Information Resources Management Journal
Volume 30 • Issue 2 • April-June 2017

The Impact of EWOM Referral, Celebrity
Endorsement, and Information
Quality on Purchase Decision:
A Case of Instagram

Randy Danniswara, University of Indonesia, Depok, Indonesia
Puspa Sandhyaduhita, University of Indonesia, Depok, Indonesia
Qorib Munajat, University of Indonesia, Depok, Indonesia

ABSTRACT
This study aims to explore factors that have impact on purchase decision on a social commerce, viz.,
social media Instagram. Thus, several dimensions namely eWOM referral, celebrity endorsement,
information quality, brand satisfaction, brand trust and brand attachment are identified and examined.
This research uses SEM method and LISREL 8.80 application. Data was collected using questionnaires
with Likert scale. The result from 350 respondents shows that a significant positive correlation
exists between eWOM referral and purchase intention, information quality and brand satisfaction,
information quality and brand trust, brand satisfaction and brand attachment, brand satisfaction and
purchase intention, brand trust and purchase intention, brand attachment and purchase decision, and
also between purchase intention and purchase decision.
Keywords
Brand Attachment, Brand Satisfaction, Brand Trust, eWOM Referral, Information Quality, Instagram, LISREL
8.80, Marketing, Purchase Decision, Purchase Intention, SEM, Social Commerce, Social Media

1. INTRODUCTION
Social media is a group of Internet-based applications that are built on Web 2.0 ideology and technology
that allow information creation and exchange of the Internet users (Kaplan and Haenlein, 2009).
The rapid growth of gadget development has been subsequently followed by the fast development
of software applications which leads to social media as a new communication trend. Social media
allows users to socialize with each other and interact without space and time limitation.
The Internet and social media opens wide opportunities for consumers to engage in social
interaction on the Internet as well as for trading companies to conduct a new way of marketing.
According to Muniz and O’Guinn (2001) in Kaplan and Haenlein (2009), some companies are
already using social networking to support brand community’s creativity. In addition, the social
media platform has become an integral element for companies who want to develop a deep online
customer relationship (Chen, Fay, and Wang, 2011). The marketing trend is known as the social media
marketing which concerns the relationship which companies ought to change from “trying to sell”
to “making connections” (Gordhamer, 2009). Businesses that engage consumers with social media
is known as social commerce which is shaped into a dynamic and profitable e-commerce (Hajli and

DOI: 10.4018/IRMJ.2017040102
Copyright © 2017, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

