Household waste prevention behavior and its effect on the implementation of construction waste prevention

Household Waste Prevention Behavior and Its Effect On The
Implementation Of Construction Waste Prevention
Nguyen Van Phuong
Do Thi Sa Huynh
Trinh Vu Anh Thi
Huynh Chau Trung Hieu
International University, Vietnam National University – HCMC, Vietnam

Abstract
Rapid urbanization not only offers advantageous socio-economic opportunities but simultaneously poses
threads to the sustainable development with one of the major obstacles – household waste. In order to
overcome the problem, this paper aims to investigate determinants of behavior on waste prevention and help
decision-makers figure out more efficient approaches to implement household waste prevention. The research
utilizes Ajzen’s theory of planned behavior (TPB) to develop a conceptual model and uses a structural equation
model to test hypotheses with a survey of 593 respondents from households in Tay Ninh province, Vietnam.
Results of the proposed model present that attitude towards prevention and perceived behavioral control are
two main predictors of prevention behavior, with the influence of attitude towards respondents’ prevention
is marginally greater than that of perceived behavioral control. Meanwhile, designers’ attitude and subjective
norms are empirically evidenced to have little impacts.
Keywords: waste prevention, household behavior, designers’ attitude.

1. Introduction

Vietnam has been thriving in the industrialized revolution leading to the development of its socioeconomic
status. In addition to the flourishing economy stimulated by the globalization, consequently, residents’ living
standard is remarkably enhanced. Pollution is, accordingly, considered an alarmingly severe problem at the
same time, especially, the domestic waste poses one of the biggest threat to the environment and as well as to
the sustainable development of the country.
Although benefits from urbanization progress essentially promote the economy and society flourish, it is
the manufacturing and daily activities that lead to environmental degradation and unsustainability in the long
term. According to Vietnam National Environment report in 2011, the average solid waste in an urban area

was 2-3 times higher compared to that in a country area. Notably, in Tay Ninh city – the heart of Tay Ninh
province, significant socioeconomic achievements are increased to the need of standard living improvement,
causing environmental protection, as well as attentive healthcare, are considerably required. Domestic waste
is steadily expanded and diversified. A survey demonstrated that about 60% of the household waste is under
standardized disposal, while the remaining is disposed of by burning, burying or direct discharge into the
environment. Successfully coping with this problem by minimization strategies can save tremendous financial
support for disposal activities, increase revenue from reusing and recycling materials as well as diminish

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resources for the manufacturing process. Therefore, this research is conducted to figure out efficient and
sustainable strategies to resolve this long-term problem.
Our structural model is built upon three main theoretical models relevant to how individuals are motivated
to act in compliance with waste management policies. Developed by (Ajzen & Fishbein, 1977) and (Ajzen &
Fishbein, 1980), the theory of reasoned action (TRA) consists of three components: behavioral intention,
attitudes, and subjective norms. The theory proposes that a person’s attitude towards a specific behavior and
the person’s subjective norms have a decisive impact on shaping the person’s behavioral intentions. TRA has
been certified to be applicable in a variety of social and behavioral sciences (e.g. (Goldenhar & Connell, 1992),
(Park, Levine, & Sharkey, 1998)); however, criticisms have been raised on the exclusive influence of
individual’s volitional control on behavior. Consequently, the theory of planned behavior is suggested by
Ajzen (1985) with the introduction of a new determinant of behavior – perceived behavioral control (PBC).
PBC predicts a particular behavior directly and indirectly from intentions, demonstrating how external
environment and individual’s perceived control may affect the ability to perform an act. In addition, the theory
of (Schwartz, 1977) claims that environmental behavior is dependent on the relationships between personal
norms, social norms, awareness of consequences and denial of responsibility. In this theoretical model,
personal and social norms form a behavior only when individuals are aware of the positive outcomes of
preventing an act and personally responsible for the consequences.
According to the waste prevention study of Tucker & Douglas (2007), it attributes waste prevention
behavior (WPB) to several classified groups of causes: attitudinal factors, contextual factors, personal

