Research on the Driving Factors and Policy Guidance for a Reduction in Electricity Consumption by Urban Residents

Abstract

The urgency of mitigating climate change and the challenges it poses to ecosystems and human systems are highlighted in the Intergovernmental Panel on Climate Change’s (IPCC) Sixth Assessment Report (AR6). In order to achieve sustainable development, it is imperative to adopt a series of adaptive measures to enhance the resilience of various sectors to climate change and reduce greenhouse gas emissions. This article analyzes the driving mechanism behind the reduction in electricity consumption by urban residents based on 302 valid questionnaires from 18 communities in nine districts in B City. Using a method that combines qualitative and empirical research, the study proposes policy recommendations aimed at guiding urban residents toward reducing their electricity consumption. These recommendations serve as a policy reference for cities striving to achieve sustainability and low-carbon targets. The primary innovations and conclusions of the study are as follows: (1) this study summarizes the primary factors and processes influencing the reduction in electricity consumption among urban residents, examined from the following three perspectives: residents’ characteristics, psychological understanding, and external environment. (2) On the basis of the research data, empirical analysis and hypothesis testing are conducted using a variety of mathematical and statistical methods. The results indicate significant differences in the electricity consumption reduction behavior of heterogeneous urban residents in both public and private areas. Subjective norms, perceived behavioral control, and knowledge of electricity conservation have significant direct influences on residents’ willingness to reduce their electricity consumption. Among these factors, subjective norms have the most significant impact, while the impact of attitude is negligible. Economic incentive policies have a significant positive regulatory effect on the relationship between “willingness (intention)” and “private area electricity consumption reduction behavior”.

1. Introduction

In September 2020, General Secretary Xi Jinping proposed the goals of striving to achieve a carbon peak by 2030 and carbon neutrality by 2060. These goals have brought about profound changes in China’s economic structure, ways of working, and life. With the continuous advancements in global environmental research, it is evident that the consumer end is also a pathway to achieving a country’s green and low-carbon transition [1]. Individuals should alter their energy consumption patterns and adopt low-carbon consumption practices. Urbanization and electrification have driven the growth of residential electricity consumption. Finding a balance between environmental protection and the need to promote economic development is a dilemma that China is currently facing. Fundamentally changing the economic growth model into a high-quality development model is a prerequisite for achieving the dual carbon goals [2]. However, the present achievement of China’s carbon peaking and carbon neutrality goals mainly depends on developing new energy industries or implementing subsidy policies for energy-saving household appliances. Nevertheless, there are few effective measures to stimulate urban residents’ domestic electricity consumption reduction, and the implementation of these measures is ineffective. Consequently, determining how to encourage urban residents to reduce their electricity consumption has become a significant concern for relevant departments and academics.

According to the Intergovernmental Panel on Climate Change’s (IPCC) Sixth Assessment Report (AR6), climate change represents the most severe security challenge faced by the world today, posing a significant threat to the survival and development of human society. As of 2020, a total of 56 countries worldwide have enacted legislation specifically targeting a reduction in greenhouse gas emissions, covering 53% of global total emissions. In recent years, substantial efforts have been made in Europe and the Americas to evaluate and enhance energy efficiency and conservation. In particular, the United States rejoined the Paris Agreement in 2021 and revised and strengthened the National Environmental Policy Act, setting a new emissions reduction target of 50–52% below 2005 levels by 2030, with a plan to achieve carbon neutrality by 2050. European countries, led by Germany and the United Kingdom, have consistently been advocates for climate protection. In 2019, the German Federal Ministry of Education and Research allocated EUR 86 million to support the European ACTRIS climate-monitoring program to achieve carbon neutrality by 2045.

According to the National Energy Administration (NEA) of China, total electricity consumption by urban and rural residents in 2023 reached 1352.4 billion kilowatt–hours (KWh), representing a year-on-year increase of 0.9%. Of this total, 75% of the carbon dioxide emissions stem from energy-consuming appliances, with air conditioners, refrigerators, and televisions accounting for over half of the energy consumed. Therefore, encouraging city dwellers to reduce their consumption of electricity is a crucial step toward lowering carbon emissions and aiding China in achieving its carbon peaking and neutrality goals. A reduction in electricity consumption by urban residents refers to daily behaviors that reduce the consumption of electricity based on personal habits, namely reducing the frequency or intensity of using electricity-consuming products through repetitive actions, for example, opening and closing the refrigerator less often. Relevant studies have discussed the influencing factors of energy-saving behaviors of residents. Junjie Bian et al. argue from a microperspective that residents’ energy-saving behavior is influenced by education and income level [3], while Hongjing Shi contends from a macroperspective that low-carbon policies can positively regulate residents’ energy-saving behavior [4]. However, fewer studies further subdivide these influencing factors, and even fewer studies specifically focus on urban residents’ electricity consumption reduction behavior. There are few studies analyzing these influencing factors and concentrating on urban residents’ electricity consumption reduction behaviors. Moreover, the majority of studies on the influencing factors of energy-saving behavior merely confirm the existence of a certain type of factor rather than providing a systematic summary of the influencing factors and a specific analysis of the influencing mechanisms from multiple dimensions.

To reveal the driving mechanism of the electricity consumption reduction behavior of urban residents, the first step is to construct a theoretical model of a reduction in electricity consumption by urban residents. The theory of planned behavior (TPB) is one of the most commonly used theoretical models by scholars to study residents’ energy-saving behavior. The theory posits that individual behavior is directly influenced by behavioral willingness, while attitudes, subjective norms, and perceived behavioral control are crucial factors that affect individual behavioral willingness. To enhance the explanatory and predictive powers of the model, this article considered the responsible environmental behavior model and the attitude–behavior–situation theory based on the theory of planned behavior. It added new explanatory variables and path relationships and studied the driving mechanism behind reductions in electricity consumption by urban residents. It also conducted an empirical study. Therefore, this article can serve as a reference for the formulation of policy guidance on reductions in electricity consumption among urban residents.

2. Literature Review

2.1. Studies on the Classification of Power-Saving Behavior

Stern and Gardner (1981) distinguished the following two categories of energy conservation behaviors: efficiency and reduction. Efficiency includes insulating walls and attics and replacing old cars, furnaces, and appliances with more energy-efficient equipment. A reduction refers to reducing the use of existing equipment, including driving less and decreasing the usage of household appliances [5]. Many researchers have subsequently refined this categorization, making adjustments to the definitions. For instance, Dillman et al. (1983) defined reduction and efficiency as adjustments and conserving actions [6], respectively, whereas Barr (2005) defined them as habitual and purchase-related energy-saving behaviors, respectively [7]. Scott (2000) further subdivided energy-saving behaviors on the basis of the above categorization into the following three types: energy-saving investment behaviors, energy-saving management behaviors, and energy-saving curtailment behaviors. Energy-saving investment behaviors refer to investments and improvements for household energy saving (e.g., purchasing energy-efficient products); energy-saving management behaviors refer to the unconscious behavior that manages habitual and repetitive energy use in daily life (e.g., turning off the lights when leaving); energy-saving curtailment behaviors, on the other hand, refer to conscious daily energy-saving behaviors that require some personal sacrifice (e.g., sacrificing part of one’s comfort) in order to achieve energy savings, such as using heaters less frequently or choosing natural drying instead of using dryers [8].

