=Paper=
{{Paper
|id=Vol-3026/paper6
|storemode=property
|title=Factors Influencing Municipal Solid Waste Sorting Behavioral Intention: A Study Among Pupils in Hanoi Urban Areas
|pdfUrl=https://ceur-ws.org/Vol-3026/paper6.pdf
|volume=Vol-3026
|authors=Quynh-Nga Nguyen,Hai-Yen Hoang,Nguyen-Nhu-Y Ho,Thi-Thuy-Anh Tran
}}
==Factors Influencing Municipal Solid Waste Sorting Behavioral Intention: A Study Among Pupils in Hanoi Urban Areas==
https://ceur-ws.org/Vol-3026/paper6.pdf
Factors Influencing Municipal Solid Waste Sorting
Behavioral Intention: A Study Among Pupils in Hanoi
Urban Areas
Quynh-Nga Nguyen , Hai-Yen Hoang , Nguyen-Nhu-Y Ho[0000-0002-7188-7927]
and Thi-Thuy-Anh Tran
1 International School, Vietnam National University, Hanoi, Vietnam
nganq.nd@gmail.com, yhoang250@gmail.com,
{hngny, tranthithuyanh }@vnu.edu.vn
Abstract. With significant economic growth in Hanoi's urban districts, solid
waste generation skyrockets, they were negatively impacting the environment
and human health. Waste classification is a required answer to this problem and
is used in many nations. Numerous publications have been written on the
importance of source-based garbage categorization and sorting. The uniqueness
of this study is to uncover elements that influence students' intentions toward
municipal solid waste sorting based on the theory of planned behaviour. A
structural equation model was validated using 170 samples from Hanoi students
(SEM). The data showed that students' intentions to sort waste were positively
influenced by attitude and subjective norm, but not by perceived behavioural
control. This study's findings may help governments, schools, and environmental
organizations encourage students to engage in MSWS.
Keywords: Theory of Planned Behavior, Pro-Environment, Municipal Solid
Waste Sorting, Hanoi urban pupils.
1 Introduction
In recent years, municipal solid waste (MSW) disposal has drawn the attention of urban
areas in Vietnam, particularly Hanoi, one of the major cities with a high population
density. However, dealing with MSW remains a significant concern and a great
challenge for the city. An example is a rise due to landfill overflow in Nam Son, Xuan
Son, becoming more and more severe and being on alert for the solid waste issue [1].
Therefore, sorting waste is a critical component in reducing the amount of MSW
generated in this scenario.
Copyright © by the paper’s authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0). In: N. D. Vo, O.-J. Lee, K.-H. N. Bui, H. G. Lim, H.-
J. Jeon, P.-M. Nguyen, B. Q. Tuyen, J.-T. Kim, J. J. Jung, T. A. Vo (eds.): Proceedings of the
2nd International Conference on Human-centered Artificial Intelligence (Computing4Human
2021), Da Nang, Viet Nam, 28-October-2021, published at http://ceur-ws.org
Corresponding author.
58 Nguyen et al.
Municipal solid waste sorting (MSWS) is critical for the human living environment
and physical health since residential garbage comprises a significant amount of
hazardous waste and corrosive compounds that endanger human health indirectly by
polluting land, water, and air. Numerous researches have examined individual
behaviour and intention toward MSWS; however, these studies have primarily focused
on groups of ordinary populations [2, 3], and few have attempted to analyze young
people's intention toward MSWS precisely. As the future society's masters, well-
educated young people are the most critical group, and their behavioural intentions are
essential to the future living environment's survival. Furthermore, creating MSWS
habits takes time, regardless of age or purpose to sort rubbish; thuơs, we should focus
on raising MSWS awareness among the younger generation.
As a result, the research will apply multiple-choice surveys to assess students'
attitudes about environmental issues, specifically garbage classification. The primary
survey subjects were students from Hanoi's urban districts (12 districts total). From 6
to 18 years old, children may develop their behaviours, and Hanoi's unsettling pollution
will somehow affect them. Therefore, the best way to assist people in creating a habit
of long-term trash classification and disseminating it to the community is to understand
their behaviour on this subject.
