Category Archives: Agentic AI

August 21, 2026 · 10:59 am

Call for papers: Strategic governance and ecosystem management in AI-enabled digital marketplaces

Deadline: 10th July 2027

Journal

Journal of Strategy and Management

Guest editor(s)

Ciro Troise, Mark Anthony Camilleri, Mohamed Hani Gheith, Jacopo Ballerini

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 

Leave a comment

Filed under academia, Agentic AI, AI, Corporate Governance, digital, digital media, digital transformation, ecommerce, internet technologies, internet technologies and society, technology

Tagged as , , , , , , , ,

July 9, 2026 · 12:32 pm

Special Issue on the theoretical foundations of Generative AI and Agentic AI

Delighted to share that the University of Malta has promoted my Call for Papers through NewsPoint:

Prof. Mark Anthony Camilleri is a leading guest editor of a special issue, entitled: “Theoretical perspectives on Generative and Agentic AI adoption in service environments”, that will be published by the Journal of Services Marketing.

Prof. Camilleri is supported by internationally recognised experts in services marketing and management, comprising Prof. Levent Altinay, Editor of The Services Industries Journal; Prof. Sang M. Lee, Editor of Service Business and Prof. Cheng Lu (Charles) Wang, Editor of the Journal of Research in Interactive Marketing.

The full text of the Call for Papers is presented below. It provides background to the special issue. It outlines the theoretical perspectives that prospective contributors may adopt. It highlights illustrative research topics and also includes the submission guidelines for authors.

Introduction

Generative Artificial Intelligence (GenAI) and Agentic Artificial Intelligence (Agentic AI) are transforming how services are designed, delivered, experienced and led. While GenAI refers to systems, such as large language models (LLMs), that produce content in response to human prompts; Agentic AI technologies may be considered as active agents that can implement tasks (rather than merely functioning as passive generators) (Acharya et al., 2025). The latter can monitor situations, allocate resources, initiate and manage processes as well as co-ordinate multiple activities (Gonzalez et al., 2026). Hence, Agentic AI algorithms and their governance affect service outcomes.

Generative AI capabilities often constitute the communicative and cognitive foundations of Agentic AI. In other words, many Agentic AI systems rely on GenAI models to reason, communicate and interact. Together, these AI technologies challenge conventional assumptions about agency, control, responsibility and value creation in service environments (Ferraro et al., 2024; Wirtz & Stock-Homburg, 2025). Unlike earlier forms of automation and analytics, these AI systems can engage in social interactions, reason in a contextual manner and may dynamically adapt to changing situations. As such, they raise profound theoretical questions about anthropomorphism, social presence, trust, autonomy, creativity, emotion, accountability, responsibility and moral agency (Banh & Strobel, 2023; Ng et al., 2026; Sun et al., 2026).

These capabilities indicate that Generative and Agentic AI represent more than incremental advances in automated technologies. They introduce different forms of interaction and agency that cannot be fully explained by utility-driven adoption frameworks (Camilleri, 2024).

Consequently, there is a growing need for theory-driven and conceptually rigorous research that explains how, why and under what conditions Generative and Agentic AI are deployed, adapted, governed, or even resisted in service environments.

This special issue seeks to advance services marketing research by encouraging scholars to utilise, extend, integrate or critically evaluate existing theories to investigate user engagement with Generative and Agentic AI across diverse service settings. In this light, the guest editorial team particularly welcomes submissions that move beyond descriptive accounts. Prospective contributions are expected to offer strong theoretical explanations of AI acceptance and usage in services.

