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Enhancing rural ecological protection and promoting the adoption of environmentally-friendly agricultural production practices largely depend on the implementation of green production methods by farmers. This research paper focuses on the green production behavior of farmers in Hainan Province, China, drawing insights from survey responses provided by 543 farmers. The study examines how farmers’ capital endowment, ecological cognition, and environmental regulation impact their multiple green production practices, using the ordered probit model, mediation effect model, and moderation effect model for analysis and further applying the Ivoprobit_CMP, PSM, and other methods for endogeneity treatment and a robustness test. The study reveals several key findings. Firstly, only a small proportion of farmers consistently adopt green production practices throughout various stages of agricultural production. Secondly, the research shows that capital endowment, including natural, economic, human, and social capital, has a significant influence on farmers’ green production behavior. Thirdly, the study finds that ecological cognition plays a crucial role in mediating the relationship between capital endowment and its dimensions (human and social capital) and the adoption of green production practices. Additionally, the research discovers that environmental regulation positively moderates the relationship between ecological cognition and farmers’ green production behavior. Finally, the research indicates that factors such as ethnicity, fluctuations in agricultural production, and the location of the village agricultural waste collection site are all significant determinants of farmers’ engagement in green production practices. The study also identifies significant regional disparities in farmers’ adoption of green production practices. To address the issue of farmers’ low adoption of green production practices, the paper recommends promoting the overall green transformation of the entire agricultural production process. This can be achieved by enhancing farmers’ capital endowment in multiple dimensions and improving their ecological cognition through various channels. Additionally, creating a supportive external environment that aligns with green production practices is deemed critical.

The growing appreciation of distance decay as an important parameter necessary for estimating willingness to pay (WTP) is hugely recognized in the literature. In this paper, we estimated the extent to which distance decay and individual’s socioeconomic characteristics influence the WTP for restoration of environmental quality attributes in the Heihe River Basin. A choice experiment technique was used to evaluate the household’s WTP for the improvements in local environmental attributes. The results of mixed logit model significant impact of distance on the individual’s WTP for the improvements in environmental attributes. Findings of the study revealed that people living within 25 km from the river are willing to pay more for an increase in the river water quality level, a reduction in sandstorm days, and an increase in the area of the east Juyan Lake than the people living within the range of 50 km and much more compared to 50 km away from the river. Based on the socioeconomic characteristics, it is concluded that the level of education, age, household’s annual income, and household size have a significant effect on the WTP. Results of the implicit prices for each attribute showed the preferences of the inhabitants for every attribute, where the highest WTP in pooled data was recorded for river water quality level (i.e., RMB 124.81/year) and the lowest for leisure and entertainment (i.e., RMB 0.40/year). The highest WTP for water quality suggests that water quality level was the most favored attribute compared to others, subject to the given conditions of water quality and the river basin.

Based on the Chinese county-level panel data from 2014–2018, in the study reported in this paper, we empirically tested the “complementarity and substitution” effects of internet finance and rural finance on rural economic development using the feasible generalized least squares (FGLS) estimation method. The research data were obtained from the China County Statistical Yearbook. Similarly, the data of agricultural credit societies were obtained from the unique database of the agricultural credit societies of Shaanxi Rural Finance Research Center, while the internet finance development index was obtained from the Digital Finance Research Center of Peking University. In this research, we found that rural finance and internet finance contribute to rural economic growth. In the context of rural economic growth, internet finance and rural finance development show a substitution effect. The scale and efficiency of rural finance contribute to rural economic growth, while the structure of rural finance has the opposite effect. The development of internet finance reduces the marginal contribution of the rural financial scale and efficiency to rural economic growth. It weakens the negative effect of the rustic financial structure on rural economic growth. Furthermore, the development of internet finance contributes to the rural economic growth of counties of high economic levels but hinders the development of counties of low and medium economic levels. In counties with a high economic status, the development of internet finance and rural finance have a complementary effect on rural economic growth, while in counties of low and medium economic levels, we can observe a substitution effect. These assessments provide guidance, a source for policy recommendations and a reference for researchers and policy makers seeking to optimize the structure and break the monopoly pattern of agricultural credit cooperation in the rural financial market and to strengthen innovation and significantly improve the operational level of rural financial institutions. Moreover, the development of internet financial business and technology is necessary to overcome the demerits of traditional financial institutions.

