International Journal of

Environmental Research
and Public Health

Article
The Influence of Information Intervention
Cognition on College Students’ Energy-
Saving
Behavior Intentions
Ranran Yang 1,2 , Chunxiao Yue 1, Jingjing Li 1
, Junhong Zhu 1,2,
*,
Hongshu Chen 1 and Jia Wei 3,*
1
School of Management, Hefei University of Technology, Hefei 230009, China;
yangranran@hfut.edu.cn (R.Y.); 2017214246@mail.hfut.edu.cn (C.Y.); jingjli@mail.hfut.edu.cn
(J.L.); 2014213599@hfut.edu.cn (H.C.)
2
Research Center for Industrial Transfer and Innovation Development, Hefei University of
Technology,
Hefei 230009, China
3
School of Economics and Finance, Xi’an Jiaotong University, Xi’an 710061, China
* Correspondence: zhujunhong@hfut.edu.cn (J.Z.); jiawei0626@xjtu.edu.cn (J.W.)

check ror
Received: 10 January 2020; Accepted: 17 February 2020; Published: 4 updates
March 2020

Abstract: Based on the theory of planned behavior, this research examines the
influence of different types of information on the behavioral intentions of college
students in the context of perceived behavioral control (perceived self-efficacy and
perceptual control) as mediating variables. The results showed that: (1) Different types
of information intervention factors have different effects on perceptual self-efficacy and
perceptual control; the influence degree of economic cost has the strongest effect,
followed by group pressure, while the influence degree of publicity and education has
the weakest effect. However, policy intervention has no statistically significant effect
on both of them (perceived self-efficacy and perceptual control). (2) Two variables,
perceived self-efficacy and perceptual control, serve as mediators between information
intervention factors and energy-saving behavior intention.
(3) Individual characteristic factors have significant moderating effects on each path
in the model of information intervention–perceived behavior control–intention. Finally,
suggestions are made on how to encourage college students to more effectively save
energy.

Keywords: energy-saving behavior intention; information intervention; perceived

behavioral control; mediation effect; theory of planned behavior

1.Introduction
As the world’s largest energy consumer and carbon emitter, China is facing severe
energy and environmental pressure. The BP Energy Outlook 2019 edition pointed out
that, although energy demand has slowed, China will still be the world’s largest energy
consumer in 2040, accounting for 22% of global energy consumption. Oil import
dependence will rise from 67% in 2017 to 76% in 2040. Dependence on gas imports will
rise from 38% to 43% by 2040. In 2017, China emitted 9.23 billion tons of carbon
dioxide, accounting for 27.6% of the global total [1]. To achieve sustainable and green
development, the Chinese government has successively issued laws and regulations on
Notice on Action Plan for Energy Saving, Emission Reduction and Low-carbon
Development in 2014-2015, Notice on the Comprehensive Work Plan of Energy Saving
and Emission Reduction during the 13th five-year Plan, Supplementary Notice on
Comprehensive Demonstration of Energy Saving, and Emission Reduction Fiscal
Policies, etc. The need to effectively encourage individuals to change consumption
behaviors and adopt low-carbon practices is key to energy saving and emission
reduction.
However, most of the existing research on individual-level energy-saving behavior
and willingness focus on individual residents. For example, based on the theory of
planned behavior, Ru et al. discussed

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www.mdpi.com/journal/ijerph
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the influence of normative factors and perceived behavior control on individuals’

willingness to save energy [2]. Zhang et al. used the structural equation model to
analyze the influencing factors and mechanisms of urban residents’ habitual and
purchasing energy-saving behavior [3]. Additionally, Van der Werf et al. tested the
impact of personal commitment strategies (i.e., individuals’ commitment to change their
behavior) on energy-saving behavior [4]. There is little research in this space on college
students, a new force in energy saving and emission reduction. However, as a top
energy-consuming group, college students’ consumption behavior has a degree of
demonstration effect on their families, and the family is the basic unit of the community
and the country [5]. Therefore, examination of college students’ energy-saving behavior
is key in building a “two oriented society” (Two Oriented Society refers to resource
saving society and environment-friendly society).
College students’ energy-saving is significantly different from that of non-student
residents. On the one hand, school is the main activity location of college students,
and the energy that students consume is provided by the school for free. Therefore,
compared with non-student residents who pay for electricity and gas every month, the
sensitivity of college students’ energy use is low, which to a certain extent propels
energy waste. On the other hand, whether college students are in class or in life, they
are in collective activities, and they are more vulnerable to the influence of group
atmosphere than non-student residents. Further, college students generally have a
herd mentality and strong plasticity [6]. At present, only a few scholars have explored
the factors that affect college students’ environment, and there is a lack of sufficient
demonstration on the functional relationship between different factors operating in this
space [7–9]. In addition, the energy-saving behavior of college students has a degree of
“knowing and doing separation,” that is, knowing is easy and doing is difficult. Most
college students have a high energy-saving awareness or attitude, but the enforcement
of energy-saving behavior is not high, there are some common implementation
obstacles [6,8,9]. In view of this phenomenon, academics employ the concept of
“perceptual behavior control” to reflect the difficulty degree of individual perceived
behavior [10]. This article aims to solve the following three problems:

(1) What are the factors that make it difficult for college students to realize their
energy-saving behavior potential?
(2) How can the difficulty of behavior perception of college students be reduced?
(3) Can perceived behavioral control improve college students’ willingness to save
energy?

