Search Results (291)

Non-food geographical indications (GIs) are emerging as strategic policy instruments in the European Union after Regulation (EU) 2023/2411 extended protection to craft and industrial products. While the literature on agri-food GIs is extensive, empirical and comparative evidence on non-food GIs remains scarce and fragmented. This study addresses this gap by constructing a harmonised dataset, combining 132 registered and 380 potential non-food GIs identified by EUIPO (512 in total across the EU). Using secondary institutional data, descriptive and comparative statistics, and a hierarchical clustering (Ward, squared Euclidean distance) on normalised indicators total GIs, GIs per million inhabitants (GI/POP), and GIs per € billion of GDP (GI/GDP), the analysis identifies three country typologies differing by scale and intensity. Results reveal a strong geographical concentration in Southern Europe but also unexpectedly high intensity in smaller or mid-sized economies such as Portugal, Cyprus, and Slovenia. A forward-looking scenario analysis based on Cost of Non-Europe (CoNE) estimates suggests that the full implementation of the new Regulation could generate 284,000–338,000 new jobs and € 37–50 billion in additional intra-EU trade. The study contributes to EU policy debates by introducing comparative indicators (GI/POP, GI/GDP) as monitoring tools for evidence-based policymaking and by highlighting the role of non-food GIs as hybrid institutions connecting industrial competitiveness, cultural identity, and sustainability transitions. Full article

This study presents a comprehensive assessment of lighting conditions in the Intensive Care Units (ICUs) of two major hospitals in the Democratic Republic of Congo (DRC): Hospital du Cinquantenaire in Kinshasa and Jason Sendwe Hospital in Lubumbashi. A mixed-methods approach was employed, integrating continuous illuminance monitoring with structured staff surveys to evaluate visual comfort in accordance with the EN 12464-1 standard for indoor workplaces. Objective measurements revealed that more than 52.2% of the evaluated ICU workspaces failed to meet the recommended minimum illuminance level of 300 lux. Subjective responses from healthcare professionals indicated that poor lighting significantly reduced job satisfaction by 40%, lowered self-rated task performance by 30%, decreased visual comfort scores from 4.1 to 2.6 (on a 1–5 scale), and increased the prevalence of well-being symptoms (eye fatigue, headaches) by 25–35%. Frequent complaints included eye strain, glare, and discomfort with posture, with these issues often exacerbated during the rainy season due to reduced natural daylight. The study highlights critical deficiencies in current lighting infrastructure and emphasizes the need for urgent improvements in clinical environments. Moreover, inconsistent energy supply to these healthcare settings also impacts the assurance of visual comfort. To address these shortcomings, the study recommends transitioning to energy-efficient LED lighting, enhancing access to natural light, incorporating circadian rhythm-based lighting systems, enabling individual lighting control at workstations, and ensuring a consistent power supply via the integration of solar inverters to the grid supply. These interventions are essential not only for improving healthcare staff performance and safety but also for supporting better patient outcomes. The findings offer actionable insights for hospital administrators and policymakers in the DRC and similar low-resource settings seeking to enhance environmental quality in critical care facilities. Full article

Background: The transition from student to professional nurse is often overwhelming for newly qualified registered nurses, especially in rural and resource-limited settings. Systemic barriers such as staff shortages, limited resources, and lack of mentorship hinder their ability to gain effective clinical experiences. This gap threatens both the professional development of newly qualified registered nurses and the quality of patient care, justifying the need for this study. Aim: This study aimed to explore how the shortage of resources and functional infrastructure affects the clinical experiences of newly qualified registered nurses. Methods: A descriptive qualitative design was employed, grounded in an interpretivist paradigm. Data were collected through three semi-structured focus group interviews with a purposive sample of 25 NQRNs. A rigorous thematic analysis, following the Braun and Clarke framework, was used to identify, analyze, and report patterns within the data. Results: The analysis revealed a complex interplay of six interconnected themes that define the NQRNs’ experiences: (1) an institutional void of clinical support and mentorship; (2) systemic failures in management and leadership; (3) crippling resource constraints and infrastructure decay; (4) pervasive emotional and psychological distress; (5) a trajectory towards professional burnout; and (6) profound job dissatisfaction and disillusionment. These barriers were found to collectively undermine clinical confidence, compromise patient safety, and threaten nurse retention. Conclusions: NQRNs in the Chris Hani District are navigating a “perfect storm” of systemic failures that hinder their professional development and personal well-being. The findings highlight an urgent need for multi-level interventions, including the implementation of standardized mentorship programs, leadership development for nurse managers, strategic investment in rural health infrastructure, and the establishment of formal mental health support systems. Addressing these foundational issues is paramount to building a resilient nursing workforce and ensuring equitable healthcare delivery. Full article

