Eoin Whelan, University of Galway

Hamed Qahri-Saremi, Colorado State University

Chelly Maes, Université Libre de Bruxelles

Christy M. K. Cheung, Hong Kong Baptist University

Uri Gal, University of Sydney

Monideepa Tarafdar, University of Massachusetts Amherst

Adolescents today engage intensely with digital platforms including social media, gaming communities, AI applications, and learning technologies. This special issue seeks research examining how these complex digital environments shape adolescent development across cognitive, emotional, psychological, social, and physical domains. The urgency stems from how contemporary platforms operate through sophisticated algorithms and AI systems that actively influence adolescents' experiences in ways fundamentally different from previous technologies.

Existing research provides limited understanding of how digital platforms specifically affect adolescent developmental experiences, with little consensus on the direction, magnitude, or mechanisms of impact. The special issue invites empirical and theoretical investigations using diverse methodologies to understand how platform designs, algorithmic systems, and regulatory approaches both benefit and harm adolescent development. Contributions should examine the mechanisms by which platform affordances and AI systems shape developmental outcomes in diverse global populations.

Appel publié par Journal of the Association for Information Systems. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Platform architectures and affordances
• Notification systems and engagement metrics
• Algorithmic curation and recommendation systems
• Generative AI and chatbots for adolescents
• AI literacy and digital resilience
• Information practices in digital environments
• Identity development and social relationships
• Privacy and data protection
• Screen time and physical health
• Mental health and well-being
• Design science for adolescent safety
• Policy and regulation of digital platforms
• Content moderation and age verification
• Comparative platform design studies
• Socioeconomic and cultural differences in digital access

Timeline

• April 9, 2027: Online information session
• November 1, 2027: Deadline for paper submission
• March 1, 2028: First-round decisions
• July 1, 2028: Deadline to submit revised papers
• October 30, 2028: Second-round decisions
• March 1, 2029: Deadline to submit revised papers
• July 1, 2029: Provisional/Final decisions
• August 1, 2029: Deadline to submit final paper (if minor revision is required)

Associate editors

• Tina Blegind Jensen, Copenhagen Business School
• Noel Carroll, University of Galway
• Aaron Cheng, London School of Economics
• J.J Hsieh, Georgia State University
• Tabitha James, Virginia Tech
• Hanna Krasnova, University of Potsdam
• Dong-Heon (Austin) Kwak, Kent State University
• Stephen McCarthy, University College Cork
• Antonia Meythaler, Ludwig Maximilian University of Munich
• Mahya Ostovar, University of Galway
• Ana Ortiz de Guinea Lopez de Arana, HEC Montréal
• Lauren A. Rhue, New York University
• Stefan Tams, HEC Montréal
• Ofir Turel, University of Melbourne
• Yingqin Zheng, University of Essex

Michela Cortini, University G. d'Annunzio of Chieti – Pescara

Teresa Galanti, University G. d'Annunzio of Chieti – Pescara

Marco Giovanni Mariani, University of Bologna

This special issue examines how artificial intelligence is transforming recruitment and selection practices in organizations. While AI technologies such as automated screening, video interview analytics, and generative AI tools offer efficiency gains, they simultaneously raise critical concerns regarding fairness, transparency, accountability, and ethics. The collection seeks contributions that explore both the opportunities and challenges of AI-mediated selection from multiple perspectives.

The special issue invites theoretical, empirical, methodological, and review contributions addressing the human-AI interface in recruitment and selection. Research should consider how AI affects applicants' and recruiters' experiences, perceptions of procedural justice, and organizational attractiveness. The editors particularly welcome work bridging theory and practice to help organizations implement AI-enabled selection responsibly and effectively.

Appel publié par International Journal of Selection and Assessment. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Applicants' and recruiters' motivational and emotional reactions to AI
• Algorithmic decision-making and perceptions of fairness, trust, and justice
• Transparency, explainability, and human oversight in selection
• Human-AI collaboration in personnel selection
• AI-enabled game-based and adaptive assessment methods
• Bias mitigation and diversity enhancement in AI recruitment
• Ethical, legal, and regulatory perspectives on AI in hiring
• Motivational theories in AI-mediated selection
• Impact of AI on recruiters' professional identity and autonomy
• Generative AI in employer branding and recruitment marketing
• Methodological innovations for studying AI-human interaction
• AI influence on candidate experience and authenticity
• Development and validation of AI-supported assessment tools

Timeline

• October 20, 2026: Initial manuscript submission period begins
• January 31, 2027: Initial manuscript submission period ends
• May 1, 2027: First round of reviews ends; revision and resubmission period begins
• August 1, 2027: Revision and resubmission period ends; second round of reviews begins
• October 1, 2027: Second round of reviews ends
• January 15, 2028: Final submissions

Qiang (Steven) Lu, University of Sydney

Jian Ni, Virginia Tech

Yanwen Wang, University of British Columbia

Ranjit Voola, University of Sydney

Junbin Gao, University of Sydney

This special issue examines how algorithmic systems shape markets, organizations, and consumer behavior beyond their technical applications. The focus extends to understanding how these systems influence competition, value distribution, market access, consumer decision-making, and broader societal outcomes including fairness, inclusion, and sustainability.

The call invites research across three interconnected domains: markets, consumers, and organizations. A key emphasis is balancing economic performance with social value creation, addressing algorithmic bias, pricing practices, and inequalities while identifying conditions under which algorithmic integration benefits society.

The special issue prioritizes practical research bridging marketing theory with real-world algorithmic system design and governance. Studies using diverse methodologies are welcomed, particularly those offering actionable insights for managers and policymakers.

Appel publié par European Journal of Marketing. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Algorithmic market shaping and platform ecosystems
• Consumer-algorithm interactions, trust and resistance
• Algorithmic personalisation and customer experience
• Pricing and fairness in algorithmic systems
• Bias, discrimination and inequality in algorithms
• Transparency, ethics, accountability and regulatory responses
• Strategic marketing capabilities and organisational adaptation
• Responsible AI adoption and implementation
• Sustainability and financial inclusion
• Societal impact and policy implications
• Managerial decision-making
• Interdisciplinary and industry-engaged research

Timeline

• September 25, 2026: Opening date for manuscripts submissions
• February 28, 2027: Closing date for manuscripts submission

Christoph Teller, Johannes Kepler University Linz

This special issue examines how retail is being transformed by technology while questioning whether human-centred principles remain central. Building on Levitt's marketing myopia concept, it seeks research exploring how trust, experience, emotion and social interaction can be preserved within digitized retail environments.

The issue welcomes both conceptual and empirical research on retail transformation across physical, digital and hybrid contexts, with emphasis on human-centred approaches, AI integration, service innovation and societal value creation. Submissions must demonstrate strong theoretical grounding and broader relevance to international retail scholarship rather than narrow local focus.

Contributions should address practical implications for retailers and policymakers, maintain methodological rigor and originality, and avoid excessive reliance on generative AI. The issue welcomes diverse methodological approaches and aims to provide insights into retail's future role in society and consumer life.

Appel publié par International Journal of Retail & Distribution Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Human-centred retailing and service systems
• AI and automation in retail environments
• Customer experience and experiential retailing
• Trust, authenticity and social interaction in retail
• Retail employee wellbeing and frontline dynamics
• Platformisation and digital retail ecosystems
• Ethical implications of retail technologies
• Smart retailing and human–technology interaction
• Consumer behaviour in digitally mediated environments
• Retail spaces as community and social infrastructure
• Sustainable and responsible retail innovation
• Omnichannel and hybrid retail experiences
• Emotional engagement and customer deviance
• Retail resilience and adaptive business models
• Future retail scenarios and societal transformation

Timeline

• July 9, 2026: Opening date for manuscripts submissions
• November 30, 2026: Closing date for manuscripts submission

Julian Birkinshaw, Ivey Business School

Valérie Duplat, Vrije Universiteit Amsterdam

Saeed Khanagha, Vrije Universiteit Amsterdam

Oli Mihalache, Athabasca University

Shaker Zahra, University of Minnesota

Artificial intelligence is fundamentally reshaping how multinational enterprises and international new ventures compete globally. This special issue seeks research exploring how AI technologies—particularly generative AI—enable new competitive strategies, from building proprietary AI capabilities to deploying AI tools for market analysis and decision-making. The call welcomes papers examining AI's impact on firm competitiveness, internationalization strategies, organizational transformation, and resilience in volatile environments.

The issue addresses three core dimensions through which AI influences global strategy. First, it considers how firms develop AI-centric capabilities that serve as sources of competitive advantage across borders. Second, it explores how organizations strategically deploy AI to interpret global markets and make faster, more informed decisions. Third, it examines how firms must redesign governance structures and navigate complex international regulatory frameworks to effectively harness AI across multiple countries and institutional contexts.

Appel publié par Global Strategy Journal. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How do proprietary generative-AI capabilities influence entry mode choice in different host-country contexts?
• What factors affect location for AI-centric MNEs and INV founders seeking global scale?
• How do AI-centric firms calibrate the balance between global standardization of models and local adaptation to institutional and cultural distance?
• How do AI-centric INVs build and scale proprietary capabilities to compete globally, and how do these digital-born assets challenge traditional views on firm-specific advantages and gradual internationalization?
• How do AI-centric MNEs and INVs manage international scaling of generative-AI capabilities, and what role do global knowledge-transfer mechanisms play in enabling rapid diffusion across subsidiaries?
• How do AI-centric MNEs manage cross-border complementarities between firm-specific data and host-country capabilities to build sustainable competitive advantage?
• To what extent do open-core versus fully proprietary model strategies shape the boundary decisions (make, buy, ally) of AI-centric firms in different regulatory environments?
• How do AI-centric firms mitigate liability of foreignness in AI ethics and bias by embedding local data and diverse cultural inputs into their global model-training pipelines?
• How can AI-enabled research methods be leveraged by firms to better understand foreign market reception and inform internationalization strategies?
• How do MNEs use generative-AI tools to refine entry-mode strategies (i.e., exporting, licensing, or FDI) by dynamically assessing host-market demand and regulatory complexity?
• Under what conditions can AI-driven scenario planning replace or complement traditional market-selection frameworks (e.g., CAGE) for entering new countries?
• How do firms leverage generative-AI-enabled localization (e.g., product design, marketing copy) to navigate cultural distance and strengthen local responsiveness in global integration strategies?
• What capabilities must regional subsidiaries develop to interpret and act on AI-generated market insights, and how does this reshape subsidiary autonomy versus headquarters control?
• How does generative AI affect the integration-responsiveness trade-off in global operations under geopolitical or natural-disaster shocks?
• In what ways do AI-mediated customer-interaction platforms alter traditional service subsidiary roles and the governance of cross-border service delivery?
• How do firms combine human judgment and AI recommendations in cross-border new product development alliances to balance exploration and exploitation?
• How do AI-enabled INVs sense and respond to global market signals differently than incumbents, and how do AI tools help them to overcome limited experience in culturally or institutionally distant markets?
• In what ways do AI-driven analytics of cultural signals and media content reshape how MNEs and INVs interpret foreign consumer preferences and adapt entry strategies?
• How can methodological advances in AI-based content analysis contribute to more fine-grained monitoring of cultural distance and liability of foreignness in real time?
• How do MNEs structure global AI governance bodies to balance headquarters-led oversight with subsidiary-level discretion across divergent institutional environments?
• What alliance governance mechanisms (joint ventures, co-development agreements) best facilitate GDPR-compliant data-sharing for generative-AI co-creation between European and Asian partners?
• How do emerging global AI regulations reshape MNEs' decisions on center-of-gravity for model deployment (cloud vs. on-prem) across host countries?
• How do entrepreneurial ecosystems in emerging markets influence the design of cross-border data trusts and co-governance structures for INV-led AI initiatives?
• How do platform partnerships with regional software ecosystems (e.g., Midjourney in European design suites, Eleven Labs in Asian media platforms) alter inter-firm governance and value-capture?
• In what ways do pre-competitive data trusts and industry consortia mitigate institutional voids and enable co-governance of domain-specific generative models in emerging markets?
• How must performance metrics and incentive systems evolve to reward cross-border AI collaboration while managing moral-hazard and knowledge-leakage risks?
• What role do board-level AI oversight committees play in enforcing a cohesive global AI ethics framework amid diverse local legal and cultural norms?
• How can AI-based methods be leveraged to examine how firms navigate cross-border governance and regulatory environments?

Timeline

• September 15, 2026: Submission window opens
• October 15, 2026: Deadline for submissions

Associate editors

• Qian (Cecilia) Gu, Georgia State University

Karathanasopoulos Andreas, :null

Kung Cheng Ho, :null

Hans von Mettenheim, :null

This special issue focuses on the application of advanced artificial intelligence methods—including deep learning, transformer models, and large language models—to forecasting problems across finance, accounting, management, and economics. The issue seeks to explore how these AI techniques can improve forecast accuracy and support decision-making while examining their theoretical foundations and practical implications.

The issue welcomes interdisciplinary research addressing both technical and ethical dimensions of AI forecasting, including fairness, reproducibility, interpretability, and regulatory considerations. Contributions comparing AI approaches with traditional econometric methods, developing hybrid strategies, or investigating how human judgment interacts with algorithmic predictions are particularly encouraged.

Appel publié par Journal of Forecasting. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI in financial forecasting (e.g., asset pricing, portfolio allocation, cryptocurrency markets)
• AI in accounting forecasting (e.g., fraud detection, reporting quality, risk assessment)
• AI in management forecasting (e.g., strategic decision-making, supply chain modelling)
• AI in economic forecasting (e.g., macroeconomic indicators, behavioral responses, sectoral trends)
• Ethical, regulatory, and practical dimensions of AI in forecasting (data governance, model fairness, reproducibility, interpretability)
• Comparisons between AI-based approaches and traditional econometric techniques
• Hybrid modelling strategies combining AI with traditional methods
• Interaction between human judgment and algorithmic outputs

Timeline

• September 30, 2027: Submission deadline

Nisreen Ameen, University of Reading

Federico Iannacci, University of Sussex

Daniel Gozman, University of Sydney Business School

James S. Denford, Royal Military College of Canada

This special issue examines how artificial intelligence embedded in public services shapes policy-making and how policies configure AI's development and use. The dynamic interplay between technology and policy intensifies with AI's scale and opacity. The issue seeks to understand how this reciprocal relationship creates, distributes or undermines public value—encompassing efficiency, equity, transparency, participation and welfare.

The special issue invites Information Systems research that theorises AI as central to policy formation and enactment. Manuscripts should examine how AI systems shape policy problems and evidence, how organisations translate AI policies into practice, and how communities participate in defining public value. Qualitative, quantitative, design science and practitioner-oriented contributions are welcome.

All submissions must include dedicated policy implications sections. Research may be set in public, private or nonprofit sectors and should address whose interests are encoded in AI systems, who benefits, who bears risks and whose experiences remain invisible.

Appel publié par Information Systems Journal. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Creation and Distribution of Public Value: How AI creates, distributes or undermines public value, including efficiency, innovation, equity, participation, dignity, sustainability, security and welfare, and how related trade-offs are managed.
• AI Use and the Production of Policy: How AI models, data, classifications, system design and organisational routines shape policy problems, evidence, interventions and evaluation, and how policies evolve through AI-enabled systems.
• AI Governance Beyond Regulatory Compliance: How accountability, transparency, explainability, human oversight and decision authority are enacted in practice, and how AI governance can address societal purposes and outcomes beyond regulatory compliance.
• Policy Translation and Organisational Capability: How organisations translate AI-policy ambitions into procurement, system design, workforce skills, professional roles, implementation and service delivery, and build capabilities to sustain public value.
• Participation, Inequality and Contestation: How AI-enabled policies affect citizens and marginalised groups, reshape voice, access and opportunity, and enable affected communities to participate in defining public value.
• IS Knowledge and Policy Formation: How IS theory and evidence inform AI policy, and how research, practitioner insights and research–practice collaborations can connect evidence, policy, organisational practice and societal outcomes.

Timeline

• June 15, 2027: Submission deadline

Caroline Barrett, University of York

Lutfun Nahar Lata, Murdoch University

Daniel Muzio, University of York

François Schoenberger, University of Oxford

This special issue examines how artificial intelligence and algorithmic management are reshaping professional work, situating current technological changes within a longer historical context of technological reconfiguration. It investigates whether AI threatens professional expertise by making knowledge more accessible or whether expertise remains fundamentally relational and generated through human interactions.

The call explores how power may shift as new AI-focused occupations emerge while established professions face disruption from new entrants and business models. Within professional service firms, hierarchical structures may flatten as AI reduces demand for junior professionals. The collection also addresses how these transformations impact individual professionals' identities, agency, and the ethical questions arising in AI-integrated practice.

Drawing on momentum from a successful conference stream, this open call welcomes global research spanning healthcare, creative labour, knowledge services, higher education, and the professions of those who build AI systems themselves.

Appel publié par New Technology Work and Employment. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How AI displaces or enhances professional work; implications of AI-driven knowledge accessibility for occupational closure; erosion or evolution of professions as exclusive knowledge domains
• New business models challenging traditional regulation; AI's impact on hierarchies, leverage ratios, and power dynamics; role of legacy institutions in mediating change; new forms of organizational experimentation
• Shifting lived experiences, identities, and agency of individual professionals; emerging essential skills such as digital literacy and ethical reasoning; new ethical challenges; adaptation of professional training; forms of resistance or compliance to algorithmic oversight
• The rise or decline of specific occupations due to AI; potential resurgence of manual and craft labour; how professionals are shaping the future of their fields; emerging alternative models of professionalism
• Healthcare and diagnostic expertise, particularly AI implementation in medical imaging, digital documentation, and radiology
• Algorithmic transformations and emerging collective agency among journalists, visual media freelancers, and creative workers
• Disruption or transition of traditional expertise across legal sectors, translation platforms, and academic institutions
• How data scientists, ML engineers, computer programmers, and data analysts find their own elite expertise reconfigured by AI systems they build
• Shifting lived experiences, professional identities, and relational reinforcement of client expertise in modern institutional settings

Timeline

• Invalid DateTime: Expected Publication
• July 1, 2026: Proposal consideration
• September 1, 2026: Call for Papers Issued
• March 1, 2027: Review Process & Revisions
• June 1, 2027: Submission Deadline for Full Papers

This special issue in the Journal of Manufacturing Systems invites submissions on artificial intelligence applications in manufacturing contexts, bridging theoretical frameworks with practical implementation and real-world deployment across industrial settings.

Appel publié par Journal of Manufacturing Systems. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• December 15, 2026: Submission deadline

This special issue explores the intersection of artificial intelligence, digital transformation, and sustainability in the financial sector. The collection invites research that examines how these technological and environmental forces are reshaping finance and the broader economic landscape.

Appel publié par International Review of Economics & Finance. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• June 30, 2027: Submission deadline

Seulki Lee-Geiller, University at Albany, State University of New York

Mila Gascó-Hernández, University at Albany, State University of New York

This special issue examines how artificial intelligence becomes embedded and institutionalized within local governments and the consequent transformations in governance. While AI scholarship typically focuses on national initiatives or public administration broadly, local governments have distinctive conditions that warrant focused attention. The issue seeks to understand not just adoption and implementation of AI systems, but how AI reshapes everyday administrative practice, institutional capabilities, organizational structures, and democratic engagement.

The special issue addresses three interconnected dimensions. First, institutional capacity examines how local governments build lasting infrastructure, expertise, and governance structures to support AI sustainably. Second, organizational arrangements explore how AI influences administrative routines, professional roles, and authority distribution. Third, democratic practices investigate how citizens participate in and influence AI integration decisions. The issue welcomes diverse methodological approaches and comparative research across different municipalities and policy sectors.

