Residential electricity consumption behavior: Influencing factors, related theories and intervention strategies

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Renewable and Sustainable Energy Reviews 81 (2018) 399–412

Contents lists available at ScienceDirect

Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser

Residential electricity consumption behavior: Inﬂuencing factors, related theories and intervention strategies

MARK

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Zhifeng Guoa, Kaile Zhoua,b, , Chi Zhanga, Xinhui Lua, Wen Chena, Shanlin Yanga,b a b

School of Management, Hefei University of Technology, Hefei 230009, China Key Laboratory of Process Optimization and Intelligent Decision-making, Ministry of Education, Hefei University of Technology, Hefei 230009, China

A R T I C L E I N F O

A BS T RAC T

Keywords: Residential electricity consumption Inﬂuencing factors Behavior interventions Theories

The proportion of residential electricity consumption in the total energy consumption has increased rapidly in the past decades all over the world. It is becoming increasingly important to promote household energy conservation for the sustainable development of a country in the case of resource constraints. This paper reviews and evaluates the existing research works which are related to the residential electricity consumption behavior. Particular attention is given to the following aspects. (1) Factors inﬂuencing residential electricity consumption in social psychology. (2) Theories of social psychology in understanding residential electricity consumption behavior. (3) Diﬀerent interventions aiming at encouraging households to reduce electricity consumption. Finally, we discuss the challenges and opportunities of research on residential electricity consumption behavior in the big data era.

1. Introduction Environmental pollution and scarcity of resources have become major factors that aﬀect the sustainable development of global economy since 21st century [1]. Irrational use of energy has led to environmental pollution and unsustainable development for a long time. Electricity has played an essential role in our society [2]. However, the main way of generating is thermal power, which accompanied with air pollution. In this sense, reducing electricity consumption has been important implications for sustainable development of society. The power demand of residents is a part of the social power demand. The proportion of residential electricity consumption has growing with increasing household appliances and population. Residents only know the monthly consumption of electricity before the popularity of smart meters. They have few information about the daily consumption of electricity, and people always receive the past electricity consumption bills after several months. The comparison of electricity consumption was lacked. Meanwhile, residents do not care about consumption of electricity. With the popularity of ﬁrst generation of smart meters, people could know their electricity consumption every day and even every 15 min [5]. People can pay oﬀ their electricity consumption bills on the Internet. The pattern of electricity consumption is more like the use of mobile phone. During this period, people have begun to pay more attention to electricity consumption gradually, so information makes the residents really give attention to their

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consumption bills and related electricity consumption behavior. At present, many scholars have done a lot of researches on residents’ energy-saving behavior [3]. From the perspective of content, the researches mainly focus on the following three aspects. The ﬁrst aspect is the analysis of the main factors that have eﬀects on residential electricity consumption behaviors, including household characteristics, socio-economic factors, social-psychology factors and related environmental behavior theory [17]. The second aspect is the statistical analysis of electricity consumption's data. The regular pattern of electricity consumption was found [6]. For example, residents with the similar load proﬁle can be clustered into one class with the help of cluster analysis. The third aspect is the implementation of intervention [11]. The researchers made an intervention on residents based on psychological factors and mode of action. So we can reduce electricity consumption by means of energy-saving intervention strategy. With the development of big data and cloud computing, it is more convenient to study the behavior hiding behind the electricity consumption [34]. By means of the Internet technology, researchers can be more convenient to investigate the behavior of residents that related to electricity consumption. During big data era, it is possible to store and analysis massive data. Power Company can give feedbacks about electricity consumption to customers more frequently through big data analysis [25]. We can draw more reliable conclusions with the support of data mining, and further make more eﬀective interventions. The purpose of this paper is to review and summarize literatures

Corresponding author at: School of Management, Hefei University of Technology, Hefei 230009, China. E-mail addresses: [email protected], [email protected] (K. Zhou).

http://dx.doi.org/10.1016/j.rser.2017.07.046 Received 6 January 2017; Received in revised form 23 March 2017; Accepted 10 July 2017 1364-0321/ © 2017 Elsevier Ltd. All rights reserved.

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related to residential electricity consumption. Firstly, the paper analyzes the vital factors inﬂuencing residential electricity consumption. Secondly, we review the social psychological factors, their mechanism of eﬀecting, and related behavior theory. Finally we summarize the ﬁve most common intervention strategies and research direction of residential electricity consumption in big data era. 2. Social psychological factors inﬂuencing residential electricity consumption behavior Home is the basic unit of electricity consumption, therefore the reduction of electricity consumption per household will reduce the electricity consumption of the whole society [27]. So we need to ﬁnd the factors which have signiﬁcant impacts on household consumption of electricity in order to reducing electricity consumption. Diﬀerent families have diﬀerent structure, cultural background and ideological concept. Under the inﬂuence of kinds of factors and their interactions, each family has a diﬀerent load proﬁle. Meanwhile, diﬀerent load proﬁle also reﬂect diﬀerent family types and consumption behaviors. This section summarizes the characteristics of the household from many literatures [29,30,32,33] including: (1) Number of family members. (2) Children. (3) Age composition of family members. (4) Level of education. (5) Social status of family. (6) Family economic situation. (7) The type of a house. The eﬀects of diﬀerent family characteristic factors on household electricity are described in the following.

(3)

(1) Number of family members. The relationship between the number of households and electricity consumption has been studied by many scholars. The majority of literatures showed that the number of households has a positive impact on electricity consumption. With the increasing number of households, household electricity consumption will also increase. Leahy and Lyons [7] studied the electricity consumption of single and double people in Ireland. By comparison, they found that a single apartment have less than 19% of the electricity consumption per week. Yohanis et al. [8] studied the relationship between the number of households and electricity consumption in an apartments in Northern Ireland. The results showed that the apartment lived with four people or more people are used to consume highest average annual electricity consumption. And there was no obvious diﬀerence between houses lived with two people and three people in average annual electricity consumption. Bartiaux and Gram-Hanssen [9] investigated the relationship among the number of families, housing type and electricity consumption. The results indicated that the correlation between the number of households and electricity consumption is the most signiﬁcant. In the three types of housing (independent, semi-independent, apartment). The number of households has always been signiﬁcantly associated with electricity consumption. (2) Children. Children is also an important factor aﬀecting electricity consumption [35]. Many scholars have made researches on the relationship between the composition of the family members and electricity consumption. There are two opposite results. A part of the studies found that the composition of family members had a signiﬁcant impact on consumption of electricity. For example, Mcloughlin et al. [10] studied on the relationship between household electricity consumption and whether the family have children or not. They found that the family had children consume more electricity than the family had no children. Brounen et al. [12] found that the family with a child consume more 1/5 electricity than the family without children. With the growth of the child, household electricity consumption will also increase. In Brounen's opinion, children tended to play computer, watch TV, play games or other electrical device, these activities would lead to consume electricity. However, Bartiaux and Gram-Hanssen [9] had opposite conclusion. They found that the family with two or

(4)

(5)

(6)

