Search Results (7,124)

Supply chain performance (SCP) has traditionally emphasized efficiency, but recent disruptions and the transition to Industry 5.0 (I5.0), organized around the principles of human-centricity, sustainability, and resilience, have exposed the limits of this orientation. These principles redefine what supply chains must deliver, yet most frameworks treat them in isolation or subordinate them to efficiency. This study reconceptualizes SCP management for the I5.0 era through an integrative review following Whittemore and Knafl’s protocol and PRISMA 2020 reporting. A Web of Science search of peer-reviewed articles (2020–2026), two-phase screening, and supplementary citation searches yielded 55 studies. The synthesis reveals three limitations: an efficiency bias privileging financial and operational metrics; an integration gap treating the I5.0 principles separately; and a human-centric measurement gap disconnecting social and workforce outcomes from strategic performance. The Supply Chain 360° Performance Management (SC360PM) framework is introduced as a conceptual architecture ready for validation that organizes SCP into five coequal dimensions: resilience and agility; cost efficiency and financial health; sustainability and environmental responsibility; innovation and digitalization; and human-centricity and social responsibility, decomposed into eighteen attributes. SC360PM conceptualizes performance as a multidimensional model for joint management, offering researchers a structured basis for empirical validation and managers a pathway toward viability-oriented performance governance. Full article

Digital twins (DTs) based on agent-based artificial intelligence (Agentic AI) provide a transformative framework for streamlining nondestructive testing (NDT) of 3D-printed rehabilitation equipment. This study applies a conceptual research methodology based on the integration and analysis of recent advances in Agentic AI, digital twin architectures, additive manufacturing, NDT technologies, and intelligent rehabilitation systems to establish a framework for autonomous quality monitoring and lifecycle management of 3D-printed medical devices. By creating intelligent virtual replicas of physical devices, these systems enable continuous monitoring of structural integrity, functional performance, and degradation mechanisms throughout the product lifecycle. Unlike conventional AI-based DTs, Agentic AI-driven DTs can autonomously perceive, reason, plan, and execute corrective actions based on real-time sensor data, NDT results, manufacturing information, and historical knowledge. The main conclusion of this work is that Agentic AI-enhanced DTs have the potential to transform NDT from a passive inspection approach into an intelligent, predictive, and autonomous decision-support system for rehabilitation equipment. Advanced machine learning and autonomous decision-making algorithms enable the identification of early signs of material degradation, manufacturing defects, fatigue accumulation, and performance anomalies, supporting predictive maintenance and proactive quality assurance. Integrating Agentic AI DTs with additive manufacturing processes enables real-time optimization of printing parameters, adaptive process control, and continuous refinement of inspection strategies without production interruption or destructive sampling, thereby supporting Industry 4.0 and smart manufacturing principles. The main innovation of this research lies in proposing an autonomous closed-loop framework that combines Agentic AI, DTs, additive manufacturing, and NDT into a unified system capable of continuous learning, reasoning, and operational optimization. Compared with existing studies that mainly focus on AI-assisted defect detection or static digital twin models, this approach introduces autonomous agents capable of coordinating sensing, simulation, diagnosis, prediction, and corrective actions across the entire lifecycle of 3D-printed rehabilitation devices. The proposed concept extends current digital twin applications by incorporating virtual stress testing, autonomous simulation, patient-specific customization, and adaptive device management, reducing dependence on physical prototypes, minimizing material waste, and accelerating design validation. By combining autonomous reasoning with predictive analytics, Agentic AI-based DTs represent a next-generation solution for intelligent, adaptive, and sustainable nondestructive testing, advancing both additive manufacturing technologies and personalized rehabilitation engineering. Full article

Modern power systems are evolving rapidly with growing distributed generation and high penetration of renewables and electric vehicles. Renewable sources, being inherently intermittent and weather dependent, may lead to rapid power fluctuations that challenge grid stability and power quality. Multilevel inverters (MLIs) have become a key enabling technology in modern power grids due to the escalating need for high-power, high-voltage, and high-quality energy conversion. Research on the control of MLIs in modern grid scenarios has significant scope due to the rising penetration of renewables, distributed generation and smart grid technologies. Hence sophisticated control strategies and topology selection of MLIs are required to enhance efficiency and to ensure optimal performance. Emerging areas like AI-based adaptive control find relevance in enabling stable, flexible and sustainable future power systems. In this comprehensive review, the state-of-the-art MLI classification, AI-driven control techniques, and their emerging technological applications are investigated. There is limited exploration of AI-based adaptive control for self-tuning operation and coordinated control of multiple MLIs in microgrids, active filtering and harmonic compensation in MLI-based modern power systems, and vehicle-to-grid (V2G) and bidirectional battery inverter control optimization integrated with MLI control. Full article

Automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) are among the key enabling technologies driving intelligent logistics and industrial automation. Despite their widespread adoption and rapid technological evolution, the literature often addresses AGV and AMR systems in a fragmented manner, lacking a structured methodological perspective that highlights their architectural foundations, levels of autonomy, and technological maturity. This paper presents a methodological survey of AGV and AMR technologies, focusing on system-level architectures and core functional components rather than isolated algorithms. The survey systematically analyzes key technological dimensions, including sensing and perception, localization and positioning strategies, navigation and path-planning approaches, communication infrastructures, and multi-robot coordination mechanisms. A clear distinction is drawn between classical AGV systems, which rely on fixed infrastructure and predefined routes, and AMR systems, which exhibit adaptive, perception-driven, and self-configuring behaviors enabled by artificial intelligence techniques. Rather than proposing new algorithms, this paper organizes existing approaches into a coherent framework that highlights technological transitions from infrastructure-dependent guidance to autonomous, data-driven navigation. Recent trends such as cloud–edge integration, learning-based navigation, scalable fleet management architectures, and cooperative multi-robot systems are reviewed and discussed from a methodological standpoint, emphasizing their role in increasing flexibility, robustness, and operational efficiency in industrial and logistics environments. The survey also addresses cross-cutting challenges, including system transparency, safety and certification, interoperability, and sustainability. Finally, this paper outlines research directions aligned with the principles of Industry 5.0, highlighting the need for human-centered, resilient, and scalable AMR and AGV systems capable of safe and explainable operation in complex industrial contexts. Full article

Tin-based halide perovskites have emerged as one of the most promising classes of lead-free materials for next-generation photovoltaic technologies. Their favorable optoelectronic properties, narrow band gaps, and structural compatibility with the ABX₃ perovskite framework position them as viable alternatives to conventional lead-based absorbers. This review summarizes the fundamental structural principles governing Sn-based perovskites, including the role of A-site cations, halide composition, tolerance factor, and octahedral distortion in determining phase stability and electronic structure. Recent advances in material engineering—such as additive-assisted crystallization, interface modification, precursor chemistry optimization, and two-dimensional/three-dimensional heterostructure formation—have significantly improved film quality, reduced defect densities, and enhanced device performance. Despite these achievements, challenges remain, particularly the spontaneous oxidation of Sn²⁺ to Sn⁴⁺, uncontrolled crystallization, and limited operational stability. Strategies aimed at stabilizing the Sn²⁺ oxidation state, suppressing self-doping, and improving charge transport are discussed in detail. The review also highlights the strategic importance of tin as a sustainable element for renewable energy technologies and provides an overview of global tin resources relevant to future photovoltaic deployment. Overall, tin-based perovskites represent a compelling pathway toward environmentally responsible and high-efficiency solar cells, with continued research expected to accelerate their transition from laboratory materials to commercially viable technologies. Full article

Paludiculture, the sustainable productive use of wet and rewetted peat soils, offers a dual solution for preserving soil carbon and reducing greenhouse gas emissions whilst offering a form of income for landowners/farmers. However, establishing best practices for the transition to wet agriculture production systems remains difficult due to the inherent variability of peatland sites. This study synthesises evidence from the peer-reviewed literature, grey literature, and stakeholder surveys to map current practices, concepts, knowledge gaps, and research priorities. The main gap is a lack of long-term studies tracking crops from establishment through multiple harvests. Practical knowledge is also geography-ically, limiting applicability without local environmental and policy context. Further critical gaps include crop species selection, upscaling, biodiversity impacts, specialised harvesting equipment, and evolving end-product markets, alongside country-specific legal and financial barriers. Key recommendations include establishing a robust initial site investigation as edaphic properties and previous land-use can inform crop establishment and potential operational hurdles. Furthermore, increased funding for long-term farm-based projects, technological innovation and prioritising producing data that supports finance models must be made available to offset the costs of transitioning and developing new, system-level agronomical tools. Ultimately, scaling paludiculture hinges on robust incentive frameworks, shared knowledge platforms, and standardised nomenclature to guarantee long-term environmental and economic sustainability. Full article