Appel publié par Local Government Studies. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How local governments build and sustain infrastructure, expertise, learning systems, governance arrangements, and collaborative capacity to support AI over time
• What enduring capabilities allow local governments to institutionalize AI
• How AI integration affects the capacity of local governments to carry out their main responsibilities
• How local governments learn from pilots, failures, and unintended outcomes
• How local governments address gaps in technical and professional expertise under resource constraints
• How AI changes administrative routines, workflows, and professional roles
• How authority, expertise, discretion, and responsibility are reorganized around AI
• Accountability and responsibility when decisions are jointly produced by officials and AI systems
• How local government uses of AI are authorized, explained, scrutinized, and revised
• How AI integration changes interactions between local governments and citizens
• How local governments involve residents in developing AI guidelines and governance frameworks
• How public feedback and community concerns regarding AI-assisted public services are incorporated into AI institutionalization

Timeline

• November 1, 2026: Abstract submission deadline
• March 1, 2027: Full manuscript submission deadline

Peilin Phua, Adelaide University

Zachary William Anesbury, Adelaide University

Michael Mehmet, University of Wollongong

Kristina Klein, University of Bremen

This special issue examines how artificial intelligence is reshaping marketing knowledge production, with a focus on the Human-in-the-Loop (HITL) perspective. Rather than emphasizing AI's efficiency and predictive capabilities, the collection investigates what these technological shifts mean for how marketing knowledge is generated, validated, and understood. HITL practices ensure that human judgment remains active and accountable throughout the knowledge production process.

The special issue draws on the journal's tradition of exploring how marketing knowledge is produced through practice rather than merely discovered. Contributors are invited to examine the relationship between human and AI agency in knowledge generation, including questions about expertise, rigour, and trustworthiness when AI tools are involved in research and practice. The collection welcomes conceptual, empirical, methodological, and critical perspectives on AI's broader disciplinary and institutional implications in marketing.

Appel publié par Journal of Marketing Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Conceptual and theoretical work examining HITL and how AI-assisted research tools shape marketing knowledge and markets
• Socio-material and more-than-human perspectives on human–AI collaboration in marketing research and practice
• Methodological innovation in AI-assisted qualitative research, including netnography, discourse analysis, and ethnographic approaches
• Critical examination of how AI shapes the labour, expertise, and interpretive practices of marketing researchers and practitioners
• The design and evaluation of HITL systems in marketing analytics, consumer research, and decision-making, including how such systems shape knowledge production and use
• The use of AI for synthetic data generation or research alternatives, examining human oversight and its implications for knowledge claims
• Ethical and societal implications of AI in marketing knowledge production
• Research revisiting established marketing findings using AI-assisted methods (e.g., replication and generalisation across contexts), evaluating how these approaches contribute to the validation, interpretation, and enactment of marketing knowledge

Timeline

• March 1, 2027: Manuscript deadline

Shahriar Akter, University of Wollongong

Carolyn Strong, Cardiff University

Marketing is experiencing rapid transformation through AI adoption, yet over 80% of AI initiatives fail to deliver expected financial returns. Despite most CMOs experimenting with AI, fewer than 10% have successfully scaled it across marketing workflows. The gap between AI potential and actual value creation highlights the need for marketing processes centered on humans orchestrating AI, channels, and personalization as a continuous growth engine.

This special issue seeks high-quality research examining how human-centered AI can enhance strategic decision-making in marketing. It welcomes papers addressing responsible AI principles such as beneficence, autonomy, security, justice, and explicability, alongside practical challenges in marketing-specific AI governance, security risks in autonomous agents, algorithmic bias mitigation, and the reskilling of marketing teams for effective human-AI collaboration.

Appel publié par Journal of Strategic Marketing. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Continuous insights: Using multiple data sources for segmentation, campaign execution, and analytics with AI collaboration to predict consumer behaviours
• Security in Agentic creativity: Addressing data breaches, cyberattacks, and security risks in agentic AI systems, including automatic campaign scaling and optimization
• Trust and algorithmic biases: Implementing auditing protocols to identify and correct distortions in data and models
• AI governance and ethical principles: Establishing AI governance frameworks and marketing-specific ethical guidelines for socially beneficial AI adoption
• Human-centred marketing skills: Reskilling and upskilling marketing talent in data analytics, hyper-personalisation, chatbots, and virtual assistants for strategic decision-making
• AI failures: Understanding why AI projects fail due to data quality, customer needs identification, expectations management, and cultural readiness in human-AI collaboration

Timeline

• October 30, 2026: Abstract deadline
• March 31, 2027: Manuscript deadline

Chiara Civera, University of Turin

Demetris Vrontis, University of Nicosia

Sanjit K. Roy, Edith Cowan University

Valentina Chiaudano, University of Turin

The special issue examines how emerging technologies like artificial intelligence, machine learning, and blockchain can reshape marketing strategies toward a multi-stakeholder approach in global contexts. While firms increasingly deploy advanced technologies to enhance customer engagement and personalization, there is limited understanding of how these technologies can support marketing that simultaneously addresses the interests of employees, suppliers, regulators, communities, and society. The issue seeks to bridge this gap by exploring how NATs enable stakeholder engagement, value creation, and governance across global marketing ecosystems.

Appel publié par Journal of Strategic Marketing. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Artificial Intelligence and Value Co-Creation in Global Marketing Ecosystems: how AI and advanced technologies reshape marketing strategies, processes, and interactions among multiple stakeholders in global markets; how NATs enable new forms of value co-creation among firms, customers, suppliers, regulators, and communities; how technology-enabled marketing infrastructures enhance transparency and coordination across global value chains
• Governance, Ethics, and Responsible AI in Marketing: ethical, governance, and organizational implications of NAT-driven marketing systems; algorithmic bias, transparency, accountability, and fairness in data-driven marketing practices; governance mechanisms and organizational capabilities for implementing responsible and transparent NAT-enabled marketing strategies; managing stakeholder tensions and trade-offs arising from NAT-supported marketing decisions
• Cross-Country Dynamics of New-age Technologies in Marketing: how institutional environments, cultural contexts, and regulatory frameworks influence the adoption and governance of artificial intelligence in global marketing; cross-country differences in implementation of NAT-enabled marketing strategies; how new-age technologies influence global marketing strategy and ecosystem coordination; how NATs support sustainable, inclusive, and responsible marketing practices in global markets

Timeline

• April 30, 2027: Manuscript submission deadline

Yao Shi, University of North Carolina Wilmington

Lukas R. G. Fitz, Brandenburg University of Technology Cottbus – Senftenberg

Fanny-Eve Bordeleau, Dalhousie University

Claudia Pelletier, Université du Québec à Trois-Rivières

Judith Gebauer, University of North Carolina Wilmington

SMEs are significantly lagging behind large organizations in AI adoption due to structural and financial constraints, limited access to technology, insufficient data infrastructure, and workforce skill shortages. This growing digital divide threatens economic competitiveness and equity across regions. As SMEs form a critical part of global economies, their meaningful participation in AI-enabled digital transformation is essential for building resilient and fair economic systems.

This topical collection welcomes multidisciplinary research exploring AI adoption, implementation challenges, workforce development, ethical considerations, and best practices in SMEs. The collection invites theoretical, empirical, design-oriented, and technical contributions that address opportunities and strategies for AI-enabled transformation in the SME context, including case studies and innovation ecosystem perspectives.

Appel publié par Electronic Markets. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI adoption drivers, strategies, and readiness models for SMEs' digital transformation
• AI barriers, challenges, and failures for SMEs' digital transformation
• Skill gaps, workforce development, organizational learning and managerial capabilities for AI-enabled practices in SMEs
• Ethical and societal issues surrounding AI in SMEs and their environments
• Case studies of AI adoption and use in SMEs and their business ecosystems
• AI innovation ecosystems inclusive of SMEs
• Design of SME-suitable AI artefacts
• SME practitioner perspectives on AI
• Implementing human-centered AI for SMEs
• AI-enabled business model innovation pathways in SMEs
• AI governance frameworks for SMEs
• AI-driven shifts in SME strategies for competition, co-opetition, co-creation, and open innovation
• Development, configuration, and management of AI ecosystems for SMEs

Timeline

• September 15, 2026: Open for submissions
• March 15, 2027: Submission deadline

Jameson Hayes, University of South Carolina

Edward Malthouse, Northwestern University

Advertising researchers are increasingly using artificial intelligence as a research tool—large language models now serve as survey respondents, moderators, analysts, and predictors. This shift is outpacing academic attention; while practitioners have deployed synthetic respondent platforms and AI-moderated research at scale, concerns about bias, validity, and accuracy remain largely unexamined. This special issue seeks rigorous work evaluating whether and when AI-based methods produce trustworthy advertising research.

The special issue addresses several pressing concerns: synthetic respondents may simulate what people say about ads rather than what ads actually do to them, given that much advertising effect operates through low-attention and implicit processes. The field lacks clear standards for validating these tools, and the gap between commercial deployment and published research is widening. Both quantitative and qualitative approaches, benchmarking studies, and independent evaluations of commercial tools are welcomed.

Appel publié par Journal of Advertising Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Does It Predict? The Validity of Synthetic Ad Testing - When can LLM-based synthetic respondents stand in for human participants in advertising research, and when do they fail?
• How well do synthetic panels reproduce human results on core advertising outcomes (e.g., attention, recall, attitude toward the ad, purchase intent), and under what boundary conditions?
• Can synthetic respondents replicate established advertising effects (e.g., mere exposure, source credibility, fear appeals), and what does failure to replicate reveal?
• What is the appropriate validation criterion: human panel agreement, or in-market outcomes such as sales and brand lift?
• How much variance compression, homogenization, or demographic distortion do synthetic samples introduce, and how should uncertainty be quantified and reported?
• Given that models are trained on the advertising literature itself, when does an apparent confirmation of theory reflect evidence rather than regurgitation?
• Which advertising responses (e.g., deliberative judgments, verbal attitudes) can LLMs plausibly simulate, and which (e.g., implicit memory, affective response, low-attention processing) remain out of reach?
• How do synthetic responses compare with human data across high- and low-involvement conditions, or across System 1 and System 2 dominant tasks?
• Do synthetic respondents exhibit persuasion knowledge, skepticism, or ad avoidance in ways that mirror or distort human patterns?
• What theoretical frameworks best explain where machine simulation of consumer response breaks down?
• Machines That Listen: AI-Moderated Qualitative Research - What happens to qualitative advertising research when the moderator, the coder, or both are machines?
• How does AI moderation compare with skilled human moderation in probing depth, laddering, and the elicitation of meaning?
• Do consumers disclose differently to AI interviewers, particularly for sensitive or socially undesirable topics relevant to advertisers?
• How reliable are LLMs as qualitative analysts relative to human coders, and what is lost or gained in machine-led thematic analysis?
• Does qualitative research at machine scale change what qualitative inquiry is for, or merely how much of it can be done?
• AI as Measurement Instrument - How trustworthy are machines as coders and predictors of advertising content and response?
• How valid are AI-predicted attention, emotion, and memorability scores relative to eye tracking, facial coding, and other biometric ground truths, and where do the predictions break down?
• Can LLMs and multimodal models reliably code advertising content at scale (e.g., creativity, emotional tone, brand prominence, message strategy), and how should such measures be validated?
• What can computational reanalysis of large advertising archives (e.g., tracking studies, open-ended verbatims, effectiveness case libraries) reveal that original analyses could not?
• Stress Tests and Stand-Ins: Studying What Could Not Be Studied - Can AI extend advertising research into territory that was previously impractical, or impermissible, to study?
• Can adversarial AI populations red-team creative before launch, surfacing misinterpretation, offense, and unintended meanings across segments?
• Under what conditions, if any, are synthetic stand-ins defensible for audiences that are restricted or difficult to research directly (e.g., children, patients, regulated categories)?
• How should the field confront the fidelity paradox: synthetic methods are most attractive precisely where human ground truth is least available?
• The Changing Research Pipeline - How is AI reshaping the practice, economics, and integrity of advertising research?
• When creative variants can be generated and scored predictively at scale, what becomes of the pretest as a discrete stage, and of the research function itself?
• How accurate are commercial AI research tools when evaluated independently, and what evaluation frameworks should the field adopt?
• How prevalent is AI contamination of human data (e.g., bots, LLM-assisted respondents), and how can it be detected, and what does it mean for the panel infrastructure advertising research depends on?
• What disclosure and reporting standards should journals, firms, and industry bodies require when AI participates in the research process?

Timeline

• July 1, 2027: Submission window opens
• August 1, 2027: Manuscript deadline

Yang Feng, California State University, Fullerton

Quan Xie, Southern Methodist University

Joanna Strycharz, University of Amsterdam

Artificial intelligence is transforming advertising at multiple levels: as a tool for creative and strategic work, and as an autonomous agent capable of planning and executing tasks independently. This transformation raises fundamental questions about how advertising professionals collaborate with AI systems, how roles and authorship are being redefined, how consumers respond to AI-driven advertising, and what research methods and ethical safeguards are needed when AI participates in the research process itself.

The special issue invites contributions addressing three interconnected domains: human-AI collaboration in advertising practice and creative work; how AI-generated and AI-personalized advertising affects consumer perception and behavior; and how researchers should adapt their methodologies, standards, and ethical frameworks when collaborating with AI in data collection, stimulus generation, and analysis. Submissions may employ any methodological approach and should move beyond describing tools toward deeper insights about advertising, persuasion, and communication in the age of AI.

Appel publié par International Journal of Advertising. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Human-AI collaboration in advertising creative processes, including authorship, creative judgment, and practitioner roles across different contexts of advertising
• AI-assisted campaign strategy, optimization, and automated decision-making
• Agentic AI as a proactive partner in advertising practice and its implications for human oversight and accountability
• Governance structures for human-AI collaboration in advertising agencies and brand organizations
• The full range of human-AI collaborative modes, from tool use to co-creation to agentic delegation, and their implications for advertising practice and governance
• Human-AI collaboration in prosocial and public interest advertising
• Consumer perception, emotion, evaluation, and response to AI-generated advertising
• AI-driven personalization and its effects on persuasion, privacy, and consumer trust, consent, data protection, and consumer vulnerability
• Anthropomorphism, virtual influencers, AI digital twins, and AI agents as advertising vehicles
• AI advertising across diverse contexts, such as PSAs, health communication, political advertising, public policy, and nonprofit campaigns
• Ethical implications of AI advertising for vulnerable audiences, including children, older adults, patients, and politically targeted publics
• Consumer awareness, literacy, and resistance in response to AI-driven advertising systems
• Construct validity and stimulus equivalence in advertising experiments using AI-generated materials
• Reliability and replicability standards for AI-assisted advertising research
• Validity of AI-mediated data collection in advertising research
• Research ethics of AI-simulated participants and agentic data collection in advertising studies
• Privacy, consent, and data protection in AI-assisted research, synthetic data, and agentic data collection
• Bias and representational equity introduced through AI-assisted research designs and/or AI-generated advertising content
• Theoretical implications of human-AI collaboration for established advertising frameworks
• Agentic AI in advertising research and the governance structures needed to maintain scholarly rigor

Timeline

• August 1, 2027: Submission window opens
• August 31, 2027: Manuscript deadline

Adele Marshall, Queen's University Belfast

Laura Boyle, Queen's University Belfast

Sally Brailsford, University of Southampton

Erwin Hans, University of Twente

Brian Denton, University of Michigan

Martin Kunc, University of Southampton

Healthcare systems globally face mounting challenges from aging populations and workforce constraints while simultaneously benefiting from expanding digital health data and artificial intelligence capabilities. This special issue explores how Operational Research and AI methods can be combined to improve healthcare planning, delivery, and evaluation. Building on prior work examining the OR-AI interface, this collection focuses specifically on healthcare applications where reliable and verifiable AI is critical.

The special issue seeks original research demonstrating substantive contributions at the intersection of OR and AI in healthcare contexts. Submissions should include methodological advances, applied studies with measurable practical value, and work addressing real-world implementation challenges. Papers focused solely on optimization or simulation without significant AI integration may be more appropriate for other venues.

Appel publié par Journal of the Operational Research Society. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Machine learning and predictive modelling for patient flow, demand forecasting, and clinical decision support integrated with OR
• Large language models, generative AI, and retrieval-augmented generation for extracting modelling insight from unstructured clinical documents and health records
• Reinforcement learning and approximate dynamic programming for sequential decisions in screening, treatment, and care planning
• Generative approaches to synthetic health data for modelling and privacy-preserving analysis
• Optimisation of healthcare resources including workforce planning, scheduling, and capacity management using integrated AI and OR methodologies
• Hybrid simulation–AI approaches for the design and evaluation of care delivery
• Data-driven and digital-twin models of care pathways and healthcare delivery
• Statistical and stochastic modelling of patient journeys and survival
• AI-enhanced planning and delivery of care in emergency, unscheduled, and elective settings
• Personalised and stratified care through AI-enabled pathways, screening, prevention, and chronic disease management
• Human–AI collaboration in clinical and operational decision-making
• Trustworthy AI in health addressing equity, ethics, transparency, and verification
• Implementation and evaluation of OR/AI models in healthcare practice

Timeline

• Invalid DateTime: Expected publication
• January 15, 2027: Submission deadline
• April 1, 2027: First-round decisions

Jie Ma, Jilin University

Lihong Zhou, Wuhan University

Naya Sucha-xaya, Chulalongkorn University

This special issue seeks research examining how artificial intelligence is transforming information science, particularly from the Asia Pacific region. The collection aims to bring together cutting-edge theoretical and applied work that demonstrates how AI is reshaping the information ecosystem across traditional disciplinary boundaries.

The special issue prioritizes work that integrates AI with libraries, archives, and cultural heritage systems, emphasizes regional perspectives and case studies from Asia Pacific, and presents actionable research with societal impact linked to the UN Sustainable Development Goals.

Appel publié par Aslib Journal of Information Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI and Data Science in Digital Libraries, Archives, and Preservation
• Human Information Interaction and AI Enhanced User Experience
• Knowledge Discovery and Organization
• Data & Information Policy, Ethics, and Governance
• Scholarly Communication, Bibliometrics, and Research Evaluation
• AI Applications in Education, Healthcare, Cultural Heritage, etc.
• Information Behavior and Social Informatics
• Interdisciplinary and Emerging Topics in Information Science

Timeline

• March 1, 2027: Opening date for manuscript submissions
• June 1, 2027: Closing date for manuscript submissions

Malek Masmoudi, University of Sharjah

Patrick Siarry, Université Paris-Est Créteil

Omar Tujjar, International Society of Medical AI (ISMAI)

This special issue focuses on the integration of large language models and agentic AI systems in healthcare. The issue invites research on how these autonomous, reasoning-capable technologies can transform clinical practice, hospital operations, and healthcare management while promoting patient-centered care and sustainability.

Healthcare organizations increasingly deploy AI agents that combine perception of diverse clinical data with capabilities like planning, tool use, and collaboration to support clinicians, patients, researchers, and administrators. As adoption grows, rigorous evaluation and trustworthiness become critical to ensure these systems remain safe, auditable, and aligned with clinical standards.

The special issue welcomes original research articles, position papers, and validated case studies on both technical topics such as architectures and algorithms, and socio-technical topics including ethics, policy, and human factors across all stages of agentic AI deployment in healthcare.

Appel publié par Expert Systems. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Foundations, Architectures, and Frameworks for Agentic AI in Healthcare
• LLM-Based Clinical Decision Support and Diagnostic Reasoning
• Multi-Agent Systems and Collaborative Healthcare Intelligence
• Multimodal Perception in Healthcare Agents
• Patient-Centered Agents and Digital Health Engagement
• Robotic and Computer-Assisted Surgery with Agentic AI
• Healthcare Operations, Administration, and Workflow Automation
• Drug Discovery, Biomedical Research, and Clinical Trials
• Evaluation, Safety, Trust, and Explainability of Healthcare Agents
• Ethics, Regulation, Governance, and Sustainable AI Deployment

Timeline

• January 31, 2027: Submission deadline

This special issue of Global Finance Journal invites submissions exploring the application and impact of artificial intelligence in capital markets. The issue seeks to advance understanding of how AI technologies are reshaping financial markets, trading practices, and investment strategies.

Appel publié par Global Finance Journal. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• September 30, 2026: Submission deadline

This special issue in the Journal of Informetrics focuses on the intersection of artificial intelligence and scholarly evaluation. The call invites research exploring how AI technologies are being applied to, and impacting, various aspects of academic evaluation and assessment.