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more children (children 0–9 years old) had a negative impact on the electricity consumption, and having children has reduced the average electricity consumption. Gram-Hanssen found that the eﬀect was signiﬁcant in the Danish region, but was not in Belgium. Wallisn et al. [87] analyzed the inﬂuence of the number of adolescents on electricity consumption, they found that adolescents’ frequent purchasing of IT appliances led to higher electricity consumption. Cramer et al [24]. found that children under 3 years old had no signiﬁcant eﬀect on household electricity consumption in the American family. However, for the family has children over 3 years old, there was a signiﬁcant impact on consumption of electricity. However, in Ireland, Leahy and Lyons [7] showed that families with children had no signiﬁcant diﬀerence in electricity consumption. Nakamura [28] showed that the mother having child was easier to participate in some schools and community organizations, and they tend to know the information of energy conservation. Age composition of family members. According to Yohanis et al. [8], the age of family member had inﬂuence on household electricity consumption. And electricity consumption is relatively high, when the age of the family member is 50–65. Electricity Consumption is relatively lower, when the age of family member is less than 50 years old or over 65 years old. Leahy and Lyons [7] pointed out that electricity consumption of household where age of the family member is between 45 and 64 was signiﬁcantly higher than that of 35–44 years old in Ireland. Household electricity consumption decreased signiﬁcantly when age of the family member is more than 64 years old. Mcloughlin et al. [10] found that household electricity consumption of family where age of the member is 18–35 was less than 36–55 or 56. Researchers believed that this is middle-aged family has more children and rooms. So the consumption of electricity is more. Kavousian et al. [26] found that in the United States, these families whose age of the family member is more than 55 or 19–35 consume less electricity. Filippini et al. [27] found in the India area, the family whose age of responsible members is less than 45 have less consumption than the family whose age of responsible members is older. Level of education. The educational level of the family member has inﬂuence on electricity consumption. The conclusion is also uncertain. Bartiaux and Gram-Hanssen et al. [9] found that household electricity consumption decreased signiﬁcantly as the level of education increased. The family members with higher degree of education consumed less electricity than the family members with low education level. However, According to Cramer et al. [24], the educational level of family members had no signiﬁcant impact on electricity consumption both in the United States and Holland. Social status of the family. Social status has diﬀerent inﬂuence on electricity consumption according to current research's conclusions. Mcloughlin et al. [10] found that socio-economic status of a family had a signiﬁcant impact on household electricity consumption. And there was a signiﬁcant positive correlation between socioeconomic status and household consumption. The higher social status of household consumption was accompanied with more electricity consumption. However, according to Leahy and Lyons [7], family members' economic status had no signiﬁcant impact on household electricity demand. Family economic situation. Economic situation mainly involves two aspects [54]. On the one hand, it is the family income; On the other hand, it is the family disposable income. These two aspects reﬂect the economic situation of a family. A large number of literatures showed that household electricity consumption increased with income. Yohanis et al. [8] found that in Northern Ireland, the households whose annual incomes of more than 30,000 Irish pounds consumed more electricity than the low income families which has annual income of 10,000 Irish pounds.

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3.1. Social cognitive theory

One possible reason was that higher income families tended to have a large area of housing and household appliances. This led to more electricity consumption. However, eﬃciency of home appliances and electronic devices is also vital to energy saving. Wealthy families have ability to buy smart appliances and install related home power management systems, some poor families can only aﬀord energy saving bulb. This situation will eventually change with the development of economic. More and more people will choose energy-saving equipment. Ozkan [81] used smart home power management systems to reduce electricity cost and improving energy eﬃciency while maintaining their comfort. The result indicated that the system provided improvements in terms of the energy consumption reduction of about 5–16% compared to conventional electronic devices usage. (7) The type of a house. House is the basic unit of people's life, diﬀerent lifestyles are determined by the type of a house. In this sense, diﬀerent house will display various load proﬁle. On one hand, diﬀerent type of a house display diﬀerent consumption behavior, on the other hand, individuals have diﬀerent attitude towards energy in diﬀerent place. For example, there are the distinction behavior between oﬃce and home settings. Littleford et al. [82] investigated the relationships between energy consumption behaviors performed in oﬃce and home settings. The result indicates that the home setting is an important feature of the energy use behavior. Dixon et al. [83] discovered the sense of community is key factor in workplace energy conservation. Therefore, type of a house is a vital factor that has an eﬀect on electricity consumption behavior.

The famous American social psychologist Bandura ﬁrst put forward social cognitive theory [66]. The theory claims that the motivation of the individual is the result of the interaction among the individual, environment and behavior (see left panel Fig. 1). The individual refers to people's belief, goal, attitude, intention, emotion, and so on, which reﬂects the individual's cognitive ability. Environment refers to the resources, the consequence of action and physical conditions, and it reﬂects the objective conditions of individual. The interaction between the individual and behavior shows that the individual's beliefs, goals, attitude, intention and emotion will aﬀect the one's behavior, and vice versa. The interaction between behavior and environmental factors shows that the environment is the result of the behavior, however the behavior can also change the objective environment to make the subject more suitable. The interaction between personal factors and environmental factors shows that the main beliefs, goals, attitudes and emotions are determined by environmental factors, but the eﬀect of the environment on the subject is not absolute. According to social cognitive theory, self-eﬃcacy and outcome expectations are the most important concepts. Self-eﬃcacy refers to extent of conﬁdence in one's own action. As a result, the higher the selfeﬃcacy is, the more likely he is to perform the action. Outcome expectation is the result of one's likelihood of completing a task. Positive outcomes are expected to promote individual behavior, while negative outcomes are expected to hinder individual behavior. As far as energy, a more pluralistic viewpoint is depicted in Fig. 1. There are two panels in the ﬁgure. The left panel is macro factors that originate from social cognitive theory, and the right panel is micro factors that are summarized form many related papers. To some extent, the right panel is concrete form of left panel. In reality, there are three aspects that are related with individual's behavior. Namely, culture, society and economic. Individual's decision environment is consist of these three factors. Culture could have the most lasting impact on people, education is a way to spread culture. Economic is important factors that are have positive eﬀect on energy-saving behavior. Many scholars have many factors has been researched the relationship between energy-saving behaviors and these factors. For example, income has positive eﬀect on electricity consumption by many scholars [84] as mentioned earlier. Kyriakopoulos et al. [97] studied the issue of technological advancements and the social acceptability of renewable energy technologies and point importance of renewable energy technologies’ diﬀusion in the everyday life of people. Education on energy issues is vital to students. They tended to form correct energy attitudes, lifestyle and behavior that will be good for whole society with the help of environmental education, and education has the most lasting impact on people. Ntona et al. [85] researched on student's viewpoints and attitudes about energy and its usage related to the environment, Their ﬁndings indicated that the education need a vital change towards an environmentally sustainable orientation. In addition to the school, the family is an important place to cultivate habits of saving energy. Social factors, such as subsidies have inﬂuence on electricity consumption behavior. Nicolini and Tavoni [98] veriﬁed if policy support for renewable electricity have been eﬀective in promoting renewables in the ﬁve largest European countries during 2000–2010. The result indicated that these policies have been eﬀective in promoting renewable energy, both in the short and in the long term. In general, economic, social, cultural factors form a vital environment that has important inﬂuence on decision process. Culture has a lasting and stable inﬂuence on behavior. Social and economic factor have transient eﬀect, for example, if welfare can not last or people's ﬁnancial status gets bad, people will choose cheap products without considering environmental factors. In aspect of environmental behavior theory, many scholars regarded social cognition theory as the research framework and analyzed the eﬀect of various psychological factors. Thøgersen and Grønhøj [67]