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Featherman, 2014). They further stated that social commerce could create an environment in which
consumers turn into brand ambassadors. Another definition of social commerce comes from Paul
(2009) in Adiputra (2013) who stated that social commerce is part of e-commerce that uses social
media as an online media that supports social interaction and user contributions to help online purchase
and sale of products and services.
One of the social media that supports social media marketing is Instagram. According to Lisa
Pomerantz, senior vice president of global communications and marketing Michael Kors, Instagram
can connect companies with fans and inspire fans with nice pictures with a message in it. Furthermore,
according to the Pew Research Center, Instagram is social media with the most rapid growth.
According to Kotler (2000), purchase decision is a problem-solving process that consists of
analyzing the needs and desires, information search, selection sources appraisal towards purchase
alternative, purchase decisions, and behavior after purchase. Previous researches were not yet able to
demonstrate the influence of social media, viz., Instagram from more than one aspect, on purchase
decision. An example is the work of Dyah (2014) and Sari (2015) that discussed only the impact of
celebrity endorserment of Instagram towards purchase intention. In addition, Goor (2012) and some
articles on http://blog.business.instagram.com/ examined only the content and marketing strategy using
Instragram, without explaining how the content and marketing strategy affect purchase decision. On
the other side, companies have had beliefs towards Instragram as media to apply marketing strategies
as supported by Simply Measured (2015) which found that in Q4 2014 86% of leading brands in the
world are already using Instagram. Therefore, given the current belief and practice of these many
companies, it is intriguing to observe and discover whether the belief and practice of using Instagram
actually meets its underlying goal viz., have significant impact towards customers’ purchase decision.
Hence, this study aims to explore aspects of Instragram, one of the existing and relatively popular
social media these days, that could have significant correlation towards purchase decision.
2. SOCIAL MEDIA (INSTRAGRAM) AND COMMERCE
Social media is divided into various forms such as social networking, Internet forums, weblogs, social
blogs, micro blogging, wikis, podcasts, pictures, video, rating and social bookmarking (Kaplan &
Haenlein, 2009). The increasing development of gadget technology makes the development of social
media increase rapidly. One quite noticeable example is that the role of the conventional mass media
to inform news already began to be replaced by social media given that social media has also evolved
from a media to get in touch with family and friends to a media for consumers to obtain information
about the company and the products sold. (Shankar et al., 2011 in Paquette, 2013).
Through social media, companies can promote their products and form communities or online
groups for consumers who like their brands (Kaplan & Haenlein, 2009). In addition, social media
platform has become an integral element for companies who want to develop a deeper online customer
relationship (Chen, Fay, & Wang, 2011). According to Gabisch and Gwebu (2011), social media is a
valuable forum in the construction of a brand relationship with consumers. Social media marketers
use all those types of online social media in persuading and influencing consumers to buy or use their
company’s products and services. By using online communities, marketing through social media,
or so-called social media marketing, have different strategy with traditional marketing in building
brand image. Social media marketing makes the communication between companies and consumers
became closer by presenting their brands rather than controlling their brand image (Gordhamer,
2009). According to him, social commerce can create an environment where consumers are turned
into brand ambassadors.
Next, according to Fisher (2010), the adoption of social networking introduces new components
in e-commerce. Fisher (2010) divided those components into six categories namely social shopping,
rating and reviews, recommendation and referrals, forums and communities, social media, and social
advertising. Each component has its own challenges and advantages for the online shopping experience.
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Instagram is one of social media-based social networking. Instagram has many features such as
feature to take, edit, and share post in the form of picture or video, feature to tag people, and feature
to explore picture and video that can be assisted using hashtag information. This photo-sharing
application was launched in October 2010 and took about 19 months to reach 50 million users. In
2012, Instagram was bought by Facebook and in September 2014, the user reached 150 million.
3. BRAND RELATIONSHIP AND CONSUMER BEHAVIOUR
Brand is a diffrentiator between products. According to the Law of the Republic of Indonesia Number
15 of 2001 on Brand, Chapter 1, Article 1, Paragraph 1, brand is a sign in the form of images, names,
words, letters, numbers, color composition, or a combintation of those forms that is able to distinguish
one product from others ad used in trading activities. Brand is also used by the company to provide
evidence in the form of fixed standards, especially for companies that do not have the opportunity to
develop relationships with customers continuously (Palmer, 2001 in Rizki, 2011). According to Kotler
(2003) on Rizki (2011), brand plays important roles for producer as: identification means to facilitate
the handling or tracking products; protection means towards features or unique aspects of products;
identification means for satisfied customers for re-purchasing; means for creating associations and
unique meaning to differentiate the product from competitors; competitive advantage through legal
protection, customer loyalty and unique image; source of financial return especially future revenue.
One that supports the formation of consumer emotional bond to products or brands is social
media. According to Gabisch and Gwebu (2011), social media is a valuable forum in forming
brand relationship with consumers. Marketers can interact with consumers frequently, and can form
friendship or personal relationship through social media (Turri, Smith, and Kemp, 2013). Brand
relationship serves a number of functions by providing a resource for consumers to make decisions,
to meet their needs, and to motivate them to purchase the product. (Turri, Smith, & Kemp, 2013).
Consumer behavious is an element in marketing activities that need to be well-understood by
companies. Therefore, observing consumers behavious is important to understand consumer’s mind
concerning company’s product or brand. According to Schiffman and Kanuk (1997) in Ghoniyah
and An (2013), consumer behavior is a process through which user do searching for, buying, using,
evaluating product, service or idea, and act after its consumption.
Brand relationship elements such as brand satisfaction, brand trust and brand attachment (Esch
et. al., 2006 in Lesmana, 2012) have an important role in affecting consumer behavior, especially in
purchasing (Rekarti, 2012). A good relationship between consumers and a brand can give a positive
impact as the consumer feels close and familiar to the brand. Therefore, the relationship between
brand and consumers must be maintained so that consumers continue to use the brand despite in a
form of different product. Customer satisfaction is the objective need to be achieved in business so
that it requires marketers to accurately identify customer needs and develop products that meet the
expectation of customer (Lancaster et al., 2005 dalam Palagan, 2012). According to Perner (2009)
in Palagan (2012), knowledge of consumer behavior in purchasing a product can help marketers in
developing marketing strategy. Therefore, marketers will gain better understanding about consumer
behavior that helps them to meet customer needs effectively and increase consumer’s loyalty to their
product and services.
4. RESEARCH CONCEPTUAL MODEL
In developing the conceptual model, we adopt several theories as underlying rationale for the
relationships among dimensions.