Purpose: This study investigates the relationship between flexible working arrangements (FWAs), employee experiences (EEs), and perceived productivity (PP) in the context of New Zealand employees. The study aims to understand how opportunities and challenges within FWAs impact employee productivity, utilising the Job Demands–Resources (JD-R) model as a theoretical framework. Design/methodology/approach: A survey was conducted with 176 employees who transitioned from traditional office settings to FWAs. Data were collected using a structured questionnaire measuring work demand, autonomy, employee experiences, and perceived productivity. The analysis involved correlational and moderated regression techniques to assess the relationships between the variables. Findings: The study found that positive employee experiences (expressed as opportunities) are significantly associated with higher perceived productivity (r = 0.610, p < 0.001), while negative experiences (expressed as challenges) are associated with lower perceived productivity (r = 0.515, p < 0.001). Moreover, management strategies were found to moderate these relationships, further influencing perceived productivity. Originality: This research contributes to the understanding of how FWAs, when effectively managed, can enhance employee productivity by fostering positive experiences. It also highlights the importance of addressing challenges to mitigate negative impacts on productivity. The use of the JD-R model offers a novel approach to exploring these dynamics in the context of FWAs. Practical and social implications: Organisations can enhance productivity by focusing on management strategies that amplify positive employee experiences and reduce challenges within FWAs. Effective FWAs can improve work–life balance, employee wellbeing, and organisational commitment, contributing to a more satisfied and productive workforce. Full article

This study investigates how environmentally specific ethical leadership (ESEL) enhances employee job performance in public healthcare organizations by examining the sequential mediating roles of communication competence and work engagement. Grounded in Social Learning Theory and the Job Demands–Resources (JD–R) model, this study further explores the moderating effect of emotional regulation in this green leadership–performance linkage. Data were collected from 384 healthcare professionals, including physicians, nurses, and administrative staff, in public hospitals across Jordan using a cross-sectional survey design. Structural equation modeling (SEM) via SmartPLS was employed to test the hypothesized relationships. The results reveal that ESEL significantly improves job performance by fostering environmentally responsible communication and enhancing employee engagement. Specifically, the findings support a sequential mediation process: ESEL cultivates communication competence, which promotes work engagement, ultimately leading to higher performance. Furthermore, emotional regulation strengthens these relationships, suggesting that employees with greater self-regulatory capacity respond more positively to green ethical leadership. This study extends the literature on sustainable human resource management by uncovering how ESEL fosters pro-environmental behavior and high performance in ethically sensitive contexts such as healthcare. In practical terms, the findings emphasize the need for healthcare organizations to embed sustainability-focused communication and emotional regulation skills into leadership training to support green transition goals. Full article