capabilities, and habits and routines. The force of individual’s moral concern, social beliefs, rights and
responsibilities towards environmental issues underlie minimization and reuse behaviors (Barr, Gilg, & Ford,
2001). Tucker & Douglas (2007) proposes that sense of responsibility at a personal level is strongly associated
with WPB due to the more emotional facets (embarrassment and guilt) being triggered than simply being one’s
duty and that attitudes can poorly predict the behavior. In addition, complying with the consideration of
severe health problem with population growth and fast urbanization, delivering appropriate waste
management is recognized as the most challenge in many communities. These problems have become more
serious in developing countries, where garbage collection still relies on labor-intensive operations and not
enough waste treatment equipment and technologies.
Specifically, prior studies have explored some main aspects of environmental cases. For instance, Dunlap
& Van Liere (1978) investigated in yard burning. And other scholars concentrated on recycling (Guagnano,
Stern, & Dietz, 1995; Hopper & Nielsen, 1991) and waste prevention (Bortoleto et al., 2012). Indeed, most
previous studies in this field have usually implemented in developed countries and emerging economies, a
little research has conducted in Vietnam. Following the call for further research on WPB (Tonglet, Phillips, &
Read 2004) to clarify determinants that are of great importance in the longitudinal process of household waste
minimization, the overall objective of the present study was to examine and comprehend which factors enforce
households participation in waste prevention behavior. Furthermore, the emphasis of our research on WPB
and its influencers would contribute to addressing significant factors that stimulate individuals to change their
behaviors for environmental benefits and introduce waste management policies to achieve.
2. Literature Review

2.1. The theory of planned behavior (TPB)
According to (Ajzen, 1991), the theory of planned behavior implies that attitude towards waste prevention
behavior, subjective norm and perceived behavioral control are most essential predictors of responses. Since
these predictors constrain the designers' waste minimization behavior, there is the possibility that TPB could
explain designers' waste minimization behavior. When both of the attitude and subjective norm towards a

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behavior as well as the perceived behavioral control of performing the behavior are more favorable, it appears
a stronger intention to perform the behavior. Successful practices of the TPB were recorded in such a wide
range of environmental behavior as household waste recycling behavior and waste prevention behavior (e.g.,
(Bortoleto, Kurisu, & Hanaki, 2012); (Ramayah, Lee, & Lim, 2012); (Steg & Vlek, 2009); (Tonglet et al., 2004).
The TPB was once applied by (Teo & Loosemore, 2001) to explain how operators (e.g., site supervisors, labors)
perform reckless behavior under the influence of attitudinal forces in the construction industry. The outcome
was that operators held no negative feelings about minimizing construction waste; however, they were
reluctant to do so. Nevertheless, according to Chen (2008) study of Chinese contractors’ viewpoints on
construction waste minimization, both site supervisors and workers were recorded to be negative towards the
process of minimizing waste. To our knowledge, there has been no explanation of the designers' behavior
towards construction waste minimization based on the TPB. According to Li, Tam, Zuo, & Zhu (2015), attitude
towards waste prevention behavior and perceived behavioral control have a significant effect on designers’
behavior.
2.2. Attitudes toward waste prevention behavior (ATT) and Personal norms (PN)
The TPB (Icek Ajzen & Timko, 1986), in previous researches, has been expanded with the addition of
personal-norm concept to study behavior regarding moral beliefs. Personal norms are specified by (Icek Ajzen,
1991) as individuals’ model perspective of what is right or wrong when performing a particular behavior.
Personal norms, according to (Heberlein & Black, 1981) and (Schwartz & Howard, 1980), refers to a strong
internalization process of moral attitudes. These attitudes are generated from mutually shared norms in
society; then, adopted individually on a personal level to become personal norms (which can be called
internalization). Previous researches reckon personal norms as a significant predictor of environmental
behaviors in such cases as recycling (Hopper & Nielsen, 1991; Thøgersen, 1996), consumer purchase behaviors
of less environmental harmful products/packaging (Thøgersen, Haugaard, & Olesen, 2010), and organic
food/wine (Aertsens, Verbeke, Mondelaers, & Van Huylenbroeck, 2009; Zhou, Thøgersen, Ruan, & Huang,
2013). This critical relationship between personal norms and waste minimization behavior also applies in the
context of transportation. Higher levels of personal norms reported minimizing environmental impact comply
with higher chances of intentions to adopt more environmental-friendly alternatives for transportation such
as public transport (Jansson, Marell, & Nordlund, 2010; Ozaki & Sevastyanova, 2011). Hence, we hypothesize
the positive relationship between personal norms and prevention behavior.
In addition, when it comes to the connection between personal norms and behavior, it is suggested by