Environmental management and monitoring are essential for translating sustainability goals into operational practices in port systems. However, empirical evidence on how these processes are implemented in African ports remains limited, partly because comparable environmental management data are rarely available across ports. This exploratory study examines reported sustainability priorities, EMS-related organisational practices, and environmental monitoring arrangements in African ports using a structured practitioner-based self-diagnosis survey. Data were collected from 18 environmental managers, each representing one port, during a dedicated professional workshop. The analysis combines importance scoring of predefined sustainability items, binary self-reported information on EMS-related practices, and qualitative coding of open-ended responses on monitoring indicators, responsible entities, methodologies, and implementation challenges. The results should not be interpreted as statistically representative of African ports as a whole. Rather, they provide preliminary, practitioner-based evidence on recurring patterns and constraints reported by the participating ports. The findings suggest that core EMS-related elements, such as objectives, legal compliance, operational control, and monitoring, are more frequently reported than strategic and resource-intensive practices, including climate change integration, sustainability planning, and green services to shipping. Monitoring practices appear largely compliance-oriented, periodic, and dependent on external actors, reflecting reported constraints related to finance, technical expertise, equipment, and institutional coordination. The study contributes exploratory evidence from an under-researched regional context and develops tentative propositions for future research on environmental management capacity, monitoring integration, and sustainability transitions in African port systems. Full article

Research on social commerce, influencer marketing, consumer–brand engagement, and CEO social media communication has rapidly expanded. However, less is known regarding how entrepreneurial leaders’ personal short-video accounts operate as platformized interfaces that organize consumer interaction. This study examines how CEO short-video communication produces an observable, collectively sustained commercial persona and connects executive visibility with fan labor, consumer–brand engagement, and consumption imagination. Using the Douyin account of a leading Chinese technology entrepreneur as a case, this study analyzes 372 short videos posted up to 15 August 2024, and 185,561 valid first-level comments. It combines structured content analysis, intercoder reliability testing, BERTopic-assisted topic location, manual thematic validation, and text-based emotional intensity analysis. Work footage, scenes of everyday life, casual presentations, and product props translate entrepreneurial authority into an approachable, platformized commercial persona. In comment sections, users perform informational, relational, affective, memetic, mobilizing, and defensive labor through product requests, familiar address, emotional identification, memes, consumption mobilization, and brand defense. These practices stabilize CEO personas, circulate product meanings, and create consumption imagination, understood as public projections of saving for, ordering, using, or affiliating with products rather than evidence of actual purchases. Emotional identification, consumption mobilization, and brand defense display higher observable emotional intensity than product requests. This study contributes a case-derived conceptual framework demonstrating how CEO identity capital, platform affordances, fan labor, and product-centered imagination are assembled in short-video social commerce. Full article

In recent decades, the intensification of the urban heat island (UHI) phenomenon has emerged as a critical challenge for European cities, exacerbated by climate change, dense urban morphologies, and the aging performance of the existing building stock. In this context, the renovation of post-war residential heritage represents a strategic opportunity to simultaneously enhance buildings’ energy performance and contribute to urban-scale thermal mitigation. This study investigates sustainable and integrated retrofitting strategies applied to residential buildings constructed between 1945 and 1990 in the metropolitan area of Milan. The research aims to evaluate how targeted refurbishment interventions can improve building energy performance and potentially support UHI mitigation through improved envelope performance and material selection. The methodology combines field surveys, archival data from public housing authorities, energy simulations, and multiple-criteria decision-making (MCDM) analysis, integrating economic, environmental, and performance-based indicators. Several retrofit scenarios are assessed across different building typologies. Results highlight that low-invasive and cost-effective measures, such as advanced glazing systems, roof insulation, and efficient heating system upgrades, achieve a favorable balance between energy performance improvement, economic feasibility, and intervention-related criteria. For buildings with larger dispersing surfaces, envelope insulation solutions using sustainable materials demonstrate increased effectiveness. Beyond individual building performance, the study discusses the potential indirect contribution of large-scale retrofit strategies to UHI mitigation through reduced building energy requirements and potentially lower HVAC-related anthropogenic heat emissions. The proposed operational framework supports public stakeholders in prioritizing interventions across a large building stock, offering a replicable decision-support tool for climate-resilient urban regeneration and for supporting UHI mitigation strategies. Full article

