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School of Public Policy and Administration, Xi’an Jiaotong University, Xi’an 710049, China
Prof. Dr. Yee Mey Goh
School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University, Leicestershire LE11 3TU, UK
Dr. Yu-Chi Lee
Department of Industrial Engineering and Management, National Taipei University of Technology, Taipei 106344, Taiwan
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Integrating Human Factors and AI: Driving the Transition to Industry 5.0 and Society 5.0

Abstract submission deadline
20 October 2026
Manuscript submission deadline
20 December 2026
Viewed by
2341

Topic Information

Dear Colleagues,

Industry 5.0 and Society 5.0 represent the next wave of technological advancements, emphasizing human-centric approaches and the seamless integration of artificial intelligence (AI) into various aspects of industry and society. This Topic calls for original research articles and reviews presenting cutting-edge theories and practices at the intersection of human factors and AI collaboration, addressing the challenges and opportunities in creating a more sustainable, inclusive, and intelligent future. Research areas may include (but are not limited to) the following:

  1. Human Factors in AI Integration
  • Human–AI Interaction: Design principles, user experience, and cognitive aspects of human–AI collaboration and advanced applications of large language model-driven human–AI interaction.
  • Ethical Considerations: Privacy, trust, and ethical frameworks for AI applications in Industry 5.0 and Society 5.0.
  • Human-Centric AI: Ensuring AI systems are designed to enhance human capabilities and well-being.
  1. AI Applications in Industry 5.0
  • Smart Manufacturing: AI-driven automation, predictive maintenance, and quality control.
  • Supply Chain Optimization: AI for logistics, inventory management, and supply chain resilience.
  • Customer service Optimization: AI tools for internal customer training, skill development, and job redesign; AI tools for external customer response and service failure recovery.
  1. AI Applications in Society 5.0
  • Smart Cities: Leveraging AI for advanced urban planning, intelligent transportation systems, and environmental sustainability initiatives.
  • Healthcare: Utilizing AI in diagnostics, personalized medicine, patient care, and urban restorative design to enhance daily healthcare for citizens.
  • Education: Implementing AI-driven learning systems, adaptive educational technologies, and promoting lifelong learning.
  1. Cross-Disciplinary Approaches
  • Collaborative Systems: Multi-agent systems, human–robot collaboration, EEG, eye tracking or advanced immersive systems on industrial contexts, and swarm intelligence.
  • Innovation and Entrepreneurship: Case studies of successful AI startups and innovation ecosystems.
  • Public Policy and Governance: Regulatory frameworks, standards, and international cooperation for AI.

We look forward to receiving your contributions.

Dr. Ching-Hung Lee
Prof. Dr. Yee Mey Goh
Dr. Yu-Chi Lee
Topic Editors

Keywords

  • human factors
  • AI
  • Industry 5.0
  • Society 5.0
  • collaborative systems

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
AI
ai 		6.5 7.3 2020 20.4 Days CHF 1800 Submit
Applied System Innovation
asi 		3.4 9.0 2018 21.3 Days CHF 1600 Submit
Big Data and Cognitive Computing
BDCC 		5.3 11.4 2017 23.3 Days CHF 1800 Submit
Digital
digital 		- 6.7 2021 25.6 Days CHF 1200 Submit
Systems
systems 		3.8 5.4 2013 19.8 Days CHF 2400 Submit

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Published Papers (1 paper)

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37 pages, 534 KB  
Article
Overcoming Technological Lock-In: How External Pressure Reshapes Innovation Trajectories in the Age of AI
by Shupeng Lyu, Ling Yuan, Pengfei Zhang and Ching-Hung Lee
Systems 2026, 14(6), 670; https://doi.org/10.3390/systems14060670 - 11 Jun 2026
Cited by 1 | Viewed by 996
Abstract
Amid the increasingly stringent technological blockade imposed by some Western developed countries, and against the backdrop of rapid advances in artificial intelligence (AI) and emerging Industry 5.0 paradigms, enhancing indigenous innovation capabilities and overcoming key technological bottlenecks has become an urgent imperative. Drawing [...] Read more.
Amid the increasingly stringent technological blockade imposed by some Western developed countries, and against the backdrop of rapid advances in artificial intelligence (AI) and emerging Industry 5.0 paradigms, enhancing indigenous innovation capabilities and overcoming key technological bottlenecks has become an urgent imperative. Drawing on path dependence and path creation theories, as well as the Stimulus–Organism–Response (SOR) framework, this study develops an analytical framework to examine how technological blockade accelerates indigenous innovation in latecomer countries. Using a multiple-case study design, the proposed framework is examined through two strategic technology domains: generative artificial intelligence and new energy vehicles (NEVs). Data were collected through technical documentation, publicly available interview materials involving key stakeholders, and third-party reports. The findings indicate that technological blockade accelerates the transition from imitative to indigenous innovation in latecomer countries. Further mechanism analysis reveals that the external pressure formation mechanism, endogenous motivation activation mechanism, and innovation behavior transformation mechanism jointly constitute a pressure-driven transformation mechanism. Specifically, technological blockade, as an external stimulus, disrupts the existing path-dependent state of imitative innovation; the blockade-induced pressure activates the endogenous motivation of innovation actors, which is further reinforced under national foundational conditions and policy guidance; and under the combined influence of external pressure and endogenous motivation, innovation actors’ behaviors undergo significant changes, gradually shifting from reliance on external technologies and resources toward indigenous R&D and breakthroughs in key technologies. This process ultimately drives the transition from imitative to indigenous innovation, marking a shift from path dependence to path creation. By demonstrating how technological blockade accelerates the transition of the innovation trajectory, this study offers theoretical insights for latecomer countries facing external technological constraints and provides policy implications for building resilient innovation ecosystems and enhancing technological autonomy in the era of AI-driven industrial transformation. Full article
(This article belongs to the Topic Integrating Human Factors and AI: Driving the Transition to Industry 5.0 and Society 5.0)
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