Factors influencing customer’s trust when purchasing on facebook social network

An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

FACTORS INFLUENCING CUSTOMER’S TRUST WHEN PURCHASING
ON FACEBOOK SOCIAL NETWORK
Tran Thi My Phuong1
An Giang University

1

Information:
Received: 10/06/2018
Accepted: 14/09/2018
Published: 02/2019
Keywords:
Trust, trust propensity,
testimonials, risk

ABSTRACT
Trust is the key element for the success of trading on Facebook, therefore,
finding the factors influencing trust of customers is necessary. The research
inherited four factors from the research model of Nor, Nazarie, and Yusoff
(2013): (1) Trust Propensity, (2) Testimonials, (3) Experience in Online
Purchasing, (4) Financial Perceived Risk and based on the interview, the
study developed two more factors: (5) Product Perceived Risk and (6) Time
Perceived Risk. After surveying 200 customers, the research shows that Trust
Propensity affects the most positively to Online Trust and Financial
Perceived Risk affects negatively to Online Trust. The study implicates to
help management build their customers’ trust as well as offers a particular
reality in an e-commerce research field.

1. INTRODUCTION

majority of Internet users are not confident to
make a purchasing decision on Facebook.
According to Gefen (2000), Harn, Khatibi and
Ismail (2006), lack of trust is a major barrier in an
online purchase. This can be explained that
Facebook users are unlimited and there has been
no legal organization regulating trading activity
on it. It is easy for a person to cheat customers out
of money on Facebook.

Purchasing online has been developing
dramatically in all corners of the world due to its
practical benefits such as help customers save
time, compare prices, access new products easily,
and save transportation cost as well as avoid
traffic congestion. Recently, a large number of
customers has moved to shop on social networks,
especially Facebook instead of buying on formal
websites such as Vatgia.com or Lazada.vn.
Facebook is considered as a public house of oneseventh of world’s population and one- third of
Vietnamese
population
(VNNIC,
2013).
Individuals and businesses, therefore, are taking
advantage of this medium to both sell products
and keep in touch with their friends (Ranganathan
& Ganapathy, 2002).

Nevertheless, most of the studies focused on the
traditional e-commerce and there are few types of
researches conducted to examine factors that
affect customer’s trust on Facebook. This study
aims to fill in this gap in order to help businesses
increase their customer’s trust by some particular
actions; besides, its results can reliably contribute
to research of e-commerce field in general.

In spite of many advantages mentioned above, the

2. LITERATURE REVIEW

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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

2.1 Trust and Online Trust

orders or write testimonials about some certain
products. However, everything has its two sides,
Facebook has some disadvantages for both sellers
and buyers.

Trust has been identified differently among
researchers. Koufaris and Hampton-Sosa (2004)
suggest that trust is the willingness to rely on a
third party after the first interaction with it.
Another study conducted by Coulter and Coulter

(2002) defined trust as a key factor to build longterm relationships between service representatives
and their customers.

2.3 Some typical researches
Customer’s Trust

on

Online

Many studies have been conducted to investigate
factors that influence customers’ trust in an online
purchase. One of recent research is by Nor,
Nazarie, and Yusoff (2013). They studied the
factors influencing individuals’ trust in an online
purchase through social network sites and the
results discovered that (1) Trust propensity, (2)
online purchasing experiences, (3) testimonials,
and (4) money risk affect customers’ trust in
online purchase. The authors surveyed 129
customers who come from Malaysia, China, by
sending emails and uploading the questionnaires
on their individual Facebook accounts. Especially,
the research used the method of multiple
regression analysis to test the relation of the
factors and discovered that testimonials have the
strongest effect on customer’s trust. In other
words, good comments and feedbacks which
come from old customers are advantageous for
attracting new customers and building stable

relations among existing customers.

