Strategic Governance and Ecosystem Management in AI-enabled Digital Marketplaces

Introduction

The special issue will focus on issues surrounding strategic governance and ecosystem management in AI-enabled digital marketplaces. Digital marketplaces have become central infrastructures through which firms design, implement, and revise competitive strategies. Across industries, platforms such as Amazon, Alibaba, and Booking.com increasingly shape how firms access markets, coordinate interactions, and capture value. These marketplaces are no longer simply transactional venues: they operate as strategic environments in which rules, data, and intermediation structures redefine the competitive landscape and reshape ecosystem-level outcomes (Bourai et al., 2024; Loonam & O’Regan, 2022). A key reason for the strategic relevance of marketplaces is that they embed governance directly into market processes. Pricing rules, commission systems, access regimes, ranking and recommendation logics, and enforcement routines influence participation incentives and competitive conduct. Marketplace governance thus becomes a strategic design issue rather than an operational detail. This aligns with research conceptualizing platforms as hybrid governance systems that blend market coordination, hierarchical control, and network interdependence, where governance mechanisms continuously evolve in response to ecosystem dynamics (Cuypers et al., 2021; McIntyre et al., 2020). This governance perspective also brings boundary decisions and distribution strategy back to the center of strategic management. For vendors—particularly SMEs—marketplace participation is a fundamental strategic choice affecting dependence, autonomy, capability development, and long-term positioning. Firms increasingly experiment with direct, indirect, and hybrid routes to market, integrating proprietary infrastructures with third-party marketplaces and offline channels. Recent evidence suggests that SME performance depends on how platform adoption interacts with commitment and organizational routines (Ballerini et al., 2023). These choices reflect strategic trade-offs between control and efficiency and are shaped by how firms design and govern multichannel systems (Homburg et al., 2020). Marketplace governance is also deeply intertwined with organizational learning, alliances, and transformation processes. Digital strategy effectiveness depends on cultural and organizational alignment (Cyfert et al., 2025), while dynamic capabilities shape firms’ ability to adapt and transform in digital contexts (Ellström et al., 2022). In turbulent environments, SMEs rely on agility and transformation capabilities to remain competitive (Troise et al., 2022). Moreover, alliances and tacit learning can enable recovery and resilience under constrained governance conditions, particularly in emerging markets (Aditchere et al., 2025). These dynamics highlight that governance is not only imposed by platforms but also shaped by how ecosystem actors learn, adapt, and coordinate over time (Öberg, 2024). At the same time, governance complexity is increasingly amplified by AI-enabled systems embedded in marketplace architectures. Algorithmic ranking, automated monitoring, fraud detection, dynamic pricing, and AI-supported customer management systems increasingly mediate competitive interactions and decision-making. Recent research suggests that generative AI can enhance market effectiveness through CRM-related applications, particularly under technological turbulence and with strong top management support (Kumar et al., 2025). Yet adoption is shaped by managerial cognition and organizational culture: technophobia, self-regulated learning, and open cultures influence managerial intentions to adopt generative AI (Zhao et al., 2025). Marketplace-based business models may also create competitive advantage by reducing time-related frictions for ecosystem participants, reinforcing the strategic role of platform architectures in enabling efficiency and coordination (Santoro et al., 2025). In practice, major marketplaces have already introduced generative AI tools for sellers and advertising optimization (e.g., Amazon’s AI listing tools and ad automation), illustrating how AI is increasingly integrated into governance and ecosystem management logics. These developments raise not only managerial and strategic issues but also broader societal and ethical questions. AI-enabled governance may increase efficiency and scalability, yet it may also intensify opacity, reinforce asymmetries, and raise concerns around accountability, contestability, and fairness. Understanding how governance mechanisms evolve under AI-enabled coordination therefore represents a timely and consequential research agenda. In addition, digital marketplace configurations may shape firm growth and internationalization trajectories in ways that depend on the strategic balance between platform reach and strategic autonomy (Ballerini et al., 2024).