Valuation of environmental goods and services are frequently spatially heterogeneous, the significance of this heterogeneity for policy analysis is gradually recognized. For the valuation of environmental goods and services in the context of attaining a better environmental status across Heihe River basin (HRB), Northwest of China by 2020, a survey was conducted employing choice experiment approach across the entire river basin. In this research we estimate the impact of distance from inland rivers’ origin (spatial attribute) on the inhabitants’ willingness to pay for restoration of ecological attributes. A total of 11 ecological attributes were selected including 6 land related attributes and 5 water related attributes. The present study displays the outcomes of the research planned to examine differences in willingness to pay across different locations/distances. A total of five cities and 33 surround villages/townships were included to examine for location effect, while four ad hoc base distances split samples were recognized for distance effect i.e. ≤100 km, ≤200 km, ≤300 and > 300 km from rivers’ origin. The results of mixed logit model recognized that people living at different locations value the attributes differently. For instance the people of Zhangye region are willing to pay RMB 95.66 annually for improvements in biodiversity while in Gaotai the individuals’ willingness to pay (WTP) for the same attributes was RMB 45.68. Similarly, the respondents’ living nearer to the origin of river were willing to pay relatively higher amount for the upgradation in the degraded ecosystem services than the remainders. The results of willingness to pay obtained by Krinsky Robb method confirmed that the attributes quality of agricultural products and water quality were the most preferred attributes with the willingness to pay RMB 91.09 and 122.89 respectively. The significant results of willingness to pay may serve as a reference for sustainable improvements and uplifting of the degraded ecological attributes.

This study examines the determinants of farmers’ climate adaptation strategies across agro-climatic zones, with particular focus on education, household characteristics, and income. A multi-stage random sample of 200 farmers was analyzed using a stochastic frontier model to assess production efficiency and a logit model to evaluate adaptation choices. Results reveal substantial heterogeneity in productivity, with mean 0.619 technical efficiency scores ranging from 0.378 to 0.961. The variance parameter (γ = 0.723) indicates that most performance differences arise from inefficiency rather than random shocks. Among production inputs, tractor use (0.182) and urea application (0.160) significantly increase yield, whereas cultivated area is negatively associated with output (− 0.943), reflecting land fragmentation and managerial constraints. Labor and DAP were not significant contributors. In the logit model (Pseudo-R 2  = 0.528), farmers’ age and education significantly increase the likelihood of adopting adaptation measures, while larger household size reduces it; agricultural income shows a modest positive effect. These findings suggest that productivity gains are more likely to come from intensification through improved timing, mechanization services, and nutrient management rather than from expanding cultivated area. Policy priorities should focus on three areas: (i) knowledge and extension support, including zone-specific advisories and training; (ii) improved access to mechanization and soil and water management technologies; and (iii) financial tools such as credit and insurance to reduce adoption barriers. Strengthening education and skills, particularly for labor-constrained households, can accelerate the uptake of effective practices, narrow the efficiency gap, and enhance the resilience of maize systems under a warming climate.

Purpose>The main aim of this study is to investigate the impact of climate change and water salinity on farmer’s income risk with future outlook mitigation. Salinity and climate change are a threat to agricultural productivity worldwide. However, the combined effects of climate change and salinity impacts on farmers' income are not well understood, particularly in developing countries.Design/methodology/approach>The response-yield function and general maximum entropy methods were used to predict the impact of temperature, precipitation and salinity on crop yield. The target minimization of total absolute deviations (MOTAD)-positive mathematical programming model was used to simulate the impact of climate change and salinity on socioeconomic and environmental indicators. In the end, a multicriteria decision-making model was used, aiming at the selection of suitable climate scenarios.Findings>The results revealed that precipitation shows a significantly decreasing trend, while temperature and groundwater salinity (EC) illustrate a significantly increasing trend. Climate change and EC negatively impact the farmer's income and water shadow prices. Maximum reduction in income and water shadow prices was observed for A2 scenario (−12.4% and 19.4%) during 2050. The environmental index was the most important, with priority of 43.4% compared to socioeconomic indicators. Subindex amount of water used was also significant in study area, with 28.1% priority. The technique for order preference by similarity to ideal solution ranking system found that B1 was the best climatic scenario for adopting climate change adaptation in the research region.Originality/value>In this study, farmers' income threats were assessed with the aspects of different climate scenario (A1, A1B and B1) over the horizons of 2030, 2040 and 2050 and three different indicators (economic, social and environmental) in Northwestern region of Pakistan. Only in arid and semiarid regions has climate change raised temperature and reduced rainfall, which are preliminary symptoms of growing salinity.

