Analysis of Influencing Factors of Farmers’ Homestead Revitalization Intention from the Perspective of Social Capital

Abstract

Revitalizing idle rural residential bases is essential for improving the utilization rate of residential resources, activating pastoral land resources assets, increasing farmers’ property income, and stimulating rural development vitality. Social capital is one of the essential social resources owned by farmers, which is closely related to rural social governance and farmers’ daily lives and plays an indispensable role in revitalizing residential land. Based on the theory of social capital and the survey data of 316 farm households in Shaanxi Province in 2022, this study first empirically analyzes the influencing factors of social capital and its constituent dimensions on farm households’ willingness to revitalize their home-steads using a Logit regression model, and then empirically analyzes the hierarchical structure relationship among the influencing factors using an ISM model. The results of the study show that: (1) Social capital and its three constituent dimensions of social network (“Contact with relatives, neighbors, and families” and “Contact with village committee staff”), social trust (“Trust in friends and relatives” and “Trust in village committee and other organizations”), and social participation (“Participation in meetings of village committees and other organizations”) have significant positive effects on farmers’ willingness to revitalize their residential land. (2) There are differences in the effects of different dimensions of social capital on farmers’ willingness to revitalize their homesteads: social trust as a deep-seated cause affects farmers’ social networks and social participation, which in turn affects farmers’ knowledge of homestead revitalization policies and ultimately farmers’ willingness to revitalize their homesteads. Based on the findings of the study, to improve farmers’ willingness to revitalize their homestead bases, government departments should base their efforts on the social capital characteristics of farmers, increase the cultivation of farmers’ social capital, and strengthen the publicity of the work of revitalizing homestead bases and related policies.

1. Introduction

With the accelerated urbanization process in China, many rural laborers have moved to the cities. The “hollowing out” of rural areas has become increasingly severe, resulting in many idle and wasted residential base resources. Since 2000, 594 million square meters of unused farm buildings have been added each year due to the transfer of rural labor, equivalent to a market value of about CNY 400 billion [1]. To promote the efficient use of rural land resources and to maintain and realize the legitimate rights and interests of farmers’ residential bases, relevant state departments have issued a series of residential base management policies. The No. 1 document of the Central Government from 2017 to 2022 deals with the reform of rural residential bases, encouraging various ways to revitalize and utilize idle residential commands. However, from the implementation of the work of revitalization of residential bases around the world, the problem of low willingness of farmers to revitalize their residential bases is more prominent. Farmers are the key subjects in home base revitalization, and fully respecting farmers’ wishes and adhering to their prominent position are essential prerequisites for rural home base regeneration [2]. China’s rural society is a typical “acquaintance society”. In this social environment, individual farmers’ wishes and behavioral decisions will be influenced by other individuals around them. Due to the limited education level, cognitive judgment ability, and information literacy of farmers, farmers will not only consider the expected benefits and costs in the process of homestead revitalization but also be influenced by public opinion within the village and the decisions of others [3]. As a result, social capital, as the value relationship and mutual identity formed by action subjects in long-term interaction and cooperation, is an essential resource for farmers’ survival and development, which can provide necessary support for farmers [4] and has an important influence on farmers’ willingness to revitalize their homesteads. How does social capital affect the willingness of farmers to revitalize their homesteads? What is the extent of its influence? What is the hierarchical structure among the influencing factors? This paper tries to answer these questions through research.

At present, a wealth of research results has been accumulated around the withdrawal of homestead bases. Homestead withdrawal covers a wide range, including farmers’ voluntary abandonment of legally owned homesteads, farmers’ voluntary withdrawal from abandoned or oversized homesteads, farmers’ withdrawal from illegally occupied homesteads, and farmers who have settled in cities and towns and quit rural idle homesteads [5]. Studies on factors influencing farmers’ willingness to withdraw from homestead bases mainly focus on subjective aspects such as traditional concepts [6], farmers’ characteristics [7], family characteristics [8], farmers’ cognition [9], and objective aspects such as inter-generational differences [10], conflicts of interest between stakeholders [11], and compensation standards and methods [12]. In contrast, studies on revitalizing homestead bases have yet to be available. In addition, the established studies on the impact of social capital on farmers’ willingness have focused on ecological conservation [13,14,15,16], financing collateral [17], and agricultural production [18,19,20,21,22], and there are relatively few studies on social capital and homesteading. With the ongoing promotion of China’s rural homestead reform, how to effectively revitalize the existing homesteads has become a vital issue of the current reform; in addition, in the process of homestead revitalization, farmers can use social capital to obtain material or emotional social support, thus having a particular influence on their willingness to revitalize their homesteads. Does social capital impact farmers’ desire to renew their homesteads? Do different dimensions of social capital have the same effect on farmers’ willingness to inventory their homesteads?

