Analysis of Factors Influencing Public Participation in Energy Conservation and Carbon Emission Reduction Projects in China’s Energy Industry Based on the Theory of Planned Behavior

Abstract

As China’s carbon inclusion policies are gradually implemented, significant progress has been made in energy conservation and emission reduction. The economical use of energy is the basis for the reduction in carbon emissions, which is a direct reflection of the benefits of energy efficiency initiatives. Nonetheless, the lack of technological innovation, challenges in carbon emission monitoring, low levels of public participation, and inadequate talent cultivation present significant obstacles to the development of energy conservation and carbon inclusion. This paper, grounded in the theory of planned behavior (TPB), addresses the issue of low public participation in emission reduction initiatives. By employing a questionnaire survey, designing a 5-point Likert scale, and utilizing SPSS techniques for regression analysis and chi-square testing, this study explores and analyzes the potential factors influencing public willingness to engage in carbon emission reduction initiatives (CERIs). This research provides theoretical reference for relevant government agencies and industry insiders to formulate and implement the policies of energy saving and carbon reduction and provides targeted suggestions for China’s energy market to help them realize the sustainable development of low-carbon, energy saving, and environmental protection.

1. Background

1.1. Background of the Study

Since the 1990s, China’s economy has sustained rapid growth, leading to a concurrent increase in fossil energy consumption greenhouse gas (GHG) emissions. According to statistics, by 2021, China’s GHG emissions will be 14.31 billion tons of carbon dioxide equivalent, and more than 30 billion tons of carbon dioxide are emitted into the atmosphere each year [1]. By 2023, China’s fossil fuel consumption is 146 AJ, ranking first in the world [2]. As the world’s largest energy consumer and greenhouse gas emitter, this has undoubtedly exacerbated China’s energy crisis and environmental pollution, making the conflict between economic development and ecologically sustainable development increasingly prominent. As a result, China made a significant commitment at the 2015 Paris Climate Change Conference to “peak carbon emissions around 2030 and strive to achieve this as soon as possible” [3]. At the 75th session of the United Nations General Assembly on 22 September 2020, General Secretary Xi Jinping further articulated the “30–60” dual-carbon goals, committing China to peak carbon emissions by 2030 and achieve carbon neutrality by 2060 [4].

In the context of the dual-carbon strategy, achieving carbon reduction is a top priority. The basis of carbon emissions is energy conservation, that is, reducing energy demand and thus carbon emissions. Cutting down the use and waste of energy at the source is conducive to improving the utilization rate of energy and forming a long-term energy-saving effect. At the same time, it also reduces pollution emissions to a certain extent, reduces the cost investment in environmental pollution control, and realizes the sustainable development of the energy industry. The amount of carbon emissions is a direct reflection of the energy-saving benefits, through the detection of carbon emissions to assess the effectiveness of energy-saving behavior and the degree of effectiveness, to provide strong support for the development and optimization of energy-saving and emission reduction programs.

In China, as consumption-side carbon emissions constitute approximately half of the total carbon emissions, reducing emissions on the consumption side is a critical task in meeting the “dual-carbon” objectives. However, consumption-side carbon emissions are characterized by their broad scope, dispersed distribution, and challenges in quantification. These emissions are also significantly influenced by consumers’ willingness to engage in energy conservation and carbon reduction efforts [5].

In order to encourage widespread public participation in energy conservation and carbon reduction efforts, a substantial number of national and local carbon-inclusive supportive policies have been introduced since 2022. These policies aim to establish comprehensive, reasonable, and effective carbon-inclusive programs and to develop a carbon-inclusive mechanism that is “recordable, measurable, beneficial, and recognized”. This approach is designed to motivate small- and medium-sized enterprises (SMEs), communities, households, and individuals to engage in carbon reduction activities, ultimately achieving synergistic effects of energy saving and carbon reduction on the consumption side and the production side. In China, there are three primary types of carbon-inclusive systems: government-led, enterprise-led, and government–enterprise cooperative models [6]. All models promote the development of energy-saving, low-carbon, and environmentally friendly energy markets in China.

In response to the non-negligible impact of low public participation on the benefits of energy efficiency and carbon reduction, in this paper, we study the public’s willingness to participate in various energy-saving and carbon-reducing projects in the energy market, analyze several possible factors affecting the public’s willingness to participate and their impacts, and thus provide suggestions for increasing the public’s willingness to participate in energy-saving and carbon-reducing projects and for promoting the energy sector to achieve sustainable development.

