In the context of escalating environmental concerns and the imperative for sustainable consumption, this study meticulously examines the variations in food literacy and the propensity to purchase green food among Chinese consumers across three generational cohorts: baby boomers, generation X, and generation Y. Utilizing the theory of planned behavior (TPB) as a conceptual framework, and employing SPSS and structural equation modeling (SEM) for rigorous data analysis, the research elucidates the influence of generational attributes on green food consumption patterns. The study’s importance is marked by its unique contributions: it identifies intergenerational discrepancies in food literacy and furnishes empirical support for the enhancement of green food literacy across all consumer demographics. Furthermore, the research constructs an innovative model of food literacy that integrates generational traits, establishing a theoretical scaffold for advancing consumers’ green food literacy. This comprehensive model synthesizes the determinants of generational variations, food literacy, and the intention to consume green food. Findings from a demographically stratified sample of 720 participants, with equal representation from each cohort and gender (240 participants per cohort), highlight the distinct profiles in food literacy and green food purchasing intentions. These findings are instrumental for stakeholders in formulating nuanced strategies that promote sustainable consumption practices, tailored to the specific characteristics of each generational group within the Chinese market.

Introduction: Given the importance of green food consumption for public health and sustainability, understanding its drivers among university students is crucial for effective health promotion. This study investigates how digital literacy and ecological values shape green food consumption within an extended Theory of Planned Behavior (TPB) framework. Methods: We collected survey data from 836 Chinese university students. An expanded TPB model, which included digital literacy and ecological values, was developed and tested using structural equation modeling to examine their effects on consumption intentions and behaviors. Results: The model yielded three main findings. First, digital literacy was directly associated with purchase intention ( β = 0.257, p < 0.001) and indirectly enhanced it by improving attitudes ( β = 0.317, p < 0.001) and perceived behavioral control ( β = 0.292, p < 0.001). Second, ecological values had a comprehensive impact, directly and indirectly (via attitudes, norms, and perceived control) shaping purchase intention ( β = 0.234, p < 0.001). Third, digital literacy’s effect on subjective norms was non-significant ( β = 0.069, p = 0.145), challenging a core tenet of the traditional TPB. Discussion: Our findings confirm that integrating digital literacy and ecological values into the TPB provides a more robust model for explaining green food consumption. Digital literacy serves as essential cognitive capital, while ecological values are foundational. The decoupling of digital literacy from subjective norms points to evolving social influence mechanisms in digital environments. This research offers practical insights for interventions and a strong theoretical foundation for future studies on sustainable dietary behaviors.

Drawing on the longitudinal dataset from 262 cities at the provincial tier and higher across China between 2011 and 2022, this research employs the production model to formulate the China Urban Industrial Land Mismatch Index, quantifying the extent of industrial land misalignment across China. It also analyzes its spatiotemporal evolution characteristics and regional differentiation characteristics, and explores the influence of China’s urban industrial land discordance on the advancement of urban ecological modernization. The key insights are outlined below. Firstly, across the entire spectrum of Chinese urban centers, cities from the eastern, central, and western zones, as well as those situated along the Yangtze River and the Yellow River basins, exhibit comparable patterns in industrial land misalignment. The extent of industrial land discordance has diminished, regional disparities have lessened to some degree, and there is an absence of polarization or the Matthew effect. Secondly, the variation in industrial land discordance within cities in the eastern region is the most pronounced, followed by the central region, with the western region showing the least disparity. The greatest contrast in the urban industrial land mismatch is found between the eastern and central regions. The primary driver of the discrepancy in industrial land misalignment across the eastern, central, and western regions is predominantly the ultra-variable density, followed by intra-regional disparities, with inter-regional differences contributing the least. Furthermore, the variation in the industrial land mismatch within cities in the Yangtze River Basin surpasses that within cities in the Yellow River Basin. The disparity in industrial land misalignment between the two follows a pattern of initially increasing, then decreasing, and subsequently rising again. The primary origin of this discrepancy lies within regional variations, followed by ultra-variable density, with inter-regional differences contributing the least. Thirdly, the regression analysis reveals that the discordance in industrial land use across Chinese cities exerts a substantial negative influence on urban ecological evolution. This effect operates through technological innovation and the employment levels in the secondary sector. Fourthly, industrial land discordance significantly hampers urban ecological advancement in the eastern region, shows a negative but statistically insignificant impact in the central region, and has a positive yet inconsequential effect in the western region. Moreover, the misalignment of industrial land exerts a notable suppressive influence on the ecological modernization of cities within the Yangtze River Basin, while it plays a significant role in fostering the ecological modernization of cities in the Yellow River Basin. Fifth, the mismatch of urban industrial land has produced significant negative spatial spillover effects on urban ecological modernization.

