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

Karl Wennberg, Stockholm School of Economics

Jeremy C. Short, University of North Texas

Jeffrey A. Chandler, University of North Texas

Marcus Wolfe, University of North Texas

Sebastian Kruse, RWTH University

Carolin Krieweth, RWTH University

Entrepreneurship research lacks a strong culture of replication despite its importance for building cumulative theory and validating findings. While many influential studies shape theoretical debates and practice, they have rarely been systematically retested to verify their robustness, stability over time, or applicability across different contexts. This special issue seeks to address this gap by encouraging rigorous replication studies of foundational empirical work in entrepreneurship.

The issue welcomes diverse methodological approaches to replication, from exact replications to reanalyses of original data and studies exploring boundary conditions and contextual factors. Rather than merely confirming prior findings, submissions should advance theoretical understanding by clarifying mechanisms, identifying when relationships hold or vary, and contributing to methodological best practices. All work will be evaluated on theoretical contribution and methodological rigor within the journal's standard review process.

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

Potential topics

• The 33 most cited entrepreneurship studies (each exceeding 1,000 citations) identified as priority candidates for replication
• Influential studies within specific BCERC research tracks highlighted as important contributions
• Studies with credible cases for broader influence on entrepreneurship research
• Identifying boundary conditions and contextual contingencies of established relationships
• Clarifying inconsistencies or mixed findings in prior research
• Refining theoretical mechanisms underlying key constructs and relationships
• Contributing to methodological transparency, rigor, and best practices in replication research
• Multi-study designs combining exact replication or reanalysis with empirical generalization or theoretical extension

Timeline

• December 1, 2026: Deadline for short proposals (3,000–5,000 words) for paper development workshop participation
• January 1, 2027: Notifications regarding paper development workshop participation
• February 1, 2027: In-person paper development workshop at University of North Texas
• March 1, 2027: Virtual paper development workshop
• May 1, 2027: Manuscript submission window opens
• August 1, 2027: Manuscript submission deadline

This special issue of The Leadership Quarterly seeks empirical research that advances our understanding of leadership through rigorous causal inference methods. We invite submissions that employ experimental designs, quasi-experimental approaches, longitudinal studies, or other methodologically sound approaches to establish causal relationships in leadership phenomena.

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

Timeline

• November 22, 2026: Full paper submission deadline