Factors influencing green purchase intention of students: A case study at Vietnam national university of agriculture
ISSN 2588-1299
VJAS 2020; 3(3): 732-745
Vietnam Journal
of Agricultural
Sciences
Factors Influencing Green Purchase
Intention of Students: A Case Study at
Vietnam National University of Agriculture
Chu Thi Kim Loan
Faculty of Accounting and Business Management, Vietnam National University of
Agriculture, Hanoi 131000, Vietnam
Abstract
The objective of the paper was to analyze factors influencing the
green purchase intention of students through a case study at the
Vietnam National University of Agriculture (VNUA), Hanoi,
Vietnam. The primary data were collected from a survey of 121
undergraduate students in 2020. The study employed descriptive
statistics, exploratory factor analysis (EFA), and multiple regression
analysis. The survey indicated that VNUA students were highly
concerned about the environment. Their green buying intention was
significantly and positively affected by two groups of factors,
including: (i) social influence and product knowledge; and (ii)
environmental concerns and subjective norms; in which, the later
group of factors has shown greater effects in this study. The study
would help managers in formulating and implementing key measures
to encourage students’ green purchase.
Keywords
Green purchase intention, students, factor scores, multiple regression
Introduction
Today, environmental problems are still the main worry for the
whole world and human beings. Air pollution, conservatory effects,
and ecological unbalance are the main environmental problems that
have occurred so far as the consequences of human activities
(Sharma, 2011). Humans now have to face environmental pollution
and suffer from severe climate change. An image of a dead whale
with 40kg of plastic bags inside its stomach in the Philippines
(Dalton, 2019), or the status of worse drought and salinity in
Vietnam’s Mekong Delta last year, etc., has raised an urgent warning
bell about environmental problems. People need to take prompt
actions against the widespread use of environmentally unfriendly
products. In other words, both producers and consumers should pay
more attention to green products, of which consumers play a large
role in environmental protection. This is supported by the evidence
Received: July 28, 2020
Accepted: November 14, 2020
Correspondence to
732
Vietnam Journal of Agricultural Sciences
Chu Thi Kim Loan (2020)
that 30-40% of environmental degradation has
been brought about by the consumption activities
of private households (Grunert, 1993).
According to Bray et al. (2011), although the
number of individuals willing to purchase green
products has increased in the last few years, there
is little evidence to suggest that purchase of green
products has increased; despite environmental
concern and positive attitude of customers
towards sustainability and green products,
market share of green products remains confined
to just 1-3% of the entire market.
students are often said to be future owners of the
country. They are young, dynamic, and
ambitious. Ottman et al. (2006) and Tai & Tam
(1997) believed that young people are more
ready than older generations to accept new and
innovative ideas. Moreover, supporters of
environmental protection tend to be younger
(Martinsons et al., 1997). Therefore, students’
knowledge, concern, and behavior towards green
products play an important role in sustainable
development. In Vietnam, there have been some
researchers conducting studies related to this
topic. For example, Hoang Trong Hung et al.
(2018) analyzed factors affecting consumers’
green purchase behavior in Hue city; Nguyen
The Khai & Nguyen Thi Lan Anh (2016) studied
consumers’ green purchase intention in Ho Chi
Minh city; etc. However, they mainly focused on
interviewing consumers. Therefore, this research
was conducted to explore factors influencing
green purchase intention of students and to make
some recommendations to encourage students’
green buying.
In Vietnam, the government has been
implementing a number of activities related to
sustainable production and consumption. Some
documents were signed and enacted such as the
International declaration and national action plan
on sustainable production and consumption; the
Law No. 50/2010/QH12 on economical and
efficient use of energy; and Decision No. 1393
on
National strategy on green
growth for
the 2011-2020 period with a vision to 2050; etc.
Despite being in place, their actual effectiveness
at the implementation level was still limited
(Hoang Thi Bao Thoa, 2016). Reitman (1992)
also found that producers have reacted to
Methodology
consumers’
growing
environmental
Theoretical background
consciousness by developing green products.
Nevertheless, only a few green products have
been successfully developed. In another study,
Kirmani & Khan (2016) emphasized that, “As of
now, green products are expensive due to lack of
economies of scale and slow adoption of cutting
edge green technology. Hence, there is a
pressing need to identify factors that can
influence consumers' decision to pay a premium
for the purchase of green products”.
Definitions of green products and green
purchase intention
The concept of a green product or
environmentally friendly product has been
mentioned by some previous researchers.
According to Shamdasani et al. (1993), a green
product is one which satisfies consumers’ needs
without damaging the environment and
contributes towards a more sustainable world.
These products are environmentally superior and
have a low environmental impact. Chen & Chai
(2010) showed that green products use materials
safer to the environment, are recyclable, and
require less packaging.
Vietnam
National
University
of
Agriculture (VNUA) is the leading national
university in human resource training and
research on agriculture and rural development
which is considered to be a large-scale multi-
disciplinary university in Vietnam. VNUA
annually enrolls around 6,000 undergraduate
freshmen and roughly 1,200 other candidates
(VNUA, 2020). The total numbers of VNUA’s
undergraduate students in April 2020 were about
18,600 (FABM, 2020). This also implies that
their demand for shopping is large. Generally,
Green purchase intentions refer to an
individual’s readiness to perform green buying
behavior, mainly reflecting the consideration of
less pollution. It is assumed to be an immediate
antecedent of behavior (Wang et al., 2019).