2.Literature Review and Model Hypothesis

Energy-saving behavior is generally divided into two types: habitual energy-saving
behavior and purchasing energy-saving behavior [11,12]. Habitual energy-saving
behavior generally refers to the reduction of some daily life behaviors and the change
or adjustment of one’s habits, and these behavioral changes can help reduce energy
consumption (e.g., turning off the lights after leaving, reducing air conditioning use,
controlling air conditioning temperature, etc.). Purchasing energy-saving behavior refers
to investing in new technology or energy-saving equipment to indirectly reduce energy
use without changing lifestyle, such as purchasing energy-saving lamps [13]. Purchasing
energy-saving behavior is influenced by the level of science and technology
developments, product prices, subsidy policies, and other objective factors. Habitual
energy-saving behavior can be controlled and changed through individuals’ subjective
motivation [14]. Thus, there are different ways to study these two energy-saving
behaviors [15]. In view of the limited energy purchase behaviors of college students,
this article focuses on the habitual energy-saving behavior of college students.
The theory of planned behavior provides a new way to explain the general
decision-making processes involved in individual behavior [10]. The theory points out
that intention is the most direct factor to affect behavior, and the intention is the most
predictive behavior tendency or motivation before behavior. The theory considers both
external and internal factors that affect individual energy-saving behavior, including
the attitude of individual internal behavior, and subjective norms and perceived
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behavior control. The theory has been widely used in research on green consumption
behavior [16], green travel [17], employee energy-saving behavior [18], etc. Among
these areas, the influence of perceptual behavior control on behavior intention and
actual behavior has attracted increasing attention. For example, Karlijn et al. explored
the factors driving young people’s energy behaviors based on the theory of planned
behavior. The results from this work showed that perceived behavioral control directly
affected the implementation of behavior [19]. Heath and Gifford, analyzing residents’
sustainable consumption behavior, found that perceptual behavior control was the most
significant factor [20]. Shen et al. illustrated that besides personal moral obligation,
perceptual behavior control was the most significant factor influencing intention to
classify solid waste among 524 young people living in Hebei province, China [21]. Ru et
al. investigated the behavioral intention to save energy among 450 eastern China
residents and found that perceived behavioral control was the most important factor
affecting behavioral intention to save energy [2]. However, at present, scholars mainly
focus on measuring the relationship between perceived behavioral control and intention
or behavior through questionnaire surveys, and there are few pre-influencing factors of
perceived behavioral control, and hence, it is impossible to truly solve the problem of
“high difficulty of perception.” Therefore, it is of great research value to determine the
factors influencing of perceived behavior control of energy-saving behavior and
intervene to change the perceived behavior control, and thereby, encourage changes in
behavioral intention and energy-saving behavior.
In recent years, information intervention has become a focus in energy-saving
behavior research. Many researchers have conducted information intervention research
on individual energy-saving behavior [22–24]. The prevalence of information
intervention strategies mainly comes from nudge theory of Thaler and Sunstein [25].
Information intervention is a specific application of nudge theory in the field of energy
aimed at promoting energy-saving behavior. Based on data from 156 papers published
between 1975 and 2012, Delmas et al. conducted a comprehensive analysis on the
household energy-saving experiment based on information strategy, and found that
average power consumption decreased by 7.4% [26]. Mi and Yang conducted a meta-
analysis of 42 articles published between 1977 and 2014 regarding the influence of
information intervention on energy-saving behavior and willingness, and concluded that
information intervention strategy had a positive role in promoting energy-saving
behavior and willingness in residents [27]. In terms of information intervention,
sociology and cognitive psychology emphasize internal factors, and intervention
behavior focuses on publicity, education, and persuasion. Furthermore, economics and
application behavior emphasize external factors, and intervene behavior through
policies, regulations, and taxes [28]. This article selects the external economic cost and
policy intervention, internal publicity, and education and group pressure as the
information intervention factors, and then analyzes the intervention path of various
factors on college students’ energy-saving behavior intention.
Therefore, based on the theory of planned behavior, focusing on the factors of
perceptual behavior control, this article establishes a theoretical model addressing the
impact of information intervention on the habitual energy-saving behavior intention of
college students, states research hypotheses, and uses questionnaire survey data to
reveal the mechanism of different pre-intervention information on the habitual energy-
saving behavior intention of college students.

2.1. Research Hypothesis on the Effect of Information Intervention Factors on Perceived

Behavior Control
Perceptual behavior control refers to the degree of controllability perceived by an
individual for a particular behavior; that is, the speculation and judgment on whether
the individual has the ability to complete the behavior. At present, scholars divide
perceived behavioral control into two independent and interrelated factors: self-
efficacy of perceived behavioral difficulty and perceptual control of behavioral
willingness [29].
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2.1.1.Research Hypothesis on the Effect of Information Intervention Factors on Self-

Efficacy
Self-efficacy is the self-judgment of whether an actor can complete a certain
behavior at a certain level. Different from behavioral control perception, self-efficacy
reflects the control of the actor on external factors that affect their behavior. Self-
efficacy reflects self-internalized cognition and judgment [30]. Bandura’s definition of
self-efficacy is the degree of confidence people have in whether they can use the skills
they have to complete a certain task; in turn, this depends on the external environment
of the agent and similar behaviors they have practiced in the past. It is the perception
of the agent’s ability to perform new behaviors [31]. Lu demonstrated that due to
costs, it is more difficult to participate in energy-saving behaviors, and thus, residents’
willingness to do so is reduced. Conversely, when the economic cost is reduced,
perceived self-efficacy of residents is weakened [32]. Shi found through empirical
analysis that whether mandatory policy, incentive policy, or social policy, the
implementation of the policy will improve residents’ low-carbon consumption ability, so
as to increase the individual’s self-perception of implementing low-carbon behavior
[33]. Yang et al. found that targeted publicity and education methods greatly enhance
residents’ awareness of energy-saving behavior, thus, making it easier for residents to
perceive the difficulty of participating in energy-saving behavior [34]. Chen et al. have
illustrated that group pressure can lead to the opposite effect of self-attitude.
Individuals will obtain group members’ approval and avoid punishment by maintaining
behaviors consistent with those of the group [9]. Therefore, this article proposes the
following hypothesis:

Hypothesis 1 (H1a): Economic cost has a significant positive effect on perceived

self-efficacy. Hypothesis 1 (H1b): Policy intervention has a significant positive

effect on perceived self-efficacy. Hypothesis 1 (H1c): Propaganda education has

a significant positive effect on perceived self-efficacy. Hypothesis 1 (H1d): Group

pressure has a significant negative effect on perceived self-efficacy.

