Willingness to Pay for Domestic Waste of Rural Households Under Low-Carbon Society Transition: A Case Study of Underdeveloped Mountainous Areas in Shaanxi, China

Abstract

A low-carbon society aims to achieve sustainable social development through innovative technologies and mechanisms, promoting low-carbon economic models and lifestyles. In light of China’s commitment to achieving carbon neutrality and transitioning to a low-carbon society, it is crucial to control waste generation at its source, as the waste management sector is highly polluting and contributes substantially to carbon emissions. Adopting the 3R (reduce, reuse, and recycle) approach, reducing the quantity of waste is the priority in waste management. Therefore, exploring rural residents’ willingness to adopt the “pay as you throw” (PAYT) policy in underdeveloped mountainous areas and the factors influencing this willingness is highly valuable. This paper adopts the Contingent Valuation Method (CVM) with a face-to-face questionnaire survey, involving 1429 farmers from six cities around the underdeveloped mountainous area in Northwestern China. It measures their willingness to pay (WTP) and preferred payment levels for the PAYT policy. Based on the theory of planned behavior, the paper finds that farmers’ environmental knowledge, environmental awareness and social trust positively influence their WTP, while farmers’ perception of pollution and daily waste disposal do not significantly impact their WTP. Additionally, social trust negatively moderates the relationship between environmental knowledge and WTP. This paper provides empirical results that can support the implementation of a nationwide waste fee management system and the promotion of volume-based waste fee management. It also offers targeted suggestions for the government to establish PAYT and improve the efficiency of rural household waste management in rural China.

1. Introduction

The green economy and low-carbon economy refer to the transformation of the traditional high-carbon growth model into a low-carbon growth model. A green economy can be considered low-carbon, resource-efficient and socially inclusive [1]. The concept of the green economy first appeared in the late 1980s. British environmental economist Pearce expounded on this concept in his book “Green Economy Blueprint” published in 1989. However, the concept of the green economy gained widespread attention at the United Nations Conference on Sustainable Development, held in Rio de Janeiro in 2012, where it became a mainstream development concept [2]. The concept of a low-carbon economy was first introduced by the British Department of Industry and Trade in the 2003 Energy White Paper, titled “Our energy future: creating a low carbon economy” [3]. The Kyoto Protocol and the Copenhagen Accord further emphasized the importance of a low-carbon economy [4,5].

China’s transition to a low-carbon society began around 2010. Since then, the Chinese government has systematically integrated low-carbon development into national policies and strategies, with specific measures aimed at facilitating the transition toward a low-carbon society. On 22 September 2020, Chinese President Xi Jinping announced China’s commitment to achieving carbon peaking and carbon neutrality (referred to as “carbon neutrality”). China is determined to peak carbon dioxide emissions before 2030 and achieve carbon neutrality before 2060. Grounded in the principles of energy conservation and ecological environmental protection, a low-carbon society seeks to achieve sustainable social development through innovative technologies and mechanisms, promoting low-carbon economic models and lifestyles.

Following the 3R (reduce, reuse, and recycle) approach, reducing waste quantity is the top priority in waste management [6]. Producer responsibility mandates sustainable product design and environmentally friendly packaging, making it imperative to control the generation of waste at the source [7,8,9]. Proper packaging reduction is the first step to “reduce” waste [10]. Regarding “reuse” and “recycling”, the waste sorting behavior on the consumer side is of crucial importance, particularly as urban households account for more than 75% of China’s household carbon emissions. Since 2013, however, per capita emissions in rural areas have surpassed those in urban areas [11]. Rural areas are a significant source of global greenhouse gas emissions, and improving environmental governance in these regions is vital for achieving the carbon neutrality goal and building a low-carbon society.

Waste disposal fees are seen as one of the important means of waste management. Compared with incineration, landfill, and deposit refund systems [12,13,14], waste disposal fees are more extensible in rural China. Currently, two mainstream waste disposal charging systems are in use: the “fixed charge” and the “charge by volume” systems. The former, typically implemented through a property tax or monthly payment by a family or individual [15], is the initial method of waste disposal charging, and is convenient for government collection and management [11]. However, since it is not directly tied to residents’ waste production and economic interests, it has limited effectiveness in encouraging waste sorting and reduction. The “charge by volume” strategy, also known as “pay as you throw” (PAYT), aims to reduce waste production at the source by adhering to two important principles: “polluter pays” and “pay as you throw” [16]. There are three main charging methods including bag or tag-based system, weight-based system and can system [17].

Since the late 1970s, a substantial series of studies, driven by Wertz has highlighted the advantages of PAYT. Then, Richardson, Havlicek and Morris, Holthausen advanced the practical application of garbage collection and decision-making models [15,18,19,20]. In the 1990s, some cities in the United States and Germany began to pilot projects to charge for garbage by volume [17,21,22]. A PAYT experiment in Georgia significantly reduced waste collection and landfill, thereby reducing collection and disposal costs [23]. Since the 21st century, the improvement of environmental awareness and the popularization of the concept of sustainable development have led more countries to promote the implementation of PAYT, and scholars have also conducted in-depth evaluation and research on the policy effects of PAYT. Research shows that PAYT improves the efficiency of public goods provision by fairly distributing the costs of waste generation, increasing the transparency of waste management costs [15,24]. PAYT also makes an important contribution towards material reuse and recycling objectives for the new circular economy, promoting waste sorting, reduction and resource utilization of waste at the source [14,22]. Currently, PAYT has become more integrated with technology. In Greece, composting technologies are being used to manage food waste as an environmentally friendly method [25]. Japan has also begun to develop and promote the application of smart trash cans in the PAYT policy [26].