1.2. Literature Review

1.2.1. Energy-Saving and Emission Reduction Practices

In the background of international carbon emission reduction, the energy markets at home and abroad have also started the practice of carbon emission reduction. For example, with the U.S. app Joro, users fill out questionnaires to estimate their carbon footprints to establish a personal carbon account, monthly carbon emissions based on the user’s carbon footprint measurement, and deductions. According to the official Joro website, the app has reduced the users’ carbon emissions by 21% in 2021. WSP Global Inc. has established a carbon emission tracking system for its employees, setting annual carbon emission limits and monitoring their emissions from daily household activities and commuting on a quarterly basis. This system is designed to implement a corresponding reward and penalty mechanism to incentivize employees to engage in carbon reduction behaviors [7]. In China, for instance, Lenovo Group has initiated a carbon emission reduction program targeted at its employees. Domestically, Lenovo has introduced the “Lenovo Carbon Circle”, an employee-oriented platform that tracks and records employees’ carbon emissions in their daily lives. The platform includes various functional modules, such as personal carbon accounts, carbon credit trading, and rewards, to effectively encourage employee participation in carbon-inclusive activities.

Both domestically and internationally, the energy industry faces numerous challenges in achieving energy conservation and low-carbon development. Data on low-carbon behaviors are often difficult to obtain, and the lack of standardization in quantitative methods [7], coupled with low public willingness and participation in emission reduction efforts, significantly impact the effectiveness of carbon reduction initiatives. Unlike the study by Wei Zhang et al. (2021) [8], which employed system dynamics to analyze the influence of multiple variables on the low-carbon development of enterprises, this paper focuses on one specific challenge: the low public participation in energy conservation and carbon reduction projects. Through in-depth research and analysis, this paper offers countermeasures and recommendations to promote carbon inclusion and achieve sustainable development.

1.2.2. Study on Public Willingness to Participate in Green Projects

Given that public willingness to participate in carbon emission reduction is influenced by a variety of factors, many scholars have extensively studied public engagement in carbon reduction and the associated influencing factors. Girish Bekaroo et al. (2018) [9] proposed a conceptualized carbon emission management framework to examine perceptions and behaviors regarding carbon emissions in the daily activities of employees within higher education institutions. Jurišević Nebojša et al. [10] used R software to create optimized composite models to study the influence of various factors such as demographic characteristics (gender, school) and transportation habits (mode, distance, frequency) on the perceived air quality of college students in an area. Jie Yang et al. [11] explored the factors influencing public willingness to reduce carbon emissions from the perspectives of demographic attributes (e.g., gender, age, education, income level) and risk perceptions. Wei Li et al. [12] investigated the positive effects of mandatory policies on residents’ attitudes and subjective norms related to waste sorting, aiming to enhance public participation in waste sorting initiatives. Chuan-Min Shuai et al. [13] examined the effects of carbon labeling on consumer purchases of low-carbon products, considering variables such as gender, monthly income, and education level. Meanwhile, many scholars have also widely applied the theory of planned behavior (TPB) to environmental psychology to study the relationship between environmental behaviors and intentions, with the goal of improving pro-environmental behaviors by identifying the psychological drivers behind carbon mitigation actions. For example, Wang et al. (2022) [14] used TPB to investigate the factors influencing carbon emission reduction among personnel in Chinese construction companies, providing valuable recommendations for corporate carbon reduction strategies. Stefan Hoffmann et al. [15] developed a carbon footprint tracking application (CFTA) to help consumers assess and adjust their personal carbon emissions. Tan et al. [16] used TPB as a theoretical foundation to explore the psychological factors affecting the participation of individuals with different personality traits in carbon reduction activities. Hu et al. [17] applied SPSS analysis techniques to study the relationship between corporate public low-carbon behaviors and consumers’ green purchasing intentions, drawing on TPB and responsible environmental behavior (REB) theories. Peng et al. [18] analyzed the differences and reasons behind the influence of various internal and external factors on low-carbon behaviors among urban and rural residents in China, utilizing the theory of planned behavior. Wang et al. [19] integrated TPB, the Norm-Activation Model, and the Attitude–Behavior–External Conditions framework to comprehensively consider demographic variables (e.g., age, gender, education) and internal and external factors affecting individual emission reduction behaviors. Yuanchao Gong et al. [20] explored ways to overcome public resistance to carbon taxes by implementing incentive-based climate policies. Hongyan Zhang et al. [21] examined the impact of limited public knowledge on environmental protection and sustainable urban development, recommending appropriate information disclosure to mitigate this impact. Umut Uzar [22] investigated the influence of public discourse and beliefs on environmental behavior and their resultant carbon dioxide emissions. Li et al. [23] analyzed the carbon emissions of residents in pilot cities based on the “attitudes, behaviors, and scenarios” framework, providing recommendations tailored to the economic and developmental conditions of different regions.