Factors affecting green purchase intention
in previous studies
733
Factors influencing green purchase intention of students: A case study at Vietnam National University of Agriculture
According to previous studies, green
purchase intentions were affected by different
factors, including environmental concerns,
product knowledge/information, subject norms,
social influence, environmental attitude,
perceived behavior control, availability of
products, and perceived consumer effectiveness,
etc. (Joshi & Rahman, 2015). Their influence
levels on green buying intention were found to be
different in various studies.
discusses about environmental products with
his/her friends, and how much he/she shares
information about green products with their
family (Finisterrado & Raposo, 2004). Perceived
behavioral control refers to the capacity of an
individual to perform a given behavior (Ajzen,
1988). The results of a review by Joshi &
Rahman (2015) showed that perceived
behavioral control, subjective norm, and social
influence had positive effects on green purchase
intention in some previous studies such as
Tarkiainen & Sundqvist (2005) and Kang et al.
(2013). In addition to these factors, the
availability of organic food was found to be one
of the independent variables in the studies by
Tarkiainen & Sundqvist (2005) and Vermeir &
Verbeke (2008). Another factor, namely
perceived consumer effectiveness (PCE), was
also pointed out to positively affect green
purchase intention in the research of Gupta &
Ogden (2009) and Gleim et al. (2013), etc.
Hessami & Yousefi (2013) argued that
environmental concerns could be defined as an
attitude towards environmental consequences.
This attitude is influenced by direct personal
experience, the experience of other people, and
media’s news. Consumers with a stronger
concern for the environment are more likely to
purchase products as a result of their
environmental claims than those who are less
concerned about environmental issues (Mainieri
et al., 1997). Environmental concern is a main
and determinant factor in purchasing green and
organic food in a number of studies (Grunert,
1993). Laroche et al. (2001) also pointed out that
consumers with higher levels of environmental
concerns would be more likely to exert
environmentally friendly consumption.
Research model
Hypothesis
Based on the above discussions and
characteristics of the study site, a research model
was developed as shown in Figure 1. All of these
factors were hypothesized to positively influence
green purchase intention of the students studying
at the Vietnam National University of
Agriculture.
Green product knowledge refers to
subjective knowledge that is the consumers’
understanding of the environmental attributes
and environmental impacts of green products
(Wang et al., 2019). Barrutia & Gilsanz (2013)
figured out that consumers’ product knowledge
could directly influence their cognition of
product attributions and evaluation criterion,
which would further influence consumers’
abilities to collect and handle information. As
stated by Wang et al. (2019), some previous
studies also pointed out that green product
knowledge is often regarded as a direct predictor
of green purchase intention, which implies the
assumption that consumers with green product
knowledge will buy green products.
Observed variables
Most dependent variables were inherited
from previous studies and were adjusted to better
match the specific conditions of the study site.
Specifically, they were mainly developed based
on the studies of Kim & Choi (2005), Chen &
Deng (2016), Puspitasari et al. (2018), and
Hoang Trong Hung et al. (2018). Few other
indicators were developed from discussions with
Vietnamese specialists and students. All of the
variable indicators were pretested before the
official survey so that some necessary
modifications could be performed. Finally, six
dependent variables with 24 items were chosen
(Table 1).
Social influence refers to the effects of the
social environment on consumers’ green
purchasing behavior. That is, how much the
person gains knowledge about green products
through his/her family, how much he/she
Vietnam Journal of Agricultural Sciences
734
Chu Thi Kim Loan (2020)
H1+
H2+
Environmental concerns
Availability of green products
H3+
H4+
H5+
H6+
Perceived behavior control
Subjective norms
Green Purchase
Intention
Social influence
Green product knowlege
Figure 1. Research model
The indicators of the dependent variable
(GPI) were mainly derived from the studies of
Chen & Deng (2016) and Puspitasari et al.
(2018). The five-point Likert scale between 1 to
5 was used to measure the observed variables.
category contains a minimum of three statements
up to a maximum of five ones. For each
statement, respondents have five options to
express their level of agreement: Strongly
disagree, disagree, undecided, agree, and
strongly agree. The respondents were required to
choose only one option for each statement.
Afterwards, an average point was calculated for
each statement and each category separately,
with 1 being the possible minimum result and 5
being the maximum possible result. The result
was then concluded with an overall average.
Data collection and analysis
Data collection
For the sample size, Hair et al. (1995)
indicated that as a general rule, the minimum is
to have at least five times as many observations
as there are variables to be analyzed, and the
more acceptable range would be a ten-to-one
ratio. In another case, Hair et al. (2010)
suggested that sample sizes should be 100 or
more. Based on these arguments, and due to the
cost and time limitation, with 24 independent
variables used for the EFA, the expected number
of samples for this study would be 140. Only
undergraduate students were chosen for the
survey by convenience sampling method. An
online survey was conducted in April and May
2020 to collect the primary data. A total of 135
questionnaires was obtained, of which only 121
were considered valid.