This paper constructs a theoretical model based on social capital theory, taking 316 farming households in Shaanxi Province as an example, and integrates the logistic regression model and ISM model (Interpretative Structural Modeling) to analyze the factors and inter-factor hierarchy of social capital affecting farming households’ willingness to revitalize their homesteads to provide the scientific basis for further improving farming households’ desire to restore their homesteads and promote the smooth implementation of homestead revitalization. The main contributions of this paper are as follows. First, focusing on the relationship between social capital and farmers’ willingness to revitalize their homesteads, few scholars currently combine the two in their research. Second, three dimensions of social capital, namely social network, social trust, and social participation, were selected and a logit regression model was chosen to analyze the influence of each dimension on farmers’ willingness to revitalize their homesteads. Thirdly, we compared the differences in the influence of social network, social trust, and social participation on farmers’ willingness to revitalize their homesteads, and chose the ISM model to analyze the hierarchical structure relationship among the influencing factors of each dimension. Most previous studies have analyzed the hierarchical structure of the factors influencing farmers’ willingness to revitalize their homesteads from an overall perspective, and lack specific analysis from a particular perspective.

The remainder of this paper is structured as follows: Section 2 presents the theoretical analysis and research hypotheses; Section 3 introduces the data sources, variable selection, and model design; Section 4 presents and analyzes the empirical results; and Section 5 gives the research conclusions and policy recommendations.

2. Theoretical Analysis and Research Hypothesis

2.1. The Concept of Social Capital

The theory of social capital was first proposed by Bourdieu, who argued that social capital is the sum of social resources possessed by individuals in society [23]; Putnam later introduced the theory to fields such as political science and economics, where he argued that social capital is a characteristic of social organizations that promote mutual coordination and cooperation through elements such as social trust, social norms, and social networks [24]. In essence, the conditions for social capital are formed based on a network of social relationships. This social network consists of one or more individuals, each of whom is a point on the web with specific social resources. Farmers’ social capital is realized through the trust relationship between farmers, which connects them and facilitates the formation and realization of their common goals and interests. Farmers’ concerned participation in all aspects of social life enables them to gain a sense of identity as a member of a group, and this sense of identity will implicitly influence farmers’ consciousness and behavior [25].

Farmers’ social capital is the network of relationships, shared values, and mutual trust among farmers formed during their long-term rural life. It can be summarized into three dimensions: social network, social trust, and social participation [26]. A social network comprises relationships formed cumulatively through farmers in social exchanges, with kinship, blood, and geography as ties. Social trust is the mutual recognition and dependence generated by farmers in their daily interactions, and the mutual trust relationship among individual farmers can promote the accumulation of social capital. Social participation refers to the farmers’ interest, knowledge, and participation in public affairs, which can give them a certain sense of identity. Because of this, the specific effects of three dimensions of social capital—social network, social trust, and social participation—on farmers’ willingness to revitalize their homesteads are further analyzed below.

2.2. A Theoretical Analysis and Research Hypothesis on the Influence of Social Capital on Farmers’ Willingness to Revitalize Their Homesteads

A social network is a relatively stable social relationship formed between individual farmers due to interaction, which emphasizes the interaction and connection between people [27]. Social networks have been shown to increase wage earnings, improve identity [28], facilitate information transfer, and enhance trust levels [29]. In this relational social environment in rural China, the influence of social networks on household production, business, and life is even more pronounced. Social networks can be classified into strongly and weakly connected networks according to the degree of connectedness among the members of the network [30]. Firmly connected networks have strong social ties between farmers and their friends and relatives. In contrast, the weakly connected network refers to the looser networks formed by farmers in their interactions beyond kinship, geography, and acquaintances. In revitalizing residential land, the strongly connected network is primarily a “human network” [31]. Farmers can rely on the help of friends and relatives to improve their ability to cope with risks, and to alleviate the adverse impact of risk expectations on farmers after the revitalization of residential land; secondly, farmers can exchange and learn from their friends and relatives through social networks, which can help to improve their knowledge of the work of residential base revitalization, so that they can realize the development opportunities brought by the renewal of residential bases for themselves and their villages, and promote their willingness to revitalize. The weakly connected network primarily plays the role of “information bridge” [32]; farmers can effectively broaden the channels and scope of obtaining information related to the revitalization of residential land, increase the capacity, validity, and reliability of the information received, and reduce the cost of information search. Secondly, the close social network enables farmers to express their needs clearly, so that relevant government departments can better understand farmers’ wishes and needs in the work process and improve the scientific nature of the policy and work on revitalizing residential land. Based on this, the first research hypothesis is proposed:

Hypothesis 1.

Social networks have a positive effect on farmers’ willingness to revitalize their homesteads.

