Research on Capital Endowment, Energy Cognition and Willingness to Pay for Green Energy Consumption of Urban and Rural Residents in China

Abstract

The willingness to pay (WTP) for green energy consumption not only indicates the public’s green energy consumption practices, but also affects the realization of China’s “dual carbon” goals and global green development. Based on data from the 2018 Chinese General Social Survey (CGSS), this study describes the WTP for green energy consumption of Chinese urban and rural residents in the context of “dual carbon”. Moreover, it provides an in-depth interpretation from the perspectives of capital endowment and energy cognition, guided by social practice theory (SPT). This study found that, firstly, the public’s WTP for green energy consumption needs to be strengthened urgently, and the percentage of the refusal to participate group reaches 41.44%, and shows significant urban–rural differences. Compared with rural residents, the proportion and amount of WTP for urban residents are 7.5% and 4.016 CNY/month higher, respectively. Secondly, capital endowment and energy cognition are important influencing factors. Among them, economic capital (β = 0.647, p < 0.01) and cultural capital (β = 0.358, p < 0.05) play a significant role for urban residents, while rural residents depend on the government support cognition of energy (β = 7.678, p < 0.001). Finally, the urban–rural divergence in WTP for green energy consumption mainly stems from the gap in capital endowment, which contributes 29.08%, significantly higher than the contribution of energy cognition (8.34%). Therefore, efforts should be made to enhance the capital endowment levels of urban and rural residents, implement a targeted energy knowledge dissemination system, build a comprehensive government support system, and break down institutional barriers through urban–rural integration to guard against the disadvantages of rural residents.

1. Introduction

Since its reform and opening up, China has achieved remarkable historical accomplishments in its economic development, transforming from a poor and weak country to the world’s second-largest economy [1]. From 1978 to 2023, China’s annual average gross domestic product (GDP) growth rate was 8.9%, significantly higher than the 3% growth rate of the world economy during the same period. This economic development cannot be supported without energy. Energy is the foundation of a country’s economy, the lifeblood of the national economy and the core of economic growth [2]. With the continuous growth of China’s economy since its reform and opening up, the total amount of energy production and consumption has also been increasing [3]. In 1978, China’s energy consumption was only 570 million tons of standard coal; by 2023, China’s energy consumption has reached 5.72 billion tons of standard coal, an increase of more than 10 times. In terms of energy production, China’s primary energy production grew from 630 million tons of standard coal in 1978 to 4.83 billion tons of standard coal in 2023, an increase of 7.67 times. At present, China’s energy supply and demand relationship is tense, there is a large energy gap, and mainly by imported fossil energy to supplement. In 2023, China imported 474.42 million tons of coal, 563.99 million tons of crude oil and 119.97 million tons of natural gas. As a result, there is a close correlation between economic growth and energy consumption, and the rapid development of China’s economy since the reform and opening up has also led to an increase in the pressure on energy consumption and a rising demand for energy to support economic growth.

The development and utilization of energy has led to China’s great economic achievements, but at the same time, it has also brought about serious ecological and environmental problems [4]. Some studies have shown that about 70% of CO₂ emissions, 90% of SO₂ emissions and 67% of NO_x emissions in the air come from the use of fossil fuels [5]. Due to various constraints, China’s energy consumption structure has long been dominated by fossil energy, of which coal has the largest proportion. According to the “China Mineral Resources Report (2024)”, in 2023, the proportion of coal consumption in China was 55.3%, while oil and natural gas accounted for 18.3% and 8.5%, respectively. It can be seen that the proportion of fossil energy consumption in China is as high as 82.1 percent, and fossil energy consumption is the main source of environmental pollutants and greenhouse gas emissions [6,7]. In terms of environmental pollution, the use of fossil energy generates a large amount of pollutants, including soot, sulfur dioxide, and nitrogen oxides, which cause environmental problems such as air pollution, water pollution, and solid waste pollution. According to the “2023 China Ecological and Environmental Status Bulletin”, 40.1% of cities in China fail to meet the standards for environmental air quality. In terms of greenhouse gas emissions, China remains the world’s largest carbon emitter. In 2023, China’s energy-related carbon dioxide emissions reached 12.6 billion tons, accounting for 31.2% of the global total. This figure exceeds the combined total of the entire Western Hemisphere and Europe. China’s climate bulletin showed that in 2024, the national average temperature was 10.9 degrees Celsius, the highest in history since 1951, and the national average precipitation was 697.7 mm, 9.0 percent more than normal, seriously affecting agricultural production and economic development.

In response to the energy and environmental problems associated with economic growth, the Chinese government began to promote “energy conservation and emission reduction” in 2006, and listed a 20% reduction in energy consumption per unit of GDP and a 10% reduction in emissions of major pollutants as binding targets. In recent years, China has taken the “Dual Carbon” goals as a guide to promote the in-depth development of “energy conservation and emission reduction”. In September 2020, the Chinese government stated in the General Debate of the 75th session of the UN General Assembly that “China will enhance its nationally owned contribution and take stronger policy measures to strive to peak carbon dioxide emissions by 2030, and endeavor to achieve carbon neutrality by 2060 [8].” (the “Dual Carbon” goals). Subsequently, China promulgated and implemented policies such as the “Action Program for Peak Carbon by 2030” to actively promote the “Dual Carbon” goals and start a new journey of green development. Among them, energy transition constitutes an important element of the “Dual Carbon” strategy and is a key element in achieving the “Dual Carbon” goals [9]. Currently, China’s carbon emission structure is directly linked to its traditional resource endowments, with coal-fired power plants, steel, and cement industries accounting for over 60% of the national total emissions, among which the power sector is the main contributor [10]. Therefore, Increasing the proportion of green and renewable energy is an important goal of energy transition, and wind and solar power generation are the engines driving the energy revolution in China’s power industry [11]. The 14th Five-Year Plan for Building a Modern Energy System (2021–2025)” also emphasizes building a modern energy system, accelerating the development of non-fossil fuels, significantly increasing the scale of wind and solar power, promoting a gradual increase in the share of new energy, and optimizing the combination of coal and new energy [12].