2 Literature review
The Theory of Planned Behavior (TPB) [4] assumes that behaviour may be predicted
or explained by the intention to conduct it (Fishbein and Ajzen, 1975) [5]. TPB is well
defined and indicated by several publications, studies, and reviews [6, 7]. If the person
accurately evaluates their amount of control, Ajzen (1991) [4] suggests that the
behavioural control element directly influences their BI.
TPB has been widely employed in research since its inception and is regularly used
to analyze pro-environmental behaviour [8-10]. Studies on waste classification systems
[11, 12], procedures [13], waste classification technology [14], and waste sorting
behaviour select the TPB model have recently been conducted. Over time, this theory
can be used to analyze and forecast individual social behaviour. Fan, Yang, and Shen
(2018) [15] used the Theory of Planned Behavior to build a "motivation-intention-
behaviour" theoretical model. According to the research, general and specialized
environmental motives influence behavioural intentions. This study adds motivation,
background, and habit factors to understanding household solid waste categorization
determinants and improves TPB.
Also, based on TPB and earlier studies, [16] determined the elements that affect
people's behavioural intents in classifying municipal solid trash in Bau Bang District
(Binh Duong Province, Vietnam). The findings reveal that attitude, subjective norms,
and perceived behavioural control favourably influence people's intention and
behaviour to sort municipal solid waste (MSW). The study made policy
recommendations to encourage people in the study region to sort their waste on this
premise.
According to TPB, individual behaviour is primarily driven by intention, which is
affected by three aspects: attitude (ATT), subjective norm (SN), and perceived
Factors Influencing Municipal Solid Waste Sorting Behavioral Intention: 59
A Study Among Pupils in Hanoi Urban Areas
behavioural control (PC). That means the more positive the ATT and SN, the more
significant influence on PC and the stronger affect individual behavioural intention.
Figure 1 displays the theoretical model.
Attitude
Subjective Norm Behavioral Intention
Perceived Behavioral Control
Source: Ajzen, 1991
Fig 1. Theory of Planned Behavior (simplified)
Attitude. To express a positive or negative opinion towards a specific action [17].
Many researchers have established the impact and prediction of AT on BI [18]. Most
research shows that those with a positive AT toward action has a stable BI [19]. This
study specifies attitude as students' cognizance and biases of behaviour toward MSWS
and conversely. Hypothesis H1 - AT relates positively to MSWS BI.
Subjective Norm. SN mentions societal variables influencing an individual's conduct
[20]. For example, the government can commence this influence by enacting
environmental legislation, or the family and school can educate pupils. It can also be
caused by social aspects like family and friends who act as essential decision-making
references. In this scenario, Vietnamese society leans towards collectivism [21]. The
more students know about MSWS, the more likely they are to attend [22]. Therefore,
the following hypothesis is proposed: Hypothesis H2 - SN relates positively to MSWS
BI.
Perceived behavioral control. PC is the expectation of a person doing a specific
controlled behaviour [4]. Ajzen (1991) [4] defines perceived behavioural control as
many aspects that constrain or enhance conduct. Students in MSWS control their
behaviour based on perceived barriers to or facilitators of waste classification. Students
who are confident in their garbage classification skills are more likely to participate in
waste separation [23]. Since that is the case, the following hypothesis is proposed:
Hypothesis H3 - PC relates positively to MSWS BI.
60 Nguyen et al.
3 Methodology
3.1 Measures and Data Collection
The research uses surveys to collect relevant data. Survey questions were developed
through the understanding of TPB [4] based on a 5 point Likert scale (1 = Strongly
Disagree to 5 = Strongly Agree).
Online surveys were utilized to assess students' attitudes toward MSWS and pro-
environmental conduct in general. Due to the complexity and severity of the COVID-
19 outbreak, online questionnaires were created to enable the authors to communicate
with them. Although 181 surveys were gathered, only 170 could be evaluated.
