This study explores the spatial correlation of global productive service trade in three stages (2005-2010, 2011-2016, 2017-2022) using the exports of productive services from 42 countries worldwide from 2005 to 2022 as a sample, and then uses social networks and QAP methods to analyze the evolutionary pattern and determining factors of the global productive service trade network. The results showed several key features of this system. (1) During the sample study period, the number of relationships in the global productive service trade network gradually increased and the stability continued to be enhanced. The network has obvious “small world” characteristics, and the speed of node interaction is accelerating. Some developed countries have a clear central position in the network, but developing countries led by China are increasingly playing a bridging role in the global productive service trade network. (2) The members of the global productive service trade network can be divided into four different sectors: “bidirectional spillover”, “intermediary”, “main benefit”, and “net benefit”, and the spillover effects of the export growth of productive service industries in different sectors have obvious ladder characteristics. However, with the increasing frequency of global trade in productive services, its network modularity continues to decline, and the division of member factions is becoming increasingly unclear. (3) The spatial relationships of the global productive service trade network exhibit characteristics of “neighborhood interaction” and “club groups”. During the three sample periods of 2005-2010, 2011-2016, and 2017-2022, geographic adjacency, economic development level, similarity in economic development mode, and the signing of regional trade agreements could collectively explain 52.6%, 60.2%, and 75.8%, respectively, of the spatial correlation in global productive service trade.

Exploring the changes in food consumption and dietary nutrient intake of Chinese urban and rural residents is of great significance. This study constructed a Chinese food nutrient model using data from “China Statistical Yearbook”, “China Rural Statistical Yearbook”, “China Yearbook of Household Survey”, and “China Yearbook of Rural Household Survey”. The structure and changes in food consumption and nutrient intake among urban and rural residents in China from 2000 to 2020 were analyzed using dietary balance indices and comparisons with dietary recommendations. The results show that higher consumption of cereals and lower consumption of dairy products remained the main problems in food consumption by both urban and rural residents from 2000 to 2020. The dietary nutrient structure of urban and rural residents developed a dual calorie structure dominated by grain and supplemented by vegetable oil, a dual protein structure dominated by grain and supplemented by pork, and a triple fat structure dominated by vegetable oil and supplemented by both pork and grain. Rural plant-based and animal-based dietary nutrition lagged behind that of urban areas, with a difference of roughly 20 years. The results of this study clarified the food consumption and dietary nutritional structures and changes of urban and rural residents. We found the deficiencies in the current dietary structure and made recommendations for improving the nutritional health of urban and rural residents.

As an emerging integrated economic system, the ice and snow economy holds significant importance for promoting high-quality regional economic development. This study first employs data visualization techniques to illustrate the current status of China's ice and snow economy. On this basis, it uses the LSTM neural network model to conduct a predictive analysis of its future development trends. Furthermore, by analyzing the industrial convergence mechanism and operational mechanisms of the ice and snow industry, the study explores the underlying logic driving the development of China's ice and snow economy. Finally, it identifies the challenges in its development and proposes relevant policy recommendations to promote the high-quality development of the ice and snow economy in the Chinese context. The findings show that since China was awarded the right to host the 2022 Winter Olympics in 2015, its ice and snow economy has entered a period of rapid growth. The total market scale expanded from 270 billion yuan in 2015 to 980 billion yuan in 2024, with a compound annual growth rate of 15.4%. However, the ice and snow economy still faces challenges such as homogeneous consumption structures, incomplete industrial chains, unbalanced regional development, and constraints on sustainable development. It is therefore urgent to formulate targeted solutions based on China's actual conditions, gradually establishing a well-structured ice and snow industry system characterized by clear government-market collaboration, supply-demand alignment, dynamic cost-benefit equilibrium and balanced development and protection-ultimately propelling the high-quality development of China's ice and snow economy.