However, in the process of green energy transformation, past focus has been on the supply side, primarily for research into specific technologies, materials, or policies, such as low-carbon technology subsidy policies [13,14,15]. In fact, the energy strategy should not only guarantee supply, but also guide demand, especially in the new situation of continuous supply of green energy, to promote the revolution of energy production and consumption, it is urgent to make efforts on the demand side, and to effectively encourage green energy consumption [16]. In 2022, China issued the “Opinions on Improving the Institutional Mechanisms and Policy Measures for the Green and Low-Carbon Transition of Energy”, which emphasized the need to establish and improve mechanisms to promote green energy consumption, encouraging society-wide prioritization of green energy utilization and procurement of green products and services [17]. Research shows that issues related to green energy and technological products are hotspots in scientific research and application. The public’s willingness to pay (WTP) is a key node for its application, and the influencing factors are one of the important problems to solve this node. However, at present, there is a lack of discussion on the public’s WTP for green energy consumption, and the WTP is rarely correlated with the amount of emission reduction [18]. Therefore, this study focuses on the energy consumption perspective (demand side), aiming to explore Chinese residents’ WTP for green energy consumption, with a special focus on analyzing its distributional differences under China’s dual structure.

The rest of this study is arranged as follows. Section 2 is the literature review, which sorts out the definition, measurement and current state of research on WTP for green energy consumption. Section 3 is the theoretical analysis and research hypothesis, which introduces Bourdieu’s social practice theory as a theoretical framework and puts forward the research hypothesis in the context of China’s dual structure. Section 4 is the research design, which includes the data sources and participants, measurements, and the choice of research strategies and modeling methods. Section 5 is the results, which describes the urban–rural differences in Chinese residents’ WTP for green energy consumption and their influencing factors. Section 6 is the discussion, which compares the similarities and differences between this study and related studies. Section 7 is the conclusion and recommendations.

2. Literature Review

2.1. Definition and Measurement of WTP for Green Energy Consumption

WTP for green energy consumption, as a quantitative measure of consumer acceptance of premium prices for clean energy products and services, has become an important area of research to drive the energy transition. Currently, the main methods for measuring WTP for green energy consumption include Revealed Preference Methods (RPM) and Stated Preference Methods (SPM) [19]. Among them, RPM is a method to infer consumers’ WTP by observing their actual choice behavior in the market. The two most commonly used methods for measuring explicit preferences include hedonic pricing and travel cost [20]. The former estimates the economic value of certain environmental goods, such as clean air or attractive scenery, while the latter infers the WTP by estimating the travel costs that consumers incur in obtaining green energy products or services [21].

Unlike the RPM, the SPM does not rely on actual market transaction data. It is a method that directly asks consumers about their WTP for green energy consumption through hypothetical market scenarios. The commonly used methods include the Contingent Valuation Method (CVM) and the Choice Experiment (CE) [22]. The former describes a hypothetical green energy product or service to the respondents and asks them what the highest price they would be willing to pay for it. The latter presents a series of green energy product combinations with different attribute levels (such as price, environmental protection level, reliability), and asks the respondents to choose the option they prefer to infer their WTP [23].

Compared with the RPM, the SPM can be used to assess the value of a wider range of environmental goods or services. In academic research, the SPM is favored because it can provide richer data and greater flexibility. For example, CVM is widely used in environmental economics to evaluate the non-use value of environmental goods. Moreover, the SPM is also easier to operate and interpret, and can better reflect consumers’ subjective preferences and value judgments [24].

2.2. Research on Residents’ WTP for Green Energy Consumption

Against the backdrop of advancing global climate governance and China’s deepening “Dual Carbon” goals, the results of research on WTP for green energy consumption are becoming increasingly abundant.

Nowadays, more and more residents prefer to adopt sustainable production and lifestyles. “The Sustainability Trends Report 2023” shows that more than half (53%) of shoppers say they prioritize sustainable products. Several studies have also shown that consumers have become more willing to pay higher prices for green energy and to purchase foods with a lower carbon impact. For example, 67% of consumers in the United States support the purchase of green products for environmental reasons, and 51% are willing to pay a higher price for these products. In Europe, the proportion of customers willing to pay higher prices for green products increased from 31 per cent in 2005 to 67 per cent in 2008 [25]. In China, the implementation of the “Dual Carbon” strategy has also had a profound impact on people’s green consumption. “Survey Report on Green, Low-Carbon and Sustainable Trends in China’s Consumer Market (2023)”, consumers’ emphasis on green and low-carbon consumption has increased significantly, especially in first-tier cities such as Beijing, Shanghai and Guangzhou. However, the current consumption of green energy by Chinese residents is characterized by the paradox of “high acceptance-medium premium”. For example, Lin and Xie’s empirical study of Chinese residents showed that while 97.9 percent of respondents were willing to use green electricity, only 63.1 percent were willing to pay more for it [26].

However, the distribution of residents’ WTP for green energy consumption is not equalized, and relevant studies have shown that there are significant group differences, which are manifested in the stronger WTP for green energy consumption of structurally advantaged groups. In terms of spatial structure, urban residents are more supportive of green energy consumption than rural residents. For example, Ouyang et al. showed that people living in urban areas (e.g., city centers) have higher WTP than those in other areas [27]. Moreover, Peng et al.’s study also showed that the length of time living in urban areas is positively correlated with residents’ WTP for green energy [28]. In terms of socio-economic structure, those with high class status are more inclined to green energy consumption. For example, Kowalska-Pyzalska’s study showed that income, education, and knowledge play an important role in explaining consumers’ WTP for green electricity, and those with more income, education, and knowledge are more willing to pay for green electricity [29]. Wang and Lei’s study [30] further showed that, on the one hand, individuals with higher levels of income, higher levels of education, and higher social classes are more willing to pay for green energy. However, on the other hand, with changes in society (e.g., economic development, popularization of environmental education, and changes in values), the environmental awareness and WTP for environmental protection of the lower-class groups will significantly increase, and the gap between different classes will narrow [30].

So far, scholars have mostly included demographic characteristics, socio-economic attributes, psychological perceptions, cultural concepts, and energy policies as influencing factors on WTP for green energy consumption in their studies. In terms of demographic characteristics, gender and age received the most attention. Of these, the effect of gender was inconsistent, while age was more consistent. For example, Dogan and Muhammad have found women to have a negative relationship with WTP for green energy, while Hojnik et al. have not found any significant difference among women and men related to WTP for green energy. In addition, they have also found that younger people are more willing to pay for green energy consumption [31]. In terms of socio-economic attributes, previous studies have shown that residents’ WTP for green energy varies with education, income and social status. In most cases, consumers with better socio-economic status may be ready to pay a premium for green products, which is in line with Maslow’s hierarchy of needs theory, which does not force a jump to higher levels of consumer demand [32].