The Chinese government attaches great importance to the green development of rural areas. China first attempted to implement a waste disposal fee in 2002, and proposed the waste disposal charging regulation at the national level in 2018. The revised “Law of the People’s Republic of China on Prevention and Control of Environmental Pollution by Solid Waste”, which came into effect on 1 September 2020, officially incorporated waste disposal fees into the law. This law stipulates that “local governments at or above the county level shall formulate household waste disposal fees according to the local circumstances and combined with the classification of household waste, which should reflect differential management such as classification pricing and metering charges” [27]. The Chinese government is establishing a Rural Domestic Waste Management Service, to provide full-process services in the collection, transportation and disposal of domestic waste. Currently, most provinces in East China have fully implemented a fixed waste charge system. However, there are still some potential challenges in implementing PAYT in rural China [28]. The economic pressures [29], weak infrastructure, imperfect charging systems and the dispersed distribution of rural residents pose obstacles to the effective implementation of the policy [30].

Therefore, this paper focuses on the underdeveloped mountainous area in Northwestern China, specifically the Qin Ling Mountains in Shaanxi province, as the study area. The Qin Ling Mountains are well known and significant as the water source of the South-North Water Transfer Project, the largest water transfer project in China, as well as for their ecological functions, including water conservation, climate regulation, and biodiversity maintenance, making the sample of this study representative. By conducting a questionnaire survey among farmers in the study area, this study aims to assess the willingness and attitudes of local residents towards the PAYT policy. The findings will provide reference and empirical results to support the gradual promotion of the PAYT policy in the Qin Ling Mountains region and other underdeveloped mountainous regions in the future.

The government cannot solely address the issue of rural household waste due to the negative externalities associated with waste and the public nature of the problem [31]. Since rural residents are the prime producers of waste in rural areas, as well as the main beneficiaries of waste management and crucial participants in environmental protection, it is important to consider their willingness to pay (WTP) under the PAYT policy. The economic cost perceived by participants is generally higher than the cost of waste classification behavior, making participants more sensitive to and concerned about the PAYT policy. Thus, understanding the factors that influence farmers’ WTP can provide valuable insights for local governments. Given the transition to a low-carbon society, it is worthwhile exploring the factors influencing the willingness of rural residents in underdeveloped mountainous areas to adopt the PAYT policy. Unfortunately, current research mainly focuses on pro-environmental and waste-sorting behaviors [32], with studies on PAYT often concentrating on demographic characteristics such as gender, age, education level, and individual income level [33]. This paper surveys 1429 farmers living in six cities around the study area using a face-to-face questionnaire and the contingent valuation method to measure their WTP and their preferred payment levels for PAYT. Based on the theory of planned behavior, this paper examines how environmental knowledge, environmental awareness, perception of pollution, daily waste disposal, and social trust affect WTP.

The contributions of this paper are as follows: First, this paper takes 1429 farmers living in the six cities around the underdeveloped mountainous area in Northwestern China as the survey objects, and adopts a contingent valuation method through the face-to-face questionnaire survey to measure their WTP and their preferred payment levels for PAYT. This provides empirical results for implementing a nationwide waste fee management system and promoting a volume-based waste fee management system. Second, using the theory of planned behavior, this paper examines whether farmers’ environmental knowledge, environmental awareness, perception of pollution, daily waste disposal, and social trust will affect their WTP. We conduct further research about marginal effect analysis of key factors and moderating effect of social trust. Furthermore, this paper analyzes the effects of the above factors across different age groups, regions, and education levels. Finally, the paper provides targeted recommendations for the government to establish PAYT and improve the efficiency of rural household waste management in rural China.

2. Literature Review and Hypothesis

2.1. Farmers’ Environmental Knowledge and Environmental Awareness

Under social dilemmas, pro-environmental behavior may lead to conflicts between individual and collective interests, with residents’ payment of household waste fees reflecting this tension [34]. If individuals are unwilling to pay for household waste disposal, the resulting financial pressure on governments may lead to insufficient funding for better waste disposal services, thereby negatively affecting collective interests. Therefore, this paper defines the behavior of paying for household waste as a form of non-radical pro-environmental behavior.

Environmental knowledge and attitude have a significant impact on human environmental behavior [35]. Environmental knowledge refers to an individual’s understanding of facts, concepts and relationships related to the natural environment and ecosystem [36]. Only when individuals possess a certain level of environmental knowledge can they have the willingness and ability to engage in environmental issues [37]. Residents with higher levels of environmental knowledge are more likely to engage in pro-environmental behavior due to their richer knowledge and skills, making it easy to promote such behavior [38]. When residents have a greater reserve of environmental knowledge, they are more willing to pay a higher price for environmentally friendly products [39]. However, some scholars have found that environmental knowledge does not always result in positive environmental behaviors [40]. Other studies have found that environmental knowledge indirectly affects pro-environmental behavior through environmental attitudes, personal beliefs and other factors [41,42].