Hopper & Nielsen (1991) that individuals only behave in accordance with their personal norms if they are
fully aware of their actions’ consequences. According to Schwartz's model (1977), when individuals hold a
positive perception of the consequences of their behaviors, those who are morally obliged to perform a
particular behavior are more inclined to play that behavior. This applies to previous environmental cases, for
example, yard burning (Dunlap & Van Liere, 1978); recycling (Guagnano, Stern, & Dietz, 1995; Hopper &
Nielsen, 1991) and waste prevention (Bortoleto et al., 2012).
Therefore, we propose the following hypothesis:
H1: Attitudes toward waste prevention behavior has a direct and positive impact on personal norms.
H2: Attitudes toward waste prevention behavior has a direct and positive impact on prevention behavior.
H10: Personal norms has a direct and positive impact on prevention behavior.
2.3. Designer’s attitude and behavior toward waste minimization by design (AB)
There have been conductions in previous studies from designers’ perception of construction waste
minimization. First, there is a passive viewpoint among several professional designers towards waste
minimization by design. According to (Poon, Shui, Lam, Fok, & Kou, 2004), it appears that waste minimization

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was not mainly considered an emphasis task during a design process. Osmani, Vitale, Borg, & EtienneManneville (2006) demonstrated that architects assumed that it is site operations during which construction
waste was mostly produced and barely generated during the design stages. Second, the waste reduction was
notably hindered by the absence of clients and design companies (N. Osmani et al., 2006). Finally, it is an
inadequacy of experience and training resulting in obstruction of designers’ initiatives in waste minimization
(Bossink, Brouwers, & Kessel, 1996; Ekanayake & Ofori, 2004). A self-study is adopted by a majority of
designers, to which approaches education on construction waste management and reduction (N. Osmani et
al., 2006); Hao & Kang, 2010). However, the effect of designers’ waste minimization behavior by these factors
and of which had a more dominant effect was not revealed. The explanation and prediction of designers’ waste
minimization behavior, for which a hypothetically adaptive model is required to be improved with enormous
efforts.
Therefore, we propose the following hypothesis:
H3: AB has a direct and positive impact on ATT

H4: AB has a direct and positive effect on prevention behavior.
H5: AB has a direct and positive impact on subjective norms.
2.4. Subjective norms (SN) and Perceived behavioral control (PBC)
Subjective norms are suggested to be the social pressure of the relevant people in individuals’ surrounding
environment on their behaviors. According to Ajzen (1985), how an individual weights the importance of
others’ opinions on the matter may affect their behaviors. An individual who believes that the relevant people
whose views are significant to approve his behavior will perceive social pressure to commit the act.
Conversely, an individual who thinks that the proper people disapprove his response will be put under the
social pressure of not performing the behavior. Possible sources of these social pressure come from internal
referents such as family members and external referents such as neighbors, peers, the community, or society
at large. That families, neighbors, or peers take initiatives in waste prevention as setting behavioral role models
can act as motives for an individual to follow. Everett & Peirce (1993) suggest that behavioral role models must
be set from which norms can be spread out widely within the community. Otherwise, there is no one
pioneering in catalyze the norm.
According to Ajzen (1985), perceived behavioral control refers to whether it is easy or difficult for an
individual to perform a particular behavior. Greater control over the behavior is recorded when more
opportunities and fewer challenges are available during the performance of the behavior. Knowledge and
ability may not act as predictors of individuals’ actual behaviors, which is stated by (Davies, Foxall, & Pallister,
2002). However, knowledge and ability may affect how individuals perceive the behavior and the
consequences it has on the environment. Hence, PBC may not have a direct influence on PB but an indirect
influence through SN.
Therefore, we propose the following hypothesis:
H6: PBC has a direct and positive impact on designers’ attitudes toward waste minimization by design.
H7: PBC has a direct and positive impact on attitudes toward prevention behavior.
H8: PBC has a direct and positive impact on prevention behavior.
H9: PBC has a direct and positive impact on subjective norms.
H11: SN has a direct and positive impact on prevention behavior.
2.5. Prevention behavior (PB)
Prevention behavior refers to actions which can be done before the disposal of a substance, a material or a
product into the environment, consisting of strict avoidance, source reduction, and product reuse. Tonglet et