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4.1. EWOM Referral and Its Relationship to Consumer Behaviour
Electronic word of mouth (eWOM) is positive or negative statements made by potential customers,
current customers or former customers, about the product or the company via the Internet (HennigThurau, Gwinner, Walsh et al., 2004). EWOM message is an important means for consumers to obtain
information about product quality and service quality. (Chevalier & Mayzlin, 2003). Additionally, the
eWOM message can also effectively reduce the risks and uncertainty perceived by the consumers when
purchasing a product or service, which means eWom may affect in consumer purchasing decisions
(Chattereje, 2001). The product review that consumers write on the Internet is the most important
form of eWOM communication. Consumers tend to search for product reviews on internet in order
to get information about a particular product. The online review searching will eventually build an
interest in purchasing (Jalilvand & Samiei, 2012). The engagement of consumers in eWOM through
social media is reflected in three behaviors, namely seeking opinion, giving opinion, and the opinion
passing (Flynn et al, 1996; Themba & Mulala, 2012). Based on previous research, eWOM referral
has a correlation with the behavior of consumer in seeking opinion. Opinion seeking behavior is
performed by consumers who seek information and advice from other consumers when making
purchasing decisions (Chu & Kim, 2011). Thus, the following hypotheses can be proposed as follows:
Hypothesis 1: EWOM referral influences on purchase intention.
Hypothesis 2: EWOM referral influences on purchase decision.
4.2. Celebrity Endorsement and Its Relationship to
Brand Relationship and Consumer Behaviour
Celebrity endorsement is recognized as a potential means in brand communication, where the
celebrities are considered to have greater power than the anonymous models Carroll, 2008). According
to Debiprased Mukherjee (2009), celebrity endorsement is considered as a winning formula in brand
marketing and development. Marketers believe that the use of celebrity affect the effectiveness of
marketing, brand recall and recognition, as well as purchase intent and action of consumers (Spry,
Pappu, and Cornwell, 2009).
For marketers, celebrity can be a valuable asset. A study by Chan, Ng, and Luk (2013) discussed
the aspects related to celebrities based on previous research. A celebrity can give testimonial about
the benefit of using certain product or services, support products or services, or act as spokesman of
the endorsed product for a long period of time (Blackwell et al., 2006). Frequently, marketers chose
celebrity who is interesting, trustworthy, or has expertise in area related to the brand image (Hakimi
et al, 2011). Celebrities who are well-known and have good skill will make the consumers have more
desires to purchase the advertised brand (Ohanian, 1991).
According to Shimp (2003), endorser celebrity can be an artist, entertainer, athelete, or wellknown public figure recognised by people for its skill or expertise in an area that can support the
brand he/she promoted. In this context, the endorser celebrity is a celebrity who supports the brand
through social media marketing. The use of celebrity endorser can influence the consumer’s response
towards a product that can make them consider purchasing a product without enforcement. With
that influence, consumers will have positive perception towards the product (brand satisfaction).
Furthermore, if they are able to buy the product, they will purchase it in the future (Shimp, 2003).
Thus, the following hypotheses can be proposed as follows:
Hypothesis 3: Celebrity endorsement influences on brand satisfaction.
Hypothesis 4: Celebrity endorsement influences purchase intention.
Hypothesis 5: Celebrity endorsement influences purchase decision.

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Volume 30 • Issue 2 • April-June 2017

4.3. Information Quality and Its Relationship to Brand
Relationship and Consumer Behaviour
Information quality is consumer’s perception towards information quality from a product that is
provided by e-commerce website (Park & Kim, 2003). Perception is a process of accepting, selecting,
organising, and giving meaning towards received stimuli (Pareek, 1983; Milton, 1981; Maskuri,
2010). According to Robbins (1991) on Maskuri (2010), three factors that influence perception are
perceptors, target and situation. The characteristic of the observed target can be influenced by what
target perceive towards movement, sound, size, or other attributes possessed by the target that will
form its perspective. Therefore, the authors propose the following hypotheses:
Hypothesis 6: Information quality influences on brand satisfaction.
Hypothesis 7: Information quality influence on brand trust.
Hypothesis 8: Information quality influence on purchase decision.
4.4. Brand Relationship and Its Relationship to Consumer Behaviour
Satisfaction is a psychological response of customers as a result of a comparison between expectation
and perceived reality after consuming a product (Kotler, 2000). According to Engel (1990) in Sreejesh
(2014), brand satisfaction is the result of a subjective evaluation of the consumers where consumers
are satisfied with the selected brand and that the brand is in line with their expectations. Brand
attachment is defined as a psychological variable that expresses affective relationship to the brand
that is durable; it states the relationship of psychological closeness to the brand (Lacoeuilhe, 2000 in
Louis and Lombart, 2010). When customers are satisfied, they might gain certain attachment towards
products’ brand. Additionally, they might also have intention to buy the product in the future. Thus,
the authors propose the following hypotheses:
Hypothesis 9: Brand satisfaction influences brand attachment.
Hypothesis 10: Brand satisfaction influences purchase intention.
In business, trust is usually called brand trust. Brand trust is consumers’ tendency to believe
that the brand can keep the promise with respect to its performance (Fuller et al, 2008 at Yana and
Siti, 2011). According to Chaudhuri and Holbrook (2001), brand trust is the desire of consumers in
general who believe in a brand because it can meet the requirements and have the necessary skills to
function. Meanwhile, according to Lau and Lee (1999) in Lesmana (2012), brand trust is the desire
of consumers who rely on the brand, in a situation of risk, as they have expectations that the brand
brings positive things. This could add customers’ attachment on the brand. In addition, this could
also lead towards consumers’ intention to buy the product. Therefore, the following hypotheses can
be proposed as follows:
Hypothesis 11: Brand trust influences brand attachment.
Hypothesis 12: Brand trust influences purchase intention.
According to McAlexander (2003) and Thomson (2005) in Rekarti (2012), brand attachment
creates connections and it could predict how often a particular brand is purchased in the past and will
be purchased in the future. Thus, the authors conjecture the following hypothesis:
Hypothesis 13: Brand attachment influences purchase decision