Fostering a dynamic sports culture relies heavily on sporting events and community engagement. In the pursuit of a robust sports culture, organizing sports events and encouraging public involvement are of utmost significance. A deep comprehension of understanding how sports events shape consumer interest holds both theoretical and practical value. This study focuses on the audience of the 2022 Beijing Winter Olympics, considering both from online and offline. Through meticulously constructing a comprehensive framework that encompasses spectator experience, demonstration effect, and media influence, and collecting 679 valid surveys nationwide, it adopts the partial least squares method-structural equation model (PLS-SEM) for in-depth analysis. The study finds that the ‘traffic’ generated by sports events directly influences consumers’ purchase intentions in three ways: spectator experience, demonstration effect, and media influence. Among these, the demonstration effect has the most significant impact, and perceived value plays a partial mediating role. Based on the findings, several practical recommendations are proposed to further unlock the cultural and economic value of large-scale sporting events. This study not only provides empirical support for understanding the mechanisms through which mega-events stimulate consumer behavior but also offers strategic insights into enhancing the social influence and commercial value of sports in the digital era.

In 2020, China clearly put forward the “double carbon” goal of striving to achieve its carbon peak by 2030 and carbon neutrality by 2060. Energy companies are the main source of carbon emissions and key players in reducing emissions, so they shoulder a pivotal responsibility in achieving this strategic goal. At the same time, Environmental, Social and Governance (ESG) concepts are highly compatible with the “dual-carbon” goal. Therefore, it is of great practical significance to explore the impact of ESG on energy companies to realize the “dual-carbon” goal. In this study, we analyzed the impact of ESG on the total factor productivity of energy companies and its mediating effect from the perspectives of investor preference and financing constraints. The results of this study show that good ESG performance of energy companies can enhance their total factor productivity through the positive effects of investor preference and financing constraints, and the extent of the effects was found to vary among companies with different equity natures, regional situations, and different backgrounds of the directors, supervisors, and senior executives. In view of these effects, energy companies should enhance their total factor productivity by strengthening investor preference and alleviating financing constraints; and they should also learn from each other’s ESG development models to promote the overall ESG level of the energy industry.

In 2022, Chinese policymakers emphasized the importance of leveraging the country’s domestic energy resource endowments and implementing a phased and well-planned carbon peaking strategy by following the principle of “establishing the new before phasing out the old”. To explore the carbon reduction potential and path optimization in resource-based regions undergoing energy structure adjustments, this study employed the Long-range Energy Alternatives Planning System (LEAP) to simulate and analyze both a baseline scenario and a comprehensive policy intervention scenario from 2021 to 2050. This study focused on the typical resource-based region of Inner Mongolia Autonomous Region and developed a customized “LEAP-Inner Mongolia” model. The findings reveal that: (1) Under the comprehensive scenario, energy demand is notably reduced by 2050, with total carbon emissions cut by 70.96% compared to the baseline scenario; (2) The Environmental Kuznets Curve (EKC) analysis suggests a persistent rise in emissions under the baseline scenario, while a carbon peak is achieved as early as 2029 under the integrated scenario; and (3) There are limitations of isolated policy instruments so a synergistic approach that integrates power generation structure optimization with improvements in energy efficiency is necessary. Accordingly, we propose a multi-pronged policy portfolio that includes the synchronized development of clean energy and efficient end-use systems, industrial low-carbon transformation, accelerated adoption of new energy vehicles, and improved inter-regional coordination. These recommendations can offer systemic insights for guiding low-carbon transitions in resource-based areas.