Based on the above analysis, this paper proposes the following hypothesis:

H1. 

Farmers’ environmental knowledge positively affects their WTP for PAYT.

Environmental awareness refers to an individual’s evaluation and concern for the environment [43]. In the theory of planned behavior, attitude refers to an individual’s evaluation of a specific behavior. Therefore, in this paper, environmental awareness is defined as an individual’s attitude and evaluation of the environment. Differences in farmers’ ecological cognition can lead to variations in waste-sorting behavior [44]. The study also found that customers with more positive environmental attitudes are more likely to purchase environmentally friendly products and are less likely to find it inconvenient to buy green products [45]. Positive environmental attitudes also positively influence individuals’ willingness to pay for green products [46].

Based on the above analysis, this paper proposes the following hypothesis:

H2. 

Farmers’ environmental awareness positively affects their WTP for PAYT.

2.2. Farmers’ Perception of Pollution and Daily Waste Disposal

The theory of planned behavior has been widely used in research on public environmental protection behavior [47]. Based on the theory of rational behavior, this theory further explains how the public changes their behavior by considering three aspects: attitude, subjective norms and perceived behavior [48]. Perceived behavior refers to the public’s perception of abilities, opportunities, and resources. Perception of pollution is an individual’s evaluation and judgment of the severity of environmental pollution in the area where they live, and this perception is linked to their environmental protection behavior [49,50]. When individuals are more sensitive to environmental perceptions and have more concerns about environmental issues, they are more likely to engage in pro-environmental actions, with social stress acting as a mediating factor in this relationship [51]. For example, the perception of plastic pollution has been shown to predict participants’ pro-environmental behaviors [52]. The level of environmental pollution perceived by rural residents not only directly promotes their waste-sorting behavior but also indirectly affects this behavior through village attachment and environmental responsibility awareness [53,54].

Based on the above analysis, this paper proposes the following hypothesis:

H3. 

Farmers’ perception of pollution positively affects their WTP for PAYT.

The essence of the PAYT policy is to dynamically determine waste costs based on the amount of waste or pollution generated by individuals. Previous studies have found that, because there is no immediate financial cost associated with generating waste, people often overlook the amount of household waste they produce, thereby exacerbating pollution [55]. Due to individual “egoism”, people are generally unwilling to pay for waste disposal as they generate more waste.

Based on the above analysis, this paper proposes the following hypothesis:

H4. 

Farmers’ daily waste disposal negatively affects their WTP for PAYT.

2.3. The Moderating Effect of Farmers’ Social Trust

The theory of planned behavior, based on the assumption of a “Rational Economic Man” from the Theory of Reasoned Action (TRA) [56], means that in this theory people are assumed to always be rational and self-interested, and pursue their subjective goals in the best way [57]. Social capital is an emerging and complex concept that emphasizes the context in which behavior occurs. As a potential benefit and resource within interpersonal networks, social capital can significantly influence the effectiveness of environmental governance [58,59]. Currently, it is agreed that social capital consists of four components: social norms, social relations, social networks and social trust [60].

Social trust plays a crucial role in the development and progress of community relations and is considered a key element of social capital [61]. Research has shown that the level of trust in other citizens and institutions can affect public acceptance of waste management policies [62]. Social capital can also increase individuals’ willingness to pay for biodiversity conservation [63]. In China’s countryside, the unique characteristics of an “acquaintance society”, are that farmers generally share similar goals and values and tend to trust one other [64]. A high degree of value consensus forms the foundation for social trust [65], which is essential for promoting information exchange, facilitating collective action, and reducing “free rider” behavior [58]. On this basis, collective action can effectively guide individual behavior [66,67]. For example, when farmers believe that their relatives and friends are likely to pay for waste disposal, they are more inclined to do the same. Additionally, village cadres in rural China play a leading role in various aspects of villagers’ lives. When village cadres take the lead in supporting waste disposal fees, villagers are more likely to accept the policy. It is precisely due to the existence of social trust that the interaction between farmers and village cadres, and the resulting trust chain may diminish the impact of farmers’ environmental knowledge on their WTP.

Based on the above analysis, this paper proposes the following hypothesis:

H5. 

Farmers’ social trust positively affects their WTP for PAYT.

There exists a gap between environmental concerns and pro-environmental behaviors [68], which is influenced by social trust, personal attitudes, and values [69,70]. Additionally, village cadres in rural China play a leading role in various aspects of villagers’ lives. When village cadres take the lead in supporting waste disposal fees, villagers are more likely to accept the policy. It is precisely due to the existence of social trust that the interaction between farmers and village cadres, and the resulting trust chain may diminish the impact of farmers’ environmental knowledge on their WTP.

Based on the above analysis, this paper proposes the following hypothesis:

H6. 

Farmers’ social trust negatively affects the relationship between their environmental knowledge and WTP for PAYT.