al., (2004) suggests that recycling and waste prevention are distinct dimensions of waste management

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behavior. Waste prevention activities can be performed under these following measures: (i) reuse, (ii) point of
purchase decisions, (iii) unnecessary purchases reduction, (iv) long-life and non-disposable products. The
measurement of behavior intention is excluded from this study for two reasons. First, regarding recycling
behavior, (Davies et al., 2002) specifies that intention is regarded as individuals’ support for prevention
behavior, not an initiative to perform an act. Hence, behavior intention is not considered a factor that
influences the behavior performance. Second, that only future intentions are assessed but not any past
intentions are the true motives for the reported behavior in the questionnaire makes behavior intentions
measurement inappropriate for the study.
Therefore, we propose the following hypothesis:
H12: Prevention behavior has a direct and positive impact on implementing waste prevention.
Figure 1 illustrates the research model.

Figure 1. Research Model
3. Measurement

3.1. Attitude towards waste prevention behavior (ATT)
In general terms, individuals’ attitude toward a specific act is a determinant of favored or against behavior
in a particular manner. It's measurement based on the using of individuals’ beliefs regarding the outcomes of
the behavior from an evaluation of its outcomes (Boldero, 1995; Cheung, Chan, & Wong, 1999). Five items
measured the variable ATT via five-point scale from ‘Strongly disagree’ to ‘Strongly agree.’
3.2. Perceived behavioral control (PBC)
There is not a generally favored method of measuring PBC. However, an essential correlation between the
product of control beliefs by the perceived power, which includes situations that would facilitate or inhibit the

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behavior, and a direct measure of PBC, which is representative of both perceived control and perceived
difficulty, is demonstrated (Cheung et al., 1999). Five items were selected for measuring this variable which
was reported on a five-point scale from ‘Strongly disagree’ to ‘Strongly agree.’
3.3. Subjective norms (SN)
Subjective norms are considered as a global measure based on direct approach. The composite approach
proposed by (Ajzen & Fishbein, 1980) and the global measure method build a correlation which is high and
statistically significant (Cheung et al., 1999). The research is a combination of both internal referents (family
members) and external referents (individuals or groups outside the family) of social pressure in a single
construct. Each item was rated on a five-point scale ranging from ‘Strongly disagree’ to ‘Strongly agree.’
3.4. Personal norms (PN)
Personal norms reflect individuals’ belief about how they should act. Based on personal beliefs, right or
wrong acts are crucially an establishment of moral or behavior prediction. It is a process of internalization of
social and moral norms that form personal norms resulting in the dependence of social norms and frequencies
of behaviors. Therefore, when it comes to accordance between individuals’ actions and their personal norms,
they experience a strong sense of pride. Conversely, when it comes to the violation of personal norms, they
experience guilty feelings. The variable was measured using a five-point scale from 1 (‘Strongly disagree’) to
5 (‘Strongly agree’).
3.5. Prevention behavior (PB)
Since it is impossible to make individual observations and assessments of prevention behavior of all
respondents participating in this research, self-report is an applicable and appropriate proxy to measure this
variable. The total of eight items adopted from (Gamba & Oskamp, 1994) were taken as measures by five-point
scale, ranging from ‘Strongly disagree’ to ‘Strongly agree.’
Table 1
Latent
Variables