Social trust is a relationship of trust that arises from farmers’ long-term interactions and determines to some extent whether farmers are willing to give credit or act on the advice of others. Rural China is an “acquaintance” society based on a “poor order pattern,” which can be divided into special trust and general trust according to the degree of closeness of interpersonal relationships [33]. Special trust refers to the degree of farmers’ trust in informal institutional subjects, which is based on kinship and geo-relationship, and can occur in groups with frequent interactions and close relationships, manifesting as the trust relationship established between farmers and their friends and relatives. General trust refers to the degree of farmers’ trust in formal institutional subjects, which can arise in groups with different socio-economic characteristics, manifesting as farmers’ trust in village collectives, government departments, and national policies. In homestead inventory, the special trust relationship between friends and relatives promotes communication among farmers, enables the rapid dissemination of homestead inventory information through the information interaction mechanism, improves farmers’ acceptance of information resources, and reduces farmers’ information asymmetry. The higher the general trust of farmers in the government, village collectives, and their staff, the more favorable the guarantee mechanism of government departments and the entire play of the informal guarantee role of grassroots cadres, the easier the compensation policy for homestead revitalization will be recognized and trusted by farmers. It will reduce farmers’ worries about unreliable government implementation in homestead revitalization [34], thus improving farmers’ courage to revitalize their homesteads and positively influencing their willingness to participate in homestead revitalization. Based on this, a second research hypothesis is proposed:

Hypothesis 2.

Social trust has a positive effect on farmers’ willingness to revitalize their homesteads.

Social participation is the farmers’ concern for understanding and involvement in collective social affairs and activities, with a strong sense of purpose and organization, which can provide farmers with more social resources and emotional support. Farmers’ social participation is mainly manifested in two aspects: public participation and special participation. Special participation refers to farmers’ concern for and participation in collective public affairs within a small village area. In contrast, public participation refers to farmers’ respect for and participation in social news and affairs beyond the village area. In the work of homestead inventory, the higher the general participation of farmers, the higher the level of their relationship network, the stronger their sense of integration into the collective [35], and the more opportunities they have to communicate with other farmers in the village, the higher their acceptance of new things, and the stronger their willingness to try new things. In addition, social participation can further build social networks, broaden farmers’ access to information, and help them obtain better social resources. The higher the degree of special participation of farmers, the better they understand the policy environment of national development. The more accurately they grasp the reform direction of the homestead system, the more farmers broaden their horizons, improve their awareness of the current situation of rural homestead revitalization, understand the necessity and urgency of revitalizing homestead bases, recognize the role of homestead revitalization in increasing property income, improve the living environment, promote rural industrial development, and overcome their resistance in participating in the process of homestead revitalization [36]; this in turn improves their willingness and participation in ecological, environmental governance. Based on this, the third research hypothesis is proposed:

Hypothesis 3.

Social participation has a positive effect on farmers’ willingness to revitalize their homesteads.

Combined with the above analysis, the theoretical analysis framework for constructing the relationship between social capital and farmers’ willingness to revitalize their homesteads is shown in Figure 1.

3. Data Sources, Variable Selection, and Model Design

3.1. Data Sources and Sample Description

3.1.1. Data Sources

To better reflect the overall situation in Shaanxi Province, one county (district) in each of northern, central, and southern Shaanxi was selected for the study, and three counties (districts) in Yuyang District (Yulin City), Long County (Baoji City), and Zhashui County (Shangluo City) were selected, and random surveys of household heads were conducted in more typical villages in the three counties (districts). The main reasons are as follows: First, considering Long County and Zhashui County for Shaanxi Province, the rural idle residential housing inventory use of pilot counties, and the provincial government policy support, home base inventory work is progressing faster. Second, Yulin City’s economic strength; although Yuyang District is not one of the 12 pilot counties in Shaanxi Province, but its home base inventory work has achieved significant results. The research team conducted field research in Shaanxi Province in August 2022. This research adopts a combination of stratified sampling and random sampling, based on factors such as the status of home base inventory, location conditions, and economic development level. A total of 5–8 villages were selected in each of the three selected counties (districts), and 35–40 farming households were randomly selected in each village. A questionnaire survey was conducted with household heads in the form of one-on-one interviews, and the research questionnaire was completed by the researcher to fully ensure the validity of the questionnaire. The content of the questionnaire includes the personal characteristics, family characteristics, home base ownership status, and social capital characteristics of the survey respondents. A total of 350 questionnaires were distributed; excluding those with wrong information and missing key information, 316 valid questionnaires were returned, with an efficiency rate of 90.29%.

3.1.2. Sample Description

In terms of sample characteristics, among the 316 surveyed farmers, most of them are older, with 33.5% of farmers aged 46–55 and 25.9% of farmers aged 56–65, indicating that there is a problem of rural aging in the surveyed areas. In terms of education level, 55.7% of farmers have elementary school education or less, indicating that the education level in rural areas is generally low. In addition, not many farmers have party membership, accounting for only 8.5%; the majority of households have 4–5 members, accounting for 53.8%; the majority of households have 2–3 members in the labor force, accounting for 70.6%; the majority of households’ main source of income is part-time work (working outside the home during non-agricultural periods), accounting for 44.6%.

3.2. Variable Selection

3.2.1. Explained Variables

The explanatory variable in this study is the willingness of farmers to revitalize their homestead bases. The questionnaire was designed to obtain the willingness of farmers to revitalize their homestead bases by asking “Are you willing to revitalize your homestead bases?” The possible answer is a binary dummy variable with a value of 1 if farmers are willing to revitalize their homesteads and 0 if they are not.

