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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.

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FACTORS INFLUENCING CUSTOMER’S TRUST WHEN PURCHASING

ON FACEBOOK SOCIAL NETWORK

Tran Thi My Phuong1

1 An Giang University

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

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

one-seventh 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)

In spite of many advantages mentioned above, the

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

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

2 LITERATURE REVIEW

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2.1 Trust and Online Trust

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

long-term relationships between service representatives

and their 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

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

2.3 Some typical researches on Online Customer’s Trust

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

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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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

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

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

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

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

3 Research methodology and hypothesis 3.1 Research methodology

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

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:

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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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

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 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

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

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Figure 1 Research Model

4 Research results

4.1 Scale descriptions

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

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)

Table 1 Results of Cronbach’s Alpha Analysis

Variables Items Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted

Trust Propensity

Testimonials

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Variables Items Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted

Online Purchasing Experience

Financial Risks

Product Risks

Product Risks

(After deleting Pro2)

Time Risks

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Variables Items Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted

Time Risks

(After deleting Time8)

Trust

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

item-total correlation greater than 0.3; therefore all of

them were put into Exploratory Factors Analysis

(EFA)

4.3 Exploratory Factor Analysis on

Independent Variables

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

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

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Table 2 Rotated Component Matrixa after deleting Test2

Component

time4 849

time3 847

time6 827

time2 824

time7 823

time1 817

time5 786

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4.4 Exploratory Factor Analysis on

Dependent Variables

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%

The matrix does not rotate because only one

dependent factor was extracted

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

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

Table 3 Cronbach’s Alpha after Removing Test2

Variable Items Corrected Item-Total Correlation Cronbach's Alpha if Item Deleted

Testimonials

4.6 The result of Pearson Correlation

Coefficient 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

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

Extraction Method: Principal Component Analysis

Rotation Method: Varimax with Kaiser Normalization

a Rotation converged in 6 iterations

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Table 4 Correlation

TRUST Pearson Correlation 1 -.250** -.310** 551** -.254** 512** 475**

TIME Pearson Correlation -.250** 1 100 -.249** 184** 088 003

FIN Pearson Correlation -.310** 100 1 -.240** 227** -.159* -.096

PROP Pearson Correlation 551** -.249** -.240** 1 -.086 362** 558**

PRO Pearson Correlation -.254** 184** 227** -.086 1 083 116

EX Pearson Correlation 512** 088 -.159* 362** 083 1 489**

TEST Pearson Correlation 475** 003 -.096 558** 116 489** 1

Sig (2-tailed) 000 966 177 000 101 000

** 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

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)

The research’s linear regression equation is as

following:

TRUST =β 0 + β 1 * PROP + β 2 * TEST + β 3 * EX -

β 4 ATIME- β 5 FIN- β 6 PRO

With R2 of 0.518 indicating that the independent

variables in the regression model can explain

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

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

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