Appel publié par Journal of Informetrics. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• February 28, 2027: Submission deadline

This special issue addresses how artificial intelligence is transforming and reshaping the conceptual and practical boundaries within entrepreneurship research. The call invites scholars to explore the implications of AI for understanding entrepreneurship, challenging established assumptions and frameworks in the field.

Appel publié par Journal of Business Venturing Insights. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• August 1, 2027: Submission deadline

This special issue focuses on the governance and management of artificial intelligence applications within business education settings. The call addresses concerns related to risks associated with AI use and explores preventive measures and strategies for responsible AI governance in educational contexts.

Appel publié par The International Journal of Management Education. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• December 31, 2026: Submission deadline

This special issue examines the governance frameworks and international regulatory approaches necessary to manage emerging ocean technologies in the context of climate action. It addresses how artificial intelligence and spatial computing applications can be effectively regulated within marine policy to support sustainable ocean management and climate mitigation goals.

Appel publié par Marine Policy. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• October 30, 2026: Submission deadline

This special issue explores the multifaceted dimensions of human-AI collaboration, examining both the opportunities it presents and the challenges it raises across various domains and disciplines. The collection seeks interdisciplinary perspectives on how humans and artificial intelligence systems can work together effectively and responsibly.

Appel publié par Technology in Society. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• December 31, 2026: Submission deadline

AI systems are increasingly used in HR functions such as recruitment, employee analytics, training, performance management and workforce planning. While organizations often expect these systems to improve efficiency and fairness, they raise concerns about transparency, employee wellbeing, job quality and whether such systems genuinely enhance organizational performance. This special issue shifts focus from simply whether organizations adopt AI to how AI-enabled HR systems should be designed, governed and experienced to benefit employees and organizational effectiveness.

The special issue examines the relationship between AI-enabled HR practices and sustainable organizational performance, considering both potential benefits and risks. It invites research exploring when and how AI strengthens or undermines work quality, fairness, employee voice, inclusion and capability development. The collection addresses emerging regulatory interest from bodies like the OECD and EU AI Act, which recognize that AI in employment decisions requires responsible governance.

Appel publié par Journal of Organizational Effectiveness: People and Performance. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI-enabled recruitment, selection and fair access to work: How AI screening, automated assessments, candidate ranking, video interviews and people analytics affect fairness, validity, transparency, accessibility and selection outcomes.
• AI-supported training, development and capability building: How AI-enabled learning systems, skills analytics, career platforms and talent systems affect reskilling, development access, career visibility and employee capability.
• AI-enabled performance management, monitoring and evaluation: How algorithmic monitoring, datafication and AI-supported appraisal affect fairness, trust, employee agency, wellbeing, reasonable adjustment and performance outcomes.
• Work design, job quality and employee voice in AI-enabled workplaces: How AI changes autonomy, workload, coordination, meaningful work, participation, consultation and human oversight in people-management decisions.
• Inclusion, disability, governance and sustainable organisational effectiveness: How organisations design AI-enabled HRM systems that reduce bias, support EDI, protect disabled workers and applicants, strengthen trust and contribute to sustainable organisational performance.

Timeline

• June 25, 2026: Opening date for manuscripts submissions
• January 25, 2027: Closing date for manuscripts submission

Marketing practice is being transformed by technological advances, geopolitical shifts, economic pressures, and growing demands for sustainability and social responsibility. Retail environments serve as key sites where these transformations unfold, with both physical and digital channels becoming laboratories for new consumer engagement and adaptive strategies. Consumers now demand greater brand ethics, transparency, and societal contributions, while external disruptions like supply chain fragility, inflation, and geopolitical tensions reshape pricing and sourcing. Simultaneously, artificial intelligence and platform ecosystems are fundamentally changing how consumers access information and make purchase decisions.

Appel publié par Journal of Consumer Marketing. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Consumer responses to global disruptions (e.g., inflation, supply chain fragility, climate events, tariffs, war)
• Impact of AI, automation, and platform-based ecosystems on consumer well-being and happiness
• How to enhance responsible consumption (e.g., reducing food waste and increasing adoptions of green energy and public transportation)
• How to serve marginalized and disadvantaged consumers and enhance equality among gender, race, ethnicity, and socioeconomic status through marketing and equitable practices
• Evolving consumer purchase patterns and consumption practices around brand ethics, transparency, and sustainability
• How firms can navigate sociopolitical activism (e.g., Should brands take a stand or remain silent?)
• Recalibrating brand-consumer relationships in times of social and political polarization
• Cross-cultural and cross-generational consumer insights in a post-globalization era
• Retail innovation in response to external forces, trends, disruptions, and shifting consumer expectations
• Marketing strategies for enhancing trust, loyalty, engagement in uncertain environments

Timeline

• August 15, 2026: Opening date for manuscripts submissions
• October 15, 2026: Closing date for manuscripts submission

This special issue examines how immersive technologies like virtual reality, augmented reality, and mixed reality are transforming service experiences by enabling multisensory digital environments. The focus is on understanding how visual, auditory, haptic, olfactory, and gustatory cues interact within these environments to shape customer perception and behavior across different stages of the customer journey.

Research on sensory marketing demonstrates that consumers process sensory information through cross-modal interactions rather than in isolation. While immersive technologies hold significant potential for creating rich multisensory experiences, existing research has primarily focused on audio-visual features, leaving a gap in understanding how diverse sensory stimuli collectively influence customer perceptions and value creation throughout their journey.

Appel publié par Journal of Service Theory and Practice. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Sensory-enabled immersive service experiences across the customer journey
• Multisensory cue interaction and cross-modal congruence in immersive services
• Role of immersive technologies, including VR, AR, and MR, as strategic service touchpoints
• AI-enabled adaptation, personalization, and orchestration of multisensory stimuli
• Generative AI and learning systems in immersive service design and delivery
• Customer perceptions, emotions, intentions, and real behaviors in immersive services
• Value creation and value co-creation through multisensory immersive services

Timeline

• January 9, 2026: Opening date for manuscripts submissions
• December 15, 2026: Closing date for manuscripts submission

Enrico Battisti, University of Turin

Francesco Schiavone, University Parthenope

Digital transformation, artificial intelligence, and sustainability pressures are reshaping how entrepreneurs access capital and how value is created and financed. These changes have created new financing mechanisms while raising questions about equity and access to funding for small businesses and startups, particularly regarding collateral, legitimacy, and institutional visibility.

The special issue addresses emerging financing channels such as crowdfunding, peer-to-peer lending, and tokenized assets, while emphasizing that financial decisions are influenced by behavioral, social, institutional, and sustainability factors beyond technical considerations. Artificial intelligence is a key focus, as it transforms credit evaluation, investment screening, and venture creation, affecting SMEs' access to finance and requiring interdisciplinary approaches.

Appel publié par Journal of Small Business and Enterprise Development. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Environmental and Social Disclosure in SMEs: Implications for Access to Capital, Investor Relations, and Financial Performance
• Access to Capital and Financing Decisions in SMEs: Behavioral, Cognitive, and Psychological Determinants
• Entrepreneurial Finance and Social Inclusion: Gender, Ethnicity, and Geography as Structural Barriers to Capital Access
• Financial Reporting, Intangible Assets, and Creditworthiness in Innovative Small Businesses
• Regulatory Frameworks and Institutional Conditions for Entrepreneurial Finance Across National Contexts
• Alternative Financing Mechanisms: Crowdfunding, Peer-to-Peer Lending, and Tokenized Assets: Financial Performance and Social Implications
• AI-Driven Financial Decision-Making: Credit Scoring, Risk Modeling, and Investment Screening for Small Businesses
• The Financial Implications of AI-Powered Venture Creation: Resource Mobilization, Capital Structure, and Legitimacy in Platform-Based Startups

Timeline

• January 4, 2027: Opening date for manuscript submissions
• April 30, 2027: Closing date for manuscript submissions

Organizations face increasing complexity from shifting geopolitical, economic, and technological conditions, requiring strategic approaches to knowledge management for sustainability. The integration of knowledge management with AI offers potential benefits for problem-solving and decision-making, yet presents challenges that require responsible and ethical implementation. This special issue examines how organizations can leverage strategic knowledge management to balance the opportunities and risks of AI while maintaining sustainability across their operations.

The call seeks contributions exploring how organizations can effectively manage both human knowledge and AI-generated intelligent knowledge, addressing issues such as knowledge overload, loss, and duplication. It emphasizes the importance of codification and personalization strategies that align with organizational values and objectives. The special issue invites researchers to examine how sustainable strategic knowledge management enables organizations to adapt to rapidly changing environments while achieving economic, social, and environmental goals.

Appel publié par Journal of Strategy and Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Knowledge management processes and sustainability in organizations
• Human-AI synergy and responsible AI use in knowledge systems
• Strategic knowledge management for organizational decision-making and problem-solving
• Managing explicit and tacit knowledge in digital environments
• Knowledge codification and personalization approaches
• Addressing knowledge overload from AI, cloud computing, and big data
• Sustainable knowledge-based organizations and resource optimization
• AI's impact on critical knowledge management processes
• Ethical and mission-aligned strategic knowledge for financial, social, and ecological benefits
• Knowledge management in complex organizational environments and geopolitical uncertainty

Timeline

• January 8, 2026: Opening date for manuscripts submissions
• October 31, 2026: Closing date for manuscripts submission

Pham Van Hau, Unitec Institute of Technology

Carolyn Strong, Cardiff University

Park Thaichon, University of Southern Queensland

This special issue focuses on the emerging intersection of artificial intelligence and sustainable marketing. AI technologies like machine learning and predictive analytics are rapidly transforming marketing practices, while sustainability challenges demand new approaches to shift consumption patterns and market systems. The special issue seeks research examining how AI-driven marketing influences sustainability outcomes at individual, organizational, and system-wide levels.

The integration of AI in marketing presents both opportunities and challenges for sustainability. AI tools can enable personalized sustainability nudges, improve resource efficiency, and support circular economy initiatives. However, concerns include algorithmic bias, privacy issues, transparency challenges, and the risk of reinforcing unsustainable consumption through hyper-personalized marketing. Understanding these dynamics is critical to ensure AI contributes positively to sustainable futures rather than exacerbating environmental and social challenges.

Appel publié par Journal of Strategic Marketing. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI nudging and recommender systems that encourage sustainable choices
• Consumer perceptions, trust, and acceptance of AI-enabled sustainability initiatives
• AI-driven segmentation for targeting sustainable consumption behaviours
• AI insights supporting sustainable product innovation and development
• AI applications in sustainability branding and communication
• Personalised marketing and its influence on responsible consumption
• Predictive analytics for reducing waste and overproduction
• AI-enabled platforms supporting reuse, repair, sharing, and circular consumption
• Transparency, fairness, and accountability in AI-driven marketing systems
• Consumer privacy and data ethics in sustainability-focused marketing
• Governance frameworks for responsible AI use in marketing
• Generative AI and sustainability communication
• Digital platforms enabling collaborative or sustainable consumption
• AI shaping sustainability narratives and consumer engagement
• Interactions between individual behaviour change and system-level transformation
• Policy and regulatory responses to AI-driven sustainability initiatives
• Cross-cultural perspectives on AI-enabled sustainability practices
• Role of generative AI in sustainability communication and storytelling
• Risks of misinformation or greenwashing through generative AI
• Consumer responses to generative AI–generated sustainability content
• Use of generative AI in sustainable product design and innovation

Timeline

• October 30, 2026: Manuscript deadline

Sara Wilkinson, University of Technology Sydney

Johnny Wong, University of Technology Sydney

Biyanka Ekanayake, University of Technology Sydney

This special issue examines how artificial intelligence is transforming the built environment across construction, real estate, facilities management, and urban planning. While AI technologies offer significant opportunities for innovation and efficiency through applications like energy optimization, smart building control, and predictive maintenance, the sector faces critical challenges regarding data integrity, algorithmic bias, privacy, and transparent decision-making.

The special issue seeks high-quality original research exploring AI's use, impact, risks, and future potential in the built environment. It welcomes contributions spanning construction automation, property valuation, smart buildings, urban planning, generative design, AI governance and ethics, sustainability applications, security systems, human-AI collaboration, and professional education in AI.

Appel publié par Building Research & Information. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI in construction: automation, robotics, quality control, progress monitoring, risk and safety analytics
• AI in property and real estate: valuation models, market intelligence, customer engagement, asset management, predictive analytics
• Smart buildings and facilities management: IoT-enabled optimisation, energy management, predictive maintenance, AI-driven knowledge systems
• AI in urban planning and infrastructure: spatial modelling, forecasting, environmental assessment, transport and mobility analytics
• Design and engineering applications: generative design, simulation, optimisation, digital twins, parametric modelling
• Explainable AI (XAI): AI governance, ethics, and regulation: transparency, bias, data integrity, privacy, and responsible GenAI in the built environment
• AI for sustainability and ESG: carbon modelling, resource optimisation, lifecycle assessment
• Security and risk management: computer vision for surveillance, access control, anomaly detection
• Multimodal and agentic AI: advanced AI systems applied to complex built environment challenges
• Human-AI collaboration: professional adoption, skills, workflows, and organisational change
• The challenge of educating and training built environment professionals in AI

Timeline

• September 30, 2026: Deadline for submission
• December 31, 2026: Deadline for review
• February 28, 2027: Deadline for revised submission
• April 30, 2027: Deadline for approval final manuscript

Yanmin He, Otemon Gakuin University

Xikai Chen, California State University

Dongyang Zhang, Capital University of Economics and Business

This special issue addresses how digital technologies, institutional environments, and governance mechanisms interact to shape firm behavior and market evolution. Contemporary firms face complex transformations driven by digitalization and artificial intelligence alongside institutional frictions such as regulatory uncertainty and financing constraints. The special issue seeks to integrate fragmented research streams on digital transformation, corporate governance, and institutional dynamics to develop a more comprehensive understanding of firm-level adaptation in emerging markets.

The call welcomes submissions exploring how digital governance frameworks, enterprise transformation, and corporate governance mechanisms jointly influence innovation and firm competitiveness. Research may examine topics including digital transformation strategies, artificial intelligence adoption, corporate governance structures, institutional frictions affecting finance and trade, geopolitical impacts, and new measurement approaches. Submissions should make significant theoretical or empirical contributions to understanding emerging market dynamics.

Appel publié par Emerging Markets Finance and Trade. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Digital governance, regulation, and corporate adaptation
• Data governance, cybersecurity, and privacy protection
• Corporate digital transformation
• Artificial intelligence, Intelligentization, and organizational upgrading
• Corporate governance and strategic adaptation in emerging markets
• Corporate governance, finance, and trade under institutional frictions
• Institutional frictions, digital finance, and firms' access to capital
• Geopolitical uncertainty and firms' strategic reconfiguration
• New trends in innovation, productivity, and value creation
• ESG, sustainability, and responsible governance
• Cross-country differences in technology institutions, and governance
• Alternative data and new measurement approaches

Timeline

• August 1, 2026: Special issue linked symposium
• December 31, 2026: Manuscript submission deadline

Boyu Lin, Macao University of Tourism

Jinwei Wang, Beijing International Studies University

Hongwen Chen, Nanchang University

Xin-Jean Lim, Universiti Putra Malaysia

This special issue examines how artificial intelligence is reshaping tourism planning and development across the Asia-Pacific region. Rather than focusing narrowly on technological efficiency, the call addresses broader transformations in destination governance, spatial flows, and how communities benefit from intelligent tourism systems. The collection seeks critical, theoretically informed research that explores the social, environmental, cultural, and economic implications of AI adoption in tourism contexts.

The Asia-Pacific region offers a particularly valuable setting for this inquiry due to its diversity: advanced smart cities coexist with rural destinations and climate-vulnerable communities, creating uneven experiences of AI-driven transformation. The region simultaneously faces urgent development challenges including overtourism, environmental pressures, and inequality, while becoming a global laboratory for experimental intelligent tourism systems. This context makes the region essential for understanding both opportunities and risks of AI-mediated tourism change.

Appel publié par Tourism Planning & Development. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Generative AI and Tourism Planning Future
• Agentic AI and Autonomous Tourism Management Systems
• Platformization and Algorithmic Governance
• AI-mediated Trip Planning and Tourist Mobility
• AI-mediated Labor and Socioeconomic Transformation
• AI Adoption and Sustainable Tourism Development
• AI-driven Reconfiguration of Tourism Planning
• AI-driven Tourism Business Innovation in Regional Development

Timeline

• May 30, 2027: Manuscript deadline

Reem Khamis Hamdan, The University College of Bahrain

Marketing has evolved beyond economic value creation to encompass broader social impacts, particularly as digital technologies like artificial intelligence and big data become deeply embedded in society. These advancements enable marketing strategies that influence not only consumer behavior but also societal values and well-being, raising critical questions about ethical implications and power dynamics that remain underexplored in academic literature.

This special issue invites research examining how strategic marketing enabled by technology reshapes society and the accompanying ethical and power concerns. The editors seek both theoretical and empirical contributions that illuminate the relationship between marketing strategies and society, with particular emphasis on ethical issues, power imbalances, and societal consequences of marketing in digital environments.

Appel publié par Journal of Strategic Marketing. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Ethical concerns of AI marketing
• Bias and fairness of marketing algorithms
• Digital surveillance and the privacy of consumers
• Power relations and manipulation of consumers by digital marketing
• Social responsibility of influencer marketing
• Mental health/well-being of consumers
• Multidisciplinary marketing and digital inequality
• Power of platforms over consumers
• Social responsibility of marketing and ESG
• Multidisciplinary marketing of brands
• Multidisciplinary marketing in vulnerable communities
• Multidisciplinary marketing of technology and the transformation of the identity of consumers
• Multidisciplinary marketing of the attention economy
• Multidisciplinary marketing strategies during social crises/uncertainty

Timeline

• October 26, 2026: Manuscript deadline

Bryan T. McLeod, University of North Carolina at Pembroke

Jose Saavedra Torres, Northern Kentucky University

This special issue addresses how artificial intelligence is transforming marketing strategy education. As AI becomes increasingly integrated into marketing practice, educators must reconsider teaching approaches to prepare students for careers where human judgment and AI collaboration are central. The issue invites research on redesigning strategy courses, integrating AI into curriculum and pedagogy, and identifying how students can develop critical thinking and decision-making skills alongside AI literacy.

Submissions may include empirical research, conceptual articles, case studies, and pedagogical innovations examining opportunities and challenges of AI integration in marketing strategy courses. The scope encompasses curriculum redesign, experiential learning with AI, assessment methods in AI-enhanced environments, and faculty perspectives on teaching strategy with emerging technologies.

Appel publié par Marketing Education Review. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Redesigning the marketing strategy course for the age of AI
• Integrating AI throughout the strategic marketing planning process
• Teaching AI literacy within marketing strategy courses
• The evolving role of marketing strategy within the marketing curriculum
• Preparing students for AI-enabled marketing careers
• Balancing traditional marketing concepts with emerging AI technologies
• Teaching strategic thinking in AI-enhanced learning environments
• AI-assisted environmental scanning and situation analysis
• AI applications for SWOT analysis
• AI-assisted market segmentation, targeting, and positioning
• Competitive analysis using AI
• AI-supported strategic forecasting
• Teaching students when to rely on AI and when managerial judgment should prevail
• Human creativity and intuition in AI-supported strategy development
• AI-enhanced consulting projects
• Client-based learning using AI
• AI-generated marketing simulations
• AI-supported business competitions
• AI throughout the development of marketing plans
• AI-assisted strategic decision-making exercises
• Experiential learning that combines human judgment with AI capabilities
• Assessing strategic thinking in AI-supported classrooms
• Authentic assessments in marketing strategy education
• Oral defenses of AI-assisted marketing plans
• Measuring creativity and higher-order thinking in AI-enhanced environments
• Student perceptions of AI in marketing strategy courses
• AI's influence on strategic reasoning and decision quality
• Academic integrity within AI-supported strategy courses
• Faculty adoption of AI within marketing strategy instruction
• Best practices for integrating AI into capstone marketing courses
• Faculty perceptions of AI's impact on student learning
• Challenges associated with teaching marketing strategy in AI-rich environments
• The future role of the marketing strategy course
• Skills and competencies required of future marketing strategists
• Employer expectations for graduates entering AI-enabled organizations
• The relationship between AI, strategic thinking, and managerial decision making
• Human-centered competencies that remain essential despite advances in AI
• Emerging research directions related to marketing strategy education and AI

Timeline

• February 15, 2027: Manuscript submission deadline

Jhih-Syuan (Elaine) Lin, National Chengchi University

Chen Lou, Nanyang Technological University

This special issue examines influencer advertising as an evolving interactive system shaped by technological advances, platform algorithms, and changing consumer expectations. The field has shifted from viewing influencers as isolated persuasion sources to understanding them as components within human-machine systems where outcomes emerge from interactions among influencers, platforms, algorithms, and audiences.