3.2 Research Method and Statistical Analysis
Relationship among AT, SN, PC and BI was verified with structural equation modeling
(SEM) by using AMOS 20.0.
The steps below are evaluated using SPSS 20. The first was to use descriptive
statistics to look at the participants' demographics and determine their means and
standard deviations for each factor. Second, Cronbach's alpha was used to assess the
model's reliability (CA). Exploratory factor analysis (EFA) is used to determine the
relationship between observed variables and baseline factors [24]. The Principal Axis
Factoring extraction method was used in EFA, while in Promax, the Kaiser
Normalization rotation approach was used. A prior theoretical model underpins a set of
observations, and AMOS 20.0 was used to extract confirmatory factor analysis (CFA)
[24]. Fourth, assess the model's reliability (CR) and convergent validity (AVE);
standardized regression weight data were used to determine each factor's CR and AVE.
In the following step, the model was tested through the recommended threshold of SEM
included: χ2/df (the ratio of chi-square to the degree of freedom), CFI > 0.9
(comparative fit index), GFI (goodness-of-fit index), RMSEA (root mean square error
of approximation) and TLI (Tucker-Lewis index). Then, the relationships among the
five factors were validated, and the report of the hypotheses testing findings was
delivered.
4 Findings: Data Analysis and Result
4.1 Measurement Model: Reliability and Validity
To confirm the convergent validity of the data, the study used EFA and CFA. According
to the EFA results, there were no eliminated variables because their factor loadings
were higher than 0.50 [25] and ranged from 0.619 to 0.913. Then, the remaining
variables were tested by CFA. The average variance extracted (AVE) was scaled from
0.531 to 0.618, higher than the recommended benchmark point of 0.50 [38]. Therefore,
the study has solid convergent validity of measurement items.
CA was conducted to examine the internal items’ consistency of each construct [44].
The results show that CA varied from 0.847 to 0.884, demonstrated exemplary
reliability (.80 or greater) [26]. Furthermore, CR ranged from 0.847 to 0.880 and was
Factors Influencing Municipal Solid Waste Sorting Behavioral Intention: 61
A Study Among Pupils in Hanoi Urban Areas
higher than 0.7 and AVE. Therefore, the constructs’ reliability was confirmed.
Table 2. Reliability and convergent validity test results.
Factor
Construct Items Mean S.D CA CR
loading
AT1 3.48 0.858 0.619
AT2 4.00 1.026 0.762
AT3 3.82 0.983 0.770
AT 0.884 0.880
AT4 3.76 1.073 0.789
AT5 3.84 0.875 0.735
AT6 4.04 1.048 0.821
SN1 2.85 1.236 0.683
SN2 2.69 1.163 0.913
SN 0.847 0.865
SN3 2.94 1.118 0.713
SN4 2.62 1.131 0.704
PC1 3.42 1.124 0.748
PC2 3.29 1.106 0.806
PC PC3 3.39 1.079 0.817 0.854 0.847
PC4 3.09 1.135 0.657
PC5 2.95 1.132 0.663
BI1 3.04 1.181 0.674
BI2 3.01 1.164 0.788
BI BI3 3.35 1.232 0.814 0.879 0.876
BI4 3.46 1.142 0.695
BI5 2.88 1.014 0.816
Source: Compiled results from SPSS 20 software
4.2 Structural Model Testing
The structural model was set up by applying AMOS 20.0. The result showed an
acceptable model fit through these values χ2 = 278.962, χ2/df = 1.743, CFI = 0.932,
GFI = 0.867, RMSEA = 0.066 and TLI = 0.919. Every statistic was in the suggested
limitation, indicating a good model fit of the advised model to the data [26-29].
Measurement of model fit indices is described in table 3.
Table 3. Measurement of model fit indices.
