Search Results (7)

The urgent global challenge of mitigating climate change has intensified the need to reduce carbon emissions. China significantly contributes to greenhouse gas emissions, placing substantial pressure on its industrial sector to shift toward a low-carbon economy. However, current efforts have not yet achieved adequate progress in emission reduction. Digital Transformation (DT), involving the integration of digital technologies into business operations, offers a promising pathway for sustainable practices and emission reduction in Chinese industrial enterprises. This study investigates the impact of DT on Carbon Emissions Intensity (CEI) using data from listed companies (2013–2022) and explores the moderating role of Environmental, Social, and Governance (ESG) practices. Findings reveal that DT significantly reduces CEI, with green technological innovation (GTI) acting as a key intermediary. ESG moderates both the direct relationship between DT and CEI and indirectly influences intermediary variables like GTI, further affecting CEI. Heterogeneity analysis shows DT effectively curbs CEI in capital- and technology-intensive industries in China’s eastern and western regions, though its impact is weaker elsewhere. The study recommends that policymakers promote DT through targeted incentives, boost GTI, and strengthen ESG oversight and disclosure. These measures can help industrial enterprises leverage digitalization and sustainability to advance China’s carbon neutrality goals. The insights also provide valuable recommendations for other developing nations facing similar environmental challenges and seeking sustainable development pathways. Full article

Analysis of the relationship between future land use change and agricultural non-point source pollution (ANPSP) evolution is vital to promoting sustainable regional development. By simulating future land use types, we can identify and analyze the evolution trend of ANPSP. This study takes Chongqing as a case study to establish an integrated solution based on the PLUS model, output coefficient model, and GIS technology. The solution can simulate data, identify trends, and identify key control areas under future development scenarios. The results show that the PLUS model can simulate land use types at the provincial scale with high accuracy, with a Kappa coefficient of around 0.9. The land use type changes show that urban expansion has occupied a large amount of cultivated land. From 2000 to 2020, the proportion of high-load areas with TN pollution load levels was 4.93%, 5.02%, and 4.73%, respectively. Under the two scenarios in 2030–2050, the number of high-load areas decreased, and the average load level decreased from west to east. Sensitivity analysis found that risk changes are more sensitive to the increase in fertilizer application. When the TN and TP output coefficients are increased, the number of towns with increased levels is greater than those with decreased levels when the output coefficients are decreased. Sensitivity analysis can better identify key pollution control areas. The areas sensitive to changes in farmers’ behavior are mainly the Hechuan District, Nanchuan District, Qijiang District, Jiangjin District, and Bishan District. This study provides data and decision-making support for rural green development and water environment improvement. Full article

The aim of the present study was to assess the suitability of mountainous areas for construction land on the basis of landslide susceptibility, to obtain the spatial distribution pattern of said suitability and to improve the existing theories and methods used to ascertain said suitability. Taking Hechuan District in Chongqing as the research area and using data relating to 754 historical landslide sites from 2000 to 2016, we selected 22 factors that influence landslides. The factors were classified into five types, namely topography and geomorphology, geological structure, meteorology and hydrology, environmental conditions and human activities. A landslide susceptibility model was constructed using the random forest algorithm, and safety factors of construction land suitability were established according to the results of landslide susceptibility, with the suitability of land for construction in mountainous areas assessed by combining the key factors (natural, social and ecological factors). The weights of the factors were determined through the use of expert approaches to classify the suitability of land for construction in the research area into five levels: prohibited, unsuitable, basically suitable, more suitable and most suitable. The results of the study show that: (1) The average accuracy of the tenfold cross-validation training set data of landslides reached 0.978; the accuracy of the test set reached 0.913; the accuracy of the confusion matrix reached 97.2%; and the area under curve (AUC) values of the training set, test set and all samples were 0.999, 0.756 and 0.989, respectively. Historical landslide events were found to be mostly concentrated in highly susceptible areas, and the landslide risk level in Hechuan District was mostly low or very low (accounting for 76.26% of the study area), although there was also a small proportion with either a high or very high risk level (9.25%). The high landslide susceptibility areas are primarily concentrated in the southern and southeastern ridge, in the valley and near water systems, with landslides occurring less frequently in the gentle hilly basin. (2) The suitability of land for construction in mountainous areas was strongly influenced by landslide susceptibility, distance from roads and distance from built-up areas; among such parameters, rainfall, elevation and lithology significantly influenced landslides in the region. (3) The land suitable for construction in the study area was highly distributed, mainly in urban areas where the three rivers meet and around small towns, with a spatial distribution pattern of high in the middle and low on both sides. Furthermore, the suitability of land for construction in Hechuan District was found to be primarily at the most suitable and more suitable levels (accounting for 84.66% of the study area), although a small proportion qualified for either the prohibited or unsuitable level (accounting for 15.72%). The present study can be extended and applied to similar mountainous areas. The landslide susceptibility map and construction land suitability map can support the spatial planning of mountainous towns, and the assessment results can assist with the development direction of mountainous towns, the layout of construction land and the siting of major infrastructure. Full article