3. Materials and Methods

3.1. The Contingent Valuation Method (CVM)

The Contingent Valuation Method (CVM), as a method to evaluate the non-market value of ecosystem services, environmental goods and cultural heritage through a hypothetical market, can make up for the shortcomings of the traditional market price method, has been widely used in watershed, forest and other ecosystems [71,72]. In a hypothetical market, CVM used either an open-ended question or a close-ended question to ask about customers’ willingness of environmental goods [73]. Commonly used valuation methods are Willingness to Pay (WTP) and Willingness to Accept (WTA). Considering that the objects evaluated by CVM are usually less substitutable, it is more appropriate to use WTP rather than WTA to estimate the value of non-market products in terms of empirical research technology [74]. The CVM method also has some limitations. Due to an incomplete understanding of the hypothetical market, individuals may not be able to fully and correctly express their true willingness to pay, which can lead to hypothetical bias in the survey results. In addition, the reliability of the CVM method is greatly affected by the design of questionnaire questions, the method of inquiry, and the survey method. These deviations will affect the respondents’ answers and lead to inaccurate results.

3.2. Data Collection

A stratified random sampling survey method was used for sample selection. After comprehensively considering the population of the 6 prefecture-level cities (Xi’an, Baoji, Weinan, Hanzhong, Ankang and Shangluo), the level of local economic development and the overall income level of residents, the questionnaire survey sites were finally determined to be 18 townships in the 6 prefecture-level cities within the study area.

The research group conducted a pre-survey and conducted a total of 60 valid questionnaires for one week. According to the results and feedback encountered in the pre-survey, the research group revised the questionnaire from several aspects, such as the design of the questionnaire question, the inquiry method, the design of the bidding point of the willingness to pay, and how to reduce the recognition bias of the participants to minimize the hypothetical bias of the contingent valuation method.

The following amendments were made after the pre-survey. The questionnaire questions were revised to be more dialectical to facilitate the understanding of participants. Before asking participants about their willingness, the cheap talk technique, which contains a combination of pictures and text describing the hypothetical market, was used. The research group conducted a formal questionnaire survey over 4 months. Data were collected through face-to-face questionnaires between trained postgraduate students and participants, and the survey time for each questionnaire was controlled around 20 min reducing the investigator bias, survey method bias and dwell time length bias of the contingent valuation method. After sorting and screening, 1429 valid questionnaires were obtained for this study.

3.3. Variable Definition

3.3.1. Dependent Variable

The dependent variables in this paper are farmers’ willingness to pay for PAYT (WTP). If the farmer was not willing to pay, we simply assigned a value of 0 to WTP. If the farmer was willing to pay, we then asked them “What is the maximum amount you can accept per pound for waste disposal fees?” and them to choose one out of the 5 price ranges provided (options include “0.1–0.2 RMB/0.5 kg”, “0.3–0.4 RMB/0.5 kg”, “0.5–0.6 RMB/0.5 kg”, “0.7–0.8 RMB/0.5 kg”, “0.9 RMB/0.5 kg and above”). The value of WTP is taken from 0 to 5 according to their willingness to pay and the price range they chose.

3.3.2. Independent Variables

A 5-point Likert scale was used to rate each question, and 4 groups of questions were summed and averaged to obtain the values of the following independent variables: farmers’ environmental knowledge (FEK), farmers’ environmental awareness (FEA), farmers’ perception of pollution (FPP) and social trust (ST), respectively.

Farmers’ environmental knowledge (FEK) was obtained from the following 6 questions: “Do you know the meaning of ‘clear waters and green mountains are as valuable as gold and silver mountains’?”, “Do you know that a high PM2.5 (fine particulate matter) index in the air can affect your health?”, “Do you know that waste incineration will produce harmful gases?”, “Do you know that household waste in Shaanxi Province is classified into 4 categories: recyclables, hazardous waste, kitchen waste and other waste?”, “Do you agree that cardboard boxes and mineral water bottles are all recyclable?”, and “Do you agree that plastic waste create great damage to the ecological environment?”.

Farmers’ environmental awareness (FEA) was calculated by the following 6 questions: “Do you agree that protecting the environment is more important than developing the economy at present?”, “Do you agree that protecting the environment is more important than individual interest?”, “Do you think protecting the mountains will improve the ecological environment of your neighborhood?”, “Do you think it is necessary to implement strict protection measures for the ecological environment of the mountains?”, “If a new waste incineration power plant is built 30 km away from your house, do you agree?”, and “Do you usually pay attention to the ecological environment damage issues in the mountains?”.

Farmers’ perception of pollution (FPP) was determined by the following 5 questions: “Personally how serious do you think the current water pollution in the mountainous area is?”, “Personally how serious do you think the current forest decline in the mountainous area is?”, “Personally how serious do you think the current air pollution in the mountainous area is?”, “Personally how serious do you think the current soil pollution in the mountainous area is?”, and “Personally how serious do you think the current waste pollution in the mountainous area is?”.

Daily waste disposal (DWD) was determined by the question “How much non-recyclable waste does your household throw away in one day ______?”. To allow participants to provide more accurate answers, we divided 0–10 kg into 6 segments and assigned the values of DWD from 1 to 6 sequentially according to the intervals from low to high.