Within the framework of China's pursuit of green and low-carbon development, Inner Mongolia is characterized by significant carbon emissions, a substantial share of energy-intensive industries, and disparate development levels across its cities, so it faces substantial challenges in attaining the objectives of carbon peak and neutrality. Utilizing the Logarithmic Mean Divisia Index (LMDI) model, this study investigated the drivers and regional differences in carbon emissions. Drawing upon Tapio’s decoupling framework, the decoupling status between economic growth and carbon emissions among cities was analyzed in phases. We introduced the Extreme Gradient Boosting (XGBoost) machine learning algorithm to construct a classification model that correlates carbon emission drivers with decoupling states, elucidated by the Shapley Additive exPlanations (SHAP) interpretable model, and performed a spatial analysis of regional differences to assess the significance of industrial energy intensity for achieving strong decoupling in each prefecture-level city. The outcomes revealed two main results. (1) Spatially, regional differences in the influence of driving factors can be classified into four categories: energy intensity-dominant, double-effect negative driven, coexistence of positive and negative effects, and economic growth-driven. (2) Temporally, regional differences in the impact of industrial energy intensity on strong decoupling can be categorized into three types: overall positive, marked fluctuation, and stage stability. Consequently, tailoring emission reduction policies based on regional differences will be instrumental for expediting the achievement of the “dual carbon” targets.

Food security has always been the cornerstone of national stability and a critical pillar of sustainable development. Exploring the laws of food supply, utilization, and structural evolution is of great significance for ensuring people's well-being and promoting socio-economic stability. However, as an agriculturally dominated and less-developed economy, the food supply has long been both a core concern and a developmental challenge for Nepal. This study employed the emergy analysis method to systematically examine the changing characteristics and structures of food supply and consumption in Nepal from 1990 to 2023, based on statistical data from the UN Food and Agriculture Organization, Nepal's Central Bureau of Statistics, and Nepal Customs. Two main conclusions were drawn. (1) Between 1990 and 2023, the total emergy of Nepal's food supply increased by over threefold (from 2.46×10²² sej to 8.27×10²² sej), and per capita emergy doubled. However, driven by shifts in dietary preferences, rising demands for dietary balance, and insufficient domestic agricultural production, the food independence ratio (FIR) exhibited a sustained decline and bottomed out in 2021. Concurrently, self-sufficiency rates plummeted for key commodities: cereals (-9%), fruits (-46%), and vegetable oils (-46%) compared to baseline levels. This highlights inadequate supply chain stability and a high reliance on global markets. (2) In terms of consumption structure, both the total and per capita emergy of food consumption fluctuated upward with convergent trends. The proportion of animal-based consumption decreased from 43.00% to 34.97%, while plant-based consumption increased by over 8%. However, there were no fundamental changes in the internal supply structures of either category, with vegetable oils and dairy products remaining dominant, respectively. The results of this study indicate that Nepal's food system faces contradictions between yield growth and the demand for dietary diversification. Strengthening the resilience of local supply chains, formulating comprehensive policies, and enhancing international cooperation are essential for addressing these food security challenges.

Plants are the primary source of traditional remedies around the world. The Baglung District of Nepal has a huge potential for medicinal herbs used ethnobotanically to treat different diseases. We had studied and evaluated the status and uses of medicinal plants with the aim of documenting the ethnomedicinal flora of Jaimini and Bareng municipalities of Baglung District. Key Informant Interviews (KII) and Focus Group Discussions (FGDs) were used in five wards to gather data between November 2021 and October 2022 utilizing open-ended, semi-structured questionnaires. Traditional healers were consulted regarding the stated traditional uses, and the results were cross-validated against previously released research. The SPSS software and MS Excel 2013 were used to aggregate and evaluate the data. Pie charts, graphs, and tables are used to display the data. Altogether, 219 medicinal plants are used by the people of both municipalities. The shrubs and herbs occupy a major percentage in Bareng and Jaimini, respectively, whereas Family Fabaceae and Asteracea represented the maximum no. of species in these municipalities. The mostly used part for the treatment was leaf (25% in Bareng and 19% in Jaimini). Medicinal plants were majorily used to cure illnesses related to digestive system mostly in the form of paste. Low-value plant diversity was rich in both municipalities. Locals were also concerned about its conservational practices. The current study's findings will serve as the foundation for future research into medicinal plants in the study region. In conclusion, plant species must be conserved, and future generations must be educated to learn information that would otherwise extinct.