Data analysis
(i) Descriptive statistics
Descriptive statistics in the form of
percentage, mean, and frequency was used to
analyze
respondents’
demographic
characteristics and their evaluation toward green
purchase.
(ii) Test of Cronbach’s Alpha reliability
Cronbach’s coefficient alpha is a measure of
internal consistency or how closely related a set
of items are. It eliminates unsatisfactory
observation variables or scales in the survey.
Variables that item-total correlation coefficient is
less than 0.3 will be crossed out and the standard
scale is Cronbach’s alpha greater than or equal to
0.6 (Peterson, 1994).
A questionnaire-based Google form was sent
to the students via their emails and Microsoft
Teams flatform. The questionnaire consists of
two parts: personal information and students’
evaluation related to the green purchase. The
second part consists of seven categories. Each
(iii) Exploratory Factor Analysis (EFA)
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Factors influencing green purchase intention of students: A case study at Vietnam National University of Agriculture
Table 1. Variables of the research model
Variables
(factors)
Variable Indicators
Code
Source
Puspitasari et al. (2018)
I am worried about the deterioration of Vietnam’s environment.
EC1
EC2
EC3
(Revised)
Mankind is severely abusing the environment.
Kim & Choi (2005)
Environmental pollution can only be eliminated when we work
together.
Hung et al. (2018)
Environmental
concerns (EC)
When humans interfere with nature, it often produces disastrous
consequences.
EC4
EC5
AV1
Kim & Choi (2005)
Kim & Choi (2005)
Paul et al. (2016)
Humans must live in harmony with nature in order to survive.
Green products are available at the common stores where I usually do
my shopping.
Availability of
green
products
Hoang Trong Hung et al.
I know where green products are sold.
AV2
AV3
(2018) (Revised)
(AV)
I do not find any inconvenience when purchasing green products
instead of ordinary non-green products.
Hoang Trong Hung et al.
(2018) (Revised)
I cannot decide whether to buy a green product.
PBC1
PBC2
PBC3
SN1
Chen & Deng (2016)
Chen & Deng (2016)
Hung et al. (2018)
Chen & Chai (2010)
Perceived
behavior
control (PBC)
Buying habits will have a strong impact on decision making.
I have time to search and consider buying green products.
Environmental issues are very important to me.
I think green products more in line with the wishes of my relatives and
friends.
SN2
SN3
Chen & Deng (2016)
Chen & Deng (2016)
Subjective
norms (SN)
I think green products are consistent with the trend of social
development.
I think green products are more in line with my moral values.
I discuss with my friends about green products.
SN4
SI1
SI2
Chen & Deng (2016)
Lee (2008)
Most of my relatives advised me to green consumer products.
Developed
Mass media in Vietnam provide much information about green
products.
SI3
Developed
Social
influence (SI)
Vietnamese government is encouraging people to buy green products.
I learn a lot about green products from my relatives and friends.
I am familiar with green products.
SI4
SI5
Developed
Puspitasari et al. (2018)
Chen & Deng (2016)
Developed
PK1
PK2
Green products are harmless to human and environment.
Green product
knowledge
(PK)
I believe in testing and identifying green products that are implemented
by certification organizations.
PK3
Chen & Deng (2016)
I know information about green products.
PK4
Puspitasari et al. (2018)
Puspitasari et al. (2018)
I intend to buy a green product because it reduces pollution.
GPI1
Comparing with ordinary non-green products, I am more willing to buy
green products.
GPI 2
GPI 3
GPI 4
Chen & Deng (2016)
Green
purchase
intention (GPI)
Hoang Trong Hung et al.
I will suggest my relatives and friends buy green products.
(2018)
Next time I go shopping, it is very likely that I would choose green
products.
Chen & Deng (2016)
Factor analysis is often used to identify a
small number of factors that explain most of the
variance embedded in a large number of
variables. According to Izquierdo et al. (2014),
Vietnam Journal of Agricultural Sciences
736
Chu Thi Kim Loan (2020)
Table 2. Five-point Likert scale
Mean
Level
Strongly disagree
Disagree
Mean
Level
Agree
1.00 - 1.80
3.41 - 4. 20
4.21 - 5.00
1.81 - 2.60
Strongly agree
2.61 - 3.40
Undecided
the first step in conducting an EFA is to
determine whether or not the data collected are
adequate for this type of analysis, specifically
determining whether the data are factorable. The
first of these is the Kaiser-Meyer-Olkin (KMO)
test that yields a qualitative index of the strength
of relationship among variables based on zero-
order and partial correlations while measuring
sampling adequacy for each variable and the
overall model. KMO test values range between 0
and 1, with higher numbers representing greater
adequacy. The second a priori analysis is
Bartlett’s test of sphericity that estimates the
degree to which the intercorrelation matrix
produced is an identity matrix.
Where, Y is the students’ green purchase
intention;
b0, b1, b2..., bn are the estimated
coefficients;
F1, F2…, Fn are the factors affecting
students’ green purchase intention (identified
after an application of EFA);
u is the stochastic error term.