3. Theories of social psychology in understanding residential electricity consumption behavior From a psychological point of view, the basis of a person's behavior is driven by psychological factors [68]. Therefore, there is a complex psychological process behind the energy consumption behavior, which involves a number of psychological factors. In recent years, many scholars have studied the behavior of energy saving from the perspective of psychology, and analyzed how these factors have inﬂuence on behavior. This section summarizes various factors that aﬀect the behavior and the mode. The main psychological factors are attitude, belief, values, culture, habits, preferences, subjective norms, environmental awareness, and self-eﬃcacy, etc. [69]. These psychological factors aﬀect the behavior indirectly. Person's behavior is inﬂuenced by psychological factors through a variety of ways. Some scholars have studied the eﬀect of psychological factors from the viewpoint of environmental behavior, and put forward the new social psychology theory based on classical theory. The behavioral theories are mainly social cognitive theory, social norms theory, and theory of reasoned action, theory of planned behavior, goal-oriented behavior model, value-belief–norm theory, norm activation theory, self-regulated behavior change theory and ABC theory [70–75]. Diﬀerent behavioral theories are based on diﬀerent psychological factors and the general pattern of eﬀecting. Each theory has its own advantages and disadvantages. And as far as the theory is concerned, it has been developing and improving. Therefore, there exists many connections among diﬀerent theories, For example, from the theory of reasoned action to the theory of planned behavior, and from the theory of planned behavior to the model of goal-oriented behavior. Another example is that value-beliefnorm theory is the perfect of norm activation theory. Therefore, none of the theories can explain all the environmental behavior, and each theory has its own limitations. Therefore, in the study of electricity consumption behavior, vital psychological factors should be determined by a variety of experiments. Table 1 presents a brief description of each behavior theory. 401

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Table 1 A brief description of behavioral theory. Theory

Author

Description

Refs.

Social cognitive theory Social norms theory Theory of reasoned action

Bandura Elster Fishbein, Ajzen

[66] [80] [53,54]

Theory of planned behavior

Ajzen

Model of goal-directed behavior Norm-activation-model Value-belief-norm theory Self-regulated behavior change theory ABC theory

Perugini

Subjective initiative is the result of the interaction between the individual factors, the environment and behavior. Social norms that created and observed by people; individual is expected to share in the group Person's behavior is determined by the behavior intention, behavior intention is affected by the attitude and subjective norm Actual behavior is determined by behavior intention, and the behavior intention is affected by the attitude, subjective norms and perceived behavioral control effect Attitude, subjective norm and perceived behavioral control did not directly affect the behavior intention, but the affect behavior intention through desire which were an intermediate variables People's environmental behavior is the result of norm, belief and value Values, beliefs, and personal norms affect a person's behavior gradually, from values to action in turn The theory suggests that a person's behavior can be changed under certain conditions, even if the behavior has been a habit Individual behavior is the result of mutual effect between attitude and the external context

Schwartz Stern Bamberg Guagnano

Macro factors

[52] [59] [50] [51] [55] [57]

Micro factors

Environmental factors resources others action results physical condition

Economic factors welfare financial status employment

Behaviors

Individual factors belief goal attitude intention emotion

Social factors cohesion inclusion acceptability

Cultural factors family environment humanistic background education profile

Fig. 1. Interactions among environment, behaviors, and person [66].

establishment of structural equation model. The results suggest that: (1) we should change the socio-structural environment to be more convenient for energy saving behaviors. (2) Feedback about their household's electricity consumption is a vital factor that has inﬂuence on their own behavior.

constructed the framework to analysis electricity saving behaviors in households based on social cognition theory (see Fig. 2). In addition to the psychological factors, the social structural factor was also put into model as an inﬂuencing factor. Self-eﬃcacy and outcome expectation are the main factors inﬂuencing the behavior intention. The sociostructural factor and perception of others’ behavior are known as structural factors. The proposing assumptions are as follows. (1) Individual's behavior is aﬀected by outcome expectations, self-eﬃcacy, socio-structural factor, perception of others’ behavior and goals. And outcome expectations self-eﬃcacy, socio-structural factor and perception of others’ behavior cannot only have a direct impact on the behavior, but also indirectly inﬂuence behavior through goal. (2) The outcome expectation, self-eﬃcacy, perception of others’ behavior, and socio-structural factor have mutual inﬂuence among themselves. (3) Outcome caused by individual's behavior can give feedback on the outcome expectations and self-eﬃcacy socio-structural factor. Researchers veriﬁed hypothesis through a questionnaire and the

3.2. Social norms theory Norms ﬁrst comes from the Latin word Norma, which means a ruler. However, the standard concepts came into the social psychology, which owing to the famous social psychologist Sherif's experiment in 1936 [61]. From then on, the norm theory has become an important theoretical in many social sciences. Norms in the ﬁeld of sociology are also known as social norms that is proposed formally by Elster [80]. To a certain extent, social norms and norms have the same connotation. Social norms have diﬀerent deﬁnitions with the development of society. In the earlier years, according to Sherif [61], it was deﬁned as customs, 402

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Attitude

Outcome expectations

Intention

Behavior

Goals Subjective norm

Self-efficacy

Fig. 3. Theory of reasoned action [53,54].

Environment al knowledge

Behavior Sociostructural factor

Environment al awareness Environment al attitude

Outcome Perception of others behavior

Economic background

Intention of green purchase

Behavior of green purchase

Fig. 2. Social cognitive model based on behavior and learning [66].

Technologica l development

traditions, standards, rules, values, fashion and so on. Recently, a concept that is more generalized is what the individual is expected to share in the group. Social norms are divided into descriptive norms and the injunctive norms in general. The descriptive norm is to point out what most people are doing, and the injunctive norms is to point out the behavior that others disapproval of [62]. The impact of social norms on individual behavior is mainly divided into three stages according to Kelman [63]. The ﬁrst stage is compliance. During this period, the individual try to change their behavior in order to get a reward or avoid punishment on the surface. The second stage is identiﬁcation. After a long-term impact, the individual begins to consciously abide by the expectations of others. The third stage is internalization, and in this stage, individual really accept the external values from the heart, convert the social norms into personal norms, and regard it as long-term guidance. Social norms on human behavior are mainly reﬂected in pro-social behavior, especially for the pro-environmental behavior [65]. Person's behavior can be inﬂuenced by social norms through diﬀerent ways. There are diﬀerent models according to the diﬀerent perspective, such as the norm activation theory, value-belief-norm theory, and the theory of planned behavior. In the ﬁeld of consumption of electricity, reduction of electricity consumption has taken good eﬀect by social norms. The most successful is the case of OPOWER Company [64]. OPOWER send Home Energy Report letters to residents, in order to make intervention. It also provides social norms information, which compares the household electricity consumption and their neighbors’ consumption in report. The results showed that the average treatment eﬀects is 2%. Therefore, social norms is of great signiﬁcance for reducing electricity consumption.