3.2.2. Core Explanatory Variables

Social capital is the core explanatory variable of this study and includes three dimensions: social network, social trust, and social participation. Drawing on the existing literature, the measure of the social network was chosen to measure the strongly connected network by “contact with relatives, neighbors, and families” and the weakly connected network by “contact with village committee staff.” To measure social trust, “trust in friends and relatives” was used to measure special trust, and “trust in village committees and other organizations” and “trust in government policies” were used to measure general trust. For measuring social participation, “participation in meetings of village committees and other organizations” was chosen to measure special participation, and “attention to social affairs and news” was chosen to measure public participation. In this paper, the questions in the questionnaire were assigned a 5-point Likert scale for subjective measurement, with the degree increasing from low to high, in the order of assignments 1–5. Based on the above seven indicators, farm households’ social capital evaluation index system is constructed as shown in

Table 1. Social capital evaluation index system of farm households.

Social Capital	Evaluation Indicators	Assignment
Social Network	Contact with relatives, neighbors, and families	1 = Never 2 = Less often 3 = Fairly 4 = More often 5 = Frequently
	Contact with village committee staff
Social Trust	Trust in friends and relatives	1 = Do not trust at all 2 = Do not trust much 3 = Good 4 = Trust more 5 = Very trusting
	Trust in village committees and other organizations
	Trust in government policies
Social Participation	Participation in meetings of village committees and other organizations	1 = Never 2 = Less often 3 = Fairly 4 = More often 5 = Frequently
	Attention to social affairs and news

.

3.2.3. Control Variables

To avoid other factors that may influence farmers’ willingness to generate homestead inventory from interfering with the test results, three aspects, including respondents’ characteristics, household characteristics, and farmers’ homestead ownership status, were selected as control variables in this study. In terms of respondents’ characteristics, this paper assumes that respondents’ age, education level, and party membership will impact farmers’ willingness to revitalize their homesteads. Party members play an important pioneering role, and whether or not they are party members affects the responsiveness and support of farmers to the home base revitalization policy. In terms of household characteristics, this paper assumes that the number of household members, the number of household laborers, the primary source of household income, and the annual household income impact farmers’ willingness to inventory their homesteads. In terms of farmers’ homestead status, this paper assumes that the homestead’s area, the homestead, the distance of the homestead from the local county, and the degree of knowledge of the homestead inventory policy impact farmers’ willingness to inventory their homestead. The specific meaning of each variable and the results of descriptive statistical analysis are shown in

Table 2. Specific meaning of variables and results of descriptive statistical analysis.

Variable Category	Variable Name		Variable Meaning and Assignment	Average Value	Standard Deviation
Explained variables	Farmers’ willingness to revitalize their homesteads		1 = Willing 0 = Not willing	0.550	0.498
Core explanatory variables	Social Network	Contact with relatives, neighbors, and families	1 = Never 2 = Less often 3 = Fairly 4 = More often 5 = Frequently	3.310	1.167
		Contact with village committee staff		3.200	1.165
	Social Trust	Trust in friends and relatives	1 = Do not trust at all 2 = Do not trust much 3 = Good 4 = Trust more 5 = Very trusting	2.890	0.953
		Trust in village committees and other organizations		3.170	0.874
		Trust in government policies		3.300	0.829
	Social Participation	Participation in meetings of village committees and other organizations	1 = Never 2 = Less often 3 = Fairly 4 = More often 5 = Frequently	2.740	1.093
		Attention to social affairs and news		3.040	1.159
Control variables	Personal Characteristics	Age	1 = 35 years old and below 2 = 36–45 years old 3 = 46–55 years old 4 = 56–65 years old 5 = 66 years old and above	3.220	1.120
		Education level	1 = Illiterate 2 = Elementary school 3 = Junior high school 4 = High school or junior college 5 = College and above	2.410	0.996
		Is a member of the party	1 = Yes 0 = No	0.090	0.280
	Family Characteristics	Number of family members	Number of actual surveyed household size/person	4.710	1.876
		Number of household laborers	Number of actual surveyed household size/person	2.240	0.997
		Arable land area	Actual surveyed arable land area/m2	1.861	2.071
		Main source of household income	1 = Pure agriculture 2 = Part-time (will work outside the home during non-farming periods) 3 = Non-agricultural	2.260	0.753
	Homestead Status	Area of residential land owned	Actual surveyed homestead area owned by farming households/square meter	156.566	84.697
		Vacant rooms number	The number of vacant rooms/room in the actual surveyed farmers’ homesteads	1.160	1.658
		Distance from local county town	Distance of the actual surveyed farmers’ homesteads from the local county town/km	4.747	3.320
		Understanding of home base revitalization policy	1 = Never heard of it 2 = Have heard of it 3 = Know a little about it 4 = Basically know about it 5 = Know a lot about it	2.600	1.118

.

