performance dashboards can reduce complexity. The article argues that proactive digital vendor portfolio management is now a strategic imperative for firms seeking efficiency, data integrity, resilience, and control.
Institute for Management, Business, and Accounting Studies