2.2. Studies on the Factors Influencing a Reduction in Electricity Consumption

In the field of energy-saving behavior research, numerous studies have confirmed the important role of psychological cognitive factors in promoting individual behavioral intentions. Concerning attitude, many studies posit that attitude can effectively promote individual behavioral intentions [9,10,11]. However, some studies suggest that attitude does not have a significant impact on energy-saving behavior [12,13] or that it can only operate when moderated by other factors [14,15]. Secondly, subjective norms have a significant positive impact on individual behavioral intentions. These intentions are mainly influenced by the norms of the surrounding groups and society [16,17]. Some studies have also indicated that subjective norms can have a positive effect on attitudes [10,18]. Regarding perception behavioral control, some studies have indicated that it can indirectly influence actual actions through behavioral intentions [19,20], while other studies have suggested that it can directly affect residents’ energy-saving behaviors [15,21,22,23]. Finally, knowledge of electricity reduction is equally important, as people with rich environmental knowledge are more likely to implement household energy savings, etc. [24,25,26,27].

In examining the relevant external factors, policy factors also have a positive impact on residents’ energy-saving behavior. Sardianou (2007) found that economic policies significantly impact residents’ energy-usage behaviors, thereby stimulating the purchase of energy-efficient and environmentally friendly household appliances through government taxation and subsidies [28]. Muhammad et al. (2011) demonstrated the significant impact of government policies on the promotion of solar photovoltaic power generation [29]. Ding Liping (2015) further identified government policies as the primary factor influencing public energy-saving awareness. Strengthening government support, developing comprehensive regulatory policies, and implementing new energy policies would enhance the public’s inclination to adopt solar photovoltaic power generation [30]. In addition, some studies have shown that government policies can regulate the impact of energy-saving intentions on energy-saving behaviors. Chang Haoran et al. (2023) found that targeted energy-saving policies had a positive impact on residents’ energy-saving behavior [31].

Finally, research on residents’ energy-saving behaviors has found that sociodemographic factors such as gender, age, education level, income, and family size have an impact on residents’ willingness and behaviors toward energy conservation. Regarding gender, Lee et al. (2013) discovered that women are more likely to adopt energy-saving measures related to residential lighting consumption [32]. Shrestha’s (2021) systematic literature review on energy conservation and management revealed that women consume less energy in conducting household activities, thereby contributing to household energy-saving behaviors [33]. Hu and Gong (2020) observed varying economies-of-scale effects on urban residents’ electricity consumption across different age groups, with younger individuals making a greater contribution, while the elderly and youths have less impact on per capita electricity consumption reduction [34]. Regarding education level, Avani and Matt (2010) found in their surveys that residents with self-owned housing, higher education levels, and higher incomes were more willing to use energy-saving facilities [35]. Concerning income, Sardianou (2007) determined through empirical research that residents’ income, family size, and housing type influenced their energy-saving preferences [28]. Martinsson et al. (2011) explored the influence of income on energy-saving attitudes based on survey data in Sweden from 2004 to 2007 and found that higher-income households have a stronger influence on energy-saving attitudes than lower-income households [36]. However, scholars’ research conclusions vary due to different sample selections. For instance, Mi Lingyun and other scholars (2016) surveyed Xuzhou City, Jiangsu, and discovered that an increase in residents’ income did not effectively promote purchase-oriented energy-saving behaviors or habitual energy-saving behaviors [20]. Teng Yuhua et al. (2020) found that a lower education level among rural residents significantly hindered energy-saving behaviors aimed at energy reduction, while age and income do not have a significant impact on energy-saving behaviors aimed at energy reduction among rural residents [37]. In general, the current research on the relationship between sociodemographic variables and energy-saving behavior suggests that the differences in social, cultural, economic, and environmental conditions across various studies affect the stability of this relationship.

3. Research Hypotheses and Theoretical Framework

3.1. Variable Selection

On the basis of a comprehensive review of the domestic and international literature concerning the factors influencing residents’ electricity reduction behavior and relevant theories, this study classified the factors that affect urban residents’ electricity reduction behavior into three distinct categories. These categories encompass cognitive–emotional factors, including attitude (ATT), subjective norms (SNs), perceived behavioral control (PBC), and electricity reduction knowledge (ECK), which are represented by four latent variables. Additionally, external contextual factors are represented by a single latent variable, economic incentive policies (EIPs). In this study, it is reflected by the government’s issuance of subsidy policies and whether a company has tax incentives. Demographic factors comprise variables such as age (AGE), gender (GEN), educational level (EDU), monthly income level (MONI), and household size (POP), totaling five variables. Furthermore, this study examined user reduction behavior, which seeks to diminish the frequency or intensity of using power-consuming products. Such behavior encompasses public domain electricity reduction behavior (PUB) and private domain electricity reduction behavior (PRI). The public domain includes actions such as choosing stairs over elevators in schools and workplaces, while the private domain involves behaviors like reducing the use of dryers at home and opting for natural air-dried clothes. The term electricity consumption reduction intention (ECI) is used to describe the deliberate inclination of residents to adopt electricity consumption reduction behaviors. Subsequently, an initial scale was developed on the basis of established scales from prior studies. As illustrated in

Table 1. Indicator measurement items.

Latent Variable	Code	Item	Reference
Attitude	ATT1	I believe electricity is a very important resource.	[38,39]
	ATT2	I believe I should try to reduce electricity consumption in my life as much as possible.
	ATT3	I believe that if everyone implements electricity-saving policies in their daily lives, a lot of energy can be saved.
	ATT4	I believe that implementing electricity reduction measures can help protect the environment.
	ATT5	I believe that implementing electricity reduction measures is an important way to reduce environmental pollution.
Subjective norms	SNs1	If my family members implement electricity-saving policies in their daily lives, I will be influenced and also do the same.	[15,19]
	SNs2	If my friends engage in electricity-saving behaviors in their daily lives, I will be influenced by them and also engage.
	SNs3	If the media promotes the benefits of reducing electricity consumption, then I will pay attention to reducing electricity consumption in my daily life.
	SNs4	If I reduce electricity consumption, I believe my family will support my actions.
	SNs5	If I reduce electricity consumption, I believe my friends will support my actions.
Perceptual behavior control	PBC1	For me, electricity-saving in daily life is something that is very easy to do.	[37,40]
	PBC2	I always manage to overcome difficulties when implementing electricity reduction measures.
	PBC3	I have some knowledge about electricity-saving behaviors.
	PBC4	I have some skills in reducing electricity consumption.
	PBC5	I have a strong ability to accept and apply new knowledge and technologies for reducing electricity consumption.
Electricity consumption reduction knowledge	ECK1	I know that household appliances consume a certain amount of energy when in standby mode.	[41,42]
	ECK2	I know that setting the air conditioner temperature higher in summer can save energy, and setting it between 26 and 28 degrees is most suitable.
	ECK3	I know that frequent opening and closing of the refrigerator door will consume more electricity.
	ECK4	I know that washing too few clothes in the washing machine can increase energy consumption.
	ECK5	I know that the higher the brightness of the TV screen, the more power it consumes.
Economic incentive policies	EIPs1	I believe that implementing electricity reduction measures can save costs.	[43]
	EIPs2	If the government raises electricity prices, I would be more willing to implement electricity consumption reduction measures.
	EIPs3	If the government rewards energy-saving behaviors, I would be more willing to implement electricity reduction measures.
	EIPs4	If the government provides subsidies for electricity-saving behaviors, I would be more willing to implement electricity reduction measures.
	EIPs5	If the community gives small gifts to families with lower monthly electricity consumption, I would be more willing to implement electricity reduction behaviors.
Residents’ willingness to reduce electricity consumption	EIC1	I am willing to implement electricity consumption reduction measures.	[20,44,45]
	EIC2	I plan to implement electricity consumption reduction measures.
	EIC3	I will encourage my family to implement electricity-saving measures.
	EIC4	If there is an ‘Earth Hour’ event, I will participate.
	EIC5	If the community organizes an energy-saving event, I will participate.
Electricity consumption reduction by residents in private sphere	PRI1	I will turn off the lights at home when not in use.	[16,46]
	PRI2	I will unplug unused appliances at home.
	PRI3	I will try to hand wash clothes at home as much as possible.
	PRI4	I will lower the volume of the TV at home.
	PRI5	I will try to use the air conditioning less at home.
Electricity consumption reduction by residents in public domain	PUB1	I will always turn off the lights at school or in the office.	[16,46]
	PUB2	I will shut down computers that are not in use promptly at school or in the office.
	PUB3	I will try to use as little lighting as possible during the day at school or work.
	PUB4	I will try to use air conditioning as little as possible in schools or companies.
	PUB5	I will try to take the stairs instead of the elevator in public places such as schools, offices, and shopping malls.