The special issue addresses both opportunities and risks in influencer advertising. While new technologies enable brand engagement, influencer advertising also presents boundary conditions and unintended consequences, including concerns about deceptive practices, consumer vulnerability, and well-being impacts, particularly within increasingly AI-mediated ecosystems.

The journal invites original research that theoretically and empirically examines how and when influencer advertising succeeds or fails, with particular emphasis on work integrating contemporary technological contexts and rigorous methodology across consumer behavior, technology innovation, industry development, negative effects, and global trends.

Appel publié par Journal of Interactive Advertising. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• eWOM, social proof, and interactive persuasion dynamics in influencer advertising
• Persuasion processes and boundary conditions
• Emotional engagement, (trans)parasocial interaction, and relational dynamics in influencer content
• Trust, authenticity, and credibility calibration across influencer types
• Unintended and counter-persuasive effects
• AI-mediated and synthetic persuasion agents
• Immersive and extended realities in influencer advertising
• Platform affordances and algorithmic amplification of influencer content
• Interactive commerce and creator-led retail ecosystems (e.g., live streaming, social shopping, short-form video)
• Influencer advertising as a profession and creator-economy dynamics
• Disclosure, regulation, and governance as interactive design challenges
• Measurement, attribution, and performance evaluation in influencer advertising
• Brand–influencer–platform–AI relationship management and governance
• The dark side of interactive and AI-mediated influencer persuasion
• Influencer fatigue, burnout, and long-term relational consequences
• Consumer vulnerability, well-being, and societal implications
• Long-term influencer partnerships in interactive and AI-enabled media
• Influencers, activism, and social or political causes
• Diversity, representation, and inclusion in influencer advertising
• Global and non-Western contexts as theory-generating sites
• Future directions in hybrid, immersive, and automated influencer campaigns

Timeline

• December 31, 2026: Manuscript deadline

This special issue in Industrial Marketing Management explores how artificial intelligence and social media are reshaping B2B marketing landscapes. The focus is on understanding the transformative impact of these technologies on business relationships, organizational capabilities, and the mechanisms through which value is created in B2B contexts.

Appel publié par Industrial Marketing Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• April 1, 2027: Full paper submission deadline

Appel publié par Journal of Management Studies. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• May 3, 2027: Full paper submission deadline

Robert Davison, City University of Hong Kong

Philip Wu, Royal Holloway, University of London

Ajay Kumar, Emlyon Business School

Efpraxia Zamani, Durham University

Artificial intelligence is rapidly transforming work and labour across organizations and sectors. This special issue moves beyond polarized narratives to examine how AI is reshaping workplace experiences, organizing labour, and affecting workers. Drawing on Information Systems' sociotechnical tradition, the call invites rigorous research examining the complex interplay between technology, organizations, and workers.

The special issue addresses significant gaps in current research, particularly invisible labour like data labelling concentrated in the Global South, care work in undervalued sectors, and how AI may exacerbate or mitigate workplace inequality. It welcomes contributions examining worker agency, identity, skill development, voice in AI-augmented environments, and governance challenges posed by self-evolving AI systems.

Appel publié par Information Systems Journal. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Compared to previous generations of information systems, how do new AI technologies reshape the distribution, delegation, performance, and evaluation of work tasks, and with what consequences for workers?
• How does working with AI tools alter the trajectories of learning, skill development, and professional identity formation among workers?
• How do workers make sense of AI-induced changes to their work, and how do they negotiate new spaces for meaning, agency, creativity, and identity in AI-augmented environments?
• Whose labour makes AI systems work and what does its erasure from dominant narratives of AI-augmented work reveal about how value, skills and visibility are constructed?
• How does the adoption of AI relate to workplace inequality within and across organisations, occupations, and sectors, and how are such inequalities manifested differently across the Global North and South?
• How do GenAI and emergent agentic AI reconfigure material and human agencies in the workplace, and what new theoretical frameworks are needed to account for their dynamic, self-evolving character?
• What does the growing capacity of AI agents to learn, adapt, and make consequential decisions mean for accountability, responsibility, and the governance of work outcomes?
• As AI becomes increasingly embedded in organisational routines, what conditions give rise to over-reliance, automation bias, and the erosion of human oversight and professional judgement?

Timeline

• January 31, 2027: Submission Deadline

Associate editors

• Petros Chamakiotis, ESCP Business School
• Alain Chong, University of Nottingham Ningbo
• Riitta Hekkala, Aalto University
• Yong Liu, Aalto University
• Ulrich Remus, University of Innsbruck
• Pauline Weritz, University of Twente
• Melody Zou, Warwick Business School

Tony Fang, Memorial University

Jennifer A. Harrison, EM Normandie Business School

Artificial intelligence is reshaping organizations by reconfiguring task structures, skill requirements, and managerial processes. Rather than eliminating jobs, AI adoption fosters new occupational roles and redefines expertise through changed patterns of human-AI collaboration. These developments promise to enhance productivity, though realizing these gains depends critically on the human skills that enable effective technology use.

The concept of skills varies significantly across disciplines, from labour economics viewing skills as human capital to organizational psychology emphasizing cognitive capabilities and sociology examining how skills are socially constructed. This fragmented understanding limits integrated knowledge about how AI shapes skills and productivity. The call seeks to bridge these perspectives by examining how skills are identified, defined, and valued in relation to AI, and how they translate into productivity gains across contexts.

Appel publié par Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI adoption and implementation in organizations, including how skills are identified, defined, measured, valued, and linked to productivity
• Human and AI collaboration, work transformation, and the identification and use of skills in changing task contexts
• Defining and developing skills in workplaces using AI (e.g., reskilling, upskilling, lifelong learning) and linking to productivity
• Changes in occupations, expertise, and professional roles, and how skill requirements are defined and evolving with AI
• Organizational and institutional factors shaping how skills are identified, defined, and managed in relation to AI and productivity (e.g., leadership, HR practices, policy contexts)
• Career sustainability, mobility, and inequality in labour markets shaped by AI, with a focus on how skills are defined, accessed, and valued

Timeline

• December 15, 2026: Submission Deadline

Ilan Alon, Ariel University

Marcin Wątorek, Cracow University of Technology

Aušrinė Šilenskytė, University of Vaasa

Ziaul Haque Munim, University of South-Eastern Norway

Organizations increasingly manage distributed decision-making and systemic complexity through blockchain technologies that function as operating systems by embedding governance mechanisms into digital infrastructures. These systems are being advanced with artificial intelligence to monitor and shape behavior. Despite blockchain-based operating systems being adopted in platforms, supply chains, and decentralized autonomous organizations, their implications for organizational administration, governance, and control remain poorly understood.

This special issue invites research that advances administrative and organizational understanding of blockchain-based operating systems with AI-enabled complexity. The call welcomes theoretically grounded, methodologically rigorous contributions including empirical studies and theory-building papers that offer clear organizational insights and engage meaningfully with blockchain and AI as organizational infrastructures.

Appel publié par Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Blockchain as an organizational operating system and potential of AI advancements in it
• Public, private, and hybrid organizations adopting blockchain OS with AI advancements
• Integration of AI on Blockchain OS in crowdsourcing platforms, crypto exchanges, fintech firms, energy management, and transport services etc.
• Organizational decision-making in blockchain-based and AI enabled systems
• AI's role in administrative functions embedded in smart contracts and protocols
• Token-based incentives as administrative and managerial mechanisms
• Strategic control and accountability in decentralized platforms with AI-enabled advancements
• AI integration in governance, coordination, and control without centralized authority (DAOs)
• Complexity, emergence, and adaptation in blockchain-based and AI enabled organizations
• Organizational legitimacy, regulation, and institutional alignment in AI and blockchain OS integrations
• Ethical, responsible, and sustainable administration of blockchain systems, especially those advanced with AI

Timeline

• November 15, 2026: Submission Deadline

Petter Nielsen, University of Oslo

Laura Brandimarte, University of Arizona

Ben Eaton, Copenhagen Business School

Juliana Sutanto, Monash University

Mary Tate, Victoria University of Wellington

Daniel Veit, University of Augsburg

This special issue addresses digital sovereignty—the capacity of actors at individual, community, organizational, or national levels to make informed choices about sourcing, designing, and governing digital systems while avoiding dependency risks. The field encompasses concerns about data governance, platform reliance, interoperability, and AI transparency, reflecting growing political momentum globally from regions like the EU, Denmark, and China.

While digital sovereignty has attracted attention across policy, philosophy, and law, information systems research remains underdeveloped despite offering valuable socio-technical perspectives. This call seeks empirically grounded and theoretically ambitious research that explains digital sovereignty as a socio-technical accomplishment, including its tensions and trade-offs, alongside conceptual and review papers.

The special issue welcomes both qualitative and quantitative contributions that foreground digital technologies in context, drawing from relevant information systems research on infrastructures, digital innovation, platform governance, open-source solutions, and human-AI relationships.

Appel publié par Information Systems Journal. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Conceptual and theoretical foundations of digital sovereignty in information systems and its unique properties compared to other conceptualizations of sovereignty
• Critical investigations of the sovereignty paradox – the sacrifice of sovereignty for the utility and efficiency of big-tech, related to path dependencies, shadow sovereignty and exit strategies
• The exercise of power by dominant players and its impact
• The specific sovereignty challenges of digital infrastructure, platforms, AI and other emerging technologies such as quantum computing
• Sovereignty-by-design: interoperability, standards, modularity, API governance, devolved, horizontal and open architectures
• Open-source, digital public goods, and open data commons as strategies for autonomy, resilience, and public value
• AI for managing sovereign digital infrastructures
• Global, regional and local governance, regulation and policy regarding data, platforms and infrastructures, and governance models
• Public sector digital sovereignty, including procurement, vendor lock-in, interoperability and capability building
• Surveillance, digital identity, biometrics, and the sovereignty implications for rights and democratic accountability
• Digital sovereignty in development and "post-aid" contexts: shifting dependencies, infrastructures at scale, and long-term sustainability
• Indigenous and minority groups disadvantaged by colonisation value sovereignty, especially over their data, including protection from misuse, responsible stewardship, and maintaining integrity
• Managing capability, skills, and technology gaps and deficits
• Managing choke points in critical technical layers
• Managing national policy alignment

Timeline

• March 31, 2027: Submission Deadline

Associate editors

• Tawfiq Alashoor, University of Navarra
• Armin Alizadeh, Technical University of Darmstadt
• Pierre-Emmanuel Arduin, Université Paris Dauphine-PSL
• Irwin Brown, University of Cape Town
• Jen Dailo Chandler, California State University
• Wonhyuk Cho, Ewha Womans University
• Jacqueline Corbett, Université Laval
• Tingru Cui, University of Melbourne
• Torgeir Dingsøyr, Norwegian University of Science and Technology
• Andreas Drechsler, Victoria University of Wellington
• Daniel Gozman, University of Sydney
• Agam Gupta, IIT Delhi
• Riitta Hekkala, Aalto University
• Federico Iannacci, University of Sussex
• Alexander Kempton, University of Oslo
• John Krogstie, Norwegian University of Science and Technology
• Shi-Ying Lim, National University of Singapore
• Shirin Madon, LSE
• Johan Magnusson, University of Gothenburg
• Antonio Martini, University of Oslo
• Silvia Masiero, University of Oslo
• Eric Monteiro, Norwegian University of Science and Technology
• Priyanka Pandey, King's College
• Roser Pujadas, University College London
• Alexander Rieger, University of Arkansas
• Tamara Roth, University of Arkansas
• Hanlie Smuts, University of Pretoria
• Timo Sturm, Technical University of Darmstadt
• Ruonan Sun, Monash University
• Johan Ivar Sæbø, University of Oslo
• Benjamin van Giffen, University of Lichtenstein
• Marjolein van Offenbeek, University of Groningen
• Will Venters, LSE
• Pauline Weritz, University of Twente
• Amber Young, University of Oklahoma
• Xiaojie Zhang, Ocean University of China
• Markus P. Zimmer, University of Agder

Kim Ceulemans, TBS Business School

Lotfi Karoui, ISC Paris

Agota Szabo, VU Amsterdam

Wafa Khlif, TBS Business School

Organizations increasingly rely on AI for consequential decisions across hiring, credit, and compliance. Yet governance frameworks designed for human-centered processes struggle to address distributed, opaque systems operating at unprecedented scale and speed. Traditional oversight mechanisms—boards, audit committees, regulators—were not built to govern technologies that challenge assumptions about accountability and responsibility.

This special issue examines how corporate governance frameworks can evolve to address AI's organizational implications. Rather than treating governance as purely technical, the issue emphasizes that governance shapes whose interests matter and how accountability is defined. The call seeks research exploring the mismatch between rapid, complex AI-enabled decision-making and slower institutional oversight.

Appel publié par Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Board oversight of AI, algorithmic risk, and digital infrastructures
• Fiduciary duty, corporate purpose, and stakeholder accountability in AI-intensive firms
• AI, sustainability, and the governance of social and environmental impacts
• Algorithmic management, the organization of labour, and workplace surveillance
• Audit, assurance, internal control, and the challenge of model opacity
• AI regulation, soft law, and the organizational translation of legal requirements
• Data governance, data ownership, and cross-border accountability
• Bias, discrimination, and issues related to classification, prediction, and fairness in AI systems
• Human oversight, contestability, and the limits of explainability
• AI in public administration, welfare systems, healthcare, policing, and education
• The role of AI in sensitive or high-impact contexts, including security, defense, and critical infrastructures
• Alternative and plural governance models for responsible AI
• Stakeholder participation, oversight, and engagement in AI governance

Timeline

• December 25, 2026: Submission deadline

David G. Collings, Trinity College Dublin

Jason L. Huang, Michigan State University

Dongyuan Wu, Fudan University

Patrick E. Downes, University of Kansas

This special issue examines how artificial intelligence, data analytics, and digital platforms fundamentally reshape talent management. Rather than treating technology as a support tool, it emphasizes technology as a central force that challenges traditional understandings of talent conceptualization, performance measurement, and value creation. The issue welcomes conceptual and empirical research on how technology influences talent identification, development, and deployment.

The call addresses three themes: how technology reshapes talent practices through AI-driven systems and remote work, ethical challenges such as bias and employee burnout, and the shift toward skills-based hiring. Organizations struggle to integrate technology into talent practices effectively and equitably, creating opportunities and risks that require scholarly attention.

Intended for human resource management and organizational behavior researchers and practitioners, this call seeks contributions advancing theoretical understanding of technology's role in modern talent systems while addressing practical concerns around implementation, ethics, and strategic coherence.

Appel publié par Human Resource Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How does technology reshape the nature of exceptional performance and how organizations define and measure high-performance and high-potential?
• What are the implications of technology for how individuals generate exceptional value in organizations?
• How does technology interact with employee KSAOs in the generation of exceptional value?
• How does technology alter the distribution and visibility of exceptional performance in organizations?
• What does agentic AI mean for the composition and performance of teams?
• Are traditional measures and understandings of high-potential still relevant in the context of emerging technological trends?
• How are companies using technology to shape talent-related expectations and outcomes?
• How do organizations design tech-enabled talent processes that shape the experiences of high-performing and high-potential employees?
• What role do digital tools play in fostering engagement, perceived justice, well-being, and retention of high-performing employees and individuals in pivotal roles?
• How do organizations adapt to ensure technological advancements enhance, rather than hinder, strategic talent strategies?
• How does technology reshape the role, authority, and activities of HR professionals in talent management?
• How can HR professionals play a leadership role and strike a balance between what technology can do and what technology should do in talent-related decision-making?
• How can organizations leverage AI and digital tools to reduce administrative burdens while improving talent outcomes?
• How do HR teams utilize efficiencies to focus on more strategic activities related to talent identification, development, and deployment?
• How can organizations manage the balance between technology and human judgment in talent management?
• How do companies integrate AI and automation without compromising the human aspects of leadership, decision-making, and talent evaluations?
• How does technology impact the emergence of expertise in organizations?
• How does technology impact the nature of performance distribution and the identification and management of critical roles in organizations?
• How can organizations transform their approaches to talent planning, attraction, and activation to address skill scarcity?
• What is the effectiveness of a skills-based hiring approach in recruiting talent for pivotal roles, and can rapid on-the-job training and reskilling better fill talent gaps?
• How do companies navigate skill gaps and talent reskilling in fast-changing industries?
• How does technology facilitate internal mobility and the dynamic recomposition of capabilities over time?
• How can digital platforms and algorithmic management enhance visibility into employees' skills and career aspirations?
• How can companies create and better utilize internal talent marketplaces to support career transitions and the allocation of talent to critical roles?
• What role does technology play in skills matching and identifying development pathways for high-potential employees in organizations?
• How can organizations effectively manage hybrid and nonstandard work arrangements as part of broader talent systems?
• What role does technology play in managing dispersed teams, ensuring productivity, and fostering collaboration among strategically valuable contributors?
• What challenges arise from integrating different employment models, and how can organizations optimize the experience and retention of talent across organizational boundaries?
• How can organizations ensure that talent continues to support the development of colleagues through knowledge transfer and mentoring in dispersed work contexts?
• How can organizations create talent systems that support experimentation with new tools and processes?
• What cultural and leadership factors influence an organization's ability to adapt to technological change in talent-related practices?
• How can businesses cultivate a mindset of continuous improvement and openness to innovation rather than resistance to change?
• How can organizations ensure that technology-enabled talent management promotes fairness, transparency, and inclusion while safeguarding ethical standards?
• How do organizations mitigate the potential that technology introduces bias into talent management, and how can organizations mitigate these risks?
• How can HR leverage AI and data analytics to drive more equitable talent identification, development, and deployment practices?
• How can organizations safeguard ethical principles related to privacy, transparency, data security, and algorithmic accountability in talent decisions?

Timeline

• March 1, 2027: Submission window opens
• March 31, 2027: Submission deadline

Raffaele Filieri, Audencia Business School

Elmira Djafarova, Northumbria University

Margot Racat, IDRAC Business School

Veronika Keller, Szechenyi Istvan University

Rickard Enstroem, MacEwan University

Social media influencer marketing faces uncertainty amid algorithm fatigue, regulatory scrutiny, declining consumer trust, and AI-generated influencers. Traditional theoretical frameworks struggle to explain how AI content, algorithmic curation, and synthetic personas reshape influence dynamics.

This special issue examines whether traditional influencer marketing is ending or undergoing paradigm shift in how influence is constructed, monetized, and governed. It explores how authenticity, artificial intelligence, and algorithmic mediation intersect to reshape influence practices while addressing emerging regulatory frameworks.

The issue welcomes empirically grounded contributions from multiple disciplines including strategy, media studies, consumer behavior, and technology management. It particularly encourages interdisciplinary, globally inclusive research examining non-Western contexts, emerging platforms, and underrepresented influencer communities.

Appel publié par Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Trust, credibility, and authenticity in digital influence
• Algorithmic mediation, platform governance, and market structure
• Consumer resistance, fatigue, and agency
• Virtual influencers, AI, and synthetic content
• Cultural, generational, and global perspectives on influence
• Professionalization, labor, and monetization in the creator economy
• Ethics, power, and the dark side of influencer marketing
• Expanding contexts of influence in B2B, nonprofit, and public sectors
• Strategic navigation of platforms, algorithms, and AI tools across global-local digital markets
• Authenticity and trust negotiation in activism, sustainability, and cause-related marketing

Timeline

• December 31, 2026: Submission Deadline
• March 1, 2027: Final Decisions and Revisions

Yanto Chandra, City University of Hong Kong

Greta Nasi, Bocconi University

Jiasheng Zhang, Chinese University of Hong Kong

This special issue examines the negative consequences of AI adoption in public organizations, particularly how algorithmic systems can amplify existing inequalities and undermine democratic governance. The call recognizes that while AI offers potential improvements to service delivery, the benefits are unevenly distributed globally, with marginalized populations facing heightened risks related to biased datasets, algorithmic discrimination, and erosion of accountability.