In summary, various scholars have conducted extensive theoretical research and practical exploration on individuals’ participation in various energy conservation and carbon reduction projects in the energy market. They have analyzed the factors influencing individuals’ willingness to engage in carbon reduction across different demographic groups and from diverse perspectives and methodologies. These studies consistently demonstrate a strong association between psychological drivers (e.g., personal intention) and participation in carbon emission reduction behaviors. Regarding the promotion of green and sustainable development in the energy industry, numerous studies have already been undertaken. For example, Liu et al. [24] found that public environmental preferences significantly inhibit corporate pollution emissions by encouraging the development of green technologies. Lijun Jia et al. [25] examined the positive impact of implementing a carbon emission trading system on the green innovation within the Chinese energy market. Li et al. [26] explored the effects of environmental regulation on the green development of enterprises, highlighting how subsidies and penalties for non-compliance can incentivize greener practices. Chen Chen et al. [27] investigated the influence of executives’ green experience in the energy market, revealing that such experience positively affects the development of green technologies and the improvement of environmental performance.

1.2.3. Influence of the Government Sector on the Development of Green Projects

In addition, it is indisputable that the government plays a pivotal role in promoting the green development of the energy market. This includes leading carbon emission reduction initiatives (Zhang et al. [28] analyzed and compared public participation in and the influence of the “Internet + Tree Planting” program, an emerging environmental protection initiative led by the government and enterprises), supervising carbon reduction efforts of relevant units (Yan Li et al. [29] empirically investigated the impact of the centralized ecological environmental protection inspection system on enhancing environmental benefits for relevant companies), and supporting related policies (Sheng Wu et al. [30] discussed the positive effects of government green credit policies on the economic and environmental performance of the Chinese energy market). National laws and regulations also play a significant role in advancing green development of the energy industry (Yuyu Liu et al. [31] examined the impact of China’s new Environmental Protection Law on the green innovation behaviors in high-pollution industries).

However, Jing Peng et al. [32] found that while governmental environmental regulatory measures effectively curbed pollution offenses in the energy industry, many enterprises lacked sufficient motivation for green innovation. They suggested that the government should provide more guidance and support to encourage green innovation, thereby fostering the green transformation and sustainable development in this industry. Junyi Wei et al. [33] further proposed that there is an optimal level of government intervention in the development of green technologies within the energy market.

1.2.4. The Content and Significance of This Paper

Based on the theory of planned behavior (TPB), this study constructed a comprehensive analytical framework to assess the role of four key factors, namely, risk perception, responsibility, belief support, and external environment, on the public’s participation in carbon reduction projects. Meanwhile, the effects of demographic factors such as age, gender, education, marital status, and occupational status on individual environmental behaviors are investigated. In addition, this paper explores the role of public participation in energy-saving and carbon reduction programs and assesses the impact of public participation on energy-saving and carbon reduction effects in the energy market, which contributes to a theoretical understanding of the relationship between public participation and carbon reduction development.

2. Models and Methods

2.1. Analysis of Influencing Factors

The public’s willingness to participate in enterprise emission reduction projects reflects the social psychological aspects of individual behavior. The attitude–behavior relationship theory provides strong explanatory power and predictability for the psychological decision-making processes underlying goal-directed behavior [34]. Drawing on the uses and gratifications theory and the existing literature on environmental values, this paper has identified and categorized four key factors that may influence public participation: risk perception, sense of responsibility, faith-based support, and external context.

2.1.1. Factor of Risk Perception

Perceived risk factors encompass the environmental changes and potential negative impacts that individuals can envision. The carbon preference system, which supports environmental governance, implies that people’s perceptions of environmental changes may significantly influence their attitudes and behaviors towards participation [35]. This factor primarily examines the roles of three elements: environmental change perception, risk perception, and concern. At its core, environmental change perception assesses whether individuals believe that the global environment has indeed undergone significant changes and whether these changes are attributed to unsustainable human production and lifestyles. Risk perception pertains to individuals’ awareness of the severity of the negative consequences associated with environmental changes. Recognizing, experiencing, or anticipating these adverse impacts is a crucial precondition for adopting environmentally responsible behaviors. Furthermore, emotional factors such as concerns about climate, ecology, and environmental degradation may also drive individuals to engage in carbon reduction activities. Environmental change concerns prompt individuals to become actively aware of and anxious about the potential negative impacts, increasing their willingness to support and participate in emission reduction initiatives. Thus, the hypothesis is proposed that perceptions of climate change, risk perception, and emotional concerns are correlated with public participation [36].