, the scale comprises eight distinct variables contrived to identify the factors that sway the behavior of urban dwellers toward reducing electricity consumption.

The resident population demographic factors refer to the research scales of Chen (2009), Yang (2015), Mi (2016), and others [20,43,46]. Duplicate items are consolidated and removed to gather essential personal information, as outlined in

Table 2. Initial scale of population demographic factors.

Control Variables	Code	Item	References
Demographic factors	Q1	Your age	[20,43,46]
	Q2	Your gender
	Q3	Your education level
	Q4	Your monthly income level
	Q5	Your household size

.

3.2. Formulation of the Research Hypotheses

3.2.1. Hypotheses of the Relationship between the Heterogeneity of Residents’ Attributes and the Impact on Reductions in Electricity Consumption by Residents

The socio-demographic variables involved in this study include age, sex, education level, monthly income level, and family population. According to the literature review, age [28,34], gender [32,33], educational background [35,37], income [28,35,36], and household size [28] are variables that have a significant effect on resident environmental behaviors. On the basis of the literature review, the following hypotheses were made in this study:

H1a. 

There are significant differences in resident attribute heterogeneity in electricity consumption reduction behavior among residents in the public domain.

H1b. 

There are significant differences in resident attribute heterogeneity in electricity consumption reduction behavior among residents in the private domain.

3.2.2. Hypotheses on the Relationship between Residents’ Psychological Cognition and Their Willingness to Curtail Electricity Consumption

According to the theory of planned behavior, some factors can directly influence behavioral intentions, for example, attitude, subjective norms, and perceived behavioral control. Empirical studies by scholars [9,10,11,15,19,20,22] have confirmed that an individual’s attitude toward the behavior and the subjective normative level are positively correlated with the perceived behavioral control and willingness to perform the behavior. Therefore, this study hypothesized the relationships between residents’ attitudes, subjective norms, and perceived behavioral control and residents’ willingness to curtail electricity consumption as follows:

H2. 

Attitude has a prominent positive effect on the willingness of residents to curtail electricity consumption.

H3. 

Subjective norms have a prominent positive effect on the willingness of residents to curtail electricity consumption.

H4. 

Perceived behavioral control has a prominent positive effect on the willingness of residents to curtail electricity consumption.

According to the responsible environmental behavior model, environmental knowledge directly influences an individual’s environmental behaviors [24,25,26,27,45,47,48]. Knowledge of electricity curtailment, which involves how to decrease power consumption and protect the environment, can be categorized under environmental knowledge. The greater the individual knowledge of the behavior, the stronger their willingness to perform the behavior. Therefore, this study hypothesized the relationship between the knowledge of electricity curtailment and willingness to curtail electricity consumption as follows:

H5. 

Residents’ knowledge of electricity curtailment has a positive effect on their willingness to curtail electricity consumption.

3.2.3. Hypotheses on the Relationship between Willingness of Residents to Curtail Electricity Consumption and Electricity Consumption Reduction Behavior

According to the TPB model, an individual’s behavioral intentions can accurately predict individual behavior without interference from external factors. A large number of empirical studies have confirmed that whether an individual performs a behavior is significantly influenced by behavioral intention [15,19,26,45,48]. Therefore, this study made the following hypotheses about the relationship between residents’ willingness to curtail electricity consumption and the reduction in electricity consumption:

H6a. 

Residents’ willingness to curtail electricity consumption has a significant positive effect on their electricity reduction behavior in the public domain.

H6b. 

Residents’ willingness to curtail electricity consumption has a significant positive effect on their electricity-cutting behavior in the private domain.

3.2.4. Hypotheses of the Moderating Role of External Contextual Factors

According to the attitude–behavior–situation theory, external contextual factors have an important influence on whether an individual performs a certain behavior [28,29,30,31]. The government has formulated a series of tax incentives and financial subsidy policies in order to enhance the public’s willingness to reduce electricity consumption and promote electricity consumption reduction behavior. Therefore, this study makes the following hypotheses about the relationship between external contextual factors (i.e., economic incentive policies) and the willingness and behavior of residents to reduce electricity consumption:

H7a. 

Economic incentive policies significantly and positively regulate the path relationship between residents’ willingness to reduce electricity consumption and their electricity consumption reduction behavior in the public domain.

H7b. 

Economic incentive-based policies significantly and positively regulate the path relationship between residents’ willingness to reduce electricity consumption and their electricity consumption reduction behavior in the private domain.

3.3. Theoretical Analysis Framework

The theory of planned behavior is fundamental in the field of social psychology and is used to explain and predict individual behavior. It originated from the theory of reasoned action and the theory of multiple attributes, which suggest that individual behavior is directly influenced by behavioral intention, attitude, subjective norms, and perceived behavioral control, all of which are important factors affecting an individual’s behavioral intention [49]. The theory of planned behavior has been widely applied in various areas, such as pro-environmental behavior, health behavior, and consumer behavior. For example, in the context of pro-environmental behavior, the theory of planned behavior can be used to explain and predict behaviors such as water conservation, energy saving, waste sorting, and low-carbon travel. In terms of health behavior, it can be used to study behaviors like seeking medical care, chronic disease management, and elderly care service selection. Regarding consumer behavior, it can be used to explain and predict behaviors such as tourism consumption, shared consumption, and purchasing behavior. Scholars continuously expand and broaden the application scope of the theory of planned behavior by introducing new explanatory variables or paths to enhance the explanatory and predictive powers of the model [50]. In summary, the theory of planned behavior serves as a foundational theory for explaining and predicting individual behavior. It possesses a high degree of explanatory and predictive power and has been extensively applied in multiple domains, providing a theoretical foundation and model framework for this research.

Building upon the theory of planned behavior, Hines and other scholars proposed the responsible environmental behavior model [50]. This model suggests that an individual’s responsible environmental behavior is closely related to their sense of environmental responsibility. The stronger their sense of responsibility, the more pro-environmental behaviors they are likely to engage in. Environmental knowledge, behavioral knowledge, and personality variables influence the intention to engage in responsible environmental behavior. Firstly, possessing responsible environmental behavior knowledge (including environmental knowledge and behavioral knowledge, which can further be divided into action skills and action strategy knowledge) is a prerequisite for individuals to implement responsible environmental behavior. Secondly, personality variables such as environmental attitudes, locus of control, and personal responsibility are determining factors in responsible environmental behavior. Lastly, considering the complexity of situational variables, factors such as personal economic conditions, social pressure, and opportunities to engage in environmental behavior are incorporated into the model to enhance its explanatory power.