2.1.2.Research Hypothesis of Information Intervention Factors on Perceptual Control

Perceptual control is an index that describes the degree of control of the agent over
their own behavior. It judges whether the agent participates in the behavior from their
own perspective, and their behavioral intention will not be easily changed by various
factors [35]. In this article, perceptual control mainly refers to the control level in
college students’ willingness to participate in habitual energy-saving behavior. From
the perspective of individual behavior, there is a certain limit in self-control. When
influenced by intervention information and perceptual control exceeds a certain critical
point, the individual’s behavioral intention will change [35]. Regarding economic cost,
research shows that the acceptance level of green consumption behavior premium is
less than 5%, and when it exceeds 5%, green consumption intention will be significantly
reduced [16]. In this article, the premium is less than 5%. At this time, as prices rise,
residents will be affected by price sensitivity and other factors [32]; and to avoid
spending more money, residents’ own perceptual control will become stronger. Mi et al.
found that the formulation and implementation of relevant energy-saving policies and
regulations ensures that residents have laws to follow when participating in energy-
saving behaviors, and hence, can participate in energy-saving behaviors with more
confidence and fulfilment [36]. Li et al. determined that when more targeted publicity of
energy-saving behaviors was conducted, residents had a higher degree of recognition of
energy-saving behaviors [35]. In a group-oriented culture, people are encouraged to
obey the organization rather than pursue individual goals [37]. Therefore, this article
proposes the following hypothesis:
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Hypothesis 2 (H2a): Economic cost has a significant positive impact on perceptual
control.
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Hypothesis 2 (H2b): Policy intervention has a significant positive effect on

perceptual control. Hypothesis 2 (H2c): Publicity and education had a significant

positive impact on perceptual control. Hypothesis 2 (H2d): Group pressure has a

significant negative effect on perceptual control.

2.2. Research Hypothesis of the Effect of Perceived Behavior Control on

Behavioral Intention of Habitual Energy-Saving
Allen and Ferrand found a significant positive relationship between self-
efficacy and pro-environment behavior [38]. Individuals with a stronger sense of self-
efficacy are more inclined to set challenging goals, more likely to achieve a higher level
of behavior, and have more endurance in the face of difficulties and obstacles. These
individuals firmly believe in the realization of their own behavior and are willing to make
an effort. On the contrary, individuals with low self-efficacy are more likely to quit when
they encounter setbacks [30]. In other words, individuals tend to choose behaviors with
high self-efficacy. Therefore, self-efficacy has a positive impact on behavioral intention
for energy saving. On the other hand, literature suggests that improvement of
perceptual control will enhance the control of behavioral intention; that is, individuals
tend to choose the behavior with strong perceptual control [29,35]. Therefore, this
article proposes the following hypothesis:

Hypothesis 3 (H3a): Perceived self-efficacy has a significant positive impact on

habitual energy-saving behavioral intention.

Hypothesis 3 (H3b): Perceptual control has a significant positive effect on habitual

energy-saving.

2.3. Hypothesis of Mediating Effect of Perceived Self-Efficacy and Perceptual Control

This article focuses mainly on the test whether perceived self-efficacy and
perceived control have mediating effects between information intervention factors and
habitual energy-saving behavioral intention. Therefore, this article puts forward the
assumption:

Hypothesis 4 (H4a): Perceived self-efficacy has a mediating effect between information

intervention factors and habitual behavioral intention to save energy.

Hypothesis 4 (H4b): Perceptual control has a mediating effect between information

intervention factors and habitual energy-saving behavior intention.

2.4. Hypothesis of Moderating Effect of Personality Characteristic Variables

Many studies, most of which focus on gender, age, income, educational
background, and occupational background, have assessed the influence of social
demographic characteristics on energy-saving behavior. For example, Pothitou et al.
[39] and Yu et al. [40] found that energy- saving behavior was significantly different
based on gender factors, while Yang et al. argued that gender was not a significant
factor influencing energy-saving behavior [41]. In terms of age, Belaid and Garcia [42]
and Yang et al. [41] showed a non-linear relationship between age and energy-saving
behavior. Income and education background have relatively inconsistent effects on
energy-saving behaviors, which may be due to the inconsistent definition of energy-
saving behaviors. For example, Yang et al.’s results showed that low-income groups are
more willing to implement habitual energy-saving behaviors, while education background
has no significant impact on myriad energy-saving behaviors [41]. Liu et al.’s research
on Tianjin residents’ low carbon travel behavior showed that characteristics of various
factors on the behavior have a direct influence. Further, on the basis of the analysis of
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the characteristic factors of the theoretical model of each path adjustment effect, the
research shows that the demographic
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factors on the residents’ psychological factors into the process of behavior intention
exists adjustment effect [43]. Based on this, combined with the characteristics of
college students, this article proposes the following hypothesis:

Hypothesis 5 (H5a): Gender has a significant moderating effect on various pathways

in the information intervention–perceived behavior control–intention model.