Social trust (ST) was obtained by the following 3 questions: “If the village cadres are willing to pay for waste disposal, are you willing to pay for it, too?”, “If your relatives are willing to pay for waste disposal, are you willing to pay for it too?”, and “If your neighbors are willing to pay for waste disposal, are you willing to pay too?”.

3.3.3. Control Variables

Demographic factors include gender, age, education level (Edu), city, total household income for the previous year (income) and the proportion of civil servants in the family (civil). As for gender, male = 1 and female = 0. Age is measured at 3 different groups (18–30 = 1, 31–50 = 2, 51–65 = 3), and education level is measured at 5 scales (Elementary school and below = 1, Middle school = 2, High school/Secondary school = 3, Junior University or Undergraduate = 4, Postgraduate and above = 5). City is divided into 6 prefecture-level cities (Weinan = 1, Xi’an = 2, Baoji = 3, Ankang = 4, Shangluo = 5, Hanzhong = 6). Total household income for the previous year is assessed at 3 levels, 21.1% of participants’ annual salaries are under 17,500 RMB (about 290 USD), 65.7% are between 17,500 and 875,000 RMB (about 290–725 USD), 13.2% are 87,500 RMB (about 725 USD) and above. And the proportion of civil servants in the family is the number of people in the family who work in government departments and public institutes.

4. Results and Analysis

4.1. Questionnaire Reliability and Validity Test

We used SPSS27.0 to analyze the reliability and validity of the questionnaire. The Cronbach’s Alpha of the reliability test is 0.719, suggesting that the reliability is “acceptable”. The results of the Kaiser–Meyer–Olkin (KMO) test are 0.796, and Bartlett’s test of sphericity value p < 0.05, indicating the questionnaire passed the validity test.

4.2. Descriptive Statistics

Table 1. Descriptive statistics.

Variables	Mean	Standard Error	Minimum	Maximum
WTP	0.872	1.183	0	5
WTP (YES/NO)	0.486	0.500	0	1
FEK	4.232	0.664	1.5	5
FEA	4.027	0.583	1.429	5
FPP	2.309	1.403	1	5
DWD	2.162	0.957	1	6
ST	3.679	1.162	1	5
Gender	0.508	0.500	0	1
Age	46.087	12.019	18	65
Edu	2.373	1.077	1	5
City	3.207	1.589	1	6
Older	0.098	0.151	0	1
Civil	0.083	0.184	0	1
Income	56,243.002	58,018.597	1500	400,000

shows the descriptive statistics for each variable in this study. The mean value of WTP is 0.872, with a minimum of 0 and a maximum of 5. When converted to a percentage, this corresponds to 17.44%, indicating that farmers generally have limited willingness to PAYT. Among all participants, 48.64% of farmers are willing to pay waste disposal fees based on volume, with 27.29% of them choosing the lowest fee level of “0.1–0.2 RMB/0.5 kg”. Our survey found that 70.05% of farmers have never paid waste disposal fees, which may be the main reason for the low percentage of farmers’ willingness to PAYT. Among the independent variables, farmers’ environmental knowledge and awareness are generally higher, with average values of 4.232 and 4.027, respectively, whereas the average value of farmers’ perception of pollution is 2.309. The main reason is that in recent years, the publicity of environmental protection in the study area has been relatively strong, and farmers present a high level of knowledge about environmental protection, and their environmental awareness has also been improved. At the same time, under the environmental protection publicity, local farmers believe that the waste pollution in their area is not very serious, and the waste disposal management work carried out by local government and communities is relatively good. The average amount of waste disposed of daily is 2.162, indicating on average the daily waste generated by farmers is relatively limited. Among the control variables, the gender ratio of the survey sample is basically the same, with males (50.8%) slightly higher than females (49.2%). The age of the survey subjects is strictly limited to 18 to 65 years old, of which the number of people over 50 accounted for 45.0%, indicating that there are many middle-aged and elderly people in the study area, which is similar to the basic demographic characteristics of “young and middle-aged people go out to work” in the underdeveloped mountainous areas. The average educational level is 2.373, indicating that most of the participants’ education levels are middle school or below, and the level of education is low. Among the prefecture-level cities, 61% of the samples live in the three cities at the northern foot of the study area, among which Xi’an has the largest sample, mainly because Xi’an has a large residential population. The average percentage of the number of people aged 65 or higher per household is 9.8%, and the average percentage of the number of civil servants per household is only 8.3%. The average household income is 56,243 RMB, and 65.7% of the farmers’ total household income is between 17,500 and 87,500 RMB in the previous year, indicating that most of the farmers have moderate economic conditions.

4.3. Baseline Regression

Table 2. Regression results.

Variables	WTP
FEK	0.212 ***
	(0.061)
FEA	0.164 ***
	(0.062)
FPP	0.024
	(0.023)
DWD	−0.001
	(0.032)
ST	0.126 ***
	(0.027)
Gender	0.255 ***
	(0.063)
Age	0.007 **
	(0.003)
Edu	0.095 ***
	(0.019)
City	0.085 **
	(0.038)
Income	0.049
	(0.035)
Older	−0.402 **
	(0.201)
Civil	0.344 **
	(0.169)
N	1429
Pseudo R2	0.051
Wald chi2	184.74 ***
Mean VIF	1.12

** p < 0.05, *** p < 0.01.

presents the baseline regression results. In the model, the Wald chi² p < 0.01, indicates that the overall regression effect of the model is good. The average VIF value is 1.12, and the VIF of all explanatory variables is less than 2, indicating that there is no multicollinearity problem among variables.