Indicators Threshold Results Model Judgment
<3 good; <5 sometimes
χ2/df 1.743 Good
permissible
62 Nguyen et al.
>0.95 great; >0.9
CFI traditional; >0.8 sometimes 0.932 Traditional
permissible
>0.95 great; >0.9
GFI traditional; >0.8 sometimes 0.867 Sometimes permissible
permissible
<0.06 good fit; 0.06-0.08
RMSEA acceptable fit; 0.08-0.1 0.066 Acceptable fit
mediocre fit; >=0.1 poor fit
TLI >= 0.9 good 0.919 Good
Source: Compiled results from AMOS 20.0 software
4.3 Hypothesis Testing
The standardized path coefficients of AT and SN indicated that AT (β = 0.305, p <
0.001) and SN (β = 0.531, p < 0.001) affect the separation intention of MSW positively
and significantly. It is explained by standardized path coefficient (β) indices in Table 5,
meaning a unit increase in AT raised the pupils’ MSWS intention by 0.305 units. A unit
increase in SN raised the pupils’ MSWS intention by 0.531 units. Nevertheless, PC (β
= -0.029, p = 0.631) did not positively affect on BI. The result supported hypotheses
H1 and H2 while rejecting H3. Table 4 and figure 2 show the result details of the
hypothesis test.
Table 4. Standardized regression weights of path analysis.
Standardized Path
Hypothesis Path Correlation p Results
Coefficient (β)
H1 AT → BI 0.305 *** Supported
H2 SN → BI 0.531 *** Supported
H3 PC → BI -0.029 0.631 Not Supported
Note: a *** means p < 0.001.
Source: Compiled results from AMOS 20.0 software
Factors Influencing Municipal Solid Waste Sorting Behavioral Intention: 63
A Study Among Pupils in Hanoi Urban Areas
Fig 2. SEM model
Source: AMOS 20.0 software
5 Conclusion and Implications
5.1 Conclusion
The authors used the TPB to examine factors impacting students' behavioural intentions
in MSWS in Hanoi. Among the three model constructs, perceived behavioural control
was insignificant, but attitude and subjective norm were. These findings can help
governments, schools, and environmental organizations inspire MSWS participants.
Specifically, all possible measures are enforcing regulations, disseminating MSWS
information, delivering MSWS lectures alongside theoretical classes, simplifying trash
classification, and increasing waste-collecting infrastructure.
5.2 Implication
AT and Its Implications. The findings indicated that AT impacted pupils' behavioural
intention toward MSWS according to p-value <0.001. Besides, standardized path
coefficient equal to 0.305, thus AT had impact on BI. As can be observed, students'
recognition of waste categorization is critical to improving students' waste
classification intention. According to the survey results, most students are pleased about
waste sorting. Generation Z may have more significant opportunities to interact with
information. Especially current environmental movements like reducing plastic straw
use and the trash cleaning challenge [30, 31]. They are interested in MSWS because
64 Nguyen et al.
they believe waste classification can help clean up the environment.
SN and Its Implications. SN had the most impact on students' waste classification
intentions. BI influenced more than AT, with a p-value of 0.001 and a normalized path
coefficient of 0.531. Due to their ages, external social pressure has a significant impact
on students' intentions. At this stage, intent and behaviour are formed by emulating the
surrounding people's behaviour and are easily influenced by external stimuli [32]. For
example, involving family and friends in MSW classification increases collectivism
[33]. However, the poll shows that the percentage of family and friends sorting rubbish
is low, lowering the pupils' intention.
To increase the students' awareness, the classification of MSW can be integrated into
the educational content. In addition, the government should enforce related legislation,
policies and disseminate MSWS information across the society to make it compulsory
for citizens.
PC and Its Implications. In this study, PC was not a significant determinant of the
pupils’ BI. However, the finding indicates that students are quite confused in their
participation in garbage classification, and their intention has not significantly
improved. The reason may be that even though the city has made specific efforts in
educating pupils on how to classify waste [34, 35], such action has not been widely
disseminated. Given the above finding, it can be implied that further education for the
pupils is necessary to identify their ability to classify waste and improve public
accessibility and convenience in MSWS to allow them to feel easier in achieving the
classification of waste.
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