Peer pressure

Energy label

Fig. 4. Research model [23].

external pressure to perform or not to perform a certain behavior. And the pressure is caused by others. The contribution of the theory of reasoned action is to consider the social factors such as the subjective norm, it means behavior is not only aﬀected by their own attitude but also by the outside world. Many scholars have constructed energy consumption behavior model based on theory of reasoned action. Zainudin [23] used the TRA (theory of reasoned action) to construct the framework, which designed to display process of public green purchase intention (see Fig. 4.). In this model, the researchers supposed that public's willingness to buy environmental product is inﬂuenced by environmental knowledge, environmental awareness, environmental attitude, environmental attitude, peer pressure and the energy label. The researchers hypothesized that: (1) Environmental knowledge, environmental awareness, environmental attitude and behavior intention indirectly inﬂuenced people's behavior by means of peer pressure. (2) Environmental knowledge, environmental awareness, environmental attitude, and peer pressure had positive impact on behavior intention. These hypotheses were veriﬁed by constructing a structural equation model. The ﬁnal analysis results showed that environmental knowledge, environmental awareness, environmental attitude and peer pressure played a positive role in promoting green energy purchase intention, and environmental label on green had a negative impact on energy purchase. However, economic background and technological development also have signiﬁcant inﬂuence on green purchase inten-

3.3. Theory of reasoned action Theory of reasoned action (see Fig. 3) was proposed by Fishbein and Ajzen in 1975 [53,54]. The theory proposes that a person's behavior is determined by the behavior intention, and the greater the behavior intention is, the more likelihood he will perform the behavior. Behavior intention is aﬀected by the attitude and subjective norm, attitude is extent of supporting behavior. Subjective norm refers to the 403

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tion (see Fig. 4). In this sense, environmental knowledge, environmental awareness, environmental attitude, environmental attitude, peer pressure, energy label, economic background and technological development form a more practical framework (see Fig. 4), and many scholars have done many researches under this framework. Pothitou et al. [89] gave attention to the impact of knowledge about environmental, attitudes, habits and energy issues on potential pro-environmental behavior in households. The results showed that signiﬁcant correlations which indicate that residents with positive environmental values and greater environmental knowledge were more likely lead to energy-saving behavior. Testa et al. [91] researched the determining factors behind individuals' decisions to purchase energy saving products. They found that personal norms and trust in information provided by private companies and family and friends have inﬂuence on adoption of energy-saving purchases. Suki [92] investigated the inﬂuence of consumption values (i.e. functional value, social value, emotional value, conditional value, and epistemic value) in environmental concern on purchasing of green products. They found that social value has most important impact on consumers' environmental concern as expressed by their purchase of green products. Ramayah et al. [93] analyzed how individual values and attitudes in a developing country inﬂuence purchase intention of a green product from the perspective of the TRA. Results indicated that individual consequences relating to amount of eﬀort and convenience of consumers was negatively related to intention to purchase of green product. OlsonHazboun et al. [94] analyzed the relationship between environmental beliefs, climate change opinions and support for renewable energy through questionnaire of ﬁve communities in the Rocky Mountain region of the U.S. The results showed that public support for renewable energy was less related to environmental than to some other factors, including economic beneﬁts. Hast et al. [95] analyzed consumers’ attitudes towards green energy in China and their willingness to purchase of green electricity or renewable energy systems. The results indicated that willingness to pay for a green electricity product is inﬂuenced by income, building type, how promising the renewable energy potential is seen. As mentioned earlier, ﬁnancial status are high related with electricity consumption on matter national level or individual level. Technological development is another factor that promote green purchase. Kyriakopoulos and Arabatzis [96] pointed that implementation of electrical energy storage systems should consider the diﬀusion of innovative technologies and comparison between innovative technologies and traditional technology.

Behavioral attitude

Subjective norms

Behavior intention

Behavior

Perceived behavioral control

Direct impact

Fig. 5. The theory of planned behavior [52].

processes hidden behind the residential electricity behavior according to the theory of planned behavior. Scott et al. [16] used the theory of planned behavior to do a survey of energy usage through a series of questions that are related with beliefs in British Yorkshire and Humber area. They measured the relationship between people's attitudes and the rate of adopting energy-saving device. The results showed that: (1) People who use energy saving devices easier were worried about abnormal changes in the global temperature. (2) The extent of familiarity with energy-saving device had impact on the rate of using energy saving devices. Residents were more willing to use familiar energy-saving devices. (3) As far as diﬀerent energy-saving devices, the respondents showed signiﬁcantly diﬀerent in the behavioral attitude, subjective norm, and perceived behavioral control. Based on the theory of planned behavior, Abrahamse and Steg [17] put forward the following hypothesis. (1) There was a strong correlation between household energy consumption and social demographic characteristics (such as income, family population). (2) Energy consumption was mainly determined by psychological factors. The results of regression analysis showed that the use of household energy was determined by demographic factors. Yazdanpanah et al. [18] studied on the relationship between social psychological factors and renewable energy. Researchers concluded that the social psychological factors (such as behavior, perception, and subjective norm) had signiﬁcant impacts on the adoption of the Energy Sources Renewable (RES) project. The researchers collected information from 260 students by questionnaires. The relationship between attitude toward RES, behavior attitude, perceived behavior, subjective norm and behavior intention was analyzed by means of structural equation model. The ﬁnal results showed that the code of ethics and behavior attitude and perceived behavioral control signiﬁcantly aﬀected the residents’ willingness to use renewable energy, but subjective norm and self-recognition did not signiﬁcantly aﬀect attitude toward renewable energy. Botetzagias et al. [19] studied the relationship between diﬀerent factors and energy-saving behavior by telephone interview. He regarded demographic characteristics, psychological factors and moral factors as explanatory variables, energy saving behavior is viewed as the explanatory variable for regression analysis. The researchers put forward the hypothesis that the power saving behavior depends on the demographic characteristics, psychological factors and moral factors. The results showed that age, gender and perceived behavioral control had signiﬁcant impact on power reduction. Paul et al. [31] constructed a new research framework (Fig. 6) by add concern environmental variables to the theory of planned behavior. He explored the factors that have inﬂuence on the willingness of Indian customers to buy green products by conﬁrmatory factor analysis through a questionnaire. The results showed that customer attitudes and perceived behavioral control can predict behavioral intention. However, social norms did not predict the intention. The results also showed that environmental concern and attitude, subjective norm, perceived behavioral control and purchase intention were positively correlated. Therefore, environmental concern can indirectly aﬀect purchase intention through