Measurem
ent items

ATT1

Attitude
toward
waste
prevention
behavior
(ATT)

ATT2
ATT3
ATT4
ATT5

Designer’s
attitude
toward
waste
minimizati
on
by
design
(AB)

AB1
AB2

AB3

PBC1

Sources
Environmental problems can affect my family’s
health
Reducing and recycling waste save space in the
landfill
Reducing and recycling waste save energy
Reducing and recycling waste reduce my
family's cost
Reducing and recycling waste establish a better
environment in the future
Implementing waste minimization by design
helps to minimize household's waste
Implementing waste minimization by design
benefits the environmental protection
Implementing waste minimization by design
benefits the establishment of an environmentfriendly enterprise image
I know how to recycle and reuse domestic waste

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Boldero, 1995;
Cheung, Chan, & Wong,
1999

Poon, C. S., & Jaillon, L.
(2002); Osmani, M., Glass, J.,
& Price, A. D. (2008);
Tonglet, M., Phillips, P. S., &
Read, A. D. (2004)

(Cheung et al., 1999)


PBC2
Perceived
behavioura
l
control
(PBC)

PBC3
PBC4
PBC5
PB1
PB2
PB3

Prevention
Behavior
(PB)

PB4
PB5
PB6
PB7
PB8
PN1

Personal

Norms
(PN)

PN2
PN3
PN4
SN1

Subjective
Norms
(SN)

SN2
SN3

Implement
ing
constructio
n
waste
minimizati
on
by
design (IS)

IS1
IS2
IS3
IS4

I control my domestic waste
I control all of recycled and reused products
I can classify daily domestic waste
I have enough space for recyclable and reusable
domestic waste
I buy things that are produced with as little
packaging as possible
I use my own bag when going shopping, rather
than one provided by the shop
I look for packaging that can be easily reused or
recycled
I buy products that can be reused rather than
disposable items
I wash and reuse dishcloths rather than using
paper towels
I donate old items to charity or to other possible
users

Ajzen,
I.
(1985);
Davies, J., Foxall, G. R., &
Pallister, J. (2002)

Gamba, R. J., & Oskamp, S.
(1994)

I reuse containers
I am economical
Recycling domestic waste is vital

I feel it is my responsibility to recycle any
possible waste

Davies et al. (2002)

Domestic waste needs collecting on regular basis
Reducing and recycling waste do not concern me
Most people who are important to me have
impacts on my environmental awareness
Most people I know have impacts on my
environmental awareness
Most people I know are environmentally friendly
Construction process of waste minimization by
design is strictly supervised
Upgrading and completing waste minimization
constructional system is essential
Waste minimiazation factories reaches their
highest productivity or not
Enterprises give households guidance on
classifying hazadous waste

Ajzen,
I.
(1985).
Cheung et al. (1999)
Bortoleto et al. (2012)

Bortoleto et al. (2012)
Osmani et al. (2008)

4. Research Methodology

4.1. Questionaire design
To investigate the attitude and behavior towards waste prevention of local households, a questionnaire
was designed with 3 main parts: (1) background of the survey, including a basic introduction and purpose of

