This special issue explores the ethical dimensions of entrepreneurship, focusing on how entrepreneurs engage in moral reasoning and decision-making. The call seeks research that examines the cognitive and emotional processes underlying ethical choices that entrepreneurs face, particularly in contexts marked by uncertainty and risk. The issue aims to advance understanding of how moral considerations shape entrepreneurial behavior and venture development.

Researchers are invited to submit work investigating the intersection of ethics, cognition, and emotion in entrepreneurial contexts. The special issue welcomes diverse perspectives on how entrepreneurs navigate ethical dilemmas, the role of affect in moral judgments, and mechanisms through which ethical considerations translate into concrete actions during the venture creation process.

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

Potential topics

• Moral cognition in entrepreneurship
• Affective processes in ethical decision-making
• Ethical action under uncertainty
• Entrepreneurial decision-making and ethics
• Moral reasoning in venture creation
• Emotional dimensions of ethical behavior

Timeline

• September 1, 2027: Submission deadline

Organizations face unprecedented challenges from uncertainty, technological change, and shifting work arrangements. This special issue calls for researchers to revisit fundamental HRM theories and examine whether established assumptions adequately explain the relationship between people, organizations, and performance in today's turbulent context. The issue seeks to move beyond incremental complexity by returning to core concepts and critically assessing whether traditional perspectives on HRM-strategy alignment, employee development, and performance outcomes remain sufficient.

The special issue welcomes theoretically grounded and methodologically rigorous contributions that challenge conventional HRM wisdom and propose new understandings relevant to uncertain environments. Research may address tensions and unintended consequences of HRM practices, sustainability concerns, digitalization, employee well-being, and emerging employment models. Empirical studies, conceptual papers, and literature reviews are all welcome, provided they offer clear advances to HRM theory and research.

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

Potential topics

• Revisiting Theoretical foundations of HRM in contexts of uncertainty
• Critical reassessments of the HRM–performance relationship
• Challenges to traditional strategic HRM assumptions
• HRM, organizational resilience, and adaptation to change
• HRM and employee performance in uncertain and complex environments
• Sustainable HRM, green HRM, and long-term organizational performance
• HRM and employee well-being, happiness, engagement, and inclusion
• HRM, knowledge management, innovation, and creativity
• HRM and the management of technological and digital transformation
• HRM and the need for professional reskilling
• Work intensification, stress, and the unintended consequences of HRM
• HRM systems, organizational culture, and competing performance outcomes
• HRM and new approaches to work
• New theoretical approaches to careers, employability, and work-life integration

Timeline

• March 31, 2027: Opening date for manuscripts submissions
• March 31, 2027: Closing date for abstract submission
• June 30, 2027: Closing date for manuscripts submission

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

Timeline

• December 31, 2026: Full paper submission deadline

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

Timeline

• October 30, 2026: Submission deadline

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

Timeline

• January 15, 2027: Full paper submission deadline

This special issue aims to examine the relationship between uncertainty and economic activity, alongside the role of policy in managing these dynamics. The collection seeks contributions that explore how uncertainty affects various economic outcomes and what policy responses may be effective in mitigating negative consequences.

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

Timeline

• November 30, 2026: Submission 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