FEK, FEA and ST have a significantly positive impact on the farmers’ WTP (p < 0.01), indicating that the improvement of FEK, FEA and ST will significantly increase farmers’ WTP on PAYT. FPP and DWD have no significant impact on farmer’s WTP. This may be because most of the participants live near the study area, as the environmental protection requirements in the study area are high, the environmental governance results are relatively restricted, and the local government and environmental protection organizations have better publicity, thus farmers perceive the degree of waste pollution is relatively moderate. Therefore, FPP does not directly affect farmers’ WTP. At the same time, due to most of the farmers having a frugal lifestyle, except for the basic household waste, there is not much waste generated in their daily lives, and therefore DWD does not have a substantial impact on the WTP.

The results also show that household income has no significant impact on WTP. This may be because most of the participants have relatively limited household income, and 70.05% of them have never paid waste disposal fees, thus reducing the impact of income on WTP. There is a significant positive correlation between the ratio of civil servants to farmers’ WTP (p < 0.05), indicating that households with government or public institution employees are more active in responding to pro-environmental behaviors and have stronger environmental protection intentions. The proportion of people over 65 years old has a significant negative impact (p < 0.05) on WTP, mainly because for most families, supporting the elderly is an important economic expenditure. The more elderly people in the family, the greater the financial pressure within the household, and the less willing to participate in the PAYT policy. Other control variables, such as gender (p < 0.01), age (p < 0.05) and education level (p < 0.01), have a positive impact on farmer’s WTP, which is consistent with previous studies and our expectations.

Further marginal effect analysis results in

Table 3. Marginal effects analysis results.

	WTP	0	1	2	3	4	5
Variables
FEK		−0.078 ***	0.021 ***	0.020 ***	0.021 ***	0.005 ***	0.011 ***
		−0.022	−0.006	−0.006	−0.006	−0.002	−0.004
FEA		−0.060 ***	0.016 **	0.015 ***	0.016 ***	0.004 **	0.009 **
		−0.023	−0.006	−0.006	−0.006	−0.002	−0.004
ST		−0.046 ***	0.013 ***	0.012 ***	0.012 ***	0.003 ***	0.007 ***
		−0.010	−0.003	−0.003	−0.003	−0.001	−0.002
Control		Yes	Yes	Yes	Yes	Yes	Yes

** p < 0.05, *** p < 0.01.

present that with each unit increase in FEK, the probability that farmers are unwilling to participate in the PAYT policy decreased by 7.8%, and the probability that farmers are willing to pay the “0.1–0.2 RMB/0.5 kg” increased by 2.1%, and the probability that farmers are willing to pay “0.7–0.8 RMB/0.5 kg” and “0.9 RMB/0.5 kg and above” increased by only 0.5% and 1.1%. Similarly, the higher the FEA and ST, the probability that farmers are unwilling to participate in PAYT decreased by 6.0% and 4.6%, respectively. In addition, the probabilities are concentrated in the highest range for “0.1–0.2 RMB/0.5 kg”, “0.3–0.4 RMB/0.5 kg” and “0.5–0.6 RMB/0.5 kg” when the marginal effects of FEK, FEA and ST increase. A possible explanation is that the higher the FEK and FEA, the more willing they are to take pro-environmental actions to protect the environment, thus increasing their WTP for PAYT. Furthermore, because the income levels of the participants are generally low, some farmers believe that the cost should be mainly borne by the government, therefore participants are more inclined to choose the lower amount for the PAYT standard. (Since the FPP and DWD results were not significant, their marginal effects were not shown in the paper).

4.4. Robustness Test

This paper selects the following three methods for the robustness test. (1) Replace dependent variables: we changed the measures for ST by the sum and average of the three questions to the average of one question, “If the village cadres are willing to pay for waste disposal, are you willing to pay for it, too?”. (2) Replace the independent variable: we transformed the independent variable into a dichotomous variable, set the sample that is not willing to pay as 0, set the sample that is willing to pay as 1, and changed the model into a probit model for regression. (3) Reduce the sample size: samples with a family size of less than three people were excluded. As shown in

Table 4. Robustness testing of variables.

Variables	(1)	(2)	(3)
FEK	0.216 ***	0.249 ***	0.199 ***
	(0.061)	(0.067)	(0.065)
FEA	0.157 **	0.253 ***	0.184 ***
	(0.063)	(0.070)	(0.067)
FPP	0.024	0.001	0.014
	(0.022)	(0.025)	(0.024)
DWD	0.001	−0.033	−0.017
	(0.033)	(0.036)	(0.034)
ST	0.125 ***	0.119 ***	0.138 ***
	(0.026)	(0.031)	(0.029)
Control	Yes	Yes	Yes
N	1429	1429	1289
Pseudo R2	0.052	0.095	0.054

** p < 0.05, *** p < 0.01.

, the results of various robustness tests are consistent with the baseline regression results, making our results robust.

