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The aim of this study is to discern the role of digital finance in driving rural industrial integration and revitalization. Specifically, it intends to shed light on how the deep development of digital finance can contribute to the optimization and transformation of the rural industrial structure. The research further explores the particular effects of this financial transformation in the central and western regions of China.

This research studies the influence of digital finance on rural industrial integration across 30 Chinese provinces from 2011 to 2020. Utilizing the entropy weight method, a comprehensive evaluation index system is established to gauge the level of rural industrial integration. A two-way fixed effects model, intermediary effect model, and threshold effect model are employed to decipher the relationship between digital finance and rural industrial integration.

Findings reveal a positive relationship between digital finance and rural industrial integration. A single threshold feature was identified: beyond a traditional finance development level, the marginal effect of digital finance on rural industrial integration increases. These effects are more noticeable in central and western regions.

Empirical outcomes contribute to policy discourse on rural digital finance, assisting policymakers in crafting effective strategies. Understanding the threshold of traditional finance development provides a new perspective on the potential of digital finance to drive rural industrial integration.

The purpose of this paper is to empirically investigate the effect of rural finance on industrial integration of rural primary, secondary and tertiary industries.

Using household-level data collected by Third National Agricultural Census and the provincial-level data collected from Wind database, the authors estimated the impacts of rural finance on rural industrial integration using Logit and Probit regression models. Further, the authors examined how the effect of rural finance varies with the age and education of householders, and with household and provincial characteristics by investigating the moderating effect.

The findings show that rural finance has a significant and positive effect on promoting farmers’ participation in new agricultural management organizations. This effect is more obvious in families whose householders are 40–50 years old, or families that have more educated members. This is because the middle-aged or educated people are more willing to accept and take part in industrial integration. The results further indicate that rural finance has a greater effect on industrial integration in provinces with a high degree of marketization, and in provinces with the high output value of industries and services in agricultural intermediate input.

The authors investigated the impact of rural finance on rural industrial integration empirically, and this topic is rarely covered before. The findings of this study also enrich the literature on financial development and economic growth as well as provide policy suggestions on how to promote rural industrial integration.

The contradiction of construction land in economically developed regions is becoming more prominent, and the scale of construction land in some large cities is close to the ceiling. Therefore, China implemented the policy of construction land reduction in 2014. The main objective is to optimize the stock of homesteads and then help to realize rural revitalization by transferring land indexes across regions. Shanghai took the lead in implementing the reduction policy in 2014, for which reduction acceptance data are available. Thus, this paper evaluates the impact of homestead reduction on rural economic development based on data from towns in Shanghai.

This paper uses the difference-in-difference (DID) model to analyze the policy effects of homestead reduction on rural residents' income and industrial integration development. Using economic agglomeration (EA) as a mediating variable, the authors explore how homestead reduction (HR) promotes EA to drive rural economic development and analyze the impact of geographic location and government investment.

HR significantly promotes rural economic development and shows a significant cumulative effect. In the long run, HR can improve rural residents' income and promote industrial integration by promoting EA. The positive effect of HR and EA in suburban regions on industrial integration development is gradually increasing. However, the incentive effect on rural residents' income is weakening. The positive mediating effect of EA is significantly higher in regions with low government investment than in regions with high government investment.

This paper contributes to testing the impact of HR policy on rural economic development and can provide a reference for other regions aiming to implement reduction policy.

The public health emergency of COVID-19 (Corona-virus disease) pandemic has greatly impacted tourism industry, especially in the rural tourism. This paper aims to study how rural tourism practitioners can get out of the mire of the pandemic. By analyzing the behaviors of various stakeholders and the logic of the impact of the pandemic, the behaviors of participants and future development were sorted out. The key elements that promote the recovery of rural tourism were discovered.

Based on the framework of institute analysis and development (IAD), this research selected six rural tourist communities in China as subjects for the studies. Based on the seven basic principles of hermeneutics and the inductive research method, following the analysis method of “first-order coding, second-order coding, aggregated dimensions,” the texts obtained through in-depth interview and work reports were analyzed and concepts were extracted.

The paper extracted 44 first-order concepts and 14 second-order concepts, and obtained 7 aggregation dimensions, including policy formulation and implementation, improvement of integrated marketing capabilities, improvement of tourism product quality, restrictions on rural tourism development, protection and optimization of environmental resources, industrial integration strategies and improvement of managerial and coordinating capabilities. During the pandemic, the government, enterprises and associations, as the service providers of rural tourism, can optimize the environmental resources and industrial resources of rural tourism by formulating policies, refining products and strengthening marketing in the action arena, to promote the industrial integration of rural tourism and provide better products and services for tourists.