Hypothesis 5 (H5b): Grade level has a significant moderating effect on various

pathways in the information intervention–perceptual behavior control–intention model.

Hypothesis 5 (H5c): Major has a significant moderating effect on various pathways in

the information intervention–perceived behavior control–intention model.

Hypothesis 5 (H5d): Monthly allowance has a significant moderating effect on

various pathways in the information intervention–perceived behavior control–intention
model.

In sum, the research model is established as shown in Figure 1, below. In this

article, information intervention is regarded as an external stimulus that can stimulate
individuals’ internal perception, while the internal perception of individuals, which is the
individuals’ response to external stimuli (individuals’ sense of competence and
autonomy), is instantiated in self-efficacy and perceptual control. In other words,
information intervention (external stimuli) could strengthen individuals’ perceived self-
efficacy and perceptual control (emotional and psychological reactions) that generate
intention of habitual energy-saving behavior (motivation and behavioral reactions).

Information Perceived
behavioral Intention
intervention
control

Economic cost

Perceived
Policy self-efficacy
intervention Habitual Gender
energy-saving Grade level
behavior Major
Publicity and intention Monthly allowance
education Perceptual
control
Group
pressure

Figure 1. Research model on the influence of information intervention on college students’

behavioral intention to save energy.

3.Materials and Methods

3.1. Questionnaire Design

The design of the questionnaire items is on the basis of the above model, some
references for domestic and foreign relevant maturity scale [2,5,15,16,30,32,33,44–46],
and combined with the specific situation of the college students. The questionnaire is
mainly divided into four parts: basic information description, behavioral intention to save
energy, perceived behavioral control, and information intervention. In the process of
questionnaire design, relevant experts were invited to discuss the problem setting, and
the questionnaire was modified and improved according to expert opinions. At the
same time, to ensure high questionnaire reliability and validity, we conducted a pre-
survey to
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test the initial questionnaire. According to the data analysis results, we modified and
deleted the index items with errors to form a formal questionnaire. The specific item
design is shown in Appendix A. Moreover, a 5-point Likert scale was used in our
questionnaire to measure the scores of items, with 1 = “strongly disagree”, 2 =
“disagree”, 3 = “neutral”, 4 = “agree”, and 5 = “strongly agree”.

3.2. Distribution and Recovery of Questionnaires

This article adopted the method of an online questionnaire and offline field
distribution to formally distribution the questionnaire. The research subjects were college
students in Hefei city, Anhui province. Hefei is the important center for technology and
education in China and the innovation capital with great international influence.
According to the statistics of the Chinese bureau of education, by the end of 2018,
there were 55 colleges and universities and more than 600,000 college students in
Hefei, and it ranked 11th among Chinese cities. On the other hand, urban per capita
disposable income and per capita consumption expenditure of Hefei is nearly the
national average. According to the statistics of National Bureau of Statistics of China, in
2018, national urban per capita disposable income and per capita consumption
expenditure are 39,251 CNY and 26,112 CNY, and the data of Hefei are 41,484 CNY and
25,339 CNY respectively. Therefore, Hefei has some representation as the research
subject. The formal investigation lasted for one week. In total, 230 questionnaires were
distributed and all were recovered; 221 questionnaires were effective with an effective
rate of 96.1%, and the number of effective questionnaires was larger than the minimum
sample size of 159 (the error range was 5%). Analysis of the characteristics of the
recovered effective questionnaires (Table 1) indicated that the ratio of male and female
students was comparable, and the proportion of students in different grade levels was
not significantly different, which minimizes the influence of gender and grade level
factors on the data, and ensures the objectivity of the questionnaire. Science and
engineering account for 83.26% of the academic majors, which conforms to the
distribution ratio of academic majors of Hefei University students. In terms of monthly
living expenses, 84.17% of the surveyed college students spent less than 1600 CNY per
month. Referring to the minimum wage standard of 1550 CNY per month in Hefei in
2018, this suggests that college students may be a low-consumption group.

Table 1. Basic respondent characteristics.

Sample Size Sample

Optio (Proportion) Size
ns
male 118 (Proportio
Optio
Gender n)
female 103 (46.6%) ns Sophomore year 48
(53.4%) Grade level (21.7%)
<800 13 (5.9%) Freshman year 38
60
Monthly (17.2%) Junior year(27.2%)
800–1200 85 (38.5%) Senior year 75 (33.9%)
allowanc
e

(yuan 1600–2000 29 Major science 103 (46.6%)

) (13.1%)
>2000 22 (9.9%) engineering 81 (36.7%)
medical 4 (1.8%)

4.Results and Discussion

We used the structural equation model (SEM) to examine the research model. This
SEM analysis is a robust and influential high quality multivariate statistical analysis
technique to examine the model with latent variables, and for parameter assessment
and hypothesis testing e.g., factor analysis and regression or path analysis [47,48]. In
this article, SEM is performed by using AMOS 24.0 which is a powerful and widely used
software produced by IBM (Armonk, NY, USA) that explores mutual relations among
different variables. We firstly tested the reliability and validity of the measurement
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model, 25
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4.1. Reliability and Validity Analysis

Scale reliability, which referred to the consistency of the indicators, was measured
using Cronbach’s alpha coefficient and combined reliability [47], and the reliability test
results are shown in Table 2. As can be seen from Table 2, the Cronbach’s alpha value
of each variable is in the interval of 0.707 to 0.916, and the CR value ranges from 0.874
to 0.941, far higher than the theoretical minimum value of 0.7, indicating that the
overall measurement results of the questionnaire had a good reliability [49].

