Search Results (3,179)

This study examines whether and under what conditions the digital economy (DGE) improves the green development efficiency of China’s tourism industry. Drawing on panel data for 30 Chinese provinces from 2012 to 2023, we develop a multidimensional index of the DGE that captures digital infrastructure, digital industrialization, and industrial digitalization. To evaluate tourism green development efficiency, we employ a non-radial, non-angular super-efficiency slacks-based measure (SBM) model that incorporates both desirable outputs and undesirable environmental externalities. From a theoretical perspective, we extend the Cobb–Douglas production framework by embedding DGE-induced technological progress, showing that digitalization can improve green efficiency through two complementary pathways: it expands expected output while reducing carbon intensity. Empirically, the baseline two-way fixed-effects results show that DGE significantly promotes tourism green development efficiency (β = 0.0153, p < 0.05), and this result remains robust in instrumental-variable (IV) estimation (β = 0.0383, p < 0.05). We further show that this relationship is conditioned by three important external conditions. First, environmental regulation strengthens the enabling effect of digitalization, consistent with a compliance-induced Porter effect. Second, tourism industry agglomeration enhances the benefits of digital transformation by deepening knowledge spillovers and network complementarities. Third, green finance relaxes financing constraints and creates more favorable conditions for digital investment. By integrating a formal theoretical model with panel-data evidence, this study provides a unified explanation of both the mechanism and the boundary conditions through which the DGE promotes tourism green development efficiency. Overall, the findings suggest that the DGE is an important driver of sustainable tourism development and offer useful policy implications for coordinated digital and green transformation. Full article

This paper examines the effects of public infrastructure spending across Ecuadorian cantons on adequate employment and the multidimensional poverty rate over the period 2008–2022, assessing whether such spending operated as a mechanism of convergence. The analysis is grounded in the hypothesis that infrastructure investment yields stronger effects in cantons characterized by lower initial levels of development. The coefficient of primary interest, associated with the interaction between low initial development and infrastructure expenditure, takes a value of −0.9542, which theoretically indicates a substantially larger impact on outcome variables in lagging cantons. This pattern is consistent with convergence theory and with the notion of investment spillovers, often described as a trickle-down process of development. Nevertheless, the estimated effect is marginally significant at the 10% level. In light of these results, the discussion revisits the convergence hypothesis by emphasizing the role of endogenous and institutional factors in shaping inclusive development across Ecuadorian cantons. The discussion underscores the importance of public expenditure quality in Latin America (LATAM) as a critical factor impacting the region’s economic growth, social equity, and overall development. Full article

As a vital engine of economic growth, the digital economy can boost agricultural productivity while curbing carbon emissions from grain production, thereby facilitating the green transformation of traditional agriculture and the sustainable development of grain production systems. It serves as a pivotal anchor for achieving China’s dual-carbon strategic goals in the agricultural sector and supporting the long-term sustainability of national grain security. This paper conducts an in-depth analysis of the carbon emission mitigation mechanisms of the digital economy for sustainable agricultural production. Using panel data covering 30 provincial-level regions in China from 2012 to 2021, this study employs and integrates panel regression estimation, mediating effect analysis, and the Spatial Durbin Model (SDM) framework to identify the underlying pathways through which the digital economy affects carbon emissions from grain production and drives low-carbon sustainable transformation of agriculture. The findings reveal the following: (1) The digital economy exerts a significant negative effect on carbon emission intensity in grain production, laying an empirical foundation for digital-enabled sustainable grain production; (2) It indirectly reduces carbon emission intensity by promoting the development of green finance as a mediating channel, unlocking the sustainable empowerment mechanism of green finance for agricultural low-carbon transition; (3) The development of the digital economy presents pronounced spatial spillover effects: improved digital development in one region also lowers grain production carbon emission intensity in neighboring areas, supporting cross-regional coordinated sustainable development of grain production; (4) The carbon-reduction effects of the digital economy exhibit regional heterogeneity, with more significant emission-reduction outcomes observed in eastern and central regions, while such effects are less prominent in western regions, providing a basis for formulating differentiated regional agricultural sustainable development policies. Based on these findings, this paper puts forward a series of targeted policy recommendations, offering theoretical and practical references for the high-quality development of green and low-carbon agriculture and the overall advancement of sustainable agricultural and rural modernization. Full article