This paper uses the IAD framework to study how rural tourism communities can successfully recover from the impact of the pandemic. It is found that the rapid recovery of rural tourism is the result of collective action. The core of establishing the collective action mechanism of rural tourism is consensus mechanism, co-construction mechanism and sharing mechanism. By studying the path and possibility of collective action of rural tourism communities, this paper explores the approach of multi-center governance of rural tourism communities to promote the imminent recovery of rural tourism.

新冠疫情（COVID-19）对旅游业，尤其是乡村旅游产生了极大影响。本文旨在探究乡村旅游从业者如何摆脱疫情危机。研究通过分析疫情带来的影响及各利益相关者的反应，梳理旅游从业者的行为，探究乡村旅游未来的发展。研究指出了促进乡村旅游复苏的关键因素。

基于制度分析与发展（IAD）理论框架，本文选取中国境内6个乡村旅游目的地作为研究对象。采用解释学七大基本原则和归纳式研究方法，通过对深度访谈和政府工作报告获得的文本进行分析，提取出“一阶编码、二阶编码、聚合维度”。

研究提取44个一阶编码和14个二阶编码，最终得到7个聚合维度，包括政策制定与实施、整合营销能力提升、旅游产品质量提升、乡村旅游发展制约因素、保护和优化环境资源、实施产业整合战略和提高管理协调能力。疫情期间，政府、企业和协会作为乡村旅游的服务提供者，可以通过制定政策、改善产品、加强营销，优化乡村旅游的环境资源和产业资源，推动乡村旅游产业融合，为游客提供更好的产品和服务。

本文利用IAD框架研究乡村旅游在疫情中的复苏。研究发现，乡村旅游的快速复苏是集体行动的结果。建立乡村旅游集体行动机制的核心是共识机制、共建机制和共享机制。本文通过研究乡村旅游社区集体行动的路径和可能性，探索乡村旅游多中心治理的途径，促进乡村旅游复苏。

This paper aims to establish a systematic cognition to alleviate the supply–demand contradiction in rural financial markets from an integrated perspective of knowledge management and proposes the concept of rural financial knowledge ecosystem (RFKE) to encourage multifaceted solutions.

The authors qualitatively describe the process that the knowledge management dilemmas cause the supply–demand contradiction in the rural finance and further summarize a systematic methodology from three dimensions: the knowledge subject, the knowledge environment and the knowledge ecology.

The authors list four types of knowledge management dilemmas leading to the supply–demand contradiction in the rural finance, i.e. the weak knowledge sharing, the poor knowledge flow, the slow knowledge updating and the imperfect knowledge environment. Meanwhile, the RFKE model consisting of the ecological subject, the ecological environment and the ecological regulation is also presented.

The role of knowledge management in improving the allocation of financial resources to various rural financial market participants (government, rural financial institutions, farmers, agricultural enterprises, etc.).

The authors creatively give the RFKE model, which complements and enriches the theory of knowledge management. Meanwhile, relevant management practices are urgently needed under the macro circumstance of the COVID-19 pandemic and the rural revitalization in China.

The results indicate that land prices exert pressure on retail performance (RP) and that the enhancement of digital means has a positive effect on RP. Additionally, digital instruments (DI) play a significant moderating role in the relationship between land prices and RP.

This paper empirically examines the impact of land prices on RP using panel data from 239 Chinese cities between 2011 and 2022.

The use of lagged land prices as instrumental variables effectively alleviates endogeneity issues. Both two-stage least squares (2SLS) and generalized method of moments (GMM) regression results suggest that higher land prices are associated with improved RP. Further analysis reveals that the increase in land prices leads to scale effects, structural effects and technological effects, contributing to the enhancement of RP. The impact of land prices on RP becomes more pronounced in larger cities and economically developed regions experience the pressure from land prices earlier.

The findings of this study have practical implications for discussions on retail industry development, site selection for retail businesses and the establishment of sustainable mechanisms for expanding domestic demand.

In 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.

The 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.

Conditional 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.

This 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.

This 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.

To 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.

This study aims to clarify the impact of agriculture–tourism integration (ATI) on in situ urbanization (ISURB) of rural residents, to highlight the role of industrial integration in the process of China's ISURB and to provide industrial integration suggestions for promoting urbanization quality in Chinese counties.

