Áp dụng phương pháp phân tích nhân tố khám phá trong nghiên cứu các yếu tố ảnh hưởng đến hành vi mua mỹ phẩm trực tuyến tại công ty TNHH Pizu
Economic & Policies
FACTORS INFLUENCE THE CONSUMER’S ONLINE SHOPPING
BEHAVIOR ON COSMETIC AT PIZU LTD COMPANY
Nguyen Thuy Dung1, Nguyen Thi Thu Nga1
1Vietnam National University of Forestry
SUMMARY
The purpose of this research is to investigate into what factors influence the consumer’s online shopping
behavior on cosmetic. Nowaday, cosmestic are becoming more and more popular with so many brands, products
in the markets, there has been a fierce competition among different cosmetic producers. Consumers have so
many choices from luxury to common brands. Thanks to the growing convenience of e-commerce, consumers
are now spared from store visiting and offline transaction... This study has been conducted based on the
structured survey of 280 customers of Pizu Ltd Company, a 5 year-old cosmetic e-commerce business. The
study results reveal that there are six factors that influence consumer’s behavior including: (1) Product; (2)
Convenience; (3) Delivery; (4) Service and infrastructure; (5) Consumer attitude; (6) Shopping attitude, while
financial and return policies are not clearly linked to consumer’s behavior. The six factors provide a useful
initial framework for Pizu company to assess its current strategy and tactics. The research also suggests several
approaches which Pizu company can undertake to better influence consumer’s behavior, thus, increasing its
own online shopping revenue. These approaches includes increasing the quality of products, provide more
product’s visuals and information on the website. Increasing the quality of service and infrastructure; quality
of product; design website display more sightly, create photos and informations about product more abundantly.
Keywords: Buying behavior, consumer, cosmetics, EFA, Pizu.
1. INTRODUCTION
more to find out trend and customer’s demand,
bring pleasure to customer and make the
business effectively.
Nowadays, the internet and technology
information has increasingly developed. E-
commerce became individual and bussiness’s
optimal choice to expand business, open wide
the their relationships, increase the their market
share, helping them seeking partner in and
outland (Al-Jabary, M.A et al., 2012).
In recent years, online shopping has become
the popular method and developed rapidly in
the world (Wu, L. et al., 2011). Its popularity
shows in in the amount of the rate of consumer
using this method and the revenue of retail
online shopping are constanly increasing
(Ozen, H., & Engizek, N., 2014).
Catching that trend, Pizu Ltd Company was
established and running business in e-
commercce as a buying and selling on social
network. By applying online selling the
company achieved success in market share,
establishing the brand and gain reputation.
However, the company is not yet
established. Finding and meeting customers’
need still play a crucial role in developing the
business so that attracting customer needs is
difficult. Therefore, the company need to do
Research on online consumber’s behavior
might reveal the factors affecting consumber
behaviors, which might shed light to hidden
problems and propose suitable solutions to
complete customer services and imply
customer support service. Hence, attractting
customer in and outland would be more
effective.
2. RESEARCH METHODOLOGY
2.1. Content of research
- Establish a framework to evaluate the
factors influence the online buying behavior on
cosmestic at Pizu Ltd Company;
- Determine the main factors that influence
the online buying behavior on cosmetic at Pizu
Ltd Company;
- Propose solutions to tackle consumer
behavior and increase e-commerce revenue of
Pizu Ltd Company.
2.2. Research methodology
2.2.1. Literature review
To identify the factors influence the
consumer’s online buying behavior, the authors
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based on some theories and studies, one of
them is the Theory of Planned Behavior (Ajzen,
1991). In his study, Ajzen proposed several
factors including consumers’s attitude,
intention to buy, personality, perceived
Nguyen Thi Bao Chau, Le Nguyen Xuan
Dao (2014), Analyzined the factors which
influence consumer’s online buying behavior at
Can Tho City. The result show that there are 8
catogories of factors including: risk in financial
and product, diversity of product, faith,
website’s responsiveness, risk in time,
convinience, comfortable and price which
influence consumer’s behavior.