The special issue seeks theoretical and empirical scholarship reconsidering how public administration frameworks must evolve to address AI-related challenges. Scholars are invited to investigate systemic downsides including workforce displacement, economic inequality, and uneven global access to AI innovations, as well as how governance mechanisms can embed fairness, transparency, and inclusiveness to protect democratic values and serve the public interest.

Appel publié par Public Administration and Development. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• North vs South disparities in AI access and innovation
• Exploitation of labor in AI data collection and platform economies
• Human rights implications of AI-driven decision-making
• Accessibility to public services
• The role of AI systems in perpetuating or challenging gender, racial, and cultural discrimination in public administration and welfare policies
• Experiments on how citizens respond to diversity, inclusion and equity issues in the increasing use of AI by governments
• Influence of dominant languages in AI training and its impact on linguistic diversity
• How minority languages of the world can maintain their survival in the age of AI
• Embedding fairness, transparency, and accountability into AI systems
• Legal and regulatory frameworks for responsible AI deployment

Timeline

• April 1, 2026: Call for Papers published
• September 1, 2026: Hybrid (online and offline) workshop in Hong Kong
• November 1, 2026: Online workshop or in-person workshop in Italy
• January 1, 2027: Full papers submitted
• April 1, 2027: Peer reviews completed
• October 1, 2027: All resubmissions completed
• December 1, 2027: Final reviews completed
• March 1, 2028: Final publication of all articles

Joon Mo Ahn, Korea University

Alberto Di Minin, Scuola Superiore Sant'Anna

Sungjoo Lee, Seoul National University

Ahreum Hong, Kyung Hee University

This special issue addresses how artificial intelligence systems function as autonomous innovators rather than tools within R&D management. As AI systems including large language models and physical AI become active participants in innovation processes, existing frameworks assuming human actors must be reconceptualized. The core challenge extends beyond how AI assists humans to how much cognitive work should be delegated to AI and what consequences this has for organizations, ecosystems, and intellectual property.

The special issue examines four interconnected themes: determining optimal levels of AI delegation; understanding how agentic and physical AI reshape innovation ecosystem architectures as autonomous actors; reconceptualizing absorptive capacity for evaluating AI-generated knowledge; and addressing IP ownership and inventorship when non-human systems generate patentable outputs. Collectively, these themes interrogate how the distinction between AI-as-tool and AI-as-innovator requires new governance mechanisms and strategic frameworks for innovation management.

Appel publié par R and D Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Is there an inverted-U relationship between the degree of AI delegation in R&D and innovation performance, mirroring the over-search paradox?
• How do firms determine the optimal breadth and depth of AI involvement across different stages of the R&D process? Specifically, under what conditions does algorithmic management enhance or hinder innovation performance?
• What is the AI-era analogue of the NIH syndrome: how does uncritical acceptance of AI-generated knowledge erode internal expertise?
• What governance architectures enable effective human–AI teaming while preserving accountability, creativity, and strategic judgment?
• How do agentic AI systems alter the architecture of knowledge flows in open innovation ecosystems, and what new governance mechanisms are required?
• How does the participation of autonomous AI agents change the logic of platform-based open innovation, including roles, incentives, and boundary conditions?
• How do digital twins and AI-enabled simulation reshape the scope and speed of distributed experimentation across organisational boundaries?
• What new forms of inter-organisational trust, contracting, and coordination are needed when AI agents act as innovation partners?
• How must absorptive capacity (or dynamic capabilities) be reconceptualised when the primary external knowledge source is an AI system rather than a human partner?
• What organisational routines and managerial processes enable firms to transform AI-generated knowledge into innovation value?
• What individual competencies — technical, cognitive, and relational — distinguish high-performing innovators in human–AI contexts?
• What learning mechanisms allow firms to continuously upgrade AI-related innovation capabilities over time, particularly in relation to exploration and exploitation?
• How should inventorship and IP ownership be attributed when agentic AI systems autonomously generate patentable outputs, and what theoretical frameworks from open innovation research best capture this challenge?
• What strategic logic governs firms' decisions to release model weights, training data, or fine-tuned AI capabilities into open-source commons?
• How do trained model weights, fine-tuning data, and emergent AI capabilities constitute a new category of strategic asset, and how do firms govern access to and monetisation of these assets?
• Under what regulatory and institutional conditions does the open-source AI movement accelerate versus impede innovation diffusion?

Timeline

• May 30, 2026: PDW (paper development workshop) at R&D Management Workshop, Seoul, Korea
• July 4, 2026: PDW at KOSIME summer conference, Jeju, Korea
• December 1, 2026: Special Issue Submission Open
• June 30, 2027: Deadline for SI Submission
• July 1, 2028: Publication of SI Articles

Andrea Vocino, Deakin University

Marta Massi, Athabasca University

Sandro Castaldo, Bocconi University

AI is increasingly central to consumer-brand interactions across digital and physical channels, raising questions about how consumers form and maintain trust, evaluate brand authenticity, and retain agency in automated decision environments. This special issue seeks to understand the psychological mechanisms underlying consumer responses to AI-mediated marketing, particularly how trust develops across diverse touchpoints and human involvement levels.

Authenticity and consumer agency emerge as critical concerns when AI shapes brand communications and customer choices. As generative AI and personalization tools become more prevalent, consumers must evaluate whether experiences feel genuine and aligned with brand values, while simultaneously navigating questions of autonomy and control in algorithmically curated environments. The issue welcomes diverse methodological approaches to advance theory, measurement, and practical understanding of these interconnected phenomena.

Appel publié par Psychology and Marketing. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Trust formation, calibration, repair, and withdrawal in AI-mediated consumer-brand interactions across channels and touchpoints
• Consumer judgments of authenticity in AI-generated content, recommendations, service encounters, and brand communications
• Trust transfer between human employees, algorithmic agents, platforms, and brands in omnichannel and phygital journeys
• Consumer agency, autonomy, control, and reactance in algorithmically curated or automated marketing environments
• Psychological and design cues (e.g., disclosure, explainability, transparency, anthropomorphism) that affect trust and authenticity
• Comparative consumer responses to human, AI, and hybrid service provision in retail, hospitality, health, education, and luxury contexts
• Mechanisms of resistance, acceptance, and adaptation to AI across different risk levels, involvement levels, and product categories
• Cross-cultural, generational, and demographic differences in responses to AI-mediated marketing and phygital experiences
• Measurement development and validation for trust, authenticity, agency, and related constructs in AI-enabled consumer settings
• Conceptual integrations linking consumer psychology, service systems, and digital platform research in AI-mediated markets

Timeline

• January 31, 2027: Submission deadline

Nicola Cucari, Sapienza University of Rome

Guanglei Zhang, Wuhan University of Technology

Jintao Lu, Shanxi University of Electronic Science and Technology

Hua Fan, Shanghai International Studies University

Eric Liguori, Florida State University

This special issue examines how artificial intelligence is transforming small and medium-sized enterprises (SMEs) across three interconnected dimensions: technological transformation, inclusive innovation, and territorial ecosystem development. The special issue seeks to move beyond simple technology adoption perspectives to explore how AI reconfigures organizational capabilities, entrepreneurial cognition, stakeholder relationships, and value creation mechanisms in SMEs. The call welcomes both theoretical and empirical studies that provide novel insights into how SMEs can leverage AI to achieve sustainable growth while addressing challenges related to investment capacity, skills gaps, cybersecurity, and unequal access to digital infrastructure.

Appel publié par Journal of Small Business Management. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI-driven business model innovation in SMEs
• Digital transformation pathways under technological turbulence
• AI and sustainable competitive advantage in resource-constrained firms
• AI-enabled work redesign and organizational reconfiguration in SMEs
• Inclusive AI ecosystems for minority, women, migrant, and informal entrepreneurs
• Algorithmic Bias and transparency in AI-assisted SMEs
• AI-enabled territorial innovation and smart regional development
• Public policies supporting equitable AI adoption among SMEs
• AI, cybersecurity, and risk governance in small businesses
• Human–AI collaboration and entrepreneurial decision-making
• Data strategies and knowledge management in SMEs
• Data ownership and territorial digital autonomy in AI-driven SME development
• Ethical, social, and governance implications of AI adoption
• AI platforms and SME participation in digital value chains
• AI for local resilience, crisis response, and adaptive entrepreneurship

Timeline

• September 25, 2026: Colloquium Extended Abstract Submission Deadline
• October 1, 2026: Colloquium Invitations Issued
• October 26, 2026: Colloquium Dates
• January 1, 2027: Full Paper Journal Submissions open
• March 31, 2027: Full Paper Journal Submissions deadline

Ruoqi Geng, Cardiff University

Di Li, University of Warwick

Yang Cheng, Aalborg University

This special issue seeks empirical research demonstrating how artificial intelligence is embedded within and enhances digital production technologies in real operational contexts. The focus is on understanding implementation pipelines and socio-technical conditions that enable AI-enabled solutions to function effectively as operational workflows. Purely conceptual, literature-based, or modelling studies without empirical validation are excluded.

Acceptable empirical research uses real-world operational evidence such as production logs, IoT sensors, machine telemetry, or industrial case studies, potentially employing machine learning or optimization when grounded in real data and validated in industrial settings with measurable outcomes. Studies must address the full AI implementation pipeline, from translating production decisions into AI use cases, to ensuring data readiness, to embedding AI outputs into human-AI workflows linked to measurable production outcomes.

Appel publié par Production Planning & Control. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI-Augmented Production Planning and Control
• Business–AI Alignment and AI Readiness Pipeline for Production Systems
• AI-enabled Quality and Process Control
• Agentic and Workflow-Oriented Deployment in Production
• AI-Enabled Cyber–Physical Production Systems and Digital Twins
• AI and Additive Manufacturing
• AI and Blockchain for Production Systems
• Human–AI Interaction and Organisational Transformation
• Empirical Innovations in Data, Measurement, and Evaluation
• Extended Production Contexts (Production-Adjacent Physical Operations)

Timeline

• September 1, 2026: Call for Papers released
• June 30, 2027: Manuscript submission deadline
• September 1, 2027: First-round decisions
• December 1, 2027: Revised manuscripts due
• June 1, 2028: Final decisions

Martin Obschonka, University of Amsterdam

Moren Lévesque, York University

Frédéric Ooms, HEC Liège

Jeffrey M. Pollack, NC State University

Denis A. Grégoire, HEC Montréal

Tara S. Behrend, Michigan State University

Boris Nikolaev, Colorado State University

Transformative Artificial Intelligence (AI) — that is, the use of AI tools that have such inherent capabilities that they could induce societal transitions similar to that of the agricultural or industrial revolutions — has become an omnipresent topic of interest. Because these tools offer order-of-magnitude efficiency improvements over prior ways of performing various human tasks, important research opportunities arise for better understanding their transformative impact.

Appel publié par Entrepreneurship Theory and Practice. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Theorizing on algorithmic entrepreneurship
• Mechanisms of external enablement of entrepreneurship via AI (e.g., generative AI)
• Can AI help reduce the destructive aspects of entrepreneurship (e.g., societal and personal costs)?
• Can AI create resource abundance, overcoming typical entrepreneurial resource scarcity and challenging leading startup methods (e.g., effectuation/bricolage, bootstrapping, lean startup)?
• Do classic research findings and theories (e.g., on the role of knowledge and human and social capital in entrepreneurship) still hold in the new AI era?
• How can AI impact entrepreneurial finance (e.g., AI-powered financial planning for entrepreneurs, VC investment portfolio management and decisions) and resource acquisition (e.g., entrepreneurs' pitch preparation, investors' due diligence, etc.)?
• Does AI change the age curve associated with entrepreneurship (does it replace the advantage of industry experience, and do we therefore see an AI-empowered rise of youth entrepreneurs)?
• How can AI contribute to equality and diversity (e.g., neurodiversity, closing the gender gap)?
• Ethical and legal issues of algorithmic entrepreneurship and AI-supported research
• How can AI support entrepreneurs' cognition, decision making, and psychological well-being?
• Will the emerging AI economy of abundance replace entrepreneurship/human entrepreneurs?

Timeline

• January 31, 2026: Final deadline for proposal submissions

Jos Akkermans, VU University

David G. Collings, Trinity College Dublin

Mila Lazarova, Simon Fraser University

Jennifer Tosti-Kharas, Babson College

Career theory has evolved over recent decades. Classic career theories were grounded in relatively stable organizational contexts with hierarchical career paths and a relatively stable external context. In the 1990s, there was increasing recognition of the emergence of more flexible, dynamic careers, driven by technological disruption, demographic shifts, and the rise of non-traditional work and career paths. This development is still often referred to as the 'new career' paradigm. Career theories (e.g., boundaryless career theory, protean career theory, and social cognitive career theory) and concepts (e.g., career orientations, career competencies, and career self-management) within that paradigm primarily emphasize theorizing how individuals can take charge and successfully navigate volatile career paths.

Appel publié par Organizational Psychology Review. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How do ongoing social, technological, and geopolitical disruptions challenge existing assumptions embedded in dominant career theories?
• How can new conceptual models better account for the relational and contextual aspects of career development in uncertain and changing environments?
• How should we reconceptualize concepts such as career competencies and employability in labor markets characterized by volatility, automation, and shifting skill demands?
• How can careers be reconceptualized in non-traditional work, including the gig economy, internal job deconstruction, and entrepreneurship?
• How do new forms of digital, hybrid, or platform-mediated work reshape notions of career identity, career success, and career self-management?
• What role does AI, including agentic AI, and the potential role of AI agents as co-workers play in how individuals' careers evolve?
• How can career theories and concepts be adapted or renewed to capture the career experiences of underrepresented and marginalized groups?
• How do organizational, institutional, and labor market structures shape individuals' capacity to construct meaningful and sustainable career paths during times of disruption?
• How do global mobility patterns, migration, and geopolitical conflict reshape traditional narratives of career progression and mobility?
• What new methodological or conceptual tools are needed to theorize non-linear, fragmented, or cyclical career patterns that increasingly deviate from traditional career models?

Timeline

• Invalid DateTime: Expected finalization of the Special Issue
• May 1, 2027: Full paper submission deadline

Glen Whelan, ESG UQÀM

Gabriel Weber, ESSCA School of Management

Yann Truong, ESSCA School of Management

Ongoing developments in Artificial Intelligence (AI) indicate that machine learning technologies will not simply match, but will potentially significantly surpass, a wide range of human cognitive abilities. Given this trend, there is reason to believe that AI could threaten humanity's hegemonic, agentic, positioning and that it could be a driver of civilizational, epochal change.

Business actors occupy a unique dual-position within this context. First, as leading architects of AI development, high-tech corporations are rebuilding the organizational structures, labour markets, and human-machinic assemblages that will define social existence for decades to come by impacting upon such fundamental concerns as democracy, peace, and human flourishing. Second, the institution of business and markets as a whole will also find itself the subject of transformative forces that it cannot control despite the fact that certain actors therewithin – such as high-tech corporations – have given rise to them.

Appel publié par Business & Society. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Speed versus safety in the rush to develop (super-intelligent) AI
• Competition and conflict over AI resources
• Defense, offense, and critical AI infrastructure
• (Rogue) AI and principal-agent misalignment
• AI and 'responsibility gaps'
• Existential threats and AI
• AI and the implicit/explicit embodiment of political goals and values
• Corporate elites (e.g., owners/founders) and the control of AI
• Corporate governance within the AI political context
• Ideological conflict in the era of AI
• The algocratic and epistocratic underpinnings of AI developments
• AI and planetary boundaries
• Environmental justice and AI
• The global south and the AI workforce
• Resource creation, extraction and commodification in the era of AI
• AI and exosomatic energy use
• AI and the changing value of human labour and human leisure
• The possibility of human excellence and flourishing in AI impacted societies
• AI and the transformation of markets for consumption and production
• The implications of AI for how we conceive and value human rights, democracy and justice
• AI and peace

Timeline

• April 1, 2026: Paper Development Workshop submission window
• May 20, 2026: Online pre-submission workshop (optional)
• September 1, 2026: Submission window opens
• September 30, 2026: Submission window closes
• January 1, 2027: Online post-submission workshop (tentative, participation optional)

Associate editors

• Simon Pek, University of Victoria

The special issue is intended to enhance corporate governance AI practices and knowledge by providing insights from both theoretical and practical lenses. All research methodologies are welcome, and papers that enhance understanding, provide explanation/prediction, and improve corporate governance practices of AI are particularly encouraged. In addition to traditional research papers, insights and commentary from practice may be considered.

Appel publié par Corporate Governance An International Review. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI practices in corporate governance
• Theoretical perspectives on AI in corporate governance
• Practical applications of AI in corporate governance
• Understanding AI's role in corporate governance
• Prediction and explanation of AI outcomes in governance
• Improving corporate governance practices with AI

Timeline

• March 31, 2026: Proposal submission deadline

This special issue explores the fundamental shift from traditional Human Resource Management (HRM) to Artificial Intelligence Management (AIM), examining how algorithms are reshaping the governance of people at work. As organizations increasingly deploy algorithmic systems to manage recruitment, performance evaluation, scheduling, and other HR functions, we need to critically understand the implications for workers, organizations, and society.

The collection seeks to bring together diverse perspectives on how algorithms are transforming workplace governance, the mechanisms through which algorithmic management operates, and the consequences for employment relationships, worker agency, and organizational practices. We welcome contributions that examine both the promises and perils of algorithmic management across different sectors, geographies, and worker populations.

Appel publié par Human Resource Management Journal. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI and algorithmic management in organizational contexts
• The role of algorithms in HR decision-making and workforce management
• Transformation of HR practices through artificial intelligence
• Governance of people at work in the age of algorithms
• Impact of AI on employment relationships and worker autonomy
• Ethical considerations in algorithmic management
• Data-driven HR and talent management systems
• Worker surveillance and monitoring through algorithms
• Resistance and adaptation to algorithmic management
• Regulatory and policy frameworks for AI in HR

Timeline

• October 15, 2026: Extended abstract submission deadline

Imon Chakraborty, Indian Institute of Technology Madras

Saji K Mathew, Indian Institute of Technology Madras

Nargis Pervin, Indian Institute of Technology Madras

Viswanath Venkatesh, Virginia Polytechnic Institute and State University

Digital technologies like AI, platforms, and IoT are transforming organizations and society, creating both significant value and serious risks including algorithmic bias, privacy violations, and cybersecurity threats. This special issue seeks research on information systems that are simultaneously responsible—fair, transparent, ethical, and respectful of human rights—and resilient, able to withstand disruptions and recover from failures.

The research community needs theoretically grounded and empirically rigorous studies that move beyond simple technology adoption narratives to examine post-adoption use, value realization, human-machine collaboration, and the long-term impacts of digital systems. Information systems researchers are uniquely positioned to explore how responsibility and resilience interplay across individuals, organizations, institutions, and society.

The special issue welcomes submissions using various research methods that advance understanding of responsible and resilient digital futures in specific technological and organizational contexts. It is linked to the InCIS 2027 conference but is also open to all authors through direct submission.

Appel publié par Information Systems Frontiers. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Responsible AI and AI Governance
• Resilient Information Systems and Digital Platforms
• Human–AI Collaboration and Decision Making
• Digital Transformation and Innovation
• User Behaviour in Digital Environment
• Digital Trust, Privacy, and Cybersecurity
• Data Governance and AI-Enabled Decision Making
• Digital Inclusion, Accessibility, and Societal Impact
• Policy and Governance of Digital Technologies
• Design Science Research for Responsible and Resilient IS
• AI and future of work and education
• Opportunities and challenges does AI create for society
• Skills and mindsets that will remain uniquely human in an AI-driven world

Timeline

• September 15, 2027: Submission deadline

Anja Grujovic-Vischer, The Geneva Association

Ruo Jia, Peking University

Zhiyu Quan, University of Illinois Urbana-Champaign

Digital technologies, artificial intelligence, data science, InsurTechs, and automation are reshaping how risks are identified, priced, mitigated, transferred, managed, and regulated. These developments raise important questions not only for re/insurers and regulators, but also for the wider research community.