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the survey; (2) characteristics of recipients, including gender, age, family members, and education level; (3) 9
questions relating to hypothetical model.
4.2. Data collection
The survey was conducted in Tay Ninh City, Vietnam with all of the recipients are local households. There
are in total 750 questionnaires were randomly distributed and immediately taken back after the survey
completed, in which 593 cases are valid.
4.3. Data analysis
The hypothetical model is tested using structural equation modeling (SEM) with the software SPSS 20.0
and AMOS 20.0. The measurement of variables in the equation system is illustrated about observed variables
and unmeasured latent variables whose correlations are also specified by SEM. SEM is a two-phase modelbuilding process consisting of two distinct but interrelated models (a measurement model and a structural
model).
The measurement model is to evaluate reliability and validity of latent variables. Reliability which
represents for the consistency among measurement items is measured by Cronbach’s α whose range is from 0
to 1. The higher values of the Cronbach’s α, the higher reliability measurement items illustrate. In general, if a
coefficient α scores higher than 0.7, it is evaluated to be highly reliable (Tonglet et al., 2004). However, it is
acceptable for a coefficient α to be higher than 0.6 in exploratory research, recommended by Fornell & Larcker
(1981). Validity represents to what extent one observed variable is measured in association with the latent
variable. Validity is assessed using confirmatory factor analysis (CFA). Hair, Black, Babin, Anderson, &
Tatham (1998) suggested that factor loading coefficients of observed variables reach a minimum requirement
of 0.5 to be stated valid and significant. In addition, model fit evaluation is one indispensable stage in the
process to assess the goodness-of-fit of the measurement model. Model fit demonstrates the normalized chisquare (X2/df), root mean square error of approximation (RMSEA), goodness-of-fit index (GFI), incremental

index of fit (IFI), comparative fit index (CFI), adjusted goodness-of-fit index (AGFI), parsimonious normed fit
index (PNFI) and parsimonious comparative fit index (PCFI).
The structural model is assessed using the technique called maximum likelihood estimate in SEM. This
estimation measures the overall fitness indices of the model, based on the same indices as measurement model
above. The estimated standardized path coefficients are the standardized regression weight, demonstrating
the degree of correlation between two variables. The statistically significant path coefficients strengthen their
hypothetical interrelation. Squared multiple correlation coefficient regarding the variance of a variable
explained by other variables is also taken into consideration.
5. Results

5.1. Demographic characteristics
There are 593 valid questionnaires collected. According to Bortoleto et al. (2012), SEM analysis is sensitive
to the sample size, which should not be too small. To examine more than 10 variables, the recommendation
cases are at least 100 (Loehlin, 1998). Therefore, the collected questionnaires are sufficient to be tested by SEM.

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Table 2. Sample profile.
Samples n = 593
Proportion
Gender
Male
Female
Age
< 20
20 - 40
40 - 60
> 60
Academic level

Undergraduate
Graduate
Others
Family members
1-4
>=5
Household position
Frontage
Alley
Waste reuse amount
< 30%
30% - 60%
> 60%
Others

61.9
38.1
10.3
38.4
36.6
14.7
39.1
5.7
55.2
78.9
21.2
50.6
49.4
54.6
32.2

10.6
2.5

The sample profile is illustrated in Table 2. By gender, the proportion of male is dominant, at 61.9%. A
majority of respondents is at the age ranging from 20 – 60 which is approximately 3/4 of the total. In the
survey, there are two kinds of household position: frontage and alley, which are at a nearly equal rate (50.6%
and 49.2% respectively). Finally, it appears that more than a half of the waste reuse amount is under 30% is
higher than the sum of other scales.
5.2. The measurement model.
Table 3 consists of the factor loadings and level of Cronbach’s alpha. All of the factor loadings are above
the recommended level (>0.5). The reliability is clearly evidenced as all of the Cronbach’s alpha levels exceed
the required standard (>0.5), most of which are > 0.8 showing high reliability. The model fit indices (X2/df =
3.043; p = 0.000; RMSEA = 0.065; GFI = 0.895; IFI = 0.919; CFI = 0.918; AGFI = 0.870; PGFI = 0.725; PNFI = 0.769)
indicate the acceptable validity of measurement model.

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Table 3. The reliability and validity of the latent variables in the measurement model.
Variables

PB

PBC

ATT

PN

IC

SN

AB

Measurement items
PB1
PB2
PB3
PB4
PB5
PB6
PB7
PB8
PBC1
PBC2
PBC3
PBC4
PBC5
ATT1
ATT2
ATT3
ATT4
ATT5
PN1
PN2
PN3
PN4
IC1
IC3

IC4
SN1
SN2
SN3
AB1
AB2
AB3

Factor Loadings
0.507
0.539
0.675
0.701
0.668
0.722
0.691
0.674
0.702
0.740
0.774
0.703
0.787
0.754
0.666
0.652
0.585
0.719
0.723
0.741
0.622