Based on these studies, the authors propose
the research framework include 7 factors:
Convinience, Shopping attitude, Delivery,
Finance, Infrastructure, Return policy, Product,
Peer reviews, to identify which affect the
consumer’s behavior when buying cosmetic at
Pizu Ltd Company.
behavioral
adjustment,
technology
improvement, risk, service’s quality and
customers’s fearful.
Acording to Mohammad Hossein Moshref
Javadi (2012), the advantages of online buying
service are variaty of products, buying
comfortably, the website able to satisfy
customer’s needs, clear price and trustable.
Beside, the study also identify three catergories
of risk that could effect the customers’buying
decision include financial risk, product risk and
time risk.
Finance
Product
Convinience
Consumer’s online
buying behavior on
cosmetic
Delivery
Return Policy
Infrastructure
Shopping
Attitude
Figure 1. Conceptual model of the study
2.2.2. Data collection methods
per estimated parameter and there are 28
parameters need to estimated. So that the
sample size necessary is 280 observations in
total. In this study, 300 questionnaires were
sent to customers of Pizu Ltd Company. The
- Sample size: follow the guideline of Bollen
(1989) the minimum size of sample is 5
observations per estimated parameter, in this
research the size of sample is 10 observations
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number of returned questionnaires was 290.
Out of these, 280 answers were qualified
(Hoang Trong and Chu Nguyen Mong Ngoc,
2008).
- Sampling method: non probility sampling
technique was used to collect data involved
consumer buying behavior online (Dinh Phi
Ho, 2011). The respondents are customers who
have been bought or are recently using online
buying service of Pizu Ltd Company.
2.2.2. Data analysis method
Based on overview reseach, internal and
external research, the researcher imply and
complete the survey appropriately researching
relistic. In this research, paticipants had to
indicate their level of agreement with 28
evaluation statement divided to 8 group about
writing on a Likert scale with 5 levels (ranging
from strongly agree to strongly disagree) that
influence online buying behavior (Detail on
Table 1) (Ha Ngoc Thang and Nguyen Thanh
Do, 2016).
Table 1. Factor scales influence the consumer’s online buying behavior on cosmetic
at Pizu Company
No
1
Scale
Code
Finance
TC
I feel the detail of my credit card may be compromised and taken advantage of by
someone else
TC1
1.1
1.2 I could be charged higher when shopping online
1.3 I feel my private information could be leaked to the third partner
TC2
TC3
SP
Product
2
2.1 I may not receive the item that I offerd
2.2 I may receive the item out of date
2.3 I find it difficult to evaluate quality product on internet
SP1
SP2
SP3
TT
3
Convenience
I do not have enough patience to wait for the product to reach my hand in online
shopping
TT1
3.1
I can’t test the product by eyes, by hands or test the product directly
I find it difficult to resolve disputes when shopping online
Canceling an order online is not easy
I may have difficulty in returning purchased goods online
Delivery
TT2
TT3
TT4
TT5
PH
3.2
3.3
3.4
3.5
4
I may not receive the product I ordered online because of a fraudulent seller
I do not shop online because I do not trust carriers (they can change or spoil the
product that I order)
PH1
4.1
4.2
PH2
The product that I ordered may be lost during shipping
Return policy
PH3
HT
4.3
5
I do not shop online without a free return or exchange service
I shop online only when I can return the product without any cumbersome and
binding conditions.
HT1
5.1
5.2
HT2
I do not shop online without a commitment to return the money if the product is
not up to order
Services and Infrastructure
I feel no fear of buying cosmetics online if there is a strict electronic transaction
law to handle fraud and hackers.
5.3
6
HT3
CSHT
CSHT1
6.1
Site loading time is slow
CSHT2
CSHT3
6.2
6.3 The dangerous code (virus, trojan...) can harm my computer
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No
7
Scale
Code
Consumer attitude
TD
7.1 Use the Internet in buying cosmetics online easily
7.2 Buying cosmetics online is an enjoyable experience
7.3 I have been using the Internet as a buying channel
TD1
TD2
TD3
7.4 I like to go buy cosmetics directly with family members or friends in the store
7.5 The opinions of friends are extremely important when I intend to buy cosmetics
TD4
TD5
HV
8
Online cosmetic buying behavior
8.1 I will choose to buy cosmetics online when the occasion
8.2 I will buy cosmetics online whenever I intend to go shopping
8.3 I will buy cosmetics online instead of going to the store
HV1
HV2
HV3
In this research, IBM SPSS 20 statistical
software program was used to analyse
descriptive statistics, EFA was used to identify
the factors influencing online buying
consumer’s behavior of cosmetic at Pizu Ltd
company. The results of EFA are the basis to
propose solutions to enhance selling ability of
Pizu Ltd Company.
