This research examines the relationship between environmental regulation and corporate green innovation, with particular emphasis on the moderating role of data asset disclosure. Against the backdrop of accelerating digital transformation, this study draws on signaling theory to investigate whether data asset disclosure partially substitutes for environmental regulation in promoting corporate green innovation. Using panel data from Chinese A-share listed companies during 2010-2024, the hypotheses are examined through panel regression analysis. A series of robustness checks are conducted to address potential endogeneity concerns, including propensity score matching and instrumental variable estimation. The results show that environmental regulation is positively associated with corporate green innovation, whereas data asset disclosure weakens this relationship. Further heterogeneity analysis indicates that this effect varies across different external environments and internal firm conditions, reflecting differences in the effectiveness of disclosure signals and firms' ability to leverage them. Overall, the findings extend the literature on environmental regulation and green innovation by highlighting the role of data asset disclosure as an important informational signal in the relationship between environmental regulation and corporate green innovation. These findings also provide practical insights for policymakers seeking to better coordinate environmental governance with digital transformation and for firms aiming to strengthen sustainable innovation through effective data disclosure.
Promoting green production behavior among large-scale rice farmers is critical to advancing the green transformation of agriculture. Existing studies have focused primarily on smallholders, while insufficient attention has been paid to how information sharing and industrial organization constraints jointly shape green production behavior among large-scale rice farmers under China’s Double Reduction policy. Using micro-survey data from 263 large-scale rice farmers in Jiangsu Province in 2024, this study defines large-scale rice farmers as those cultivating at least 50 mu of rice and deriving at least 60% of their total household agricultural income from rice production. An ordered Probit model is used for the baseline estimation, supplemented by OLS estimations, CMP-based endogeneity tests, and robustness checks using alternative variable specifications. The results show that both information sharing and industrial organization constraints significantly promote green production behavior among large-scale rice farmers. These findings remain robust after accounting for potential endogeneity and using alternative variable specifications. Moreover, the interaction between information sharing and industrial organization constraints is significantly positive, indicating that the two factors reinforce each other in promoting green production behavior. By integrating information sharing and industrial organization constraints into a unified analytical framework, this study clarifies how the two factors jointly shape green production behavior among large-scale rice farmers and provides micro-level empirical evidence for the green and low-carbon transformation of agricultural production under the Double Reduction policy.
Runoff-driven transport of crop-derived non-point source pollutants is a major cause of water quality deterioration in small and medium-sized agricultural watersheds in hilly regions. However, there is a lack of scientific and effective evaluation methods for farmland non-point source pollution control. In this study, an indicator system for non-point source pollution control technologies in watershed crop production was developed based on the characteristics of the available control technologies. The indicator weights were quantified using the improved analytic hierarchy process and the Criteria Importance Through Intercriteria Correlation (CRITIC) method. A comprehensive evaluation of non-point source pollution control technologies for crop production was then conducted through the combination of the scores of each technology. Finally, a case study of pollution control in the Yaoshi River, China, was conducted to validate the model. The top three technologies identified were ecological buffer strips, ecological interception ditches, and ecological detention ponds, which were implemented in the Yaoshi River project. After implementation, the project achieved removal rates of 59.38% for chemical oxygen demand, 78.57% for total phosphorus, and 72.18% for nitrate. The practical application demonstrates that the evaluation model can provide a theoretical basis for selecting technologies to control non-point source pollution from crop production within the watershed.
Unsustainable clothing consumption poses increasing environmental, socio-economic and health concerns globally, yet evidence on students’ sustainability practices across the clothing consumption cycle remains limited. This study examined such practices among tertiary institution students in Enugu State, Nigeria. A cross-sectional survey of 2,055 students selected from six tertiary institutions in Enugu State was conducted using a validated Sustainable Clothing Consumption Practices Questionnaire (SCCPQ). Reliability was confirmed (Cronbach’s α: 0.707-0.898; composite reliability: 0.768-0.912). Data were analysed using descriptive statistics, Mann-Whitney U test, Kruskal-Wallis H test and Dunn’s post-hoc tests. Respondents were mostly females (65%) aged 21-25. Students demonstrated high awareness of sustainable clothing consumption especially in environmental impact of clothing consumption (mean, 3.92-3.99) but low for social issues, sustainable purchasing, and recycling. Weather and fashion trends mostly influenced pre-acquisition decisions. Acquisition practices moderate wear frequence but low local buying or label-checking. Utilization involved basic mending/stain removal, rarely care label adherence. Significant institutional differences were found in acquisition-utilization practices (p, 0.001). The major barrier was limited awareness of sustainable, trendy clothing options. Students recommended curriculumbased sustainability education, partnerships with sustainability brands, and on-campus repair-recycling systems. Tertiary institutions should institutionalize these strategies to reduce the awareness-practice gap and promote sustainable clothing behaviour.
This study investigated the nutrient composition and in situ dry matter (DM) degradability of hydroponic feeds produced from white barley, black barley, and wheat in comparison with their corresponding unsprouted original grains. Additionally, the growth characteristics of these hydroponic feeds were assessed. Hydroponic fodders were cultivated under controlled conditions and evaluated for fresh weight, dry weight, dry matter loss, sprout length, and root mat thickness. Nutrient composition was determined, and DM degradability was assessed using the in situ nylon bag technique. Hydroponic feeds exhibited lower DM content but higher ash, crude fiber, acid detergent fiber, and crude protein than the original grains (P = 0.0001). Fresh weight, sprout length and root thickness were found similar among the hydroponic fodders (P > 0.05). However, the lowest dry weight and highest dry matter loss and total phenolic compounds were detected in hydroponic wheat (P < 0.05). In situ ruminal incubation indicated that grains showed overall greater DM degradability than hydroponic fodders (P < 0.05). The rapidly degradable fraction (a) was higher in hydroponic feeds, particularly wheat, whereas the slowly degradable fraction (b) and degradation rate constant (c) were greater in grains (P = 0.0001). In conclusion, hydroponic fodders can be used as beneficial source to improve microbial activity and early ruminal nutrient availability.
