Influence of Household Endowment on Rural Household Sewage Treatment: The Moderating Effect of Village Cadre Credibility

Abstract

Strengthening rural domestic sewage treatment has practical significance for the rural living environment. Based on household survey data from Liaoning Province, China, this paper explores the effects of household endowment and village head credibility on the use of clean sewage treatment methods. Our results indicate that there is a positive correlation between household endowment and the use of clean sewage treatment methods. The credibility of village cadres plays a positive moderating role in the influence of household endowment on the behavior of households using clean sewage treatment methods. The age and non-agricultural work experience of the respondents are also correlated with the use of clean sewage treatment methods in rural households, but the specific effects are different in each dimension of household endowment. This article proposes policy recommendations such as considering the endowment level of rural households, emphasizing the cultivation of trust capital for village cadres, and increasing environmental education.

Keywords

rural environment village cadre credibility domestic sewage environmental awareness household endowment

Introduction

As China’s economy has developed and living conditions in rural areas have improved, the amount of rural domestic wastewater discharge has increased dramatically, posing a serious threat to ecological balance in rural areas (Mu et al., 2023). According to a survey by the Ministry of Ecology and Environment of China, rural wastewater accounted for 40% of the total wastewater in China in 2020 (Jin, 2021). In fact, only 25% to 30% of rural domestic sewage in China has been effectively treated, and only a few villages have sewage discharge pipelines or sewage treatment facilities (Y. Xu et al., 2022). The reasons behind this phenomenon are complex and varied, including but not limited to the fact that villagers lack sufficient awareness of the environmental and health risks associated with the indiscriminate discharge of wastewater, leading them to ignore the importance of wastewater treatment in their daily lives (Tang et al., 2023). Additionally, due to economic constraints, some households may not be able to afford the cost of constructing and maintaining sewage treatment facilities, meaning that even if they are aware of the necessity of sewage treatment, they find it difficult to put it into practice (Werkneh & Gebru, 2023; Werkneh, 2024). In addition, the lack of effective environmental education in rural areas has created barriers to the promotion and application of clean treatment technologies (Huang et al., 2023). Rural residents usually discharge domestic sewage directly into nearby rivers and lakes, which negatively affects the environment and human health and restricts sustainable rural development (Berendes et al., 2017; Duong et al., 2014; Oyekale, 2013). Therefore, rural domestic wastewater treatment has become an urgent problem.

To improve the rural environment, water quality and the quality of life of rural residents, the Chinese government has taken direct measures such as establishing sewage treatment stations and formulating village rules and regulations (Ai et al., 2020; Bo & Wen, 2022; Qi-yu et al., 2021). However, some scholars argue that the lack of environmental awareness among villagers has led to slow progress in domestic wastewater treatment projects. Therefore, increasing the effective participation of rural residents in wastewater treatment is key to the success of rural wastewater treatment projects (Ding et al., 2021). At present, rural domestic sewage treatment still faces problems such as insufficient investment in environmental protection infrastructure, imperfect management and protection mechanisms, imperfect participation methods for farmers, and low levels of rural domestic sewage treatment (Y. Li & Song, 2020; Song et al., 2020). To solve environmental problems, farmers' participation is necessary (R. Zhang et al., 2020).

Numerous studies have been conducted on how to involve villagers in rural wastewater treatment. Resource endowment plays a crucial role in farmers’ decisions (J. Liu & Zhou et al., 2024; Xie et al., 2021; Xiang & Lu, 2023; X. Xu et al., 2023; R. Zhang et al., 2020), as farmers’ participation in treatment programs mainly depends on their household capital stock (Mendola, 2008). Farmers’ household endowment, that is, all the resources and capabilities that the whole household possesses, includes three major categories: economic, social, and human capital endowment. Economic capital refers to the household’s income and wealth; social capital involves the social network and mutual cooperation within the community; and human capital includes their level of education, health, and professional skills (Yu et al., 2023).

In addition, village cadres are an important part of village governance and have a great impact on village development. Trust is the foundation of cooperation, and the credibility of village cadres is a manifestation of political trust (Chanley et al., 2000; Job, 2005). Studies have found that a close relationship between village cadres and the people they govern significantly enhances disciplinary monitoring and transmits internalization effects, and that grassroots leaders who have gained the political trust of farmers are more likely to organize and mobilize villagers to participate in village public affairs (Hao et al., 2022; Xue et al., 2021; M. Zhang et al., 2023).

Although sewage treatment is a topic of scholarly interest, little attention has been paid to the relationship between household endowments and household sewage treatment methods. Most of the existing studies explore the influencing factors of farmers’ participation in domestic sewage treatment, but there is room for further expansion in the following two areas. First, although some scholars have explored the impacts of farmers’ participation in rural human settlements governance, such as domestic sewage treatment or domestic waste treatment, from the perspectives of economic capital, human capital, social networks or environmental awareness alone, scholars have not integrated these dimensions into the same household endowment research framework. Second, few studies have considered the possible moderating role of village cadre credibility between the two. In addition, few studies have considered both household endowment and village cadre credibility. Accordingly, this study intends to explore the following questions: How do household endowments affect rural residents’ behavior and decision-making regarding wastewater treatment? What is the role of village cadre credibility? Does the effect of household endowment on rural households’ domestic wastewater treatment vary by age and region?

Our research makes three key contributions to the study of rural domestic sewage treatment. First, this paper uses field survey data to measure rural household endowments and study the impact of these endowments on the choice of clean sewage treatment methods, providing a new perspective for understanding the relationship between household endowments and sewage treatment decisions. Second, this paper explores the moderating role of village cadres’ credibility, providing new empirical evidence for understanding the relationship between household endowments and farmers’ use of clean sewage treatment methods. Third, the paper discusses the effects of heterogeneity on different age groups and amounts of non-agricultural work experience, as well as at different regional levels. These factors contribute to the implementation of rural domestic wastewater treatment policies across households. This study investigates the relationship between farm household endowments and sewage treatment practices and further explores the role of village cadre credibility in this context. In order to explain the relationship between village cadre credibility and farmers’ domestic sewage treatment decisions, this study also analyzes the moderating effect involved. Through empirical analysis, this study reveals the ways that household endowment influences clean rural domestic sewage treatment, and provides a scientific basis for the formulation of rural sewage treatment policies that promote the adoption and application of clean sewage treatment technologies by increasing household endowment.

Theoretical Framework and Hypotheses

Farmers’ participation in the treatment of domestic sewage is a complex decision-making process, which is not solely based on individual preferences and experiences. As an embedded resource that includes economic, social, and human capital, household endowment plays a role in farmers’ choice of domestic sewage treatment.

Relationship Between Household Endowment and Domestic Wastewater Treatment Behavior of Farm Households

Farm households’ participation in the construction and management of clean sewage treatment facilities is influenced by many factors. This study examines the impact of household endowment on clean rural sewage treatment based on economic, social, and human capital. Resource endowment theory assumes that the resource holdings of an individual or household affect their behavior and decision-making. In this hypothesis, economic capital is viewed as the financial and physical resources available to households to invest in clean sewage treatment facilities. Specifically, households with higher economic capital are more likely to invest in clean wastewater treatment technologies because they are able to afford the associated costs and expect long-term gains in their quality of life (Ju et al., 2022). Previous studies have shown that capital investment is the prerequisite for farmers to manage domestic sewage treatment facilities (Shan et al., 2021). Therefore, when deciding whether to use clean sewage treatment methods, farmers consider the financial cost of constructing and maintaining clean sewage facilities. As household income increases, residents have higher expectations for their living environment, and will pay more attention to the issue of domestic sewage pollution and regulate their own domestic sewage behavior. Farmers with greater economic capital are more likely to invest in wastewater treatment facilities, thereby improving the efficiency and quality of domestic wastewater treatment.