At present, research on the influence of human activities (especially urbanization) on the microbial diversity, structural composition, and spatial distribution of rivers is limited. In this paper, to explore the prokaryotic community structure and the relationship between the community and environmental factors in the Jialing River Basin of Chongqing, so as to provide a basis for monitoring microorganisms in the watershed. The V3–V4 region of the 16 S rRNA gene was analyzed by high-throughput sequencing and the microbial community of the waters of the Jialing River was analyzed for the diversity and composition of the prokaryotic community as well as the species difference of four samples and correlations with environmental factors. The main results of this study were as follows: (1) The diversity index showed that there were significant differences in the biodiversity among the four regions. At the genus level, Limnohabitans, unclassified_f_Comamonadaceae, and Hgcl_clade were the main dominant flora with a high abundance and evenness. (2) A Kruskal–Wallis H test was used to analyze the differences of species composition among the communities and the following conclusions were drawn: each group contained a relatively high abundance of Limnohabitans; the Shapingba District had a higher abundance of Limnohabitans, the Hechuan District had a wide range of unclassified_f_Comamonadaceae, and the Beibei District had a higher Hgcl_clade. (3) Through the determination of the physical and chemical indicators of the water—namely, total nitrogen, total phosphorus, chemical oxygen demand, chlorophyll A, and an analysis by an RDA diagram, the results demonstrated that the distribution of microbial colonies was significantly affected by the environmental factors of the water. Chemical oxygen demand and ammonia nitrogen had a significant influence on the distribution of the colonies. Different biological colonies were also affected by different environmental factors. Full article

Frequent natural hazards such as flooding and the devastating consequences of severe events make the humanitarian supply chain particularly important in alleviating the suffering of those communities impacted by such events. However, the ambiguity of information and the different goals of stakeholders demand that the humanitarian supply chain must be resilient. This research adopts the use of literature review and expert opinions to identify the indicators that affect the resilience of the humanitarian supply chain using the flood event in Hechuan District, China in 2020 as an example. Based on the combination of fuzzy Decision-making Trial and Evaluation Laboratory and Analytic Network Process (fuzzy-DEMATEL-ANP), the interrelationships between the indicators and the weights of each indicator are calculated. The research results indicate that decision-makers in the humanitarian supply chain should vigorously coordinate the cooperation among stakeholders, ensure the effective transmission of information, and formulate forward-looking strategic plans. At the same time, these key decision makers should also be aware of the need to adjust their strategies at different stages of the flooding event in order to achieve a flexible humanitarian supply chain that responds to the varying demands over the course of a flooding event. The results of this study will help professionals involved in humanitarian supply chains to develop strategies and plans to become more resilient thus helping to reduce losses from natural hazards such as floods. Full article

Capturing the spatial heterogeneity and characteristic scale is the key to determining the spatial patterns of land surfaces. In this research, the core observation area of the middle reaches of the Heihe River Basin was selected as the study area, and the scale identification of several typical objects was carried out by implementing experiments on moderate- and high-resolution remotely sensed ASTER and CASI NDVI images. The aim was to evaluate the potential of the local variance and semivariance analysis to characterize the spatial heterogeneity of objects, track their changes with scale, and obtain their scales. Our results show that natural objects have multiscale structures. For a single object with a recognizable size, the results of the two methods are relatively consistent. For continuously distributed samples of indistinctive size, the scale obtained by the local variance is smaller than that obtained by the semivariance. As the image resolution becomes coarser and the research scopes expand, the scales of objects are also increasing. This article also indicates that with a small research area of uniform objects, the local variance and semivariance are easy to facilitate researchers to quickly select the appropriate spatial resolution of remote sensing data according to the research area. Full article

The innovation behavior (IB) of followers is vital for individuals and organizations. It is not only an important part of individual performance but also an essential foundation of organizational innovation. In general, understanding the formation mechanism of followers’ IB could enhance organizational innovation performance and sustainable competitiveness. The innovation of this study includes the following points. First, in the previous research on the antecedent variables of the IB of followers, the key factor of implicit follow cognitive difference (IFCD) was not examined. We add this key factor to the independent variables of our formation mechanism. Second, in the relationship between IFCD and followers’ IB, we investigate the mediating role of psychological empowerment (PE) and the moderating role of person-organization Fit (P-O Fit), further shown as a mediation model with moderating variables. Third, this study adopts a longitudinal research design, and the data were obtained from 1:1 matched leaders and their followers of large and medium-sized enterprises in China. To avoid deviation in the homologous method, this study gathers data at three-month intervals to ensure that leadership’s influence on followers is effective. In this study, Amos 24.0 and SPSS 24.0 are used for empirical research. The results show IFCD has a negative effect on the IB of followers; PE has a partial mediating effect on the relationship between IFCD and IB of followers; P-O Fit plays a positive regulatory role in the relationship between IFCD and PE, and P-O Fit moderates the mediating effect of PE on the relationship between IFCD and IB. Based on our empirical research, we put forward some feasible suggestions for company managers to increase sustainability in market competition by promoting the formation of the IB of followers. Full article