Results and Discussion
Overview of the respondents
Among the total of 121 respondents, the
percentages of males and females were
approximately 72% and 28%, respectively
(Table 3). About 66% of the total sample were
third- and fourth-year students. The monthly
average income of the surveyed students mainly
ranged from 1.5 to 3.0 VND million. In addition
to family allowance, some students had a part-
time job, so their income could reach over 3
VND million.
Standards applied for the EFA in this study
are as follows: (1) If the value of KMO is
higher than 0.5, the EFA will be appropriate;
(2) All variable with communalities less than
0.50 do not have sufficient explanation; (3) The
numbers of factors are determined based on the
eigenvalue index. The factors with eigenvalue
less than 1 will be excluded from the research
model; (4) Total variance explained must be
greater than 50%; (5) In a sample size of 120,
a factor loading of 0.50 is requested for
significance (Hair et al., 1995).
Based on VNUA’s secondary data of April
2020, the percentage of the first-year students
was quite similar to that of the second-, third- and
fourth-year students (e.g., from 20.1 to 28.7%).
The number of over fourth-year students
accounted for only 6.5% of the total population.
As compared to the population’s characteristics,
the ratio of the first-year students in the sample
was much lower. Regarding gender, the ratio of
surveyed male students was also lower than that
of the population (e.g., 28% as compared to
45%). This can be explained by the fact that the
study employed convenience sampling, thus the
representative of the sample was affected.
The EFA was used to reveal the number
of factors and variables that belong to specific
factors as follows:
Fi = wi1X1 + wi2X2 + … + wikXk
Where, Fi is the factor estimation
wik is the weight or factor score
coefficients
k is the number of variables
(iv) Multivariate regression analysis
The study used regression analysis to
estimate the influences of different factors on
students’ green purchase intention. The
regression equation has the following form:
Factors affecting students’ green purchase
intention
Testing the reliability of scales and observed
variables in the model
Y = b0 + b1F1 + … + bnFn+ u
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Factors influencing green purchase intention of students: A case study at Vietnam National University of Agriculture
Table 3. The descriptive statistics of the sample
Item
Quantity (persons)
Percentage (%)
1. Gender
Female
87
34
71.9
28.1
Male
2. Student year
1st year
7
5.8
21.5
37.2
28.9
6.6
2nd year
3rd year
26
45
35
8
4th year
Over 4 th year
3. Average income (million VND per month)
< 1.5
16
31
21
25
28
13.2
25.6
17.4
20.7
23.1
1.5 – 2.0
2.0 – 2.5
2.5 - 3.0
Over 3.0
Source: FAOSTAT (2018) and our calculations.
Reliability statistics was obtained by
analyzing the collected data using SPSS
software. The results showed that the factor of
PBC had a Cronbach’s alpha of 0.546 and the
corrected item-total correlation coefficient of
PBC1 was only 0.14. Therefore, PBC1 was
deleted from the model. After that, the reliability
test of PBC was performed again. The
Cronbach’s Alpha coefficients of 7 factors are
shown in Table 4. All of the Alpha coefficients
were greater than 0.6 and the total correlation
coefficients of observed items were all greater
than 0.3 (the lowest value was 0.334 for AV1).
Thus, it can be concluded that the scales for all
measured factors were reliable and appropriate,
and then continued to be used in factor analysis.
eigenvalue of 1.161. However, the item of SI1 had a
communality of 0.458 (lower than the acceptable
level of 0.50). After that, the EFA continued to be
implemented with the remaining items. SN2 had the
same problem as SI1 (its communality was 0.498),
so it was removed. Finally, the EFA results are
shown as follows: The value for KMO was 0.877,
the Bartlett's Test had a significant value at below
0.001; all of the remaining items with
communalities were greater than 0.50; the factors
were extracted at eigenvalue of1.117 and the sum of
extracted variance was 67.06%; the individual
factor loadings were more than 0.50. Therefore,
factor analysis could be conducted successfully
for data reduction. The rotated factor matrix
validated the underlying dimensions of
independent variables into 4 major dimensions
(Table 5). Two items of SN, namely SN1
(Environmental issues are very important to me)
and SN3 (I think green products are consistent
with the trend of social development), were
grouped into the same dimension as EC. Then,
the four significant factors were named social
influence and product knowledge (10 items),
Exploratory factor analysis
The factor extraction method used in this
study is the Principal component with Varimax
rotation to extract the smallest number of factors.
Regarding the independent variables, the
first EFA result indicated that 6initial factors were
grouped into four factors, which were extracted at
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Chu Thi Kim Loan (2020)
Table 4. Cronbach’s Alpha coefficients of the factors
Factors
Cronbach’s alpha (α)
Number of items
Environmental concerns (EC)
Availability of green products (AV)
Perceived behavior control (PBC)
Subjective norms (SN)
0.902
0.629
0.772
0.838
0.816
0.805
0.946
5
3
2
4
5
4
4
Social influence (SI)
Product knowledge (PK)
Green purchase intention (GPI)
Table 5. Rotated component matrix of the independent variables
Component
New names of the factors
Item
1
2
3
4
SI5
SI2
0.788
0.781
0.750
0.748
0.726
0.700
0.671
0.619
0.560
0.541
PK4
PK1
PK3
SI3
Social influence and product
knowledge (F1)
PK2
SI4
AV1
SN4
EC3
EC5
EC1
EC2
EC4
SN3
SN1
AV2
AV3
PBC3
PBC2
0.876
0.833
0.807
0.777
0.749
0.633
0.561
Environmental concerns and
subjective norms (F2)
0.888
0.648
Product availability (F3)
0.860
0.753
Perceived behavior control (F4)
environmental concerns and subjective norms (7
items), product availability (2 items), and
perceived behavior norms (2 items). Four of
these factors were hypothesized to have a
739
Factors influencing green purchase intention of students: A case study at Vietnam National University of Agriculture
positive and significant impact on green purchase
intention of the students.
