
Logistics is entering a new era. While the classic goals of increasing efficiency, reducing costs, and ensuring delivery reliability remain central, climate change, geopolitical uncertainties, and pandemic-related disruptions are shifting requirements toward resilience and sustainability. In this tense environment, the concept of intelligent logistics is gaining importance. But what exactly makes logistics smart, and why is it essential for the future of both the economy and society? The articles in this issue present various approaches—from predictive analytics and requirements analysis to skills development and the use of machine learning. Here you can find out why smart logistics is more than just a technological trend.
All articles at a glance
- Technologies for Assisting Manual Order Picking
From conventional pick-by systems to AI-driven manual picking assistance - Proactive Skill Development in Logistics Management
The future of dynamic work contexts - Smart Business Models in Intralogistics
A service-oriented approach to customized logistics solutions - Increasing Resilience in Logistics with IT
Investigating supply chain risk management information systems - Machine Learning to Promote Sustainability
Company analysis based on expert interviews - Sustainability Information Across the Supply Chain
Structured requirements analysis for using sustainability data in networks - Bridging Automated and Traditional Approaches in Material Transport
Why manual tugger train systems remain prevalent in intralogistics - Design Thinking
A practical approach - Requirements Analysis for Predictive Analytics in SCM
Decision support for research and practice - Enabler for the Digital Twin
Requirements for Technical Documentation 4.0 - Developing Data Standards in Battery Cell Manufacturing
From requirements analysis to standard development procedure - Field Meets Code
Artificial intelligence for better collaboration in software development
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