By sorting out the panel data of China's 1868 counties, the evaluation index system of ISURB was constructed. Difference in difference (DID) and spatial Durbin-difference in difference (SDM-DID) model is used for estimate the relationship between ATI and ISURB.

First, ATI can improve ISURB by 11.4% higher than other regions. Second, theoretical analysis model of ATI on ISURB is constructed from four aspects of “drive–push–pull–block.” The results show that ATI can promote ISURB by increasing upgrading of rural industries, rural employment demand and income capacity, whereas ATI may inhibit ISURB by reducing farmland. Third, considering changes in institutional, hard and soft factors, rural collective economy, information infrastructure and digital finance all promote positive impact of ATI on ISURB. Fourth, ATI will produce spillover effects on ISURB in neighboring regions, which is more pronounced in the central and western regions.

This study lacks quantification of ATI, so future studies are encouraged to further quantify ATI at the county level.

This study has policy significance for constructing ATI demonstration counties and promoting ISURB in China's counties.

It is of great practical value to promote China's ISURB. By stimulating ATI, it can improve income and employment capacity of rural residents and stimulate ISURB of China.

This study enriches the theoretical and practical research on industrial integration behaviors during the process of ISURB.

1. Use county data to measure in situ urbanization (ISURB)

2. Agriculture–tourism integration (ATI) can increase ISURB

3. Constructs a “drive-push-pull-block” model to explain the influence mechanism

4. Use spatial Durbin-difference in difference (SDM-DID) models

5. Consider collective economy, rural information infrastructure and digital finance

Use county data to measure in situ urbanization (ISURB)

Agriculture–tourism integration (ATI) can increase ISURB

Constructs a “drive-push-pull-block” model to explain the influence mechanism

Use spatial Durbin-difference in difference (SDM-DID) models

Consider collective economy, rural information infrastructure and digital finance

The purpose of the paper is to identify, analyze and select the enablers for vertical integration of Aloe vera supply chain (AVSC) so that rural employability will be enhanced in the context of Rajasthan, India.

Interpretive structural modeling (ISM) was proposed to develop a structural model to identify the right enablers for enhancing the rural employability and business prospects. Also, fuzzy-matrix cross-reference multiplication applied to classification (F-MICMAC) was applied to segregate the enablers into four clusters on the basis of their driving and dependence power. Finally, the significant enablers were selected.

Out of identified 13 enablers, three enablers (i.e. institute for training and research, transportation infrastructure and government incentives for value addition) were appearing at the bottom of the ISM structural model and also in the driving quadrant of driver-dependent diagram. Therefore, they are the significant enablers for vertical integration of AVSC to enhance the rural employability in the context of Rajasthan, India.

The interactions among enablers are not statistically validated. However, the empirical analysis and total interpretive structural modeling may be used for this purpose.

The outcomes of the study will provide the guidelines for implementation of vertical integration at the village level to enhance rural employability in the context of Rajasthan, India in specific.

Although a few studies have been reported in the literature related to value-addition process (vertical integration), but the modeling of enablers to segregate and identify the appropriate enablers for vertical integration of AVSC for enhancing employability at the rural areas is unique.

Development of urban-rural integration is essential to fulfill sustainable development goals worldwide, and comprehension about urban-rural integration types has been highlighted as increasingly relevant for an efficient policy design. This paper aims to utilize an unsupervised machine learning approach to identify urban-rural integration typologies based on multidimensional metrics regarding economic, population and social integration in China.

The study introduces partitioning around medoids (PAM) for the identification of urban-rural integration typologies. PAM is a powerful tool for clustering multidimensional data. It identifies clusters by the representative objects called medoids and can be used with arbitrary distance, which help make clustering results more stable and less susceptible to outliers.

The study identifies four clusters: high-level urban-rural integration, urban-rural integration in transition, low-level urban-rural integration and early urban-rural integration in backward stage, showing different characteristics. Based on the clustering results, the study finds continuous improvement in urban-rural integration development in China which is reflected by the changes in the predominate type. However, the development still presents significant regional disparities which is characterized by leading in the east regions and lagging in the western and central regions. Besides, achievement in urban-rural integration varies significantly across provinces.

The machine learning techniques could identify urban-rural integration typologies in a multidimensional and objective way, and help formulate and implement targeted strategies and regionally adapted policies to boost urban-rural integration.

This is the first paper to use an unsupervised machine learning approach with PAM for the identification of urban-rural integration typologies from a multidimensional perspective. The authors confirm the advantages of this machine learning techniques in identifying urban-rural integration types, compared to a single indicator.