This paper examines the evolving role of social economy organisations (SEOs) in advancing sustainability and contributing to the green transition. While traditionally focused on social inclusion and local development, SEOs are increasingly integrating environmental objectives into their operations, particularly through circular economy (CE) practices, decarbonisation strategies, and short food supply chains (SFSCs). Based on qualitative research and the analysis of 16 good practices from five European countries, the study demonstrates how SEOs create blended social and environmental value by combining economic, social, and ecological goals. The findings show that SEOs foster environmental sustainability by reducing resource consumption and carbon emissions, creating green jobs, strengthening local cooperation, and raising environmental awareness within communities. Importantly, SEOs emerge not only as service providers but also as innovators and agents of change in local ecosystems. The paper concludes with policy recommendations to enhance the role of SEOs in the green transition and identifies directions for future research, particularly regarding the measurement of their long-term environmental impact and the conditions enabling effective collaboration with public and private sector actors. Full article

Media coverage plays a pivotal role in shaping public perception of the energy transition. This study provides a comprehensive analysis of how the lignite phase-out is represented in Greece, both by national and regional media, with a specific focus on the impacted region of Western Macedonia. Using data from the Leipzig Corpora Collection and regional news portals from 2013 to 2022, the analysis reveals significant divergences between media levels. While both show synchronized peaks for key terms like “Climate change” (2019) and “Western Macedonia” (2021), regional media addressed the direct impacts of the transition earlier and more intensely, with terms like “post-lignite” and “de-lignification” peaking in 2020 following the announcement of the Master Plan. National media framed the transition within a broader, top-down policy context, often with an optimistic tone, reflecting EU directives. In contrast, regional media provided a community-centric perspective, highlighting concerns over job losses and the preservation of local identity. The findings underscore a clear tension between official narratives of progress and local-level concerns, demonstrating that media discourse is a critical, multi-faceted component of just transition processes that policymakers must consider. Full article

Heat treatment is a critical intermediate process in copper strip manufacturing, where strips go through an air-cushion annealing furnace. The production scheduling for the air-cushion annealing furnace can contribute to cost reduction and efficiency enhancement throughout the overall copper strip production process. The production scheduling problem must account for time window constraints and gas atmosphere transition requirements among jobs, resulting in a complex combinatorial optimization problem that necessitates dual-objective optimization of the total atmosphere transition cost of annealing and the total penalties for time window violations. Most multi-objective optimization algorithms rely on the evolution of a single population, which makes them prone to premature convergence, leading to local optimal solutions and insufficient exploration of the solution space. To address the challenges above effectively, we propose a Bi-population Co-evolutionary Multi-objective Optimization Algorithm (BCMOA). Specifically, the BCMOA initially constructs two independent populations that evolve separately. When the iterative process meets predefined conditions, elite solution sets are extracted from each population for interaction, thereby generating new offspring individuals. Subsequently, these new offspring participate in elite solution selection alongside the parent populations via a non-dominated selection mechanism. The performance of the BCMOA has undergone extensive validation on benchmark datasets. The results show that the BCMOA outperforms its competitive peers in solving the relevant problem, thereby demonstrating significant application potential in industrial scenarios. Full article

Manufacturing industries are undergoing a significant transformation toward Smart Manufacturing (SM) to meet the ever-evolving demands for customized products. A major obstacle in this transition is the integration of Computer-Aided Process Planning (CAPP) with Scheduling. This integration poses challenges because of conflicting objectives that must be balanced, resulting in the Integrated Process Planning and Scheduling problem. In response to these challenges, this research introduces a novel hybridized machine learning optimization approach designed to assign and sequence setups in Dynamic Flexible Job Shop environments via dispatching rule mining, accounting for real-time disruptions such as machine breakdowns. This approach connects CAPP and scheduling by considering setups as dispatching units, ultimately reducing makespan and improving manufacturing flexibility. The problem is modeled as a Dynamic Flexible Job Shop problem. It is tackled through a comprehensive methodology that combines mathematical programming, heuristic techniques, and the creation of a robust dataset capturing priority relationships among setups. Empirical results demonstrate that the proposed model achieves a 42.6% reduction in makespan, improves schedule robustness by 35%, and reduces schedule variability by 27% compared to classical dispatching rules. Additionally, the model achieves an average prediction accuracy of 92% on unseen instances, generating rescheduling decisions within seconds, which confirms its suitability for real-time Smart Manufacturing applications. Full article