2.1.2. Factor of Responsibility

The responsibility factor pertains to the public’s intrinsic values related to environmental protection. This factor differentiates between the influence of environmental values and self-regulation. Environmental values represent the cognitive foundation and critical condition for promoting green and low-carbon behaviors, reflecting the public’s level of concern for the ecological environment and closely aligning with environmental decision-making processes. For individuals, the adoption of environmental values significantly influences their willingness to engage in carbon emission reduction initiatives [18]. Self-regulation in environmental protection reflects whether the public perceives participation in environmental public services as a moral obligation. Recognizing the importance of personal carbon reduction behaviors in environmental protection implies that individuals should view a low-carbon lifestyle as a fundamental responsibility. Consequently, the hypothesis is proposed that a correlation exists between environmental values, self-regulation in environmental protection, and public participation in emission reduction efforts.

2.1.3. Factor of Faith-Based Support

The faith-based support factor refers to the degree to which individuals comprehend and engage with policies and carbon reduction programs. This factor is analyzed on two levels: self-efficacy and cost-fairness perception. Self-efficacy pertains to an individual’s subjective evaluation of their ability to participate in environmental initiatives and achieve environmental goals. The ease of operation, control over unseen risks, and willingness to continue participation are prerequisites for public involvement in carbon reduction efforts. These elements significantly influence individuals’ understanding and implementation of carbon emission reduction programs. Perceived cost fairness involves the economic and behavioral costs individuals must bear when supporting and participating in emission reduction initiatives. This includes concerns such as whether participation increases living expenses or if environmental behaviors are time-consuming and labor-intensive. Public perceptions of cost fairness also encompass considerations of individual equity and distributive justice—whether it is fair for individuals to shoulder the costs of a policy or whether these costs are equitably distributed between industries and the public or among different demographic groups. These perceptions are critical factors affecting individual participation. Consequently, it is hypothesized that a correlation exists between beliefs such as self-efficacy and cost-fairness perception and the level of public participation in carbon reduction programs.

2.1.4. Factor of External Context

Public participation in carbon reduction initiatives is influenced by both intrinsic individual traits and the external context. External factors, particularly the role of conditions such as material incentives, psychological motivations, social trends, and norms, are critical in shaping behavior [37]. Demand motives—including material incentives, psychological experiences, and punitive measures—significantly impact individual actions. Individuals do not operate in isolation; their behaviors and decisions are deeply influenced by societal norms and the actions of others. The public opinion factor examines the potential impact of social norms on public support for carbon reduction efforts. The prevalence of participation within the public, societal expectations, and the broader social context highlight the relationship between social norms and individual involvement in environmental initiatives. Additionally, the questionnaire was designed to explore the relationship between these external factors and individual attitudes and decision-making processes, considering variables such as gender, age, education level, employment status, marital and family status, and physical health.

2.2. Methods

A chi-square analysis is employed to examine the association between the X and Y variables. The p-value is utilized to determine whether there is a statistically significant difference between these variables [38]. If the p-value indicates significance (typically p < 0.05 or p < 0.01), it suggests that there is a significant difference between the two groups of data. The magnitude of this difference can be further assessed by comparing the percentages associated with each group.

$${\chi }^2={\displaystyle \sum \left[\frac{{(O-E)}^2}{E}\right]}$$

(1)

O represents the observed frequency, and E denotes the expected frequency, which is calculated under the assumption that variables X and Y are independent, based on their marginal frequencies [38].

Based on the aforementioned theory, four types of influencing factors were identified as latent variables. Questionnaire items were developed around these core concepts, and the scale was designed by drawing on existing research and considering the current state of carbon inclusion mechanisms. The items were measured using a 5-point Likert scale.

The project team conducted an online survey in pilot provinces and municipalities, resulting in 171 valid responses by the time data collection concluded. To enhance the reliability and consistency of the questionnaire scales, SPSS 27 software was used to assess the reliability of the valid responses. The Cronbach’s α coefficient for the entire questionnaire and its variable factors was 0.924, which exceeds the 0.8 threshold, indicating high reliability.

To further assess the validity of the scale items, a validity test was performed. The KMO test, used to determine the appropriateness of factor analysis, yielded a result of 0.901, and the p-value for Bartlett’s sphericity test was 0.000. These results indicate that the questionnaire’s validity is strong and that the study data are well-suited for information extraction. See

Table 1. Validity analysis study.

KMO and Bartlett Sphericity Test
KMO		0.901
Bartlett sphericity test	approximate chi-square (math.)	1494.960
	df	78
	p-value	0.000

KMO is used to test the degree of commonality between the factors, and the KMO statistic ranges from 0 to 1. It is usually considered that a KMO value of 0.6 or above indicates that the data are suitable for factor analysis. Bartlett’s spherical test is mainly used to determine whether the data are significant. If the p-value of Bartlett’s test of sphericity is less than the level of significance (usually 0.05), the observed data are considered suitable for factor analysis; conversely, they are deemed unsuitable for factor analysis.

below.