Social capital theory emphasizes the important role of social networks and community participation in promoting clean wastewater practices, and increasing the effective participation of rural residents is key to rural wastewater treatment (Ding et al., 2021). Social capital is a network of relationships embedded in individuals, as well as a productive resource that can facilitate individual behaviors (Coleman, 1990). Anderson and Schirmer (2015) found that social capital promotes public participation in low-carbon actions. Putnam (1993) believed that social capital influences farmers’ behavior through social trust, norms, and relationship networks, thereby increasing farmers’ demand for and adoption of clean sewage treatment methods. Rural China is a typical “acquaintance society” that is linked by blood and kinship (Du et al., 2016). Sewage treatment facilities are public goods, and the soft coercive mechanism formed by the trust and reputation established in informal relationship networks reduces farmers’“free rider” mentality (Putnam, 1993). As a result, community members living within the same sphere of influence form a community of interest for mutual benefit and cooperation. In communities with strong social capital, farmers are able to share resources and knowledge more effectively by cooperating with each other and exchanging information to promote the implementation and maintenance of clean wastewater treatment technologies (R. Zhang et al., 2020).

Human capital theory, on the other hand, focuses on the impact of education and health on improving farmers’ awareness and ability to use wastewater treatment technologies (J. Liu & Zhou et al., 2024). Human capital development requires health, education, and professional training and improves the economic capacity of families or individuals (Mihalache, 2019). Rural households with higher per capita education more fully recognize the importance of regulating sewage discharge behavior, and have a more comprehensive understanding of sewage treatment policies, so they are more inclined to use clean sewage treatment methods. Mushkin (1962) emphasized that health is an important component of human capital formation. Increasing human capital in rural households helps ensure a better family economic situation, giving these families more funds to invest in sewage construction. Increased education levels enable rural households to better understand the importance of wastewater treatment and related policies, while good health allows farmers to participate in wastewater treatment practices. Thus, increased human capital helps farmers to adopt and maintain clean sewage treatment practices more effectively.

In summary, the three dimensions of household endowment: economic capital, social capital, and human capital, complement each other and contribute to the cleaner treatment of rural domestic wastewater. That is, increased household endowment contributes to the likelihood of rural households adopting clean sewage treatment methods. As a result, the following research hypotheses have been formulated:

Hypothesis 1: Household endowment positively influences the use of clean sewage treatment methods in rural households.

Moderating Effect: Indirect Impact of Village Cadre Credibility

Previous studies have confirmed that farmers’ resource endowment has a positive impact on their behavior (Y. Cheng et al., 2022), but these studies lack an in-depth exploration of the relationship between the two. According to the trust-cooperation theory, cooperation is more stable when farmers’ trust in the government is high, which suggests that good relations between the cadres can not only encourage farmers’ participation, but also lead to a better understanding and awareness of the institutional rules, thus increasing their willingness to participate in rural governance (Cao et al., 2020; Kumar & Saha, 2017). G. R. Yang et al. (2023) noted that places with low levels of trust are prone to policy target group mismatch. Village cadres play a crucial role in managing village affairs and assisting the government in performing its official duties; they are not only agents of the government but also stewards of farmers (Wu, 2002). Existing studies have shown that village cadre credibility increases the level of trust that farmers have in village cadres and that this trust is an important factor in promoting collective action (J. Liu et al., 2022). The better the relationship between villagers and village cadres, the higher the frequency of socialization among them, which increases the frequency of supervision issued by village cadres and the normative pressure released by them, strengthening the role of the village cadre (Hao et al., 2022; Ju et al., 2022). Greater affective trust between village cadres and the villagers that they lead may make those villagers more willing to comply with and cooperate with the cadres, reducing the likelihood of discharging domestic sewage indiscriminately (R. Zhang et al., 2020). Therefore, this paper proposes the following research hypothesis:

Hypothesis 2: Village cadre credibility plays a moderating role in the effect of household endowment on rural domestic wastewater treatment.

The theoretical analysis framework of this paper is shown in Figure 1.

Figure 1.

Theoretical analysis framework.

Materials and Methods

Data

The data in this paper come from the 2022 Liaoning Rural Revitalization Tracking Survey (LRVLS), a large-scale sample survey of farm households organized and implemented by the School of Economics and Management of Shenyang Agricultural University in Liaoning Province. Rural areas in Liaoning Province include different geographic regions such as the coast, central plains, eastern mountains, and hilly and mountainous areas in northwestern Liaoning, and the level of economic development, climatic conditions, and living habits in these regions vary significantly, affecting the construction and operation of wastewater treatment facilities and leading to different needs and practices of domestic wastewater treatment. Therefore, this paper researches rural residents in Liaoning Province to explore the impact of household endowment on rural domestic wastewater treatment.

Before conducting the formal survey, a pre-survey was conducted to test the reliability and validity of the questionnaire and necessary adjustments were made to the questionnaire based on the results of the pilot survey. The formal survey was conducted using a stratified random sampling method—Probability Proportional Sampling (PPS) study. Sampling followed standard practices. The specific process is as follows: (a) Determine the sample counties (districts and cities). The counties were then categorized into three categories of high, medium, and low based on their 2020 GDP per capita. Four counties were randomly selected from each category. (b) The same stratified random sampling method was then used to identify three sample towns in each sample county, totaling 36 towns. (c) Using the random sampling method, 106 villages were selected from the sample townships. (d) 1,164 households were randomly selected from the 106 villages.

After excluding inconsistencies and questionnaires with missing data, a total of 106 village questionnaires and 1,081 farm household questionnaires were obtained, of which the efficiency of the village questionnaires was 100% and the farm household questionnaires was 92.9%. Questions directly related to this study are added as supplementary material in the Appendix section (see Appendix: Questionnaire). The village questionnaire collected data on infrastructure and sanitation rules, while the household questionnaire focused on household size, household income and living conditions, as well as the characteristics and demographics of the respondents. There may be significant differences in socio-economic characteristics such as income level, employment status and family structure among different age groups, which may influence their access to rural domestic wastewater treatment technologies and resources. Therefore, drawing on Sayujya and Navyashree’s (2021) study, we categorized the participants into the following age groups: 30 years old and below, 31 to 40 years, 41 to 50 years, 51 to 60 years, and 60 years old and above. Such a division helps us to analyze the differences in domestic wastewater treatment technology adoption among different age groups.

Variable Selection

Dependent variable: The dependent variable is the sewage treatment method of rural households, and the questionnaire question is “How is your household’s domestic sewage treated?” Options were scored as 1 = discharge into the public sewer network; 2 = discharge into their own sewage treatment facilities; 3 = discharge anywhere and seep into the ground; 4 = discharge anywhere, and flow into lakes and other water bodies; 5 = dump into fields or feed livestock; 6 = other. Option 6 was manually identified and determined by the researcher based on the respondents’ answers. The purpose of this study is to assess the impact of household endowment on the adoption of environmentally-friendly technologies. Based on this, this article divides sewage treatment methods into two categories: clean and non-clean. The clean sewage treatment methods, which include discharge into the public sewer network and discharge into their own sewage treatment facilities, are assigned a value of 1. The rest are considered non-clean sewage treatment methods and assigned a value of 0.