3.1. Current status of business result at Pizu
Ltd Company
The Company recently has over 300 agents
located in 63 provinces and cities inland, 1
agent abroad. Beside, the distribution system
also has thousands of wholesale buyers
resellers sell products online in social network
such as Facebook or Zalo.
3. RESULTS AND DISCUSSION
Table 2. Revenue of Pizu Ltd Company since 2017 to 2019
Average
Growth
Rate
No.
Revenue
2017
2018
2019
(%)
1 The North Vietnam
2 The Central Vietnam
3 The South Vietnam
4 Abroad Agent
Total
74 499.98
29 134.57
12 496.48
1 834.15
107 051.92
38 614.16
23 650.50
2 940.79
115 746.03
49 459.50
25 381.86
3 098.10
124.65
130.29
142.52
129.97
128.14
117 965.18
172 257.36
193.685.49
The revenue of the Company tends to
increase over the years, the average growth rate
is 128.14%. The revenue in Northern is highest,
and followed by the Central and the South.
The revenue is concentrated on big cities
and provinces such as Ha Noi, Ho Chi Minh
and Da Nang, which has large and dense
population, high demand, high purchase power
create favorable conditions to expand cosmetic
business.
in the undeveloped provinces, the provinces in
remote areas with average economic conditions
and underdeveloped so the demand is low and
it is difficult to sell for example: Cao Bang, Ben
Tre, Can Tho, Ha Tinh…
3.2. Results of EFA
3.2.1. Reliability
A reliability test was conducted to see if the
item in the questionare had been rightfully
operationalize
The company’s product are gradually
developing and expanding consumption
markets such as agents in the provinces of Bac
Ninh, Dong Nai, Hai Duong, Hai Phong, Hue
and Lam Dong.
Using the result of 280 observations,
Cronbach Alpha test reveals that all the 8
groups of variables are statistically significant,
the testatistic value is greater than the critical
value of 0.6. The result reported in Table 3.
The rest are agents with the lowest revenue
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Table 3. The significance of the variables
No
Scale
TC
SP
TT
PH
HT
CSHT
TĐ
Variable
TC1, TC2, TC3
SP1, SP2, SP3
TT1, TT2, TT3, TT4, TT5
PH1, PH2, PH3
HT1, HT2, HT3
CSHT1, CSHT2, CSHT3
TD1, TD2,TD3, TD4, TD5
HV1, HV2, HV3
Cronbach’s Alpha
0.806
1
2
3
4
5
6
7
8
0.779
0.874
0.894
0.797
0.821
0.682
0.784
HV
3.2.2. The evaluation on the survey result
3.2.2.1. Suitability of selection of EFA, using
Kaiser Meyer Olkin (KMO) method
The result of the model regression, using
KMO method is reported in Table 4. Table 4
reveals that KMO test statistic value = 0.719
which falls within the critical value range
(0.5<KMO<1); therefore the EFA method is
accepted in this case.
Table 4. The regression result of KMO test and Bartlett’s Test
KMO Measure of Sampling Adequacy
0.719
Approx. Chi-Square
3594.397
300
Bartlett’s Test of Sphericity
df
Sig.
.000
- Investigate the relationship among variables:
From Table 5, the column Cumulative %
that the variance value is 74.535%, which
indicates that 74.535% of the value of
dependent variables is explained by the
independent variables, therefore the EFA
method is accepted in this case.
From Table 4, the Barlett test statistic value
= 0.000 less than 0.05; therefore, the
independent variable have linear relationship
with the dependent variable.