environment. The average scores of these items
ranged from 3.9 to 4.45 (Table 7). Notably,
about 71% of the survey students strongly agreed
with EC3 (Environmental pollution can only be
eliminated when we work together). Regarding
the component score coefficient, the factor F2
was affected the most by variables of EC3 and
EC5.
With regard to the dependent variable, the
EFA showed that the KMO was 0.85, the
Bartlett's test was significant (Chi-square =
466.78, P< 0.001). Four items converged into
one dimension with the extracted variance total
of 86.09%, which then was still named green
purchase intention (GPI).
(iii) Product availability and perceived
behavior control (F3 and F4)
Students’ evaluation of factors affecting
The average scores of the items in the factor
of product availability were around 3.1 on the
five-point Likert scale (undecided). This implies
that the students did not find it so easy to gain
access to green products. Only one-third of the
sample agreed and strongly agreed with the
statement of AV2 (I know where green products
are sold). Between the two items, AV2 had a
higher effect on the F3 when its component score
coefficient was 0.589 (Table 8). If this indicator
is improved by 1 score, the factor F3 will increase
by 0.589 score (the other variables are supposed
to be constant).
green purchase intention
In this section, descriptive statistics was
firstly used to explore the respondents’
evaluation of the items of each factor.
Furthermore, component score coefficients (wi)
of a factor were also calculated to determine the
weights of the items. These coefficients were
extracted from a component score coefficient
matrix of the EFA process.
(i) Social influence and product knowledge
(F1)
Table 6 shows that the students evaluated
six components of the factor F1 at the neutral
level (undecided) when their average scores
ranged from 2.89 to 3.40. Notably, about 37.2%
of the surveyed students strongly disagreed and
disagreed with the statement of PK1 (I am
familiar with green products). Four remaining
items were at the agreed level. These indicate that
the students’ green product knowledge was only
moderate and the social influence on their green
purchase was not so strong. The highest average
point was devoted to SI4, while PK1 and SI2 had
the lowest mean. As regards the component score
coefficients (wi), PK1 had the largest influence on
the F1, followed by SI5 and PK4. If the students’
evaluation towards PK1 is increased by 1 score,
the factor F1 will be enhanced by 0.194 score (the
other variables are supposed to be constant). This
implies that if the F1 has a positive effect on green
purchase intention, we should firstly pay
attention to those items to improve the students’
readiness to perform green buying.
Both of the indicators of the factor F4
(perceived behavior control) were evaluated at
the agreed level. As compared to employees or
workers, students tend to have more free time, so
PBC3 (I have time to search and consider buying
green products) was highly evaluated. Between
these items, PBC3 had a higher coefficient, so it
would have a larger impact on F4.
Quantifying the effects of factors affecting
students’ green purchase intention
Multiple regression analysis was then used
to analyze the factors (Fi) affecting the students’
green purchase intention (GPI). The multiple
regression model employed in the study is as
follows:
GPI = b0 + b1F1 + b2F2 + b3 F3 + b4 F4 + u
Based on the results of the FEA, the values
of the factors were calculated and saved in the
form of standardized data. Therefore, both
independent and dependent variables in the study
were standardized ones, and then the
standardized regression coefficients (beta) were
used to analyze the relationship between them.
(ii) Environmental concerns and subjective
norms (F2)
The survey result indicates that VNUA’s
students were highly concerned about the
Vietnam Journal of Agricultural Sciences
740
Chu Thi Kim Loan (2020)
Table 6. The students’ evaluation of the factor of F1
Item
Mean
Std. Deviation
Component score coefficient (w)
PK1
PK2
PK3
PK4
SI2
2.89
3.40
3.51
3.05
2.98
3.45
3.75
3.33
3.18
3.52
1.153
1.085
1.026
1.094
1.016
1.118
1.019
1.143
1.232
1.246
0.194
0.152
0.147
0.187
0.177
0.140
0.101
0.192
0.099
0.077
SI3
SI4
SI5
AV1
SN4
Note: F1 = 0.194 PK1 + 0.152 PK2 + 0.147 PK3 + 0.187 PK4 + 0.177 SI2 + 0.14 SI3 + 0.101 SI4 + 0.192 SI5 + 0.099 AV1 + 0.077 SN4
Table 7. The students’ evaluation of the factor of F2
Item
EC1
EC2
EC3
EC4
EC5
SN1
SN3
Mean
4.19
4.28
4.45
3.94
4.22
3.93
4.20
Std. Deviation
1.171
Component score coefficient (w)
0.218
0.194
0.271
0.216
0.253
0.072
0.132
1.018
1.000
1.157
1.037
1.153
1.046
Note: F2 = 0.218EC1 + 0.194EC2 + 0.271EC3 + 0.216EC4 + 0.253EC5 + 0.072SN1 + 0.132SN3
After an application of OLS estimation, the
predictive equation would be written as follows:
significant impacts on the students’ green purchase
intention (i. e. the hypotheses stated for F1 and F2
were supported). In addition, the signs of the
independent variables were in the hypothesized
direction. This implies that we can improve these
factors to increase the students’ green purchase
intention. Among the variables included in the
model, F2 (Environmental concerns and
subjective norms) had the largest effect on the
students’ green purchase intention (beta = 0.552).