In terms of psychological perceptions, psychological factors such as energy cognition, environmental attitude, environmental belief, and values can significantly influence the WTP for green energy consumption. Existing studies have shown that the more fully an individual understands energy, the more positive their environmental attitude is, and the more likely they are to purchase green products or services [33]. In terms of cultural concepts, regional cultures such as collectivism, individualism, historical traditions, folk customs and religious beliefs are closely related to residents’ WTP for green energy consumption. For example, Cho and Jung’s study shows that collectivism is positively associated with high environmental awareness and WTP for green consumption, and that collectivism contributes to individual WTP for green consumption even among low environmental awareness groups [34]. In terms of energy policies, supportive policies such as new energy subsidies, tax incentives and infrastructure development have significantly boosted residents’ WTP for green energy consumption. For example, the research by Yoo and Kwak, using the contingent valuation (CV) evaluation method, revealed the positive impact of the South Korean government’s initiative to increase the proportion of green electricity supply on residents’ WTP green consumption [35].

Therefore, previous studies have laid a solid foundation for this study. Meanwhile, in China’s “Dual Carbon” context, although existing studies have revealed differences in residents’ WTP for green energy consumption, they have not made enough comparisons between urban and rural residents, nor have they explored the complex influencing mechanisms behind the differences, and this study can help to make up for the above shortcomings.

3. Theoretical Analysis and Research Hypothesis

3.1. Theoretical Analysis

Research on residents’ WTP for green energy consumption has long been dominated by two theoretical paradigms: traditional economics (i.e., rational choice theory), which views residents as utility-maximizing “economic beings” and argues that payment decisions are rooted in cost–benefit calculations, and the social psychological model, which emphasizes the determinative role of individual attitudes, values, and other psychological factors [36]. However, they do not explain why residents who claim to support environmental protection often refuse to pay a premium for green energy consumption.

Social Practice Theory, proposed by the famous French sociologist Pierre Bourdieu, provides a strong and irreplaceable theoretical basis for interpreting residents’ WTP for green energy with its profound relational thinking and dissection of deep social structures [37]. It transcends the limitations of traditional economics (i.e., rational choice theory), which reduces WTP to a “price-preference” relationship, and breaks through the framework of social psychology, which focuses on the attitudes of individuals, and places this economic decision in a broad socio-cultural field, revealing its nature as a social practice.

The theoretical framework consists of three core concepts: Field, Capital and Habitus [38]. Bourdieu reveals the practice of actors with the simple formula “Field + [(Capital) (Habitus)] = Practice”. According to his views, the practice of actors belongs neither to objective factors nor to pure consciousness, but to the everyday activities of people in the field with their respective capitals and guided by habitus. Among them, “Field” is the space of social practice, which refers to the network and configuration of objective relations between positions, and is the space where individuals act correspondingly on the basis of themselves. “Capital” is the tool of social practice, and unlike Marx’s capital, it is not only limited to the economic field, but also extends to the symbolic and immaterial fields, mainly including economic capital, social capital and cultural capital. “Habitus” is the idea or logic of social practice, referring to the system of dispositions and tendencies internalized by individuals in their long-term social experience, which shapes their perception, evaluation and action in the world [39].

Social practice theory answers the questions of where the actors practice, what they practice, and how they practice (i.e., field, capital, and habitus). In addressing these three concepts, Bourdieu maintains an openness to the idea that concepts can only gain true meaning in a relational system and argues for defining these three concepts as they function. This gives the theory of social practice a universal application and opens up the possibility of using the theory to explore the WTP for green energy consumption in practice for both urban and rural residents.

3.2. Research Hypothesis

3.2.1. Field Characteristics and Urban–Rural Differences in WTP for Green Energy Consumption

In social practice theory, the field consists of a relatively autonomous social micro-world, a space of objective relations with its own logic and necessity, as well as the place and contradictory forms of residents’ green energy consumption practices [40]. Therefore, the study of residents’ WTP for green energy consumption must pay attention to the characteristics of the field in which it is located.

Similar to other countries in the world, China also has an “urban-rural dual structure” in the process of modernization, i.e., for a long period of time, it is a dual structure consisting of modern industry in the city and traditional agriculture in the countryside. It can be seen that urban and rural fields are not only different in terms of geographical space, but also different in terms of the network relations formed by the interconnection of various nodes of capitals, subjects of action and habits, and thus have relative independence. The urban and rural fields have different “logics and necessities”, and each has its own special interests and roles [41].

In the 1950s, China opted for a dualistic development model in order to escape poverty and modernize the country. In 1958, the “Regulations of the People’s Republic of China on Registration of Households” established a household registration system that separated urban and rural fields, dividing all residents into agricultural and non-agricultural households, and restricting the transfer of people from rural to urban fields. In addition to the household registration system, the State has also introduced a series of policies in the areas of the food and oil supply system, the labor and employment system, and the social security system. These policies have separated the urban population from the rural population, creating a dual structure of Chinese characteristics in which the status of citizens (workers) and peasants is closed and the urban and rural areas are separated. Since 1978, although there has been large-scale population mobility in China, it is still difficult for the rural population entering the cities to enjoy equal rights to employment, education, social security and so on, because the core barriers built on the household registration system remain unchanged [42]. Moreover, the previous crude-scale urbanization, while raising the rate of urbanization, has severely constrained the development of rural areas and rural populations, widening the gap between urban and rural areas to a certain extent, and is attracting great attention from the Government [43].

Under the dual structure, urban–rural differences have led to the divergence of Chinese residents’ WTP for green energy consumption. Urban residents are more inclined to support and participate in green energy consumption due to their advantages in education, income and environmental awareness. On the contrary, rural residents are constrained by a variety of conditions that reduce their willingness and ability to pay for green energy consumption, leading to a widening gap between urban and rural environments [44]. Dunlap et al. summarize the five major assumptions of scholars since the 1970s about the social basis of environmental concern, one of which is “The Residence Hypothesis”, pointing out that urban–rural differences exist, and urban residents are more concerned about the environment than rural residents [45].

Hypothesis 1.

Urban residents are more willing to pay for green energy consumption than rural residents.