Independent variables: Kahl (1954) gave a detailed definition of household endowment, stating that family endowment includes various natural and acquired resources and abilities owned by family members and the family as a whole. This paper divides household endowment into three categories: economic, social, and human capital endowment, according to Piroddi’s research (2021).

(1) Economic capital refers to material wealth. This has a direct impact on the ability of households to invest in clean sewage treatment technologies and facilities. Households with more economic capital are more capable of purchasing and maintaining wastewater treatment equipment and thus treating domestic wastewater more efficiently (Ju et al., 2022). Drawing on Yu et al.’s (2023) study, we use annual household income as a proxy indicator of economic capital. This indicator is widely recognized as a direct and valid way of capturing the economic status of a household. Since data on annual household income often span several orders of magnitude, ranging from a few thousand to millions, taking logarithms can help to narrow down and focus the data, making it easier to analyze and interpret. For this reason, this paper uses the logarithm of annual household income to measure household economic capital.

(2) Social capital refers to the resources obtained by family members as members of an organization and involves social networks and mutual cooperation within the organization. Strong social capital improves the efficiency of wastewater treatment by organizing and mobilizing community members to participate in the construction and maintenance of wastewater treatment projects (Ding et al., 2021). Community participation and cooperation facilitates the sharing of knowledge and technology and increases awareness of the importance of wastewater treatment. Drawing on R. Zhang et al. (2020) and Yu et al. (2023), we selected the presence of village cadres in rural households and the number of people members of the household can borrow money from when in urgent need to calculate average social capital.

(3) Human capital includes education and health, factors that influence an individual’s knowledge and ability to operate clean sewage treatment technologies. Farmers with higher levels of education are more likely to understand the importance of wastewater treatment and be more willing to adopt effective wastewater treatment methods (J. Liu & Zhou et al., 2024). In addition, good health also contributes to farmers’ participation in wastewater treatment-related labor and maintenance. Drawing on the studies of Eftimoski (2022) and X. Xu et al. (2023), this paper uses two factors, per capita educational attainment of household members and average health status, to measure human capital, and derives a human capital score by calculating the average of the two.

Control variables: According to existing studies, differences in individual, household, and village characteristics of behavioral subjects may have an impact on participation in domestic sewage treatment (Chen, 2018; Z. Liu, 2015; Su et al., 2022).

Individual characteristics include gender, age, marital status, whether the respondent is a party member, and whether he or she is engaged in non-agricultural work. Age is an important factor affecting farmers’ participation in domestic sewage treatment (Lam et al., 2015). Individuals lose strength as they age, and their living habits tend to stabilize, which is not conducive to participating in domestic sewage treatment. Meanwhile, existing literature also confirms that non-agricultural work has a positive impact on the participation of farmers in rural domestic sewage treatment (Ju et al., 2022). Rural residents engaged in non-agricultural work are usually more willing to accept new knowledge and technologies.

Household characteristics include household size, if the family is poor, the source of domestic water, and whether the road leading to the household is accessible by car. Existing literature has shown that family size is an important factor affecting behavior (D. Zhang et al., 2020). A number of studies also reveal that the source of domestic water is an important factor (Tan et al., 2011), because it is a representation of farmers’ current water resource utilization, which has a direct impact on their behavior. Sewage treatment infrastructure accessibility has been found to be an important factor influencing rural household sewage treatment behavior (C. Zhang et al., 2023). The main difficulty with rural wastewater treatment is the slow construction of wastewater treatment facilities and the low throughput of the facilities. Road accessibility directly affects the ease with which households can use these facilities, which influences their choice of sewage treatment (Hidalgo et al., 2018).

Village characteristics include the availability of domestic sewage treatment projects, the availability of public sewage networks, and the existence of village rules and regulations on sanitation. The availability of sewage services at the village level is an important factor influencing household sewage treatment choices, and the implementation of sewage treatment projects can help to effectively manage sewage discharge patterns across broad areas (Estévez Rivadulla et al., 2022; Wei et al., 2020). Specifically, the availability of domestic sewage treatment projects in villages significantly influences the likelihood of households adopting cleaner treatment options (Bo & Wen, 2022). In addition, the ability of households to connect to the public sewage network has been confirmed by several studies as a key factor for clean treatment practices (Huang et al., 2021; Sood et al., 2023). Relevant studies have also shown that village rules and regulations give farmers a sense of collective responsibility and ownership (F. Yang et al., 2020).

Moderating variable: The credibility of village cadres is measured by a rating from the survey participants. Previous studies have shown that a good relationship between village cadres and farmers promotes farmers’ participation in local village affairs (Cao et al., 2020).

Definitions of variables and descriptive statistics are shown in Table 1. It can be seen from the statistics that 48.7% of the sample was male and 51.3% was female, with the ratio of men to women being close to the same proportion, implying that the research is a representative gender distribution. Most respondents were middle-aged, which reflects the phenomenon of young people leaving rural areas to work. Married people accounted for 84.8% of the sample. Party members accounted for only 15.8% of the sample, while non-party members accounted for 84.2%. Those engaged in non-agricultural work made up 18.1% of the respondents, indicating that the majority of the respondents were not engaged in non-agricultural work. In terms of household characteristics, the mean household size was 2.853 persons, meaning that respondents generally had smaller households. Poor households accounted for 7.1% of the sample, indicating that the majority of respondents' households were economically well off. 63.3% of households used piped water, while the other 36.7% used well water. 93.9% of households had access to a vehicle, but only 15.4% of the villages sampled had sewage treatment programs, while an even smaller 3.3% of villages had public sewage networks. The low penetration of sewage treatment facilities and public sewage networks may be related to the level of local economic development, environmental awareness of the residents, and government investment and planning, meaning that more policy support and financial investment may be needed to improve sewage treatment facilities. 48.1% of villages had sanitation rules and regulations, indicating solid coverage with ample room for improvement. Respondents had high levels of trust in village cadres, giving them a credibility score of 9.085 out of 10.

Table 1.

Summary Statistics.

Variables	Description	Mean	SD	Min	Max
Dependent variable
Clean sewage treatment methods	1 = yes, 0 = no	0.614	0.487	0.000	1.000
Independent variables
Economic capital	annual household income	11.904	0.531	11.262	12.938
Social capital	through calculation	1.165	0.488	0.000	2.000
Human capital	through calculation	4.451	0.821	2.000	7.000
Moderating variable
Credibility of village cadres	Score 0–10	9.085	1.325	1.000	10.000
Individual characteristics
Gender	1 = male, 0 = female	0.487	0.500	0.000	1.000
Age	1 = less than or equal to 30 years old, 2 = 31–40, 3 = 41–50, 4 = 51–60, 5 = more than 60 years old	3.940	1.226	1.000	5.000
Marital status	1 = married, 0 = unmarried	0.848	0.359	0.000	1.000
Party member	1 = yes, 0 = no	0.158	0.365	0.000	1.000
Non-agricultural work	1 = yes, 0 = no	0.181	0.385	0.000	1.000
Household characteristics
Household size	discrete variable (people)	2.853	1.274	1.000	8.000
Poor family	1 = yes, 0 = no	0.071	0.257	0.000	1.000
Domestic water source	1 = tap water, 0 = well water	0.633	0.482	0.000	1.000
Household is accessible by car	1 = yes, 0 = no	0.939	0.240	0.000	1.000
Village characteristics
Domestic sewage treatment projects	1 = yes, 0 = no	0.154	0.362	0.000	1.000
Public sewage pipe network	1 = yes, 0 = no	0.033	0.180	0.000	1.000
Village rules and regulations	1 = yes, 0 = no	0.481	0.500	0.000	1.000

Analysis Model

A Logit Regression was conducted to analyze the impact of household endowment on respondents’ household sewage treatment. The specific model is:

Y_{i} = β_{0} + β_{1} x_{i} + β_{2} C_{i} + ε_{i}

(1)

In Formula (1), $Y_{i}$ is the dependent variable, representing the household sewage treatment method of the respondent. Clean treatment values are assigned a value of 1, while other treatment methods are assigned a value of 0; $x_{i}$ is the core explanatory variable, representing household endowment, specifically divided into household economic, social, and human capital; $β_{1}$ is the coefficient to be evaluated; $C_{i}$ is the control variables and $ε_{i}$ is the random perturbation term.