3.3. Model Design

3.3.1. Binary Logistic Model

In this paper, farmers’ homestead exit behavior is measured based on whether farmers are willing to revitalize their homestead inventory, a typical dichotomous discrete variable. In this regard, the logistic regression model was chosen for the empirical analysis, and the specific model is constructed as follows:

$$P=F(\mathrm{y}=1|X_i)=\frac{1}{1+{\mathrm{e}}^{-y}} (i = 1, 2, 3, \dots \dots , \mathrm{n})$$

(1)

In the formula, P is the probability of farmers’ willingness to revitalize their homesteads; Y is farmers’ willingness to revitalize their homesteads and set Y = 1 when farmers are willing to revitalize their homesteads and Y = 0 otherwise; and X_i denotes the i-th explanatory variable that may affect farmers’ willingness to revitalize their homesteads. The explanatory variable y is a linear combination of the explanatory variables X_i, i.e.,:

$$\mathrm{y}={\beta }_0+{\beta }_1{X}_1+{\beta }_2{X}_2+{\beta }_n{X}_n$$

(2)

In the formula, β₀ denotes the intercept term of the regression equation and β₁ denotes the regression coefficient of the i-th explanatory variable. The logistic model obtained by collapsing Equations (1) and (2) is as follows:

$$\ln (\frac{P}{1-P})={\beta }_0+{\beta }_1{X}_1+{\beta }_2{X}_2+{\beta }_n{X}_n+\epsilon$$

(3)

In the formula, ε denotes the random error term.

3.3.2. ISM Model

American professor Warfield first proposed the ISM model as a system analysis method, mainly used to study the hierarchical structure relationship among factors in complex systems [37]. The factors of social capital influencing farmers’ willingness to revitalize their homesteads are independent and affect each other, so the ISM model is chosen to explore the logical relationship between the factors influencing social capital. The analysis process of the ISM model is as follows.

First, the logical relationship among the factors is judged. According to the regression results of the logistic model, it is determined that m factors in social capital affect the willingness of farmers’ homesteads to be revitalized, C₀ is used to denote the willingness of farmers’ homesteads to be revitalized, and C_i (i = 1, 2, ......, m) denotes the factors that affect the willingness of farmers’ homesteads to be revitalized. If any two factors in C₀ and C_i affect each other, there is a logical relationship between the factors.

Second, an adjacency matrix between factors is constructed according to the logical relationship between the factors, and the constituent elements of the adjacency matrix were defined as follows:

$$r_{\mathrm{ij}}=\left\{\begin{array}{l}1, C_i is \mathit{related} \mathit{to} C_j\\ 0, C_i \mathit{is} \mathit{not} \mathit{related} \mathit{to} C_j\end{array}\right.$$

(4)

In the formula, i = 1, 2, ..., m; J = 1, 2, ..., m.

Third, the matrix is calculated. Based on the adjacent matrix, the matrix M is:

$${\mathrm{M}=(\mathrm{R}+\mathrm{I})}^{\mathsf{\lambda }+1}{=(\mathrm{R}+\mathrm{I})}^{\mathsf{\lambda }}\ne {(\mathrm{R}+\mathrm{I})}^{\mathsf{\lambda }-1}\ne \dots \ne {(\mathrm{R}+\mathrm{I})}^2\ne (\mathrm{R}+\mathrm{I})$$

(5)

In the formula, R is the adjacent matrix of the Equation (4) and i is the unit matrix, 2 ≤ λ ≤ m.

Fourth, the hierarchical structure between factors is determined. The determination of the element collection from the highest level to the lowest level is as follows:

$$P\left(C_i\right)=\left\{C_j\right|m_{\mathrm{ij}}=1\}, \mathrm{Q}\left(C_i\right)=\{C_j\left|m_{\mathrm{ij}}=1\right\}$$

(6)

$$L_i=\left\{C_i\right|P\left(C_i\right)\cap Q\left(C_i\right)=\mathrm{P}\left(C_i\right)\}$$

(7)

In the formula, i = 1, 2, ......, m; P (C_i is the reachable set, which denotes the set of elements in the reachable matrix M that are reachable by element C_i and Q (C_i) is the prior set, which denotes the set of elements in the reachable matrix M that will reach element C_i.

After determining the set of factors L₁ at the highest level according to Equation (7), the factors contained in the other levels are determined from high to low. To determine the set of elements at other levels, the corresponding rows and columns in the L₁ layer of the original reachable matrix M are deleted to obtain the new matrix M1, the corresponding rows and columns are similarly deleted for the new matrix M1 to obtain the factors located in the second layer L₂, and so on for all levels of factors. Finally, according to the hierarchical relationship, by connecting the factors between adjacent levels and at the same level with directed edges, we can obtain the correlation relationship and hierarchical structure among the factors influencing social capital’s willingness to revitalize farmers’ homesteads.

4. Empirical Results and Analysis

4.1. Reliability and Validity Tests

To ensure the reliability of the questionnaire data results, a reliability test of the internal consistency of the questionnaire is necessary. SPSS 27.0 was selected to conduct the reliability test, and Cronbach coefficient values of 0.882 for the social network dimension, 0.795 for the social trust dimension, and 0.775 for the social participation dimension were obtained, indicating good reliability of the questionnaire. For testing the validity of the questionnaire, the KMO value and Bartlett’s test were chosen; the KMO value was obtained as 0.932, and Bartlett’s spherical test value was 1441.568 with a significance level <0.001, indicating good structural validity of the questionnaire. The overall reliability and validity of the questionnaire are good and can be subjected to regression analysis [38].