A just and sustainable energy transition in historically coal-dependent regions like Kentucky requires more than the adoption of new technologies and market-based solutions. This study uses a stated preferences approach to evaluate public support for various attributes of energy transition programs, revealing broad backing for moving away from coal, as indicated by a negative willingness to pay (WTP) for the status quo (–USD 4.63). Key findings show strong bipartisan support for solar energy, with Democrats showing the highest WTP at USD 8.29, followed closely by Independents/Others at USD 8.22, and Republicans at USD 8.08. Wind energy also garnered support, particularly among Republicans (USD 4.04), who may view it as more industry-compatible and less ideologically polarizing. Job creation was a dominant priority across political affiliations, especially for Independents (USD 9.07), indicating a preference for tangible, near-term economic benefits. Similarly, preserving cultural values tied to coal received support among Independents/Others (USD 4.98), emphasizing the importance of place-based identity in shaping preferences. In contrast, social support programs (e.g., job retraining) and certain post-mining land uses (e.g., recreation and conservation) were less favored, possibly due to their abstract nature, delayed benefits, and political framing. Findings from Kentucky offer insights for other coal-reliant states like Wyoming, West Virginia, Pennsylvania, Indiana, and Illinois. Ultimately, equitable transitions must integrate local voices, address cultural and economic realities, and ensure community-driven planning and investment. Full article

Research on commuting patterns has mainly focused on urban and metropolitan areas, and such studies are not typically applied to rural and small-town regions, where workers often face longer commutes due to limited job opportunities and inadequate public transportation. By using the Census Transportation Planning Package (CTPP) data, this research fills that gap by analyzing commuting behavior by ethnic group and industry in south-central Minnesota, which is a predominantly rural area of 13 counties in the United States. The results show that both white and minority groups in District 7 experienced an increase in excess commuting from 2006 to 2016, with the minority group in Nobles County showing a significantly higher rise. Analysis by industry reveals that excess commuting in the leisure and hospitality sector (including arts, entertainment, and food services) in Nobles County increased five-fold during this time, indicating a severe spatial mismatch between jobs and affordable housing. In contrast, manufacturing experienced a decline of 50%, possibly indicating better commuting efficiency or a loss of manufacturing jobs. These findings can help city and transportation planners conduct an in-depth analysis of rural-to-urban commuting patterns and develop potential solutions to improve rural transportation infrastructure and accessibility, such as promoting telecommuting and hybrid work options, expanding shuttle routes, and adding more on-demand transit services in rural areas. Full article

As the global energy transition accelerates, the integration of solar power and artificial intelligence (AI) technologies offers new pathways for sustainable local development. This study examines four Serbian municipalities—Šabac, Sombor, Pirot, and Čačak—to assess how AI-enabled solar power systems can enhance energy resilience, reduce emissions, and support community-level sustainability goals. Using a mixed-method approach combining spatial analysis, predictive modeling, and stakeholder interviews, this research study evaluates the performance and institutional readiness of local governments in terms of implementing intelligent solar infrastructure. Key AI applications included solar potential mapping, demand-side management, and predictive maintenance of photovoltaic (PV) systems. Quantitative results show an improvement >60% in forecasting accuracy, a 64% reduction in system downtime, and a 9.7% increase in energy cost savings. These technical gains were accompanied by positive trends in SDG-aligned indicators, such as improved electricity access and local job creation in the green economy. Despite challenges related to data infrastructure, regulatory gaps, and limited AI literacy, this study finds that institutional coordination and leadership commitment are decisive for successful implementation. The proposed AI–Solar Integration for Local Sustainability (AISILS) framework offers a replicable model for emerging economies. Policy recommendations include investing in foundational digital infrastructure, promoting low-code AI platforms, and aligning AI–solar projects with SDG targets to attract EU and national funding. This study contributes new empirical evidence on the digital–renewable energy nexus in Southeast Europe and underscores the strategic role of AI in accelerating inclusive, data-driven energy transitions at the municipal level. Full article