Based on their research on residents’ recycling behavior, Guagnano et al. put forth the attitude–behavior–context (ABC) theory [51]. The theoretical model posits that the individual adoption of a specific behavior is influenced by both attitudes and external conditions, representing a combined effect of the two. Unlike the theory of planned behavior, the ABC theory not only focuses on the impact of individual attitude factors, such as subjective norms and values, on actual behavior but also takes into account the influence of external factors, such as policy regulations, personal economic conditions, and social systems, on one’s actual behavior.

Based on the analysis of the preceding theories, the theoretical framework is depicted in Figure 1.

4. Empirical Study

4.1. Demographic Analysis of the Research Respondents

This study used a network questionnaire to conduct formal research. In order to ensure the representation and reliability of the sample, this study adopted a stratified sampling method. It selected nine districts and 18 communities as the questionnaire distribution locations based on the economic development level and geographical location of each administrative district in B city. A total of 310 questionnaires were distributed and 310 were recovered, of which 302 were valid, with an effective recovery rate of 97.42%.

In the descriptive analysis of the samples, the gender composition of the respondents was relatively balanced, with 150 male respondents accounting for 49.7% of the total sample and 152 female respondents accounting for 50.3% of the total sample.

In terms of age distribution, the respondents under 18 years old and over 60 years old accounted for 7.3% of the total sample, respondents aged 31 to 44 accounted for 39.1%, which was the largest group, and respondents aged 45 to 59 accounted for 21.2%. In terms of educational background, 69.5% of the respondents had received a college-level education or above. In terms of monthly income, 56 respondents’ income was less than CNY 3000, accounting for 18.5% of the total sample. About half of the surveyed residents reported a monthly income of more than CNY 6000. In terms of household size, the proportion of respondents from households with three or more members reached 74.2%; respondents living alone accounted for only 7.7% of the total. As a whole, the structure of the respondents’ genders, ages, educational backgrounds, income levels, and family sizes was reasonable, as well as representative and reliable, and can be used as the source of the sample data in this study.

4.2. Reliability and Validity Tests

In this article, SPSS 22.0 was used to test the reliability and validity of the questionnaire data, employing the collinearity test and discriminant validity test. In order to improve the reliability and validity of the questionnaire, questions with a factor loading below 0.5 and poor discrimination results were excluded on the basis of the analysis of the results of the discriminant, reliability, and validity tests on the initial measurement items. The results of the reliability test for the final retained measurement items are shown in

Table 3. Results of the data reliability and validity analyses for the questionnaire.

Latent Variable	Items	Standard Factor Loading	α	CR	AVE
Attitude	ATT1	0.841 ***	0.962	0.871	0.692
	ATT3	0.809 ***
	ATT4	0.845 ***
Subjective norms	SNs1	0.812 ***	0.838	0.814	0.593
	SNs3	0.733 ***
	SNs4	0.763 ***
Perceived behavioral control	PBC1	0.803 ***	0.946	0.865	0.682
	PBC2	0.812 ***
	PBC3	0.849 ***
Electricity consumption reduction knowledge	ECK2	0.774 ***	0.929	0.856	0.665
	ECK2	0.809 ***
	ECK3	0.861 ***
Willingness to reduce electricity consumption	ECI2	0.598 ***	0.951	0.771	0.530
	ECI4	0.710 ***
	ECI5	0.774 ***
Economic incentive policies	EIPs1	0.696 ***	0.931	0.819	0.603
	EIPs2	0.672 ***
	EIPs5	0.733 ***
Electricity consumption reduction behavior in the public domain	PUB3	0.814 ***	0.949	0.805	0.580
	PUB4	0.770 ***
	PUB5	0.696 ***
Electricity consumption reduction behavior in the private domain	PRI3	0.699 ***	0.944	0.751	0.501
	PRI4	0.715 ***
	PRI5	0.710 ***

*** p < 0.001.

. Cronbach’s alpha ranges from 0 to 1, with higher coefficients indicating better internal consistency and reliability of the test. It can be seen from the table that among all variables, the lowest value for Cronbach’s alpha was 0.838, and the lowest composite reliability was 0.751, which are greater than the standard value of 0.7, indicating that the measurement scale in this study has high reliability and good internal consistency. The convergent validity was tested using the factor loading and average volume of extraction (AVE), and the results show that the standardized loading coefficients of each item were greater than the acceptable value of 0.6, and the average volume of extraction was above the desirable value of 0.5, which indicates that the convergent validity of each variable was good.

In this study, SPSS 22.0 was used for the KMO and Bartlett’s spherical tests, and the results are shown in

Table 4. KMO and Bartlett’s sphericity test results.

Latent Variable	KMO	Bartlett
Power-saving attitude	0.754	0.000
Subjective norms	0.657	0.000
Perceived behavioral control	0.749	0.000
Electricity consumption reduction knowledge	0.705	0.000
Willingness to reduce electricity consumption	0.743	0.000
Economic incentive policies	0.730	0.000
Electricity consumption reduction behavior in the public sector	0.730	0.000
Electricity consumption reduction behavior in the private sector	0.757	0.000

. It can be seen from Table 4 that the KMO values of each variable are above the standard value of 0.6, and the chi-square value of Bartlett’s sphericity test is larger. The significance level of the test results is less than 0.001, which shows that this study scale is suitable for factor analysis. Bartlett’s sphericity test produced a result approximating zero, represented as 0.000 in Table 4, suggesting a correlation among all factors.

4.3. Difference Significance Test

As shown in

Table 5. Results of the one-way ANOVA for demographic variables.

Variables			Square Sum	df	Mean Square	F	Significance
Age	PUB	Among different groups	6.929	4	1.732	2.167	0.073
		Within the group	236.574	296	0.799
		Aggregate	243.503	300
	PRI	Among different groups	11.406	4	2.851	3.943	0.004
		Within the group	214.033	296	0.723
		Aggregate	225.439	300
Educational background	PUB	Among different groups	17.697	4	4.424	5.799	<0.001
		Within the group	226.577	297	0.763
		Aggregate	244.274	301
	PRI	Among different groups	16.901	4	4.225	6.015	<0.001
		Within the group	208.612	297	0.702
		Aggregate	225.513	301
Monthly income	PUB	Among different groups	12.142	4	3.884	3.371	0.004
		Within the group	231.132	297	0.782
		Aggregate	244.274	301
	PRI	Among different groups	17.708	4	4.427	6.327	<0.001
		Within the group	207.805	297	0.700
		Aggregate	225.513	301
Household size	PUB	Among different groups	9.956	3	3.319	4.221	0.006
		Within the group	234.317	298	0.786
		Aggregate	244.274	301
	PRI	Among different groups	12.670	3	4.223	5.913	0.001
		Within the group	219.718	295	0.745
		Aggregate	225.513	301

, the results of the one-way ANOVA show that age, educational background, monthly income, and household size have significant effects on electricity consumption reduction behavior in the public domain (PUB, hereinafter referred to as public domain behavior) and electricity consumption reduction behavior in the private domain (PRI, hereinafter referred to as private domain behavior), which show significant differences according to age, educational background, monthly income, and household size.

The F value for electricity reduction behavior in the public domain is 4.886 (p = 0.028 < 0.05), indicating variance heterogeneity, with p = 0.683 > 0.05, which does not pass the significance test. The F value for electricity reduction behavior in the private domain is 0.185 (p = 0.668 > 0.1), indicating variance homogeneity, with p = 0.159 > 0.05, which also does not pass the significance test. Therefore, the factor of gender does not have a significant impact on electricity reduction behavior; that is, there is no significant difference in electricity reduction behavior between different genders in both the public and private domains. According to the results of the comparison of the average value of residents’ electricity consumption reduction behavior among groups based on demographic variables, as shown in

Table 6. Comparative analysis of the group means of variables related to residents’ electricity reduction behavior.