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4.5. Relationship between Consumer Attitude and Behaviour
One of the fundamental aspects of consumer behavior is consumers’ intention to buy. According to
Keller (2013), consumers’ intention to buy could be expressed as the probability whether consumers
would buy product of a brand or switch from one brand to another brand. Another study suggested
that the interest to buy is a function of the monetary deliberation, not only of behavior (Rizwan,
Qayyum, Qadeer and Javed, 2014). Thus, affordability is an economic aspect that could affect the
intention regardless the product price. The Theory of Reasoned Action (TRA) developed by Martin
Fishbein and Ajzen Icek is a model of social psychology theory that fundamentally explains the factors
that drive human behavior. They suggested that a person’s actual behavior could be determined by
considering his/her prior intention along with the belief that the person would have for the given
behavior. Thus, the authors propose the following hypothesis:
Hypothesis 14: Purchase intention influences purchase decision.
Therefore, all hypotheses can be formulated as Figure 1.
5. METHODOLOGY
5.1. Data Collecting Procedure
This research was quantitative and used a survey technique that was developed based on the
research conceptual model (Figure 1). Before the questionnaire was distributed, readability test
was performed towards 10 people with different educational background. The indicators were also
reviewed by academician with marketing background. In order to get as many samples as possible,
the questionnaires were distributed online using Google form.

Figure 1. Conceptual Model

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5.2. Instruments
In the questionnaire, there are 8 dimensions with the total 35 statements (see Appendix) that contain
all of the indicators in this research, each of which should be scored by the respondents for their
agreements. For each statement, a Likert scale of 1 to 5 is provided to rate each indicator. Scale
1 is used to express “strongly disagree”, scale 2 is used to express “disagree”, scale 3 is used to
express “neutral”, scale 4 is used to express “agree”, and scale 5 is used to express “strongly agree”.
EWoM referral dimension is represented by 4 indicators. Celebrity endorsement dimension consists
of 4 indicators. Information quality dimension has 6 dimensions. Brand satisfaction dimension
is represented by 4 indicators. Brand trust dimension consists of 4 indicators. Brand attachment
dimension has 5 indicators. Purchase intention dimension is represented by 4 indicators. Lastly,
purchase decision consists of 4 indicators.
6. RESULTS
6.1. Respondent Demographics
From the data collection, the authors obtained 350 respondents. Table 1 shows the demographics of
the respondents who completed the questionnaires in this study.
6.2. Data Analysis
First step to perform data analysis with LISREL is making a path diagram. This requires the following
steps: changing raw data into data PRELIS, opening the path diagram, calling PRELIS data, and
determining the exogenous-endogenous variables. Next, to identify the model the degree of freedom
(df) should greater than the number of parameters to be estimated. The df in this research is 510.
There are several criteria that must be met in using SEM method viz., sample size, data normality
(Hair, Black, Babin et al., 2009), and offending estimates. The minimum sample size for 35 indicators

Table 1. Respondent demographics
Sex

Respondents

Profession

Respondents

Male

75

High School Student

10

Female

275

Student

293

Age

Respondents

Employee

41

16-20

180

Unemployee

6

21-25

163

Last Education

Respondents

>25

7

Junior High School

10

Following Online Shop

Respondents

High school

240

1-5

185

Bachelor

98

6-10

74

Master

2

> 10

91

Salary

Respondents

Instagram Experience

Respondents

< 1 millions

123

<1 year

50

> 1 millions

227

1-3 years

225

Location

Respondents

> 3 years

75

Java

289

Non Java

61
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Volume 30 • Issue 2 • April-June 2017