Based on the consideration of the level of the regional radiation effect of the photovoltaic industry, four main regions were selected as case sites in Pingluo County, Ningxia Province, for this research. The study used the double-bound dichotomous CVM model and C-optimal design to revise the bidding value of the payment scheme that reduced the WTP range error. Five independent sub-sample questionnaires, including seven bidding value payment schemes, along with four internal range tests and six external range tests, were designed. The results showed that the comparison of the WTP for the improvement of agricultural resources and the environment among different independent sub-samples in the same region passed the external quantitative scope test, indicating that the questionnaire design, survey implementation, and WTP estimation results of the double-bound dichotomous CVM in this study were reliable. Saturation degree, diminishing marginal utility, and substitution effect are the main influencing factors of low marginal WTP added value and embedding effect. When the quantity range changes, the utility of respondents tends to saturate and marginal utility rapidly decreases. Influenced by the aforementioned factors, the sum of the independent estimates of the respondents on the WTP for the improvement of agricultural green resources and environment of the photovoltaic industry in the four research areas is 3.04 times the average value of the overall estimates of the four areas. In order to obtain and maintain the local photovoltaic industry for agricultural production resources and environmental improvement, the average WTP of each respondent was 99.80 yuan per year.

The emphasis of current study is on the assessment of households' willingness to pay (WTP) and preference heterogeneity for the upgradation of degraded terrestrial and aquatic ecosystem services across sub-basins of Heihe River. A sum of 1679 households were interviewed through choice experiment, and random parameter logit model is applied for welfare estimation. The estimated results signified the importance of selected terrestrial and aquatic ecological attributes. Sampled respondents of upper and middle basins placed highest WTP for reducing the emission of greenhouse gases among all other attributes and the WTP amount was 99.27 and 66.49 Yuan/Year respectively. Whereas in lower basin, improvement in landscape of farmland was highly valued, i.e., 107 Yuan/Year. In terrestrial ecosystem services the lowest WTP was recorded for Ejinaqi oasis size in all sub basins. In aquatic ecosystem services, improving water quality was the most valued attribute in all sub basins, and the corresponding WTP values are 122.81, 99.87 and 177.43 Yuan/Year in upper, middle and lower basins respectively, which ensure the significance of water quality in the entire basin. In aquatic ecosystem services the lowest WTP amount was recorded for leisure and entertainment conditions in each sub basin.

The current study aims to analyze the regional differences and spatiotemporal dynamic evolution of carbon emission intensity (CEI) and carbon emission per capita (CEPC) of planting industry with consideration of carbon sink effect. The results indicate that: (i) The CEI and CEPC of China’s planting industry present significant non-equilibrium distribution characteristic during the investigate period, provinces with high CEI are mainly distributed in major agricultural provinces, while high CEPC provinces are mainly located in northeast and individual central provinces with large planting industry. (ii) Inter-regional difference is the principal course of the total differences, the CEI Theil index demonstrates gradient decreasing pattern of “western > central > eastern > northeast,” the contribution rate of CEI Theil index shows “northeast > eastern > central > western,” the CEPC Theil index shows the spatial pattern of “northeast > central > western > eastern,” and the contribution rate of CEPC Theil index presents the spatial pattern of “eastern > central > western > northeast.” (iii) The dynamic evolution of CEI and CEPC curve presents polarization or multipolar differential phenomenon accompanies with distinct gradient characteristics, the regional difference of agglomeration level in CEI is gradually narrowing, while the CEPC gradually expanding and the dispersion level is increasing, which implies the “intra-regional convergence and inter-regional divergence.” Consequently, differential carbon reduction policies have been put forward according to the study findings.

The Chinese government has proposed a “double carbon” target as a response to climate change and has been incorporated in the vision 2035. Agriculture’s green development is intrinsically related to financial support, but conventional financial mechanisms fall short in their efforts to foster economic growth and curb environmental degradation. The current research examines the theoretical effects of green finance on agricultural green total factor productivity in the context of “double carbon.” The mediating effect and moderating effect models are used to empirically examine this mechanism based on the panel data (2015–2019) of 30 provinces in China. The estimated results suggest that green finance development can significantly increase agricultural green total factor productivity, with an inverted U effect and an apparent regional heterogeneity. The eastern region has a stronger promotional effect than the central and western regions. The advanced industrial structure plays a mediating effect on the impact of green finance on agricultural green total factor productivity. Rural human capital can effectively mediate the mediating effect of advanced industrial structure on the impact of green finance on agricultural green total factor productivity. The aforementioned results offer fresh perspectives and empirical evidence for China’s green finance policy improvement, harmonizing regional green finance development, promotion of industrial structure improvement, and rural human capital optimization.