We welcome submissions to this special issue. The special issue seeks a mix of theoretical, conceptual, and empirical cases and is open to various methods (e.g., qualitative case studies, quantitative analysis of platform data, or formal modeling, etc.). It welcomes theoretically grounded and empirically rich contributions that advance strategy and management research on governance and ecosystem management in AI-enabled digital marketplaces. We encourage conceptual and theory-building contributions, qualitative and process-based studies, large-scale empirical analyses (including digital trace and platform data), mixed-method research, and comparative cross-country work. In line with emerging methodological developments, we also explicitly welcome innovative approaches such as agent-based modeling, longitudinal ecosystem mapping, and multi-level designs that connect governance mechanisms to ecosystem-level outcomes. Topics covered include (but are not limited to):

1. Designing and revising governance architectures in digital marketplaces

• How governance systems are deliberately designed, experimented with, and revised over time
• Strategic trade-offs between openness, control, and scalability across platform life cycles
• Emergent governance practices beyond formal rules (e.g., informal coordination, adaptive enforcement, negotiated control)
• AI-driven enforcement and adaptive governance (e.g., automated compliance monitoring, fraud detection, dynamic rule implementation)

2. Boundary choices and the strategic reconfiguration of distribution ecosystems

• How firms navigate shifting boundaries between proprietary infrastructures, third-party marketplaces, and hybrid configurations
• Experimental and transitional forms of direct–indirect–hybrid distribution under platform dependence
• Governance implications of coordinating online and offline channels within platform-mediated systems
• Boundary decisions under AI-enabled intermediation (e.g., AI-based pricing tools, automated advertising systems)

3. Ecosystem power, dependence, and the micro-foundations of value capture

• How governance mechanisms redistribute bargaining power and strategic discretion across ecosystem actors
• Vendor strategies for managing dependence, asymmetry, and multi-homing under algorithmic control
• Long-term consequences of marketplace participation for autonomy, growth trajectories, and competitive positioning
• Strategic implications of algorithmic visibility and attention allocation (e.g., ranking and recommendation regimes)

4. Capabilities, alliances, and organizational learning under platform governance

• How firms build governance-specific capabilities to operate under rule-based and algorithmic coordination
• Alliances, relational contracts, and tacit learning as complements or substitutes for formal governance
• Co-evolution of corporate transformation and ecosystem-level change in platform settings
• Learning mechanisms for adapting to AI-enabled governance and platform policy changes

5. AI-enabled governance and the transformation of managerial control

• How algorithmic and generative-AI systems reshape monitoring, ranking, enforcement, and coordination practices
• Managerial sense-making, learning, and resistance in the adoption of AI for governance and ecosystem management
• Strategic consequences of opacity, automation, and explainability for trust, legitimacy, and accountability
• Ethical and societal implications of AI-enabled governance (e.g., fairness, contestability, transparency)
• The impact of GenAI on ranking algorithms
• Governance of cross-border data in platforms

6. Ecosystem orchestration, global expansion, and institutional complexity

• Governance challenges in platform-enabled global value chains and cross-border ecosystems
• Orchestration strategies for resilience, reconfiguration, and ecosystem renewal under technological turbulence
• Strategic responses to regulatory fragmentation and institutional pluralism in digital marketplaces
• AI-enabled orchestration capabilities and ecosystem coordination across borders

Deadline and Submission Details

The submission will open May 10, 2027

The submission deadline for all papers is July 10, 2027

The publication date of this special issue is January 31, 2028

To submit your research, please visit the Scholar One manuscript portal. https://mc.manuscriptcentral.com/jsma 

To view the author guidelines for this journal, please visit the journal's page. https://www.emeraldgrouppublishing.com/journal/jsma 

Contact the Guest Editor:

Ciro Troise, Department of Management, University of Turin, Ciro.troise@unito.it