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.

Local communities and their opinion on shale gas exploitation (SGE) play an essential role in the implementation of energy policies, while little is known about the reasoning process underpinning the acceptance of SGE. The present study develops a conceptual framework to examine the psychological process of residents’ acceptance of local SGE, in which the impacts of trust, knowledge, and fairness are mediated by risk and benefit perceptions. Structural equation modeling has been applied to analyze the hypothesized relationships based on a dataset of 825 households in China’s largest shale gas field. Our results indicate that residents’ perceived fairness and trust positively affect their benefit perceptions and negatively affect their risk perceptions, which results in positive influences on acceptance, and knowledge of SGE’s environmental impacts positively affects perceived risks, which results in a negative influence on acceptance. Moreover, residents’ acceptance is primarily determined by their benefit perception, followed by perceived fairness, and knowledge is the least important determinant. Thus, our study contributes to the literature by exploring the structural relationships between various psychological predictors and the acceptance toward SGE, and the results from our empirical survey provide insight into designing appropriate strategies in the process of generating and communicating shale policies.

This study investigates the economic and ecological impacts of straw returning technology among apple growers in Shaanxi and Gansu provinces, China. Using Propensity Score Matching (PSM) and survey data, the findings reveal that straw returning significantly increases farmers’ incomes by 20.33% compared to those who do not adopt the technology. Additionally, the technology mitigates soil fertility decline by 11.07%, offering substantial ecological benefits. The heterogeneity analysis highlights that older farmers benefit more from the technology in terms of both income and soil fertility improvement, likely due to their experience and reliance on farming. Smaller-scale farmers also show greater gains in income and soil health, while larger-scale farms face complexities that may delay visible benefits. However, land fragmentation did not significantly influence the outcomes. The study recommends promoting straw returning through enhanced farmer training, financial incentives, and improved access to credit. Policymakers should consider tailoring support to different farmer demographics and orchard sizes. Future research should focus on long-term evaluations of straw returning’s sustainability in terms of soil fertility and crop yields. Overall, straw returning technology offers a promising solution for enhancing both economic returns and environmental sustainability in apple production.

Digital new infrastructure (DNI) has emerged as a pivotal force in reshaping regional economic geography. However, the existing literature primarily focuses on its macro-growth effects, leaving a significant gap regarding whether it effectively bridges the divide in Digital–Real Economy Integration (DRI) and promotes sustainable regional development. Based on panel data from 31 provinces in China (2013–2023), this study employs a two-way fixed-effects model to empirically investigate the impact of DNI on the balanced development of DRI and its underlying mechanisms. The research findings are threefold: First, DNI acts as a critical driver of regional convergence in DRI by accelerating digital technology diffusion and facilitating digital talent mobility, thereby significantly mitigating inter-provincial disparities. Second, heterogeneity analysis reveals that the convergence effect of DNI is contingent upon regional environments: the “picking the winners” bias in fiscal expenditure inadvertently weakens the inclusive nature of DNI; conversely, a robust high-tech industrial base, financial deepening, and the “East Data, West Computing” strategy significantly enhance the convergence effect by strengthening technology absorption capacity and alleviating financing constraints. Third, threshold effect analysis confirms the catalytic role of marketization, demonstrating that a mature market environment effectively breaks the geographical stickiness of factor flows, thus amplifying the balanced growth dividends of DNI. This study not only extends the theory of regional convergence into the digital era but also provides critical policy insights for achieving sustainable and inclusive digital transformation.

With the construction and development of the Silk Road Economic Belt, it is of great significance to analyze the land urbanization level of cities along the route. This paper established a new evaluation system, consisting of 11 indexes from 6 aspects, to measure the land urbanization level of 71 core cities in the Silk Road Economic Belt in 2014.The Principal component analysis (PCA) method was used to determine weight of indexes and get calculation results. In the course of these studies, it is visually apparent that spatial differentiation phenomena and unbalanced development exist both in provincial scale and urban scale. To promote sustainable development of Silk Road Economic Belt, enhancing the top design, improving the evaluation system, strengthening the cooperation and handling the relationship between exploitation and protection of resources are considered effective methods.