3.4. Theory of planned behavior In 1991, Ajzen [52] proposed the theory of planned behavior (TPB), which was an extension of the theory of reasoned action (TRA). According to the theory, there exists a complicated psychological process behind the individual behavior. The behavior is the results of a series of mental processes [60]. The actual behavior is decided by behavior intention, and the behavior intention is aﬀected by the attitude, subjective norms and perceived behavioral control (see Fig. 5). Behavioral attitude is extent of a person's support or not support a behavior. Subjective norm refers to the social pressure that people perceives when to decide whether or not to perform a particular behavior. Perceived behavioral control refers to the ability to perform a behavior. Accurate perception behavior control reﬂects the actual control conditions, it can be used as an alternative measure of the actual control conditions, so it can also be used as a direct impact on the behavior (as shown in Fig. 5). The accuracy of the prediction depends on the perceived behavioral control. Individual and social cultural factors such as personality, intelligence, experience, age, gender and cultural background aﬀect the behavior intention and behavior indirectly through behavior control behavior attitude, subjective norm and perceived behavioral control. Some scholars have done a lot of researches on psychological 404

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Attitude

Attitude Autonomous motivation

Environmental concern

Subjective norm

Purchase intention

Positive anticipatory effect

Actual behavior

Negative anticipatory effect

Perceived personal control

Desire

Intention

Perceived behavioral control

Direct impact Fig. 6. Research model [31].

Past behavior

attitude, subjective norm and perceived behavioral control, and it can also directly aﬀect the purchase intention. So when a person has a positive attitude towards green products and a high environmental concern, he is more likely to buy green products.

Subject norm

Fig. 8. Research model [58].

autonomous motivation factor and past behavior to model of goaldirected behavior. He intended to ﬁnd most signiﬁcant explanatory variable through the survey analysis. The results showed that autonomous motivation factor has most signiﬁcation ability to predict behavior than other variables, such as behavior intention, subjective norm, perceived behavioral control, and past behavior.

3.5. Model of goal-directed behavior Perugini and Bagozzi [59] proposed a model of goal-directed behavior based on theory of reasoned action and theory of planned behavior (see Fig. 7). The theory pointed out that attitude, subjective norm and perceived behavioral control did not directly aﬀect the behavior intention, but the aﬀect behavior intention by desire was an intermediate variable. And he put forward the concept of anticipatory eﬀect. Anticipatory eﬀect a dynamic reﬂection of reality. Anticipatory eﬀect is divided into positive anticipatory eﬀect (such as the desire for success) and negative anticipatory eﬀect (such as fear of failure). In the model of goal-directed behavior (see Fig. 7), attitude, subjective norm, positive anticipatory eﬀect, negative anticipatory eﬀect, perceived behavioral control have eﬀect on desire that have eﬀect on behavior intention. Behavior intention ultimately aﬀects the behavior. Model of goal-directed behavior was an improvement of the theory of reasoned action and theory of planned behavior. They pointed out that psychological factors have important eﬀect on behavior such as desire. Some researchers have applied the model of goal-directed behavior to energy. For example, Webb et al. [58] established a new theoretical framework based on Model of goal-directed behavior (Fig. 8). He added

3.6. Norm-activation-model The norm-activation-model was proposed by psychologist Schwartz in 1977 [50]. The model explains the intrinsic mechanism of people's pro-social behavior in the perspective of psychology. Pro-social behavior refers to all kinds of behavior that be beneﬁcial to others or society, such as: environmental protection, energy-saving behavior, water conservation and other environmental behaviors. Schwartz [50] described the process of people's environmental behavior (see Fig. 9) by introducing the conception of social norms, person norms, awareness of consequence, and ascription of responsibility. Social norms refer to values, attitudes and behaviors that most people identify with in society. Person norms refer to the moral obligation of a person. Person norms are the speciﬁc embodiment of social norms and mainstream values of the society. And what he behavior criterion reﬂected to the individual is the personal norms. Awareness of the consequences is that a person's attention to the consequences that caused by person's choice. Ascription of responsibility is refers to the negative consequences of cognition that caused by ignoring the action. According to norms of social activation theory, social norms have eﬀect on the individual through personal norms, but the person norms do not lead to environmental behaviors deﬁnitely. To some extent, it depends on the person's situation, which means that environmental behavior is also inﬂuenced by awareness of the consequences and ascription of responsibility. In other words, Person norm will cause the environmental behavior when awareness of the consequences and ascription of responsibility are relatively high. Zhang et al. [44] studied on the factors that have eﬀect on electricity saving behaviors in the company using the norm-activation-model. The researchers pointed out that electricity saving behavior in company is diﬀerent from electricity saving behavior in family. For example, workers who consume electricity in a company do not need to worry about spending money. In this case, saving electricity behavior is driven by moral norms. Researchers added organization electricity saving climate into the original model (see Fig. 10). They measured

Attitude

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Perceived behavioral control Fig. 7. Model of goal-directed behavior [59].

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Awareness of consequence

Social norms

Ascription of responsibility

Personal norms

Environmental behavior

Fig. 9. Normative-activation-model [50].

ment through questionnaire and analysis the relationship among them with the help of structural equation model. The results showed that the relationship between the sense of responsibility and the responsibility attribution is not signiﬁcant. Han [41] combined value-belief-norm theory with the theory of planned behavior to form a new theoretical framework (see Fig. 12). The lower part is the value belief norm theory and the upper part is the theory of planned behavior. The results showed that the integrated framework performs better than the single theoretical framework.

explanatory variable through the questionnaire and analysis data by partial least squares method. Results showed that when the employees have higher person norms, they are more likely to save electricity. However, higher organization electricity saving climate has weakened the inﬂuence of personal norms that has positive eﬀect on energy consumption behavior. When employees feel a higher ascription of responsibility, awareness of consequence and organization electricity saving climate, the staﬀ is more likely to form strong personal norms. Personal norms have positive impact on energy saving behavior. Han et al. [45] combined the norm-activation-model with model of goaldirected behavior in order to establish a new theoretical framework. The research results showed that the integrated framework has more explanatory power than the norm activation theory or model of goaldirected behavior.