Artificial intelligence (AI) is changing the way we study transport systems, yet its contribution to sustainable transportation planning remains uneven. While AI-based methods have shown strong performance in operational tasks such as traffic prediction and signal control, their integration into strategic planning is still fragmented. This paper provides a narrative review of AI applications in transportation planning and, more specifically, on-demand modeling, arguably the most challenging side of transport planning, and will focus on three arbitrary field macro-aggregations: machine learning (ML), artificial neural networks (ANN), and neurosymbolic AI (NeSy). The findings show that AI methods can improve predictive performance and capture complex nonlinear mobility patterns; however, predictive accuracy alone is insufficient for planning practice. Strategic planning requires models that are interpretable, transparent, and able to accommodate expert-defined constraints. The European Union AI Act further reinforces this requirement by classifying AI systems used in critical infrastructure, including road-traffic management, as high risk; this creates a regulatory need that many current AI applications do not yet satisfy. The paper argues that neurosymbolic AI architectures offer a promising research direction by combining neural learning from heterogeneous mobility data with symbolic representations of behavioral rules, network constraints, as well as accessibility, equity, and environmental objectives. Full article

Oil and gas companies operating under energy transition and wartime pressures require transparent tools for linking risk diagnosis to feasible sustainable development decisions. This study develops a residual risk-based diagnostic framework and applies it to three major Ukrainian oil and gas companies: NJSC Naftogaz of Ukraine, PJSC Ukrnafta, and JSC Ukrgasvydobuvannya. The evidence base combines a mixed-mode survey of 140 managers, engineers, and specialists conducted from February to May 2025 with public company information, financial and operational evidence, SWOT and PEST analyses, and collective consensus judgment by the seven-member research team. The survey was used to identify and contextualize sectoral barriers; it was not used to estimate the model parameters directly. For each material risk, the probability of occurrence, potential impact, and mitigation effectiveness were expressed on a [0, 1] scale and combined as residual risk contributions. The resulting company-specific index values were 0.782 for Naftogaz, 0.769 for Ukrnafta, and 0.757 for Ukrgasvydobuvannya under their respective scenario pathways. Deterministic ±10% parameter stress tests produced adverse-case values of 0.637, 0.653, and 0.607. Because the companies were assessed using different material risk sets, these values are interpreted as scenario-specific diagnostics rather than as a strict cross-company ranking or external validation of organizational resilience. The framework supports differentiated risk control and sustainable development priorities while making the assumptions, residual risk contributions, and uncertainty of the assessment explicit. Full article

Hosting capacity (HC) has become a key concept in planning and operating modern distribution networks to sustainably integrate distributed energy resources (DERs), including photovoltaic systems, wind generation, battery energy storage, and electric vehicles. However, the literature shows variation in HC definitions, assessment assumptions, limiting criteria, and reporting practices, complicating cross-study comparison and utility implementation. This paper examines HC from four interconnected perspectives: limiting factors and performance indices, assessment methods, enhancement strategies, and standardization efforts. The review examines the influence of voltage constraints, thermal loading, power quality, protection coordination, network topology, system inertia, regulatory requirements, and load diversity on HC. It compares major assessment approaches, including deterministic, stochastic, time-series, optimization-based, iterative, hybrid, data-driven, and artificial intelligence-based methods, highlighting their strengths, limitations, and suitable applications. The paper also reviews HC enhancement techniques for sustainable network capacity utilization, including network reinforcement, smart inverter control, demand-side flexibility, energy storage, and coordinated multi-layer control. Particular attention is given to emerging HC standardization and the gaps between formal standards and the research frontier, especially in probabilistic, dynamic, and real-time assessment. Overall, HC depends on binding network constraints, operating conditions, assumptions, and controls, while methodological and reporting gaps limit comparability and sustainable DER integration. Full article