3.2.2. Capital Endowment and WTP for Green Energy Consumption of Urban and Rural Residents

Social practice theory states that capital is the resources and leverage of practice. Capital is a set of resources and power that can be used, and individuals have different capital endowments that determine their position and practices in the field [46]. According to Bourdieu, capital endowment is an important condition that restricts the practice of an individual, and only by possessing a minimum amount of capital can an individual’s practical behavior make sense. Therefore, when the public decides whether they are willing to pay for green energy consumption, they will definitely consider their capital endowment, and in comparison, the more capital endowment an individual has, the stronger their willingness to pay for green energy consumption [47].

Meanwhile, Bourdieu expanded capital mainly into economic capital (e.g., money), cultural capital (e.g., education), and social capital (e.g., networks) [39]. Among them, economic capital is the material support to ensure public participation in green energy consumption: the more economic capital an individual has, the more they demand higher quality of life and ecological environment, and the stronger the willingness to consume green energy; cultural capital is the technical or knowledge support to ensure public participation in green energy consumption: the more cultural capital an individual has, the more they recognize the importance of green energy consumption, and the stronger the willingness to pay; social capital is the information or normative support to ensure public participation in green energy consumption. Social capital is the information or normative support for public participation in green energy consumption. The more social capital an individual has, the better the accumulation of their own resources, the greater the capacity and the better the demonstration and guidance effect for participation in green energy consumption [48]. The specific hypotheses are as follows:

Hypothesis 2.

The more capital endowment the public has, the stronger the WTP for green energy consumption.

Hypothesis 2a.

The more economic capital the public has, the stronger the WTP for green energy consumption.

Hypothesis 2b.

The more cultural capital the public has, the stronger the WTP for green energy consumption.

Hypothesis 2c.

The more social capital the public has, the stronger the WTP for green energy consumption.

As Bourdieu argued, the practice depends on the capital endowment of individuals in a given field. Differences in capital endowments affect the willingness to pay for green energy consumption of urban and rural residents. Due to the long-term influence of the dualistic structure, there is a huge development gap between urban and rural fields, and the capital endowment of urban and rural residents is also clearly differentiated [49]. Ye Lu et al. found through the panel data of 31 provinces and cities across the country that the dual structure has not yet been completely broken, and multidimensional urban–rural residents’ gap measurement indicators such as economic capital are still significant [50]. In summary, capital endowment is an indispensable objective constraint on the public’s WTP for green energy consumption, while the dual social structure has led to the differentiation of capital endowment between urban and rural residents, which in turn has brought about differences in their WTP for green energy consumption.

Hypothesis 3.

Capital endowment is the objective mechanism of the difference in WTP for green energy consumption between urban and rural residents.

3.2.3. Energy Cognition of Individual Habitus and WTP for Green Energy Consumption of Urban and Rural Residents

Social practice theory also states that practice consists of capital and habitus, and is the everyday activity of individuals in a certain field with their respective capital guided by habitus [51]. Habitus is the subjective debugging of an individual’s objective position and is the result of the internalization of external structures in experience. Habitus specifically manifests itself in the public’s practice of green energy consumption in the form of energy perceptions [52]. Thus, in addition to capital endowment, the public’s willingness to participate in green energy consumption also depends on energy cognition, and positive energy cognition will enhance their willingness to pay for green energy consumption.

Energy cognition refers to the overall understanding of energy, particularly related issues such as energy consumption, formed by the public. Energy cognition is an overarching concept that encompasses multiple dimensions. Referring to the existing relevant studies and considering the objects related to energy (i.e., the government supply subjects, energy and public consumption subjects), energy cognition is divided into government support cognition of energy, environmental impact cognition of energy and personal efficiency cognition of energy. Moreover, the more positive the public’s government support cognition, the greater the political legitimacy and external driving force for energy, promoting a shift towards green energy consumption; the more positive the public’s environmental impact cognition, the higher the value legitimacy and acceptance of energy, attracting public participation in green energy consumption; the more positive the public’s personal efficacy cognition, the greater the social legitimacy and sense of responsibility, stimulating the public’s WTP for green energy consumption [53]. The specific hypotheses are as follows:

Hypothesis 4.

The more positive the public’s energy cognition, the stronger the WTP for green energy consumption.

Hypothesis 4a.

The more positive the public’s government support cognition of energy, the stronger the WTP for green energy consumption.

Hypothesis 4b.

The more positive the public’s environmental impact cognition of energy, the stronger the WTP for green energy consumption.

Hypothesis 4c.

The more positive the public’s personal efficiency cognition of energy, the stronger the WTP for green energy consumption.

For Bourdieu, habitus as a subjective mental structure guides practice [49]. Differences in habitus shape the distribution of WTP for green energy consumption among urban and rural residents. In the context of the dual structure, the environmental cognition of urban and rural residents, including energy cognition, are very different, and the environmental concerns and cognition of rural residents are worse than those of urban residents. For example, Nie’s empirical study based on China found significant differences between urban and rural residents in terms of the severity of energy and environmental problems, pollution risks and awareness of protection responsibilities [54]. Specifically, compared with urban residents, rural residents’ awareness of energy and the environment lags behind relatively [54]. In summary, energy cognition is an indispensable subjective constraint on the public’s WTP for green energy consumption, while the dual structure also leads to the differentiation of urban and rural residents’ energy cognition, bringing about differences in their WTP for green energy consumption.

Hypothesis 5.

Energy cognition is the subjective mechanism of the difference in WTP for green energy consumption between urban and rural residents.

4. Research Design

4.1. Data Sources and Participants

The data analyzed in this paper come from the China General Social Survey (CGSS) organized and implemented by Renmin University of China in 2018 [55]. The survey adopts multistage stratified probability proportional to Size (PPS) random sampling: first, according to the administrative division setup information of “China Statistical Yearbook 2009”, a sample stratum of 2003 counties (districts) is selected; second, in each sample county (district), four village committees or neighborhood committees are selected; third, in each selected neighborhood committee or village committee, 25 households are selected; and finally, within the selected households, the whole population aged 18 and above is listed, and one person is randomly selected as the final respondent.

Compared with other years’ surveys, CGSS2018 sets up a special “energy module”, including energy access and use, energy attributes and perceptions, energy subsidies and policies, and willingness to pay for energy consumption, which meets the research needs of this paper. Therefore, we selected the survey sample for the “energy module”, and the final total sample included in the analytical model is 2997, of which 1169 were urban samples and 1828 were rural samples.

