The transition from data-driven to cognitively adaptive supply chains represent a critical step toward Industry 6.0, where learning, coordination, and sustainability must be addressed jointly. Existing supply chain analytics approaches remain limited in capturing adaptive and systemic behaviors under uncertainty, particularly in resource-and energy-intensive industrial contexts. This study proposes a Cognitive and Data-Driven Framework for Supply Chains based on federated learning and synthetic data simulations grounded in aggregated industrial benchmarks. The framework introduces the Adaptivity Coefficient (Ac), a composite metric integrating learning velocity, anticipatory responsiveness, and technological exposure to quantify cognitive readiness at the network level. Results from simulation experiments show that cognitively adaptive supply chains achieve significant performance improvements compared to conventional predictive approaches. Specifically, cognitive coordination reduces cumulative disruption costs by 18-25 %, lowers emissions intensity by up to 15 %, and shortens recovery time by approximately 27 %. The analysis further demonstrates that adaptive learning expands the Pareto-efficient frontier, enabling simultaneous gains in cost efficiency, resilience, and environmental performance under varying levels of uncertainty. These findings suggest that cognitive adaptivity functions as a strategic capability rather than a purely technical feature. The study concludes by highlighting the managerial and policy implications of embedding cognitive learning into supply chain governance and by outlining pathways for future empirical validation in hard-to-abate manufacturing sectors.

With increasing geopolitical risks, environmental pressures, and regulatory demands, the sustainable sourcing of raw materials has become a global priority for achieving the United Nations Sustainable Development Goals (SDGs), particularly SDG 9 (Industry, Innovation and Infrastructure), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action). This study presents a data-driven framework for assessing the substitution of imported primary raw materials with secondary resources derived from mining waste, using the Italian ceramic industry as a testbed. Through a combined approach integrating material characterization, life cycle assessment, and supply chain analytics, we evaluate the technical, environmental, and resilience performance of substituting Turkish albite with feldspathic waste from Calabrian quarries. Results show that hybrid logistics configurations (truck and ship) for domestic by-products can outperform imported materials in terms of greenhouse gas emissions, supply chain resilience, and strategic autonomy while supporting circular economy principles. The framework provides replicable analytical tools to support evidence-based sourcing decisions in resource-intensive sectors, helping companies and policymakers align operational practices with sustainability goals. Implications for circular value creation, climate mitigation, and industrial policy are discussed.

This study advances toward establishing the theoretical foundations of Industry 6.0 by developing a comprehensive framework that integrates artificial intelligence (AI), decentralized control systems, and cyber–physical production environments for intelligent, sustainable, and adaptive manufacturing. The research employs a tri-modal methodology (deductive, inductive, and abductive reasoning) to construct a theoretical architecture grounded in five interdependent constructs: advanced technology integration, decentralized organizational structures, mass customization and sustainability strategies, cultural transformation, and innovation enhancement. Unlike prior conceptualizations of Industry 6.0, the proposed framework explicitly emphasizes the cyclical feedback between innovation and organizational design, as well as the role of cultural transformation as a binding element across technological, organizational, and strategic domains. The resulting framework demonstrates that AI-driven decentralized control systems constitute the cornerstone of Industry 6.0, enabling autonomous real-time decision-making, predictive zero-defect manufacturing, and strategic organizational agility through distributed intelligent control architectures. This work contributes foundational theory and actionable guidance for transitioning from centralized control paradigms to AI-driven distributed intelligent manufacturing control systems, establishing a conceptual foundation for the emerging Industry 6.0 paradigm.

This paper introduces cognitive adaptivity as a novel framework for addressing human factors in cybersecurity during the Industry 5.0–6.0 transition, with a focus on hard-to-abate industries where digital transformation intersects sustainability constraints. While the integration of IoT, automation, digital twins, and artificial intelligence expands industrial efficiency, it simultaneously exposes organizations to increasingly sophisticated social engineering and AI-powered attack vectors. Traditional resilience-based models, centered on recovery to baseline, prove insufficient in these dynamic socio-technical ecosystems. We propose cognitive adaptivity as an advancement beyond resilience and antifragility, defined by three interrelated dimensions: learning, anticipation, and human–AI co-evolution. Through an in-depth case study of the ceramic value chain, this research develops a conceptual model demonstrating how organizations can embed trust calibration, behavioral evolution, sustainability integration, and systemic antifragility into their cybersecurity strategies. The findings highlight that effective protection in Industry 6.0 environments requires continuous behavioral adaptation and collaborative intelligence rather than static controls. This study contributes to cybersecurity literature by positioning cognitive adaptivity as a socio-technical capability that redefines the human–AI interface in industrial security. Practically, it shows how organizations in hard-to-abate sectors can align cybersecurity governance with sustainability imperatives and regulatory frameworks such as the CSRD, turning security from a compliance burden into a strategic enabler of resilience, competitiveness, and responsible digital transformation.