A symbiotic mechanism exists between household livelihood capital and land use transition (LUT). However, previous studies have seldom examined, from a macro perspective, the characteristics of household livelihood capital and its impact on LUT, lacking an in-depth analysis of the spatial spillover effects and regional heterogeneity. Household livelihood capital influences LUT by shaping livelihood strategies. This article incorporates psychological capital into the Sustainable Livelihood Framework (SLF) and utilizes data from the China Family Panel Studies (CFPS) database and land use data spanning 24 provincial-level administrative units in China from 2010 to 2022; this study employs the Spatial Durbin Model to empirically analyze the impact of household livelihood capital on LUT and its regional variability, along with the spatiotemporal evolution patterns of household livelihood capital and land use change. The results demonstrate the following: (1) From 2010 to 2022, household livelihood capital increased, with higher levels of psychological, natural, and human capital, while social, financial, and physical capital were lower. The eastern region exhibited higher livelihood capital levels than the central and western regions, but the gap narrowed annually. (2) Between 2010 and 2022, LUT primarily involved the transition of cropland to construction land, cropland to forest and grassland, and forest and grassland to cropland. The intensity of LUT increased over time and showed a spatial gradient from west to east. (3) LUT positively affected the LUT of adjacent provinces. Various forms of capital and livelihood strategies had different effects on LUT within a province and across neighboring provinces. (4) The heterogeneity analysis reveals that the eastern region is significantly affected by the competitive effect and the spillover effect from neighboring provinces, while the central and western regions are constrained by water resources and inhibited by pure agricultural farmers. The article reveals the mechanism through which household livelihood capital drives LUT and the spatial spillover patterns, providing scientific evidence for regionally differentiated land management and ecological compensation policies, which is of great importance for the sustainable use of regional land resources. Full article

Urban green spaces are increasingly recognized as key elements of sustainable urban development; however, their economic implications, particularly for labor productivity, remain underexplored in developing countries. This study examines the impact of urban green spaces on labor productivity across 92 Indonesian cities over the period 2014–2024, while accounting for spatial dependence and dynamic effects. Urban green space is measured using the Normalized Difference Vegetation Index (NDVI), and labor productivity is defined as the ratio of regional economic output to employment. The analysis incorporates control variables including life expectancy, environmental quality (AOD), average years of schooling, and GDP per capita. To address spatial and temporal dynamics, this study employs a Spatial Dynamic Panel Data (SDPD) framework. The results show that urban green spaces have a positive and significant effect on labor productivity. In addition, spatial spillover effects are evident, indicating that productivity in one city is influenced by conditions in neighboring areas. Socio-economic factors, particularly health, education, and economic development, also play a significant role. These findings highlight the economic relevance of urban green infrastructure and underscore the importance of integrating environmental considerations into urban policy to enhance productivity in developing country contexts. Full article

Based on the stimulus–organism–response (S–O–R) framework, this study explored the psychological spillover mechanism through which tourism experiences in Museum Agglomeration Areas (MAAs) enhance city image and influence behavioral intentions. Structural equation modeling (SEM) based on survey data yielded several key findings. First, information visibility, content visibility, and the quality of amenities and the operational environment played critical roles in shaping tourists’ internal states, including perceived experiential value, affective response, immersion, and satisfaction. In addition, the social atmosphere emerged as an important factor in enriching these evaluations. Second, accessibility and connectivity were identified as factors that reduce friction along the visitor journey, thereby enhancing experiential continuity and immersion. Third, experiential value and immersion were found to be the primary mediators among the internal-state variables, transmitting the effects of environmental stimuli to city-level perceptions and behavioral intentions, such as revisit and recommendation intentions. These findings suggest that the competitiveness of MAAs lies not merely in spatial agglomeration itself but also in their ability to provide engaging and meaningful content, maintain safe and enjoyable operational environments, and develop integrated circulation and information systems. By conceptualizing MAAs as sites of district-scale tourism experiences, this study extends the application of the S–O–R framework to a multi-site urban cultural context and clarifies how differentiated internal states mediate the spillover from district experience to city-level perceptions and behavioral intentions. Rather than proposing a fundamentally new theoretical framework, the study offers a context-specific refinement of the organism layer and provides empirically grounded implications for design and operational strategies in culturally clustered urban districts. Full article

Bornaviruses are neurotropic, negative-sense RNA viruses with zoonotic potential, notably Borna disease virus 1 (BoDV-1) and variegated squirrel bornavirus 1 (VSBV-1). BoDV-1 is endemic in certain regions of Central Europe and maintained in bicolored white-toothed shrews, but its presence in Croatia has not been investigated. Given Croatia’s diverse biogeography and the prevalence of rodent-borne diseases, this study aimed to investigate the presence of orthobornaviruses in wild canids and mustelids. Brain samples from red foxes (Vulpes vulpes), golden jackals (Canis aureus moreoticus), wolves (Canis lupus), martens (Martes martes) and badgers (Meles meles) were analysed using pan-bornavirus RT-PCR. Despite successful RNA extraction and internal control amplification, bornavirus RNA was not detected in any of the 860 animal samples tested. Although no orthobornavirus RNA was detected, the results still provide valuable information: bornavirus infections appear to be absent or extremely rare in Croatian wild canids and mustelids. By excluding these species as current potential reservoir hosts, this study helps to refine the geographical extent of bornavirus endemicity and emphasises the importance of continuous One Health surveillance in regions with favourable ecological conditions for zoonotic spillover. Full article