4.2. Measurements

4.2.1. Dependent Variable

WTP for green energy consumption is the dependent variable. Previous studies have shown that the CVM is a representative appraisal tool for measuring the public’s WTP, which estimates the value of a product or service by using a questionnaire to examine the economic behavior of individuals in a hypothetical market in order to obtain their willingness to pay [56]. Moreover, compared with other assessment methods such as Experimental Auctions, Hedonic Pricing and Travel Cost, the CVM does not need to rely on real market transaction data, and it is simple and easy to be understood by the respondents, so it has become the most commonly used method for scholars to conduct willingness-to-pay studies [22].

Therefore, this paper also uses the conditional value method to measure the public’s WTP for green energy consumption with reference to Huang et al. (2020) [18]. At the same time, considering that wind power and photovoltaic (PV) technologies are the focus of China’s energy consumption transition under the “dual-carbon” goal, we use “wind power and PV” to represent green energy [18]. The question reads “If you increase the amount of wind and PV power generation to 10 kWh per 100 kWh of electricity consumed by your household, you would be willing to pay an additional monthly electricity bill of _____ yuan per month (Note: Currently, about 7 kWh out of 100 kWh of electricity consumed by an average household in China is generated by wind or PV power, which is slightly more costly.)”.

4.2.2. Categorical Variable

From social practice theory, it is clear that field (i.e., a space constituted by various social relations) is the practical space in which the public engages in green energy consumption, and that urban–rural identity is a central categorical variable that reveals the dual structure pattern of the field [41]. Urban–rural identity is determined by the type of household registration. The measurement question is “What is your current hukou (i.e., household registration) status?” from CGSS2018, and the options “Agricultural hukou” and “Resident hukou (formerly agricultural hukou)” are combined to form the rural population; “Non-agricultural hukou” and “Resident hukou (formerly non-agricultural hukou)” are combined to form the urban population.

4.2.3. Independent Variable

Social practice theory states that capital endowment and energy cognition of individual habitus are the core independent variables affecting public green energy consumption [35]. Among them, capital endowment includes economic capital, cultural capital and social capital. Economic capital is measured by “What was your total income for the whole year last year?” with responses taken as natural logarithms (Ln). Cultural capital is measured by “What is your highest level of education currently”: with responses converted to corresponding years of education. Social capital is measured through social networks [57], and the specific question item is “In the past year, have you often engaged in the following activities in your free time?—Socializing (i.e., meeting with friends).”.

Energy cognition consists of government support cognition of energy, environmental impact cognition of energy and personal efficiency cognition of energy. Government support cognition of energy is measured by “How familiar are you with the following energy policies?—Subsidies for residential photovoltaic power stations,” with responses categorized as “familiar” or “unfamiliar”. Environmental impact cognition of energy is measured by “To what extent do you agree with the following statement?—The use of energy is a major cause of the greenhouse effect,” with responses categorized as “agree” or “disagree.” Personal efficiency cognition of energy is measured by “To what extent do you agree with the following statement?—The role of individuals in controlling energy consumption and improving the environment is very limited,” with responses categorized as “agree” or “disagree”.

4.2.4. Control Variables

According to the existing relevant studies, demographic sociological and regional environmental variables are regarded as control variables [31]. Among them, demographic sociological variables include gender, age, religious belief, health status and marital status; Regional environmental quality variables are measured by air quality (

Table 1. Statistical description of variables.

Variable Name			Variable Definition and Assignment	Mean	Standard Deviation
Dependent variable	WTP for green energy consumption		WTP for wind and PV ($)	11.036	24.967
Categorical variable	Urban–rural identity		Hukou attributes (Rural population = 1; Urban population = 0)	0.609	0.488
Independent variable	Capital endowment	Economic capital	Annual income (Ln)	8.419	3.822
		Cultural capital	Educational attainment (No education = 0; Private school, literacy class = 3; Elementary school = 6; Junior high school = 9; Vocational high school/general high school/secondary school/technical school = 12; University college = 15; Undergraduate degree = 16; Postgraduate and above = 19)	8.961	4.761
		Social capital	Socializing/hanging out (Never = 1; Rarely = 2; Sometimes = 3; Often = 4; Very often = 5)	2.724	1.054
	Energy cognition	Government support cognition of energy	Understanding of residential PV plant subsidies (No understanding = 0; Understanding = 1)	0.104	0.305
		Environmental impact cognition of energy	Energy use is the main cause of the greenhouse effect (Disagree = 1; Agree = 0)	0.348	0.476
		Personal efficiency cognition of energy	Individuals have a very limited role in controlling energy consumption and improving the environment (Disagree = 0; Agree = 1)	0.590	0.491
Control variables	Age		Age (Years)	35.131	15.533
	Gender		Gender (Female = 0; Male = 1)	0.471	0.499
	Religious belief		Religious belief (No = 0;Yes = 1)	0.103	0.304
	Health status		Physical health (Very unhealthy = 1; Relatively unhealthy = 2; Average = 3; Relatively healthy = 4; Very healthy = 5)	3.560	1.076
	Marital status		Marriage (Without marriage partner = 0; With marriage partner = 1)	0.784	0.411
	Regional environmental quality		The air quality in the area where I live is very good (Strongly Disagree = 1; Disagree = 2; Indifferent = 3; Agree = 4; Strongly Agree = 5)	3.435	1.123

).

4.3. Research Strategy and Statistical Modeling

According to the research question, this paper is divided into the following three steps: the first step is to describe the overall situation of the public’s WTP for green energy consumption and to make urban–rural comparisons. Specifically, continuous data were described as Mean ± Standard Deviation, and Independent Samples t-test was used to compare between two groups or one-way analysis of variance among multiple groups. Categorical data were described as frequency (%), and Chi-square test was used to compare the distribution of the categorical variables.

