Search Results (745)

The transition towards sustainable aluminum manufacturing is commonly assessed through recycling rates, energy savings, and resource efficiency, but its distributive effects across global value chains remain insufficiently examined. This study evaluates whether recycled aluminum value chains contribute to both circularity and north–south redistribution, or whether they reproduce unequal patterns of value capture, industrial upgrading, employment quality, and trade dependency. The analysis combines UN Comtrade trade data for HS 7601–7616, OECD ICIO 2025 value added indicators, ILOSTAT labor statistics, and UN SDG data for the 2018–2020 three-year average. Eighty economies are classified into four groups: advanced industrial economies, emerging industrial economies, lower-middle-income economies, and low-income economies. A composite indicator linked to SDGs 8, 9, 10, and 12, with SDG 17 incorporated only as a trade dependency context, is constructed from normalized industrial, circular material flow, distributive, and job-quality variables. The results show a clear north–south hierarchy: advanced economies concentrate a larger share of exports in aluminum manufactures, while low-income economies remain more dependent on scrap flows. Group A captures most chain value added, whereas Groups C and D retain only marginal shares. Labor productivity falls sharply from advanced to low-income economies, while working poverty increases substantially. By contrast, circularity scores vary less strongly across groups, suggesting that participation in circular material flows does not necessarily imply equitable industrial upgrading. This study shows that circularity in recycled aluminum value chains does not automatically generate redistribution and provides a replicable framework for distinguishing material circularity from distributive justice. Full article

As a crucial indicator for measuring regional social equity and equality of opportunity, intergenerational mobility exerts an important impact on the employment quality of the agricultural migrant population. However, despite extensive research on migrant employment, limited attention has been paid to how intergenerational mobility interacts with localized technological environments and fiscal resource constraints to shape the labor assimilation of rural-to-urban migrants. This study assesses this relationship by constructing an urban intergenerational educational mobility index and analyzing the China Migrants Dynamic Survey (CMDS) data. The results indicate that intergenerational mobility significantly improves the employment quality of the migrant population. Mechanism analysis was used to reveal that the digital economy exerts a positive regulatory effect, acting as a form of technological empowerment that enhances the transition of structural opportunities into tangible employment prospects. Conversely, local fiscal pressure exerts a negative regulatory effect, imposing contractive resource constraints that attenuate the promotional dividends of social mobility. Heterogeneity analysis results further demonstrate that the positive impact of intergenerational mobility is more prominent in cities with higher public education expenditure, higher levels of marketization, and fewer traditional cultural constraints. These findings suggest that geographical mobility alone does not automatically guarantee high-quality employment; rather, enhancing institutional openness, expanding digital infrastructure, and optimizing the allocation of public resources are essential to translating equity of structural opportunity into decent work. Full article

In the context of China’s Carbon Peaking and Carbon Neutrality Goals, understanding how non-agricultural employment affects agricultural carbon emission intensity is critical for achieving green and sustainable agricultural development. This study asks whether the reallocation of labor away from agriculture increases or reduces agricultural carbon emission intensity, through which transformation-related pathways this relationship may operate, and whether the relationship changes across development stages and spatially connected regions. Using panel data from 295 prefecture-level cities in China from 2011 to 2023, this study constructs a factor-substitution framework and applies fixed-effects models, potential pathway analysis, threshold models, and Spatial Durbin Models. The results show that non-agricultural employment has a significant inverted U-shaped association with agricultural carbon emission intensity: at relatively low levels it is associated with higher emission intensity, whereas beyond the estimated turning point it is associated with lower emission intensity. Non-agricultural employment is also systematically associated with agricultural structural adjustment, mechanization transformation, and AI-related patenting activity, which are interpreted as potential pathways rather than definitive causal mediation channels. Threshold results indicate that economic development and urbanization condition the marginal effect of non-agricultural employment, while spatial estimates show that the nonlinear relationship extends to neighboring regions through significant spillover effects. These findings suggest that agricultural carbon-reduction policies should distinguish between cities at different stages of labor reallocation, promote low-carbon forms of capital and technology substitution, and strengthen cross-regional coordination in agricultural producer services and green technology diffusion. Full article