In the Internet shopping platform, online trust is
also the willingness of a consumer to be
defenseless to the actions of an Internet business
and based on the hopes that he or she will be
treated agreeably, regardless of the ability of the
consumer to regulate or control the Internet
business (Lee & Turban, 2001). Meanwhile, Hui
and Kejin (2009) defined online trust as a process
including requirement, attitude, intention, and
purchase behavior.
From various definitions, trust shows an
important role in online shopping. Without trust,
customers are not confident enough to make
online purchasing decision and businesses can not
establish sustainable relationships with their
customers.
2.2 Social Networks (SNs)
SNs is the top of Internet applications which
allows users to create profiles and keep contact
with friends who are already registered on the site.
Some of the examples are MySpace, Facebook,
Friendster and Twitter. In Vietnam, Facebook has
about 9 million users (Comscore, 2012) and
becomes a phenomenon in the youngsters even
the elderly and the kids. One of the special
functions of Facebook is that users can upload
their photos and make their information visible to
their friends. This enables them to communicate

more effectively and make friends unlimitedly. In
terms of e-commerce, sellers find it easy to
describe the products and services, and convenient
to reply customer’s questions on Facebook, while
buyers think it easy to approach new products
from their favorite Facebook stores, easy to place

Moreover, Gefen (2000) also studied the role of
familiarity and trust in an e-commerce context. He
analyzed the relations of five factors: (1)
familiarity, (2) trust propensity, (3) trust, (4)
inquiring, and (5) purchasing. The results show
that both familiarity with an Internet vendor and
its processes as well as trust in the vendor
influenced purchasing intension Therefore, it is
necessary to concentrate on building trust by
increasing familiarity. Moreover, the study proved
that familiarity is primarily people's disposition to
trust that influenced their trust in the venders.
In addition, another important research was
conducted by Kim et al. (2007) on “A trust-based
consumer decision-making model in electronic
commerce: The role of trust, perceived risk,
and
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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

their antecedents”. This study focused on
developing a theoretical framework which

describes the trust-based decision-making process
that a consumer uses when purchasing on the
Internet and on examining the model which use
Structural Equation Modeling method. The study
results show that online trust and perceived risk
affect customer’s purchasing decisions strongly.

factors mentioned and repeated in most of the
researches are Trust Propensity, Online
Purchasing Experience, Testimonials, and
Perceived Risks. This inspires the author to
implement a study to survey the factors
influencing customer’s online trust when
purchasing on Facebook.

In Vietnam, the number of research on online trust
has been increasing. Tran Minh (2012) studied
“Factors affecting customer trust in online
shopping in Vietnam”. The author proposed a
research model including four factors affecting
trust in online shopping: (1) Privacy Perceptions,
(2) Security Protection, (3) Perceived Risks, and
(4) Perceived Benefits. The study used
convenience sampling and purposing sampling to
select 216 Vietnamese students and office
workers who used to shop online by electronic
payments. The results proved that Perceived Risks
and Privacy Perceptions have strong impacts on
online trust. This is explained that in a developing
country like Vietnam, customers are not familiar

with online shopping. Therefore, they tend to care
about risks rather than profits.

3.1 Research methodology

3. Research methodology and hypothesis
The study was implemented by combining
quantitive and qualitative research methodology.
After reviewing a wide range of national and
international papers and researches related to
online trust, the author conducted six focus
interviews with six customers who had purchased
on Facebook in order to compare the previous
results to the reality and to find out new factors.
An online questionnaire was prepared and
developed based on the previous results and focus
interviewed results. The study used convenience
sampling method which allows reaching the
responders who are available conveniently to
participate in the study and targeted Facebook
users who had purchased on Facebook. All of 38
dependent and independent variables were
measured by Likert 5 scales.

Furthermore, Nguyen Mai Trang and Nguyen
Ngoc Bich Tram (2014) studied about the factors
affecting actual use of Facebook in Vietnam by
examining six factors: (1) Social Identity, (2)
Altruism, (3) Telepresence, (4) Perceived ease of
use, (5) Perceived usefulness, and (6) Perceived

encouragement. There were 363 Facebook users
in Ha Noi, Da Nang, and Ho Chi Minh City
taking part in the survey. The results indicated
that Perceived ease of use, Perceived usefulness,
and Perceived encouragement influence directly
on the actual use of Facebook.