4.2. Results of Logistic Regression Analysis of Farmers’ Willingness to Revitalize Their Homesteads

4.2.1. Factors Influencing Different Dimensions of Social Capital on Farmers’ Willingness to Revitalize Their Homesteads

First, the econometric analysis software Stata17.0 was selected to perform the White test and variance inflation factor (VIF) test on the model. The results showed that the model did not have heteroskedasticity and multicollinearity problems. Then, logistic regression analysis was conducted to explore the effects of different dimensions of social capital on farmers’ willingness to revitalize their homesteads. Among them, model (1) contains social network variables and individual characteristics, household characteristics, and house base status variables; model (2) contains social trust variables and individual characteristics, household characteristics, and house base status variables; model (3) contains social participation variables and individual characteristics, household characteristics, and house base status variables, and model (4) contains all variables. The optimization of the model uses the Backward LR method in regression; that is, first let all variables into the regression equation to get model (4) and filter out all significant variables according to the backward stepwise regression method to get the final estimation results of model (5). The specific regression results are shown in

Table 3. Regression results analysis of the effect of social capital on farmers’ willingness to revitalize their homesteads.

Variable Name	Model 1		Model 2		Model 3		Model 4		Model 5
	Coefficient	Standard Deviation	Coefficient	Standard Deviation	Coefficient	Standard Deviation	Coefficient	Standard Deviation	Coefficient	Standard Deviation
Contact with relatives, neighbors, and families	1.784 ***	0.425					1.232 **	0.498	1.189 ***	0.422
Contact with village committee staff	2.255 ***	0.471					1.111 **	0.550	1.257 ***	0.476
Trust in friends and relatives			1.793 *	0.400			1.177 **	0.564	1.284 ***	0.396
Trust in village committees and other organizations			2.062 ***	0.436			1.182 **	0.582	0.881 **	0.374
Trust in government policies			2.441 ***	0.622			1.652 **	0.769
Participation in meetings of village committees and other organizations					1.630 ***	0.318	0.948 **	0.431	0.513 *	0.288
Attention to social affairs and news					1.684 ***	0.313	−0.368	0.499
Age	−0.011	0.269	0.311	0.240	0.497 **	0.238	0.173	0.313
Education level	0.020	0.302	0.388	0.272	0.387	0.261	0.400	0.370
Is a member of the party	0.831	1.245	0.454	1.156	0.199	1.246	1.604	1.449
Number of family members	0.114	0.188	0.114	0.169	−0.165	0.158	0.127	0.225
Number of household laborers	−0.117	0.382	−0.241	0.336	0.010	0.320	−0.577	0.508
Arable land area	0.181	0.191	−0.086	0.142	0.163	0.154	0.095	0.221
Main source of household income	−0.678	0.422	0.219	0.352	−0.008	0.343	−0.258	0.518
Area of residential land owned	0.002	0.004	0.001	0.003	−0.002	0.003	0.000	0.004
Vacant rooms Number	0.272 *	0.149	0.567 ***	0.174	0.358 **	0.152	0.408 **	0.193	0.345 **	0.156
Distance from local county town	0.122	0.095	0.159 *	0.087	0.220 **	0.088	0.225 *	0.119	0.203 ***	0.077
Understanding of home base revitalization policy	1.125 ***	0.313	0.773 **	0.255	0.974 ***	0.252	1.252 ***	0.415	0.981 ***	0.215
Constant term	−15.427 ***	2.759	−24.879 ***	3.690	−14.909 ***	2.336	−26.047 ***	4.901	−18.980 ***	2.429
Log likelihood	−58.151		−64.222		−72.884		−43.037		−49.69
Prob > chi2	0.000		0.000		0.000		0.000		0.000
Pseudo R2	0.732		0.704		0.664		0.802		0.771
LR chi2	318.10		305.96		288.64		348.33		74.95

Note: *, **, *** indicate significance at the 10%, 5% and 1% statistical levels, respectively.

.

Social network and farmers’ willingness to revitalize their homesteads. The empirical results from model (1), model (4), and model (5) show that both indicators of the social network have a significant effect on farmers’ willingness to revitalize their homesteads.

4.2.2. Effect of Control Variables

The willingness of farmers to revitalize their homesteads is not only influenced by social capital; this paper finds through empirical analysis that the number of idle rooms, the distance from the county town, and the degree of knowledge of the homestead revitalization policy also have some influence on farmers’ willingness to revitalize their homesteads. From the empirical results of model (5), it can be seen that the number of unused rooms has a positive effect at the 5% significant level; a higher number of unused rooms indicates that a farmer’s existing living standard is more prosperous, the less they value the residential function of the homestead, the more they prefer to use the property function of the homestead, and the higher their willingness to revitalize the homestead. The distance from the local county town has a positive effect at a 1% significant level; the closer the village is to the county town, the higher the value of the homestead base. The idle homestead base can be used to develop suburban tourism, bed and breakfast, and farm carnival industries, so the shorter the distance from the county town, the lower the willingness of farmers to inventory. The degree of understanding of the homestead inventory policy has a positive effect at the 1% significant level. Farmers can clearly understand the benefits brought by the inventory through the homestead inventory policy, thus helping to increase their willingness to inventory their homestead.