Results

Regression Analysis

Table 2 reports the marginal effects of the explanatory variables based on the estimated parameters of the Logit model. On the basis of model (1), individual, household and village characteristic are successively added to models (2) to (4), and regional fixed effects are added to model (5).

Table 2.

Baseline Regression Results.

Variables	Clean sewage treatment methods
Variables	(1)	(2)	(3)	(4)	(5)
Economic capital	0.301*** (0.009)	0.209*** (0.015)	0.097** (0.040)	0.087** (0.034)	0.093*** (0.035)
Social capital	0.135*** (0.011)	0.139*** (0.005)	0.092* (0.048)	0.119*** (0.042)	0.107*** (0.039)
Human capital	0.275*** (0.016)	0.237*** (0.012)	0.148** (0.058)	0.122** (0.058)	0.118* (0.062)
Controls	No	Yes	Yes	Yes	Yes
Area fixed effect	No	No	No	No	Yes
Observation	1,081	1,081	1,081	1,081	1,081

Note. Control variables include gender, marital status, whether the participant party member, household size, whether the participant comes from a poor family, domestic water source, household accessibility by car, domestic sewage treatment projects, public sewage pipe network, and village rules and regulations. Column (1) has no control variables, columns (2) through (4) incorporate individual, household, and village characteristics in that order, and column (5) incorporates area fixed effects. Robust standard errors are reported in parentheses.

p < .10, **p < .05, ***p < .01.

As shown in column (5) of Table 2, the marginal coefficient of household economic capital is 0.093, which is statistically significant at the 1% level, indicating that for every 1% change in the economic capital of a rural household, the probability of a farmer using a clean sewage treatment method increases by 9.3 percentage points. This result indicates that increase in household economic capital promotes clean sewage treatment methods by rural households. This is consistent with the findings of Yu et al. (2023). Possible explanations include that farmers with higher income have a clearer understanding of domestic sewage treatment methods (Ye, 2012), since they know that casual discharge of sewage is detrimental to the health of their family members and negatively affects their income, so they prefer to use clean sewage treatment methods. Farmers with higher incomes also have a greater ability to pay for sewage treatment.

The regression coefficient for social capital is positive and statistically significant at the 1% level. These findings suggest that increased social capital encourages rural households to choose clean sewage treatment methods. This is consistent with the findings of Anderson and Schirmer (2015) that social capital promotes public participation in low-carbon initiatives, and that in communities with strong social capital, farm households are able to share resources and knowledge more effectively by cooperating with each other and exchanging information about the implementation and maintenance of clean wastewater treatment technologies (R. Zhang et al., 2020). One possible reason for this is that the construction of clean sewage treatment facilities requires a large amount of material and financial resources, and rural households with close-knit neighborhoods have stronger social networks and are more likely to be able to address the investment required for the construction of clean sewage treatment facilities. At the same time, if there are village cadres among the family members, the family’s network of contacts will be wider, and the information about sewage treatment obtained will be more timely, accurate, and comprehensive. As a result, the probability of using clean sewage treatment methods will be higher.

The marginal coefficient of human capital is 0.118, which is statistically significant at the 10% level, indicating that each 1% change in the accumulation of human capital in rural households increases the probability of farmers using clean sewage treatment methods by 11.8 percentage points. The result of the study suggests that increase in human capital encourages clean sewage treatment among rural households. This is consistent with the studies of Eftimoski (2022) and X. Xu et al. (2023). A possible explanation for this phenomenon is that more educated and physically fit farmers will have more off-farm employment opportunities, and therefore have greater ability to participate in rural domestic sewage treatment. Meanwhile, rural residents with higher human capital have a clearer understanding of things and are more willing to accept new technologies, and therefore, have a broader vision in making decisions about domestic sewage treatment methods. In summary, the three dimensions of H1 household endowment (economic, social, and human capital) have a positive impact on the use of clean sewage treatment methods by rural households.

Endogeneity Treatment

In order to avoid endogeneity problems that can arise from omitted variables and bidirectional causality between household endowments and farmers’ household use of clean sewage treatment, the model also needs to be tested for endogeneity. Drawing on Meng et al. (2024), Godoy et al. (2007), and Pokropek (2016), this study uses the level of mechanization at the village level, the level of social capital of other farmers in the same village, and the level of human capital of other farmers in the same village as instrumental variables for economic, social, and human capital. Table 3 reports the results of the two-stage least squares (2SLS) regression on the effect of household endowment on the use of clean sewage treatment by farmers.

Table 3.

Estimation Results Based on 2SLS.

Variables	Economic capital	Clean sewage treatment methods	Social capital	Clean sewage treatment methods	Human capital	Clean sewage treatment methods
Variables	First	Second	First	Second	First	Second
Level of village mechanization	0.002*** (0.000)
Economic capital		0.728** (0.339)
Level of social capital of other farmers in the same village			0.233*** (0.073)
Social capital				0.717* (0.386)
Level of human capital of other farmers in the same village					0.482*** (0.061)
Human capital						0.180** (0.084)
Controls	Yes	Yes	Yes	Yes	Yes	Yes
Area fixed effect	Yes	Yes	Yes	Yes	Yes	Yes
F-values	17.0927		10.0916		63.3124
Observations	986	986	986	986	986	986

Note. Control variables include gender, marital status, whether the participant is a party member, household size, whether the participant comes from a poor family, domestic water source, household accessibility by car, domestic sewage treatment projects, public sewage pipe network, and village rules and regulations. Robust standard errors are reported in parentheses.

p < .10, **p < .05. ***p < .01.

This study refers to Shair et al.’s (2024) endogeneity test. The first stage model uses economic capital, social capital and human capital as the dependent variables, and the level of mechanization at the village level, the level of social capital of other farmers in the same village and the level of human capital of other farmers in the same village as independent variables; the second stage model uses the use of clean sewage treatment or not as the dependent variable, and economic capital, social capital and human capital, as predicted in the first stage, are used as the independent variables. The estimation results of the first stage show that the coefficients of the level of mechanization at the village level, the level of social capital of other farmers in the same village, and the level of human capital of other farmers in the same village are all significant at the 1% level. This result indicates that the level of village-level mechanization, the level of social capital of other farm households in the same village and the level of human capital of other farmers in the village are highly correlated with household economic, social, and human capital. The F-value is also greater than 10, which basically excludes the possibility of weak instrumental variables. Specifically, for every 1% increase in the level of mechanization at the village level, the economic capital of the household increases by 0.2%; for every 1% increase in the level of social capital of other farmers in the same village, the level of social capital of the household increases by 23.3%; and for every 1% increase in the level of human capital of other farmers in the same village, the level of human capital of this household increases by 48.2%. The results of the second stage estimation show that economic, social, and human capital promote the use of clean sewage treatment by farming households at the 5%, 10%, and 5% significant levels, respectively.