The second step is to explore and compare the relevant factors affecting urban and rural residents’ WTP for green energy consumption. Since the dependent variable (i.e., WTP for green energy consumption) is a continuous variable and the independent variables include capital endowment and energy cognition, etc., this paper adopts a multiple linear regression model for estimation [58]. The expression of this regression model is shown in Equation (1):

$$Y_i=\alpha +{\beta }_1{X}_1+{\beta }_2{X}_2+{\beta }_3{X}_3\dots \dots +{\beta }_{\mathrm{i}}{X}_{\mathrm{i}}+\epsilon$$

(1)

where Y_i is the WTP for green energy consumption, α is the estimated coefficient of the constant term, X₁, X₂, X₃ … X_i is a set of explanatory variables including economic capital, cultural capital, social capital, etc., β₁, β₂, β₃ … β_i, are the estimated coefficients of the corresponding explanatory variables, and ε is the random error term.

The third step is to further analyze the causes of urban–rural differences in the public’s WTP for green energy consumption on the basis of the previous two steps, i.e., to explore how urban–rural identity affects the divergence of the public’s WTP for green energy consumption. Therefore, firstly, the roles played by capital endowment and energy cognition between urban–rural identity and WTP for green energy consumption are analyzed. As it involves the decomposition of multiple effects such as capital endowment and energy cognition, the Karlsson-Holm-Breen (KHB) method is used, which has been shown to present their complex effects more comprehensively and with higher statistical validity [59]. Next, the paper further analyzes the contribution of capital endowment and energy cognition to the urban–rural differences in WTP for green energy consumption. The Oaxaca-Blinder decomposition is a classic tool for examining the causes of intergroup differences proposed by Oaxaca and Blinder in 1973. And as in previous studies, this method is used in this paper to measure the effects of capital endowment and energy cognition [60]. The decomposition formula is:

$${\overline{\mathit{W}}}_{\mathrm{u}}-{\overline{\mathit{W}}}_{\mathit{r}}=({\overline{\mathit{X}}}_{\mathit{u}}-{\overline{\mathit{X}}}_{\mathit{r}}){\widehat{\beta }}_{\mathit{r}}+({\widehat{\beta }}_{\mathit{u}}-{\widehat{\beta }}_{\mathit{r}}){\overline{\mathit{X}}}_{\mathit{u}}$$

(2)

where ${\overline{\mathit{W}}}_{\mathit{u}}$ and ${\overline{\mathit{W}}}_{\mathit{r}}$ denote the average level of WTP for green energy consumption of urban and rural residents, respectively; ${\overline{X}}_u$ and ${\overline{X}}_r$ denote the mean values of a series of personal characteristics of urban and rural residents, respectively. As a result, the urban–rural differences in WTP for green energy consumption are divided into two parts: the first part on the right side of the equation is the explainable part due to differences in individual characteristics such as capital endowment and energy perceptions among urban and rural residents, while the second part on the right side of the equation consists of the unexplainable part due to differences in returns to characteristics.

5. Results

5.1. Urban–Rural Comparison of WTP for Green Energy Consumption

According to the measurement question “If you increase the amount of wind and PV power generation to 10 kWh per 100 kWh of electricity consumed by your household, you would be willing to pay an additional monthly electricity bill of _____ yuan per month”, the respondents’ answers are categorized into “types of willingness to pay” and “amounts of willingness to pay”, to better present the distribution of green energy consumption among urban and rural residents. As shown in

Table 2. Urban and rural residents’ WTP for green energy consumption.

Types of WTP	Unwilling (%)	Willing (%)	Difference Test
The whole population	41.44	58.56
Urban population	36.87	63.13	χ2 = 16.511, p < 0.001
Rural population	44.37	55.63
Amounts of WTP	Mean ($)	Standard Deviation ($)	Difference Test
The whole population	11.036	24.968
Urban population	13.486	26.717	t = 4.308, p < 0.001
Rural population	9.470	23.656

below.

On the one hand, “Types of WTP” defines the nature of public participation in green energy consumption. Among all residents, 58.56% are “willing” to participate in green energy consumption, which belongs to the “medium” category, but there is a significant difference between urban and rural residents, with 63.13% of urban residents “willing” to participate in green energy consumption, while the proportion of rural residents is only 55.63%. On the other hand, “Amounts of WTP” defines the level of public participation in green energy consumption. Among all residents, the average “willingness” to pay for green energy consumption is $11.036, which is lower than that of urban residents ($13.486) and higher than that of rural residents ($9.47).

The results in Table 2 indicate that urban residents have a stronger willingness to pay for green energy consumption compared to rural residents, and this is further verified in the multiple linear regression model estimates in

Table 3. The impact of rural–urban identity on the public’s willingness to pay for green energy consumption.

Variable Type	Model 1.1 (The Whole Population)	Model 1.2 (The Whole Population)
	β	β
Control variable
Gender (Female = 0)		−0.207
Age		−0.582 ***
Age squared		0.004 **
Religious belief (No = 0)		0.763
Health status		0.866 *
Marital status (Without marriage partner = 0)		1.601
Regional environmental quality		−0.851 *
Independent variable
Urban–rural identity (Urban population = 0)	−4.016 ***	−3.613 ***
Constant	13.486 ***	29.734 ***
F	18.56 ***	10.99 ***
R2	0.006	0.029

Note: * p < 0.05, ** p < 0.01, *** p < 0.001.

. Model 1.1 shows that the regression coefficient of urban–rural identity is −4.016 and passes the test at the significance level of 0.001, i.e., the willingness to pay for green energy consumption of rural residents is 4.016 units lower compared to urban residents. Model 1.2 controls for demographic sociological and regional environmental variables, and the regression coefficient for urban–rural identity changes but remains negative (−3.613) and passes the test at the 0.001 level of significance. In summary, urban residents’ WTP for green energy consumption is better than rural residents, and Hypothesis 1 is supported.

5.2. Influencing Factors of WTP for Green Energy Consumption and Urban–Rural Comparison

What factors influence the public’s WTP for green energy consumption, which in turn leads to differences in its distribution between urban and rural fields? Under the guidance of Bourdieu’s social practice theory, this paper examines two types of factors, namely capital endowment and Energy cognition of individual habitus, and compares their impacts on urban and rural residents, in order to test whether there is consistency in the social basis of urban and rural residents’ WTP for green energy consumption?

In

Table 4. Influencing factors of urban and rural residents’ WTP for green energy consumption.