3.8. Self-regulated behavior change theory Bamberg [55] put forward self-regulated behavioral change theory (SSBC) based on the theory of norm activation theory and the theory of planned behavior in 2013. The theory suggests that a person's behavior could be changed under certain conditions, even if the behavior has been a habit (see Fig. 13). Self-regulated behavior change theory is mainly applied to the analysis process of complex behavior. The selfregulated behavior change theory is divided into four interdependent stages, that is, pre-decision, pre-action, action, and post-action. Four states proceed in turn. There are also goal intention, behavioral intentions, implementation intention and new behavior in the modal. The goal intention refers the desire to achieve some kind of goal. The goal intention is through a series of psychological processes as well as the outside interference realization. Aiming at producing a goal, a person need to feel the negative impact of their current behavior ﬁrst of all, it will have a sense of responsibility. This sense of responsibility will produce negative emotions, and ultimately in the role of social norms and negative emotions, resulting in the intention of the target. When a person in the role of multiple factors to produce a target intention, it will be the transition to the second stage, which is, the stage of behavior and the stage of behavioral intention. Behavior intention refers to a person's speciﬁc behavior to achieve the goal. The main factors that aﬀect the realization of intention are behavior plan, cognitive plan and the ability to keep the plan. When the goal of the implementation of the intention to reach, after entering the stage of behavior. Behavior is mainly used in the third stage of the behavior, so as to achieve the real change behavior. In recent years, many scholars have begun to utilize self-regulated behavior theory to study residents’ energy consumption behavior. Based on the framework, Nachreiner et al. [21] investigated the relationship between smart meter information feedback and energy saving behavior. In the ﬁrst stage, researchers provided residents with information of electricity consumption. In this case, electricity con-

3.7. Value-belief-norm theory Stern et al. [51] put forward the value-belief-norm theory that combined with the value theory, norm-activation-theory and the new environmental paradigm in 1999. The new environmental paradigm is proposed by Dunlap and Liere Van [56]. It is an eﬀective tool to measure the environmental awareness, and NEP is short for new ecological paradigm (see Fig. 11). The theory pointed out that values, beliefs, and personal norms aﬀect people's behavior gradually. Valuebelief-norm theory consists of ﬁve variables, namely, values, NEP, awareness of consequence, attribution of responsibility, environmental ethics (see Fig. 11). Values is mainly consist of the ecological values, altruistic values, and self-interested values. NEP represents the general belief of people. Value-belief-norm has been expressed the transition from values to environmental behavior by a series of psychological changes. In value-belief-norm theory, a person's environmental behavior will occur only when he thinks it is his obligation to protect the environment. People will have NEP in their minds under the inﬂuence of a variety of values. And awareness of consequence, attribution of responsibility and environmental ethics proceed from the initial values to energy saving behavior in turn. In recent years, many scholars have studied the psychological factors that aﬀect residents’ behavior by means of the value-beliefnorm framework. Fornara et al. [20] used the value-belief-norm theory to study the relationship among the individual values, NEP, the consequences of consciousness, responsibility attribution, environmental ethics and the willingness to buy green equipment. They measures people’ values, NEP, awareness of the consequences, attribution of responsibility, environmental ethics, and the purchase of green equip-

Organizational electricity saving climate

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Fig. 10. Research model [44].

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Self -interested values Fig. 11. Value-belief-norm [51].

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Subjective norm Biospheric value

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Fig. 12. Research model [41].

saving skills, and people begin to make a plan for saving energy. In the fourth stage, people will be change energy-saving behavior into habits. Based on the SSBC framework, Mack and Tampe-Mai [22] developed an information system for making interventions on electricity consumption behaviors, the system mainly included: (1) electricity consumption and related data visualization (2) feedback chart (3) consumption analysis module (4) what is the tile (5) module the source

sumption information makes residents know their electricity consumption, people begin to set an energy-saving target. In the second stage, the researcher provided more detailed information on the electricity consumption, including each home appliance. In this case, residents learned consumption of each home appliance. They know which home appliance consumes most, and people begin to form behavior intention. In the third stage, the researchers provided people with many energy-

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Action planning cognitive planning maintenanc e selfefficacy

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Attitude toward and perceived behavioural control over alternative behavioural change strategies

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Fig. 13. SSBC model [55].

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providing information and result feedback are most used. Some researchers try make a comprehensive intervention strategy by means of the combination of ﬁve basic interventions. The results showed that the eﬀect of the comprehensive intervention strategy is better than the single intervention strategy. The following brieﬂy describe diﬀerent intervention strategies and the corresponding literature.

Behavior occurrence

External conditions Adverse

(1) Commitment. Commitment is one of the most common intervention strategies. Commitment is achieved by oral contract or written contract in which people promise to change their behavior for the reduction of electricity consumption. There are various forms of setting goal for people. At the beginning, the eﬀect of intervention strategies were obvious, but the eﬀect of intervention begin to get worse after a period of time. Katzev and Johnson [13] sent a paper contract to diﬀerent families, and it required people to reduce energy consumption by 10%. After a period of time, household that accept contract consumed less electricity compared with these who refused to accept the contact. The researchers further did another intervention experiment. The experiment compared commitment with other intervention strategies such as rewards and comprehensive intervention strategy. The results showed that comprehensive intervention strategy has best eﬀect on reduction of energy consumption. Commitment is used as an intervention strategy frequently in earlier year, in recent years, commitment is less used, at the end of experiment, the residents’ behavior is as usual as before. In this case, Commitment cannot lead to sustained energysaving behavior. (2) Goal setting. Goal setting is to set a goal for the family, such as reduction of 5% or 15% electricity consumption. The target value can either be set by the family itself, or it be set by the researchers. Target value cannot only be determined in the form of absolute value, but also determined in the form of proportion. Goal setting is used by most researchers. The goal that set too high or too low often led to worse eﬀect. Becker [14] set two targets for diﬀerent households, one is relatively easy to reach (saving 2%) and another is diﬃcult to reach (saving 20%). At the same time, the experimental group received feedback every week. In the experimental period, researchers provided with information about energy-saving skills. The results showed that these household that received a higher goal of saving 20% electricity saved most (15.1%). The experimental indicated that higher goal of reducing electricity consumption is achieved by providing with energy-saving information. Harding and Hsiaw [46] executed a plan that aims to encourage people to set a goal by themselves in Northern Illinois. The results showed that the reasonable goal of saving electrical consumption is achieved, and household saved average of nearly 11%, which is signiﬁcantly higher than those whose targets are too low or too high. Abrahamse et al. [47] performed an energy-saving intervention in Groningen. The households were divided into two groups. The ﬁrst group received tail information, tail feedback, and goal setting (5%). The second group is regarded as the control group without any intervention. During 5 months, researchers performed three aforementioned interventions, and the ﬁnal results showed that comprehensive intervention strategy reduces the energy consumption by 5.1%. (3) Providing information. Providing information is another common intervention strategy. Information is about environmental pollution, the signiﬁcance of saving electricity and the tips of saving energy. Providing information cannot only improve residents’ awareness of energy conservation, but also increase the knowledge of energy conservation. There are also a variety of ways to provide information. Common way of providing information is mass communication. The aim of providing information is to change people's consumption behavior from the heart, so providing

Favorable

Behavior does not occur Negative

Attitude Fig. 14. ABC model [57].