Theoretical perspectives

The editors of this special issue particularly welcome submissions that explicitly draw upon, refine or combine well-established theories that have been influential in service and technology research, including (but not limited to) the following ones (as discussed in Camilleri & Troise, 2023):

  • Anthropomorphism theory (e.g., human-likeness, emotional attachment and/or moral attributions to AI).
  • Affordance theory (perceived action possibilities enabled or constrained by GenAI and/or Agentic AI interfaces).
  • Assemblage theory (AI as part of dynamic socio-technical service systems).
  • Behavioural reasoning theory (reasons for and against AI use in service encounters).
  • Cognitive fit theory (task–AI alignment and decision quality).
  • Commitment–consistency theory (habit formation and sustained AI use).
  • Communication accommodation theory (linguistic and stylistic adaptation in human–AI interaction).
  • Contingency theory (contextual conditions that can have an impact on AI effectiveness).
  • Diffusion of innovations theory (organisational and market-level adoption trajectories).
  • Expectancy and expectation-violation theories (surprise, delight, discomfort or distrust in AI services).
  • Flow theory in computer-mediated environments (engagement, creativity and immersion).
  • Functionalist theory of emotion (affective responses to AI-enabled services).
  • Human–computer interaction / human–machine communication theories.
  • Information systems success model (service quality, satisfaction and net benefits of AI).
  • Politeness theory (face-management and social norms in AI communication).
  • Self-determination theory (autonomy, competence and relatedness in AI use).
  • Situational theories of problem-solving and publics.
  • Social cognitive theory (learning AI use through observation and social influence).
  • Social presence and social response theories.
  • Structural role theory (AI as role-performing service actors).
  • Technology acceptance model (TAM) and unified theory of acceptance and use of technology (UTAUT).
  • Theory of conversation.
  • Theory of planned behaviour (TPB) and its related theory of reasoned action (TRA).
  • Trust–commitment theory.
  • Uses and gratifications theory.

Submissions that integrate multiple perspectives, compare existing conceptual frameworks and develop new theoretical models specific to GenAI and Agentic AI in services are especially encouraged for this special issue.

Illustrative research questions may include (but are not limited to): How and to what extent do customers and employees anthropomorphise Generative versus Agentic AI in service encounters? Which GenAI and Agentic AI affordances drive value co-creation, trust, reliance or resistance in services? How do emotional cues, social presence and politeness strategies influence engagement with AI-driven service agents? Under what contingencies does AI adoption enhance or undermine service quality, relationships and well-being? How do expectations and expectation violation aspects influence satisfaction and continued use of AI-enabled services? How do organisations implement Agentic AI within broader service systems? What ethical, relational, psychological and accountability tensions emerge from sustained human–AI interactions, particularly when AI acts autonomously?

The special issue welcomes conceptual, qualitative, quantitative, experimental or mixed-methods approaches, provided that the contributing authors demonstrate strong theoretical grounding and relevance to the underlying objectives of this journal.

List of topic areas

  • Theoretical perspectives on Generative and Agentic AI adoption in service environments.
  • Comparative or multi-theoretical frameworks for studying human-AI interaction in services.
  • Anthropomorphism, social presence and human-AI relationships.
  • Perceived affordances, interface design and service experiences.
  • Emotions, expectations and psychological responses to AI.
  • Adoption, acceptance and continued use of AI in services.
  • Trust, ethics, accountability and relational governance.
  • AI as a service actor within socio-technical systems.
  • Contextual and contingency-based perspectives.
  • Value co-creation, value co-destruction and service outcomes.
  • Organisational, strategic and policy implications of Generative and Agentic AI in services.

Submissions Information

Submissions are made using ScholarOne Manuscripts. Registration and access are available here.

Author guidelines must be strictly followed which are available online.

Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to ““Please select the issue you are submitting to”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Key deadlines

Opening date for manuscripts submissions: 23 June 2026

Closing date for manuscripts submission: 26 February 2027

Email for submissions: mark.a.camilleri@um.edu.mt

In January 2026, Professor Camilleri launched another call for papers for a special issue focused on ethical AI. The latter one, entitled: ‘Ethical implications of artificial intelligence (AI) and automation in service industries’, will be published by The Service Industries Journal. In this case, the deadline for submission will be on 31 January 2027.

Leave a comment

Filed under academia, Agentic AI, AI, Generative AI, Marketing, Services Marketing

Tagged as , , , , , , , , , , , , , , ,