3.2.2.2. Investigate the explanatory power of
variables
Table 5. Total Variance Explained
Extraction Sums of Squared
Loadings
Rotation Sums of Squared
Loadings
Initial Eigenvalues
Componet
% of
Cumulative
% of
Cumulative
% of
Cumulative
%
Total Variance
%
Total Variance
%
Tota Variance
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
4.358
3.471
3.196
2.091
1.770
1.494
1.165
1.089
.860
.628
.564
.528
.498
17.433
13.882
12.783
8.365
7.080
5.974
4.659
4.357
3.439
2.512
2.257
2.112
1.991
1.739
1.660
1.568
17.433
31.316
44.098
52.464
59.544
65.518
70.178
74.535
77.973
80.485
82.742
84.855
86.846
88.586
90.245
91.814
4.358
3.471
3.196
2.091
1.770
1.494
1.165
1.089
17.433
13.882
12.783
8.365
7.080
5.974
4.659
4.357
17.433
31.316
44.098
52.464
59.544
65.518
70.178
74.535
3.383
2.701
2.561
2.248
2.243
2.152
2.148
1.198
13.533
10.802
10.245
8.994
8.971
8.606
8.593
4.790
13.533
24.335
34.580
43.574
52.545
61.151
69.745
74.535
.435
.415
.392
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JOURNAL OF FORESTRY SCIENCE AND TECHNOLOGY NO. 9 (2020)
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Extraction Sums of Squared
Loadings
Rotation Sums of Squared
Loadings
Initial Eigenvalues
Componet
% of
Cumulative
% of
Cumulative
%
% of
Cumulative
%
Total Variance
%
Total Variance
Tota Variance
17
18
19
20
21
22
23
24
25
.343
.334
.261
.254
.238
.216
.178
.124
.099
1.372
1.334
1.042
1.015
.953
.862
.714
.498
.396 100.000
93.186
94.520
95.562
96.578
97.531
98.393
99.107
99.604
3.2.2.3.The regression results using EFA
framework
From the result of KMO method and
Cronbach Alpha test, there are 8 groups of
variable represent for main factors influence on
consumer’s online buying behavior of
cosmestic at Pizu Company.
Table 6. Adjusted Model after Cronbach Alpha test and EFA
No
Scale
1 F1
Variable
Scale’s explain
TT1, TT2, TT3, TT4, TT5
TD1, TD3, TD2
PH1, PH2, PH3
TC3, TC2, TC1
CSHT1, CSHT2, CSHT3
HT3, HT2, HT1
SP1, SP2, SP3
Convinience
Shopping attitude
Delivery
2 F2
3 F3
4 F4
5 F5
6 F6
7 F7
8 F8
Finance
Infrastructure
Return policy
Product
TD5
Friends’s oppinion
3.2.2.4. The regression equation
The regression was used as following:
HV = 0 + 1*F1 + 2*F2 + 3*F3 + 4*F4 +
5*F5 + 6*F6 + 7*F7 + 8*F8 + i
In which:
below 10 which indicates reliability. The
multicollinearity is not a problem in this study.
Durbin-Watson, a test of independence of
residuals should be close to 2 and that means
that there is independence of errors; which it is:
1.990. The column Sig. shows the significant
level of variable F1, F2, F3, F5, F7, F8 is less
than 0.05, which mean these variables are
statistically significant with 95% confidence
level. Whereas, variables F4, F6 have Sig.
higher than 0.05, which mean they are not
clearly related to online purchase intention.
Adjusted R square implies that the
independence variables from F1 to F8
explained 90.6% of the variation of the
dependence variable: consumer’s behavior.
Therefore the model is suitable.
i : is the random error;
0: a constant;
1: the slope of regression surface (the
represents the regression coefficient associated
with each independent variable.
Dependent variable: HV - Online cosmetic
buying behavior of consumers
Independent variables: F1, F2, F3, F4, F5, F6,
F7, F8
The model’s regression results using SPSS
software are summarized in Table 7.
Table 7 shows the VIF for each variable is
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Table 7. Model Summary
Standardized
Absolute
value of
Beta
Unstandardized
Coefficients
Percentage
(%)
Predictors
t-value
Sig.