Variables		Mean
		PUB	PRI
Age	Under 18 years old	3.94	4.36
	19–30 years old	3.71	3.95
	31–44 years old	3.82	3.96
	45–59 years old	4.03	4.07
	Over 60 years old	4.24	4.06
Educational background	Junior high school and below	3.92	4.12
	High school (specialized secondary schools)	4.02	4.33
	Junior college	4.24	4.32
	Bachelor’s degree	3.76	3.92
	Master’s degree and above	3.51	4.06
Monthly income	CNY 3000 or below	3.87	4.21
	CNY 3001–6000	4.01	4.18
	CNY 6001–8000	4.10	4.26
	CNY 8001–10,000	3.67	3.76
	CNY 10,000 or higher	3.55	3.66
Household size	1 person	3.86	4.31
	2 people	4.01	4.11
	3 people	4.01	4.21
	3 people and above	3.61	3.76

, the middle-aged and elderly groups (i.e., those aged over 45 years old) engage in more electricity consumption reduction behaviors compared to youths, namely those aged 19–44. This may be because older residents in China generally have a fine tradition of thrifting and a lower demand for high-energy appliances as they age, while the group under the age of 18 is more likely to accept advanced environmental protection concepts and knowledge, developing good electricity consumption habits and therefore are more likely to perform electricity consumption reduction behaviors.

Education level has a significant impact on reduction behavior in both the public domain (p < 0.001) and the private domain (p < 0.001). Specifically, significant differences in reduction behavior were observed across different education levels in both domains. The average value of the residents’ electricity consumption reduction behavior among groups with different educational backgrounds varied. The electricity consumption reduction behavior of residents with a secondary education was the highest, while that of the residents with less education was lower. Generally speaking, the more education residents receive, the more ways they have to acquire knowledge about electricity consumption reduction and the more sensitive they are to energy issues. With the improvement in residents’ education, those with a bachelor’s degree or above had higher requirements for quality of life, and their demand for electricity consumption rose accordingly. So, they are less concerned about performing electricity consumption reduction behaviors.

The factors of monthly income level had a significant impact on the electricity consumption reduction behavior of the public domain (p = 0.004 < 0.05) and the electricity consumption reduction behavior of the private domain (p < 0.001); that is, there were significant differences between the electricity consumption reduction behavior of the public domain and the electricity consumption reduction behavior of the private domain at different monthly income levels. Based on the monthly income, the average value comparison of the residents’ insurance intention shows that there is an obvious inverted “V” relationship between the reduction behavior aimed at the electricity consumption of residents and monthly income. This may be because middle-income residents have more room to save energy than low-income residents, and low-income residents themselves do not consume much energy. Urban residents with higher income levels are less sensitive to product prices, and the cost savings or subsidies brought about by electricity consumption reduction behavior is less attractive. In addition, the higher the income level of urban residents, the stronger the desire to improve their quality of life by purchasing high-energy appliances, to a certain extent, weakening their willingness to engage in behaviors related to electricity consumption reduction.

The variable of household size has a significant impact on electricity reduction behavior in both the public domain (p = 0.006 < 0.01) and the private domain (p = 0.001). This indicates that there are significant differences in electricity reduction behavior between the public and private domains across different household sizes. In terms of household size, larger households consume more energy, probably because of the inconsistency in electricity consumption habits within families, which may result in some waste in order to meet the electricity needs of each family member at the same time. The electricity consumption habits developed in families will also affect their PUB. The PRI of residents living alone was significantly higher than their PUB, which may be because their electricity demand was lower in private areas. So, they are more likely to engage in electricity reduction behavior.

4.4. Model Path Analysis and Hypotheses Testing

In this section, the structural equation model was fitted using the least squares method with AMOS 24.0. The following main parameter indicators were obtained: the ratio of the chi-square to degrees of freedom (CMIN/DF) was used to assess the discrepancy between the observed and modeled data, yielding a value of 3.332, which falls within the favorable range of 3–5. The root mean square error of approximation (RMSEA), a measure of the model fit, was found to be 0.088, meeting the criterion of being less than 0.1. The standardized root mean square residual (SRMR), which evaluates the discrepancy between the observed and predicted data, yielded a value of 0.042, satisfying the requirement of being less than 0.05. The adjusted goodness-of-fit index (AGFI), indicating the degree of model fit, was 0.805, surpassing the threshold of 0.8. The normed fit index (NFI), incremental fit index (IFI), Tucker–Lewis index (TLI), and comparative fit index (CFI) all exceeded 0.9, meeting the cutoff for adequate fit. These results demonstrate a satisfactory fit of the model according to the parameter requirements, allowing for further research to be conducted.

The path analysis of the model is shown in

Table 7. Results of the path analysis.

Hypothetical Path	Influence	β	S.E.	C.R.	p	Conclusion
Attitude—willingness to reduce electricity consumption	+	0.096	0.067	1.430	0.163	nonsupport
Subjective norms—willingness to reduce electricity consumption	+	0.403	0.070	5.749 ***	<0.001	support
Perceived behavioral control —willingness to reduce electricity consumption	+	0.386	0.045	8.498 ***	<0.001	support
Electricity consumption reduction knowledge—willingness to reduce electricity consumption	+	0.333	0.066	5.064 ***	<0.001	support
Willingness to reduce electricity consumption—PUB	+	0.858	0.047	18.328 ***	<0.001	support
Willingness to reduce electricity consumption—PRI	+	0.957	0.054	17.708 ***	<0.001	support

+ Positive influence; *** p < 0.001.

. The standard error (S.E.) serves as an indicator of the accuracy of the regression coefficient. A lower S.E. implies a greater accuracy in the estimation of the regression coefficient. The critical ratio (C.R.) denotes the significance of the regression coefficient. A higher C.R. value suggests that the regression coefficient is significant. The p-value is used to assess the statistical significance of the regression coefficient. A lower p-value suggests that the regression coefficient observed is significant.

The analysis in Table 7 shows that subjective norms (β = 0.403, t = 5.759, p < 0.001), perceived behavioral control (β = 0.386, t = 8.498, p < 0.001), and knowledge of electricity consumption reduction (β = 0.333, t = 5.064, p < 0.001) are all significantly and positively correlated with the willingness to reduce electricity consumption. This conclusion is consistent with the findings in [15,19,20,26,37,52,53]. Among all of the factors, subjective norms were the strongest influencing factors on residents’ willingness to curtail electricity consumption, which fully proves that whether residents perform reduction behaviors related to electricity consumption is mainly influenced by the expectations of important external references rather than by internalized social influences. In addition, the perceived behavioral control factor and the grasp of related knowledge, which reflect the individual’s control ability, have a strong predictive ability on residents’ willingness to curtail electricity, while attitude (β = 0.096, t = 1.430, p = 0.163) had no significant correlation with willingness to reduce electricity consumption, indicating that it is difficult to stimulate residents’ willingness to curtail electricity consumption even when they possess positive attitudes. This is inconsistent with the findings of existing studies on the relationship between attitude and willingness to save energy [37,43,54,55]. The probable reason for this is that electricity consumption reduction behavior is a daily, habitual electricity-saving behavior, which is greatly affected by their habits. The residents’ positive attitude has no obvious impact on their willingness to reduce electricity. There was a significant positive correlation between the willingness to curtail electricity consumption and PUB (β = 0.858, t = 18. 328, p < 0.001) and PRI (β = 0.957, t = 17.708, p < 0.001), which indicates that the stronger the willingness of residents, the greater the possibility of performing the behavior. This conclusion is in accordance with [15,19,45]. In summary, it is assumed that H3, H4, H5, H6a, and H6b are valid but H2 is not.