Public participation plays a crucial role in modernizing urban renewal and advancing social sustainability; however, micro-renewal practices often navigate complex institutional coordination and varying levels of community engagement. To better understand these operational dynamics, this study adopts an institutional–behavioral analytical framework to examine how institutional mechanisms shape public participation, grounded in an empirical investigation of pocket parks in Shenyang, China. Integrating policy text analysis with 20 in-depth interviews framed within a citywide baseline of 3198 pocket parks, qualitative content analysis reveals that coercive, mimetic, and normative institutional pressures foster three distinct implementation pathways: Mandate-Driven, Exemplar-Driven, and Collaborative Co-governance. These pathways generate differentiated behavioral responses across four key stakeholder cohorts, while highlighting specific alignment opportunities regarding governance timing, feedback channels, and inter-departmental roles. To resolve these operational friction points and secure long-term social and institutional sustainability, we propose a full-lifecycle governance strategy offering group-tailored policy recommendations. This research bridges neoinstitutional theory with participatory spatial governance, providing actionable insights for advancing sustainable urban micro-renewal and stock space management. Full article

In recent years, the concept of “connectivity” between financial and sustainability reporting has emerged as a central construct in both regulatory frameworks and academic discourse, being recognised as a qualifying attribute of high quality corporate reporting by major standard setters, including the IIRC, the EFRAG and the IFRS/ISSB. Despite its growing normative prominence, the concept remains theoretically fragmented, empirically underexplored and methodologically contested—with interpretations varying significantly across regulatory frameworks, theoretical traditions and empirical research designs. A preliminary critical narrative review was conducted, combining structured searches of major academic databases (WOS, Scopus, Google Scholar)—which identified a total corpus of 115 publications—with a purposive examination of key regulatory documents produced by the IIRC, the EFRAG and the IFRS/ISSB. This review was structured around three research questions addressing, respectively, the conceptualisation of connectivity across theoretical and regulatory frameworks, its principal typologies and theoretical foundations, and the approaches developed for its empirical measurement. The analysis reveals that connectivity is an intrinsically multidimensional concept—aptly described as a “portemanteau” term—whose meanings, typologies and measurement approaches remain fragmented and only partially convergent. Five families of typologies are identified (direct/indirect; specific/general; technical–accounting/informational–managerial; investor-focused/stakeholder-oriented; textual/intertextual/relational), operating at different analytical levels and not mutually exclusive. Regulatory frameworks conceptualise connectivity as an attribute of holistic, coherent corporate reporting but diverge significantly in their underlying conception of materiality—single financial materiality in the IFRS/ISSB framework versus double materiality in the ESRS—with direct implications for the scope and direction of connectivity. Empirical measurement remains a genuine “work in progress”: disclosure indices, textual measures and hybrid indicators each capture different facets of the construct and do not yet converge towards a shared and widely validated framework. The available evidence—while broadly consistent in reporting low to medium-low levels of connectivity, with qualitative linkages predominating over quantitative ones—should be interpreted as associative rather than causal, given unresolved endogeneity concerns. This paper provides the first structured critical mapping of all principal dimensions of connectivity in corporate reporting, at a stage when the literature is still in formation. It identifies the distinction between formal and substantive connectivity as a central open question and outlines a specific future research agenda addressing construct validity, causal identification, longitudinal analysis and the role of assurance. Full article

This critical assessment develops a mechanistic framework for plasma-engineered oxynitride thin films in photoelectrochemical (PEC) water splitting, moving beyond description to predictive understanding. Analyzing 30 peer-reviewed studies (2010–2025) via PRISMA 2020 and a structured reliability framework, we evaluate relationships between plasma conditions, film characteristics, and solar hydrogen generation. Results reveal that plasma power, gas composition, and substrate temperature collectively control nitrogen incorporation, crystallinity, and defect formation. Optimized plasma processing conditions were generally associated with improved photocurrent generation, hydrogen evolution performance, and operational stability relative to thermal synthesis routes across most of the reviewed studies, although the 30-study evidence base is still limited and the proposed power-domain classification should be treated as a preliminary framework requiring validation against additional studies. Mechanistic analysis indicates that moderate plasma energies provide sufficient activation for nitrogen incorporation while minimizing lattice damage and excessive defect formation. A unified conceptual framework is proposed relating plasma parameters, film properties, and PEC performance, providing mechanistic guidance for photoelectrode optimization and future process development. Quality assessment identifies that only 13.3% of studies provide high-confidence evidence (46.7% moderate, 40% low), with most lacking complete plasma diagnostics or long-term stability data, highlighting critical research gaps. The framework establishes that plasma engineering’s transformative potential lies in precise control over the composition–structure–property cascade, offering a reproducible route to high-performance oxynitride photoelectrodes for sustainable hydrogen production. Full article