4.3. Results of ISM Analysis of Farmers’ Willingness to Revitalize Their Homesteads

According to the estimation results of the previous logistic regression model, the factors that have a significant influence on farmers’ willingness to revitalize their homesteads are selected, using C₁ to represent the walk with relatives and neighbors among families, C₂ to represent the walk with village committee staff, C₃ to represent the degree of trust in friends and relatives, C₄ to represent the degree of trust in organizations such as village committees, C₅ to represent the participation in meetings of organizations such as village committees, C₆ to represent the number of vacant rooms, C₇ to represent the distance from the local county, and C₈ to represent the degree of understanding of the policy on homestead revitalization.

The relationship between the screened significant factors was judged based on the currently available studies. First, the more visits with relatives and neighbors and village council staff, the more policy information is obtained from other sources [39], so C₁₈ and C₂₈ take the value of 1. Second, the higher the level of social trust, the stronger the tightness of ties among farmers [40], the stronger the sense of dependence on friends and relatives, and the easier it is to learn more about the policies related to homestead inventory through social network members, so C₃₁ and C₃₈ take the value of 1. Again, the higher the level of farmers’ trust in organizations such as village committees, the more willing they are to participate in relevant meetings organized by village committees, the smoother the promotion of the house base revitalization policy will be, and the more information farmers are willing to learn, so C₄₂, C₄₅, and C₄₈ take the value of 1. In addition, the more farmers attend meetings organized by village committees and other organizations, the more they know about the process of inventory work and related policies, so C₅₈ takes the value of 1. Finally, the shorter the distance from the county, the higher the property value of the homestead, and the more the farmer can rent out the vacant house or conduct commercial operations, so C₇₆ takes the value of 1. Combining the above analysis, the adjacency matrix C established is:

$$C=\left|\begin{array}{cccccccc}1& 0& 0& 0& 0& 0& 0& 1\\ 0& 1& 0& 0& 0& 0& 0& 1\\ 1& 0& 1& 0& 0& 0& 0& 1\\ 0& 1& 0& 1& 1& 0& 0& 1\\ 0& 0& 0& 0& 1& 0& 0& 1\\ 0& 0& 0& 0& 0& 1& 0& 0\\ 0& 0& 0& 0& 0& 1& 1& 0\\ 0& 0& 0& 0& 0& 0& 0& 1\end{array}\right|$$

Based on the adjacency matrix C, the reachable matrix M is calculated using Matlab 2022 as:

$$M=\left|\begin{array}{cccccccc}1& 0& 0& 0& 0& 0& 0& 1\\ 0& 1& 0& 0& 0& 0& 0& 1\\ 1& 0& 1& 0& 0& 0& 0& 1\\ 0& 1& 0& 1& 1& 0& 0& 1\\ 0& 0& 0& 0& 1& 0& 0& 1\\ 0& 0& 0& 0& 0& 1& 0& 0\\ 0& 0& 0& 0& 0& 1& 1& 0\\ 0& 0& 0& 0& 0& 0& 0& 1\end{array}\right|$$

According to the reachable matrix M, the hierarchy among the factors is determined, and finally it can be divided into three layers. The stratification matrix L is calculated as follows:

$$L=\left|\begin{array}{cccccccc}6& 8& 0& 0& 0& 0& 0& 0\\ 1& 2& 5& 7& 0& 0& 0& 0\\ 3& 4& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\end{array}\right|$$

From the stratification matrix L, it can be seen that among the influencing factors of farmers’ willingness to inventory their homesteads, the surface factors of homestead inventory policy understanding and the number of vacant rooms directly drive farmers’ willingness to inventory their homesteads. At the same time, the direct surface factors are also influenced by the middle indirect factors of the social network, social participation (participation in organizational meetings such as village committees), and distance from the local county. In addition, the profound root factor of social trust influences both surface and middle factors. As shown in the hierarchy diagram created in Figure 2 based on the stratification among factors, two paths of occurrence influence the willingness of farmers to inventory their homesteads: The first possible path is that the degree of trust in relatives and friends and the degree of trust in organizations such as village committees as deep influencing factors in social trust can have a direct impact on the walk with relatives and neighbors among families, the walk with village committee staff, and the participation in meetings of village committees and other organizations respectively, which in turn affects farmers’ understanding of the policy of homestead inventory and ultimately affects farmers’ willingness to inventory homesteads. Another possible pathway is that the distance from the local county town can directly affect the number of vacant rooms, which ultimately impacts farmers’ willingness to inventory their homesteads.