4.5. Moderating Effects Test

In this article, SPSS was used to analyze the moderating effect of economic incentive policies. The moderating effect of economic incentive policies on electricity consumption reduction willingness and PUB is shown in Figure 2 (β = 0.417, t = 1. 390, p > 0.1), which is not significant, assuming that H7a is not valid. Figure 2 shows the moderating effect of economic incentive policy variables on the path relationship between electricity consumption reduction willingness and PRI (β = 0.808, t = 2.489, p < 0.01), which is significant, assuming that H7b holds. The statistical results show that when the level of the economic incentive policy is high, PRI will increase with the increase in residents’ willingness to reduce electricity consumption. When the level of the economic incentive policy is low, PRI will weaken with the increase in residents’ willingness to reduce electricity consumption. This suggests that economic incentive policy is an important factor influencing residents’ engagement in electricity consumption reduction behavior and the higher the level of the economic incentive policy, the higher the likelihood of the residents’ performance of PRI. This result is in accordance with the findings in [43,56,57,58].

5. Policy Recommendations for a Reduction in Electricity Consumption by Urban Residents

5.1. Formulation of Policies and Regulations

Relevant policies and regulations should be formulated by the government to guide and regulate a reduction in electricity consumption by urban residents. However, the current policies guiding residents to reduce electricity consumption are incomplete and superficial, making it difficult to ensure that residents actively participate in reduction activities. Passive participation makes for poor results. On the one hand, there are few policies and regulations that guide residents to reduce electricity consumption. When formulating relevant policies and regulations, the government focuses on promoting the utilization of energy-saving appliances, new energy products, ecofriendly materials, etc., neglecting the important role played by individual residents in reducing electricity consumption. In the course of local policy implementation, no policy documents have been issued that are specifically aimed at guiding residents to reduce their electricity consumption. Instead, the relevant contents are in the National Action Plan for Energy Conservation and Emission Reduction, Reinforcement on the Implementation for Energy Conservation, and other documents. Contents concerning the reduction in electricity consumption are presented in a few respects and hardly distinguished because of their combination with other contents, which results in a lack of a specific legal basis and policy guidance for the government’s efforts in guiding residents to reduce consumption. Moreover, most of the policies on guiding residents to reduce electricity consumption are complementary measures in the process of implementing national policies, and there are few targeted policies designed to promote a reduction in electricity consumption by residents according to local conditions, leading to a political gap in this field. Moreover, pertinent contents in policies and regulations are not comprehensive. Existing policies on guiding residents to reduce electricity consumption mainly focus on simple aspects of daily life, such as turning off lights, unplugging, thus reducing the energy consumption for standby, using less air conditioning, opening windows more in summer, and climbing more stairs instead of taking elevators. In comparison, there is a lack of all-round and systematic policies and regulations guiding residents to reduce electricity consumption in both public and private places. In addition, there is insufficiently matched support for demonstration policies. Policies mainly concerned with guiding residents to reduce their electricity consumption are mostly general notices with only a few normative documents. Most of them provide guidance and plans from a macroscopic view, and only a few specific measures and policies are developed for the residents to promote their reduced consumption of electricity based on microcosmic psychological cognition and demography. Furthermore, with the predominance of encouraging and advocating policies and the deficiency of hard regulations and strict standards, policy implementation has been seriously affected. In addition, the laws guiding residents to reduce electricity consumption have not been fully effective, and many residents do not recognize the energy conservation law or have only heard of it without much understanding of the content of the law. As a result, many laws and regulations that have been introduced are not binding and guiding, and they have not been well implemented and enforced. Moreover, in terms of a reduction in electricity consumption by residents, the energy-saving laws that have been promulgated are too simple, with many repetitions, and their provisions are not sufficiently detailed, resulting in unclear responsibility divisions and poor operability. These problems are not conducive to effectively guiding residents to reduce their electricity consumption and need to be resolved urgently.

Therefore, improving relevant policies, regulations, and supporting measures is the basis for guaranteeing a reduction in electricity consumption by residents. Only by strengthening the top-level design and reinforcing institutional norms can a unified policy and theoretical guidance be provided for a reduction. At present, most of the relevant policies are focused on standard setting, new energy development, and enterprise subsidies, and there is a lack of policies and regulations directly related to urban residents. It is recommended that government departments introduce more targeted policies and norms, and comprehensively utilize a variety of policy devices to ensure the effectiveness of their policies and regulations.

(1)

Comprehensive and operable policies and regulations on reducing electricity consumption should be formulated. Through the promulgation of relevant policies and regulations, residents should realize their obligations and responsibilities, understand the harm caused by carbon emissions to the environment, form the value of being ashamed of wasting electricity, and be able to consciously cut down on electricity consumption, thus creating a social atmosphere for reducing electricity consumption. In daily life, work, and study, it is necessary to create a culture of cutting down on electricity consumption and reducing energy waste. First, before formulating policies, the government should ensure smooth communication with people, encourage the active participation of residents, and listen to the views of all parties extensively. Policies and regulations guiding residents to reduce electricity consumption should be formulated on the basis of the interests of all relevant parties through comprehensive consideration. Then, the effective implementation of laws and regulatory documents should take priority. On the one hand, residents’ perceptions of the policies and regulations should be promoted, and their difficulty in understanding the relevant documents should be reduced. On the other hand, it is necessary to strictly implement the laws and regulations related to reducing electricity consumption and standardize law enforcement action, coordinate the functions of law enforcement and regulatory departments, give full play to the binding effect of the law, and ensure implementation. Ultimately, the feedback system of relevant policies and regulations should be improved. Timely and effective policy feedback can reflect the deviations in the implementation of policies and regulations, so surveys and statistics on the result of policy implementation should be collected to adjust the policies.

(2)

Government departments should focus on the integration of various policy devices to form an energy-saving and emission reduction pattern led by the government, with enterprises as the main body and jointly promoted by the whole society. Public policies urging residents to cut electricity consumption can be categorized into psychological and structural policies. Psychological policies mainly refer to information, education, and demonstration, which regularize residents’ behavior aimed at electricity consumption mainly through changing their cognition, subjective norms, perceptual behavior control, etc. Structural policies mainly include pricing strategies and rules of statute laws, which are aimed at guiding residents to cut down on electricity consumption by changing the external environmental conditions. Different types of policies have their focus. Government departments should adopt a variety of policy devices and organically combine a series of macro-policies such as information policies, subsidy policies, convenient policies, and incentive policies. They should also utilize policy devices such as information means, economic means, technical means, administrative regulations, etc., to fully mobilize all areas of society to participate in reducing electricity consumption and create synergy for a better implementation of the policies.

(3)

Policy supervision is an important part of ensuring the effectiveness of the policy guiding residents to reduce electricity consumption. Inadequate social supervision mechanisms can cause problems in the implementation of the policy and affect its effectiveness. First of all, it is necessary to clarify the supervisory responsibilities and methods. The work of guiding residents to cut electricity consumption involves several departments, including the municipal economic and information administrative departments, the administrative departments working on energy conservation qualified by the people’s governments at the district or county level, the administrative departments of various areas, etc. These departments all have the functions and responsibilities of promoting a reduction in electricity consumption and should strengthen the management in the course of policy implementation, the effects of which need to be included in the assessment system. Then, external supervision should be guaranteed. Professional third-party organizations should be hired to systematically check or supervise the content and implementation process of the policy, focusing not only on whether the policy implementation process is legally compliant but also to assess the implementation effects of the policy.