Table 2. Reliability and validity.

Latent Measurement Cronbach’s Combined Average Variance

Variable Item Loading Alpha Reliability Extracted
Habitual HEBI1 0.800 0.865 0.905 0.656
energy-saving HEBI 2 0.781
behavior HEBI 3 0.765
intention HEBI 4 0.809
(HEBI) HEBI 5 0.890
PSE 1
Perceived PSE 2 0.840 0.860 0.905 0.705
self-efficacy 0.835
PSE 3
(PSE) 0.840
PSE 4 0.843
PC 1
Perceptual PC 2 0.853 0.826 0.898 0.745
control (PC) 0.878
PC 3 0.859
Economic cost EC 1 0.882 0.714 0.875 0.778
(EC) EC 2 0.882
PI 1 0.872 0.884 0.921 0.745
Policy interven
PI 2 0.872
(PI) tion
PI
PI 34 0.842
0.866
PE 1 0.903 0.916 0.941 0.800
Publicity and PE 2 0.902
education (PE) PE 3 0.891
PE 4 0.882
Group pressure GP 1 0.881 0.707 0.874 0.776
(GP) GP 2 0.881

In terms of questionnaire validity, the questionnaire in this article mainly refers to

relevant mature scales and was consulted on by experts, which can help ensure high
validity. Meanwhile, construct validity, convergence validity, and discriminant validity
were detailed analyzed as follows.
Construct validity was tested by measuring factor loading and cross loading of each
item using AMOS 24.0. As shown in Table 2, the factor loading values of all
measurement items are higher than 0.50, and the measurement results show that the
factor loading is larger than the cross loading. Therefore, the questionnaire had a high
construct validity [49].
Convergence validity was measured using factor loading, combined reliability (CR),
and average variance extracted (AVE). As shown in Table 2, the factor loading value of
the items ranges between 0.765 and 0.903, above the minimum threshold 0.7. The
measured values of CR are in the interval of 0.874 and 0.941, above the minimum
threshold 0.7. The values of AVE range from 0.656 to 0.800, above the critical value of
0.5, which indicates that the questionnaire had a high convergence validity [49].
Discriminant validity was tested by the square root of AVE. According to the
Fornell–Larcker criterion, the square root of AVE should be greater than the correlations
between the variables [49]. As the calculation results shown in Table 3, the bold text on
the diagonal in the table represents the square root of AVE, and the non-diagonal lines
are the correlation coefficients between variables. This indicates that the questionnaire
had a high discriminant validity.
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Table 3. Results of discriminant validity.

Latent HEBI PSE PC EC PI PE GP

Variable
HEBI 0.810
PSE 0.560 *** 0.840
PC 0.418 *** 0.423 *** 0.863
EC 0.449 *** 0.423 *** 0.339 *** 0.882
PI 0.401 *** 0.380 *** 0.309 *** 0.403 *** 0.863
PE 0.471 *** 0.417 *** 0.341 *** 0.415 *** 0.453 *** 0.894
GP 0.371 *** 0.356 *** 0.262 *** 0.368 *** 0.428 *** 0.384 *** 0.881
Note: *** P < 0.01.

4.2. Structural Equation Model Test

After the establishment and identification of the structural equation model, AMOS
24.0 was used to estimate and test the initial structural equation model. As indicated in
Table 4, the final structural model reached a good fit, with all the indices conforming to
the reference values in Bagozzi and Yi [50].

Table 4. Fitting index of the modified structural equation model.

Fitting Index Fitting Index Value Best Standard Fitting Evaluation

Chi-Square (χ2) 551.071 the smaller the better -
degrees of freedom (df) 235 The bigger the better -
Chi-Square/df 2.345 1 < NC < 3 ideal
Parsimonious Normed Fit
0.719 >0.50 ideal
Index (PNFI)
Comparative Fit Index 0.903 >0.90 ideal
(CFI) Incremental Fit 0.904 >0.90 ideal
Index (IFI) Root Mean
Square Error of 0.074 <0.05 Relatively ideal
Approximation (RMSEA)

The results of the modified model path/load analysis are shown in Table 5. All the
path coefficients are statistically significant except that of policy intervention to
perceived self-efficacy (β = −0.084, CR
= −0.851, P > 0.05) and policy intervention to perceptual control (β = −0.008, CR =
−0.076, P > 0.05). Moreover, it can be seen that different types of information
intervention factors have different effects on perceived self-efficacy and perceptual
control. Specifically, among the supported hypotheses, economic cost is the most
important factor affecting perceived self-efficacy (β = 1.734, CR = 4.426, P < 0.001)
and perceptual control (β = 1.688, CR = 4.484, P < 0.001). This is also consistent with
the characteristics of college students. According to the characteristics of 84.17% of the
sample, college students’ monthly living expenses under 1600 CNY, the consumption
level of college students is generally low. Because there is no source of economic
income, students’ consumption mainly depends on family support, and thus, they are
more sensitive to the economic cost of energy saving and emission reduction.
Propaganda and education are the least influential factors on perceived self-efficacy (β
= 0.550, CR
= 4.904, P < 0.001) and perceptual control (β = 0.406, CR = 3.322, P < 0.001). On the
one hand, it takes considerable time to change the concept of individual energy saving
and emission reduction with the help of publicity and popularization, making it difficult
to achieve significant results in the short-term. On the other hand, the cost-benefit
correlation between publicity and education, and energy saving and emission reduction
of college students is not directly affected by economic factors, and the incentive effect
is weak. Regarding the significant negative influence of group pressure on perceived
self-efficacy (β = −1.036, CR = −2.778, P < 0.01) and perceptual control (β = −1.108,
CR
= −3.023, P < 0.01), it is also consistent with the characteristics of college students.
Compared with
individual non-student residents, college students are almost always in a collective life,
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and they are more likely to be influenced by the group, which may affect 25
their
judgment.
Int. J. Environ. Res. Public Health 2020, 14 of
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Table 5. Revised model path/load analysis results.