Robustness Check

Replacing core variables is a common practice for robustness testing. After standardizing the indicators of various dimensions of household endowment, this article uses the average weight method to calculate the average value of each dimension indicator, and forms a comprehensive indicator value of household endowment. Then the comprehensive indicator value is used to perform regression estimation of Logit model for the dependent variable. The results in Table 4 show that the household endowment coefficients are significantly positively correlated with the use of clean sewage treatment methods by rural households at the 1% level, and the regression results are consistent with the baseline regression results.

Table 4.

Robustness Tests.

Variables	Clean sewage treatment methods
Variables	(1)	(2)	(3)
Household endowments	0.255*** (0.007)	0.110*** (0.002)	0.106*** (0.014)
Controls	No	Yes	Yes
Area fixed effect	No	No	Yes
Observation	1,081	1,081	1,081

The Moderating Effect of Village Cadres’ Credibility

The results (Table 5) show the moderating role of village cadres’ credibility between household endowments and farmers’ use of clean sewage treatment methods.

Table 5.

Results of the Moderating Effect of Village Cadre Credibility.

Variables	Clean sewage treatment methods
Variables	(1)	(2)	(3)
Economic capital	0.141** (0.055)
Social capital		0.147*** (0.040)
Human capital			0.138*** (0.008)
Village cadre credibility	0.047*** (0.011)	0.052*** (0.010)	0.051*** (0.010)
Economic capital × village cadre credibility	0.012* (0.007)
Social capital × village cadre credibility		0.087*** (0.014)
Human capital × village cadre credibility			0.012*** (0.004)
Controls	Yes	Yes	Yes
Area fixed effect	Yes	Yes	Yes
Observation	1,081	1,081	1,081

Note. Control variables include gender, age, marital status, party member, non-agricultural work, household size, poor family, domestic water source, household accessible by car, domestic sewage treatment projects, public sewage pipe network, and village rules and regulations. Robust standard errors are reported in parentheses.

p < .10. **p < .05. ***p < .01.

It can be seen that the interaction coefficients between each dimension of family endowment and the credibility of village cadres are positive and significant at the 10%, 1%, and 1% levels, respectively. This implies that the positive impact of household endowment (including economic, social and human capital) on farmers’ adoption of clean sewage treatment methods is enhanced when village cadres are perceived to be more credible and reliable. This could be because, in terms of economic capital, rural households with better incomes are more willing to spend money on the construction, maintenance and management of clean sewage treatment facilities due to their trust in village cadres (Ju et al., 2022). Village cadres, as leaders and liaisons in the community, can facilitate information flow and community collaboration to increase participation in wastewater treatment (Ding et al., 2021). Village cadre credibility can strengthen social capital, discourage free-riding and opportunistic behavior, and promote the use of clean wastewater treatment methods. In terms of human capital, village cadres can improve the environmental awareness and wastewater treatment skills of rural households through education and training programs. In addition, village cadres serve as role models to demonstrate the importance of clean sewage treatment through their own behavior (J. Liu & Qi et al., 2024). The more farmers trust village cadres, the more willing they are to cooperate with related policies (Cao et al., 2020). Those with higher levels of education are able to establish effective communication with village cadres and are more willing to accept the suggestions and actions of village cadres. Therefore, H2 Village cadres’ credibility is confirmed to play a moderating role in the effect of household endowment on rural domestic wastewater treatment.

Heterogeneity Analysis

The impact of household endowments on farmers’ participation in rural domestic sewage treatment may vary depending on their non-agricultural work experience (Wang et al., 2022; W. Zhang et al., 2017). In this paper, grouped regression is performed based on non-agricultural work experience (see Table 6). Economic capital has a more significant impact on farmers with non-agricultural work experience than those without. One possible reason for this is the increased environmental literacy and investment capacity of environmental governance brought about by non-agricultural income (Jiang et al., 2019). Farmers without non-agricultural work experience do not have sufficient economic capital to participate in village-level public affairs, and their understanding of rural domestic sewage treatment is weak. Therefore, social capital has a greater impact on farmers without non-agricultural work experience. This difference may be because when the household population engages in non-agricultural work, their sense of belonging and dependence on the village is greatly reduced, resulting in lower expected benefits and higher psychological costs of sewage treatment, thereby reducing participation in rural domestic sewage treatment (Shi et al., 2011). For farmers who have lived in the village their whole lives, it is easier to obtain relevant information about sewage treatment and establish good relationships with their neighbors, increasing the likelihood that they use clean sewage treatment methods. Therefore, it can be seen that there is no significant difference in sewage treatment methods between farmers with different levels of human capital.

Table 6.

Heterogeneity Analysis Results.

Variables	Clean sewage treatment methods
Variables	With non-agricultural work experience	Without non-agricultural work experience	Under 60 years old	Over 60 years old
Economic capital	0.295* (0.179)	0.053 (0.125)	−0.092 (0.140)	0.244*** (0.027)
Social capital	0.217 (0.199)	0.099*** (0.023)	0.490*** (0.041)	−0.168*** (0.046)
Human capital	0.218*** (0.043)	0.110*** (0.008)	0.154*** (0.032)	0.039 (0.053)
Controls	Yes	Yes	Yes	Yes
Area fixed effect	Yes	Yes	Yes	Yes
Observation	196	879	600	481

Note. Control variables include gender, marital status, party member, household size, poor family, domestic water source, household accessible by car, domestic sewage treatment projects, public sewage pipe network, village rules and regulations. Robust standard errors are reported in parentheses.

p < .10. **p < .05. ***p < .01.

In addition, farmers of different ages have different resource endowments (Bellin et al., 2019). Firstly, compared with farmers under 60 years old, economic capital has a greater significant positive impact on the use of clean sewage treatment methods by farmers over 60 years old. A possible explanation is that the construction of sewage treatment facilities requires money and time. Farmers over 60 years old have more free time, work experience, and accumulated wealth (X. Y. Li et al., 2022). Meanwhile, those under the age of 60, due to their involvement in non-agricultural work, depend less on their villages, resulting in less enthusiasm for rural domestic sewage treatment. Secondly, social capital has a more significant positive impact on the use of clean sewage treatment methods by farmers under 60 years old. This is perhaps because young farmers have a wider range of ways to learn domestic sewage treatment technology (Hu & Hu, 2016). Thirdly, human capital has a significant positive impact on farmers under the age of 60, possibly because young farmers are able to learn new concepts and new technologies. For elderly farmers, their knowledge of rural domestic sewage treatment is relatively outdated, and they are less willing to learn about new technology (P. Cheng et al., 2020).

Rural areas of Liaoning Province are distributed in different regions, including coastal, central plain, eastern mountainous areas, and hilly and mountainous areas in northwestern Liaoning Province. These areas have significant differences in their levels of economic development, climatic conditions, customs, and resource endowments, which influences the construction and operation of wastewater treatment facilities in these areas. Thus, regional heterogeneity may lead to different outcomes in terms of the effect of household endowment on the use of clean wastewater treatment practices by farm households. Therefore, this study categorizes the sample in Liaoning Province into three groups: Liaodong, Liaozhong, and Liaoxi to investigate the effect of regional heterogeneity on the use of clean sewage treatment by rural households.