Existing approaches mainly characterize connectedness in four dimensions: node size, direction, spillover magnitude between nodes, and time variation. However, the sign of spillovers has not been explicitly incorporated into the analysis. To address this limitation, this paper introduces sign as a fifth dimension and constructs a five-dimensional signed network-topology framework based on BVAR historical decomposition. The framework is used to examine the evolution of spillover signs and to explore the multidimensional spillover effects among the cryptocurrency, NFT, and foreign exchange markets. The results show that the signed spillovers across these three markets vary over time during the sample period. On average, DXY exerts negative spillover effects on the cryptocurrency market, while ETH exerts more pronounced negative spillover effects on the NFT market. Furthermore, during the COVID-19 pandemic and the cryptocurrency crash period, BTC shifted from a net receiver of risk spillovers to a net transmitter. In terms of sign, spillover magnitudes vary relatively little across periods, whereas sign reversals occur more frequently. Full article

Bats are reservoirs for many emerging viruses, yet broad-scale spatial patterns of bat viromes and their ecological determinants remain unclear, limiting spillover risk assessment. To address this, we conducted a standardized survey across central to southern China. During 2022–2023, fecal samples were collected from 527 bats representing 17 species at 21 caves in seven provinces. Using each cave as the analytical unit, samples from all species at a site were pooled to construct 21 fecal RNA virome libraries for metatranscriptomic sequencing; viral-like contigs were annotated, and viral alpha/beta diversity was quantified at the genus level. Sites were grouped by geographic distance and latitude to evaluate spatial differentiation and to relate virome patterns to host community attributes and environmental factors. We annotated 56 viral families, including 19 vertebrate-associated families, with multiple families and genera shared across geographic groupings. Vertebrate-associated viral diversity showed limited evidence of geographic isolation within the study region but suggested gradual turnover with latitude. Host species richness was the strongest correlate of virome diversity, exceeding the effects of evaluated environmental variables (e.g., climate and human activity). These results support prioritization of species-rich bat habitats for surveillance and risk assessment. Full article

Yellow fever (YF) remains a re-emerging vector-borne zoonotic disease in tropical regions of the Americas despite the availability of an effective vaccine. In South America, the virus is maintained through a jungle transmission cycle involving Haemagogus and Sabethes mosquitoes and non-human primates (NHPs), which act as amplifying hosts and key epidemiological sentinels. This narrative review examines the current status of YF epizootics in South America, with a focus on the role of NHPs in viral circulation, early detection, and spillover risk to human populations. We synthesize recent evidence on epizootic patterns across endemic countries, the differential susceptibility of neotropical primates, and the ecological and environmental drivers influencing transmission, including deforestation, habitat fragmentation, and human encroachment into forested areas. In addition, we analyze current surveillance strategies, including wildlife monitoring, entomological and genomic surveillance, and their integration within a One Health framework. This review highlights that YF epizootics are expanding geographically and are closely linked to environmental change and human–ecosystem interactions. Strengthening integrated, multidisciplinary surveillance systems is essential to improve early detection, guide vaccination strategies, and prevent human outbreaks. These findings underscore the critical importance of operationalizing the One Health approach to enhance preparedness and response to YF in South America. Full article

Antibiotic resistance genes (ARGs) are prevalent in livestock environments due to antimicrobial use, yet their airborne dispersal into human-occupied indoor spaces remains poorly characterized. We investigated whether airborne ARGs disperse from livestock stables into farmers’ homes and surrounding outdoor environments. Electrostatic dust collectors were deployed in paired pig and cow stables and their associated homes in Jutland, Denmark, to collect settled airborne dust. Pooled samples were analyzed using shotgun metagenomic sequencing. ARG dispersal patterns were assessed using FEAST source tracking and ecological similarity metrics, including shared ARG ratios and Jaccard indices. Pig production systems exhibited higher antibiotic use and stronger resistome continuity with farmers’ homes than cow systems, reflected by greater FEAST contributions (P = 0.029) and Jaccard similarity (P = 0.029). Beta-diversity analysis supported higher compositional similarity between pig stables and homes (PERMANOVA R² = 0.23, p = 0.052), whereas cow environments showed greater divergence (R² = 0.41, P = 0.035). Across environments, tetracycline, macrolide–lincosamide–streptogramin B, and aminoglycoside resistance genes dominated, consistent with livestock-specific antibiotic use patterns. Supplementary indoor–outdoor comparisons across cow, pig, and chicken stables (from an independent 2024 sampling campaign not directly comparable to the 2008 EDC-based survey) revealed contrasting dispersal dynamics, with higher bacterial species spillover from cow stables but stronger ARG overlap from pig stables. Collectively, these findings are consistent with airborne ARG connectivity across occupational and environmental interfaces and support consideration of air as a potential pathway in One Health AMR surveillance. Full article