and climate information (6) comparison module (7) target setting module (8) energy saving module (9) energy-saving skills module. The system is used to support the behavior of diﬀerent stages in the SSBC model. In the energy and climate information module, people can understand the current global climate and energy status of the world, as well as the important signiﬁcance of emission reduction. Under the intervention of all kinds of information, the residents have the goal intention and tend to show more energy-saving behaviors. 3.9. ABC theory Guagnano et al. [57] proposed ABC theory in the study of garbage collection issues. The theory considers that individual behavior (B) is the result of mutual eﬀect between attitude (A) and the external context (C). The theory deems that a person's behavior is not only aﬀected by the individual's attitude, but also by the external environment. ABC theory emphasizes the impact of external factors (see Fig. 14). The horizontal axis represents the external conditions. The vertical axis represents the attitude. When external conditions and attitudes are greater than zero, behavior will occur. Behavior will not occur when the external conditions and attitudes are less than zero. When the external conditions are in a favorable position, action will occur. In the ABC theory, Guagnano emphasized the inﬂuence of external environment on the behavior of a person. He pointed out that when a person's attitude tends to zero, the external environment have a determined eﬀect on person's behavior. At this point, if the external environment is very favorable for behavior, it will greatly promote the occurrence of behavior; on the contrary, if the external environment is unfavorable for behavior, it will greatly prevent the occurrence of a person's behavior. In the same manner, when a person implements a behavior that costs much, the occurrence of behavior will depends on the attitude. ABC theory provides a new way of thinking for the research of energy saving behavior. 4. Intervention strategies The number of household electrical equipment has been increasing with the development of social economy, the same as the proportion of residential electricity consumption. Therefore, advocating energy-saving behavior has been an important issue for society. For a long time, household electricity behavior did not get enough attention. With the number of household equipment increases, electricity consumption accounted for the proportion of whole electricity consumption has increased too. In this sense. A number of studies have shown that intervention strategies can be used to reduce energy consumption. In this section, common ﬁve kinds of intervention strategies is reviewed, including commitment, goal setting, providing information, reward, result feedback. Among many intervention strategies, goal setting, 408

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intelligent device, namely intelligent device is two diﬃcult for people to use. Another reason is that people are not interested in consumption information, so intelligent hardware device cannot always be useful. Hargreaves et al. [37] found that after a period of time, the residents tend to adjust the status of intelligent device into background mode, rather than having the positive interaction with it. Burchell et al. [42] studied the eﬀect of feedback that based on intelligent community. Diﬀerent from the traditional intelligent hardware feedback mode, people gained their own electricity consumption information through the weekly e-mail feedback that sent by researchers. E-mail consists of not only people's own electricity consumption information, but also the average electricity consumption of the whole intelligent community and some useful energy saving tips. The results showed that people can participate in this form of feedback in long term. And they can draw women's attention, ultimately people tend to change the behavior. Matsui et al. [43] installed electricity consumption monitoring system in people's house. It provided people with electricity consumption per 15 min through the web page. In addition to the people's recent electricity consumption data and some tips, people's knowledge improved obviously after a year's intervention, and electricity consumption is decreased. Karjalainen [40] investigated people's preference for forms of feedback. He displayed eight diﬀerent chart to people through the questionnaire analysis. The results showed that people is most interested in three kinds of information, namely, electricity expenses, proportion of household appliances accounted and other people's electricity consumption information.

information often have the eﬀect of changing people's behavior. Hutton and Mcneill [15] assessed the eﬀect of the Low Cost/No Cost energy conservation program of the US Department of Energy, The project tried to achieve the goal of saving energy by provide people with energy-saving manual and a nozzle control device. The results showed that these families that received the manual could master skills to reduce energy consumption. Hargreaves et al. [37] tried to make an intervention by persuading people to install the smart meter. Residents can obtain the realtime condition of electricity consumption with the help of smart meter. However, after a year, the researchers found that most families let the smart meters to run in the background state. The use of smart meters does increase the people's knowledge of electricity consumption, but after a long time, the smart meter does not reduce the electricity consumption due to various reasons. Komatsu and Nishio [38] investigated the eﬀect of providing information in Japan, they provided household with their neighbor's electricity consumption information. The results showed that a household's consumption of electricity is associated with their neighbor's electricity information. (4) Rewards. Rewards is an intervention that encourages people to reduce the electricity consumption by giving them a certain amount of incentives. Awards mainly consists of economic reward and social reward. Economic reward is to give the family a certain economic incentives, and the number of economic incentives can be ﬁxed or changed with the quantity of saving. Social reward mainly refers to encouragement through public propaganda. Economic rewards can receive obvious eﬀect of intervention at once, and social incentives are better than the economic incentives in the long term. Handgraaf et al. [48] conducted a research on the eﬀect of economic rewards and social rewards. He selected company's employees as target sample in Holland. Social rewards are positive descriptive reviews. And each of rewards have two forms, namely give people rewards public or secretly. Researchers provided diﬀerent rewards according to employees’ weekly electricity consumption during the period of 13 weeks. The results showed that social incentives have better eﬀect than the economic incentives. And public reward is better than the secret reward. Bertoldi et al. [49] pointed out that in earlier years, economic incentives are mainly used to support the promotion of eﬃcient technology equipment for reducing the CO2 emissions, but not to change the people's behavior. (5) Feedback. Feedback provides the family with their electricity consumption and energy saving tips. Form of feedback is very rich according to frequency. There are continuous feedback, daily feedback, weekly feedback and monthly feedback, etc. According to the feedback content, there are daily electricity consumption, the monthly electricity consumption and annual electricity consumption. Some feedback includes synthetic index, such as daily growth rate, month growth rate, and the rankings in the region. From the way of feedback, it is not only text messages but also web feedback through the Internet. Feedback's content can also be a series of number, and it can also be combined with multimedia pictures. Diﬀerent form of feedback will have diﬀerent eﬀects.

5. Research direction of residential electricity In recent years, the Internet has become an indispensable part of people's daily life. The rapid development of cloud computing technology and big data provide new opportunities for the study of residential behavior. However, many new challenges follow too. During the Internet era, the residents are not only the electricity consumption groups, but also belong to net citizen. More and more people are willing to share some of their daily activities on the Internet, which are true reﬂection of the way of life, values, habits, educational level, and so on. Residents’ social network activities and online shopping information can be used to analyze the energy consumption behavior of residents. Compared with the traditional way of questionnaire, the residents’ behavior in the social network more truly reﬂects the pattern of the residents’ behavior. So analysis of residents’ behavior by Internet is an important direction to electrical consumption behavior. The Internet environment has also bring some new challenges in the ﬁeld of residential electricity. For example, ﬁrst of all, how to get the information of daily activities of residents and analyze them is a big challenge. The second is how to discover the electricity consumption behavior according to people's online information. Residents left a lot of information on the Internet, but this information is not a direct mapping of consumption behavior. So it is necessary to conduct a multidimensional analysis. In this case, the pattern behavior of consumption behavior can be discover. Therefore, how to explore the pattern of behavior becomes a new challenge for this ﬁeld. Based on the summary of the previous literatures, this section puts forward two aspects of the analysis of the behavior in the Internet. The ﬁrst is how to use the Internet and data mining technology to dig the typical load proﬁle of electricity consumption and related pattern of behavior. The second is to develop personalized intervention strategies for each family based on the pattern.