Climate change and land-use change are making landscape fires worse, causing them to grow in intensity and spread in range across Earth’s ecosystems. Extreme landscape fires can be devastating to people, ecosystems, and sociology. However, most research on landscape fires has not considered their potential impact on the economy, particularly with regard to entrepreneurial activity. Entrepreneurial activity includes the entry of new markets and the creation of new products or services, thereby facilitating the creation and expansion of economic activity. This manuscript empirically analyzes the impact of landscape fires on entrepreneurial activity, based on satellite monitoring data of landscape fires in China from 2014 to 2018. Different wind direction models and instrumental variable methods are used for empirical analysis. The results of the analysis show, first, that an increase in landscape fires in a county can significantly reduce local entrepreneurial activity. We further adopt the wind direction approach and instrumental variable approach to deal with potential endogeneity issues, and the regression results are consistent. Second, compared to eastern or high-economic-development areas, central and western or low-economic-development areas are more susceptible to exogenous landscape fires. Third, landscape fires have a negative impact on entrepreneurial activity through increasing air pollution, damaging human health, increasing risk aversion, and reducing the labor supply. It is important for both the government and the public to fully recognize the potential dangers that landscape fires pose to corporate behavior. This awareness can help reduce the impact of natural disasters such as landscape fires, protect the ecological environment, and provide solid support for corporate investment and regional development.

Based on 2010–2019 Chinese logistics listed companies as research samples, the paper used the binary Logit model measuring degree of financing constraints. The Kernel density function and Markov chain model are used to forecast China listed companies financing logistics dynamic constraints and business performance growth. Furthermore the stock of knowledge was chosen as a threshold variable to explore the impact of financing constraints on corporate performance growth of listed logistics enterprises. We find that the degree of financing constraints of logistics enterprises in our country has not been significantly eased. Corporate performance has not changed significantly and there are no obvious spatial gap and polarization with the passage of time. The impact of financing constraints on the corporate performance growth of logistics enterprises in China has a double threshold effect of knowledge stock, and has an inhibitory effect that first increases and then decreases. This is because in the short term, the investment of knowledge stock by enterprises can crowd out more corporate liquidity, and in the long run, it is related to the conversion rate of the knowledge stock itself. Because of the uneven regional distribution of resources and differences in the degree of economic development, there is a growing disincentive effect in central China as the stock of knowledge accumulates.

Objectives: We investigate the impact of wildfire disasters on cognitive health (i.e., thinking and language skills) in individuals aged 10 years and older using 2014 and 2018 wildfire and cognitive ability survey data from China.Methods: We distinguished wildfires in each county at different wind directions each day by exogenous wind direction changes, and analyzed the effects of wildfires on cognitive abilities through upwind and non-upwind wildfires.Results: Our analysis shows that for every 10-unit increase in upwind wildfires compared to non-upwind wildfires, respondents’ scores on word and math tests decrease by 0.235 and 0.236 standard deviations, respectively. Furthermore, we find that the impact of wildfire on cognitive ability is more pronounced in younger individuals, and those with lower defensive expenditures experience more severe impacts. Additionally, wildfires negatively affect individuals’ cognitive abilities by generating air pollution.Conclusion: Wildfires significantly reduce individuals’ cognitive abilities. Two recommendations are as follows: 1) governments should follow the principle of green development, introduce relevant regulations, and increase investment in adaptive technologies. 2) Individuals should raise awareness of climate hazards preparedness and strengthen defensive protection.