4.5. Moderating Effect of Social Trust

Further analysis considers whether social trust has a moderating effect between farmers’ environmental knowledge and WTP for PAYT.

Table 5. The moderating effect of social trust.

Variables	WTP
FEK	0.216 ***
	(0.061)
ST	0.139 ***
	(0.028)
Interaction term	−0.096 **
	(0.043)
FEA	0.021
	(0.023)
FPP	0.158 **
	(0.063)
DWD	−0.006
	(0.032)
Control	Yes
N	1429
R2	0.052

** p < 0.05, *** p < 0.01.

shows that FEK and ST have a significant positive impact on WTP (p < 0.01), and the interaction item has a significant negative impact on WTP (p < 0.05), that is, as the level of ST increases, the positive impact of FEK on WTP is weakened. A possible explanation may be because the higher the level of ST in farmers, the more convergence their behaviors might be, and therefore the amount of payment that farmers are willing to pay is more likely to be influenced by the amount chosen by their neighbors and relatives, therefore the influence of FEK on WTP for PAYT is weakened.

4.6. Heterogeneity Analysis

The heterogeneity is analyzed by participants’ education level, age and location as shown in

Table 6. Heterogeneity analysis results.

Variables	Education		Age		Location
	Low	High	Young	Old	Southern	Northern
FEK	0.223 ***	0.157	0.161	0.247 ***	0.124	0.247 ***
	(0.069)	(0.116)	(0.100)	(0.074)	(0.101)	(0.076)
FEA	0.206 ***	0.115	0.182 **	0.177 **	0.293 ***	0.089
	(0.079)	(0.101)	(0.089)	(0.086)	(0.097)	(0.080)
FPP	0.014	0.035	−0.017	0.077 **	0.005	0.047
	(0.030)	(0.033)	(0.030)	(0.033)	(0.037)	(0.029)
DWD	−0.014	0.012	−0.008	−0.004	0.149 ***	−0.086 **
	(0.042)	(0.051)	(0.051)	(0.042)	(0.055)	(0.040)
ST	0.141 ***	0.111 ***	0.109 ***	0.136 ***	0.035	0.183 ***
	(0.038)	(0.042)	(0.039)	(0.042)	(0.044)	(0.038)
Control	Yes	Yes	Yes	Yes	Yes	Yes
Gender	0.256 ***	0.274 ***	0.281 ***	0.201 **	0.014	0.401 ***
	(0.082)	(0.098)	(0.089)	(0.089)	(0.103)	(0.081)
Age	0.004	0.007	0.008	−0.008	0.017 ***	0.001
	(0.004)	(0.005)	(0.007)	(0.008)	(0.005)	(0.004)
Edu	0.110	−0.054	0.109 *	0.097 *	0.241 ***	−0.029
	(0.089)	(0.111)	(0.057)	(0.056)	(0.062)	(0.051)
City	0.082 ***	0.116 ***	0.071 ***	0.126 ***	0.104 *	0.172 **
	(0.027)	(0.029)	(0.027)	(0.029)	(0.057)	(0.068)
Income	0.023	0.085*	0.047	0.043	0.063	0.028
	(0.048)	(0.050)	(0.049)	(0.049)	(0.053)	(0.046)
Older	−0.608 **	−0.073	−0.499 *	−0.276	−1.009 ***	−0.076
	(0.268)	(0.324)	(0.283)	(0.312)	(0.344)	(0.261)
Civil	−0.173	0.504 **	0.455 *	0.054	−0.106	0.695 ***
	(0.492)	(0.204)	(0.243)	(0.276)	(0.270)	(0.247)
N	867	562	700	729	536	893
Pseudo R2	0.046	0.038	0.051	0.059	0.065	0.060

* p < 0.1, ** p < 0.05, *** p < 0.01.

.

In the groups of education level and age, the regression results of the less educated and older groups are consistent with the results of the baseline regression, with a significant positive impact (p < 0.01 and p < 0.05, respectively). Indicating that enhancing environmental education for these groups and improving their environmental knowledge and awareness will be conducive to the implementation of the PAYT policy. However, in the higher educated and younger groups, FEK and FEA do not show a significant impact on WTP for PAYT. The possible reason is that the higher educated and younger groups already acquire a higher level of environmental knowledge or awareness. Moreover, they consider whether to accept the new policy more carefully based on the knowledge and information they have acquired, and they tend to think more rationally about whether it is reasonable to implement the PAYT policy in the local area and whether the government should take more responsibility for environmental issues. Therefore, the effect of FEK is not significant in these groups. It is worth noting that in the older group, FPP has a significant positive effect (p < 0.05) on their WTP for PAYT. The possible reason is that the pollution perception in this paper is the subjective feeling of farmers. The older group has lived in the region for a longer period, and they have more opportunities to be exposed to environmental damage accidents, thereby having a more negative perception of pollution. But they also have a strong emotion of the village and a collective notion, therefore they have higher WTP for PAYT. In addition, there is no difference in the impact of ST between different groups, indicating that most farmers prefer to refer to the behavior of people around them to make their decisions, further proof of the unique substantial influence of social trust in rural China.