0.818
0.701
0.758
0.795
0.851
0.880
0.703
0.760
0.710
0.830

Cronbach's alpha

0.889

0.881

0.826

0.788

0.740

0.859

0.799

5.3. Structural model
Values of model fit indices are all acceptable. As demonstrated in Table 4, X2/df is 3.501, the RMSEA (0.065)
is above 0.05 and less than 0.08, indicating an acceptable fit index; GFI (0.875) is less than the required level of

0.90 but very close to that; AGFI (0.850); PGFI (0.728) and PNFI (0.771) separately exceed the recommended
requirements. IFI and CFI share equal scores at a high level (0.897) and are nearly adequate for the required
indices of 0.9.
Table 4. Fit indices of the model.
Indices value
X2/df
RMSEA
GFI
AGFI

3.501
0.065
0.875
0.850

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IFI

0.897

CFI
PGFI
PNFI

0.897
0.728
0.771

The standardized estimation of the path coefficients and their significance levels for the structural model
are visualized in Table 5. The table illustrates that all the path coefficients, apart from the effect of AB and SN
on PB, are statistically significant. ATT, PBC, and PN are demonstrated to have moderate impacts on PB, with
all indices meet the standard requirement. This means hypothesis H1, H8 and H10 are supported. Meanwhile,
AB and SN bear little statistical relations to PB, indicating that hypothesis H4 and H11 are not supported. In
addition, the significance between PB and IC is statistically proved, supporting for hypothesis H12.
The path coefficients of AB and PBC to ATT is 0.600 and 0.212 respectively. The prior figure is nearly more
than threefold the latter one, which means AB has a more significant influence on ATT than PBC and this path
coefficient plays the most important part of all. However, in the relationship with SN, AB rather than PBC, is
shown to have a more significant effect (path coefficient of the former being 0.478 and the latter being 0.286).
The path coefficients of PBC to AB is at 0.265 and that of ATT to PN is at 0.277, are estimated to be moderate.
Moreover, among all five effects of PN, ATT, SN, PBC, and AB to PB, ATT appears to be the most critical factor
of prevention behavior (0.261). Finally, the statistic shows path coefficient of PB to IC as the second most
significant of all coefficients at 0.590.
Table 5. Path coefficient and its significance of the structural model.
Hypothesis

Estimate

S.E.

C.R.

P

Label

Result

H1

ATT has a positive effect on PB

0.261

0.043

6.082

***

par_24

Accepted

H2

ATT has a positive effect on PN

0.277

0.034

8.050

***

par_22

Accepted

H3

AB has a positive effect on ATT

0.192

0.038

5.069

***

par_33

Accepted

H4

PBC has a positive effect on ATT

0.600

0.045

13.184

***

par_32

Accepted

H5

AB has a positive effect on PB

0.032

0.026

1.225

0.221

par_30

Rejected

H6

AB has a positive effect on SN

0.478

0.051

9.350

***

par_25

Accepted

H7

PBC has a positive effect on AB

0.265

0.050

5.292

***

par_31

Accepted

H8

PBC has a positive effect on PB

0.225

0.036

6.196

***

par_28

Accepted

H9

PBC has a positive effect on SN

0.286

0.050

5.783

***

par_26

Accepted

H10

PN has a positive effect on PB

0.197

0.037

5.301

***

par_23

Accepted

H11

SN has a positive effect on PB

0.015

0.022

0.674

0.5

par_27

Rejected

H12

PB has a positive effect on IC

0.590

0.071

8.294

***

par_29

Accepted

6. Discussion and conclusion

6.1 Discussion
This result reveals the strong relationship between ATT and PBC through the mediating role of PB. It
echoes the previous researches of Bortoleto et al. (2012) and Li et al. (2015), showing that a good awareness
among households would probably improve waste prevention tremendously. It is worth noting that ATT,
PBC, PN have a direct impact on PB, aligning with the previous studies (Hines, Hungerford, & Tomera, 1987;