5.2. Improvements in the Incentive Policy

From the results of the empirical analysis, it can be seen that an economic incentive-based policy can actively turn residents’ willingness to reduce electricity consumption into actual actions of cutting electricity consumption in the private sphere, indicating that economic incentive-based policy has an impact on the reduction. It also activates residents’ actions to reduce electricity consumption. Since electricity consumption reduction by urban residents is still in its initial stage, it is difficult to achieve the goal of energy savings and emissions reduction solely by relying on residents. So, it is necessary to strengthen policy incentives and support. However, existing incentive policies, which are mostly relevant to finance, tax, price, credit, and government procurement, support the utilization and publicity of energy-saving products and new energy sources mainly through financial subsidies, and there are few economic incentives and behavioral incentives for residents to reduce their electricity consumption. Moreover, some local governments have failed to fully realize the real situation of residents’ electricity consumption reduction. Moreover, they have not provided substantial financial support, which would dampen, to a certain extent, people’s motivation to reduce their electricity consumption and affect the smooth implementation of related governmental works. Although relevant legal provisions are given to guide residents to reduce their electricity consumption, such as Article 67 of the Law of the People’s Republic of China on the Conservation of Energy Resources, which states that “The people’s governments at all levels shall commend and reward units or individuals that achieve outstanding successes in energy conservation control or research or wide application of energy conservation technologies, or that report against serious energy waste”, there is a lack of assessment criteria for the effectiveness of a reduction, and there are no voluntary compliance agreements and supporting incentives, which fail to provide sufficient motivational support for residents to reduce their electricity consumption. In addition, numerous commercially owned communities have adopted the price system of peak and valley electricity, which signifies a time-differentiated pricing strategy. Under this system, electricity charges are high during designated peak periods and low during fixed off-peak times. It should not be overlooked that the current low residential electricity prices in China and the implementation of a uniform model on electricity prices fail to encourage residents to cut electricity consumption and fully reflect the cost of electricity and the principle of horizontal equity. The goal of rational sharing of electricity costs among residents at different levels of income has not been realized, resulting in an unreasonable distribution pattern of more subsidies for higher-income groups and fewer for lower-income groups, which does not conform to the principle of equitable burden sharing. Therefore, only by improving the relevant incentive policies and adopting corresponding incentive measures can we effectively promote a reduction in electricity consumption by residents. Foreign developed countries have enacted some positive policies to promote a reduction in electricity consumption by their residents. For example, the “Energy rebate subsidy project” put forward by the United States stipulates that if a user’s electricity consumption sees a year-on-year decrease in the summer, the government will return the user’s summer electricity charge. Japan’s “Voluntary Standby Power Reduction Program” aims to promote a reduction in standby energy consumption in household appliances and office equipment, which has achieved remarkable success. However, in this stage, China has formulated few incentive policies to alleviate electricity consumption by residents. To solve this problem, China should give priority to the establishment of a market-based mechanism for the common interest of all parties. In addition, it should optimize resource allocation, publish incentive policies, and guide residents to cut down on electricity consumption.

(1)

Pricing as a means of regulation should be implemented to encourage residents to develop the habit of reducing electricity consumption. A step tariff policy is aimed at encouraging residents to reduce electricity consumption. Under the step tariff policy, electricity consumers are divided into different tiers based on their electricity consumption, with each tier corresponding to a specific price. The tiered pricing is divided into multiple stages, with the price gradually increasing as the electricity consumption increases. On the premise of ensuring the stability of electricity prices for residents, government departments should improve the current step tariff policy, reflect the scarcity of electricity through price gradients, and achieve market-oriented divisions by pricing different levels of electricity consumption, promoting residents to consciously reduce electricity consumption, and improve electricity efficiency, respectively. In addition, a combination of centralized and unified government leadership and actions that suit local circumstances can be adopted. The State Council should formulate step tariff policies, and local governments should make specific rules for implementation in line with the actual situation of local economic development, residents’ income, and electricity consumption. Specifically, the impact of step tariff policies can be expanded by reducing the first-tier electricity price, which will not only safeguard the interests of low-income groups and encourage them to reduce electricity consumption but also enhance the enthusiasm of middle- and high-income residents’ awareness of it. At the same time, ensuring reasonable utilization of the second-tier electricity price and widening the price gap between the first and second tier can drive residents to consciously reduce electricity consumption. In addition, appropriate adjustments should be made to the difference in electricity prices among different gradients; the third-tier electricity price should be raised and the severe waste of electricity or extravagant behavior related to electricity consumption should be punished to guide residents to form an awareness of electricity reduction, cultivate good habits related to reduction, and avoid waste. The government should strengthen its dominant position in formulating regulatory policies, fully balance the role of the market in promoting residents to reduce electricity consumption, effectively utilize economic policy devices relevant to prices, fees, taxes, financial subsidies, etc., and encourage residents to consciously reduce the consumption of electricity.

(2)

An incentive mechanism for residents should be established to reduce electricity consumption and residents should be encouraged to reduce electricity consumption more by making them fully aware of the contribution of individual electricity reduction to energy conservation and emissions reductions. Firstly, a point-rewarding system can be established, praising residents who actively reduce electricity consumption and who have shown an outstanding performance in their communities or work units. The system should also be constructed as an important indicator for evaluation, referring to public services enjoyment, point-based settlement, talent points, etc. Secondly, the construction of a national carbon trading market should be accelerated, the establishment of personal carbon accounts encouraged, and the energy saved by individuals converted into a carbon currency for the quantification of residents’ reductions. The carbon currency can be used to deduct electricity charges, exchange goods and vouchers, or directly engage in transactions. By formulating clear and detailed carbon trading rules, we can achieve a close connection between carbon trading and residents’ daily lives and work, expand residents’ participation, and increase their enthusiasm for reducing electricity consumption. It is worth establishing a family carbon account and selecting family role models to drive the whole family to reduce electricity consumption as well. According to empirical analysis, perceived behavioral control is a factor that affects residents’ behavior regarding electricity consumption reduction, while family members have the greatest impact on individuals. Therefore, positive interactions within the family can encourage residents to reduce household electricity consumption and help each family member develop good habits related to electricity reduction. Thirdly, support and incentives for reducing electricity consumption in public areas should be increased. Party and government organizations and institutions should take the lead in reducing electricity consumption, incorporating electricity consumption reduction into the assessment system, and conducting quarterly or annual evaluations based on the contribution of electricity consumption reduction. Honors such as “Contribution Award of Electricity Consumption Reduction” and “Electricity Consumption Reduction Star” or related bonuses should be awarded to motivate employees’ participation. In addition, in public areas such as supermarkets, hotels, and office buildings, physical rewards are set up for residents who voluntarily use less electricity. Residents are encouraged to reduce their electricity consumption by shortening the working time of equipment, reserving their duration of usage, and other methods. By using intelligent monitoring systems to monitor electricity consumption in real time, data such as electricity consumption and carbon emissions generated by electrical appliances in public places can be made public to residents to motivate them to conserve energy and actively reduce electricity consumption.