VIF
Coefficients
(Beta)
Importance
Constant
F1
2.59E-16
0.039
0.134
0.176
-0.029
0.917
0.023
0.055
0.112
0
1.000
0.037
0.000
0.000
0.115
2.097
7.29
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
0.039
0.134
0.176
-0.029
0.917
0.023
0.055
0.112
0.039
0.134
0.176
0.029
0.917
0.023
0.055
0.112
1.485
2.63
9.02
11.85
1.95
61.75
1.55
3.70
7.54
100
6
3
2
7
1
8
5
4
F2
F3
9.573
-1.582
F4
F5
49.839 0.000
F6
1.268
2.986
6.114
0.206
0.003
0
F7
F8
Sum
Dependent Variable: HV
280
N
335.438
0.908
F
R-squared
0.906
Adjusted R-squared
Dubin- Watson
1.990
3.2.2.5. Discussion
reputation and brand imagine could be
enhanced
- Company should promote online selling
through popular social network such as:
Facebook, Zalo… Advertising and sale off
policy should be more abundent.
All six variables F1, F2, F3, F5, F7, F8 are
positvely related to HV, while two variables
F4, F6 are not clearly related to HV. In this
study, infrastructure contributes the most
(61.75%) to explain relationship with
consumer’s behavior, delivery comes second
(11.85%), consumer attitude comes third
(9.02%), peer review comes fourth (7.54%),
Product comes fifth (3.7%) and convenient
comes sixth (2.63%).
4. CONCLUSIONS
This study proposes and analyzes fators
influence the consumer’s online shopping
behavior on cosmetic at Pizu Ltd Company. 6
identified groups of factors are infrastructure,
delivery, customer attitude, peer preview,
product, convinience.
Based on that, the study propose four
solutions to improve Company selling ability:
- Improving infrastructure and quality of
services, security policy, loading speed;
- Improving quality of products;
3.3. Proposed solutions to enhance Pizu Ltd
Company’s selling ability
- The company should concentrate in service
quality, infrastructure to provide best quality
service for customer; especially increasing the
site loading speed as fast as possible. Establish
security protocols to avoid virus and malicious
code intrusion to private computer.
- Thus, the company should concentrate in
improving product quality, proving more
return policy when customer don’t pleasure
about product.
- Designing display website attractively and
easy to use;
- Providing more promotion activities to
stimulate buying behavior.
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- Update and provide products’s visuals and
information regularly. By doing so, company
could reinforce belief of customer, the
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ÁP DỤNG PHƯƠNG PHÁP PHÂN TÍCH NHÂN TỐ KHÁM PHÁ
TRONG NGHIÊN CỨU CÁC YẾU TỐ ẢNH HƯỞNG ĐẾN HÀNH VI
MUA MỸ PHẨM TRỰC TUYẾN TẠI CÔNG TY TNHH PIZU
Nguyễn Thùy Dung1, Nguyễn Thị Thu Nga1
1Trường Đại học Lâm nghiệp
TÓM TẮT
Trong nghiên cứu này, để xác định các yếu tố ảnh hưởng đến hành vi mua mỹ phẩm trực tuyến tại công ty trách
nhiệm hữu hạn Pizu Việt Nam, tác giả đã tiến hành khảo sát 280 khách hàng có hành vi mua hàng trực tuyến
tại công ty TNHH PiZu. Kết quả phân tích nhân tố khám phá (EFA) đã chỉ ra được 7 nhóm yếu tố ảnh hưởng
đến hành vi mua mỹ phẩm trực tuyến: (1) Tài chính; (2) Sản phẩm; (3) Sự thuận tiện; (4) Giao phát hàng; (5)
Chính sách hoàn trả; (6) Dịch vụ và cơ sở hạ tầng; (7) Thái độ mua sắm có ảnh hưởng đáng kể đến hành vi mua
mỹ phẩm trực tuyến tại công ty THHH Pizu. Kết quả nghiên cứu có thể làm cơ sở để đề xuất một số giải pháp
nhằm nâng cao khả năng mua mỹ phẩm trực tuyến của khách hàng tại công ty TNHH Pizu, bao gồm: nâng cao
chất lượng dịch vụ và cơ sở hạ tầng; Nâng cao chất lượng sản phẩm; Thiết kế website có giao diện đẹp mắt, đầu
tư về hình ảnh, thông tin chi tiết sản phẩm; giải pháp kích thích khả năng mua sắm của khách hàng.
Từ khóa: EFA, hành vi mua, mỹ phẩm, người tiêu dùng, Pizu.
Received
Revised
Accepted
: 09/9/2019
: 26/02/2020
: 24/3/2020
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