Background: Digital transformation in the sports industry has become increasingly crucial for sustainable development, yet comprehensive empirical evidence on policy effectiveness and risk management remains limited. Purpose: This study investigates the impact of policy support and risk factors on digital transformation in sports companies, examining heterogeneous effects across different firm characteristics and regional contexts. Methods: Using panel data from 168 sports companies listed on China's A-shares markets and the New Third Board from 2019 to 2023, this study employs multiple regression analyses, including baseline models, instrumental variables estimation, and robustness tests. The digital transformation level is measured through a composite index incorporating digital infrastructure, capability, and innovation dimensions. Results: The findings reveal that policy support significantly enhances digital transformation levels (coefficient = 0.238, p < 0.01), while financial risks demonstrate the strongest negative impact (−0.162, p < 0.01). Large firms and state-owned enterprises show stronger responses to policy support (0.312 and 0.278, respectively, p < 0.01). Regional development levels significantly moderate the effectiveness of policy implementation. Conclusions: The study provides empirical evidence for the differential effects of policy support and risk factors on digital transformation across various firm characteristics. The findings suggest the need for differentiated policy approaches considering firm size, ownership structure, and regional development levels. Implications: Policy makers should develop targeted support mechanisms addressing specific challenges faced by different types of firms, while considering regional disparities in digital transformation capabilities.

With the economic development and the carbon emissions cluster rise, this study uses CiteSpace, VOSviewer, and R-based Bibliometrix software to visualize and analyze the relevant literature on carbon emissions retrieved from the Web of Science database from 2014 to 2023. Through the analysis of the trend of publication volume, author co-citation analysis, institutional co-citation analysis, country co-citation analysis, literature co-citation analysis, thematic analysis of research, research evolution, and other related contents, it reveals the main academic forces, hot research areas, thematic focus changes and cutting-edge trends of international carbon emission research. The results of the study found that the themes of international carbon emissions research focus on carbon emissions, the drivers of carbon neutrality, and the impacts of climate change. An in-depth study of these aspects can help formulate more effective climate policies and emission reduction strategies to achieve global carbon neutrality and combat climate change.

Under the background of economic globalization and the rapid development of science and technology, the development of higher education (HE) has undergone profound changes. Nowadays, in order to increase the international competitiveness, training international talents has become the primary task of universities and HE institutions. Therefore, taking Shenzhen as an example, the research takes quantitative method to study how the educational resources in the society affect the school from a macro perspective, and the micro perspective of students, teachers and schools, studying the impact on the development of universities. Through in-depth analysis of the integration of educational resources, the results show that multilingual library resource, and other three factors followed, are critical factors in the development of HE. And then, this study puts forward corresponding countermeasures and suggestions after discussion, aiming to provide strategic insights to enhance the quality and international competitiveness of HE in the GBA, especially in the construction of multilingual library resources (MLR), international exchange platform (IEP), sufficient and diverse laboratory facilities (SDLF), and rich academic resources (RAR). Thus, the research narrows the gap in this field to some extent.

This project analyzes the evolution of the manufacturing sector in Portugal from 2009 to 2021, focusing on the variations in the number of active companies across various subcategories, such as food, textiles, and metal product industries. The goal of this analysis is to understand the dynamics of growth and contraction within each sector, providing insights for companies to adjust their market and operational strategies. Key objectives include analyzing the overall evolution in the number of companies, identifying subcategories with notable changes, and providing a comprehensive analysis of observed trends and patterns. The study is based on data from PORDATA 2024, and the research employs temporal trend analysis, linear and quadratic regression, and the Pareto representation to identify patterns of growth and decline. By comparing annual data, the project uncovers periods of growth and decline, allowing for a deeper understanding of the sector’s dynamics. The findings also highlight variations in periods of economic crises and during the Covid-19 pandemic, and recommendations for action are presented to support businesses resilience and continuity. These results are valuable for companies within the manufacturing sectors analyzed and policy makers, guiding strategic decisions to navigate the complexities of the market dynamics and to ensuring long-term organizational sustainable success.

Assessment of water resources carrying capacity (WRCC) is of great significance for understanding the status of regional water resources, promoting the coordinated development of water resources with environmental, social and economic development, and promoting sustainable development. This study focuses on the Longdong Loess Plateau region and utilized panel data spanning from 2010 to 2020, established a three-dimensional evaluation index system encompassing water resources, economic, and ecological dimensions, uses the entropy-weighted TOPSIS model coupled with global spatial autocorrelation analysis (Global Moran’s I) and the hot spot analysis (Getis-Ord Gi* index) method to comprehensively evaluate the spatial distribution of the WRCC in the study region. It can provide scientific basis and theoretical support for decision-making on sustainable development strategies in the Longdong Loess Plateau region and other regions of the world.From 2010 to 2020, the overall WRCC of the Longdong Loess Plateau area show some fluctuations but maintained overall growth. The WRCC in each county and district predominantly fell within level III (normal) and level IV (good). The spatial distribution of the WRCC in each county and district is featured by clustering pattern, with neighboring counties displaying similar values, resulting in a spatial distribution pattern characterized by high carrying capacity in the south and low carrying capacity in the north. Based on these findings, our study puts forth several recommendations for enhancing the WRCC in the Longdong Loess Plateau area.