Carroll et al. [4] studied eﬀect of provide knowledge of energy eﬃciency tips with people through feedback, and the results showed that the household who received a feedback once a month reduced the power consumption by 2.9%. Nilsson et al. [36] provided feedback through installing intelligent hardware device in people's house. Feedback information includes daily electricity consumption, week electricity consumption and electricity consumption trend. The results showed that intelligent hardware device did not have signiﬁcant impact on electricity consumption. The researchers pointed out that an important reason is that people are lack of ability of understanding

(1) Big data analysis. With the help of big data and cloud computing technology, it is possible to store and analyze massive electricity data, and to explore the pattern of electricity consumption. From the point of time, the daily pattern of electricity consumption can be explored. The pattern of the week, month, quarter and year, and peak and valley will be found easily. From the perspective of 409

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researchers have made intervention experiment depend on single behavioral theory. In recent years, some scholars have begun to combine diﬀerent behavioral theories into a new theoretical framework and got good results. Therefore, it is a new trend to combine diﬀerent behavioral theories to make the intervention experiment, because each behavioral theory has some limitations, and the combination of diﬀerent theories can overcome the limitations. Any behavioral theory is not suitable in all cases, so the combination of the theory with regional cultural factors to form a new framework is the challenge of intervention strategy research. The family is the basic unit of electricity consumption. Every family has a diﬀerent load proﬁle, which reﬂects the behavior of family members. Diﬀerent families have diﬀerent values and ways of life. During the big data era, we can use cloud computing technology to mine the pattern of behavior that hidden behind load proﬁle. Furthermore, we can make diﬀerent intervention strategies according to the diﬀerent family. In this case, each family will receive most suitable intervention strategies. In previous studies, scholars have provided the same intervention strategies for all families in a region. In the big data era, the pattern of action could be discovered in all aspects, so as to make a personalized intervention strategy for each family according to the pattern of human behavior.

region, it can be used to explore the pattern of electricity consumption in diﬀerent regions. It is also easy to discover these households which share with similar load proﬁle by means of data mining. Electricity demand predication is another import issue that could be done batter by the big data technology. For example, Rathod and Garg [88] discovered electricity consumption pattern at regional level in a city and extract knowledge concerning to the electricity consumption by data mining. Pre-processing of data, application of DM algorithms and discovered knowledge are involved. Zhou et al. [76] discovered consumption patterns of residential users by fuzzy c-means (FCM) clustering method in Jiangsu Province in China. He found eight kind of typical electricity consumption proﬁles of residential users, and diﬀerent proﬁle indicated people's diﬀerent lifestyles. Hussain et al. [77] forecasted total electricity consumption by means of Holt-Winter and Autoregressive Integrated Moving Average (ARIMA) models from 1980 to 2011 in Pakistan. The result was useful for Power Company. Ramos et al. [78] discovered typical load proﬁle by combining classiﬁcation and clustering. First, they clustered daily load proﬁles into several typical proﬁles. Second, they used labeled sample to train a multi-class model. Finally, they did the out-ofsample prediction. This was a meaningful research, because clustering will be diﬃcult during big data era. Furthermore, discovering people's behavior pattern hide behind typical load proﬁle is important. In order to achieve this goal. However, mining users’ behavior is more diﬃcult, because the people's behavior is not a complete mapping form electricity consumption data. In earlier studies, researchers often investigated the behavior through the questionnaire. However, the questionnaire has problem of simple and low credibility. In the Internet environment, we can grasp the behavior of the residents from diﬀerent perspectives. Social network is an important way to analyze the behavior of the residents. Through the collection and analysis of data from social network, we can have a batter knowledge of the people's behavior, so as to get the pattern of the residents’ electricity consumption behavior. In this case, we should combine energy with big data into energy big data. Energy issue should be handled by many related disciplinary. Zhou and Yang [79] proposed a framework of the interdisciplinary research of energy, social and information science. Under this framework, a new perspective is that people energy consumption behavior can be analyzed in time dimension, user dimension and spatial dimension. During the big data era, there is a stronger connection between energy consumption and behavior. It is beneﬁcial for us to discover typical load proﬁle and behavior pattern. Zhou et al. [86] pointed out that Energy Internet will be a new development form of energy system. It realized the integration of energy ﬂow, information ﬂow and business ﬂow. In this case, electricity consumption was not merely an energy issues. Recently, deep learning, a very powerful machine learning algorithm, is applied in electricity load forecasting. For example, Dedinec et al. [90] used a deep belief networks make short-term electricity load forecasting based on the Macedonian hourly electricity consumption data during the period 2008–2014. The results showed that the mean absolute percentage error was reduced by up to 8.6% when using deep learning compared with traditional method. Once obtaining typical load proﬁle, on the one hand, the power company can convey it to the residents through the visual feedback technology and stimulate the attention of residents for consumption of electricity. On the other hand, it can be better to develop intervention strategies according to the pattern of consumption. (2) Intervention framework and individual intervention strategies. The theoretical basis of the experimental intervention is mainly based on various behavioral theory, such as social cognitive theory, social norm theory, theory of reasoned action, theory of planned behavior, and norm activation theory. In the earlier years, the

6. Conclusions This paper ﬁrst the review vital factors that inﬂuencing people energy consumption in the aspect of social psychology. We also review related behavioral theories that have eﬀect on energy consumption behavior, including social cognitive theory, social norms theory, theory of reasoned action, theory of planned behavior, goal-oriented behavior model, value-belief–norm theory, norm activation theory, self-regulate behavior change theory and ABC theory. Then, a review of the ﬁve common strategies of intervention in residential electricity consumption is conducted, namely, commitment, goal setting, providing information, reward, and feedback. Finally, in big data era, this paper points out the challenges and opportunities in ﬁeld of residential electricity consumption. The factors reviewed in this paper are mainly related with social psychological, there are many other factors that we do not consider. Intervention strategies need to be determined in speciﬁc environment, we cannot give a comprehensive review in aspect of the combination energy, information and behavior. This is the direction of our future research. Acknowledgements This work is supported by the National Natural Science Foundation of China (Nos. 71501056, 71690235), China Postdoctoral Science Foundation (No. 2017M612072), the Fundamental Research Funds for the Central Universities (No. JZ2016HGTB0728), Anhui Provincial Natural Science Foundation Program (No. 1608085QG165), Anhui Provincial Philosophy and Social Science Planning Project (No. AHSKQ2015D42), and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (No. 71521001). References [1] Zhou K, Yang S, Shen C, et al. Energy conservation and emission reduction of China's electric power industry. Renew Sustain Energy Rev 2015;45:10–9. [2] Zhou K, Yang S. Demand side management in China: the context of China's power industry reform. Renew Sustain Energy Rev 2015;47:954–65. [3] Lopes MAR, Antunes CH, Martins N. Energy behaviours as promoters of energy eﬃciency: a 21st century review. Renew Sustain Energy Rev 2012;16(6):4095–104. [4] Carroll J, Lyons S, Denny E. Reducing household electricity demand through smart metering: the role of improved information about energy saving. Energy Econ

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