The F3 (product availability) and F4 (perceived
behavior control) variables were found to not
significantly affect green purchase intention.
Therefore, the hypotheses for F3 and F4 were
rejected, although their signs were satisfied.
GPI = 0.486 F1 + 0.552 F2 + 0.0250 F3 +
0.013 F4
t
(7.736) (8.777) (0.405) (0.207)
Adjusted R2 was 0.526, which indicated that
the overall regression equation explained 52.6%
of the total variance, and the result was
statistically significant at the 0.000 level {F(4,116)
= 34.275, P< 0.001}. Two estimated coefficients
of F1 (social influence and product knowledge)
and F2 (environmental concerns and subjective
norms) were statistically significant at the 99%
confidence level. Therefore, these variables had
741
Factors influencing green purchase intention of students: A case study at Vietnam National University of Agriculture
Table 8. The students’ evaluation of the factors of F3 and F4
Item
Mean
Std. Deviation Component score coefficient (w)
The factor of product availability (F3)
AV2
AV3
3.05
3.12
1.132
1.229
0.589
0.366
The factor of perceived behavior control (F4)
PBC2
3.69
3.46
1.017
1.049
0.478
0.600
PBC3
Note: F3 = 0.589 AV2 + 0.366 AV3
F4 = 0.478 PBC2 + 0.6 PBC3
Envỉonmental concern is established as an
important predictor of the consumers’ attitude
towards green products in almost all the studies.
Laroche et al. (2001) pointed out that consumers
with higher levels of environmental concerns
would be more likely to exert environmentally
friendly consumption. Environmental concerns
were found to motivate the purchase of organic
food products by Padel & Foster (2005). The
results of this study are consistent with those of
Smith & Paladino (2010), and Khai & Anh
(2016), who identified environmental concern
and subjective norm as major drivers towards the
purchase of green products. The findings also
agree with the result by Puspitasari et al. (2018)
and Lee (2008) that environmental concern and
social influence had significant influences on
green purchase intention. The result suggests that
interpersonal communication and mass media
vehicles are effective tools for affecting students’
green purchasing intentions.
affected perceived consumer effectiveness as
well as green trust that further affected green
purchase intention (Wang et al., 2019). Those
roles of PK, however, were not tested in this
research.
Some authors such as Wang et al. (2014) and
Chen & Deng (2016) found that perceived
behavioral control had a significant and positive
impact on purchase intention of green products.
However, a study by Arvola et al. (2008)
reported that perceived behavioral control and
consumer green purchase intention were not
related. While reviewing articles related to
attitude-behavior inconsistencies, in the context
of green purchasing, Joshi & Rahman (2015)
concluded, “it can be said although there is some
evidence that perceived behavioral control
positively influences green purchase behavior,
yet further empirical investigation is warranted
due to the limited research in the area”.
Regarding product availability, most studies
showed that limited availability and difficulties
in accessing green products were major barriers
to purchasing environmentally sustainable
products (Joshi & Rahman, 2015). For example,
the availability of organic food was found to have
a positive relation with green purchase intention
in two studies performed by Tarkiainen &
Sundqvist (2005) and Vermeir & Verbeke
(2008). Although the finding of this study
contrasts with the above studies, it is consistent
with the research conducted by Hoang Trong
Hung et al. (2018). Their hypotheses that product
availability, subjective norms, and perceived
behavior control had positive effects on
Green product knowledge plays a key role in
consumers’ decision to purchase green products
and is often considered as a direct prerequisite
variable for green purchase intention (Wang et
al., 2019). The result of this study supported the
previous studies when showing a significant
positive relationship between green product
knowledge and green purchase intention.
However, besides acting as a predictor, several
researchers have also confirmed its moderating
roles between green purchase attitudes and
behaviors, etc. (e.g., Chen & Deng, 2016). It was
also found to have an indirect influence on
consumers’ green purchase intention as it
Vietnam Journal of Agricultural Sciences
742
Chu Thi Kim Loan (2020)
consumer GPI, were also rejected because of low
significant levels. This fact may be because of the
students’ unique characteristics. They usually
have more free time than other consumers and
enjoy exploring surrounding places, while their
incomes are not so high.
information about green products and advocating
the green lifestyle. Specifically, the government
should pay more attention to deliver information
on green products by suitable tools (i.e.,
YouTube, social networks, training courses, and
contests related to environmental protection).
Universities should form green consumption
norms, such as buying green office supplies and
printing theses and documents in double sided
papers to save natural resources, etc. In addition,
lecturers should provide students with more
green knowledge through lectures and
extracurricular activities.
