Purpose: This study investigates the transition from Industry 4.0 to Industry 5.0, focusing on the integration of artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) to support human-centric, sustainable and resilient production systems. It aims to identify key trends, challenges and opportunities within this evolving industrial paradigm. Design/methodology/approach: A scientometric approach was employed using bibliometric and co-word analysis to examine global scientific literature on Industry 5.0. The study maps the evolution of research and technological advancements across sectors such as manufacturing, education, supply chains, and disaster management. Findings: The analysis highlights the growing importance of predictive maintenance, collaborative robots and cyber-physical systems in advancing sustainable and inclusive industrial practices. It also reveals increasing academic focus on ethical concerns such as workforce inclusion and data privacy. Emerging technologies like augmented reality and blockchain are identified as key enablers of Industry 5.0. Social implications: The findings support the development of inclusive, human-centered technologies that enhance societal well-being and promote ethical digital transformation in educational and industrial contexts. Originality/value: This study contributes to the field by offering a comprehensive scientometric overview of Industry 5.0 literature and its applications. It underscores the significance of interdisciplinary research and ethical frameworks in achieving balanced technological and societal progress. Moreover, this study bridges the gap between theory and practice by offering actionable insights for SMEs, healthcare and digital supply chains. It contributes a methodological framework applicable to other emergent interdisciplinary fields beyond Industry 5.0.

This study examined the integration of Industry 4.0 technologies with environmental, social, and governance (ESG) strategies to improve organizational sustainability and competitiveness. Industry 4.0 technologies, including blockchain, artificial intelligence (AI), the Internet of Things (IoT), and big data analytics, offer transformative capabilities for ESG reporting, resource optimization, and operational efficiency. By addressing sustainability challenges and advancing governance practices, these technologies enable businesses to meet their environmental and governance responsibilities while achieving economic growth. However, implementing Industry 4.0 in ESG frameworks presents challenges, such as high costs, poor data quality, and resistance to change. This paper analyzed existing literature to identify opportunities and barriers to aligning ESG with Industry 4.0, providing insights for managers, researchers, and policymakers. The report adds to the body of knowledge on sustainable innovation by pointing out the advantages and disadvantages of this integration. It also provides a roadmap for achieving sustainability-implementing goals over the long run in a rapidly evolving digital landscape.

This paper investigates the adoption of Industry 4.0 in developing countries, emphasizing the unique challenges these economies face compared to advanced nations. Despite the global spread of digital technologies such as automation, big data analytics, and the Internet of Things (IoT), adoption in resource-constrained contexts remains limited due to inadequate infrastructure, financial restrictions, skill gaps, and organizational resistance. To address these issues, the study employs a bibliometric methodology, analyzing 398 journal articles indexed in Web of Science through co-word and bibliographic coupling techniques. This approach enables the mapping of dominant themes, influential research clusters, and key gaps in the literature. The results highlight five thematic areas: global technological developments, sustainability integration, adoption barriers, implementation practices, and strategies for overcoming obstacles. Findings indicate that while challenges are considerable, Industry 4.0 can enhance productivity, stimulate Innovation, and support sustainability by strengthening supply chains and promoting efficient resource use. The study also reveals that transformative benefits can only be realized when supportive policies, international collaboration, private-sector participation, and workforce development are followed in a coordinated manner. The research contributes to theory by linking Industry 4.0 adoption to sustainability frameworks such as the Circular Economy and the Sustainable Development Goals. It also offers practical guidance for policymakers, SMEs, and managers on designing context-sensitive strategies tailored to developing economies. By providing a structured overview of challenges and opportunities, the study lays a foundation for future empirical research and offers actionable insights for advancing sustainable industrial transformation.

The emergence of Industry 4.0 has transformed the manufacturing sector, necessitating established frameworks to appraise digital preparedness. To fill in the gaps in current models that ignore the particular obstacles faced by small and medium-sized businesses (SMEs) and urban manufacturing firms, this study suggests a customized Urban Smart Factory (USF) maturity model. The approach incorporates essential elements, including sustainability, resilience, digitalization, and workforce competencies, providing a thorough assessment of smart manufacturing preparedness. Key research trends were diagnosed by bibliometric analysis, and case studies from several manufacturing sectors were used to validate the suggested model. According to the findings, a large number of firms inadequately use the instruments necessary to evaluate workforce and technology readiness, which leads to irregular attempts at digital transformation. By offering an organized framework for distinguishing technology gaps, assessing organizational adaptability, and facilitating the creation of strategic roadmaps for Industry 4.0 adoption, the USF maturity model fills this gap. By highlighting the connections between technology, human capital, and administrative processes, the study advances our acquiesce of digital transformation in the urban manufacturing framework and adds to the theoretical conversation. The recognition of the model provides useful information for businesses perceiving to advance their digital maturity while negotiating the challenges of smart manufacturing. Future studies should concentrate on incorporating cutting-edge technology like blockchain and artificial intelligence while broadening the model’s application through many businesses and geographical areas. Conclusively, our research creates the groundwork for manufacturing ecosystems that are robust, sustainable, and technologically sophisticated, spurring long-term growth and innovation.

The desire to balance environmental sustainability and food security is causing a significant upheaval in the agricultural sector. This study investigated how prepared stakeholders are to embrace agriculture in Industry 4.0, which integrates green, intelligent, and sustainable technologies like blockchain, IoT, and AI. Although these advances promise increased resilience and efficiency, they present significant obstacles to implementation, such as inadequate infrastructure, socioeconomic inequality, and a lack of technology awareness. This study highlights these technologies' theoretical and managerial implications and finds critical gaps using bibliometric and thematic analysis. To overcome adoption obstacles, it emphasizes the significance of inclusive policies, strategic alliances, and capacity-building programs. The study concludes that these impediments must be addressed to secure food systems for future generations and align agriculture with global sustainability goals. Longitudinal studies, stakeholder-centric methodologies, and investigating emergent technology synergies are among the suggestions for future research.

In the period of sustainable development, Environmental, Social, and Governance (ESG) reporting has turned a critical practice for enterprises. However, Small and Medium Enterprises (SMEs) look unique challenges in ESG compliance, particularly in tracking and transparency. This paper explores how digital technologies such as blockchain, Internet of Things (IoT), cloud computing, and AI enable ESG traceability and monitoring within SMEs. Throughout a structured review of recent 50 literature, the study investigates how digital ESG systems support regulatory compliance, stakeholder engagement, and sustainable development. We propose a framework for implementing digital ESG monitoring in SMEs and highlight practical challenges and opportunities. This review offers insights into scalable strategies and digital toolkits that SMEs can adopt to meet growing regulatory and societal expectations.