This special issue welcomes high-quality empirical, experimental, policy-oriented, and practice-based contributions that deepen our understanding of digital and AI transformation in insurance and related risk-transfer markets. We particularly encourage submissions that speak to broad academic debates while offering clear implications for insurance markets, insurers, consumers, regulators, and society.

Appel publié par The Geneva Papers on Risk and Insurance Issues and Practice. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Digital technologies and their impact on insurance
• Artificial intelligence applications in insurance
• Data science in risk identification and pricing
• InsurTechs and automation in insurance
• Risk mitigation and transfer in digital contexts
• Insurance regulation in the digital age
• Consumer implications of digital transformation
• Societal impacts of AI in insurance

Timeline

• March 31, 2027: Submission deadline

Hoang Pham, Rutgers University

The special issue addresses the growing importance of reliability and statistical computing in artificial intelligence systems used in everyday applications and service industries. It seeks contributions covering both theoretical advances and practical implementations in these areas, with emphasis on papers demonstrating real-world applicability.

The special issue welcomes research on mathematical and statistical methods for reliability, machine learning approaches for intelligent systems, big data analysis techniques, and system dependability measures. Industrial applications are particularly valued, including case studies from fields such as robotics, healthcare, education, surveillance, and transportation.

Appel publié par Annals of Operations Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Mathematical reliability and statistical methods
• Big data modeling and prediction
• Statistical learning algorithms, models, and theories
• Machine learning models for intelligent systems
• Text mining and deep machine learning
• Intelligent system dependability and performability
• Reliability modeling and optimization
• High-dimensional data analysis
• Statistical inference for intelligent systems
• Industrial case studies in intelligent systems

Timeline

• October 30, 2026: Submission deadline

Olga Battaïa, Kedge Business School

Yasser Dessouky, San Jose State University

Reza Zanjirani Farahani, Paris School of Business

Masood Fathi, University of Skövde

Madjid Tavana, La Salle University

This special issue investigates how collaborative intelligence—combining human expertise, artificial intelligence, and distributed problem-solving—can advance operations research to address modern decision-making challenges. Traditional OR methods struggle with the dynamic and interconnected nature of contemporary problems, from logistics to emergency response. The collection seeks contributions that demonstrate how human-AI collaboration can enhance decision-making, boost system resilience, and optimize complex operational environments.

The call invites theoretical, computational, and applied research on human-AI collaboration in OR models, optimization and game-theoretic approaches for multi-agent systems, adaptive and decentralized frameworks, and data-driven learning-based optimization. Submissions should demonstrate both theoretical rigor and practical relevance, with innovative methodologies and real-world applications that advance collaborative intelligence in operations research.

Appel publié par Annals of Operations Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Designing OR models that facilitate seamless interaction and information exchange between human decision-makers and AI agents
• The framework for integrating human judgment, preferences, and ethical considerations into AI-driven decision-making
• Techniques for visualizing and interpreting AI outputs to enhance human understanding and trust
• Novel optimization algorithms and game-theoretic frameworks for coordinating and optimizing decisions in multi-agent environments
• Models addressing diverse objectives, capabilities, and interactions among multiple agents
• Approaches to managing conflicts, uncertainties, and strategic behaviors in multi-agent decision-making
• OR frameworks capable of dynamically adapting to real-time changes and uncertainties
• Decentralized optimization algorithms and control strategies for distributed systems
• Online learning and adaptive control techniques to improve system responsiveness and resilience
• Leveraging machine learning and data analytics to extract insights and patterns for OR applications
• Learning-based optimization algorithms that improve performance through data feedback
• Predictive analytics and simulation techniques for enhanced decision-making and risk management

Timeline

• December 31, 2026: Submission deadline

Stefan Gold, Technical University of Munich

Antoine Harfouche, Paris Nanterre University

Paul Jones, Swansea University

Maryam Lotfi, Cardiff University

Guoqing Zhao, Swansea University

An estimated 50 million people worldwide experience unethical labour practices, with numbers expected to rise due to regional conflicts and restrictive migration policies. While digital technologies such as blockchain, AI, and cloud computing offer potential solutions for monitoring and addressing these practices, research in this area remains limited. This special issue seeks to understand how digital technologies can theoretically and empirically be deployed to monitor, detect, report, and remediate unethical labour practices.

The special issue welcomes original research using various methodologies that examines the relationship between digital technologies and unethical labour practices. Submissions should identify specific technologies examined and move beyond surface-level analysis to provide nuanced insights. The collection particularly encourages studies that challenge existing paradigms, explore underexamined aspects, or propose innovative frameworks for leveraging digital solutions to advance ethical and sustainable societies while informing policymakers, business leaders, and practitioners.

Appel publié par Information Systems Frontiers. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Role of digital technologies (blockchain, AI, cloud computing, IoT, big data analytics, virtual and augmented reality) in monitoring and detecting unethical labour practices
• Application of digital technologies to address modern slavery, human trafficking, forced labour, and other forms of labour exploitation
• Digital technologies for reporting and remediating unethical labour practices in supply chains
• Use of machine learning and AI for identifying trafficking patterns and at-risk populations
• Blockchain applications for tracking labour exploitation in global supply chains
• Digital technologies for social inclusion and reintegration of survivors of modern slavery
• Biometric recognition and satellite imagery applications by governments and NGOs
• Comparative analysis of multiple digital technologies versus single-technology approaches
• Theoretical frameworks and conceptual models for understanding digital technology adoption in addressing unethical labour practices
• Empirical studies on the effectiveness and limitations of digital solutions in combating labour exploitation

Timeline

• February 15, 2027: Submission deadline

Jyoti Choudrie, University of Hertfordshire

Sherah Kurnia, The University of Melbourne

Gabrielle Peko, University of Auckland

David Sundaram, University of Auckland

This special issue addresses the critical gap between technology adoption and actual value realization, focusing on how organizations and societies integrate, adapt, and leverage ICTs and AI beyond their initial implementation. While existing research emphasizes adoption decisions, there remains limited understanding of post-adoption dynamics, continued use, and the translation of technological investments into tangible organizational and societal benefits.

The issue welcomes research exploring post-adoption phenomena across individual, organizational, and societal levels, including technology assimilation, value creation, and transformation. It also addresses significant risks and ethical concerns arising from ICT and AI deployment, such as algorithmic bias, privacy threats, digital inequality, and unintended consequences that require scholarly attention.

Appel publié par Information Systems Frontiers. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Technology assimilation, routinization, and deep integration
• Post-adoption behaviors: continued use, discontinuance, and switching
• Value creation, capture, and measurement in ICT and AI use
• Cross-cultural and comparative post-adoption studies
• Changes to work practices, organizational structures, and decision-making
• ICT-enabled institutional and governance transformation
• Digital platforms, ecosystems, and network effects
• Public sector and societal impacts of sustained technology use
• Success and failure of digital transformation initiatives
• Algorithmic bias, transparency, and accountability
• Privacy, cybersecurity, and data governance challenges
• Overuse, misuse, and unintended consequences of ICTs and AI
• Environmental and societal externalities of digital technologies
• Regulation and governance of AI and digital technologies
• Organizational strategies for effective post-adoption management
• Public policy for sustainable and ethical technology use

Timeline

• July 15, 2026: Submission of abstract (up to 300 words)
• August 15, 2026: Notification of abstract acceptance
• December 4, 2026: Submission of full paper
• April 5, 2027: Notification of first-round reviews
• July 1, 2027: Revised manuscripts due
• October 29, 2027: Notification of second-round reviews
• November 30, 2027: Final versions due
• January 31, 2028: Expected final decision

Jiaguo Liu, Dalian Maritime University

Hakan Yildiz, Wayne State University

Guoqing Zhang, University of Windsor

This special issue addresses the urgent need to understand and manage global supply chain reconfiguration in response to tariff uncertainty and shifting trade policies. Rising tariffs and trade tensions are forcing organizations to redesign their sourcing strategies, manufacturing locations, and logistics networks, creating significant practical challenges that require new analytical approaches.

The journal seeks high-quality contributions that apply operations research and artificial intelligence methods to develop decision-making models for supply chain management under tariff uncertainty. Both theoretical advances and practical case studies are welcome, particularly interdisciplinary research that combines OR, AI, supply chain management, and international economics with real-world applications.

Appel publié par Annals of Operations Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Supply network redesign and optimization under tariff uncertainty
• Robust and stochastic optimization models for tariff-driven supply chain planning
• Global supply chain reconfiguration under trade policy uncertainty
• AI-powered dynamic supply chain adaptation and tariff response strategies
• Dynamic production, sourcing, and logistics strategies facing tariff risks
• Supply chain resilience and risk management for tariff disruptions
• Logistics and warehousing for global e-commerce and omnichannel supply chains
• Maritime network and logistics optimization with tariff impacts
• Hybrid OR–machine learning for adaptive decision-making in global supply chains
• Multi-echelon inventory management under fluctuating tariff policies
• AI and data-driven methods for trade policy analysis and supply chain impacts
• Optimization models and algorithms for large-scale global supply chain problems

Timeline

• October 31, 2026: Submission deadline

Matteo Rocca, University of Insubria

Davide La Torre, Skema Business School

Constantin Zopounidis, Technical University of Crete

This special issue focuses on the intersection of Multiple Objective Optimization, Goal Programming, and Artificial Intelligence, addressing complex decision-making challenges in economics and social sciences. The collection seeks papers that combine these three domains to develop frameworks where optimization methods prioritize conflicting objectives, goal programming establishes specific targets, and AI enhances decision models through data analytics and machine learning.

The special issue welcomes both papers substantially extending contributions presented at the 16th International Conference on Multiple Objective Programming and Goal Programming (MOPGP'25) and new original work addressing theories and applications of MOP, GP, and AI in economic and social contexts.

Appel publié par Annals of Operations Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Advancements in Multiple Objective Programming Techniques
• Goal Programming Techniques and Formulations
• Goal Programming Approaches in Public Policy
• AI-Enhanced Decision Support Systems for Resource Allocation
• Data-Driven Methods in Economic and Social Decision-Making
• Integrating Machine Learning with MOP
• Multicriteria Deep Learning
• Applications of MOP and GP in Sustainable Development
• Real-Time Decision-Making Frameworks Using AI
• Comparative Studies of MOP and GP in Various Contexts
• Multi-Criteria Decision Analysis in Sustainable Economics
• Multiple Criteria Decision Making in Environmental Economics
• Optimization Models for Social Welfare
• Behavioural Insights in Multi-Objective Decision-Making
• Metaheuristics and Computational Methods in MOP
• MOP and MCDM in AI applications
• Innovative Applications to Economic and Social Sciences

Timeline

• June 30, 2027: Submission deadline

Brian King, Texas A&M University

Kyoung Jun Lee, Kyung Hee University

Danae Manika, Brunel University of London

Babak Taheri, Texas A&M University

This special issue seeks to advance understanding of how artificial intelligence can be designed and deployed responsibly and trustworthily within tourism and hospitality sectors. As AI becomes increasingly embedded in service delivery, marketing, operations, and guest experiences, the sector faces both opportunities for innovation and significant ethical challenges regarding fairness, accountability, transparency, and consumer trust.

The special issue invites interdisciplinary research examining the technical, managerial, legal, and societal dimensions of responsible AI adoption. Submissions should explore the design, governance, and impacts of AI-enabled platforms and systems, addressing topics such as algorithmic bias, consumer trust, sustainable AI applications, ethical frameworks, digital transformation, and labor implications within tourism and hospitality contexts.

Appel publié par Electronic Markets. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Ethical AI frameworks in tourism and hospitality: fairness, accountability, transparency, and inclusivity
• AI-driven consumer experiences: balancing personalization, convenience, and privacy
• AI robustness and risk: testing booking, pricing, and chatbot vulnerabilities, modeling threats, and strengthening resilience
• Trust, reliability and safety: building consumer trust, ensuring reliable performance, and managing risks
• Auditing AI systems: ongoing evaluations in pursuit of fairness, accuracy, and compliance
• Generative AI in marketing: pursuing responsibility in branding, engagement, and consumer journeys
• Sociotechnical and cultural dimensions: cross-cultural and historical perspectives on AI adoption
• AI, sustainability, and CSR: supporting or hindering responsible and sustainable practices in tourism and hospitality
• Future directions: conceptual frameworks and policy challenges for responsible and trustworthy AI in service innovation and resilience
• Social and labor impacts: the effects of adopting AI on employment, equity, and workforce well-being
• Frugal AI and digital twins: cost-effective and resource-conscious applications for operations and guest experiences
• Algorithmic transparency and rights: making AI decisions understandable and offering recourse for affected consumers
• Dark side of AI: risks of manipulation, surveillance, over-automation, and addictive design
• Corporate digital responsibility (CDR) in the age of AI within tourism and hospitality
• AI on digital platforms: exploring recommender systems, marketplaces, and platform governance
• Data ecosystems: sharing and leveraging user/usage data across digital travel and hospitality platforms
• Trustworthy AI principles: ensuring AI systems in tourism and hospitality are lawful, ethical, and technically robust
• Verification, validation, and explainability: designing AI that is interpretable and auditable for multiple stakeholders
• Trustworthy AI and consumer journeys: balancing automation with transparency and user empowerment

Timeline

• September 15, 2026: Submission deadline

Rainer Schmidt, Munich University of Applied Sciences

Rainer Alt, Leipzig University

Alfred Zimmermann, Reutlingen University

The Topical Collection on Artificial Intelligence-based Assistants and Platforms focuses on assistant systems (e.g. chatbots, recommenders) that are based on artificial intelligence and the interaction with users via declarative natural-language interfaces. They are present in various forms as well as industries and often assume a platform logic when services and devices from different providers are included.

The Topical Collection relates to a minitrack at the Hawaii International Conference on System Sciences (HICSS) and comprises research on novel methods, models, processes, and approaches related to the design, implementation, deployment, operation, and optimization of AI-based assistants and platforms for the digital economy.

Appel publié par Electronic Markets. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Design, implementation, and deployment of AI-based assistants and platforms
• Novel methods and models for AI-based assistants (e.g., chatbots, recommenders)
• Natural language interfaces and user interaction with AI systems
• Platform logic and integration of services from different providers
• Operation and optimization of AI-based assistants and platforms for the digital economy
• AI-based assistants in various industries and applications

Timeline

• Invalid DateTime: Submission deadline

This special issue explores the intersection of artificial intelligence and international business, examining both theoretical challenges and strategic implications for the field. The call welcomes research that addresses how AI transforms international business practices and theory.

Appel publié par Journal of World Business. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• September 30, 2026: Submission deadline

Appel publié par Pacific-Basin Finance Journal. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Artificial intelligence and machine learning applications in financial markets
• Algorithmic trading and high-frequency trading
• AI-driven market microstructure and price discovery
• Systemic risk and financial stability implications of AI
• Regulatory frameworks and governance of AI in finance
• Market efficiency and anomalies in AI-dominated markets
• Risk management and portfolio optimization with AI
• Ethical considerations and fairness in AI-driven finance
• Impact on market participants and trading strategies
• Data quality, bias, and robustness of AI models in finance

Timeline

• April 30, 2027: Full paper submission deadline

Appel publié par Transportation Research Part D: Transport and Environment. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• February 12, 2027: Submission deadline

Appel publié par Economic Modelling. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• February 28, 2027: Submission deadline

Appel publié par Journal of Financial Economics. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• July 17, 2027: Full paper submission deadline

Appel publié par Technological Forecasting and Social Change. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• February 28, 2027: Full paper submission deadline

Appel publié par Government Information Quarterly. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• November 1, 2026: Full paper submission deadline

This special issue invites submissions exploring the applications, implications, and innovations of Large Language Models (LLMs) in the tourism industry and for enhancing tourist experiences. The rapidly evolving landscape of artificial intelligence presents unprecedented opportunities and challenges for tourism stakeholders, from destination management organizations to hospitality providers to individual travelers.

Appel publié par Annals of Tourism Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Applications of LLMs in tourism management and operations
• LLMs for personalized tourist experiences and recommendations
• Natural language processing applications in tourism marketing
• LLMs for tourism chatbots and customer service
• Language translation and communication in tourism contexts
• LLMs for travel planning and itinerary generation
• Sentiment analysis and tourist feedback analysis using LLMs
• LLMs for tourism research and data analysis

Timeline

• August 31, 2026: Full paper submission deadline

This special issue focuses on the applications and implications of Large Language Models (LLMs) in the tourism sector. We invite research exploring how LLMs can enhance tourist experiences, improve tourism service delivery, and support both tourism businesses and individual travelers. The issue welcomes empirical studies, theoretical frameworks, case studies, and critical analyses of LLM technologies in tourism contexts.

Appel publié par Information Processing & Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Applications of LLMs in tourism industry
• LLMs for personalized tourist recommendations
• Natural language processing for tourism content
• Chatbots and virtual assistants in tourism
• Tourist information retrieval using LLMs
• Language translation for tourism
• Sentiment analysis of tourist reviews
• LLM-based travel planning and itinerary generation
• Multilingual tourism communication
• AI ethics in tourism applications

Timeline

• August 31, 2026: Submission deadline

Appel publié par Technovation. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• November 30, 2026: Full paper submission deadline

This special issue focuses on the intersection of sustainable maritime transportation and artificial intelligence technologies. Maritime transportation plays a crucial role in global commerce and logistics, accounting for a significant portion of international trade. However, the shipping industry faces considerable environmental challenges, including greenhouse gas emissions, fuel consumption, and pollution. Artificial intelligence and machine learning offer promising opportunities to address these sustainability challenges while improving operational efficiency.

The special issue welcomes contributions that explore innovative AI-based solutions for enhancing sustainability in maritime transportation. This includes research on optimizing vessel performance, reducing carbon footprints, improving safety protocols, and developing intelligent systems for port and logistics management. We are particularly interested in studies that demonstrate practical applications of AI technologies in real-world maritime contexts.

Appel publié par Transportation Research Part D: Transport and Environment. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI and machine learning applications in maritime transportation
• Optimization of shipping routes and fuel efficiency
• Autonomous vessels and maritime automation
• Environmental impact assessment and emissions reduction
• Port operations and logistics optimization
• Maritime safety and risk management
• Data analytics for sustainable shipping
• Integration of renewable energy in maritime transport
• Smart navigation systems
• Digitalization of maritime supply chains

Timeline

• October 1, 2026: Full paper submission deadline

Appel publié par Business Horizons. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• October 1, 2026: Submission deadline

Appel publié par Appetite. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• November 30, 2026: Full paper submission deadline

Appel publié par International Journal of Research in Marketing. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• November 30, 2026: Full paper submission deadline

Appel publié par Journal of Engineering and Technology Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Timeline

• February 15, 2025: Full paper submission deadline

Paul Leonardi, :?

Alex Murray, :?

Frank Nagle, :?

Nelson Phillips, :?

Juliana Schroeder, :?

Paula Ungureanu, :?

Elisa Villani, :?

The fundamental concept of agency—who can act, what action requires, and who bears responsibility—has long shaped organizational theory. With intelligent technologies now actively participating in organizational processes, this foundational understanding is being challenged as action, intention, and consequences can no longer be attributed solely to individual human actors.

This special issue invites theoretically sophisticated research that reimagines agency when humans and machines co-produce organizational action. The editors seek work that both reconceptualizes agency itself and examines how this shift transforms core organizational phenomena including behavior, leadership, careers, strategy, institutions, and governance.