is 350 (Kline, 2005). Data normality can be tested by looking at the value of the P-Value Skewness
and Kurtosis that must be greater than 0.05 after previously changing the data type into a continuous
multivariate. Normality test results of this study can be seen in Table 2 and Table 3.
It can be seen that the research model is not normal in univariate where the P-Value of ER3, ER4,
BA2, and BA3 ≤ 0.05. In addition, the P-Value for multivariate test is 0.00 which is less than 0.05.
Therefore, the authors decided to replace Maximum Likelihood (ML) estimation with Diagonally
Weighted leasts Squares (DWLS) estimation (Soreh and Gorji, 2014; Kline, 2005) to perform parameter
estimation and the subsequent steps. Next is testing the offending estimates. Offending estimates are
negative error variances for existing constructs (Hair et al., 2009). The test results offending estimates
from this study can be seen in Table 4 that exhits there is no negative errorvariance and no correlation
coefficient is greater than 0.9.
Next is to test the measurement model. First is to conduct validity test that asseses whether a
variable measure what it should measure. According to Hair, Black, Babin, and Anderson (2009)
variables have good validity to construct if the T-Values ​​greater than or equal to the critical value
(≥1.96) and according to Sharma (1996) the standardized loading factor is greater than or equal to
0.60 (≥0.60). Based on the validity test results, ER3, ER4, CE1, CE4, IQ3, and IQ6 has loading factor
below 0.6. Thus, those indicators are declared invalid and removed from the study, both for the overall
reliability test and subsequent data processing. Second is to perform realibility test that evaluate the
consistency of a measurement where high reliability shows that the indicators (variables observed)
have a high consistency in measuring the construct / latent variables. According to Hair, Black, Babin,
and Anderson (2009), for SEM measurement, reliability can be assessed using Construct Reliability
Measure (CR) and Measure Variance Extracted (VE). Reliability of the construct is good if CR value
≥ 0.70 and VE value ≥ 0.50. Based on the results of the reliability test in this study, ER has a CR
value under 0.7 while IQ and BS have a VE value below 0.5. However, the value is still acceptable
when CR is greater than 0.6 and VE is greater than 0.4 (Fornell, 1981 in Huang et al., 2013).
Last is to test the structural model. It is performed by evaluating the GoF between data and model
(Hooper, Coughlan, and Mullen, 2008). The results are shown in Table 5.
It can be seen that the Chi-Square and Chi-Square divided by degree of freedom (df) has values
beyond threshold, however this could be disregarded as Chi-Square statistic nearly always rejcts
the model when large samples are used and data could be considered normal (Hooper, Coughlan &
Mullen, 2008).
6.3. Hypotheses Testing Results
Table 6 shows the the hypotheses tests (T-values) based on the results of the structural model testing
by using LISREL. Of the 14 hypotheses tested, only 8 hypotheses were accepted, while 6 others
were rejected.
7. DISCUSSIONS AND IMPLICATIONS
7.1. Theoretical Implications
H1: ER-PI (accepted) and H2: ER-PD (accepted).
From the testing result of hypothesis H1, we find that EWOM referral from ‘comment’ and ‘tag people’
feature in Instagram influences customer purchase intention towards the corresponding brand. The
‘comment’ and ‘tag people’ feature enables Instagram users to see how many people are interested in
the product. This finding shows that—for Indonesian people represented by the sample—attention,
appraisal, and other positive responses about a brand influences Instagram user’s purchase intention.
There is a tendency of people who intend to buy product online to check beforehand how many people
are interested in that product and to search the product review from other customers.
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Table 2. Test of Univariate Normality for Continuous Variables
Test of Univariate Normality for Continuous Variables
Code

ER1

Skewness

Kurtosis

Skewness and Kurtosis

Z-Score

P-Value

Z-Score

P-Value

Chi-Square

P-Value

-0.960

0.337

-0.083

0.934

0.928

0.629

ER2

-1.222

0.222

-0.282

0.778

1.573

0.455

ER3

-2.044

0.041

-1.759

0.079

7.273

0.026

ER4

-2.505

0.012

-2.269

0.023

11.422

0.003

CE1

-0.649

0.516

-1.173

0.241

1.798

0.407

CE2

-0.225

0.822

-0.540

0.589

0.342

0.843

CE3

-0.704

0.482

-0.612

0.540

0.870

0.647

CE4

-0.893

0.372

-1.230

0.219

2.310

0.315

IQ1

-0.845

0.398

-1.614

0.107

3.318

0.190

IQ2

-1.288

0.198

-0.324

0.746

1.764

0.414

IQ3

-0.385

0.700

-1.871

0.061

3.648

0.161

IQ4

-1.189

0.234

0.231

0.817

1.467

0.480

IQ5

-1.180

0.238

-0.091

0.927

1.401

0.496

IQ6

-0.720

0.472

-0.671

0.502

0.968

0.616

BS1

-1.288

0.198

-0.991

0.322

2.641

0.267

BS2

-0.959

0.337

-0.951

0.342

1.825

0.402

BS3

-1.379

0.168

-1.220

0.222

3.390

0.184

BS4

-1.573

0.116

-1.801

0.072

5.718

0.057

BT1

-1.102

0.270

-1.325

0.185

2.969

0.227

BT2

-0.753

0.452

-0.759

0.448

1.142

0.565

BT3

-0.983

0.326

-0.991

0.321

1.949

0.377

BT4

-1.127

0.260

-0.136

0.892

1.290

0.525

BA1

0.389

0.697

-1.008

0.313

1.168

0.558

BA2

0.997

0.319

-2.613

0.009

7.824

0.020

BA3

1.074

0.283

-2.767

0.006

8.810

0.012

BA4

0.171

0.864

-1.468

0.142

2.183

0.336

BA5

0.771

0.441

-2.674

0.007

7.746

0.021

PI1

-1.961

0.050

-1.074

0.283

4.999

0.082

PI2

-1.583

0.113

-0.636

0.525

2.912

0.233

PI3

-1.407

0.159

-0.144

0.886

2.000

0.368

PI4

-1.391

0.164

0.284

0.777

2.015

0.365

PD1

-0.625

0.532

-0.338

0.735

0.505

0.777

PD2

-0.498

0.619

-0.915

0.360

1.086

0.581

PD3

-1.363

0.173

-1.059

0.290

2.978

0.226

PD4

-1.026

0.305

-0.730

0.466

1.586

0.452

Relative Multivariate Kurtosis = 1.239

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Table 3. Test of Multivariate Normality for Continuous Variables
Test of Multivariate Normality for Continuous Variables
Skewness