Variable Type	Model 2.1 (The Whole Population)	Model 2.2 (Urban Population)	Model 2.3 (Rural Population)
	β	β	β
Control variable	Controlled	Controlled	Controlled
Categorical variable
Urban–rural identity (Urban population = 0)	−1.917	——	——
Independent variable
Capital endowment
Economic capital	0.334 **	0.647 **	0.217
Cultural capital	0.269 *	0.358 *	0.198
Social capital	0.594	0.962	0.345
Energy cognition
Government support cognition of energy	3.743 *	−0.793	7.678 ***
Environmental impact cognition of energy	0.542	1.979	−0.286
Personal efficiency cognition of energy	2.427 **	3.958 *	1.431
Constant	19.916 ***	15.668 *	20.332 ***
F	8.61 ***	3.40 ***	5.61 ***
R2	0.039	0.037	0.038

Note: * p < 0.05, ** p < 0.01, *** p < 0.001.

, Model 2.1 presents the situation in the whole population. Among the capital endowment factors, the regression coefficients of economic, cultural and social capital are all positive (0.334, 0.269, 0.594), but only economic and cultural capital pass the statistical test, i.e., the more the public’s economic and cultural capital are, the stronger their WTP for green energy consumption, while the effect of social capital is not significant. Hypotheses 2a and 2b are supported, while Hypothesis 2c is not supported. Among the energy cognition factors, the government support cognition of energy, environmental impact cognition of energy and personal efficiency cognition of energy are also positive (3.743, 0.542, 2.427), but the environmental impact cognition of energy does not pass the statistical test, i.e., the more positive the public’s government support cognition of energy and personal efficacy cognition of energy are, the stronger the WTP for green energy consumption, while the role of the environmental impact cognition of energy is not significant. Hypotheses 3a and 3c are supported, while Hypothesis 3b is not supported. Moreover, after adding the factors of capital endowment and energy cognition, the regression coefficient of urban–rural identity is −1.917, the absolute value of which is much smaller than that of 3.613 in Model 1.2, i.e., these two types of factors have strong explanatory power for the difference in the public’s WTP for green energy consumption, and also preliminarily demonstrates the rationality of its use as a socially grounded variable.

Models 2.2 and 2.3 present the situation in the urban and rural populations, respectively. Comparing the results of these two models shows that capital endowment and energy cognition do not have the same impact in the urban and rural fields. From the perspective of capital endowment factors, social capital has no significant effect on both urban and rural residents, while economic and cultural capital only enhances urban residents’ WTP for green energy consumption. From the perspective of energy cognitive factors, the role of environmental impact cognition of energy is not significant in both urban and rural residents, but government support cognition of energy and personal efficacy cognition of energy have a differential impact between them, where government support cognition of energy only enhances rural residents’ WTP for green energy consumption, while personal efficacy cognition of energy only enhances urban residents’ WTP for green energy consumption. In summary, in contrast, urban residents are more derived from independent capital endowments, while rural residents are constrained by dependent situational factors, especially government support cognition of energy.

5.3. Decomposition of Urban–Rural Differences in WTP for Green Energy Consumption

After initially identifying two socially based variables, capital endowment and energy cognition, this paper uses path analysis to test the accuracy of this finding and to explore whether they contribute to the divergence of WTP for green energy consumption due to urban–rural differences? If so, what is their respective contribution?

Table 5. Path analysis of capital endowment and energy perceptions.

Total, Direct and Indirect Effects of Urban–Rural Identity
Variable Type	β	Percentage (%)
the total effect	−3.613 ***	——
the direct effect	−1.917	53.079
the indirect effect	−1.695 ***	46.921
Capital endowment
Economic capital	−0.598	16.551
Cultural capital	−1.001	27.706
Social capital	0.062	−1.716
Energy cognition
Government support cognition of energy	−0.129	3.570
Environmental impact cognition of energy	0.067	−1.854
Personal efficiency cognition of energy	−0.096	2.664

Note: *** p < 0.001.

shows that when capital endowment and energy cognition are included, the total effect coefficient of urban–rural identity is −3.613 (p < 0.001), the direct effect coefficient is −1.917 (p > 0.05), and the indirect total effect coefficient is −1.695 (p < 0.001), which suggests that capital endowment and energy cognition play a fully mediating function. That is, capital endowment and energy cognition become a bridge connecting urban and rural residents’ WTP for green energy consumption, and their role size accounts for 42.541% and 4.380% of the total effect, respectively. Specifically, among the capital endowment factors, both economic capital and cultural capital show mediating effects, while social capital is the masking effect; among the energy cognition factors, both government support cognition of energy and personal efficiency cognition of energy are also mediating effects, while environmental impact cognition of energy is the masking effect. Overall, this is consistent with the findings in Table 4, which again suggests that capital endowment and energy cognition are the key underlying and potential factors in the WTP for green energy consumption of urban and rural residents.

Further analysis reveals that the influential role of capital endowment and energy cognition with urban–rural differences leads to a divergence in WTP for green energy consumption.

Table 6. Decomposition effect of capital endowment and energy cognition on the difference in WTP for green energy consumption between urban and rural residents.

Variable Type		β	Percentage (%)
The explainable part	Overall coefficient	1.797 **	44.746
	Difference in control variables	0.294	7.320
	Differences in capital endowments
	Differences in economic capital	0.425	10.582
	Differences in cultural capital	0.784	19.522
	Differences in social capital	−0.041	−1.021
	Differences in energy cognition
	Differences in government support cognition of energy	0.255	6.350
	Differences in environmental impact cognition of energy	0.038	0.946
	Differences in personal efficiency cognition of energy	0.042	1.046
The non-explainable part	Overall coefficient	2.219 *	55.254
Urban–rural disparities		4.016 ***	100

Note: * p < 0.05, ** p < 0.01, *** p < 0.001.

shows that the difference in WTP for green energy consumption of urban residents relative to rural residents is 4.016, and the coefficient of the explainable part of their difference is 1.797, which accounts for 44.746% of the total difference. Specifically, the contributions of the dimensions of capital endowment are, in descending order, cultural capital, economic capital, which account for 19.522% and 10.582% of the total difference, while social capital does not explain their differences, supporting Grootaert’s statement that “social capital is the poor man’s capital” (i.e., its return on rural residents’ WTP for consumption is higher than that of urban residents). The contributions of the dimensions in energy cognition are, in descending order, government support cognition of energy, personal efficiency cognition of energy and environmental impact cognition of energy, accounting for 6.350%, 1.046% and 0.946% of the total difference.