This study investigates how AI-driven innovations are reshaping manufacturing value chains through the transition from Industry 4.0 to Industry 6.0, particularly in resource-intensive sectors such as ceramics. Addressing a gap in the literature, the research situates the evolution of manufacturing within the broader context of digital transformation, sustainability, and regulatory demands. A mixed-methods approach was employed, combining semi-structured interviews with key industry stakeholders and an extensive review of secondary data, to develop an Industry 6.0 model tailored to the ceramics industry. The findings demonstrate that artificial intelligence, digital twins, and cognitive automation significantly enhance predictive maintenance, real-time supply chain optimization, and regulatory compliance, notably with the Corporate Sustainability Reporting Directive (CSRD). These technological advancements also facilitate circular economy practices and cognitive logistics, thereby fostering greater transparency and sustainability in B2B manufacturing networks. The study concludes that integrating AI-driven automation and cognitive logistics into digital ecosystems and supply chain management serves as a strategic enabler of operational resilience, regulatory alignment, and long-term competitiveness. While the industry-specific focus may limit generalizability, the study underscores the need for further research in diverse manufacturing sectors and longitudinal analyses to fully assess the long-term impact of AI-enabled Industry 6.0 frameworks.

In the contemporary era of Industry 5.0, characterized by the integration of digital technologies and human-centered approaches, the assessment of social sustainability remains a critical challenge. Corporate responsibility and Environmental, Social, and Governance compliance are being reshaped by these developments. This paper aims to address the gap between industrial development and social impact by exploring the transformative potential of Social Life Cycle Assessment within the stakeholder framework established by the United Nations Environment Program. The proposed methodology is both standardized and data-driven, employing advanced techniques such as Principal Component Analysis and sigmoid normalization to minimize subjectivity and enhance comparability. It is validated through a case study in the Italian ceramic industry, utilizing internal organizational data aligned with Social Organizational Life Cycle Assessment guidelines. The findings highlight the urgent need for reliable, data-driven social impact assessments to support regulatory compliance, strengthen Environmental, Social, and Governance strategies, and foster long-term corporate sustainability. Furthermore, the results demonstrate how integrating Social Organizational Life Cycle Assessment into Industry 5.0 frameworks can improve stakeholder engagement, drive social innovation, and contribute to sustainable business practices.

Smart manufacturing demands adaptive, scalable, and human-centric solutions for predictive maintenance. This paper introduces the concept of Agentic AI, a paradigm that extends beyond traditional multi-agent systems and collaborative AI by emphasizing agency: the ability of AI entities to act autonomously, coordinate proactively, and remain accountable under human oversight. Through federated learning, edge computing, and distributed intelligence, the proposed framework enables intentional, goal-oriented monitoring agents to form self-organizing predictive maintenance ecosystems. Validated in a ceramic manufacturing facility, the system achieved 94% predictive accuracy, a 67% reduction in false positives, and a 43% decrease in unplanned downtime. Economic analysis confirmed financial viability with a 1.6-year payback period and a €447,300 NPV over five years. The framework also embeds explainable AI and trust calibration mechanisms, ensuring transparency and safe human–machine collaboration. These results demonstrate that Agentic AI provides both conceptual and practical pathways for transitioning from reactive monitoring to resilient, autonomous, and human-centered industrial intelligence.