The paper analyzes the structural transformations in tourism using the network input–output (IO) model. The study is based on IO tables for two years (2013 and 2023). This allows a comparative analysis of changes in the structure of technical coefficients and in multipliers associated with production and tax revenues. The approach enables the identification of changes in tourism’s position within the economic network. Tourism is also analyzed in terms of the degree of integration, dependence on intermediate inputs, and the capacity to spread the economic effects. The results show few upstream linkages for tourism. There is a low level of spillovers. To make it more resilient and generate more spillovers, it is important to build relationships with sectors such as agriculture, creative industries, and business services. The reliance on outsourced services could affect relationships with productive industries. Full article

Universities play a critical role in knowledge creation and technological innovation, serving as key drivers of regional development. However, existing research has paid limited attention to the mechanisms through which university innovation inputs translate into firm-level performance, particularly in the context of science and technology corridors in emerging economies. This study investigates how university innovation resources affect enterprise performance in the G60 Science and Technology Corridor within China’s Yangtze River Delta, one of the country’s most dynamic innovation regions. Using a panel dataset of 55 universities across nine cities from 2008 to 2017, we employ spatial analysis and fixed-effects panel regression models to examine the relationship between university innovation inputs and firm performance and further explore the mediating roles of local human capital and firm R&D investment. The results show that university innovation inputs significantly enhance enterprise performance, although excessive human resource inputs exhibit a negative effect on both short-term and long-term outcomes. Local human capital and firm R&D investment serve as key mediating mechanisms, with input and output resources influencing enterprise performance through distinct pathways. Heterogeneity analysis reveals that non-state-owned enterprises and small- and medium-sized enterprises derive greater long-term benefits from university resources. These findings contribute to the literature by clarifying the conceptual distinction between university innovation inputs and outputs, and by demonstrating the micro-level mechanisms—R&D investment and human capital—through which university-generated knowledge affects firm performance. The results also provide empirical evidence from an emerging economic context, extending the applicability of knowledge spillover and absorptive capacity theories. Policy implications include optimizing university human resource allocation, strengthening university–enterprise collaboration, and providing targeted support for non-state-owned enterprises and SMEs. Future research may extend the analysis to include institutional factors and university heterogeneity. Full article

Misclassification of binary outcomes in network settings may bias the estimates of causal effects, including spillover effects that arise from social interactions, and may generate spurious causal effects. To address this issue, we develop a parametric framework that jointly estimates misclassification probabilities and causal effect parameters within a binary choice model with neighborhood exposure mappings. Monte Carlo simulations show that ignoring outcome misclassification or network-related variables leads to substantial bias, whereas the proposed method achieves a smaller bias and RMSE. By applying the method to microfinance and social network data from Karnataka, we find that under binary exposure, ignoring outcome misclassification yields statistically significant spillover and overall effects, whereas these effects become statistically insignificant once outcome misclassification is corrected for. Furthermore, omitting network-related variables overstates the direct effect. These results underscore the importance of jointly correcting for outcome misclassification and accounting for network-related variables to obtain credible causal inference. Full article

Aujeszky’s disease (AD), caused by suid herpesvirus 1 (pseudorabies virus, PRV), is a highly contagious infection primarily affecting swine, with wild boars serving as an important reservoir in Europe. Spillover infections in non-suid species, including carnivores, are rare but typically fatal and of epidemiological concern. This study presents the first case of AD in a grey wolf (Canis lupus) in Central Europe with genomic characterization. The 8-month-old wolf was found in the Carpathians (SE Poland), moribund with acute neurological signs, and euthanized for animal welfare reasons. Necropsy revealed no pathognomonic gross lesions. Molecular analyses of tissues confirmed the presence of PRV DNA using real-time PCR, and virus isolation was successful. Genomic analysis revealed that the PRV isolate clustered within genotype I, the predominant circulating genotype in Europe. However, due to the limited availability of reference PRV genome sequences from European wildlife, the precise geographic origin and transmission pathways of this strain could not be fully resolved. In the presented case, wild boars were considered a possible source of infection. This highlights the potential for PRV transmission to apex predators. This study emphasizes the importance of systematic surveillance of PRV in wildlife and the need for expanded genomic databases of PRV strains. Full-genome sequencing is crucial for improving the understanding of PRV transmission. Full article