Regression Path Estimate S.E. C.R. P Correspondence Verification Results
Hypothesis
EC→PSE 1.734 0.392 4.426 0.000 H1a Verified
EC→PC 1.688 0.377 4.484 0.000 H2a Verified
PI→PSE −0.084 0.099 −0.851 0.395 H1b Failed
PI→PC −0.008 0.112 −0.076 0.940 H2b Failed
PE→PSE 0.550 0.112 4.904 0.000 H1c Verified
PE→PC 0.406 0.122 3.322 0.000 H2c Verified
GP→PSE −1.036 0.373 −2.778 0.005 H1d Verified
GP→PC −1.108 0.367 −3.023 0.003 H2d Verified
PSE→HEBI 1.226 0.257 4.765 0.000 H3a Verified
PC→HEBI 0.506 0.245 2.064 0.039 H3b Verified

The conclusion that policy intervention has no significant effect on perceived self-
efficacy and perceptual control is different from research conducted with urban
residents. For example, Shi shows that different policy interventions have a significant
impact on residents’ energy-saving behavior [33]. Yue Ting found that the
implementation of policies can strengthen residents’ willingness to conduct energy
saving [30], etc., but these studies are all targeted at urban residents. Although college
students’ policy interventions on energy-saving behavior and willingness may be known
through the Internet, teachers, classmates and other channels, students lack practical
experience, and their policy acceptance is very limited. Therefore, it is difficult for them
to generate a personal sense of identity. For example, Zhang and Zhang found that
college students are in a relatively fixed living environment, with a relatively weak
sense of social responsibility, and they will be a mind of indifference [51]. To a certain
extent, this also explains why the effect of policy intervention is not significant for
college students.

4.3. Analysis of Mediating Effects

According to Baron and Kenny [52], the mediating effect test can be divided into
the following four steps: (1) discuss the significance (c) value of independent variable
and dependent variable;
(2) discuss the significance (a) value of independent variable and intermediate variable;
(3) discuss the significance (b) value between the mediating variable and the
dependent variable. At this point, the significant values of (c), (a), and (b) indicate that
the mediating variables play an intermediary role, and then further discussion plays a
role of complete mediation or partial intermediary role; (4) discuss the establishment of
regression model by using independent variables and intermediate variables to jointly
predict the significance of (c’) value of the significance of dependent variables. The
significant (c’) correlation indicates that the model plays a partial mediating role,
otherwise it is a complete mediating role.
The mediating effect was analyzed by bootstrap (self-sampling 2000 times) results
in AMOS 24.0. After the model operation, the data is iterated to the 14th time to get
convergence, at this time the c, a, and b values of significance are shown in Table 6.
Policy intervention factors have no significant influence on perceived self-efficacy and
perception control, so the mediation inspection will no longer discuss the information
interference factors. The analysis shows that a values of group pressure, publicity and
education, and economic cost are significant (p < 0.01). Additionally, the b values of
perceived self-efficacy and perceptual control are also significant (p < 0.01). This result
indicates that the model has a statistically significant mediating effect. Further check
the value of (c’), as shown in Table 6, the value of (c’) is also significant (p < 0.01).
Therefore, we may know that perceived self-efficacy and perceptual control play a
partial mediating role in the paths from economic cost, publicity and education, group
pressure to intention of exhibit habitual energy-saving behavior.
Int. J. Environ. Res. Public Health 2020, 15 of
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Table 6. Double-tailed test results based on BC (Bias-Corrected) method.

The Path The Total Effect (c Direct Effect (a, b The Indirect Effect (c’
value) value) value)
EC→PC 0.000 0.000 —
EC→PSE 0.000 0.000 —
EC→HEBI 0.001 — 0.001
GP→PC 0.000 0.000 —
GP→PSE 0.000 0.000 —
GP→HEBI 0.002 — 0.002
PE→PC 0.002 0.002 —
PE→PSE 0.001 0.001 —
PE→HEBI 0.001 — 0.001
PC→HEBI 0.027 0.027 —
PSE→HEBI 0.001 0.001 —

4.4. Analysis of the Influence of Individual Characteristics on Energy-Saving Behavioral

Intentions and Paths
The influence of individual characteristics of gender, grade level, academic major,
and monthly living expenses on behavioral intention to save energy was tested using
variance analysis (One-way ANOVA). Prior to ANOVA modeling, homogeneity of variance
testing was required to determine whether ANOVA was appropriate (IBM SPSS 22.0,
Armonk, NY, USA). The results are shown in Table 7. None of the variables were
statistically significant (p > 0.05), and the variance was homogeneous; thus, suitable for
variance analysis.

Table 7. Tests of homogeneity of variance.

