Conference Information

MSIE 2027: International Conference on Management Science and Industrial Engineering

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Submission Date:
2026-11-30 Due in 80 days
Notification Date:
2026-12-30
Conference Date:
2027-04-28
Location:
Seoul, South Korea
Years:
Viewed: 20690   Tracked: 5   Attend: 2

Conference Partner Index (CP-I)

51.1 / 100
Ranked #1,328 of 5,680 conferences · Top 24%

#9 of 73 in Management & Social Sciences

Academic recognition (35%) No data - scored at the neutral baseline of 50 —
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
62
Community attention (10%)
29
Public record completeness (15%)
55

Inputs used: Editions on record: 9 · Researchers following it here: 5 · Researchers who opened this page in the past 24 months: 4

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 45% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-09-11

Call For Papers

MSIE 2027 (International Conference on Management Science and Industrial Engineering) is an academic conference held in Seoul, South Korea on 2027-04-28. The paper submission deadline is 2026-11-30. Acceptance notifications are sent on 2026-12-30.

The 2027 9th International Conference on Management Science and Industrial Engineering (MSIE 2027) invites high-quality submissions that explore innovative, interdisciplinary, and transdisciplinary approaches to addressing complex challenges at the intersection of management science, industrial engineering, and beyond. Topics of interest include, but are not limited to: 1. Interdisciplinary Decision Science and Optimization Hybrid Models for Decision-Making: Combining Operations Research, Behavioral Science, and AI Multi-Criteria Decision Analysis for Complex Systems Computational and Simulation-Based Approaches in Risk and Crisis Management Human-AI Collaboration for Strategic and Tactical Decision-Making 2. Sustainable and Resilient Systems Circular Economy and Sustainable Industrial Operations Transdisciplinary Approaches to Achieving Net-Zero Emissions in Industrial Systems Resilient Supply Chain Networks in the Face of Global Disruptions Systems Thinking and Integrated Modeling for Sustainability 3. Industry 4.0 and Smart Systems AI, IoT, and Blockchain for Smart Manufacturing and Logistics Digital Twins and Cyber-Physical Systems in Industry 4.0 Autonomous Systems and Robotics in Industrial Applications Ethical and Human-Centric Automation for Future Workplaces 4. Data-Driven and Computational Approaches Big Data Analytics and Predictive Modeling in Management Science Machine Learning and AI for Operations Optimization Quantum Computing Applications in Management and Industrial Systems Cross-Disciplinary Applications of Data Science in Industrial Innovation 5. Human-Centric Management and Engineering Integrating Psychology, Sociology, and Engineering in Workforce Optimization Ergonomics and Human Factors for Productivity and Well-Being Managing Diversity and Inclusion in AI-Driven Workplaces The Future of Work: Hybrid Work Models and Virtual Collaboration 6. Innovation in Supply Chain and Logistics Blockchain-Driven Supply Chain Transparency and Efficiency AI-Optimized Logistics in Global and Regional Contexts Sustainable Logistics and Green Transportation Networks Risk Management in Dynamic and Uncertain Supply Chains 7. Education and Knowledge Management in Industrial Engineering Innovative Pedagogies for Interdisciplinary Engineering Education Cross-Functional Knowledge Management and Organizational Learning AI and Virtual Reality for Workforce Training and Skill Development 8. Ethics, Society, and Policy Ethical Implications of AI and Automation in Industrial and Management Practices Policy Frameworks for Sustainable Industrial Development Social Responsibility in Industrial Engineering and Management Systems Bridging the Gap Between Policy, Technology, and Society 9. Big Data in Quality and Reliability Engineering and Management Deeper Insights into Products, Processes, and Systems ML Algorithms to Identify Patterns Life-cycle Modelling Moving from Reactive Quality Control to Quality 5.0 Proactive Model Innovations in Service Delivery Models Aligning Supplier KPIs with Organizational Quality and Reliability Goals 10. Systems Engineering and Simulation Track Cognitive Systems Architecture and Design Energy Systems and Sustainability Simulations IoT-enabled Smart City Systems System Dynamics Modelling for Defence Systems Trade-off Analysis for Complex System Design Special Sessions and Tracks Authors are also encouraged to submit proposals for special sessions that tackle emerging transdisciplinary challenges or focus on case studies and applications that span multiple disciplines.
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