To assess commonality (used to exclude unreasonable research items), one scale item, “Considering my professional status, I think it is difficult not to participate in the emission reduction program of the company I work for”, had a commonality value below 0.4. This indicated that the item did not effectively capture the intended information. After removing this item and reanalyzing the data, all remaining items had commonality values greater than 0.4, suggesting that the research items could effectively represent the underlying constructs. Additionally, the KMO value was 0.898, exceeding the 0.8 threshold, indicating that the data were suitable for factor analysis. The variance explained by the two factors was 43.95% and 22.52%, respectively, with a rotated cumulative variance of 66.48%, surpassing the 50% benchmark. This implies that the research items effectively captured the relevant information. Finally, the absolute values of the factor loading coefficients were all greater than 0.4, confirming a strong correspondence between the items and the factors.

Each question on the scale was rated on a 5-point Likert scale to gauge the level of support and agreement among respondents: 1 = not at all, 2 = mostly not, 3 = somewhat, 4 = mostly, and 5 = completely. The statistical results for the scale test items are presented in

Table A2. Design of questions on scale variable factors.

Factor	Observed Variables	Description of Questionnaire Items
Perception of risk	A1	I believe that environmental change is caused by our environmentally unfriendly or unsustainable way of producing and living.
	A2	I am concerned about environmental change and its negative impacts, and am actively involved in corporate programs to reduce emissions.
Responsibility	B1	I believe that my personal low-carbon behavior is of great importance to the environmental cause, and I see my participation in corporate emission reduction projects as my own moral responsibility.
Faith-based support	C1	The higher the income, the lower the economic and behavioral costs of participating in the project, and the more actively they participate in corporate emission reduction projects.
	C2	I was able to easily understand how to use and operate the emission reduction programs introduced by the company.
	C3	During my participation, I was able to overcome the legal, information security, and financial risks that may be associated with corporate emissions reduction programs.
	C4	Getting involved in corporate emissions reduction programs is something for me to be able to try and stick with.
	C5	I will recommend and encourage others to participate in the business’s emissions reduction program.
External context	D1	The emission reduction programs of participating firms have certain material incentives that entice me to use them.
	D2	It gives me a sense of accomplishment to be involved in such projects that produce better emission reductions.
	E1	If my family or people around me are participating, I would want to participate.
	E2	The emission reduction programs of participating companies are in line with society’s expectations for individuals to live a low-carbon lifestyle.
Other factors	F1	Considering my professional status, I find it difficult not to participate in the emission reduction programs of the companies I work for.

of the Appendix A.

3. Results and Discussions

3.1. Analysis of Results—Overall Description of the Data

A total of 171 individuals participated in this questionnaire survey. The specific demographics of the respondents are illustrated in Figure 1 and Figure 2.

As shown in Figure 1, the gender distribution of survey respondents was skewed towards female participants, accounting for 63.74% (109 individuals). The largest age group represented in the survey was between 18 and 29 years, comprising 42.11% (72 individuals). In terms of educational background, the majority of respondents held university degrees (100 individuals), while only a small number were graduate students or higher (4 individuals). The disparities in proportions across these demographic categories are evident.

As shown in Figure 2, the vast majority of respondents were members of the general public (i.e., not internal employees of the enterprise), representing 93.57% (160 individuals). Similarly, 93.57% of respondents reported being in good health (160 individuals), with only a small number (4 individuals) experiencing health issues related to environmental problems. Additionally, 86.55% (148 individuals) reported that their family members had not participated in the emission reduction projects initiated by the enterprise. The frequencies of marital status and reproductive status were comparable (figure omitted).

3.2. Difference Analysis of Influencing Factors

A chi-square analysis was conducted to examine the difference between variable X and variable Y. The p-value was used to determine whether X significantly affects Y. If the p-value indicates significance (p-value less than 0.05 or 0.01), it suggests that the two sets of data are significantly different. The specific differences can be further analyzed by comparing the percentages. A total of six studies with different sample sets were integrated through data analysis to draw the final conclusions.

3.2.1. Gender Studies

Figure 3 presents the analysis of gender differences across various variables. The chi-square test results for gender and the 13 variables show that all p-values are greater than 0.05, indicating no significant differences between gender and these variables. This suggests that gender does not influence individuals’ motivation to participate in carbon emission reduction projects, which further supports the reliability of the survey results.