3.2 Research hypothesis
Trust propensity was mentioned in several types
of researches on e-commerce. According to
McKnight and Chervany (2002), trust propensity
or disposition to trust can be defined as “general
willingness based on extended socialization to
depend on others” and concluded that those who
have a strong belief in human’s good
characteristic may have a high level of trust
propensity. This finding leads to the first
hypothesis of the study:

In conclusion, the above research overview
indicates that in Vietnam most of the studies
concentrated on online purchasing intention or
Facebook-using behavior while many researchers
in the world have investigated online trust
popularly and profoundly in different sides. The

Hypothesis 1: Trust propensity influences
positively on customers’ trust when purchasing on
Facebook.
Testimonials play an important role in online

shopping. Testimonials are sentences spoken or
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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

written about some feelings of customers after
they experienced the products or services with a
hope that they can recommend or prevent other
customers from buying a particular product or
service. In social networks, customers can write
their testimonials publicly or send a message
privately (Dwyer, Hiltz & Passerini, 2007). That
is the reason why businesses on Facebook try to
gather more and more positive testimonials about
their product or service to enhance their
customers’ trust. Therefore, the second hypothesis
is suggested.

such as phone numbers, home address, e-mail
address, and debit or credit card numbers which
are attractive to financial frauds (March, 2006).
Therefore, the fourth hypothesis is proposed.
Hypothesis 4: Financial risk influences negatively
on customers’ trust when purchasing on
Facebook.
Product risk is another widespread issue that
every customer concerns before making a
purchasing decision. Product risk involves both
quality and quantity. In terms of quantity,

customers receive more or fewer items than they
order. In terms of quality, customers receive
products that are not matched to the ones they
order, namely they may be damaged or defective
and they may have different color or size. In
another word, product risk is the loss that
customers get when the provided products are not
matched to the ones that they expect (Horton,
1976). Therefore, the fifth hypothesis is proposed.

Hypothesis 2: Testimonials influence positively
on customers’ trust when purchasing on
Facebook.
Jiang, Chen and Wang (2008) researched on the
relation between knowledge, trust in online
purchasing and online buying intention of
customers. The results pointed out that knowledge
are related positively to trust in online purchasing.
In the words, those who have awareness of online
shopping tend to trust and be willing to shop
online because they can identify risk in online
transactions. The third hypothesis is given.

Hypothesis 5: Product risk influences negatively
on customers’ trust when purchasing on
Facebook.
Despite the convenience of online shopping, a
loss of time may occur in all stages such as
making inquiries, ordering products, paying the
bills, receiving products, even asking for refund.

Roselius (1971) confirmed in his research that
time loss was considered as an additional risk of
products and services. Therefore, the sixth
hypothesis is proposed.

Hypothesis 3: Experience in online purchasing
influences positively on customers’ trust when
purchasing on Facebook.
Purchasing online involves a wide range of
risks in which financial risk is the most
concerned. Most of the cases, the customers lose
their money by sending money in advance and do
not receive their ordered products or receive
dissatisfied ones. Moreover, the customers have to
disclose their personal information to the sellers

Hypothesis 6: Time risk influences negatively on
customers’ trust when purchasing on Facebook.

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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

Figure 1. Research Model

4. Research results
4.1 Scale descriptions

is a measure of internal consistency on the closely

level that the variables of the scale correlate with
each other in order to eliminate the inappropriate
variables. According to Nguyen Dinh Tho (2013),
a good reliability scale must have Cronbach’s
Alpha coefficient from 0,70 to 0,80. However, the
Cronbach’s Alpha coefficient of scale from 0,6
upward are accepted. Furthermore, the condition
to carry out Exploratory Factors Analysis (EFA)
is that the variables must have corrected item-total
correlation greater than 0,3 (Nunnally and
Burnstein, 1994).