Among the southern and northern groups, FEK in the southern group has no significant influence on their WTP for PAYT, while DWD positively affects the WTP (p < 0.01). The significant results of FEA suggest that, because the southern group is closer to the protection area, they are more likely to perceive that the environmental state is closely related to their well-being and therefore possess stronger environmental awareness. Despite having a lower level of environmental knowledge, they still demonstrate a strong willingness to protect the environment. As a result, farmers in the southern group argue that the more waste they generate each day, the more they should pay to compensate for the environmental damage they cause. For the northern group, FEK and ST have a more significant positive impact on their WTP, which may be due to the local government’s efforts to promote the importance of environmental knowledge, thereby enhancing communication and trust between farmers and village cadres. Additionally, whether the differences between the southern and northern foothills are influenced by other factors is worthy of further study.

4.7. Factors Affecting Farmers’ Willingness to Pay for PAYT

According to our sample data, farmers’ environmental knowledge (FEK), farmers’ environmental awareness (FEA) and social trust (ST) have a significantly positive impact on the farmers’ WTP as shown in Figure 1, indicating that the improvement of FEK, FEA and ST will significantly increase farmers’ WTP on PAYT. And farmer’s gender, age, level of education, city, and ratio of civil servants have a significantly positive impact on the farmers’ WTP as shown in Figure 2. The proportion of people over 65 years old has a significant negative impact on WTP.

5. Conclusions

The management of rural household waste is one of the most important tasks in the implementation of a rural revitalization strategy in China. It is necessary to gradually implement the nationwide waste fee management system and promote the volume-based waste fee management system. Our survey found that 70.05% of farmers have never paid waste disposal fees, and their WTP for PAYT is generally low. Further, 48.64% of farmers are willing to pay waste disposal fees by volume, of which 27.29% of farmers choose the lowest level of “0.1–0.2 RMB/0.5 kg”. This is consistent with the characteristics of “high intention and low payment” shown in previous studies [75,76].

This paper explores how farmers’ environmental knowledge, awareness, perception of pollution, daily waste disposal, and social trust affect farmers’ WTP for PAYT. The results show that farmers’ environmental knowledge, environmental awareness and social trust have direct positive effects on their WTP, while the perception of pollution and daily disposal have no effect on their WTP. In addition, social trust, as a unique information transmission network in rural China, can weaken the positive influence of farmers’ environmental knowledge on their WTP. Farmers’ social trust also demonstrates a substitution effect between environmental knowledge and WTP. As farmers’ social trust increases, the frequency of the information exchange among them rises, leading to greater behavioral interaction and influence, thereby enhancing their WTP. This shows that in rural societies, connections between farmers can play a more essential role than professional knowledge. The government could focus on the publicity and guidance of PAYT, so that farmers can subconsciously increase their acceptance of PAYT and form a group identity.

In addition, the farmers’ environmental knowledge in the higher educated and younger groups shows no effect on their WTP, the farmer’s gender, age, and ratio of civil servants have a significantly positive impact on the farmers’ WTP. It was also found that farmers’ environmental knowledge and social trust present no effect on their WTP in the southern group, which is more underdeveloped compared to the central and northern regions in Shaanxi Province. In general, the willingness among different groups is affected by different factors, therefore strengthening environmental education, improving farmers’ awareness of environmental protection, and broadening farmers’ interaction channels are conducive to carrying out the PAYT policy.

According to the above conclusions, we propose the following policy recommendations: First, enhance farmers’ environmental knowledge and awareness through environmental education. A strong foundation of environmental knowledge is crucial for farmers to become aware of environmental issues and to strengthen their environmental consciousness. Only with proper guidance on environmental matters can farmers increase their environmental awareness and promote pro-environmental behavior. Through the gradual cultivation of environmental knowledge, we can inspire farmers’ positive attitudes towards environmental protection, leading them to more actively embrace the waste disposal charging policies.

Second, leverage the active leadership role of village cadres and community organizations. The active participation of village cadres in the “pay as you throw” waste policy will significantly encourage other farmers and reduce their distrust of the policy. Additionally, community information dissemination should be utilized effectively, and channels for policy publicity should be expanded. This will allow farmers to fully understand the benefits of the waste disposal charging policy, creating a positive cycle of widespread participation in waste management and environmental protection.

Third, tailor the introduction of a new policy to local conditions. Different policies can be implemented in different regions based on an investigation of local conditions and should be gradually promoted. For instance, in areas with higher economic income, the formulation of specific small fees can be informed by scientific research, such as that presented in this manuscript, to ensure that the charging standards are scientific and reasonable. In economically weaker regions, the advantages of the policy should be emphasized, possibly accompanied by appropriate subsidies.

Although this is a case study, the sample within it is highly representative and the research method is reliable, which is of reference significance for China’s relatively backward western region. More specifically, we identified the key factors influencing WTP, thereby providing a basis for subsequent policymaking. Moreover, the value of WTP can serve as a valuable reference for setting prices in waste charging systems in other less developed areas. Overall, our research can be generalized for governments in underdeveloped mountainous areas to further promote waste management policy and establish a fee-based management system.

Given the complexity of the process by which awareness translates into action, further research could explore the causal relationship by means of experimental research. Additionally, we also plan to enlarge the sample size and reduce bias to improve the universality and applicability of our findings.