Kurtosis

Skewness and Kurtosis

Value

Z-Score

P-Value

Value

Z-Score

P-Value

Chi-Square

P-Value

253.687

44.799

0.000

1605.126

23.314

0.000

2550.499

0.000

Table 4. The test results offending estimates from this study
Code

Errorvar

R2

ER1

0,45

0,38

ER2

0,34

0,53

ER3

0,58

0,31

ER4

0,76

0,17

CE1

0,67

0,27

CE2

0,31

0,64

CE3

0,42

0,49

CE4

0,74

0,25

IQ1

0,70

0,29
0,22

IQ2

0,68

IQ3

0,98

0,19

IQ4

0,47

0,27
0,28

IQ5

0,52

IQ6

0,71

0,10

BS1

0,44

0,44

BS2

0,27

0,63

BS3

0,36

0,44

BS4

0,51

0,41

BT1

0,33

0,63

BT2

0,15

0,81

BT3

0,39

0,52

BT4

0,24

0,66

BA1

0,40

0,58

BA2

0,48

0,57

BA3

0,47

0,60

BA4

0,27

0,74

BA5

0,49

0,55

PI1

0,51

0,35

PI2

0,40

0,36

PI3

0,31

0,54

PI4

0,24

0,63

PD1

0,30

0,60

PD2

0,31

0,66

PD3

0,43

0,51

PD4

0,38

0,51

Based on the hypothesis H2 test result, EWOM referral indirectly influences customer purchase
decision. This finding supports the theory of reasoned action of Ajzen (1991). The theory stated that
external factor does not directly influence people’s behavior. This finding also supports previous
study of Jalilvand and Samiei (2012) that was conducted in automobile industry in Iran. The study
found that searching activity of the online reviews builds customer’s interest in purchasing a product
of certain brand in Instagram.
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Table 5. Goodness of fit of CFA and Structural Model
Indicator

Results

Standard

1092.23
(P = 0.0)

Bergantung pada df
(P>0.05)

1092.23:359
(3.04)

3:1
(3)

Kline, 2005

RMSEA

0.06

≤ 0.07

Steiger, 2007

GFI

0.96

≥ 0.95

AGFI

0.96

≥ 0.95

RMR

0.052

Kecil

Tabachnik & Fidell, 2007

SRMR

0.062

≤ 0.08

Hu & Bentler, 1999

NNFI

0.96

≥ 0.95

CFI

0.96

≥ 0.95

Chi-Square x

2

Relative x2 (x2/df)

Source

Table 6. Hypotheses tests based on the results of the structural model testing
Hypothesis

