This study is based on the relationship between the anxiety of social groups (especially the young) in today’s social environment and the increasingly younger and more sociable consumer groups in China’s luxury market. In combination with the new consumption characteristics of sustainable luxury goods, we rethink the factors that contribute to conspicuous consumption behavior in which social groups exhibit differences. In order to test our research hypothesis, two questionnaires were conducted through online channels. In the first survey, data from 135 valid subjects showed a significant negative correlation between subjective social class and conspicuous consumption behavior. In the second survey, data obtained from 255 valid subjects again verified the main effect hypothesis of this study, which is that subjective social class has a significant negative influence on conspicuous consumption. Additionally, it is verified that status anxiety plays a mediating role in the influence mechanism of subjective social class on conspicuous consumption, and the social comparison orientation of individual consumers moderates the influence of subjective social class on status anxiety. This study reveals the applicability of subjective social class to Chinese scenarios and finds that individuals of different social classes have different conspicuous consumption behaviors, which expands the research on the antecedents of conspicuous consumption and enriches the research on consumer psychology and social behavior. In practice, the results of this study will play a positive guiding role in rationally regulating psychology, dispelling social anxiety, reshaping the moral concept of conspicuous consumption, and promoting the sustainable development of luxury consumption at the individual or social level.

Speed climbing has become an Olympic event. However, there have been limited studies on the athletic performance of elite speed climbers under the current IFSC rule. Thus, this study aims to perform a statistical analysis of the performance of elite speed climbers and compare the different sex of the 2019 IFSC Speed Climbing World Cup. The 384 times climbing result in total climbing time, the time of four phases, and the start reaction time were calculated. In addition, the statistical data of men and women’s total error rate in the final round, the error rate in each final round, as well as the body position and the phase when errors occurred were gathered. Several results were not found in previous studies. Firstly, there is no statistical significance between starting reaction and climbing time of male and female. Secondly, there was no significant correlation between phases of the route for male athletes. While there was a statistical correlation between adjacent stages for women, the time of women in each stage was significantly correlated with the previous stage (p < 0.05). The error rate of both men and women in the medal competition stage reached a high rate of ~50%. While the error rate of men in each phase of route has no significant difference, While the error rate of women in the fourth phase was significantly different from the first three parts (p < 0.05), gender-specific training procedures should be developed for elite athletes. Future research should test the psychological state and pressure of speed athletes in the competition.

Under the new development model, the digital economy has become a new engine to promote the green development of the economy and realize the goal of “double carbon”. Based on the panel data of 30 provinces in China from 2010 to 2020, this paper empirically investigates the impact of the development of the digital economy on energy and carbon emissions using a series of econometric models such as baseline regression, a mechanism test, and the spatial Durbin model, etc. Common prosperity plays an intermediary role between digital economy development and carbon emissions; digital economic development optimizes resource allocation, effectively solves the problem of uneven resource distribution, and reduces energy and carbon emissions while achieving common prosperity. In addition, green innovation, industrial structure, urbanization level, R&D intensity, and the degree of marketization also have different degrees of influence on energy and carbon emissions. Therefore, the government should accelerate the construction of new digital infrastructure and implement the digital economy development strategy according to local conditions, so as to promote the digital economy to produce a more significant carbon emission reduction effect.

Electric vehicles, known for their eco-friendliness and rechargeable–dischargeable capabilities, can serve as energy storage batteries to support the operation of the microgrid in certain scenarios. Therefore, photovoltaic-storage electric vehicle charging stations have emerged as an important solution to address the challenges posed by energy interconnection networks. However, electric vehicle charging loads exhibit notable randomness, potentially altering load characteristics during certain periods and posing challenges to the stable operation of microgrids. To address this challenge, this paper proposes a hierarchical optimal dispatching strategy based on photovoltaic-storage charging stations. The strategy utilizes a dynamic electricity pricing model and the adaptive particle swarm optimization algorithm to effectively manage electric vehicle charging loads. By decomposing the dispatching task into multiple layers, the strategy effectively solves the problems of the “curse of dimensionality” and slow convergence associated with large numbers of electric vehicles. Simulation results demonstrate that the strategy can effectively achieve peak shaving and valley filling, reducing the load variance of the microgrid by 24.93%, and significantly reduce electric vehicle charging costs and distribution network losses, with a reduction of 92.29% in electric vehicle charging costs and 32.28% in microgrid losses compared to unorganized charging. Additionally, this strategy can meet the travel demands of electric vehicle owners while providing convenient charging services.

Heterogeneous environmental regulation provides dynamic incentives for green innovation through diversity and complementarity, and promotes technological breakthroughs and market responses. Based on the panel data of 30 provinces in China from 2010 to 2020, this paper constructs a bi-directional fixed-effect model to examine the relationship between heterogeneous environmental regulation and green innovation and the moderating effect of common prosperity. The empirical results show that: (1) there is a significant U-shaped relationship between command-control and public participation environmental regulation and green innovation, while there is a significant inverse U-shaped relationship between market incentive environmental regulation and green innovation; (2) Common prosperity has a significant promoting effect on green innovation, and positively regulates the U-shaped relationship between command and control, public participation environmental regulation and green innovation, and negatively regulates the inverted U-shaped relationship between market incentive environmental regulation and green innovation; (3) There are obvious regional differences in the relationship between heterogeneous environmental regulation, common prosperity and green innovation. Therefore, the government should implement differentiated environmental regulation policies, optimize the incentive mechanism for green innovation according to local conditions, build a multi-level environmental governance system, and strengthen the regulatory role of common prosperity to promote the balanced development of green innovation.

Green innovation is the key endogenous driving force for enhancing the level of coordinated pollution reduction and carbon emission reduction governance. Based on the panel data of 273 prefecture-level and above cities in China from 2014 to 2023, this article constructs a city-level pollution reduction and carbon emission synergy index. Using a two-way fixed effects model, a mediating effect model, a threshold regression model, and a spatial Durbin model, this study systematically examines the impact of green innovation on pollution-carbon synergy and explores its underlying mechanisms. The results show that: (1) Green innovation significantly promotes the enhancement of the synergy effect of urban pollution reduction and carbon emission reduction, and the conclusion remains valid in multiple robustness tests. (2) The upgrading of industrial structure and the optimization of energy consumption structure play a significant mediating role in the process of green innovation influencing the synergistic effect of pollution reduction and carbon emission reduction. Green innovation, by promoting the high-endization of industries and the low-carbonization of energy, enhances the synergistic effect of emission reduction at a deeper level. (3) Green innovation has a significant dual threshold feature for the synergistic effect of pollution reduction and carbon emission reduction. Its promoting effect depends on the improvement of the cleanliness level of the industrial structure and energy consumption structure. (4) Green innovation has a significant spatial spillover effect. It not only enhances the collaborative governance level of local cities but also has a positive impact on surrounding cities through technology diffusion and regional linkage. Therefore, it is necessary to adhere to the governance approach of adapting measures to local conditions and advancing in phases, by improving the green innovation support system, consolidating structural basic conditions and strengthening regional coordination.