Agricultural green development is increasingly being discussed in sustainable development. This paper constructs agricultural green development from four dimensions: resource savings, environmental protection, ecological conservation, and quality industrialization. We apply the entropy-weighted Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method to measure agricultural green development and employ a panel dataset of provinces in China from 2011–2019. Then, the dynamic spatial Durbin model is adopted to estimate the spatial effect of digital inclusive finance on agricultural green development. The main findings are as follows: (1) digital inclusive finance effectively promotes agricultural green development, and the promotional effect shows temporary and spatial spillover; (2) regional heterogeneity exists in the spatial effect in the short and long term; and (3) education, digital infrastructure, and traditional finance are important factors influencing this spatial effect of digital inclusive finance on agricultural green development.

Purpose – Based on a survey of 897 farm households, the purpose of this paper is to build a framework using cluster analysis to explain how farmers make decisions on joining group guarantee, and analyzes factors influencing their decisions using multinomial and binary Logit regressions. Design/methodology/approach – The approach of combining cluster analysis with Logit regression is an innovative approach to survey assessment. In addition, by design the authors have identified the four mutually exclusive groups of borrowers combining Group Guarantee membership and actual formal borrowing. Findings – An extremely important observation according to the data is that most farmers appear to be part of group guarantees only because they have to in order to get access to formal credit products. 87.21 percent of the people who belong to groups and utilize the formal credit products belong to this category because their lenders have made participation in groups compulsory for access to credit. This may ration farmers’ willingness to even apply for credit. It also indicates a preference on the part of older and more risk-averse respondents to avoid participation in group guarantees. Out of financial characteristics the total loan holdings appears to be the only significant indicator of participation in group guarantees. Furthermore the results indicate that informal and formal credit appear to be replaceable for farmers. Research limitations/implications – The survey is confined only to the counties investigated. China is very diverse in its agricultural economies and many RCCs operate under different guidance and rules from those investigated here. Hence, while the authors can claim that the results are indicative, the authors cannot claim that they will hold generally. Practical implications – Based on group guarantee loan mechanism and survey data analysis of 897 farm households, this paper analyzes influencing factors affecting farmers’ participation in group guarantees from microcosmic level, so as to provide some reference to further perfect micro credit operation mode and mechanism. Social implications – The results indicate that the Group Guarantee mechanism, while beneficial to some, may not hold global appeal for Chinese farmers. In the future RCCs may want to consider alternative approaches to loan security than placing the burden of guarantee on farmers’ family and friends. Originality/value – The approach of combining cluster analysis with Logit regression is an innovative approach to survey assessment. In addition, by design the authors have identified the four mutually exclusive groups of borrowers combining Group Guarantee membership and actual formal borrowing.

Although the increasing adoption of digital finance in recent years has exerted a wide-ranging influence on farmers’ consumption and production activities, many farmers in China still seriously suffer from digital financial exclusion. Few studies have documented the different impacts of e-commerce adoption characterized by online purchases and sales on farmers’ participation in the digital financial market measured by their engagement in digital payments, digital wealth management, and digital credit in rural China. Using survey data from 832 entrepreneurial households in rural China, we contribute to the literature by confirming that both online purchases and sales have a robust significant and positive impact on farmers’ participation in the digital financial market and that this impact on digital wealth management is successively larger than that on digital payments and digital credit, with the propensity score matching (PSM) method and instrument variable (IV) approach employed. We further discover that the impact of online purchases and sales on farmers’ participation in the digital financial market is significantly mediated by digital financial literacy. Moreover, the impact of online purchases and sales on farmers’ participation in the digital financial market is larger for those with high education levels, pursuing skills training, running new agricultural operation entities (i.e., family farms, professional cooperatives), and engaging in agricultural entrepreneurship. Our findings suggest that more effective measures to enhance adoption rates of online purchases and sales, innovation in rural market-oriented digital financial products and services, systematic training for farmers in e-commerce skills as well as digital financial literacy, and differentiated support measures for different groups of farmers to reduce the gap are urgently needed in China.