T-Value

Significant/ Insignificant

Conclusion

H1: ER → PI

2.11

Significant

Hypothesis Accepted

H2: ER → PD

0.72

Not Significant

Hypothesis Rejected

H3: CE → BS

0.33

Not Significant

Hypothesis Rejected

H4: CE →PI

0.15

Not Significant

Hypothesis Rejected

H5: CE → PD

0.89

Not Significant

Hypothesis Rejected

H6: IQ → BS

6.38

Significant

Hypothesis Accepted

H7: IQ → BT

9.05

Significant

Hypothesis Accepted

H8: IQ → PD

0.22

Not Significant

Hypothesis Rejected

H9: BS → BA

2.87

Significant

Hypothesis Accepted

H10: BS → PI

2.83

Significant

Hypothesis Accepted

H11: BT → BA

1.48

Not Significant

Hypothesis Rejected

H12: BT → PI

3.14

Significant

Hypothesis Accepted

H13: BA → PD

3.83

Significant

Hypothesis Accepted

H14: PI → PD

4.37

Significant

Hypothesis Accepted

H2: CE-PD (rejected), H3: CE-BS (rejected) and H4: CE-PI (rejected).
In this study, it can be observed that celebrity endorsement has no influence on brand satisfaction,
purchase intention, nor purchase decision. Based on this study’s finding, looking at a trusted and
attractive celebrity endorsing a product does not provide enough force for the invidial to build
satisfaction, purchase intention or purchase decision.
This finding has different result with marketer’s believe stated in Spry, Pappu and Cornwell’s
(2009) study. Marketers believe that celebrity have significant role in improving marketing
effectiveness, brand recall and recognition, as well as purchase intention and action of consumers.
In addition, this study’s finding does not align with the previous study (Mukherjee, 2009) that stated
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that celebrity endorsement is the winning formula for brand marketing and development. O’Mahony
and Meenaghan (1997) stated that alignment between the celebrity image and the related brand is
desired by consumers However, this study contradicts that phenomenon in the case Instagram case
in Indonesia.
H6: IQ-BS (accepted), H7:IQ-BT (accepted) and H8:IQ-PD (rejected).
Siau and Shen (2003), in their study, developed a model of trust building in mobile commerce
context and they included information quality as one of the component that affects customer trust
to perform e-commerce activites. Meanwhile, Loiacono et al. (2002) found that information quality,
combined with functional-fit-to-task, was one of the important factors that drive consumer to purchase
a product from a website. Both studies show that information quality has correlation in customer trust
and purchase decision. This study aligns with the previous study in term of brand trust; however, we
found that in Instagram case in Indonesia, information quality has weak correlation with purchase
decision which can be concluded that information quality does not influence customer purchase
decision.
As for brand satisfaction factor, some previous studies (Wen et al, 2008 and Park and Kim, 2008)
found that information quality has a direct and positive impact on customer satisfaction. This study’s
finding aligns with those studies. We find that information quality influences brand satisfaction.
H9: BS-BA (accepted) and H10: BS-PI (accepted).
As for hypotheses H9 and H10, the finding is consistent with Lesmana’s (2012) finding. This
study and the previous study (Lesmana, 2012) both find that brand satisfaction influences positively
to brand attachment.
Besides trust, many studies in e-commerce found that customer satisfaction was the main factor
that influences customer’s purchase intention. One of the studies is Adji and Semuel’s (2014) study
that found there was significant correlation between trust and purchase intention. Although there were
different indicators and object of study, both yielded the same result, i.e. the dimension of satisfaction
and trust influences purchase intention.
H11: BT-BA (rejected) and H12: BT-PI (accepted)
The previous study of Lesmana (2012) found there was strong positive correlation between
brand trust and brand attachment. However, the finding in this study is in contrast with his finding.
Eventhough this study uses the same four evaluation indicators this study receives different result.
In this study, we find that brand trust has weak positive correlation to brand attachment, hence we
conclude that brand trust does not influence brand attachment. It is likely that the difference is
because this study investigates Instagram while his study examined Twitter. The nature of Instagram
and Twitter is different on how the way information is represented, delivered, taken into action and
perceived as benefit to user. Twitter focuses on text based information while Instagram uses pictures
as the main information.
Meanwhile, brand trust is confirmed to have direct influence to user’s purchase intention. Many
have believed that trust dimension is one of the main dimensions that have strong correlation to
purchase intention; for example, Gefen’s (2000) study that discussed trust in online world. In tourism
sector, Ponte et al. (2015) studied the impact of trust to customer purchase intention through travel
website.
H13: BA-PD (accepted)
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The findings show that brand attachment influences purchase decision. Customer’s decision to
buy a product is influenced by the degree of attachment toward the underlying brand. This finding
supported the study of McAlexande (2003) and Thomson (2005) in Rekarti (2012). This finding
also implies that brand attachment is an important factor that should be utilized by sellers who uses
Instagram as it has direct effect on purchase decision.
H14: PI-PD (accepted)
This study found that there is strong correlation between purchase intention and purchase decision
that purchase intention influences purchase decision. This finding is aligned with the previous studies
that also used Instagram social media (Prabowo, 2013 & Sandrakh, 2013).
7.2. Managerial Implications
The results show that eWOM referral has direct impact towards purchase intention while information
quality has direct impact towards brand satisfaction and brand trust. These results could give directions
towards online shops or companies which use Instagram as marketing media. First, since eWOM
referral has direct impact towards purchase intention, companies should optimize the feature ‘comment’
in order to filter unnecessary or unfavorable comments. Thus, it is expected that Instagram users would
get more concern and more positive feeling from others about a particular product that would lead
to higher intention to buy. Second, companies should pay more attention towards figure captions in
Instagram such that the completeness, conciseness, understandability and relevance of the captions
could support proper information delivery towards the users so that they perceive the information
as in good quality. From the hypotheses testing it can be inferred that captions with such qualities
would likely have impact towards brand satisfaction and brand trust.
8. CONCLUSION
This research aims to examine the impact of Instagram social media as a marketing media towards
purchase decision. From 14 hypotheses, 8 were accepted and 6 were rejected. Thus, this reseach
conforms that eWOM referral and information quality have indirect relation towards purchase decision.
EWOM referral has relation towards purchase decision via purchase intention while information quality
has relation towards purchase decision via brand satisfaction and via brand trust. Interestingly, celebrity
endorsement is found not having impact towards purchase decision either directly or indirectly. It
has no relation towards any brand relationship dimensions, purchase intention or purchase decision.
Brand relationship dimensions namely brand satisfaction and brand trust have indirect relation
with purchase decision. Brand satisfaction has indirect impact towards purchase decision via brand
attachment and via purchase intention. Brand attachment and purchase intention has direct relation
with purchase decision. Similarly, brand trust also has indirect impact towards purchase decision via
purchase intention.
9. LIMITATIONS AND FUTURE RESEARCH
This research could not get the list of Instagram users who follow at least one online shop account.
The authors only got an estimation of Instagram users in Indonesia i.e., circa 18 million. Conceptually,
the convenience sampling used in this research could not generalize finding in the samples towards its
population. Thus, further research might be conducted for better generalization of sample data towards
its population. In addition, as this research uses Instagram users’ point of view, a further research to
examine companies’ perspective in using Instagram as its marketing media would complement this
study result and thus provide a more complete elaboration on this topic.
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APPENDIX

Indicator

Code

Description

Get concern from others
(Sari, 2012)

ER1

Consumer receives forms of care, pride and satisfaction from other consumers about
a product of a brand.

Get positive feeling
(Sari, 2012)

ER2

Consumer receives positive feelings expressed by other consumers for a product of
a brand.

Economic incentive
(Sari, 2012)

ER3

Consumer receives an amount of information—related to discounts, promotions, and
other information related to economic incentive—about a product of a brand that is
expressed by other consumers.