Individual Levene Statistic df1 df2 Significant

Characteristics
Gender 1.939 1 190 0.165
Grade level 3.366 3 188 0.065
Major 1.080 3 188 0.359
Monthly allowance 2.309 4 187 0.060

Gender, grade level, major and monthly allowance were used as independent
factors and energy-saving behavior intention was the dependent variable. One-way
ANOVA was conducted using SPSS 22.0, and the results showed that only different
grade levels had a significant difference (Pgrade = 0.040 < 0.05) in energy-saving
behavior intention. Gender, major and monthly allowance had a significant influence
(Pgender = 0.254, Pmajor = 0.835, Pma = 0.319) on behavioral intention to save
energy. This conclusion is consistent with the research conclusions of Yang et al. [36]
and Belaid and Garcia [37]. Specifically, the mean difference of energy-saving behavior
intention among different grade levels was ranked from the highest to the lowest in the
following order: freshman (4.33) > senior (3.73) > junior (3.56) > sophomore (3.44).
Freshmen had the highest energy-saving behavior intention, sophomores had the
lowest, and there were significant differences among grade levels.
In addition, on the basis of analyzing the direct influence of personality characteristics
on intention,
this article further analyzed the influence degree of personality characteristics on the
paths in the model; that is, the moderating effect of demography was analyzed by the
multi-path grouping method. The specific results are shown in Table 8. To facilitate the
statistical analysis, this article defines the students in the first and second year of
university as junior grade, and the students in the third and fourth year of university as
senior grade. The majors are divided into three groups: liberal arts, science, and
engineering. Monthly allowance higher than 1200 are divided into high consumption.
Monthly allowance below 1200 CNY are divided into low consumption.
Int. J. Environ. Res. Public Health 2020, 16 of
17, 1659 25

Table 8. Results of multi-group analysis.

Gender Grade Level Major Monthly Allowance
Path
Male Female Junior Senior Arts Science Engineering Lower Higher
EC→PSE 1.54 *** 1.49 *** 0.87 *** 1.92 *** 1.26 *** 1.98 *** 1.40 *** 1.72 *** 1.05 ***
EC→PC 0.54 *** 0.03 0.53 ** 0.19 0.89 ** 0.25 0.2 0.44 ** 0.16
PE→PSE 0.87 *** 0.62 *** 0.82 *** 0.76 *** 0.81 *** 0.72 *** 0.82 *** 0.87 *** 0.61 ***
PE→PC 0.29 *** 0.01 0.49 ** 0.06 0.44 *** 0.09 0.11 0.21 ** 0.07
GP→PSE 0.76 *** 0.70 *** 0.73 *** 0.73 *** 0.77 *** 0.61 *** 0.83 *** 0.97 *** 0.42 ***
GP→PC 0.22 *** 0.01 0.43 * 0.04 0.26 * 0.05 0.09 0.22 * 0.03
PSE→HEBI 0.87 *** 0.85 *** 0.92 *** 0.75 *** 0.78 *** 0.85 *** 0.77 *** 0.87 *** 0.67 ***
PC→HEBI 0.84 *** 0.61 *** 0.92 *** 0.62 *** 0.78 *** 0.59 *** 0.79 *** 0.85 *** 0.47 ***
Note: *** P < 0.01, ** P < 0.05, * P < 0.1.

As shown in Table 8, individual characteristic variables on each path have a specific

regulation effect. But because of the more significant differences between the groups,
compared with the perceived self-efficacy, individual characteristic variables
adjustment mainly embodies in containing perceptual control path. Specifically, male
students, junior grade, liberal arts students, and low consumption students are more
likely to significantly affect their perceptual control because of the changes of their
economic factors, the degree of contact of publicity and education, the degree of
perception of group pressure, and other information intervention factors. For example,
the difference between male (β = 0.54, P < 0.01) and female (β = 0.03, P > 0.1) on
EC→PC was very significant. Moreover, it is also easier to significantly improve their
habitual energy-saving behavior intention because of the perceptual control
improvement. Therefore, this group should be the main target of information
interventions, because this group has better cognitive and behavioral transformation
effects of information intervention, and the stimulation effect will be better after
implementation.

5.Conclusions and Recommendations

5.1. Research Conclusions

The main conclusions are as follows: (1) different types of information intervention
factors have different effects on the perceived self-efficacy and perceptual control.
Economic cost, group pressure, and propaganda education have significant effects on
perceived self-efficacy and perceptual control. Among them, the degree of influence of
economic cost is the strongest, followed by group pressure, and the degree of influence
of publicity and education is the weakest. However, policy intervention factors have no
significant effect on perceived self-efficacy and perceptual control. (2) Perceived self-
efficacy and perceptual control have significant positive effects on habitual energy-
saving behavior intention.
(3) Perceived self-efficacy and perceived control have a partial mediating effect between
information
intervention factors and habitual energy-saving behavioral intention. Additionally,
information intervention factors have a direct effect on habitual energy-saving behavior
intention. (4) Among the individual characteristic factors such as gender, grade, major
and monthly living expenses, only the grade factor has a direct significant correlation
with the habitual energy-saving behavior intention of college students (non-linear
relationship). However, almost all individual characteristic factors have significant
moderating effects on each path in the model of information intervention–perceived
behavior control–intention.

5.2. Policy Suggestions

Based on the above conclusions and the characteristics of college students, this
article proposes the following strategies and suggestions to improve the willingness of
college students to save energy:

(1) Economic incentive activities. Since economic cost has a great impact on the
college students in the low-consumption group, the school or class can give
material rewards to energy-saving behavior markers, such as distributing small
Int. J. Environ. Res. Public Health 2020, 17 of
17, 1659gifts, to stimulate improvement 25
of college students’ energy-saving behavior
intention in the economy or in-kind.
Int. J. Environ. Res. Public Health 2020, 18 of
17, 1659 25

