Aamir Rashid, City University of New York

Rizwana Rasheed, City University of New York

Organizations face ongoing disruptions and must adapt their supply chains while managing sustainability and digital transformation. However, there is limited frameworks for measuring and comparing adaptive supply chain performance across different organizations and contexts. This special issue seeks to advance research that uses benchmarking logic to systematically evaluate how well supply chains adapt.

The special issue emphasizes understanding adaptive performance through the interaction of people, technology, governance, and sustainability practices. Rather than treating adaptation as a general concept, research should operationalize adaptability with measurable constructs and benchmarking frameworks that highlight performance differences between configurations.

Contributions should employ rigorous comparative designs using quantitative, qualitative, or mixed methods to benchmark adaptive supply chains across industries and countries. By identifying which configurations perform better and under what conditions, the research will provide actionable insights for practitioners and policymakers.

Appel publié par Benchmarking: An International Journal. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Benchmarking adaptive supply chain performance across industries and regions
• Performance metrics and composite indices for adaptive, sustainable, and resilient supply chains
• Supply chain maturity models and benchmarking trajectories
• Socio-technical configurations and comparative performance outcomes
• Benchmarking digital and AI-enabled supply chain systems
• Performance frontiers and efficiency analysis of adaptive supply chains
• Cross-country and institutional benchmarking of supply chain adaptability
• Governance, collaboration, and coordination as benchmarked performance drivers
• Comparative analysis of sustainability and resilience performance trade-offs

Timeline

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

Fernando Miramontes Forattini, Dublin City University

Regina Connolly, Dublin City University

This special issue examines how care ethics and relational approaches can advance responsible design and governance of AI-enabled systems. While contemporary AI ethics discourse has focused on fairness, transparency, and compliance frameworks, this call seeks to address the structural, relational, and institutional dimensions of how digital systems affect vulnerability, participation, and human agency.

The special issue invites empirical research, conceptual contributions, design science research, and interdisciplinary perspectives that move beyond procedural approaches to explore responsibility distribution across socio-technical arrangements. Submissions should examine relationships between technology, power, participation, exclusion, and accountability in digital environments, grounded in diverse epistemological and methodological traditions.

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

Potential topics

• Care ethics and Information Systems design
• Responsible AI and relational accountability
• Ethics of participation, inclusion, and exclusion in digital systems
• Structural ethics and socio-technical governance
• Human-centred and care-centred AI design
• Vulnerability, dependency, and digital infrastructures
• AI governance and institutional legitimacy
• Ethics of repair, maintenance, and redress in digital systems
• Participatory and inclusive approaches to AI governance
• Responsible innovation and structurally aware design
• Public sector AI and questions of care, trust, and legitimacy
• Algorithmic systems and the distribution of risk and burden
• Gender, inequality, and digital governance
• Ethics of automated decision-making
• Relational approaches to trust, transparency, and accountability
• Organizational responsibility in AI-enabled environments
• Care ethics and sustainability in digital transformation

Timeline

• September 30, 2026: Manuscript submission deadline
• November 30, 2026: First review decisions
• February 1, 2027: Revised manuscript submission
• March 15, 2027: Final decisions

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,