3.2.2. Age Studies

The analysis of age-related differences across various variables is detailed in Table A2 of the Appendix A. Figure 4 presents the p-values for the relationship between age and these variables.

Figure 4 displays the p-values from the chi-square test examining the relationship between age and the 13 variables. The p-values for all variables, except for D1, are greater than 0.05, indicating a consistent level of participation in carbon emission reduction projects across different age groups.

Figure 5 illustrates the relationship between age and the D1 variable. The analysis reveals a significance level of 0.05. Among respondents aged 18 to 29, 30.56% chose to fully comply, which is significantly higher than the average compliance rate of 22.81%. Conversely, 24.44% of respondents aged 30 to 45 indicated they do not comply, which is notably higher than the average non-compliance rate of 12.28%. Additionally, 18.75% of respondents under 18 also reported basic non-compliance, exceeding the average rate of 12.28%. These results suggest that individuals aged 18 to 29 are more likely to engage in the emission reduction program due to a higher inclination towards material incentives. In contrast, those aged 30 to 45 and under 18 are less influenced by material incentives, which affects their participation levels differently.

3.2.3. Education Degree Studies

The results of the analysis examining the differences between education levels and various variables are detailed in

Table A3. Cross-sectional studies on age and variables.

Variable	A1	A2	B1	C1	C2	C3	C4	C5	D1	D2	E1	E2	F1
χ2	9.449	8.747	8.373	14.711	8.313	12.574	9.934	11.038	23.128	6.106	9.397	11.416	12.994
p	0.664	0.724	0.755	0.258	0.760	0.401	0.622	0.526	0.027	0.911	0.669	0.494	0.369

of the Appendix B. Figure 6 shows the p-values between education level and various variables.

In examining the relationship between education level and 13 variables, the p-values for all variables, except for C1, D1, and F1, exceed 0.05. This indicates that the level of education may influence individuals’ motivation to participate in carbon emission reduction projects under specific conditions.

As illustrated in Figure 7, the analysis of the relationship between education level and the C1 variable shows statistical significance at the 0.05 level (χ² = 25.093, p = 0.015). The proportion of graduate students and above who chose to fully comply with carbon emission reduction measures is 100.00%, significantly higher than the average of 22.81%. Conversely, the proportion of college graduates choosing partial compliance is 33.33%, which is also notably higher than the average of 26.90%. These findings suggest that individuals with higher education levels are more likely to believe that income level has a relatively significant influence on their participation in emission reduction projects.

As illustrated in Figure 8, the study of the relationship between education level and the D1 variable shows a 0.05 level of significance (χ² = 22.391, p = 0.033 < 0.05). The proportion of university and higher education respondents who select “fully in line with” is 27.88%, significantly higher than the average level of 22.81%. Conversely, the proportion of technical secondary school respondents who select “not matching up” is 24.49%, markedly higher than the average level of 12.28%. This indicates that the higher the level of education, the more inclined to believe that the influence of material incentives is great.

As seen in

Table 2. Cross-sectional study on education degree and F1 variable.

Cross-Sectional (Chi-Square) Analysis Results
Theme	Name	Your Level of Education (%)				Total	χ2	p
		Vocational Secondary School	Three-Year College	College	Graduate Student or Above
Considering my professional status, I find it difficult not to participate in the emission reduction programs of the companies I work for.	fully in line with	6 (12.24)	7 (38.89)	25 (25.00)	2 (50.00)	40 (23.39)	26.343	0.010
	basically in line with	13 (26.53)	5 (27.78)	40 (40.00)	0 (0.00)	58 (33.92)
	partially in line with	16 (32.65)	4 (22.22)	25 (25.00)	1 (25.00)	46 (26.90)
	not matching up	7 (14.29)	2 (11.11)	9 (9.00)	0 (0.00)	18 (10.53)
	not at all	7 (14.29)	0 (0.00)	1 (1.00)	1 (25.00)	9 (5.26)
total		49	18	100	4	171

, the study of the relationship between the level of education and the F1 variable shows a level of significance of 0.01 (χ² = 26.343, p = 0.010 < 0.01). The proportion of respondents with university and higher education qualifications who selected “fully in line with” is 25.96%, significantly higher than the average of 23.39%. The proportion of university respondents selecting “basically in line with” is 40.00%, significantly higher than the average level of 33.92%. The proportion of vocational secondary school respondents selecting “partially in line with” is 32.65%, considerably higher than the average level of 26.90%. This indicates that as the level of people’s education increases, the public tends to believe that it will become less and less feasible not to participate in carbon emission reduction programs due to differences in occupational identity.

3.2.4. Occupational Identity Studies

The results of the analysis of differences between occupation and various variables can be found in

Table A4. Cross-sectional study on education degree and variables.