The data was collected from 200 respondents who
have been purchasing on Facebook and 38% are
male. Most of them are from 22 to 35 years old.
The majority have been buying online for a year
(accounting for 39%), for more than one year
(accounting for 26,5%), and for a month
(accounting for 20,5%).
4.2 Cronbach’s Alpha analysis
The Cronbach’s Alpha coefficient is used to
evaluate the reliability of the scale. In addition, it

Table 1. Results of Cronbach’s Alpha Analysis

Variables

Trust Propensity

Items

Corrected Item-Total
Correlation

Cronbach's Alpha if
Item Deleted

prop1

0,595

0,832

prop2

0,693

0,806

prop3

0,745

0,791

prop4

0,644

0,818

prop5

0,603

0,830

=> Cronbach’s Alpha of the scale

Testimonials

0,847
test1

0,643

0,788

test2

0,532

0,819

test3

0,571

0,810

test4

0,734

0,762

test5

0,656

0,783

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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

Variables

Items

Corrected Item-Total
Correlation

=> Cronbach’s Alpha of the scale

Online Purchasing Experience

0,827
ex1

0,632

0,885

ex2

0,687

0,873

ex3

0,753

0,857

ex4

0,769

0,854

ex5

0,803

0,846

=> Cronbach’s Alpha of the scale

Financial Risks

0,888
Fin1

0,702

0,889

Fin2

0,699

0,890

Fin3

0,753

0,878

Fin4

0,811

0,865

Fin5

0,797

0,868

=> Cronbach’s Alpha of the scale

Product Risks

Cronbach's Alpha if
Item Deleted

0,900
Pro1

0,807

0,802

Pro2

0,263

0,922

Pro3

0,832

0,795

Pro4

0,769

0,813

Pro5

0,780

0,812

=> Cronbach’s Alpha of the scale

0,864
Pro1

0,844

0,891

Product Risks

Pro3

0,861

0,885

(After deleting Pro2)

Pro4

0,771

0,915

Pro5

0,808

0,903

=> Cronbach’s Alpha of the scale

Time Risks

0,922
Time1

0,739

0,890

Time2

0,745

0,890

Time3

0,784

0,886

Time4

0,787

0,887

Time5

0,734

0,891

Time6

0,753

0,889

Time7

0,781

0,886

Time8

0,286

0,926

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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

Variables

Corrected Item-Total
Correlation

Items

=> Cronbach’s Alpha of the scale

Time Risks
(After deleting Time8)

0,906
Time1

0,740

0,917

Time2

0,767

0,914

Time3

0,793

0,912

Time4

0,793

0,913

Time5

0,730

0,918

Time6

0,774

0,914

Time7

0,774

0,914

=> Cronbach’s Alpha of the scale

Trust

0,926
trust1

0,623

0,901

trust2

0,831

0,857

trust3

0,871

0,847

trust4

0,660

0,894

trust5

0,761

0,873

=> Cronbach’s Alpha of the scale

0,898

In the process of verifying reliability, Pro2 and
Time8 were deleted because they both have
Corrected Item-Total Correlation less than 0.3.
The remaining 36 variables have Cronbach’s
Alpha coefficient of the constituent larger than
0.7; this means that the variables have closely
connected each other in the same factor. The
observing variables in the same factors have itemtotal correlation greater than 0.3; therefore all of
them were put into Exploratory Factors Analysis
(EFA).
4.3 Exploratory
Factor
Independent Variables.

Cronbach's Alpha if

Item Deleted

Analysis

Risks, Online Purchasing Experience, Trust
Propensity, Testimonials. Among them, Test2,
which belongs to Testimonials, had loading
coefficient of less than 0.5 so it was removed
from the scale. Then, another EFA was conducted
in which
KMO test coefficient had a value
of 0.840 > 0.5 showing the suitability of the
analysis to the data (Nguyen Dinh Tho, 2013).
Bartlett's Test of Sphericity is 4006.98 with Sig. =
0.00 < 5%. This asserts that variables closely
connected each other (Nguyen Dinh Tho, 2013).
Cumulative Variance is 71.293 > 50%. In other
words, the first factor can explain 71.29% of the
variation of data (Gerbing and Anderson, 1988).
Moreover, Eigenvalue coefficient is greater than
one.

on

The analysis result shows that the independent
variables gather in groups and have loading
coefficients larger than 0.5. There are six factors
grouped: Time Risks, Financial Risks, Product

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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38
Table 2. Rotated Component Matrixa after deleting Test2

Component
1
time4

.849

time3

.847

time6

.827

time2

.824

time7

.823

time1

.817

time5

.786

2

fin4

.864

fin3

.857

fin5

.850

fin1

.791

fin2

.791

3

4

ex5

.845

ex4

.819

ex3

.803

ex2

.781

ex1

.739

pro1

.906

pro3

.901

pro5

.892

pro4

.841

5

prop3

.829

prop4

.780

prop2

.724

prop1

.656

33

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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

prop5

.642

test4

.832

test5

.757

test1

.729

test3

.595

Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
4.4 Exploratory
Factor
Dependent Variables.