From the results in Table 7, it can be seen that economic capital has a significant positive effect on farmers’ use of clean wastewater treatment in western and central Liaoning, suggesting that, in these areas, better-off farmers are more capable of investing in clean wastewater treatment facilities. However, in the Liaodong region, the effect of economic capital is not significant, possibly because the higher economic level of Liaodong region may mean that they already have wastewater treatment infrastructure, including public wastewater treatment plants and sewage pipe networks. The well-developed infrastructure may imply that the accessibility of clean sewage services is high and farmers do not need additional economic inputs to connect to these services. Therefore, economic capital is not a major factor in determining the adoption of clean sewage treatment in this region. In the Liaodong and Liaozhong regions, the effect of social capital on the use of clean wastewater treatment by farm households passed the 1% significance level test, indicating that farm households in Liaodong and Liaozhong have a high probability of using clean wastewater treatment through interpersonal networks of cooperation and reciprocity and sharing of resources. However, in Liaoxi, social capital has an inhibitory effect on the use of clean sewage treatment by farm households, which implies that there may be specific socio-cultural factors that inhibit this effect in the region. Human capital passed the significance positive test in the Liaodong and Liaoxi regions, possibly because rural residents in Liaodong and Liaoxi regions have higher levels of education, clearer understandings of rural domestic wastewater treatment, and anticipate that indiscriminate discharging of domestic wastewater will lead to pollution, which is detrimental to their family members’ health and leads to a decline in the quality of agricultural products, leading them to use clean wastewater treatment. Human capital, on the other hand, does not play a significant role in Liaozhong, which indicates that the relationship between education and health levels and the choice of sewage treatment method is weak in this region, or that more data are needed to verify this relationship.

Table 7.

Regional Heterogeneity Results.

Variables	Clean sewage treatment methods
Variables	Liaodong	Liaozhong	Liaoxi
Economic capital	−0.491 (0.470)	0.167*** (0.064)	0.229*** (0.044)
Social capital	0.077*** (0.018)	0.871*** (0.073)	−0.134*** (0.030)
Human capital	0.108*** (0.016)	−0.096 (0.093)	0.260*** (0.009)
Controls	Yes	Yes	Yes
Area fixed effect	No	No	No
Observations	272	173	610

p < .10. **p < .05. ***p < .01.

Conclusions and Policy Recommendations

This study analyzes in depth the impact of household endowment on farmers’ adoption of clean sewage treatment methods based on field survey data from rural areas of Liaoning Province. The results show that there is a significant positive correlation between household economic, social and human capital and the use of clean sewage treatment methods, providing new empirical evidence for understanding the relationship between household endowments and farmers’ use of clean wastewater treatment methods. Second, this study examines the moderating role of village cadres’ credibility, an area that is under addressed in the existing literature. The study found that the credibility of village cadres played a positive moderating role in this relationship, which provides new perspectives on rural environmental governance and offers opportunities for future research. Third, this study’s analysis of heterogeneity across age groups, occupations, and regions further reveals differences in sewage treatment behavior across groups: economic capital has a more significant effect on the adoption of clean sewage treatment by farmers with non-agricultural work experience and those age 60 and older; social capital has a more prominent positive effect on farmers with only agricultural work experience and those under 60 years of age; and human capital had a more significant effect on farmers under 60 years old. Economic capital has a significant positive effect on farmers’ use of clean wastewater treatment in western and central Liaoning; social capital has a significant positive effect on farmers’ use of clean wastewater treatment in eastern and central Liaoning; and human capital has a significant positive effect on farmers’ use of clean wastewater treatment in eastern and western Liaoning. Our heterogeneity study provides an important reference for the effective implementation of rural domestic wastewater treatment policies in different households, as well as providing a theoretical basis and practical guidance for the government to formulate more targeted rural wastewater treatment policies.

First, in promoting rural domestic sewage treatment measures, attention should be paid to the relationship between household endowments and the use of clean sewage treatment methods. The government should emphasize the construction of clean sewage treatment facilities for low-income rural households and increase the economic endowment of these rural households through financial subsidies and technical assistance, thereby promoting the adoption of clean sewage treatment methods. It is also necessary to grow farmers’ social capital. Farmers should be actively involved in the planning, implementation and supervision of wastewater treatment projects to strengthen social ties among farmers and to enhance the collective efficiency of wastewater treatment. In addition, local educational resources can be used to carry out environmental awareness-raising and professional skills training programs and to broaden farmers’ access to information, so as to increase their awareness of the importance of wastewater treatment and to improve their capacity in the practical operation and maintenance of wastewater treatment facilities.

Second, in order to enhance the credibility of village cadres, village affairs should be publicized, so as to build trust between farmers and village cadres and ensure the fairness and transparency of the decision-making process by regularly announcing the progress of wastewater treatment projects, the use of funds, and the expected environmental and social benefits. Village officials should demonstrate the effectiveness of wastewater treatment, including by sharing specific data on water quality improvement, improved sanitation, and positive impacts on the local ecosystem. Farmer participation should be increased by organizing demonstration sessions and participatory assessment activities. In addition, a participatory decision-making process should be introduced to involve farmers in the planning and monitoring of the project to increase trust and improve project adaptability. Effective feedback mechanisms, such as village meetings and digital platforms, should be established to collect opinions and optimize strategies. Groups should also establish a recognition system to motivate farmers to actively participate and promote the dissemination of positive behaviors. Finally, non-farm employment opportunities for farmers should be encouraged to promote the widespread use of clean sewage treatment technologies. Rural environmental protection industries, such as eco-agriculture and renewable energy, should be developed to create non-farm employment opportunities that are closely aligned with environmental protection; vocational skills training should be implemented to help farmers build professional skills in environmental protection and wastewater treatment. These steps can raise farmers’ incomes and motivate them to adopt cleaner wastewater treatment technologies. Another potential method is establishing incentive mechanisms, such as technology subsidies and a recognition system, to increase farmers’ motivation to adopt cleaner technologies. In addition, environmental education can be improved by implementing differentiated education and training for farmers of different ages. For farmers under 60 years old, the focus should be on promoting new technologies and increasing environmental awareness, while for farmers over 60 years old, the focus should be on their life experience and traditional knowledge. It is also important to improve rural infrastructure to attract investment in non-agricultural industries. Finally, a cooperative mechanism involving the government, enterprises and farmers should be established to promote the widespread application of clean sewage treatment technologies and realize sustainable development of the rural economy and environment.

This study has several limitations. First, the data for this study were mainly from rural areas in Liaoning Province, which limits the generalizability of the findings. The socio-economic conditions, cultural backgrounds, and policy environments of different regions may have an impact on the findings, and therefore, research in a wider geographic area is needed to verify the generalizability of the findings. In the future, the sample can be extended to conduct comparative studies of rural households in different provinces and regions. Second, limitations of cross-sectional data. The data used in this paper are cross-sectional and lack temporal continuity, which limits in-depth understanding of the trends and dynamic processes of changes in rural sewage treatment behavior. In order to explore the relationship between household endowments and domestic wastewater treatment in greater depth, future research could collect data at multiple points in time by using longitudinal tracking or panel data methods.

Footnotes

Appendix: Questionnaire

Personal characteristics section:

Household Characteristics section:

Village Characterization section:

ORCID iDs

Mi Zhou

Li Huang

Ethical Considerations

The study received ethical approval from the Shenyang Agricultural University Institutional Review Board, and all procedures performed in studies involving human participants were following the 1964 Helsinki Declaration and its later amendments. Informed consent was obtained from all of the participants of our study.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Preparation of this manuscript was supported by Liaoning Provincial Social Science Planning Fund Project (Grant No. L23BGL009).