Appel publié par Organization Science. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Reconceptualization of agency in contexts involving artificial intelligence and human actors
• Distribution and location of agency when action is co-produced by people and machines
• Implications for organizational behavior and motivation theories
• Leadership and decision-making in AI-augmented environments
• Control mechanisms and accountability in human-AI systems
• Value creation involving intelligent technologies
• Career development and work structures affected by AI participation
• Institutional change driven by agentic AI
• Technological change and organizational adaptation
• Management and organizational control with autonomous systems
• Strategic implications of distributed agency
• Entrepreneurship in the age of AI
• Sociology of work and labor transformation
• Information systems and autonomous action
• Governance frameworks for AI-driven organizational action

Timeline

• February 1, 2027: Submissions due

Claudine Gartenberg, .pop

Sharique Hasan, .pop

Lamar Pierce, .pop

Christopher Bail, .pop

Hengchen Dai, .pop

Oliver Hauser, .pop

Hatim Rahman, .pop

Dennis Zhang, .pop

This special issue asks a fundamental question about artificial intelligence and social science: do we want it to produce faster, cheaper versions of what we already do, or do we want fundamentally new science? Returning to Organization Science's founding mission—Daft and Lewin's 1990 call to break out of the "normal science straitjacket" and March's "exploration of new possibilities"—we want to shift our focus to how AI is changing the production of science and how it can expand our knowledge, rather than merely increasing the number of papers through efficiency and reduced labor.

In this call for science, we seek contributions that reimagine what a social science research contribution is in an AI-enabled world, encouraging wild ideas and radical innovation over obvious incremental improvement. We are not looking for conventional full-length papers with AI-related content, nor "AI slop"—we want the innovative applications themselves.

Appel publié par Organization Science. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI-enabled research loops under human direction
• Reusable research infrastructure
• New forms of measurement
• AI-enabled qualitative and theory-building work
• Synthetic social systems
• New approaches to established research designs
• Critical or boundary-setting work on the limits of AI-enabled science
• Reimagining social science research contributions in an AI-enabled world

Timeline

• October 1, 2026: Submissions Open
• November 1, 2026: Submissions Close

Yung Kyun Choi, Dongguk University

Tae Hyun Baek, Sungkyunkwan University

This special issue examines how generative AI is transforming advertising creativity. Generative tools are shifting creative work from slow, expensive human-led processes to rapid, scalable production of copy, images, video, and message variants. This technological shift raises fundamental questions about how advertising creativity is imagined, produced, evaluated, and valued in an industry where creative advantage has long been central to competitive success.

The papers sought will investigate how AI affects each stage of creative work, from idea generation through asset production to personalization and variant creation. Beyond the mechanics of creative production, the issue addresses how agencies, brands, and platforms are reorganizing creative labor, which roles and skills remain valuable, and how business models built on production fees are being reshaped as marginal costs approach zero.

Appel publié par Journal of Advertising Research. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How does AI change the way creative ideas are generated, selected, and refined, and where in that process is human judgment most valuable?
• When does AI assistance widen the range of creative directions a team explores, and when does it narrow it?
• How should briefs, brainstorming, and creative workflows be redesigned around generative tools?
• What is the most effective division of labor between human creatives and AI across ideation, drafting, and refinement?
• How does near-zero marginal cost production change what advertising creative gets made, and how much of it?
• What is gained and lost when finished assets are generated rather than crafted?
• How does AI-produced creative compare with human-produced work on effectiveness, quality, and cost (for example, click-through, attention, and brand lift)?
• How does production at scale change media planning, creative testing, and iteration?
• How does generative AI change dynamic creative optimization and one-to-one message tailoring?
• How can brands produce thousands of variants without eroding distinctiveness and brand consistency?
• When does personalized AI creative outperform a single strong idea, and when does it not?
• How do consumers respond to creative that is visibly machine-tailored to them?
• How are agencies, in-house teams, and platforms reorganizing creative labor around AI?
• Which creative roles and skills are being automated, augmented, or newly created?
• How does AI reshape the agency and client relationship, the pitch process, and value capture?
• What happens to agency business models when the cost of production approaches zero?
• Does AI change how creativity is defined, judged, and rewarded in advertising?
• How should originality, distinctiveness, and craft be valued when execution becomes commoditized?
• Does widespread AI use homogenize advertising creative, and how can brands resist sameness?
• How should creative awards, evaluation standards, and quality benchmarks adapt?
• What methods (field experiments, computational and multimodal analysis, large-scale A/B testing) best capture the effect of AI on creative outcomes?
• How can creativity itself be measured at scale across large volumes of AI-generated work?
• How can researchers study homogenization, distinctiveness, and the diversity of creative output?
• When does AI-generated creative help or hurt brand building and long-term equity, and what guardrails keep it on-brand and effective?

Timeline

• January 15, 2027: GMC Tokyo 2027 submission deadline
• September 1, 2027: Special issue submission window opens
• October 15, 2027: Special issue manuscript deadline

Hyun-Jung Kim, KAIST

Shu-Kai Fan, National Taipei University of Technology

Fugee Tsung, Hong Kong University of Science and Technology

Thomas Volling, Technical University Berlin

Jang Ho Kim, Korea University

Dong-Young Lim, Ulsan National Institute of Science and Technology

This special issue addresses decision-making in complex industrial systems facing dynamic uncertainty through artificial intelligence and optimization techniques. The issue seeks research combining AI methods such as reinforcement learning, generative AI, and digital twins with operations research and optimization approaches to manage manufacturing, supply chains, healthcare, and other sectors dealing with demand fluctuations and disruptions.

The special issue welcomes both theoretical and practical contributions demonstrating how AI-driven methodologies can improve decision-making under uncertainty. Particular emphasis is placed on interdisciplinary research with clear industrial applicability and the adoption of open science practices including data and code sharing to enhance reproducibility.

Appel publié par International Journal of Production Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI-driven decision-making under uncertainty
• Production planning and scheduling in stochastic and dynamic environments
• Reinforcement learning for uncertain industrial systems
• Stochastic optimization and robust operational strategies
• AI-enabled statistical quality control and process improvement
• Hybrid AI and optimization approaches for uncertain environments
• Data-driven optimization and prescriptive analytics
• AI-enhanced supply chain and logistics management under disruptions
• Real-time and adaptive decision-making systems
• Simulation-based optimization and digital twins under uncertainty
• Agentic AI and autonomous industrial systems
• Explainable and trustworthy AI for operational decision-making
• AI for resilient and sustainable operations
• Industrial applications and case studies of AI-driven decision systems

Timeline

• October 1, 2026: Submissions open
• January 31, 2027: Submission deadline

Sandra Fisher, FH Münster

Janet Marler, University at Albany - SUNY

Guido Hertel, University of Münster

This special issue examines how artificial intelligence and related technologies reshape human resource management practices and organizational work. Building on decades of e-HRM research, the collection investigates AI's transformative potential while remaining critical of its limitations, including bias, lack of transparency, and skill erosion concerns.

The issue welcomes research exploring which HRM processes should be automated versus augmented, what alternative technologies might complement or replace AI, and what comes after the current wave of AI advancement. It seeks evidence-based scholarship that helps organizations implement AI to benefit all stakeholders while avoiding technological determinism.

Appel publié par The International Journal of Human Resource Management. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• New theories and methodologies to study AI/HRM
• New HRM strategies
• AI-Human collaboration at work
• e-HRM/AI value propositions
• AI/Technology-enabled HR roles
• AI Agents' roles and intended and unintended outcomes in HRM
• AI/Technology-enabled HR functions: recruitment, selection, performance management, leadership, training and development, coaching, compensation and employee relations
• Algorithmic management of employees or gig workers
• Gig-worker management and employment/work relations
• e-HRM and employee experience
• e-HRM and employee wellbeing
• AI and Bias in decision-making
• AI and job design/crafting
• HR data management and confidentiality
• People Analytics and AI
• Digital talent management
• Employee and digital onboarding systems
• Gamification in HRM
• Robots and artificial intelligence (AI) in HRM
• Employer branding and digital communication
• AI/e-HRM and trust/ethics

Timeline

• Invalid DateTime: Special issue completed
• July 1, 2026: Submission portal opens
• October 31, 2026: Special Issue Submissions due

Linda Tuncay Zayer, Loyola University Chicago

Jing Yang, Boston University

Shu-Chuan (Kelly) Chu, DePaul University

Appel publié par International Journal of Advertising. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Ethical implications of AI, social media, AR, VR, metaverse, and other emerging technologies
• Ethics and well-being related to AI companions, bots, and virtual influencers
• Personalized content generation and psychological manipulation concerns
• Algorithmic amplification of beneficial versus harmful advertising content
• Anthropomorphic design ethics and emotional manipulation through physical presence of AI/Robot
• Consent and autonomy in human-robot advertising/marketing communication interactions
• Parasocial relationships with advertising/marketing communication robots and their exploitation
• Consumer understanding and control of integrated AI advertising experiences
• Data sharing and privacy concerns across social media platforms and emerging technologies
• Building AI and digital media literacy
• Children's well-being related to AI, social media and new technologies
• Elderly consumers and potential exploitation through advertising systems embodied by emerging technologies
• Consumer involvement in advanced advertising system design and governance
• Professional ethics for AI-automated decision-making
• Deepfakes and synthetic media ethics in commercial contexts
• Synthetic data and digital twins in the advertising context
• Automation and replacement of advertising industry employees by AI
• Bias detection, measurement, and mitigation strategies across digital applications
• Bias and representational harms of AI-generated advertising and other emerging technologies
• Extremism, misogyny, and gender-based violence enabled by AI, social media, and emerging technologies
• Immersive storytelling, embodiment, and consumer well-being in hybrid digital–physical advertising experiences
• Sustainability issues related to the use of AI in advertising industry
• AI, energy consumption, and the carbon footprint of the advertising industry

Timeline

• August 31, 2026: Manuscript deadline

Jingsha He, Beijing University of Technology

Sohail S. Chaudhry, Villanova University

Galina Ilieva, University of Plovdiv

This special issue examines how data intelligence and advanced technologies are transforming e-commerce enterprises. The rapid integration of big data analytics and AI with e-commerce has enabled innovations such as dynamic pricing, personalized recommendations, and optimized supply chains. However, challenges remain in handling massive data volumes, processing both structured and unstructured data, and differentiating competitive offerings through algorithms.

The special issue seeks research addressing current bottlenecks in data-driven e-commerce, including operational efficiency improvements, data processing complexity, and reducing over-reliance on historical data. Contributions should explore how emerging technologies like AI and generative AI can enhance recommendation systems, marketing strategies, and cross-channel retail integration while overcoming algorithm homogenization issues.

Appel publié par Enterprise Information Systems. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Paths to enhance e-commerce efficiency driven by big data
• Data intelligence empowers innovation in e-commerce operations and service upgrading
• Optimization of complex data processing in e-commerce operations through data intelligence
• AI enables solving the problems of structured and unstructured data processing in e-commerce
• E-commerce marketing strategies and accurate capture of user behavior based on in-depth AI analysis
• AI enables optimization of the guidance effectiveness and accuracy of recommendation systems for e-commerce users
• Generative AI breaks through algorithm homogenization to realize personalized services in e-commerce
• Data intelligence promotes the format innovation of integration between e-commerce and physical retail

Timeline

• September 30, 2026: Submission of manuscript
• November 15, 2026: First notification
• December 31, 2026: Submission of revised manuscript
• February 15, 2027: Final paper due

Steve Yang, Stevens Institute of Technology

Jing Chen, Cardiff University

Aparna Gupta, Rensselaer Polytechnic Institute

Zachary Feinstein, Stevens Institute of Technology

William Knottenbelt, Imperial College

Appel publié par The European Journal of Finance. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Asset pricing models using Generative AI and LLMs
• Financial intermediation applications of AI technologies
• Generative AI applications in financial markets and investment analysis
• Behavioral finance research incorporating LLM insights
• Banking sector applications of Generative AI
• Accounting and auditing with LLM technologies
• Insurance industry applications of AI and LLMs
• Ethical implications of Generative AI in finance
• Financial inclusion benefits through AI/LLM innovations
• Regulatory and policy changes driven by Generative AI
• Data generation and analysis using LLMs in finance
• Risk management with Generative AI and LLMs
• Natural language processing applications in finance
• Information processing improvements through FinBERT and similar models
• Data privacy concerns in AI-driven finance
• Regulatory challenges of Generative AI in financial systems

Timeline

• September 15, 2026: Manuscript deadline

Kirsten Cowan, University of Edinburgh

Yang Feng, University of Florida

Seth Ketron, University of St. Thomas

Aidin Namin, Loyola Marymount University

Appel publié par Journal of Advertising Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How advertisers can effectively leverage AI-generated content and zero-click searches to reach their target audiences
• The impact of AI-generated content on search results and consumer decision-making
• The evolution of SEO strategies in response to AI-driven search algorithms
• The role of AI in shaping consumer journeys and experiential marketing
• How AI has shifted and/or will shift psychological mechanisms in search, including but not limited to empowerment, attention, memory, processing styles, and cognitive bias
• How social, cultural, and other contextual differences might lead different consumer segments or markets to react to and utilize AI differently in search
• The role of AI in relation to marketer-controlled vs. nonmarketer-controlled sources of information (e.g., ads or website content vs. customer reviews or social media) and consumers' relative reliance on each
• The effects of AI on speed, locus of control, and effort in consumer search
• The potential for AI-driven advertising to enhance or undermine consumer trust and brand loyalty
• The impact of AI on ad pricing and revenue models, including the potential for more nuanced and contextual pricing strategies
• The role of AI in facilitating more personalized and relevant advertising search experiences, and the potential trade-offs with consumer privacy
• The need for new metrics and benchmarks to measure the effectiveness of AI-driven advertising campaigns, and the potential for AI to provide more granular and actionable insights into consumer behavior and preferences
• The potential for AI to create more intimate and human-like interactions with consumers
• The ethical implications of AI-driven search and advertising practices
• The future of search interfaces, including voice-activated, image-based, and multimodal search
• The interplay between AI-generated search experiences and consumer autonomy
• The implications of AI-driven search ecosystems for market competition and brand visibility
• The role of AI transparency and explainability in consumer trust and regulatory compliance
• The sustainability and environmental impact of AI-driven search and advertising ecosystems
• Cross-platform integration and continuity in AI-mediated consumer journeys
• How the reduced visibility of paid versus organic influence in conversational AI affects consumer understanding, disclosure, and trust in recommendations
• How the growing tendency to treat AI systems as social or companion-like partners might reshape the value of impressions, expectations of authenticity, and marketplace pricing for AI-mediated advertising interactions

Timeline

• June 1, 2026: Submission window opens
• September 7, 2026: Manuscript deadline

Paul Tae-Woo Lee, Zhejiang University

International organizations have implemented regulations requiring decarbonization of transportation and logistics industries. The special issue addresses net-zero emissions implementation through multimodal transport networks, where major cargo owners and stakeholders have committed to zero-emission transportation. AI and big data technologies are identified as catalysts for digital transformation and carbon reduction optimization.

The special issue aims to fill research gaps concerning net-zero pathway implementation, particularly around three key challenges: direct emissions reduction, higher capital and operating costs for green technologies, and establishing sustainable green energy supply chains. The collection seeks comprehensive and integrated approaches to enable logistics and transportation industries to achieve carbon reduction and multimodal network sustainability.

Researchers are invited to explore how AI, digitalization, new technologies, and policy mechanisms can support decarbonization. The special issue targets the research community and practitioners in transport, logistics, and supply chains to provide managerial insights and expand literature on net-zero pathways.

Appel publié par International Journal of Logistics Research and Applications. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Decarbonization pathways for transport and logistics services
• Zero-emission freight transport
• Decarbonization and digitalization in transport and logistics services
• Application of AI & big data for decarbonization
• Green shipping and digital corridors
• Green transport and logistics models
• Green fuel supply chains, comprising supply, transport, and storage
• Green energy transitions in smart cities
• Sustainable procurement for net-zero transitions
• Regenerative supply chain design and resilient networks
• Electrification of transport fleets and charging infrastructure challenges
• Policy, regulation, and carbon pricing impacts on logistics decarbonisation
• Safety and environmental monitoring

Timeline

• Invalid DateTime: Paper proposal submission deadline
• April 30, 2027: Manuscript deadline

Associate editors

• Kai-Chieh Hu, Soochow University
• Kyoung-Suk Choi, Jeonbuk National University

René Riedl, University of Applied Sciences Upper Austria & Johannes Kepler University Linz

Jan vom Brocke, University of Münster

Jella Pfeiffer, Karlsruhe Institute of Technology

Robert Gleasure, Copenhagen Business School

Appel publié par European Journal of Information Systems. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How does sustained interaction with AI-enabled systems (e.g., LLMs) and other advanced digital tools reshape neural networks associated with language, reasoning, and memory?
• Does reliance on AI systems and other forms of automation/digital decision support alter attentional control, working memory, metacognition, or problem-solving processes at the neurophysiological and behavioral levels?
• What are the implications of digitally augmented cognition for neuroplasticity, skill acquisition, and expertise development over time?
• How can integrated neurophysiological and behavioral measures provide a fuller picture of technology-mediated cognitive processes?
• How do individuals' brains respond to empathetic or anthropomorphic cues exhibited by conversational AI and other interactive systems?
• What neurophysiological correlates underlie trust, reliance, distrust, or skepticism toward AI systems and other algorithmic or platform-based systems?
• How does emotional regulation change when decision-making is mediated by AI support, algorithmic decision aids, or digital nudges?
• What are the neurophysiological mechanisms of stress, fatigue, or overload in contexts of AI-assisted work and other digitally intensified work settings?
• How does technological mediation in team collaboration influence the neurophysiological foundations of social coordination, empathy, and shared attention?
• What neural mechanisms underlie shifts in authority, leadership, and influence when AI becomes a co-decision-maker?
• How do cultural differences modulate neurophysiological responses to AI and other digitally mediated collaboration settings?
• How do gender, age, or personality differences modulate neurophysiological responses to IS artifacts?
• How might AI-driven systems and other algorithmic/persuasive designs reinforce or mitigate cognitive biases?
• What neural signatures accompany ethical dilemmas and moral decision-making in AI-mediated contexts and broader digital governance settings?
• How does long-term use of AI and other digitally intensive work systems shape neurophysiological well-being, stress, or mental health at the workplace?
• How can neurophysiological insights inform the design of AI systems and other digital systems that are more intuitive and aligned with human cognitive limits?
• What are the neurophysiological underpinnings of productivity, efficiency, or value creation in digitally mediated economic interactions?
• How can genetic and neurophysiological approaches together explain individual differences in the adoption and use of digital systems?
• Which neurophysiological tools are best suited for investigating contemporary IS phenomena?
• How can hybrid approaches combining neurophysiology with computational methods enrich IS theory development?
• How can multi-level research designs integrate genetic, neurophysiological, behavioral, self-report, and organizational data to address IS phenomena more holistically?

Timeline

• March 31, 2026: Abstract deadline
• August 31, 2026: Manuscript deadline

Associate editors

• Bonnie B. Anderson, Brigham Young University
• Dinko Bačić, Loyola University Chicago
• Colin Conrad, Dalhousie University
• Verena Dorner, Vienna University of Economics and Business
• Nadine R. Gier-Reinartz, Heinrich-Heine-University Düsseldorf
• Milena Head, McMaster University
• Alan R. Hevner, University of South Florida
• Qiqi Jiang, Copenhagen Business School
• Marion Korosec-Serfaty, University of Québec in Montréal
• Alexander Maedche, Karlsruhe Institute of Technology
• Gernot R. Mueller-Putz, Graz University of Technology
• Pierre-Majorique Léger, HEC Montréal
• Mario Nadj, University of Duisburg-Essen
• Fiona Nah, Singapore Management University
• Adriane Randolph, Kennesaw State University
• Ofir Turel, University of Melbourne
• Eric A. Walden, Texas Tech University
• Peter Walla, Sigmund Freud Private University Vienna
• Dezhi Wu, University of South Carolina

Eunju Ko, Yonsei University

Teresa Sádaba, ISEM Fashion Business School, Universidad de Navarra

Carmen Valor, Universidad Pontificia Comillas

Appel publié par International Journal of Advertising. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How can influencers disclose data-driven targeting practices while preserving transparency and trust?
• How do AI-generated avatars and human influencers co-create content, and what balance sustains authenticity and aspiration?
• In what ways does AI-enabled personalization enhance luxury advertising without undermining exclusivity and symbolic value?
• How do AI-powered influencers and proliferating collaborations shape consumer trust, differentiation, and purchase decisions?
• How do platform-specific affordances (e.g., Instagram, TikTok, WeChat) shape storytelling, authenticity cues, and parasocial ties?
• How do different types of influencers (celebrity, micro, virtual, AI-generated) shape perceptions of authenticity, aspiration, and brand legitimacy?
• In what ways does the proliferation of influencer collaborations affect consumer trust, attention, and differentiation in luxury markets?
• How do AI-powered tools for influencer identification, personalization, and content creation alter the dynamics of luxury influence?
• How do influencers interact with broader institutional forces, such as regulation, ethics, and sustainability expectations?
• Under what conditions do sustainable luxury communications operate effectively, and why?
• How do sustainable advertising strategies influence consumers beyond purchase—shaping post-purchase satisfaction, long-term loyalty, and lifestyle adoption?
• How can luxury advertising integrate sustainability (e.g., recycled materials, fair labor) without diluting aspirational value?
• Which execution formats (storytelling, branded content, live events, influencer collaborations) most effectively balance marketing and societal objectives?
• How can luxury brands use communication to encourage minimalist consumption ('buy less but better') while maintaining aspiration and desirability?