Analysis

on

In conclusion, after conducting Exploratory
Factor Analysis, six independent variables and
one dependent variable remain as before.

KMO Measure of Sampling Adequacy is 0.833 >
0.5. This means that the test is essential. Bartlett's
Test of Sphericity is 653.509 with Sig. = 0.00<
5% (0.05) showing that the variables correlate
closely each other. Cumulative of Variance is
71,148 >50%.

4.5 Examining the reliability of the scale after
removing Test2
This step aims at re-examining to ensure the scale
is still reliable after removing Test2. Fortunately,
the result makes certain that Cronbach’s Alpha of
the scale get value 0.819 and reliabilities of all
items are larger than 0.5.

The matrix does not rotate because only one
dependent factor was extracted.

Table 3. Cronbach’s Alpha after Removing Test2

Variable

Testimonials

Items

Corrected Item-Total
Correlation

Cronbach's Alpha if Item
Deleted

test1

0,643

0,771

test3

0,546

0,823

test4

0,764

0,715

test5

0,631

0,776

=> Cronbach’s Alpha of the scale
4.6 The result of Pearson
Coefficient Analysis

0,819
Correlation

All of the Sig. values are smaller than 5%. This
means that the Pearson Correlation Coefficient
Analysis results are significant in statistics. The
table shows value from -0.310 to +1, that means
the variables are relevant to each other and can be
used in regression analysis.

After encoding the average value of dependent
and independent variables, the author analyzes the
Pearson correlation in order to find out the
variables that are relevant to each other and to
remove irrelevant or fewer relevant ones.

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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

Table 4. Correlation

TRUST

Pearson Correlation

TRUST

TIME

FIN

PROP

PRO

EX

TEST

1

-.250**

-.310**

.551**

-.254**

.512**

.475**

.000

.000

.000

.000

.000

.000

1

.100

-.249**

.184**

.088

.003

.160

.000

.009

.217

.966

1

-.240**

.227**

-.159*

-.096

.001

.001

.025

.177

1

-.086

.362**

.558**

.226

.000

.000

1

.083

.116

.244

.101

1

.489**

Sig. (2-tailed)
TIME

FIN

PROP

PRO

EX

TEST

Pearson Correlation

-.250**

Sig. (2-tailed)

.000

Pearson Correlation

-.310**

.100

Sig. (2-tailed)

.000

.160

Pearson Correlation

.551**

-.249**

-.240**

Sig. (2-tailed)

.000

.000

.001

Pearson Correlation

-.254**

.184**

.227**

-.086

Sig. (2-tailed)

.000

.009

.001

.226

Pearson Correlation

.512**

.088

-.159*

.362**

.083

Sig. (2-tailed)

.000

.217

.025

.000

.244

Pearson Correlation

.475**

.003

-.096

.558**

.116

.489**

Sig. (2-tailed)

.000

.966

.177

.000

.101

.000

.000
1

**. Correlation is significant at the 0.01 level (2-tailed)
*. Correlation is significant at the 0.05 level (2-tailed
N = 200

4.7 Regression analysis

51.8% of the variation of the dependent variable.
Sig. value of F test < 0.05 shows that the model is
statistically significant at significance level 5%. In
addition, VIF coefficients of all factors are < 2
implying that multi-collinearity does not influence
much on regression results.

Regression analysis was conducted between
TRUST and six independent variables (1) Trust
Propensity (PROP), (2) Testimonials (TEST), (3)
Online Purchasing Experience (EX), (4) Time
Risks (TIME), (5) Financial Risks (FIN), (6)
Product Risks (PRO).