5. Discussion

Using research data from 316 farm households in Shaanxi Province, this paper empirically analyzes the impact of social capital on farm households’ willingness to revitalize their homesteads using the logistic model and ISM model, and the main findings obtained are as follows: First, there is a significant relationship between social capital and farmers’ willingness to revitalize their homestead bases, and social networks measured by the mobility among families with relatives and neighbors in the village and mobility with village committee staff have a significant positive effect on farmers’ willingness to revitalize their homestead bases. This result is consistent with the findings of Chen Xia et al. [41]. Second, there are differences in the influence of three different dimensions of social capital on farmers’ willingness to revitalize their homestead bases, among which the social network, the interaction with relatives, neighbors and families, the interaction with village committee staff, and the participation in meetings of village committees and other organizations in social participation affect farmers’ willingness to revitalize their homestead bases as the middle-level reasons. In contrast, the degree of trust in friends and relatives and the degree of trust in village committees and other organizations in the social trust are the deep-level reasons affecting farmers’ willingness to revitalize their homestead bases. This indicates that social trust helps to enhance farmers’ trust in the work of the village committee, and also facilitates communication among farmers, i.e., social trust has a positive impact on social networks and social participation, and under the effect of herd mentality, farmers will actively refer to the relevant evaluations and attitudes of village cadres, friends, and relatives when they make decisions on homestead inventory, which will influence farmers’ willingness to inventory their homesteads.

In the process of homestead revitalization, when farmers seek material or spiritual support, they can use social capital to obtain corresponding resources. Many scholars have studied farmers’ willingness to participate in the economy and their behavior in China, and found that social capital is a factor that cannot be ignored [42]. There have been relevant studies on the willingness to finance the mortgage of homestead use rights [43] and farm household income [44] from the perspective of social capital, but few scholars have studied the combination of social capital and homestead inventory. The revitalization of residential land is crucial for farmers, and their willingness to revitalize is also influenced by social capital factors to be further verified. As a complement to the existing research, this paper introduces social capital theory into the study of farmers’ willingness to revitalize their homesteads, analyzes the factors influencing farmers’ willingness to revitalize their homesteads in depth under social capital theory, and sorts out the hierarchical relationships among the influencing factors. This has, to some extent, innovated the research perspective and enriched the research content of homestead. Of course, there are some limitations to this paper. On the one hand, this paper uses cross-sectional data from a survey of farm households in Shaanxi Province, which does not allow an in-depth analysis of the dynamic change process of farm households’ willingness to revitalize their homesteads. On the other hand, due to the different economic and social conditions in different regions, the means and effectiveness of homestead revitalization varies, which may also lead to significant differences in farmers’ willingness to revitalize, and the extension of the findings requires further expansion of the study area to support the contextualized characteristics of the theory. However, this also provides a direction for future comparative studies.

6. Conclusions and Policy Recommendations

Using field research data from 316 farmers in Shaanxi Province, this paper empirically analyzed the impact of social capital on farmers’ willingness to revitalize their homesteads and obtained the following conclusions: First, both social capital and its component dimensions (social network, social trust, and social participation) have significant positive effects on farmers’ willingness to revitalize their homesteads. Among them, social trust as the deepest reason and social network and social participation as the middle reasons affect farmers’ willingness to revitalize their homestead bases. Second, among the control variables, the degree of knowledge of the homestead inventory policy, the number of vacant rooms, and the distance from the local county significantly positively affect farmers’ willingness to inventory their homesteads.

Based on the above findings, the following policy recommendations are put forward: The level of social capital of farmers should be further enhanced to better play an active role in the revitalization of farmers’ homesteads. First, group activities should be actively organized and carried out for villagers, communication between farmers and village committee staff should be strengthened, and the formation of a good culture of solidarity and mutual assistance should be promoted to give full play to the role of social networks in promoting farmers’ willingness to revitalize their homesteads. Second, to enhance the quality of village cadres and improve their work style, the process of work should be oriented to the service needs of farmers, helping farmers solve practical problems to “win the trust of the people” and enhance the recognition and trust of farmers to village cadres and village committees, and give full play to the critical role of social trust on the willingness of farmers to revitalize their residential bases. Third, the village collective should implement sunshine village affairs, actively promote the construction of democracy, organize meetings of villagers’ representatives to decide on matters related to the decision of revitalization of residential bases, listen to the views and suggestions of the masses so that villagers actively participate in the work of residential bases revitalization, and give full play to the role of social participation in promoting the willingness of farmers to revitalize their residential bases. Fourthly, publicity activities should be carried out related to the work of residential bases to popularize the knowledge of laws and regulations and relevant policies to farmers, improve their awareness of the work of residential base revitalization, and promote the generation of farmers’ willingness to revitalize residential bases. Fifthly, diversified and multi-combination policies for the revitalization of residential bases should be implemented. In view of the level of economic development in different areas, location conditions, and real preferences of farmers in different areas, the differentiated arrangement of the policy of revitalization of residential bases of different farmers in the same area should be realized, and different standards and ways of compensation for revitalization of residential bases should be implemented.