(2) Establish a notification system of energy-saving behavior. The establishment of a

timely information notification system, weekly or monthly timely notification;
especially dormitory electricity saving and the corresponding energy and
environment improvement, to enable college students to better understand energy-
saving behavior and its significance, to enhance their willingness to engage in
energy-saving behaviors. On the other hand, group pressure will significantly
affect college students’ behavioral intention to save energy. Therefore, this
potential advantage should be given full play to shape the energy-saving
atmosphere in schools and improve individual behavioral intention to save energy
under group pressure and supervision.
(3) Carry-out targeted publicity and education activities. Although there are many
publicity activities, such as having an energy-saving month and energy-saving
slogans on campus, participation and awareness of college students are not high
enough in practical applications. Many of these efforts fail to capture the attention
and interest of college students. Therefore, more colorful and interesting publicity
methods of energy-saving are needed, such as one-hour energy-saving activities
on earth or campus exchange activities organized out of dormitory that night.
(4) Enhance the sense of experience and identity in the implementation of policies
and systems. Due to the limitation of campus activities, college students lack
practical experience and experience in energy-saving policies, and their degree of
acceptance is very limited, which makes it difficult to have a personal sense of
identity. Therefore, the school can enrich students’ social practice activities and
extracurricular cognition, improve their sense of social responsibility, make students
feel and understand policies, and enhance their sensitivity to policy intervention.
(5) The implementation of information intervention should focus on males, junior
grade, liberal arts students, and low consumption college students, because they
are more likely to affect their perceptual behavior control due to the received
information intervention, and then affect their willingness to adopt energy-saving
behavior. Besides, one group leads another group to gradually improve the
information acceptance and behavior transformation power of female, senior,
science and engineering, and high-consumption university groups.

5.3. Deficiency and Prospect

Limited by data availability, this study still has the following shortcomings: First, the
establishment of the model only examines the willingness of energy-saving behavior;
the path from the willingness to energy-saving behavior is not considered. There may
be changes in intervention information in this process, which makes the final energy-
saving behavior produce different differences. Second, the results cannot be well
generalized to the entire population as our sample is composed by university students.
Third, we did not show to respondent different scenarios as in a stated preference
survey. Future research must address these limitations.

Author Contributions: Conceptualization, R.Y. and J.Z.; methodology and software, C.Y.;
validation, R.Y., J.L. and J.W.; formal analysis, C.Y. and J.L.; investigation and data curation, H.C.;
resources, J.Z.; writing—original draft preparation, C.Y. and H.C.; writing—review and editing,
R.Y., J.W. and J.L.; visualization, J.W.; supervision, J.Z.; project administration, R.Y.; funding
acquisition, R.Y. and J.W. All authors have read and agreed to the published version of the
manuscript.
Funding: This research was funded by National Natural Science Foundation of China, grant
number 71704045, 71804141 and 71502047, the Fundamental Research Funds for the Central
Universities, grant number JZ2017HGBZ0924 and, the China Postdoctoral Science Foundation,
grant number 2017M620459 and 2018T111080.
Acknowledgments: We would also like to thank our anonymous reviewers for their valuable
comments.
Conflicts of Interest: The authors declare no conflict of interest.
Int. J. Environ. Res. Public Health 2020, 19 of
17, 1659 25

Appendix A

Table A1. Research instrument.

Latent Variables Questions

I think I have a high desire to save energy.
When I finally leave the classroom or dormitory, I will pay
attention to turning off the lights.
Daily energy-saving When using the air conditioner, I am willing to adjust to the
behavior intention optimum temperature of 26 °C, not too high or too low.
I am willing to use air conditioning in moderation, and
try to increase or decrease clothing to adapt to room
temperature.
When travel conditions allow, I would like to choose more
public transportation, bicycle or walking modes.
In life, I find it easy to implement energy-saving behavior,
so there is a high willingness to save energy.
When I plan to conduct energy-saving behaviors, I can
Perceived self- clearly recognize the difficulty I perceive in this behavior.
efficacy
Although the actual number of times I participated in
energy-saving activities is not many, I always maintain the
enthusiasm and confidence to participate in energy-saving
activities.
I think I have a higher willingness to save energy than my
classmates around me.
I think I can stick to an energy-saving behavior for
more than three months.
Perceptual control I am more supportive of energy-saving behavior. Although
it is restricted by various factors (such as time, economy,
etc.), I can do my best.
My desire to save energy will not be easily changed
by external influences.
My first concern is cost performance, but also
The economic costs environmental protection.
If the cost premium for participating in energy-saving
activities is within my affordable range (generally 5%), I still
have a strong desire to save energy.
The standardization and perfection of the rules and
regulations of the school on energy-saving behavior will
make me more willing to save energy.
The school’s mandatory regulations on energy-saving
Policy intervention
behavior will make me more willing to save energy.
If I set rewards (commendations or prizes) for energy-
saving behaviors, I will be more willing to save energy.
The timely disclosure of energy-saving information in the
dormitory (once a week) will make me more willing to save
energy in
the dormitory.

Publicity and Good media publicity activities on energy-saving behavior

education will inspire me to have a higher desire to save energy.
The publicity of energy-saving behavior by the school and
the media can help me better understand the connotation
of energy-saving behavior and thus inspire me to be more
willing to save energy.
Int. J. Environ. Res. Public Health 2020, 20 of
17, 1659 25

Table A1. Cont.

Latent Variables Questions

Public publicity can make me pay more attention to
environmental protection and energy saving, and inspire
me to have a higher desire to save energy.
The longer and more comprehensive the publicity of
energy-saving behavior, the more attention I will pay to
environmental protection, so as to inspire me to be more
willing to save energy.
I often change my intention to save energy and give up
energy-saving behavior for reasons such as saving face, even
though
Group my intention to save energy is very high at this time.
pressure
When my friends and relatives do not participate in the
energy-saving behavior, I will give up the energy-saving
behavior even though I have the intention to save energy.

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