5.3. Innovations in Policy Publicity

The policy publicity of guiding residents to reduce electricity consumption not only allows for more residents to understand relevant knowledge on reducing electricity consumption but also enhances their subjective norms, perceived behavioral control, and other psychological cognition through dissemination. Because of them, good social norms for the whole of society can be formed to encourage residents to consciously reduce electricity consumption in their daily lives. In encouraging residents to reduce electricity consumption, the government usually relies on publicity to ensure policies are better received, such as by advocating “Propaganda Week of Energy Conservation”, “World Environment Day”, and other themed activities. Promoting experiences raised from such practices with outstanding energy-saving effects and energy conservation laws and policies, popularizing energy-saving knowledge, and conducting public opinion supervision on energy waste behavior are feasible measures as well. Compared with its various means of implementation, policy publicity is characterized by obvious homogenization with less novelty, resulting in a lack of innovation and adaptability. This is mainly manifested in the following three aspects: First, there is the single publicity model. Policy publicity covers limited fields. The existing publicity mainly involves centralized training organized by environmental protection departments and irregular offline dissemination in communities, campuses, etc., resulting in a low coverage rate. Second, many publicists lack a deep understanding of the publicity content and cannot answer residents’ questions convincingly, which affects the effectiveness of the publicity. Finally, there is a lack of communication and cooperation among different advocacy groups that work with their plans. The environmental protection departments leading existing policy publicity have collaborated with news media, social organizations, volunteer groups, and other organizations, but there is still a lack of coordination among different organizations and institutions, causing procrastination in publicity work sometimes. The organizations and institutions that jointly carry out publicity work have not put enough effort into engaging at the grassroots level and being close to life, which leads to marginal success. Second, there are relatively few forms of publicity media. The existing publicity media are still dominated by traditional forms, such as brochures, banners, posters, and public service advertisements. Although it can be publicized through the WeChat official account, short videos, the most searched topic, and other new media channels, the massive amount of content has resulted in the repetition of certain information, while some content has never been popularized. It is more difficult than expected to arouse residents’ interest. Third, there is a lack of targeted publicity. The existing policy publicity generally adopts a universal approach. However, residents are scattered in different regions. They have different ages and educational backgrounds, as well as variable incomes and family situations. So, using the same publicity method cannot achieve the relevant goals and enhance residents’ policy perceptions. In addition, the current policy publicity pays attention to superficial practice and lacks in-depth and detailed content. For example, some residents pointed out in interviews that during the annual “Propaganda Week of Energy Conservation”, publicists only provided simple introductions and hung banners. They did not explain energy-saving knowledge and methods in detail, which seriously affects the publicity and leads to residents’ limited acceptance of the content.

(1)

Implementing targeted policy publicity is an effective way to solve the problem of poor publicity’s effectiveness, as mentioned above. According to the previous research results, demographic factors such as gender, age, education, and income have a significant impact on residents’ reduction in electricity consumption. Therefore, targeted education and publicity for groups with different characteristics is a prerequisite for guiding residents to reduce electricity consumption. First, publicity is based on gender. Generally speaking, women pay more attention to electricity conservation in their daily lives than men. Therefore, when promoting, supervising, and guiding electricity conservation, it is necessary to strengthen education and guidance for men. Women’s family status can also be utilized to mobilize them to reduce electricity consumption and promote mutual supervision among family members through grassroots women’s federations and other organizations. Second, publicity is based on age. According to the previous analysis, compared with the middle-aged, elderly, and underage groups, electricity consumption reduction among youths was significantly lower, so more attention should be paid to guiding them to increase their understanding of electricity consumption reduction. For the elderly, with better habits related to electricity reduction, their acceptance of knowledge and methods of electricity reduction can be strengthened. For families with children, the community can collaborate with schools to carry out “carbon education” or organize parent–child activities to enhance their ability to reduce electricity consumption through the exemplary role of parents. Third, publicity is based on education and income. In the previous difference analysis, we found that education and monthly income have an impact on residents’ electricity consumption reduction. On the one hand, the higher the level of education, the more open the mindset toward electricity conservation and the greater the understanding of relevant knowledge. On the other hand, some groups with high education and income levels do not pay attention to reducing electricity consumption due to fewer economic constraints. It is necessary to link the reduction in electricity consumption by such groups with their social status and social value so that they can achieve social value and improve social status while reducing electricity consumption to promote a change in their behavior. Fourth, attention should also be paid to phased publicity during the process of reducing electricity consumption by residents. In the early stage, the Internet can be used to spread information and increase residents’ cognition rate. For example, it is necessary to popularize knowledge on reducing electricity consumption through organizing community activities, publishing WeChat pushes, distributing publicity materials, and other means. In the medium term, model residents can be selected according to their responses and receive professional training to further cut down electricity consumption to promote the active participation of other residents. Finally, when certain goals are achieved in the later stage of electricity conservation, model families and individuals can be selected and widely praised to play an exemplary role and encourage more families to participate in electricity conservation activities.

(2)

Innovative publicity methods can effectively enhance residents’ perception of policies. First, digital means can be utilized. Policies guiding residents to reduce electricity consumption can be disseminated through social media, video production, website design, and other channels or methods. Innovative technologies, such as data visualization and virtual reality, can also be adopted to visually present policy content and its implementation effects to residents. Second, interactive elements can be introduced. For example, improving residents’ participation and making policy publicity more interesting and interactive through interactions such as live streaming and online Q&A are valid methods. Third, full play to the “brand effect” can be provided. By printing relevant policy slogans on billboards, clothing, office supplies, etc., the “brand influence” of policies is enhanced, and the attention of residents is widely attracted. Fourth, interesting elements can be incorporated. Policy content can be integrated with interesting daily events, cultural phenomena, and common sense to draw residents’ attention. Fifth, multimedia presentations can be used. Vivid and expressive multimedia presentations should be utilized to demonstrate and analyze the content, implementation process, and advantages of relevant policies to residents in order to enhance their awareness and support for policies. The comprehensive application of the above methods can bring vitality and innovation to the policy publicity of guiding residents to reduce electricity consumption. It can stimulate their enthusiasm for participating in relevant activities and improve the efficiency of policy implementation.

6. Conclusions

Through a one-way ANOVA of the demographic factors, this study found that residents’ behavior related to reducing electricity consumption showed significant differences across different ages, educations, incomes, and household sizes. Through a structural equation modeling analysis, it was found that subjective norms, perceived behavioral control, and knowledge of electricity conservation had a significant positive impact on residents’ willingness to reduce electricity consumption. Subjective norms were the strongest influencing factors, while attitude had no apparent influence on residents’ willingness to reduce electricity consumption. Through hierarchy regression analysis, this study found that economic incentive policies can positively regulate the relationship between willingness to engage in electricity conservation and behavior aimed at reducing electricity consumption in the private sphere, so willingness can be better converted into behavior.

On the basis of the results of the qualitative research and empirical analysis, the following suggestions are put forth: (1) formulate policies and regulations to guide residents in reducing electricity consumption; (2) improve incentive policies encouraging residents to reduce electricity consumption; and (3) promote the innovation of policy publicity for electricity consumption reduction by residents.

Limited by personal ability and other objective factors, there were some limitations to this study in selecting the influencing factors, representative research samples, and other aspects. The outlooks for future research work are as follows:

(1)

Explore in depth the influencing factors. Different simulated scenarios should be set up to explore the factors influencing residents’ behavior related to reducing electricity consumption through experimental research. Some variables can be further studied, such as residents’ sense of environmental responsibility, electricity-using habits, and policy perception.

(2)

Expand the scope of research. The research can be conducted gradually with a larger scope, from B city to the whole country, which would guarantee more accurate and reliable research conclusions.