Technological infrastructures critically drive resilience and sustainability in manufacturing supply chains yet remain severely underrepresented in conventional sustainability assessment frameworks. This paper introduces the Organizational Technological Sustainability Assessment (O-TSA), an innovative data-driven model that transforms operational technology data into strategic insight. Anchored in Life Cycle Thinking, O-TSA evaluates technological sustainability through three quantifiable dimensions: Input/Output Availability, Operational Performance, and Technical Quality, each measured via weighted indicators and standardized scoring functions. The framework delivers two actionable metrics: the Technological Sustainability Index (TSI), providing a precise measurement of current technological maturity, and the Technology Improvement Index (TII), quantifying performance evolution to enable evidence-based decision-making. When applied to a ceramic tile manufacturer, the model revealed specific operational inefficiencies while documenting a significant improvement in technological sustainability over a one-year period, primarily through enhanced documentation systems and digital integration. Empirical validation confirms the model's effectiveness in converting fragmented data streams into prioritized action points. By rendering previously invisible technological dependencies explicit and measurable, the O-TSA framework enables supply chain managers to align technological investments with sustainability objectives, facilitating the development of analytically-managed, resilient industrial ecosystems in resource-intensive environments.

The European Union (EU) is fundamentally transforming sustainability governance by developing dual approaches that extend far beyond traditional environmental policy. This study explores how EU institutions integrate strategic sustainability, which embeds environmental goals within economic security and geopolitical frameworks, with systemic sustainability, which emphasizes circularity, stakeholder engagement, and long-term resilience. Using hermeneutic methodology, the research analyzes key policy documents including the European Green Deal, Circular Economy Action Plan, and Carbon Border Adjustment Mechanism to reveal how sustainability narratives align with strategic autonomy and economic resilience. The findings demonstrate that sustainability governance now operates as a multi-dimensional paradigm balancing sovereignty, competitiveness, and inclusiveness. The study introduces the Neo-Sovereign Strategic Management (NSSM) framework, conceptualizing sustainability as a strategic field where economic security, geopolitical influence, and environmental objectives converge. This dual strategic–systemic approach represents a paradigm shift from standalone environmental goals toward integrated governance that positions sustainability as both economic driver and geopolitical asset. The research contributes to the sustainability governance literature by providing actionable insights for policymakers navigating the complex intersection of environmental objectives, economic security, and strategic autonomy in contemporary EU governance. Unlike existing models such as multi-level governance or resilience theory, the frameworks conceptualize sustainability as a strategic field where sovereignty, competitiveness, and legitimacy converge.

The combined action of the pandemic first and geopolitical tensions later has highlighted the fragility of many global supply chains. An unexpected event in an interconnected world requires companies to react quickly to respond to change. This chapter analyzes critical issues emerging in the Italian ceramic industry supply chain, which is characterized by a high intensity of natural and energy resource use and a sourcing system with high geopolitical risk. Using the transdisciplinary methodological approach as a perspective for solving complex problems in manufacturing, alternative supply chain scenarios are outlined to identify nearshoring and reshoring strategies for a more resilient and sustainable supply for the Italian ceramic industry.

This seminal study explores systemic sustainability within the Industry 5.0 paradigm, using the strategic lens of geoanthropology to shape the emerging concept of Industry 6.0. A transdisciplinary approach is adopted, integrating geoanthropological insights into the analysis of the Italian ceramic district. Seven key factors are considered: resource consumption, production dynamics, innovation, environmental impact, social impact, market dynamics, and economic impact. Historical events such as changes in Italian industrial policy, market slowdowns, and the COVID-19 pandemic are identified as significant for the sector. A contingent analysis tailored to the unique characteristics of the ceramic district provides an in-depth understanding of its challenges and opportunities. The incorporation of geoanthropology provides a transdisciplinary perspective that allows for an in-depth examination of the complex interactions between people and their environment in an industrial setting. The study highlights the central role of innovation, digitalization, and government policies in driving positive changes in production efficiency, market dynamics, and economic impact. Nevertheless, challenges remain, including the delicate balance between environmental sustainability and resource consumption, as well as the effective management of the social impacts of digitization. To address these challenges, a systemic sustainability index derived from geoanthropological insights is proposed as a pragmatic tool to measure and guide the development of sustainability initiatives in the ceramic district. The results of this study not only pave the way for new horizons in sustainability assessment but also provide valuable insights for industrial district managers to formulate strategies that foster organizational flexibility and resilience.

This study explores the complex nexus between technological innovation, Industry 4.0′s transformative paradigm, and the emerging concept of Industry 5.0, highlighting the critical role of integrating sustainability into factories to enhance organizational competitiveness. In this context, confusion arises between the terms “sustainable technologies” and “technological sustainability” due to two factors: the misuse of the terms as synonyms and the misattribution of conceptual meaning to each term. To clarify this ambiguity, this study validates a conceptual framework for technological sustainability by examining the processes of a ceramic manufacturing company. This assessment highlights the potential of technological sustainability and its associated measurement model to facilitate the transition from Industry 4.0 to Industry 5.0. This research provides fundamental insights into technological sustainability and serves as a guide for future empirical efforts aimed at achieving a balanced and sustainable integration of technology into manufacturing practices.