After EU accession, Croatia has leveraged the advantages of EU membership, such as access to a large market and EU funds, to accelerate economic growth and reduce the development gap in comparison to advanced EU economies. Although EU membership has stimulated economic growth, it has also brought negative effects, such as labor emigration to more developed EU economies with higher wages and increased inflation due to price convergence and the adoption of the Euro. The weak growth of labor productivity in Croatia is a consequence of the slow transformation towards technology-intensive industries, the dominance of traditional labor-intensive sectors such as construction and hospitality, and the rapid growth of employment in the public sector. The novelty of the research lies in applying an input–output model to estimate direct and indirect labor requirements in Croatia, an example of a small, service-oriented economy that, after joining the EU, witnessed a significant increase in final demand. Research is based on the Eurostat FIGARO database. The increase in gross value added across industries during 2015–2024 is separated into price and real growth effects. Analysis indicates that the current Croatian growth model is unsustainable because of high labor requirements and slow productivity growth. Results imply that European Union membership brings many advantages, but if not coupled with an adequate industrial development strategy, economic growth based exclusively on increasing final demand could reach its limits. Labor constraints and continued demand growth without substantial structural changes could result in rising wages and prices rather than real GDP growth. Full article

Purpose: The purpose of this paper is to provide an integrative review of Positive Psychology in contemporary organizational contexts, examining how psychological resources such as Psychological Capital, Emotional Intelligence, Mindfulness, Psychological Safety, Self-Determination Theory, and Positive Leadership contribute to employee well-being, flourishing, and organizational effectiveness. Design/Methodology/Approach: This study adopts a narrative integrative literature review approach, synthesizing recent theoretical and empirical research in Positive Organizational Psychology, Organizational Behavior, and Human Resource Management. The review integrates foundational theories with contemporary empirical findings published in high-impact academic journals to develop a comprehensive conceptual framework. Findings: The findings indicate that Positive Psychological constructs are consistently associated with higher levels of employee engagement, job satisfaction, performance, resilience, and flourishing, while reducing burnout, stress, and turnover intentions. Psychological Capital emerges as a key malleable resource, while Mindfulness and Emotional Intelligence enhance self-regulation and interpersonal effectiveness. Originality: The paper integrates multiple streams of Positive Psychology into a unified conceptual model, combining individual-level psychological resources with motivational and organizational-contextual factors. Research limitations/implications: As a narrative review, the study does not include primary empirical data or statistical testing. Future research should empirically validate the proposed integrative framework using longitudinal and cross-cultural designs. Practical implications: Organizations can enhance employee well-being and performance by implementing Psychological Capital Interventions, mindfulness-based programs, strengths-based development, and psychologically safe leadership practices. Social implications: The findings highlight the broader societal value of fostering psychologically healthy workplaces that promote sustainable employment, mental health, and human flourishing. Full article

Gibberellic acids (GAs) are a class of tetracyclic diterpene carboxylic acid compounds produced by green plants, fungi, and bacteria, which have a wide range of applications in agricultural production and food ingredients processing. Owing to the continuously growing market demand, enhancing GA yield has become imperative. The biosynthesis of GAs is a multi-enzymatic synergistic process that can be enhanced through genetic and metabolic engineering strategies. In this review, we first summarize recent advances in GA production by Fusarium fujikuroi. We then highlight key metabolic engineering strategies, including biosynthetic pathway engineering, cluster-specific channeling of geranylgeranyl diphosphate biosynthesis, cofactor engineering, as well as regulatory mechanisms involving nitrogen modulation and histone modification. Finally, we discuss promising approaches for constructing high-efficiency microbial cell factories, such as implementation of the CRISPR/Cas9 system, the application of strong promoters, the development of target-specific technologies for small molecules, and the employment of genome-scale metabolic models. Recent metabolic engineering efforts have achieved GA3 titers of up to 3.16 g/L through multi-target nitrogen regulation strategies, highlighting the potential for further yield improvement. Full article

