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


393


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


394


was not mainly considered an emphasis task during a design process. Osmani, Vitale, Borg, &
Etienne-Manneville (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

395


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


396


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 Sources
ent items
ATT1
Environmental problems can affect my
family’s
health
Attitud
ATT2
Reducing and recycling waste save space in
e
the
landfill
Boldero,
toward
1995;
waste
ATT3

Reducing and recycling waste save energy Cheung, Chan, & Wong,
prevention
1999
ATT4
Reducing
recycling waste reduce my
behavio
and
r
(ATT)
family's cost
ATT5
Reducing and recycling waste establish a
better
environment in the future
Designer’s AB1
Implementin
waste
by design
g
minimization
attitud
helps to minimize household's
Poon, C. S., & Jaillon,
e
waste
L.
toward
Implementin
waste

by design (2002); Osmani, M.,
AB2
g
minimization
Glass, J.,
waste
benefits the environmental
&
A.
D. (2008)
protection
Price,
;
minimizati


on
design

by
AB3

(AB)
PBC1

Implementin
g

waste
minimization

by design Tonglet, M., Phillips, P. S.,
&
Read, A. D. (2004)

benefits the establishment of an
environmentfriendly enterprise image
I know how to recycle and reuse domestic
waste
397

(Cheung et al.,
1999)


PBC2
Perceived

PBC3
behavioura
l
control PBC4
(PBC)
PBC5

I am economical

PN1

Recycling domestic waste is

vital
I feel it is my responsibility to recycle
any
possible waste

Prevention PB4

PB5
PB6

PN2

Norms
PN3
PN4
SN1
Subjective
Norms
(SN)

SN2
SN3

Implement IS1
ing
IS2
constructio
n

(1985)

;
Davies, J., Foxall, G. R., &
I control all of recycled and reused products Pallister, J. (2002)

PB8

PB3

(PN)

I.

PB7

PB2

Personal

Ajzen,

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
Gamba, R. J., & Oskamp,
I buy products that can be reused rather
S.
than
disposable items
(1994)
I wash and reuse dishcloths rather than
using
paper towels
I donate old items to charity or to other
possible
users
I reuse containers

PB1

Behavior
(PB
)

I control my domestic waste

waste

minimizati IS3

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
reaches their
factories
highest productivity or not

Davies et al.
(2002)

Ajzen,
Cheung

I.
et

(1985)
.
al.

(1999)

Bortoleto et al.
(2012)

Bortolet et al.
o
Osmani et al.
(2008)

(2012)


on
by
design (IS) IS4

Enterprises give
households
classifying hazadous waste

guidanc

e

on

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

398


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 model-building 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 chi-square (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.

399


Table 2. Sample profile.
Samples n = 593
Proportion

Gender
Male
Female

61.9
38.1

Age
< 20
20-40
40-60
> 60

10.3
38.4
36.6
14.7

Academic level
Undergraduate
Graduate
Others

39.1
5.7
55.2

Family members
1-4
>=5

78.9
21.2

Household position
Frontage
Alley

50.6
49.4

Waste reuse amount
< 30%
30% - 60%
> 60%
Others

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.

400


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

PB

Measurement items
PB1
PB2
PB3
PB4
PB5
PB6
PB7
PB8

Factor Loadings
0.507
0.539
0.675
0.701
0.668

0.722
0.691
0.674

PBC

PBC1
PBC2
PBC3
PBC4
PBC5

0.702
0.740
0.774
0.703
0.787

0.881

ATT

ATT1
ATT2
ATT3
ATT4
ATT5

0.754
0.666

0.652
0.585
0.719

0.826

PN1
PN2
PN3
PN4

0.723
0.741
0.622
0.818

IC

IC1
IC3
IC4

0.701
0.758
0.795

0.740

SN

SN1
SN2
SN3

0.851
0.880
0.703

0.859

AB

AB1
AB2
AB3

0.760
0.710
0.830

0.799

PN

Cronbach's alpha

0.889

0.788

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
3.501
0.065
0.875
0.850

X2/df
RMSEA
GFI
AGFI
401



IFI
CFI
PGFI
PNFI

0.897
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
H1
H2
H3
H4
H5
H6
H7
H8
H9
H10

H11
H12

Estimate S.E.
ATT has a positive effect on
PB
ATT has a positive effect on
PN
AB has a positive effect on
ATT
PBC has a positive effect on
ATT
AB has a positive effect on
PB
AB has a positive effect on
SN
PBC has a positive effect on
AB
PBC has a positive effect on
PB
PBC has a positive effect on
SN
PN has a positive effect on
PB
SN has a positive effect on
PB
PB has a positive effect on IC

C.R.

P

Label

Result

0.261

0.043 6.082

***

par_24

Accepted

0.277

0.034 8.050

***

par_22

Accepted

0.192

0.038 5.069

***

par_33

Accepted

0.600

0.045 13.184 ***

par_32

Accepted

0.032

0.026 1.225

0.221 par_30

Rejected

0.478

0.051 9.350

***

par_25

Accepted

0.265

0.050 5.292

***

par_31

Accepted

0.225

0.036 6.196

***

par_28

Accepted

0.286

0.050 5.783

***

par_26

Accepted

0.197

0.037 5.301

***

par_23

Accepted

0.015

0.022 0.674

0.5

par_27

Rejected

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;


402


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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