The world is currently undergoing an unprecedented period of global disruption, marked by the COVID-19 pandemic, the ongoing war in Ukraine, and escalating geopolitical tensions [...]

Historically, corporate assessment of performance has placed a significant emphasis on financial measures, while largely ignoring the broader environmental and resource efficiency implications of organizational operations. This paper introduces a novel framework that integrates thermoeconomic principles into performance measurement. Systemic Exergy Management (SYMΞX) The study employs a theoretical construction approach, deriving conceptual claims from an extensive literature review to bridge the gap between thermoeconomics and existing frameworks. These claims are then synthesized into a novel theoretical construct, designated the SYMΞX framework, through the process of abductive reasoning. This flexible paradigm focuses on measuring the effectiveness of resource consumption in organizations using exergy analysis. Moreover, it enables the development of sustainability performance indicators for assessing impacts on the environment, economy, society, and technology. SYMΞX offers a more comprehensive perspective on organizational performance, accounting not only for financial outcomes but also for resource efficiency and environmental impacts. The study posits that SYMΞX has the potential to advance business science in two main ways: by fostering ethical corporate practices and by enhancing performance measurement. In conclusion, the framework promotes systemic sustainability while offering new avenues for empirical validation and industry-specific applications, thereby ensuring adaptability to evolving business environments.

This study explores the use of Additive Digital Molding, an Industry 5.0-driven approach, to improve business agility and sustainability within supply chains. By integrating digital reverse engineering, additive manufacturing, and plastic injection molding, this methodology streamlines product development processes, particularly for highly customized products in isolated environments. Additive Digital Molding provides cost-effective solutions for overcoming sourcing challenges, meeting customization requirements, and ensuring confidentiality. It also empowers SMEs and individuals to take greater control of their supply chains and foster entrepreneurial ventures. By enabling new business models such as direct manufacturing and home production, additive digital molding contributes to achieving the Sustainable Development Goals of the 2030 Agenda. This research highlights the transformative potential of Additive Digital Molding to drive innovation and sustainability across industries.

Sustainability’s growth, year after year, continues to be staggering, becoming a reference point for those working on these issues [...]

Purpose The best strategy to apply for the future cannot disregard a careful analysis of the past and is the one capable of seizing opportunities from outside. Manufacturing sectors are characterized by sudden changes, and in this work, we analyze the ceramic tiles sector characterized by a mature technology in which innovation has played a key role. Design/methodology/approach This study aims to provide a sectorial analysis based on a historical data set (2004–2019) to highlight how an industry is performing both operationally and in terms of eco-efficiency. For this purpose, from a methodological point of view, the data envelopment analysis (DEA) was used. Findings The results of the analysis show that the Spanish ceramics industry shows a growing economic trend by taking advantage of lower industrial costs, while the Italian industry is characterized by a modest decline partially mitigated by exports. The industrial districts are an aggregation of companies that in the ceramic sector has allowed to combine innovation, sustainability and digitalization and is a model toward the maximization of sustainable efficiency because it is a place of aggregation of resources and ideas. Originality/value This study experiments with an innovative way of addressing traditional industry analysis, namely, integrating the reflective management approach with DEA-based backward analysis. This provides decision makers with the basis for new interpretations of variable trends.

Equality of opportunity for all people, regardless of their abilities, is a fundamental principle in contemporary society. This includes the ability to use any object, service, or environment. The analysis of universal accessibility in the built environment is a requirement to achieve the full inclusion of society as a whole, both in the urban and architectural spheres. This study is based on the analysis of the current and potential states of accessibility, which makes it possible to obtain the accessibility improvement index, a parameter that identifies how much the accessibility of a physical environment can be improved by removing architectural barriers. The methodology is applied to a sample of 25 heritage buildings used as museums to observe how they function. The results show that the feasibility of barrier removal is higher than 75% in all the buildings in the sample, reaching 100% in some cases. The results obtained are contrasted with other works and highlight the potential of expanding the analysis developed to other urban and built environments to ensure full equality of access to the physical environment.