All regression coefficients (β) are statistically
significant since Sig. β < 5%. There are three
regression coefficients taking negative sign
corresponding to risk factors that affect negatively
TRUST. All the six hypotheses were therefore
accepted.

The research’s linear regression equation is as
following:
TRUST =β0 + β1 * PROP + β2 * TEST + β3 * EX β4 ATIME- β5 FIN- β6 PRO
With R2 of 0.518 indicating that the independent
variables in the regression model can explain

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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

Table 5. Estimates of Coefficientsa
Unstandardized
Coefficients
B

Standardized
Coefficients

Std. Error

(Constant)

2.039

.280

TIME

-.122

.037

FIN

-.082

PROP

Beta

Collinearity
Statistics
t

Sig.

Tolerance

VIF

7.281

.000

-.172

-3.263

.001

.874

1.144

.038

-.113

-2.156

.032

.886

1.128

.229

.065

.227

3.512

.001

.582

1.718

PRO

-.161

.037

-.229

-4.393

.000

.892

1.121

EX

.280

.046

.352

6.069

.000

.722

1.385

TEST

.175

.059

.193

2.958

.003

.571

1.751

a. Dependent Variable: TRUST
5. RESEARCH IMPLICATIONS

can attract. For this reason, it is essential for those
who do business on Facebook to invest in
collecting valuable testimonials from their clients.
In addition to improving product’s quality, online
sellers need to spend time taking care of their
customers such as asking about how they feel
about the products if they have any suggestions
for increasing the product’s quality, or how to
serve them better. By talking to customers,
businesses can both keep track of their demand
and pick out valuable feedbacks to build online
customer’s testimonials corner which is the best
proof for a quality product.

Trust propensity influences positively and most

strongly on customer’s trust. People who have
high trust propensity feel easy to trust in
something they intend to buy. Therefore, online
shops are encouraged to observe meticulously in
order to know their groups of customers who have
a high trust propensity to their products or
services.
In addition, online purchasing experience affects
customers’ trust supportively when they shop on
Facebook. This result reminds online businesses
enabling customers to approach online shopping
process. For instance, shop owners can simplify
the purchasing steps, create more payment
channels, and arrange the easy-to-shop
appearance. Once customers do online
transactions several times, they will get some
certain experience and may become loyal
customers of the stores on Facebook.

The research result also proves that financial risks
influence negatively and the most sharply on
customer’s trust. Problems such as losing money,
losing bank account information, or being charged
exorbitantly mostly always disturb customers. To
avoid them, firstly, business managers need to
disclose different types of payment such as by
cash on delivery (COD), bank account, delivery
companies, electronic money, or charging mobile
phone cards. Each group of customers will be
suitable for each type of payment. Secondly,

opening various bank accounts enables customers

Testimonials include purchasers’ feedbacks,
comments, or suggestions about products or
services that they used. The better testimonials
online businesses have, the more customers they
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An Giang University Journal of Science – 2019, Vol. 6, 26 – 38

to choose the one they have, therefore, they do not
have to pay any fees for a different bank.
Furthermore, all of the charges related to products
should be listed down clearly to avoid
misunderstanding when paying. In the same way,
the products should be checked considerately so
that the customers do not have to pay another fee
to return or exchange products. Last but not least,
any information of customers must be secured
absolutely.

researches will overcome these limitations and
could focus on the differences between
customer’s trust in purchasing on Facebook and
other e-commerce websites.
REFERENCES
Comscore. (2012). Introduction of Online Video
Measurement Service in Taiwan, Vietnam,
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/>Releases/2012/8/comScore_Announc
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Service_in_Taiwan_Vietnam
_Indonesia_and_the_Philippines.

The second risk in online shopping is product risk
including defected products, wrong size, wrong
quantity, wrong color or products do not meet
enough characteristics and utilities as advertised.
Product risks reduce customers’ trust especially at
the first time they deal with an online shop. For
this reason, shops on Facebook need to be truthful
to advertise their products, not to blow up some
features or functions that their products cannot
fulfill. Likewise, salespeople need to give useful
advice and introduce the products in details to
customers before setting up an order.

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