Variable	A1	A2	B1	C1	C2	C3	C4	C5	D1	D2	E1	E2	F1
χ2	10.241	16.807	5.597	25.039	16.157	11.665	11.891	11.828	22.391	15.117	13.226	15.074	26.343
p	0.595	0.157	0.935	0.015	0.184	0.473	0.454	0.460	0.033	0.235	0.353	0.237	0.010

in the Appendix B. Examining the relationship between occupational identity and 13 variables, the p-value of all variables except A1 and C1 variables is greater than 0.05, indicating that different occupational statuses will have a certain degree of influence on the people’s motivation to participate in carbon emission reduction projects.

As can be seen in Figure 9, which examines the relationship between occupational identity and the A1 variable, showing significance at the 0.05 level (χ² = 9.971, p = 0.041 < 0.05), the percentage of internal employees (employees within the green industries) choosing “fully compliant” is 45.45%, which is significantly higher than the percentage of the general public (employees in other industries) (28.75%). The proportion of the general public choosing “partially in line with” is 28.13%, significantly higher than that of employees within the energy industry (0.00%). This suggests that in-house employees are more inclined to believe that environmental changes are caused by environmentally unfriendly and unsustainable lifestyles.

As can be seen in Figure 10, the relationship between occupational identity and the C1 variable is significant at the 0.05 level (χ² = 10.296, p = 0.036 < 0.05), i.e., in-house employees tend to perceive that an increase in their income effectively reduces the economic and behavioral costs of participating in emission reduction projects, presenting a more positive attitude than the general public. This attitude is reflected in the proportion of employees choosing the “full Compliance” option, which is as high as 36.36%, significantly exceeding the 21.88% of the general public. In contrast, the general public chose a relatively high percentage of “basic compliance” and “partial compliance” (34.38% and 28.75%, respectively), both of which exceed the corresponding percentages of employees in the energy industry. This phenomenon shows that there is a certain degree of diversity and dispersion in the views of the general public on this issue.

3.2.5. Marital Status Study

As shown in Figure 11, examining the relationship between marital status and the 13 variables, the p-values of all variables except the D1 variable are more significant than 0.05, indicating that marital status has a less impact on public participation in carbon reduction programs.

As can be seen in Figure 12, the study of the relationship between marital status and the D1 variable shows significance at the 0.01 level (χ² = 17.122, p = 0.002 < 0.01), with 29.41% (25 people) of unmarried people choosing “fully in line with”, significantly higher than that of married choosing 16.28% (14 people). The proportion of unmarried choosing “partially compliant” is 30.59% (26 people), significantly higher than that of married choosing 23.26% (20 people). The percentage of married individuals choosing “not matching up” is 17.44% (15 people), which is significantly higher than that of unmarried individuals, which is 7.06% (6 people). The results indicate that unmarried individuals are more likely to perceive that they are driven by material incentives when they choose to participate in carbon reduction projects. In contrast, the married individuals are more likely to believe that they are not solely motivated by material incentives.

3.3. Variable Observation Statistics

The statistical observations of the variables are shown in Figure 13.

Using the sample data from the questionnaire, we systematically sorted out the related research progress to analyze the influencing factors of public participation in the awareness and behavior of energy conservation and emission reduction projects, and at the same time, we found that four factors, namely, risk perception, responsibility obligation, conviction support, and external environment, have a significant impact on the public’s participation in these projects. This indicates that individual behavior is a complex decision-making process influenced by intrinsic characteristics and the external environment.

In the “responsibility obligation” factor, environmental values and environmental self-regulation have a significant influence. Individuals with higher environmental values and stronger environmental self-regulation are more likely to participate in carbon reduction projects. Therefore, environmental values and self-regulation, as major influencing factors, powerfully drive individual behavior.

Additionally, social opinion significantly influences individual behavior. In the social context that emphasizes low-carbon and energy-saving concepts, individuals are positively influenced by the external norms. Public behavior may be shaped by the prevalence of participation behaviors or tendencies, others’ expectations of the behavior, and the desire to align with societal low-carbon values, leading to changes in personal behavior.

Furthermore, the “risk perception” factors including environmental change awareness, risk perception, and concern beliefs have a significant effect on individual behavior. Lastly, in the “belief support” factor, Individuals’ perceptions of the security risks and ease of use of energy conservation and carbon reduction projects can also affect their participation behavior, although to a less extent. The influence of psychological motivation in the “external incentives and penalties” factor on individual behavior is minimal, with perceived cost fairness and material incentives having the weakest impact.