Workforce transformation is one of the most pressing challenges in the AI-driven construction industry, as traditional skilled labour roles are rapidly evolving into more interdisciplinary, digitally enabled positions. This study aims to investigate how AI is fundamentally reshaping skill requirements within the construction sector, to analyse stakeholder perceptions and adaptive responses to workforce transformation, and to explore strategies for optimizing construction workforce development to facilitate the critical transition from traditional “skilled workers” to contemporary “smart talent.” It employs phenomenological qualitative research methodology to conduct in-depth interviews with 20 stakeholders in Chongqing, and uses NVivo 14 to conduct thematic analysis of the data. The findings indicate that AI has penetrated all areas of the construction process and is transforming jobs to more likely be digitalized, collaborative, and multi-faceted. However, significant cognitive disparities and varying adaptive capacities among different stakeholder groups have created structural imbalances within the workforce development ecosystem. Based on these key findings, a four-pillar talent development strategy is proposed, encompassing institutional support, educational reform, enterprise engagement, and group development, while stressing the necessity for systemic-orchestrated coordination to reimagine a smart talent ecosystem. This study advances theoretical understanding of digital transformation within construction labour markets, while offering real pathways and institutional contexts for developing regions that desire to pursue workforce transformation and sustainable industrial development in the AI era. Full article

The transition to hybrid work has become a defining feature of the post-pandemic IT sector, yet organizations lack empirical benchmarks for balancing flexibility with performance and well-being. This study addresses this gap by identifying an optimal hybrid work structure and exposing systematic perception gaps between employees and managers. Grounded in Self-Determination Theory and the Job Demands–Resources model, our research analyses survey data from 1003 employees and 252 managers across 46 countries. The findings identify a hybrid “sweet spot” of 6–10 office days per month. Employees in this window report significantly higher perceived efficiency (Odds Ratio (OR) ≈ 2.12) and marginally lower office-related stress. Critically, the study uncovers a significant perception gap: contrary to the initial hypothesis, managers are nearly twice as likely as employees to rate hybrid work as most efficient (OR ≈ 1.95) and consistently evaluate remote-work resources more favourably (OR ≈ 2.64). This “supervisor-optimism bias” suggests a disconnect between policy design and frontline experience. The study concludes that while a light-to-moderate hybrid model offers clear benefits, organizations must actively address this perceptual divide and remedy resource shortages to realize the potential of hybrid work fully. This research provides data-driven guidelines for creating sustainable, high-performance work environments in the IT sector. Full article

The generation of fine coal particles during mining and processing presents significant environmental and logistical challenges, particularly in coal-dependent, developing countries like South Africa (SA). This review critically evaluates the technical viability of fine coal briquetting as a sustainable waste-to-energy solution within a SA context, while drawing from global best practices and comparative benchmarks. It examines abundant feedstocks that can be used for valorization strategies, including fine coal and agricultural biomass residues. Furthermore, binder types, manufacturing parameters, and quality optimization strategies that influence briquette performance are assessed. The co-densification of fine coal with biomass offers a means to enhance combustion efficiency, reduce dust emissions, and convert low-value waste into a high-calorific, manageable fuel. Attention is also given to briquette testing standards (i.e., South African Bureau of Standards, ASTM International, and International Organization of Standardization) and end-use applications across domestic, industrial, and off-grid settings. Moreover, the review explores socio-economic implications, including rural job creation, energy poverty alleviation, and the potential role of briquetting in SA’s ‘Just Energy Transition’ (JET). This paper uniquely integrates technical analysis with policy relevance, rural energy needs, and practical challenges specific to South Africa, while offering a structured framework for bio-coal briquetting adoption in developing countries. While technical and economic barriers remain, such as binder costs and feedstock variability, the integration of briquetting into circular economy frameworks represents a promising path toward cleaner, decentralized energy and coal waste valorization. Full article