Persistent urban–rural inequality remains a major challenge for sustainable regional development, especially in countries where rural communities still face limited access to markets, employment, and public services. This study examines whether rural road network density promotes inclusive regional growth in China. Using county-level panel data from 2013 to 2024, we construct an inclusive regional growth index that combines economic output, nighttime-light-measured economic activity, rural income, and the urban–rural income gap. rural road network density is measured by the length of county, township, and village roads per 100 square kilometers. Two-way fixed-effects models, mechanism tests, robustness checks, instrumental-variable estimation, and heterogeneity analysis are employed. The results show that rural road network density significantly improves inclusive regional growth. Dimensional analysis indicates that higher rural road network density increases real GDP per capita, strengthens nighttime-light-measured economic activity, raises rural income, and reduces the urban–rural income gap. Mechanism analysis shows that these effects operate through labor mobility, market access, and non-agricultural industrial development. The results remain robust to alternative road measures, lagged specifications, outlier treatment, sample restrictions, and instrumental-variable estimation. Heterogeneity analysis further shows that the effects are larger in central-western counties, low-accessibility counties, and less-developed counties. These findings suggest that rural road network density is not only a transport infrastructure indicator but also a key spatial condition for promoting sustainable and inclusive regional development. Full article

Technological and social development is desirable and even indispensable, which necessarily involves the restriction of new life situations within legal frameworks. European legislation has been visibly struggling with this problem in recent years, but the established/ongoing regulation may be an obstacle to development. Among other things, this includes the issue of regulating platform work. The emergence and spread of platform work has numerous advantages from an economic point of view, but from a legal point of view, the cautious regulation of this relatively new employment construction is not acceptable to the majority dealing with labour law. In our opinion, the relevant EU legislation is fundamentally flawed, as it basically seeks to answer the question of whether a given legal relationship is an employment relationship or not. The current binary classification might not be sufficient. Thus, the present study examines why platform work can be considered special and what are the labour law guarantees that are justified to be extended—at least as a rule—in this regard. To further investigate the practical risks of the current rules, a recent and relevant judgement of the Hungarian Supreme Court is also analysed in order to illustrate the uncertainties in litigation. The ruling demonstrates that traditional employment tests fail to recognise algorithmic control—including GPS surveillance, scheduling penalties, and unilateral remuneration determination—as indicators of subordination, while placing an insurmountable burden of proof on workers. This case empirically confirms the practical difficulties of the current binary classification. Our aim is to examine whether it is necessary to develop a minimum guarantee system that allows for easier transparency, greater legal certainty and a more uniform application of the law, unlike the current regulation. Full article

China’s transition from strict fertility control toward a pronatalist regime raises important questions regarding how institutional regime changes are associated with wage outcomes across different policy stages. While previous studies primarily examine contemporaneous labor-market outcomes, this study evaluates wage associations across fertility-policy regime stages using a dynamic panel specification. Using five waves of the China Family Panel Studies (CFPS) from 2014 to 2022, the analysis constructs a short, unbalanced panel and estimates a wage equation using two-step System Generalized Method of Moments (System GMM) with collapsed instruments and restricted lag depth to address dynamic endogeneity and unobserved heterogeneity. To improve representativeness and mitigate observed wage-observability differences, survey weights are combined with inverse-probability weighting. The preferred baseline estimates indicate a positive but modest lagged-wage coefficient. Monte Carlo and sensitivity analyses further suggest that the persistence estimate is fragile and may overstate the degree of true persistence in this short-panel setting. Accordingly, the findings do not support strong intertemporal wage persistence and instead indicate only limited dependence of current wages on past wage realizations. The dynamic specification is therefore informative primarily as a diagnostic framework for assessing whether regime-stage wage associations exhibit meaningful persistence. Additional exposure-based heterogeneity analyses show negative interaction coefficients for Female and childbearing women (CBW). Married women aged 20–39 experience additional negative wage associations during fertility-policy regime stages, with similar results obtained under a narrower CBW20–35 robustness definition. These findings suggest that positive aggregate regime-stage associations may conceal relative wage disadvantages among women in demographic groups more plausibly exposed to fertility-policy-related labor-market conditions. The CBW indicator is interpreted as a demographic-exposure proxy rather than as a direct measure of employer expectations, fertility intentions, or discrimination. Overall, the results highlight exposure-based heterogeneity in regime-stage wage associations while emphasizing that the estimates should be interpreted as conditional associations embedded within broader institutional transitions rather than as causal fertility-policy effects. Full article