Based on the above analysis, capital endowment and energy cognition are important influencing factors explaining the difference in WTP for green energy consumption between urban and rural residents, constituting their objective and subjective mechanisms of action, respectively. Moreover, the contribution of capital endowment is greater compared to energy cognition, which is 20.741 percentage points higher. Hypotheses 3 and Hypotheses 5 are supported.

6. Discussion

Actively addressing climate change has become a pressing issue for sustainable development, and the 2015 “Paris Agreement” calls for countries to participate in the global response to climate change through autonomous contributions. As an important party, the “dual-carbon” strategy is not only an initiative to implement the concept of green development in China, but also a solemn commitment to fulfill the “Paris Agreement”, which is key to promoting the transition to green energy consumption. Unlike previous studies that examined the supply side of green energy technology research, green energy market development, and green energy subsidies, this paper starts from the demand side, using WTP as an entry point, with the aim of exploring urban and rural residents’ preferences for green energy consumption.

First of all, in the process of China’s modernization, the dualistic structure of the field has shaped the urban–rural differences in the public’s WTP for green energy consumption. At present, the dual structure is still the most important social characteristic in China, and its influence in various fields such as resources, environment, and population is so great that “urban-rural identity” has long occupied a place in the study of Chinese society, which is concerned with inequality. Similarly, this paper reveals a “high urban-low rural” picture of the public’s WTP for green energy consumption. This is similar to the empirical study of the environmental concerns of urban and rural residents by Hong Dayong et al., which suggests that it reproduces a dualistic structure in the environmental dimension [61]. And it is also similar to “The Residence Hypothesis” proposed by Dunlap et al., which suggests that urban residents exhibit better environmental attitudes and behaviors than rural residents due to greater exposure to environmental pollution [45].

Secondly, as Bourdieu’s social practice theory points out, the main factors affecting urban and rural residents’ WTP for green energy consumption are their capital endowment and Energy cognition of individual habitus. Among capital endowments, economic capital and cultural capital are positively related to the WTP for green energy consumption of the public, especially urban residents. This is in line with the findings of most studies, which concluded that the higher the income and education level of an individual, the higher his/her willingness to pay for green energy consumption [62]. However, social capital does not contribute to the WTP for green energy consumption of urban and rural residents, which is inconsistent with most studies [63]. Among the energy cognition factors, government support cognition of energy and personal efficiency cognition of energy are positive impact factors, which enhance the willingness to pay for green energy consumption of rural and urban residents, respectively, which is consistent with existing studies [64]. However, environmental impact cognition of energy has no effect, which is inconsistent with the differential exposure hypothesis in environmental studies [61].

Finally, combining Bourdieu’s social practice theory and the dual structure pattern of Chinese society, this paper reveals that the differences in capital endowments and energy cognition of individuals in the urban and rural fields lead to differences in their WTP for green energy consumption. In particular, economic constraints influenced by capital endowment are the most critical factor. This is similar to existing research that suggests that the higher acquisition cost of green energy can pose a significant threshold for low- and middle-income groups, inhibiting their green energy consumption choices [65].

In addition, this study points out that the contribution of capital endowment and energy cognition to the difference in WTP for green consumption between urban and rural residents is relatively limited, and that there are other influencing factors, so it is necessary to dig for a more comprehensive, diversified, and reasonable explanatory path, and to explore how to further promote the participation of urban and rural residents in green energy consumption. And previous studies have also shown that public preference for green energy consumption not only varies with individual demographic sociological characteristics (e.g., capital endowment or environmental perceptions), but also correlates with regional economic development, socio-cultural perceptions, and environmental pollution at the macro level [66].

7. Conclusions and Recommendations

In the new context of global green development and China’s “Dual Carbon” Strategy, this paper examines the WTP for green energy consumption of Chinese urban and rural residents and its influencing factors. The main conclusions are as follows: Firstly, the public’s WTP for green energy consumption generally falls into the medium category, and shows urban–rural inequality, with rural residents significantly worse than urban residents. Secondly, capital endowment and energy cognition significantly affect the public’s WTP for green energy consumption. On the one hand, as a whole, the more economic and cultural capital the public has, the stronger their WTP for green energy consumption. Moreover, the more positive the public’s government support cognition of energy and personal efficacy cognition of energy are, the stronger the WTP for green energy consumption. On the other hand, divided into urban and rural fields, urban residents depend more on economic and cultural capital, while rural residents are mainly limited by the government support cognition of energy. Thirdly, urban–rural differences in WTP for green energy consumption are largely determined by differences in their capital endowments and energy perceptions. Moreover, in contrast, differences in capital endowment contribute the most and are mainly reflected through economic and cultural capital.

It can be seen that this paper forms an expansion of the established research through the innovation of theoretical perspective and the deepening of mechanism analysis. In terms of theoretical perspective, most of the existing studies are based on traditional economics (i.e., rational choice theory) or social psychology models, focusing on the influence of individual economic rationality (e.g., income level) and psychological factors (e.g., environmental attitudes), while this paper introduces Bourdieu’s social practice theory, which regards WTP as a result of the interaction between capital endowment, energy cognition of individual habitus, and urban–rural fields. In terms of mechanism analysis, existing studies have found differences in WTP for green energy consumption between urban and rural residents, but mostly attributed to income disparity, while this paper further elucidates the source of the differences: capital endowment contribution is significantly higher than energy cognition, and rural residents are more dependent on the “government support cognition of energy”.

Meanwhile, the revelation of this paper to improve the WTP for green energy consumption of urban and rural residents is as follows: Firstly, multiple measures are needed to increase the public’s capital stock. Capital is the basic condition for public participation in green energy consumption, which can be facilitated in a variety of ways, such as developing the local economy, popularizing culture and education, and organizing residents to participate in collective activities. Secondly, expanding public education efforts to enhance public energy cognition. Energy cognition is the internal driving force for public participation in green energy, which can be promoted through offline activities such as lectures and online methods such as short videos. Thirdly, the government support system should be improved to reduce the public’s consumption burden. In addition to the public’s own capacity, external support, especially from the Government, is very important, and the “acquisition threshold” can be lowered by strengthening energy infrastructure and supplementing it with energy subsidies. Finally, urban–rural development should be integrated to avoid the rural areas falling into a “depression”. At present, China’s dual structure still exists and has become a deep structural shackle on the unequal consumption of green energy by urban and rural residents, thus requiring the promotion of urban–rural integration in the context of rural revitalization.