Although rapid urbanization is often considered as one of the most important drivers for changing dietary patterns, little attention has been paid to rural areas despite the profound transformation they have undergone. Using longitudinal data from the China Health and Nutrition Survey (CHNS) for the period from 2004 to 2011, this study seeks to better understand the relationship between the urbanization of rural areas and dietary transition, with the focus on nutrition intake and dietary quality. Our results suggest that with increasing urbanization, rural residents tend to have on average lower calorie intakes but higher dietary quality. Specifically, increasing urbanization consistently reduces carbohydrate consumption and reduces fat consumption after a turning point; protein consumption first decreases and then increases after the turning point with increasing urbanization. Urbanization shows a significant and positive effect on the Healthy Eating Index (HEI). In addition to sociodemographic changes, we find that changing consumer preferences and knowledge serve as important determinants in explaining the dietary transition in rural China from 2004 to 2011. In our study, urbanization appears to positively affect rural residents’ healthy food preferences and dietary knowledge. This study is a first attempt for better understanding the nutrition transition resulting from accelerating urbanization in rural China; several limitations and areas for future research have been highlighted.

PurposeIn this study, the authors examined demand-side credit in rural China with the aims of understanding attribute preferences and the willingness of farmers to pay for credit.Design/methodology/approachThe authors implemented an in-the-field discrete choice experiment (DCE) using a D-optimal block (6 × 9 × 3) design applied to 420 farm households across five Chinese provinces (Shandong, Sichuan, Shaanxi, Jiangsu and Henan) in the summer and fall of 2018. The DCE included six attributes including the interest rate, term of loan, type of loan, type of repayment, type of institution and mobile banking services.FindingsConditional and mixed logit results indicated a downward sloping credit demand curve with variable elasticity across regions. Provincial willingness-to-pay (WTP) indicators suggested that farmers were willing to pay a premium for long-term ( 0.03–0.687%) and low collateral credit loans ( 0.79–2.93%). Also, four of five provinces indicated a preference for loan amortization rather than lump-sum payment. Interestingly, in comparison to the Agricultural Bank of China (ABC), only farmers in Shandong, Sichuan and Shaanxi indicated a preference for rural credit cooperatives (RCCs)/banks and the Postal Savings Bank of China (PSBC). Another quite surprising result was bank services, in our case, access to mobile banking did not appear to induce WTP for agricultural credit. While conditional and mixed logit regression coefficients were similar (and therefore robust), the authors found that there was substantial heterogeneity across attribute preferences on term of loan, type of loan and amortization. Preferences for type of lender and mobile banking were generally homogenous. This result alone suggested that lenders should consider offering a suite of credit products with different attributes in order to maximize the potential pool of borrowers. While there were some differences across provinces, farmers appeared to be indifferent to lenders, and it did not appear that offering banking services such as mobile banking had any bearing on credit decisions.Research limitations/implicationsThis paper presents a first step in using in-the-field choice experiments to better understand rural finance in China. Although the sample size satisfies conventional levels of significance and rank conditions, the authors caution against attributing results to China as a whole. Different provinces have different institutional structures and agricultural growing conditions and economies and these effects may differentially affect WTP for credit. Although by all indications farmers were aware of credit, not all farmers, in fact a minority, actually borrowed from a financial institution. This is not unusual in China, but for these farmers, the DCE was posed as hypothetical. Likewise, the study’s design was based on a generic credit product typical of rural China, and the authors caution against making inferences about other products with different attributes and risk structures.Social implicationsThis study is motivated by the rapidly changing dynamic in China's agricultural economy. With specific reference to new laws and regulations about the transfer of land use rights (LURs), China's agricultural economy is undergoing significant and rapid change which will require better understanding by policy makers, lenders and practitioners of the changing credit needs of farmers, including the new and emerging class of commercial farmers.Originality/valueTo the best of the authors’ knowledge, the authors believe that the result provided in this paper present the first use of in-the-field DCE and are the first to be reported in either the English or Chinese literature on rural credit product design.