The COVID-19 pandemic generated unprecedented disruptions to the global tourism industry, severely affecting tourism-dependent economies and related employment. India, as one of the world’s major tourist destinations, experienced substantial declines in tourist arrivals during the pandemic period. This study investigates the effects of COVID-19-induced fear on tourism demand and economic performance in India using the COVID-19 Fear Index, which captures behavioural responses to pandemic-related uncertainty beyond conventional indicators such as infection rates, mortality, and lockdown restrictions. The COVID-19 Fear Index is constructed using reported COVID-19 cases and mortality data sourced from the European Centre for Disease Prevention and Control and the Johns Hopkins Coronavirus Resource Centre. Monthly data from January 2020 to October 2023 are analysed using autoregressive distributed lag (ARDL) and nonlinear autoregressive distributed lag (NARDL) models to examine both tourism demand dynamics and the asymmetric tourism–growth relationship. The results confirm a stable long-run cointegration relationship among tourism demand, the COVID-19 Fear Index, exchange rate, and ICT development. Pandemic-induced fear significantly reduces tourism demand in the long run ($-0.152$, $p=0.021$) and short run ($-0.084$, $p=0.000$), indicating that heightened uncertainty suppresses tourist arrivals. Exchange rate depreciation also negatively affects tourism demand ($-0.267$, $p=0.000$), whereas ICT development positively enhances tourism resilience ($0.463$, $p=0.000$). The error correction term ($-0.436$, $p=0.000$) confirms rapid adjustment toward long-run equilibrium. Furthermore, the nonlinear analysis reveals asymmetric effects, where positive tourism shocks increase economic growth by $0.088\%$ ($p=0.003$), while negative shocks exert a stronger contractionary effect ($0.409$, $p=0.000$). These findings highlight the vulnerability of tourism-dependent economies to uncertainty shocks and emphasise the importance of ICT-driven resilience strategies, adaptive tourism policies, and crisis-responsive economic planning. Full article

Collective operating construction land marketization (COCLM) is a major institutional innovation in China’s land reform process. However, the impact of this reform on farmers’ livelihood resilience (FLR) remains underexplored. This study uses data from the 2020–2022 China Land Economic Survey (CLES) conducted in Jiangsu Province to construct an FLR index from three dimensions—buffer capacity, self-organization capacity, and learning capacity. It also incorporates the actual status of COCLM at the village level to examine the impact of COCLM on FLR and its underlying mechanisms. The results show the following: (1) COCLM significantly improves FLR, and this conclusion remains consistent after a series of robustness checks. (2) In terms of FLR dimensions, COCLM has significant positive effects on all three dimensions, but its effects on buffer capacity and learning capacity are more pronounced than those on self-organization capacity. (3) Mechanism analysis reveals that COCLM improves FLR mainly by increasing farmers’ property income and promoting household non-agricultural employment. (4) Heterogeneity analysis shows that the positive effect of COCLM is more pronounced in southern and central Jiangsu, among high-income households, and in villages with higher governance levels. This study suggests that COCLM reform should be further deepened to steadily promote the sustained improvement of FLR, enable land value-added returns and non-agricultural employment opportunities to reach farmers more effectively, and pay greater attention to regional differences, income-group disparities, and differences in grassroots governance capacity, while promoting inclusive growth through COCLM. The above conclusions have some reference value for regions similar to Jiangsu, while their applicability in other regions with substantially different development conditions still requires further examination. Full article