Platform assistance
(Sari, 2012)

ER4

EWOM is suitable as a medium for the implementation of social commerce and
social media marketing of a product of a brand.

EWOM REFERRAL

Indicator

Code

Description

CELEBRITY ENDORSEMENT
Visibility (Dyah, 2014)

CE1

Celebrity who becomes the brand model in the product image posted by a brand is
popular.

Credibility (Dyah, 2014)

CE2

Consumer is confident of the celebrity who becomes the model of a product of a
brand in the image posted by a brand.

Attractiveness (Dyah,
2014)

CE3

Celebrity who becomes the model of a product of a brand in the image posted by a
brand is appealing.

Product match up (Dyah,
2014)

CE4

Celebritiy’s profile who becomes the model of a product of a brand matches the
profile of the endorsed product.

Indicator

Code

Description

Completeness (DeLone and
McLean, 2003)

IQ1

Good information quality is provided so that product description in the caption
of an image posted by a brand is complete

Conciseness (DeLone and
McLean, 2003)

IQ2

Good information quality is provided so that product description in the caption
of an image posted by a brand is concise

Accuracy (DeLone and
McLean, 2003)

IQ3

Good information quality is provided so that hashtag used to complement the
description of a product in an image posted by a brand is accurate

Undestandbility (DeLone and
McLean, 2003)

IQ4

Good information quality is provided so that image posted by a brand to
promote its product or brand image is easily understood

Relevance (DeLone and
McLean, 2003)

IQ5

Good information quality is provided so that brand’s product description
written in the image’s caption is highly relevant to the image posted by a brand

Currency (DeLone and
McLean, 2003)

IQ6

Good information quality is provided so that the brand frequently posts images
in one day

INFORMATION QUALITY

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Volume 30 • Issue 2 • April-June 2017

Indicator

Code

Description

Decision
(Lesmana, 2012)

BS1

Consumer is satified with the decision taken related to a brand

Experience (Lesmana, 2012)

BS2

Consumer has satisfying experience related to a brand

Function (Lesmana, 2012)

BS3

Consumer is satisfied with the utilization of media to promote the brand

Service (Lesmana, 2012)

BS4

Consumer is satisfied with the services provided by a brand

BRAND SATISFACTION

Indicator

Code

Description

Delivery (Lesmana, 2012)

BT1

Consumer trusts the information delivered by a brand

Statement (Lesmana, 2012)

BT2

Consumer trusts the statement given by a brand

Action (Lesmana, 2012)

BT3

Consumer trusts a brand’s action

Benefit (Lesmana, 2012)

BT4

Consumer trusts that the brand gives benefits to consumers

BRAND TRUST

Indicator

Code

Description

Brand self-connection: Bond (Lesmana, 2012)

BA1

There is a bond between consumer and brand

Brand self-connection: Emotional (Lesmana, 2012)

BA2

There is emotional bond between consumer and brand

Brand prominence: Mind (Lesmana, 2012)

BA3

The brand is prominent in consumer’s mind

Brand prominence: Feel (Lesmana, 2012)

BA4

The brand is prominent in consumer’s feeling

Brand prominence: Memory (Lesmana, 2012)

BA5

The brand is prominent in consumer’s memory

BRAND ATTACHMENT

Indicator

Code

Description

Information seeking (Sandrakh,
2013)

PI1

Consumer wants to find more information about a product of a brand as he/
she has intention to buy the product

Intention to understand
(Sandrakh, 2013)

PI2

Consumer wants to understand more about a product of a brand as he/she has
intention to buy the product

Intention to try (Sandrakh,
2013)

PI3

Consumer wants to try a product of a brand as he/she has intention to buy the
product

Intention to buy (Sandrakh,
2013)

PI4

Consumer wants to buy a product of a brand

PURCHASE INTENTION

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Volume 30 • Issue 2 • April-June 2017

Indicator

Code

Description

Think (Palagan, 2012)

PD1

Consumer thinks deeply about his/her decision of buying a product of a brand

Feel (Palagan, 2012)

PD2

Consumer develops an emotional feeling in buying a product of a brand

Distinguish (Palagan,
2012)

PD3

Consumer distinguishes a product of a brand from other brands in his/her decision of
buying the product

Choose (Palagan, 2012)

PD4

Consumer chooses a product of a brand from other brands in his/her decision of
buying the product

PURCHASE DECISION

Randy Danniswara obtained his bachelor degree in Information Systems from the Faculty of Computer Science,
Universitas Indonesia. He has interest on social media commerce.
Puspa Indahati Sandhyaduhita is a lecturer at the Faculty of Computer Science, Universitas Indonesia. She received
her master degree from TU Delft, the Netherlands. Her research interests include e-commerce, information systems,
requirements engineering, business process modeling, enterprise architecture, enterprise resource planning, and
supply chain management.
Qorib Munajat is a lecturer at the Faculty of Computer Science, Universitas Indonesia. He received his master degree
from University of Melbourne, majoring in Information Systems. His research interests are software engineering,
enterprise systems, and enterprise architecture.
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