Conclusions and Implications
The survey indicates that the students’ green
product knowledge was only moderate. The
social influence on the students’ green purchase
was not so strong, especially their relatives’
effect. It is a good sign to find that VNUA
students were highly concerned about the
environment. The students’ evaluation of the
availability of green products was also at a
moderate level.
Making green products more accessibles to
students. Vietnamese students generally have
low incomes, so the higher prices of green
products are one of the main obstacles to their
green buying behavior. Therefore, companies
should develop new green products at reasonable
prices. Furthermore, the development of a wide
distribution network for green products is also
needed so that consumers, in general, and
students, in particular, can purchase them more
easily.
Based on the component score coefficients,
PK1 had the largest effect on the F1 (social
influence and product knowledge), while the
factor F2 (environmental concerns and subjective
norms) was affected the most by variables of EC3
(Environmental pollution can only be eliminated
when we work together) and EC5 (Humans must
live in harmony with nature in order to survive).
Between the two items included in the factor F3,
AV2 had a higher effect. Similarly, PBC3 (I have
time to search and consider buying green
products) had a larger impact on F4 (Perceived
behavior control). The results imply that
managers should firstly pay attention to those
items to improve the students’ evaluation of the
factors, and then stimulate their green buying
intention.
Enhancing the roles of social groups. Most
of the students could decide their buying choices.
However, those decisions are still affected by
past experiences, families’ tradition, and friends’
behavior, etc. Thus, the government should do
more campaigns to convince consumers that
purchasing green products would make a
difference in protecting the environment from
further deterioration. When buying green
products becomes a social trend, the students’
green purchase would be positively influenced.
On the other hand, companies should emphasize
using authority certification of green products
and designing labels carefully to create the
consumers’ confidence.
The regression analysis shows that students’
green buying intention is affected significantly
and positively by two variable groups, namely
the F1 (social influence and product knowledge)
and the F2 (environmental concerns and
subjective norms); in which, the variable of
environmental concerns and subjective norms
had the biggest influence on their green buying
intention.
References
Ajzen I. (1988). Attitudes, personality, and behavior.
Chicago: Dorsey Press.
Ajzen I. (2002). Constructing a TPB Questionnaire:
Conceptual and Methodological Considerations.
Working Paper. University of Massachusetts,
Amherst.
Based on the above findings, this paper
makes the following recommendations to the
government, companies, and universities:
Taking efforts to enhance students’ green
purchase intention by offering positive
Arvola A., Vassallo M., Dean M., Lampila P., Saba A.,
Lähteenmäki L. & Shepherd R. (2008). Predicting
743
Factors influencing green purchase intention of students: A case study at Vietnam National University of Agriculture
intentions to purchase organic food: The role of
affective and moral attitudes in the Theory of Planned
Behaviour. Appetite. 50(2): 443-454.
University’s Journal of Economics and Business.
32(1): 66-72 (in Vietnamese)
Hoang Trong Hung, Huynh Thi Thu Quyen & Huynh Thi
Nhi. (2018). Factors affecting consumers’ green
purchase behaviour in Hue city. Hue University’s
Journal of Economics and Development. 127(5A):
199-212 (in Vietnamese).
Barrutia J. M. & Gilsanz A. (2013). Electronic service
quality and value: Do consumer knowledge related
resources matter? Journal of Service Research. 16:
231-246.
Izquierdo I., Olea J. & Abad F. J. (2014). Exploratory factor
analysis in validation studies: Uses and
recommendations Psicothema. 26(3): 395-400.
Bray J., Johns N. & Kilburn D. (2011). An exploratory
study into the factors impeding ethical consumption.
Journal of Business Ethics. 98(4): 597-608.
Jewell J. D., Brown D. L., Thompson R., & Smith G.
(2010). Examining the influence of caregiver ethnicity
on youth placed out of the home: Ethnicity matters for
some. Children and Youth Services Review. 32: 1278-
1284.
Chen K. & Deng T. (2016). Research on the Green
Purchase Intentions from the Perspective of Product
Knowledge. Journal of Sustainability. Retrieved from
www.mdpi.com/journal/sustainability on 15th May,
2020.
Joshi Y. & Rahman Z. (2015). Factors Affecting Green
Purchase Behaviour and Future Research Directions.
International strategic management review. 3: 128-
143.
Chen T. B. & Chai L. T. (2010). Attitude towards the
Environment
and Green Products:
Consumers
Perspective. Management and Science Engineering.
4(2): 27-39.
Kang J., Liu C. & Kim S. H. (2013). Environmentally
sustainable textile and apparel consumption: the role
of consumer knowledge, perceived consumer
effectiveness and perceived personal relevance.
International Journal of Consumer Studies. 37(4): 442-
452.
Dalton J. (2019). Whale that starved to death had record
40kg of plastic waste in its stomach, Retrieved from
FABM (Faculty of Accounting and Business Management)
Kim Y. & Choi S. M. (2005). Antecedents of green
purchase behavior: An examination of collectivism,
environmental concern, and PCE. Advances in
Consumer Research. 32: 592-599.
(2020).
A
report of undergraduate students’
scholaships in the academic year of 2019-2020,
collected at the FABM office (in Vietnamese).