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

Dong

Nie

Wang

Sun

Zhu

Bian

(2021). Pilot study on urban sewage treatment with micro-pressure double-cycle reactor. Desalination and Water Treatment, 215, 10–22.

Anderson

Schirmer

(2015). An empirical investigation of social capital and networks at local scale through resistance to lower-carbon infrastructure. Society & Natural Resources, 28(7), 749–765.

Bellin

A. R.

Zhang

Thai

Rosenblum

N. D.

Cullen-McEwen

L. A.

Bertram

J. F.

Gilbert

R. E.

(2019). Impaired SIRT 1 activity leads to diminution in glomerular endowment without accelerating age-associated GFR decline. Physiological Reports, 7(9), e14044.

Berendes

D. M.

Sumner

T. A.

Brown

J. M.

(2017). Safely managed sanitation for all means fecal sludge management for at least 1.8 billion people in low and middle income countries. Environmental Science & Technology, 51(5), 3074–3083.

Wen

(2022). Treatment and technology of domestic sewage for improvement of rural environment in China. Journal of King Saud University-Science, 34(7), Article 102181.

Cao

Zhang

(2020). Collective Action in maintaining rural infrastructures: Cadre-farmer relationship, institution rules and their interaction terms. Land Use Policy, 99, 105043.

Chanley

V. A.

Rudolph

T. J.

Rahn

W. M.

(2000). The origins and consequences of public trust in government: A time series analysis. Public Opinion Quarterly, 64(3), 239–256.

Chen

Yao

(2018). Processing technology selection for municipal sewage treatment based on a multi-objective decision model under uncertainty. International Journal of Environmental Research and Public Health, 15(3), 448.

Cheng

Jin

Jiang

Hua

(2020). Efficiency assessment of rural domestic sewage treatment facilities by a slacked-based DEA model. Journal of Cleaner Production, 267, 122111.

10.

Cheng

Zeng

Liu

(2022). Farmer heterogeneity and land transfer decisions based on the dual perspectives of economic endowment and land endowment. Land, 11(3), 353.

11.

Coleman

J. S.

(1990). Foundation of social theory. Harvard University Press.

12.

Ding

Zhu

Wang

Dong

(2021). Public participation in rural domestic sewage treatment: a study from Inner Mongolia of China. Desalination and Water Treatment, 228, 72–83.

13.

Y. Q.

Liu

P. Y.

Bao

C. K.

(2016). A study on the rural environmental governance through the lens of social Capital-A case of livestock farming pollution in the undeveloped region. Journal of Public Management, 13(4), 101–112+157-158. 10.

14.

Duong

H. T.

Kadokami

Pan

Matsuura

Nguyen

T. Q.

(2014). Screening and analysis of 940 organic micro-pollutants in river sediments in Vietnam using an automated identification and quantification database system for GC–MS. Chemosphere, 107, 462–472.

15.

Eftimoski

(2022). Human capital and economic growth in OECD countries revisited: Initial stock versus changes in the stock of human capital effects. Jahrbücher für Nationalökonomie und Statistik, 242(1) 1–38.

16.

Estévez Rivadulla

González García

Feijoo Costa

Moreira Vilar

M. T

. (2022). How decentralized treatment can contribute to the symbiosis between environmental protection and resource recovery. Science of the Total Environment 812, 151485.

17.

Godoy

Reyes-García

Huanca

Leonard

W. R.

Olvera

R. G.

Bauchet

St. John

Miodowski

Rios

O. Z.

Vadez

Seyfreid

(2007). The role of community and individuals in the formation of social capital. Human Ecology, 35, 709–721.

18.

Hao

Yan

Wang

(2022). Effect of village informal institutions and cadre-mass relationship for farmers’ participation in rural residential environment governance in China. International Journal of Environmental Research and Public Health, 20(1), 3.

19.

Hidalgo

Martín-Marroquín

J. M.

Corona

Juaristi

J. L.

(2018). Sustainable vacuum waste collection systems in areas of difficult access. Tunnelling and Underground Space Technology, 81, 221–227.

20.

Z. Y.

(2016). Social capital and innovation of rural environmental governance pattern. Jianghuai Trib 59, 51–56.

21.

Huang

Zhao

(2023). The moderating effect of clean technology innovation in the process of environmental regulation affecting employment: Panel data analysis based on 22 industrial sectors in China. Journal of Cleaner Production, 414, 137672.

22.

Huang

Zhang

(2021). To centralize or to decentralize? A systematic framework for optimizing rural wastewater treatment planning. Journal of Environmental Management, 300, 113673.

23.

Jiang

(2019). The causes of farmland landscape structural changes in different geographical environments. Science of the Total Environment, 685, 667–680.

24.

Jin

Sumaila

U. R.

Yin

(2021). Evaluation of the policy effect of China’s environmental interview system for effective air quality governance. International Journal of Environmental Research and Public Health, 18(17), 9006.

25.

Job

(2005). How is trust in government created? It begins at home, but ends in the parliament. Australian Review of Public Affairs, 6(1): 1–23.

26.

Chen

Zhang

(2022). How do non-agricultural employment and regional selection affect farmers’ domestic sewage discharge behavior? Empirical evidence from rural China. International Journal of Environmental Research and Public Health, 19(17), 10694.

27.

Kahl

J. A.

(1954). Social mobility in Britain. Routledge and Kegan Paul Edition, 1954.

28.

Kumar

S. P.

Saha

(2017). Influence of trust and participation in decision making on employee attitudes in Indian Public Sector undertakings. SAGE Open, 7(3), 215824401773303.

29.

Lam

Kurisu

Hanaki

(2015). Comparative environmental impacts of source-separation systems for domestic wastewater management in rural China. Journal of Cleaner Production, 104, 185–198.

30.

X. Y.

Huang

S. W.

Lin

Q. J.

Zhang

Y. S.

(2022). A study on the factors influencing the intention and behavior deviation of rural residents in waste separation—based on LOGIT-ISM-MICMAC combination model. Sustainability, 14(22), 15481.

31.

Song

(2020). Study on the current situation and countermeasures of rural domestic sewage treatment in being city. Meteorological and Environmental Research, 11(3), 89–92.

32.

Liu

Han

Zheng

(2024). Exploring the influence of village social capital and rural development on farmers’ entrepreneurial decision-making: Unveiling the path to local entrepreneurship. Sage Open, 14(2), 21582440241249118.

33.

Liu

Wang

Hou

(2022). The impact of village cadres’ public service motivation on the effectiveness of rural living environment governance: an empirical study of 118 Chinese villages. SAGE Open, 12(1), 215824402210797.

34.

Liu

Zhou

Wang

Yan

Zheng

Cao

Cai

Liu

(2024). Characteristics of rural domestic sewage discharge and their driving mechanisms: Evidence from the Northern Region, China. Frontiers of Environmental Science & Engineering, 18(7), 1–12.

35.

Liu

Lan

(2015). The sloping land conversion program in China: Effect on the livelihood diversification of rural households. World Development, 70, 147–161.

36.

Mendola

(2008). Migration and technological change in rural households: Complements or substitutes? Journal of Development Economics, 85(1–2), 150–175.

37.