4. Conclusions

4.1. Summaries

Based on the data from 171 authentic questionnaires and the cross-tabulation analysis mentioned above, this paper discusses the demographic characteristic factors (gender, age, education, marital status, occupational status) and the four factors under the TPB theory: risk perception (awareness of environmental change, perception of risk, worry, etc.), responsibility (environmental values, norms of self-environmental preservation, etc.), faithed-based support (sense of self-efficacy, sense of cost equity, etc.), and external environmental factors on the individual’s decision-making attitudes and behavioral factors. Results found that gender has no significant influence on the willingness of individuals to participate in energy-saving and emission reduction programs, and material incentives have less influence on people younger than 18 years old and 35–45 years old, as well as on unmarried people. The more educated people are, the more inclined they are to participate in energy-saving and emission reduction programs, and the more influenced they are by material incentives and participation costs. Social environment and public opinion have a positive effect on increasing the public’s willingness to participate. Employees within a green enterprise are more likely to be influenced by danger perception and responsibility and obligation factors and therefore have a higher willingness to participate. This could be concluded as follows:

(1)

The results of the study show that most people have a positive attitude towards participating in energy-saving and emission reduction programs. They believe that personal low-carbon behaviors are important for reducing energy waste and environmental protection and consider participation in these programs a moral responsibility.

(2)

Most respondents believe that higher income reduces the economic and behavioral costs of participating in these projects, leading to more active involvement in emission reduction initiatives. However, opinions on material incentives, the effectiveness of emission reduction efforts, and overcoming potential risks varied.

(3)

Most respondents expressed a willingness to recommend and encourage others to participate in energy conservation and emission reduction projects of the energy industry.

4.2. Suggestions

This study provides valuable insights into how public participation affects the benefits of energy efficiency and carbon reduction. These findings will inform the development of energy efficiency and carbon reduction programs within the energy market, contributing to the achievement of the “dual carbon goals”.

(1)

Future research could focus on deepening sociological studies to reveal the intrinsic mechanism between public participation and energy-saving and emission reduction benefits. Apply quantitative and qualitative research methods to systematically analyze how public participation affects their emission reduction behavior and energy-saving benefits. This will help to provide a scientific basis for developing targeted methodological strategies.

(2)

The government and relevant departments can create diversified public participation platforms. Through participation platforms such as online forums and community meetings, the public can monitor each other and provide feedback, thus improving the openness and effectiveness of energy-saving and emission reduction behaviors.

(3)

The government could implement more policy incentives to encourage the energy market to actively reduce emissions. With additional public education on energy saving and carbon reduction, the government could provide the public with more energy-saving and low-carbon lifestyle choices and incentive subsidies so that the public gradually develops energy-saving and low-carbon habits at source. Examples include the establishment of a smart canteen system, the provision of purely electric and hybrid vehicle options, and the introduction of subsidies for the purchase and maintenance of new-energy vehicles, as well as license plate facilitation.

(4)

Finally, it is recommended that government departments further strengthen environmental education and energy-saving awareness in order to promote public participation in environmental protection. The government could take the cultivation of public environmental values as a starting point, disseminate environmental protection knowledge through various channels, and encourage green consumption and low-carbon lifestyles. At the same time, publicity and education can be diversified and popularized. For example, it can encourage the creation of literary and film works on the themes of energy crisis, environmental pollution, and human survival or make use of positively influential exemplary figures to publicize and call for publicity, etc., so as to provide a good social atmosphere for the public to better participate in energy conservation and emission reduction projects. In addition, based on the findings of this paper, more targeted suggestions can be provided to different characteristics of the population, such as material incentives for the 30–45-year-old group, under-18-year-old people do not play an obvious role; and for the lower education level of the population, the environmental protection willingness is low, so we can target these groups to strengthen the environmental education and environmental protection awareness cultivation.

4.3. Future Research Directions

As an empirical study, this research has certain limitations. This study focuses on the impact of public participation on the effectiveness of carbon emission reduction in the energy sector and may have overlooked other important factors. For example, public participation in energy efficiency and carbon reduction programs is low, and other factors such as technology costs, market supply and demand, and data collection and management challenges also constrain the effectiveness of energy efficiency and reduction. Future related studies may focus on the impact of other factors on the effectiveness of energy conservation and emission reduction. In addition, other demographic characteristics, such as region, influence the public’s willingness to participate in energy conservation and emission reduction through environmental, economic, and cultural pathways, and ignoring this variable may weaken the precision and policy appropriateness of research findings. The existing studies still provide important references for theory and practice through multidimensional demographic analysis and solid empirical data. Future studies can further deepen the understanding of the behavioral driving mechanism of energy conservation and emission reduction by incorporating regional variables or conducting regional comparative analyses.