Timeline

• August 31, 2026: Manuscript submission deadline for direct submissions to the International Journal of Advertising

Saverio Barabuffi, Scuola Superiore Sant'Anna

Giulio Ferrigno, Scuola Superiore Sant'Anna

Letizia Mortara, University of Cambridge

Yogesh K. Dwivedi, King Fahd University of Petroleum and Minerals

Innovation increasingly depends on collaboration among diverse actors who combine and recombine their knowledge. While organizations traditionally select partners based on complementary knowledge structures, the emergence of large volumes of structured and unstructured data alongside artificial intelligence technologies has fundamentally altered how firms search for external knowledge, identify complementarities, and govern collaborative innovation. Recent advances in AI, particularly Large Language Models, enable systematic analysis of millions of documents to map technological trajectories and detect emerging knowledge fields, potentially reshaping the scope and modalities of knowledge search.

Despite growing interest in AI and innovation, understanding of how AI technologies influence open innovation processes remains fragmented. There is limited evidence on how AI affects partner selection, reconfigures knowledge search strategies, and alters coordination mechanisms within innovation ecosystems. While AI-driven tools promise expanded collaboration opportunities, they also raise challenges including transparency, algorithmic bias, and unequal access to computational capabilities.

Appel publié par Industry and Innovation. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI and Inbound Open Innovation: Partner Search and Knowledge Scouting
• How do AI-based tools reshape the classic trade-off between search breadth and depth in open innovation? Can algorithmic scouting explore distant knowledge domains more efficiently than traditional methods?
• To what extent can AI overcome local search biases, revealing latent complementarities across industries, regions, or technologies that human managers may overlook?
• Can AI-powered analysis of diverse data sources democratize access to innovation ecosystems, or does it favor incumbents with larger digital footprints?
• Orchestration & Governance of Innovation Networks
• How do AI tools enable algorithmic governance of knowledge flows in multi-partner networks?
• How can AI help coordinate heterogeneous actors, including firms, universities, NGOs, and governments, within mission-oriented innovation systems?
• How are platforms leveraging AI-tools to shape technological trajectories and orchestrate complementors in ecosystems?
• What are the implications of AI-mediated orchestration for value capture, appropriation, and transparency in collaborative innovation?
• Knowledge Flows, Spillovers and Innovation Mapping
• How do generative AI and Natural Language Processing techniques uncover tacit knowledge flows and early-stage spillovers invisible to traditional patent- or publication-based metrics?
• How do AI tools improve the mapping of technological landscapes, identify "white spaces", and detect emerging trajectories to inform strategic decisions such as make, buy, or ally?
• What methods best integrate multiple data streams to track cross-sectoral and cross-regional knowledge diffusion enabled by AI?
• AI-Enabled Absorptive Capacity and Human AI interaction
• How should absorptive capacity be reconceptualized when AI tools, such as LLMs, assist in the recognition of external knowledge?
• What is the optimal division of labor between AI systems and human R&D managers in scanning, interpreting, and assimilating external knowledge?
• How can AI support organizational learning while mitigating barriers such as the "Not Invented Here" syndrome, especially when AI identifies previously unknown sources of innovation?

Timeline

• September 1, 2026: Submission window opens
• September 30, 2026: Manuscript deadline

Yichuan Wang, University of Sheffield

Minhao Zhang, University of Bristol

Francesco Schiavone, University of Naples Parthenope

This special issue examines how shifting political contexts and policy decisions influence artificial intelligence innovation, governance, and investment globally. The call addresses the interplay between regulatory changes, technological development, and organizational strategy in response to evolving geopolitical uncertainties and governance frameworks around AI.

The issue seeks interdisciplinary research exploring how relaxed or tightened AI regulations affect innovation ecosystems, competitive dynamics, and cross-border collaboration. It welcomes submissions analyzing governance models, investment strategies, and the balance between rapid AI development and ethical considerations such as data protection and algorithmic fairness across different economic and institutional contexts.

Appel publié par Enterprise Information Systems. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How do shifting political contexts and leadership changes shape countries' AI R&D investments and strategic alliances?
• What are the short-term and long-term implications of relaxed AI governance on economic performance, data privacy, and algorithmic bias?
• Under what conditions can reduced AI regulations foster or hinder innovation ecosystems in sectors such as healthcare, finance, manufacturing, and transportation?
• How can policymakers and organizations balance the need for rapid AI innovation with the ethical and social risks arising from limited oversight or fragmented governance?
• How might relaxed AI governance in certain countries influence global competitive dynamics, international collaborations, and the uneven distribution of AI capabilities?
• What strategies can multinational enterprises adopt to navigate complex regulatory landscapes, protect intellectual property, and maintain data security while pursuing AI innovation?
• Which governance models or policy frameworks from different regions most effectively balance innovation, accountability, and social welfare in AI?
• How can scenario planning and forecasting methods be applied to model the impact of political volatility on AI investments, talent flows, and market structures?

Timeline

• November 15, 2026: Manuscript deadline

Alexandra Brintrup, University of Cambridge

Thomas Choi, Arizona State University

George Huang, Hong Kong Polytechnic University

Dmitry Ivanov, Berlin School of Economics and Law

Recent advances in agentic Large Language Models have created new opportunities for autonomous decision-making in supply chains. This special issue seeks to advance rigorous research on how these AI agents can transform supply chain management by integrating perspectives from operations, AI, complexity science, and industrial engineering. While multi-agent systems have been studied for years, recent LLM breakthroughs now enable more flexible, scalable, and practical implementations that major corporations and technology providers are already exploring.

The special issue welcomes diverse research methodologies including technical solutions, modeling, empirical studies, and experimental work with practical implications. Topics span from using agentic systems for optimization and forecasting to managing risks, designing interorganizational coordination systems, and addressing technical and governance challenges such as trustworthiness, safety, and performance evaluation.

Appel publié par International Journal of Production Research. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Discourse on utilising agentic systems for complex scenarios in supply chain management: Risk and disruption management, logistics and supply chain optimisation, transportation routes, inventory management, quality control, demand forecasting, and warehouse planning and location, and cash flow predictions
• Supply network design with agentic technology: Supplier relationship configurations, agentic digital twins to simulate inventory flows, sustainability implications across the supply chain, circular supply chains, supply chain visibility, and supply chain financing
• Interorganisational agentic systems: Effective multi-agent negotiation and coordination, the design of mediative and persuasive agentic systems, preservation of organisational privacy during multi-agent communication
• Hybrid systems: Integration of agentic systems with blockchain, IoT, Omniverse, and traditional multi-agent systems
• Emergence and Complexity: Unintended consequences of agentic deployment at the system scale, governance, trustworthiness and safety, centralised versus decentralised control, human-in-the-loop agentic systems
• Technical challenges: Performance evaluation, efficient task division, ablation analysis and back testing, sensitivity analysis, agentic architectures operating in high uncertainty environments, long-term horizon reasoning, overcoming hallucinations

Timeline

• September 30, 2026: Manuscript deadline

Mariachiara Barzotto, University of Bath

Jennifer Clark, The Ohio State University

This special issue addresses the regional development implications of artificial intelligence as an emerging enabling technology. AI functions both as an independent industry and as infrastructure integrated across existing sectors, with potential to reshape production systems, innovation dynamics, regional governance, and spatial economic organisation. The issue recognises that understanding AI requires examining not only industrial transformation but also how it influences knowledge production and regional governance practices.

The special issue seeks to develop a coherent research agenda by bringing together fragmented discussions across different literatures and scales of analysis. It invites empirically grounded contributions that examine three interconnected dimensions: the spatial organisation of the AI industry itself, the effects of AI on regional development governance and planning, and how AI adoption across incumbent sectors reshapes patterns of regional economic concentration and dispersion.

Appel publié par Regional Studies. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• The economic geography of the AI industry: spatial organisation of AI production, agglomeration and dispersion patterns, factors determining spatial organisation (skills, capital, infrastructure, energy, regulatory regimes)
• AI and the governance of regional development: impact on administration and management, effects on decision-making processes and outcomes, new expectations or criteria for regional development and planning practices
• AI diffusion and the restructuring of incumbent industries: how adoption and diffusion of AI alter regional geography of incumbent sectors, changes to spatial logics, substitution effects with other technologies, new patterns of concentration or dispersion
• Conceptually robust and empirically grounded contributions examining regional development implications of AI as an emerging enabling technology

Timeline

• October 16, 2026: Abstract deadline
• December 1, 2026: Manuscript deadline

Cristina Alaimo, ESSEC Business School

Lauren Waardenburg, ESSEC Business School

Jonny Holmström, Umeå University

Lior Zalmanson, Tel Aviv University

Reza M. Baygi, VU Amsterdam

The special issue addresses a fundamental shift in how artificial intelligence operates: contemporary AI systems are built upon, learn from, and generate data at scale, making data rather than rules the core substrate of computational intelligence. This requires Information Systems scholars to develop new conceptual frameworks for understanding the data-AI nexus as a socio-technical phenomenon, moving beyond purely technical perspectives.

The call emphasizes that data are shaped by institutional practices and cognitive frames, while AI systems increasingly reshape the data they depend on, blurring boundaries between data and AI. Practitioners primarily engage with AI through data practices such as curation, labelling, and quality control, making it essential to understand the organizational routines and historical infrastructures that underpin these processes. Additionally, AI now generates synthetic data that feeds back into model training, raising institutional and epistemic challenges.

Appel publié par European Journal of Information Systems. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Data and AI co-constitution: exploring where intelligence emerges in computational architectures, datasets, or their entanglement; how data selection, curation, labelling, and historical accumulation shape AI capabilities
• AI as a data-maker: conceptualizing AI as an active producer of data; how classification systems, predictive models, and generative tools reorganize reality; AI agents autonomously generating and acting upon data; recursive dynamics of synthetic data training other AI systems
• Data decoupled from practice: consequences of data production detached from institutionalized knowledge practices; governance and decision-making based on decontextualized data; risks when data-driven systems lack ties to local knowledge and professional judgment
• The social life of the data-AI nexus: institutional, historical, and cognitive trajectories of data; how organizational memory, institutional logics, and collective sensemaking shape datasets and AI output interpretation; AI agents as new organizational actors
• Theoretical and methodological discussions: analyses of co-constitution, entanglement, flow, recursion, performativity, and classification; reconceptualizing constructs like intelligence, data quality, ground truth, and model performance as relational and emergent
• Cross-level insights: how assumptions about data and intelligence are embedded in AI systems; studies of data work (curation, labelling, cleaning), model development, synthetic data pipelines, generative AI integration
• Data, AI and grand challenges: addressing climate change, public health, inequality, and geopolitical tensions; responsible AI design with incomplete, biased, or synthetic data; governance and accountability in distinctive contexts (scientific, environmental, planetary)

Timeline

• May 28, 2026: Call launch at the Theorizing Data & AI Conference
• January 15, 2027: Initial paper submission deadline
• April 15, 2027: First round authors notification
• July 31, 2027: Invited revisions deadline
• October 31, 2027: Second round authors notification
• January 15, 2028: Final revision deadline

Associate editors

• Aleksi Aaltonen,
• Ida Asadi Someh,
• Ioanna Constantiou,
• Domenico di Prisco,
• Mayur Joshi,
• Ekaterina Jussupow,
• Jannis Kallinikos,
• Tomislav Karačić,
• Stan Karanasios,
• Alexander Kempton,
• Angelos Kostis,
• Harris Kyriakou,
• Christine Legner,
• Kalle Lyytinen,
• Eric Monteiro,
• Jeff Parsons,
• Mike Power,
• Jan Recker,
• Paavo Ritala,
• Marta Stelmaszak Rosa,
• Lauri Wesssel,

Zuzana Virglerova, Tomas Bata University in Zlín

Nicola Capolupo, San Raffaele Roma University

The aim of this special issue is to explore how algorithmic and behavioral biases influence the adoption, use, and outcomes of Artificial Intelligence (AI) in organizational settings. As AI systems increasingly shape decision-making, human resource management, operational processes, and strategic planning, understanding how biases emerge and interact within socio-technical systems has become a critical scholarly and societal challenge.

The special issue seeks to integrate interdisciplinary perspectives to explain how biases arise both from AI systems and from the human and organizational decisions that design, implement, interpret, and govern them. It offers an original contribution by bridging two research streams that are often treated separately: algorithmic biases embedded in data, models, and computational architectures, and behavioral biases rooted in human cognition, organizational routines, and institutional structures. Building on socio-technical systems theory, AI is conceived as co-constructed by technologies, individuals, and the environments.

Appel publié par Business Process Management Journal. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Algorithmic biases in AI systems applied to HR and decision-making processes
• Cognitive and behavioral biases of users interacting with AI systems
• Governance, ethics, and regulation of AI in organizations
• Methodologies for identifying and mitigating socio-technical biases in work processes
• Organizational and social impacts of AI on equity, environment, inclusion, and job quality

Timeline

• June 1, 2026: Opening date for manuscripts submissions
• July 31, 2027: Closing date for manuscripts submission

Victoria-Sophie Osburg, Catholic University Eichstätt-Ingolstadt

Dina Khalifa, Regent's University London

Jonas Holmqvist, KEDGE Business School Bordeaux

Vignesh Yoganathan, Aston University

The concept of luxury is undergoing significant changes in the digital age, merging traditional ideas of exclusivity and craftsmanship with innovative digital experiences. Technology increasingly influences our daily lives as luxury brands increasingly apply digital tools to enhance the customer experience, reshaping the luxury markets and fundamentally altering how luxury is perceived, experienced, and consumed. Additionally, changing societal norms and consumer expectations require luxury brands to engage in new ways, such as through brand activism. This transformation impacts how luxury brands connect with consumers and deliver value.

Virtual contact points are increasingly replacing or supplementing human interactions, providing personalized and seamless experiences. Consumers can now display their luxury consumption on social media and explore and interact with luxury products through immersive virtual experiences, such as digital flagship stores, which blur the lines between physical and digital realms. Furthermore, digital technologies enable unprecedented levels of personalization.

Appel publié par European Journal of Marketing. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Drivers of consumer adoption of technological solutions in luxury markets
• The evolving understanding of luxury among consumers in the digital age
• The impact of digital technologies on luxury value perceptions and consumer experiences
• Consumers' preferences and needs regarding the joint implementation of technology and a human touch in luxury consumption
• Consumer reactions to virtual luxury goods and experiences
• Consumer agency and engagement in luxury through digital tools
• Tensions that consumers face when brands integrate luxury with technology
• Luxury brands' opportunities to navigate technological innovation while maintaining brand heritage
• Managing the paradox of the ephemerality of technology with the permanence of luxury brand identity
• The role of social media and influencers in shaping digital luxury consumption, including virtual influencers
• The integration of physical and digital luxury experiences in omnichannel strategies
• Consumers' ethical considerations in virtual luxury markets, including sustainability, traceability, and inclusivity
• Generational differences in the adoption of digital luxury experiences and how luxury brands can cater to cross-generational consumer needs

Timeline

• March 6, 2026: Opening date for manuscripts submissions
• November 30, 2026: Closing date for manuscripts submission

Teemu Laine, Tampere University

Tuomas Korhonen, Tampere University

Carsten Rohde, Copenhagen Business School

Vesa Tiitola, Tampere University

The special issue will reflect and revisit the role and value of management accounting (MA) in the current evolving and complex business context. The value of management accounting lies in its ability to serve managers in different roles in their decision making and broader managerial work, all situated in their operational environment. The nature of managerial work and the potential support from MA therein are being challenged by several intertwined contemporary developments: a) technology advancements, such as algorithms and the artificial intelligence (AI) penetration to many professions, MA included, b) human judgement, ethical considerations and responsible behaviour, and c) global and local issues that influence the business context, such as geopolitics and climate change.

Appel publié par Qualitative Research in Accounting & Management. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Revisiting the Foundations of Management Accounting (MA) and Management Control (MC)
• Digitalization, Artificial Intelligence, and the "Post-Analytics" Era
• Human Judgment and Accountability in the Age of AI
• Sustainability, Ethics, and the Evolving Role of Management Accounting
• Transformation and Innovation in MA&MC Systems and Practices
• Management Accounting that Expands over Organizational Boundaries
• Emerging Business Models and Performance Paradigms
• Inter-, Multi-, and Transdisciplinary MA Studies that Increase Practical Relevance of Research

Timeline

• June 8, 2026: Opening date for manuscripts submissions
• September 30, 2026: Closing date for manuscripts submission

Mark Camilleri, University of Malta

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). The latter can monitor situations, allocate resources, initiate and manage processes as well as co-ordinate multiple activities. Hence, Agentic AI algorithms and their governance affect service outcomes.

Appel publié par Journal of Services Marketing. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• 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
• Organizational, strategic and policy implications of Generative and Agentic AI in services

Timeline

• June 23, 2026: Opening date for manuscripts submissions
• February 26, 2027: Closing date for manuscripts submission

This Special Issue aims to advance understanding of how AI is reshaping work and employment for underrepresented groups, and to stimulate research on how HRM can foster more inclusive, equitable, and human-centered AI-enabled workplaces. It seeks to bring together multidisciplinary scholarship examining both the opportunities and risks of AI for women, migrants, refugees, older workers, people with disabilities, and Indigenous employees. These aims will be met by inviting conceptual, empirical, and review-based contributions that examine bias, accessibility, trust, human–AI collaboration, inclusive design, and responsible governance in AI-HRM systems. In doing so, the Special Issue will generate new theoretical insights, practical implications, and future research directions that position HRM scholarship to respond more effectively to the challenges and possibilities of AI-driven organizational change, while helping organizations foster more equitable, inclusive, and human-centered human–AI interactions.

Appel publié par Personnel Review. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• AI in Talent Acquisition and Selection: How do AI-based recruitment and selection systems create, reproduce, or mitigate biases against candidates from underrepresented groups (e.g., people with disabilities, older workers, migrants), and what mechanisms can ensure equitable outcomes in AI-assisted hiring?
• Accessibility and Inclusion in Employment: In what ways can AI technologies be designed to enhance workplace accessibility, enable equitable participation, and expand employment opportunities for employees with disabilities or other marginalized groups?
• Human–AI Collaboration and Bias Mitigation: How can human oversight, input from minority employees, and inclusive design processes help AI systems learn more equitably—reducing bias and performing more human-like or human-better tasks in HR contexts?
• Talent Development, Reskilling, and Learning in the Age of AI: How can HRM leverage AI-enabled learning, development, and reskilling systems to support diverse employees and prepare both workers and organizations for ethical AI use? How can organizations use talent development strategies to train both humans and AI systems toward ethical and inclusive performance?
• Ethical, Legal, and Governance Challenges in AI-HRM: What are the ethical and legal implications of using AI in managing diversity and disability inclusion, and how can organizations establish responsible AI governance frameworks aligned with human rights and DEI principles?

Timeline

• January 9, 2026: Opening date for manuscripts submissions
• January 3, 2027: Closing date for manuscripts submission