Finisterrado P. A. M. & Raposo M. L. B. (2004).
Determining the characteristics to profile the green
consumer: an exploratory approach. International
Review on Public and Nonprofit Marketing. 121-140.
Kirmani M. D. & Khan M. N (2016). Green Consumerism:
A Review of Extant Literature. Pacific Business
Review
International.
1(2).
DOI:
Gleim M., Smith J. S., Andrews D. & Cronin J. Jr. (2013).
Against the Green: A Multi-method Examination of
the Barriers to Green Consumption. Journal of
Retailing. 89(1): 44-61.
Laroche M., Begeron J. & Barbaro-Forleo G. (2001).
Targeting consumers who are willing to pay more for
environmentally friendly products. Journal of
Consumer Marketing. 18: 503-520.
Grunert S. C. (1993). Everybody seems concerned about
the environment but is this concern reflected in
(Danish) consumers’ food choice? European Advances
in Consumer Research. 1: 428-433.
Lee K. (2008). Opportunity for green marketing: young
consumers. Marketing Intelligence and Planning.
26(6): 573-586.
Mainieri T., Barnett E. G., Unipan T. R. & Oskamp S.
(1997). Green Buying: The Influence of
Environmental Concern on Consumer Behavior.
Journal of Social Psychology. 137(2): 189-204.
Gupta S. & Ogden D. T. (2009). To buy or not to buy? A
social dilemma perspective on green buying. Journal
of Consumer Marketing. 26(6): 376-391
Hair J. F, Anderson R. E., Tatham R. L. & Black W. C.
(1995). Multivariate Data Analysis with Reading (4th
ed.). Prentice Hall International, Inc.
Martinsons M.G., So S. K. K., Tin C. & Wong D. (1997),
“Hong Kong and China: emerging markets for
environmental products and technologies. Long Range
Planning. 30(2): 277-290.
Hair J. F., Black W. C. & Babin B. J. (2010). Multivariate
data analysis: A global perspective. Pearson Prentice
Hall, New Jersey.
Nguyen The Khai & Nguyen Thi Lan Anh. (2016). A study
on customers’ green purchase intention in Ho Chi
Minh city. Ho Chi Minh city Open University’s
Journal of Science. 2 (47): 42-53 (in Vietnamese).
Hessami H. Z. & Yousefi P. (2013). Investigation of major
factors influencing green purchasing behavior:
Interactive approach. European Online Journal of
Natural and Social Sciences. 2(4): 584-596.
Ottman J. A., Stafford E. R. and Hartman C. L. (2006).
Avoiding green marketing myopia: ways to improve
consumer appeal for environmentally preferable
products. Environment. 48(5): 22-36.
Hoang Thi Bao Thoa (2016). Green Consumption in the
World and Implications for Vietnam. VNU
Vietnam Journal of Agricultural Sciences
744
Chu Thi Kim Loan (2020)
Tai S. H. C. & Tam J. L. M. (1997). A lifestyle analysis of
female consumers in Greater China. Psychology and
Marketing. 14(3): 287-307.
Padel S. & Foster C. (2005). Exploring the gap between
attitudes and behavior: Understanding why consumers
buy or do not buy organic food. British Food Journal.
107(8): 606-625.
Smith S. & Paladino A. (2010). Eating clean and green?
Investigating consumer motivations towards the
purchase of organic food. Australasian Marketing
Journal. 18(2): 93-104.
Paul J., Modi A. & Patel J. (2016). Predicting green product
consumption using theory of planned behavior and
reasoned action. Journal of Retailing and Consumer
Services, 29,123–134.
Tarkiainen A. & Sundqvist S. (2005). Subjective norms,
attitudes and intentions of finnish consumers in buying
organic food. British Food Journal. 107(11): 808-822.
Peterson R. A. (1994). A meta-analysis of Cronbach’s
coefficient alpha. Journal of consumer research. 21:3
81-391
Vermeir I. & Verbeke W. (2008). Sustainable food
consumption among young adults in Belgium: Theory
of planned behaviour and the role of confidence and
values. Ecological Economics. 64(3): 542-553.
Puspitasari N. B., Rinawati D. I., Suliantoro H. & Sutrisno
B. D. (2018). The effect of green purchase intention
factors on the environmental friendly detergent
product. E3S Web of Conference 73, 06007.
VNUA website (2020). General Introduction. Retrieved
on November 24, 2020.
Reitman V. (1992). Green Products Sales Seem to Be
Wilting. The Wall Street Journal. May 18, B1.
Wang H, Ma B. & Bai R. (2019). How Does Green Product
Knowledge Effectively Promote Green Purchase
Shamdasani P., Chon-Lin G. & Richmond D. (1993).
Exploring green consumers in an oriental culture: Role
of personal and marketing mix. Advances in Consumer
Research. 20: 488-493.
Intention?
Sustainability.
11(4):
1193.
DOI:10.3390/su11041193.
Wang P., Liu Q. & Qi Y. (2014). Factors influencing
sustainable consumption behaviors: a survey of the
rural residents in China. Journal of Cleaner Production.
63: 152-165.
Sharma Y. (2011). Changing consumer behavior with
respect to green. International Journal of
Multidisciplinary Research. 1(4): 152-162.
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