Meng

Zhang

Zhu

Shi

(2024). Agricultural mechanization and rural worker mobility: Evidence from the Agricultural Machinery Purchase Subsidies programme in China. Economic Modelling, 139, Article 106784.

38.

Mihalache

I. C.

(2019). Health state of human capital in the economic theory. Postmodern Openings, 10(4), 182–192.

39.

Mou

Tang

Gao

(2023). Exploring preference and willingness for rural water pollution control: A choice experiment approach incorporating extended theory of planned behaviour. Journal of Environmental Management, 332, 117408.

40.

Mushkin

S. J.

(1962). Health as an investment. Journal of Political Economy, 70(5, Part 2), 129–157.

41.

Oyekale

A. S.

(2013). Households’ access to improved drinking water and water treatment behavior in urban and rural nigeria. Asia Life Sciences, 134(4), 283–300.

42.

Piroddi

(2021). Hope, habitus and social recognition: A Bourdieusian proposal. Journal for the Theory of Social Behaviour, 51(4), 619–635.

43.

Pokropek

(2016). Introduction to instrumental variables and their application to large-scale assessment data. Large-scale Assessments in Education, 4, 1–20.

44.

Putnam

R. D.

Leonardi

Nanetti

R. Y.

(1993). Making democracy work: Civic traditions in modern Italy. Princeton University Press.

45.

Qi-yu

Zeng-jin

Lai-sheng

(2021). Research on comprehensive evaluation model of rural domestic sewage treatment technology based on fuzzy comprehensive evaluation and analytic hierarchy process method. Water Practice & Technology, 16(2), 452–471.

46.

Sayujya

Navyashree

G. C.

(2021). Humor and subjective well-being among women across age groups. International Journal of Indian Psychology, 9(3), 2.

47.

Shair

Anwar

Hussain

Kubra

(2024). The differential effect of internal and external remittances on labor participation and employment choices in Pakistan. SAGE Open, 14(3), 21582440241265879.

48.

Shan

S. N.

Duan

Zhang

T. T.

Zhang

Wang

(2021). The impact of environmental benefits and institutional trust on residents’ willingness to participate in municipal solid waste treatment: a case study in Beijing, China. International Journal of Low-Carbon Technologies, 16(4), 1170–1186.

49.

Shi

Heerink

Futian

Q. U.

(2011). Does off-farm employment contribute to agriculture-based environmental pollution? New insights from a village-level analysis in Jiangxi Province, China. China Economic Review, 22(4), 524–533.

50.

Song

Liu

Sheng

Chen

(2020). Management mode construction for operation and supervision of rural sewage treatment facilities: Towards the information-to-intelligence strategy. Bioresource Technology Reports, 11, 100481.

51.

Sood

Lokhande

Krishnankutty

Kalbar

P. P.

(2023). Economic assessment of centralized and decentralized sewerage network systems: A case study of Ludhiana, India. Journal of Urban Planning and Development, 149(3), 05023016.

52.

Lin

Wang

Quan

Chang

Rui

(2022). Sewage treatment system for improving energy efficiency based on particle swarm optimization algorithm. Energy Reports, 8, 8701–8708.

53.

Tan

Zhang

(2011). Automatic modulation recognition of mixed multiple source signals. Automatic Modulation Recognition of Mixed Multiple Source Signals 65, 37–45.

54.

Tang

Luo

Huang

Yan

(2023). Can smartphone use increase farmers’ willingness to participate in the centralized treatment of rural domestic sewage? Evidence from rural China. Environment, Development and Sustainability, 25(4), 3379–3403.

55.

Wang

Feng

Wang

Guo

Gao

Zhang

Chen

(2022). Revealing factors influencing spatial variation in the quantity and quality of rural domestic sewage discharge across China. Process Safety and Environmental Protection, 162, 200–210.

56.

Wei

J. F.

Zhang

R. L.

(2020). Exploring the planning of rural domestic sewage treatment in county based on upgrading and transformation with Zhejiang as an example. Water Water Engineering, 46, 35–41.

57.

Werkneh

A. A.

(2024). Decentralized constructed wetlands for domestic wastewater treatment in developing countries: Field-scale case studies, overall performance and removal mechanisms. Journal of Water Process Engineering, 57, 104710.

58.

Werkneh

A. A.

Gebru

S. B.

(2023). Development of ecological sanitation approaches for integrated recovery of biogas, nutrients and clean water from domestic wastewater. Resources, Environment and Sustainability, 11, 100095.

59.

(2002). The dual marginalization: A typologic analysis of the part played by and the behavior of village officials. Management World, 11, 78–85.

60.

Xiang

(2023). How does family factor endowment change affect farmers’ production decision-making: An empirical analysis based on national rural fixed observation point data in 2004~2013. Academic Journal of Management and Social Sciences, 2(3), 12–20.

61.

Xie

Yang

Wang

Xia

(2021). How do network embeddedness and environmental awareness affect farmers’ participation in improving rural human settlements?. Land, 10(10), 1095.

62.

Wang

Khan

S. U.

(2023). How does capital endowment impact farmers’ green production behavior? Perspectives on ecological cognition and environmental regulation. Land, 12(8), 1611.

63.

Zheng

Zhang

Gao

Chen

Tan

(2022). Systematically assess the advancing and limiting factors of using the multi-soil-layering system for treating rural sewage in China: From the economic, social, and environmental perspectives. Journal of Environmental Management, 312, 114912.

64.

Xue

Guo

Sun

Feng

L. S.

Zhang

(2021). Influencing factors of farmers’ cognition on agricultural mulch film pollution in rural China. Science of the Total Environment, 787, 147702.

65.

Yang

Chi

Wang

Tang

(2020). Untangle the complex stakeholder relationships in rural settlement consolidation in China: A social network approach. Land, 9(7), 210.

66.

Yang

G. R.

Wang

Ding

R. X.

Lin

S. P.

Lou

Q. H.

Herrera-Viedma

(2023). Managing non-cooperative behaviors in large-scale group decision making based on trust relationships and confidence levels of decision makers. Information Fusion, 97, 101820.

67.

(2012). Study on willingness to pay and value evaluation of rural domestic sewage treatment facilities in Zengcheng City based on CVM. South China University of Technology, 2012.

68.

Wang

Cui

Zhou

(2023). Influence of capital endowment on rural households’ willingness to pay for rural human settlement improvement: Evidence from rural China. Applied Economics, 55(34), 3980–3995.

69.

Zhang

Quan

Tang

Cheng

Tang

Shen

Zhang

(2023). China’s wastewater treatment: Status quo and sustainability perspectives. Journal of Water Process Engineering, 53, 103708.

70.

Zhang

Wang

Zhou

Zhang

Zuo

(2020). The effect on poverty alleviation and income increase of rural land consolidation in different models: A China study. Land Use Policy, 99, 104989.

71.

Zhang

Shi

Williams

Lighterness

Khan

A. U.

(2023). An empirical test of the influence of rural leadership on the willingness to participate in public affairs from the perspective of leadership identification. Agriculture, 13(10), 1976.

72.

Zhang

Zheng

Zhang

(2020). Study on the influence of social capital on farmers’ participation in rural domestic sewage treatment in Nanjing, China. International Journal of Environmental Research and Public Health, 17(7), 2479.

73.

Zhang

Swaney

D. P.

Hong

Howarth

R. W.

(2017). Influence of rapid rural-urban population migration on riverine nitrogen pollution: perspective from ammonia-nitrogen. Environmental Science and Pollution Research, 24, 27201–27214.