This study examines how the concept of academic success is constructed and represented both in international scientific literature and in the perceptions of higher education students, using the OPSA 2.0 project at the Polytechnic University of Leiria as a case study. Adopting an exploratory multimethod approach, the research combines bibliometric analysis of publications indexed in Scopus (2020–2025) with qualitative content analysis of students’ responses collected through participatory workshops. The bibliometric results reveal that academic success is increasingly conceptualised as a multidimensional construct, structured around institutional, pedagogical, psychological, and identity-related dimensions. However, the analysis of students’ perceptions shows a predominance of instrumental and performance-oriented representations, particularly associated with grades, course completion, and employability. At the same time, emerging references to well-being, resilience, and personal fulfilment suggest a gradual shift towards more holistic understandings of success. By articulating global research trends with local student narratives, the study highlights the coexistence of traditional and emergent conceptualisations of academic success in higher education. The findings underline the relevance of institutional strategies, such as OPSA 2.0 Project, that promote a comprehensive and preventive approach to student success. Methodologically, the study demonstrates the potential of combining bibliometric mapping with qualitative analysis to bridge macro-level scientific developments and micro-level lived experiences. Full article

This article develops and empirically supports a multi-level model for integrating sustainable practices in the hospitality industry, using the Zhetysu region of Kazakhstan as a regional case. The theoretical basis of the study is formed by the concepts of sustainable development, ESG principles and the Triple Bottom Line framework, which are integrated into a macro-, meso- and micro-level structure of sustainability management. The empirical analysis uses regional statistical data on the hotel sector for 2022–2025, including service volume, employment, wages, accommodation capacity, bed-days, investments and environmental protection expenditures. On this basis, a system of sustainability indices was constructed to assess economic, social and environmental dynamics. The results show that the Composite Sustainability Index increased from 0.00 in 2022 to 0.66 in 2025, indicating positive but uneven progress. Social indicators demonstrated the most stable improvement, while economic sustainability remained constrained by low capacity utilisation and unstable labour productivity. Environmental indicators were the weakest component, reflecting fragmented and inconsistent green practices. The novelty of the study lies in linking ESG and Triple Bottom Line principles with measurable regional indicators and a multi-level governance model. The proposed framework and roadmap can support regional authorities, tourism organisations and hospitality enterprises in coordinating sustainability initiatives and monitoring their implementation. Full article

In the context of urban regeneration, identifying the nonlinear and interactive effects of the built environment on commercial vitality is essential for targeted spatial improvement. Using Xi’an’s central urban area as a case study, this study integrated multi-source data, including POI, AOI, street-view imagery, and mobile phone signaling data, to delineate commercial spaces via kernel density analysis. With actual service population density as the vitality indicator, a built-environment framework was constructed using 14 indicators across four dimensions: transport accessibility, functional diversity, street quality, and environmental capacity. Random forest regression and SHAP-based interpretable machine learning were employed to examine factor importance, nonlinear thresholds, and interactions. Results show that environmental capacity and transport accessibility are the dominant dimensions, with building density, road network density, and employment density contributing most. Built-environment variables generally exhibit nonlinear threshold effects; key thresholds include road network density > 8 km/km², building density > 40%, functional mix > 4.5, and sky view factor around 40%. Interactions involving building density are most pronounced, and its positive effect is significantly amplified under higher accessibility or employment density. These findings suggest prioritizing road network optimization and building coverage, while balancing functional mix and spatial scale in commercial space regeneration. Full article

Under the concurrent advancement of ecological civilization and resource-dependent region transformation, key state-owned forest areas in northeast China have shifted from timber supply to ecosystem protection. However, while the Natural Forest Protection Program has restored forest resources and increased coverage, it has also led to the contraction of traditional industries, reduced employment, population outflow, and a structural tension between weak economic growth and enhanced ecological functions. This study aims to investigate how labor mobility affects the coordinated development of economic and ecological welfare in these regions. To achieve this, we construct economic and ecological welfare indices using entropy weighting and calculate their coupling coordination degree based on panel data from the China Forestry Statistical Yearbook (2000–2017) and the China Forestry and Grassland Statistical Yearbook (2018–2025). Our key scientific contributions are as follows: (1) we reveal a nonlinear and significantly negative impact of labor mobility on coupling coordination; (2) we identify industrial structure as a partial mediating channel; and (3) we uncover significant regional and developmental stage heterogeneity. Methodologically, we employ fixed-effects, mediation, threshold, and spatial panel models to ensure robustness. The findings provide novel insights into labor–environment trade-offs in forest-dependent regions and offer policy implications for optimizing labor allocation, strengthening ecological compensation and industrial synergy, and improving regional governance to achieve coordinated economic–ecological development. Full article