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Davies et al., 2002) which indicate the influence of ATT on PB is moderate. It is also proved that other factors
have a moderate effect on PB.
It is contradictory to Barr, Gilg, & Ford's (2001) and Tucker & Douglas's (2007) studies demonstrating the
relationship between ATT and PB is insignificant, this result indicates that ATT has the greatest influence on
PB. It strengthens the finding of Hines et al. (1987). The finding implies that the spread of mass media
positively enhances the residents’ awareness of environmental issues resulting in their prevention behavior.
Another highlighted finding is the connection between PBC and PB. While it is inconsistent with the result
of (Davies et al., 2002), the result is in line with that of (Bortoleto et al., 2012) showing that PBC is a significant

factor that impacts on PB. In addition, to individuals who find it is in difficult in waste prevention as well as
barely have a strong self-responsibility, there are higher possibilities of involvement in waste prevention. It is
similar to those who have high PBC that they would likely to turn the possibilities into actions.
As pointed out by (Davies et al., 2002), there is a direct influence of PBC to PB, which does not mediate by
SN. Similarly, the corresponding result is revealed in this study. Also, the finding shows that the effect of PBC
is more important than AB in waste prevention, which is match with the study of Wang, Li, & Tam (2014), and
contrast to that of M. Osmani, Glass, & Price (2008).
AB and SN have the weakest influence on PB, with the former’s coefficient being 0.032 and that of the latter
being 0.015. The result of no direct relationship between SN and PB is matched with the study of Bortoleto et
al. (2012). In other words, there is the only indirect influence of SN on PB mediating by PN. Moreover, it is
rejected the relationship of SN and PB by previous study Bortoleto et al. (2012); Li et al. (2015). On the other
hand, there are some researchers support this relationship pointing out that SN is the most significant factor
that impacts on PB. In Ramayah et al.'s (2012) study, they assert that SN was the most important predictor of
recycling behavior as collectivism was dominant in South-east Asia, which has an impact on people’s behavior.
However, the result shows that individuals are not influenced by others’ opinion such as family, friends or
society in their prevention behavior, aligning with the finding of Schwartz (1977).
According to Hines et al. (1987) and Li et al. (2015), AB moderately affects to PB and PB is the mediator of
AB and IC. However, the finding of this study indicates that AB has a very small effect on PB, echoing the
result of Poon et al. (2004) and M. Osmani et al. (2008). This implies that designers’ attitude towards waste
prevention insignificantly affects the waste prevention behavior of the residents, which is determined by their
attitude and awareness. If there is the good management of the factors, it would probably result in better
improvement in waste prevention.
Last but not least, our study indicates the mediator role of PB linking AB and PBC with IC. Since the
coefficient of AB to PB, PBC to PB, and PB to IC is significant, hence, the role of PB is essentially vital. The
finding was also consistent with the study of Wen, Chang, Hau, & Liu (2004). The result proves the fitness of
our model based on TPB.
6.2. Conclusion
The paper attempts to develop a research model to investigate the household behavior on family waste
prevention in Tay Ninh province, Vietnam at the most fundamental level of a household unit inwards. Most
previous studies have been conducted in either other countries or some big cities in Vietnam. However, this

study explored at a local scale with different characteristics of citizens and different patterns of performing a
behavior. Overall, exploring determinants of behavioral intention that leads to waste minimization actions
makes a crucial contribution to the environment, society, and economy. The findings demonstrate a poor
relationship between designers’ attitudes towards waste minimization and social norms and behavior
intention. However, individuals’ attitudes towards the behavior and perceived behavioral control have been
statistically supported to be determining factors in the implementing process of household waste
minimization. Moreover, designers’ attitudes and perceived behavioral control appear to have a relatively

403


equal impact on prevention behavior, suggesting waste management policies to be more concentrated on these
two factors. Particularly, if the local government implemented incentive policies as well as promoted the
spread of mass media, the households would be aware of environmental issues and change their behavior in
littering garbages. They are more likely to proact in waste prevention.
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