Global Journal of Emerging Trends in e-Business, Marketing and Consumer Psychology (GJETeMCP)
An Online International Research Journal (ISSN: 2311-3170)
2018 Vol: 4 Issue: 1
565
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The Impact of Social Media Platforms to Online Consumers’
Intention to Purchase in Restaurant Industry
Patricia Bianca M. Arceo,
Industrial Engineering Program, College of Engineering and Architecture,
Technological Institute of the Philippines, Philippines.
E-mail: [email protected]
Ivan Ray C. Cumahig,
Industrial Engineering Program, College of Engineering and Architecture,
Technological Institute of the Philippines, Philippines.
E-mail: [email protected]
Michael B. De Mesa,
Industrial Engineering Program, College of Engineering and Architecture,
Technological Institute of the Philippines, Philippines.
E-mail: [email protected]
Marie Jessica V. Buenaventura,
Industrial Engineering Program, College of Engineering and Architecture,
Technological Institute of the Philippines, Philippines.
E-mail: [email protected]
Jaypy T. Tenerife,
Industrial Engineering Program, College of Engineering and Architecture,
Technological Institute of the Philippines, Philippines.
E-mail: [email protected]
___________________________________________________________________________
Abstract
As social media continue to break geological boundaries and connect people together and
has revolutionized the way people interact and socialize with each other. Businesses and
entrepreneurs alike have taken advantage of these online channels to grow and expand
businesses. The study aimed to determine the influence of various social media platforms used
to advertise foodstuff. The study posits that advertisements, blogs, and promotions on
Facebook, Twitter, Instagram, and other social media sites affected the decision of the
customers to purchase. Quantitative research methods were used to study the responses of
100 participants recruited via convenience sampling. The relationship of the various types of
online consumers identified as engagers; expressers and informers; socializers and
networkers; and watchers and listeners were explained using descriptive and inferential
statistics. Focused on the consumers found in different restaurants, the results of the study
revealed that watchers and listeners through the use of social media platforms affected online
social convergence. Online convergence influence purchase intention and is influenced by
social media platforms and the frequency of social media use. Food businesses essentially
need more networkers and socializers that can relate to engagers or watchers and listeners.
The study contributed to the many untapped types of research in the area of consumer
behavior, social media influences, marketing and advertising, and food advertising.
___________________________________________________________________________ Key Words: Consumer Behavior, Restaurant Industry, Purchase, Decision-making, Social
media
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1. Introduction
In the past years, the use of social media revolutionized the way entrepreneurs do
business. Entrepreneurship paired with social media become one of the factors that triggered
entrepreneurs to be more engaged in startup businesses. Social media as one of the most
effective tools was used by small business entrepreneurs as a platform to accelerate growth
(e.g., Facebook, Twitter, Instagram). Normally, all small businesses use social media for
advertising and publicity (Shabbir et al., 2016). Making fan pages is one way for small
businesses to acquire suggestions and opinions from followers and potential clients which
businesses use to improve operations. Also, Mangold and Faulds (2009) mentioned that social
media build a relationship between the enterprise and the customers by giving information
about the goods and services offered online. Social media platforms can build online
convergence which in turn helps in creating informal groups and establishing a community
that shares the same thoughts and opinions. The utilization of online networking as a
marketing tool enables organizations to blend with kindred experts in the field, associated
with the group and get business openings with convenience as mentioned by Smith and
Taylor (2004); and directly find online information about marketing and advertising
techniques that are presently used by business owners. Generally, social media is a helpful
tool used by businesses in marketing that may not just be limited to products. Social media
helps in establishing a relationship with customers and serves as a direct reference to
consumers’ opinions and suggestions that guides businesses toward improvement and growth.
2. Literature Review
It has been identified that majority of people spend almost a quarter of their daily lives
surfing through various social networking sites (Forbes, 2017). By allowing users to interact
and socialize with each other through these sites, social networking is formed according to
Kaplan and Haenlein (2010).
The interacting users of social media may also be the consumers that have the ability to
purchase an item or avail an online service. A research conducted by Schlosser et al. (2006)
and Shoa (2009) in social media consumers categorized these online users as either
contributors or observers and followers. However, this phenomenon has changed through
time as many social media users have become more active contributors and more active
followers of online business portals and advertisements (Ngai et al., 2015)
At present, organizations are looking for the most effective marketing strategy to minimize
advertising cost (Kirti and Karahan, 2011). Social Media has become an optimal tool that
addresses the need to come up with a cost-effective advertising and marketing strategy. The
work of Kallas (2017) mentioned that social media can reach an estimated number of two
billion users around the world with the highest speed of information dissemination. For this
Global Journal of Emerging Trends in e-Business, Marketing and Consumer Psychology (GJETeMCP)
An Online International Research Journal (ISSN: 2311-3170)
2018 Vol: 4 Issue: 1
567
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reason alone, companies prefer to shift from the traditional tools of marketing to the use of
social media platforms. Additionally, companies from different industries started to convert
its marketing strategies to new approaches using the internet for convenience, and for more
economic reasons (Chui and Manyika, 2012). This means that at present, social media was
presented as an alternative to the traditional, expensive and time-consuming marketing
approaches. This phenomenon was described by Wally and Koshy (2014) as the phase where
advertising has overcome the many flaws of traditional marketing.
Smith (2011) mentioned that a total of 88% of marketers are utilizing various social media
channels as a tool for business development. Smith (2011) also mentioned that USD 60
Billion is spent annually by business on social media for advertisements in the United States.
alone. The relationship built between companies and customers through social media
platforms was perceived to increase returns for marketers (Okazaki & Mueller, 2007).
Besides the numerous advantages, social media marketing provided undeniable benefits that
lessened business expenditure. Social media bridged firms and organizations and created
social networks that utilized advertising and marketing driving better administration of
marketing activities (Kim and Ko, 2011). Social media marketing strategies were identified to
have several advantages e.g., sharing information is faster, and social media boost social
interaction between users as mentioned by Chen (2014). Businesses can not only improve
marketing through the use of social media, but businesses may also gain returns from
investment campaigns deployed online (Benwell, 2014).
Social media consumers tend to include themselves in groups with similar interests, this
uniqueness allows marketers to effortlessly target specific groups (Kahle, Valetter-Florence,
& Ebrary, 2012). Also, through the use of consumer blogs, a stage for marketing service
industries can be cost-effective, if not free, and fresh to other consumers (Wah, 2009).
Purchase intention is the most reliable pointer that builds the connection between
consumers’ interest and actual purchase (Chen, 2014), this will make or break marketing
strategies. Purchase intention provided more proof of the efficiency rate of marketing
activities. Gaber and Wright (2014) mentioned that social media has a huge effect on
consumers’ decision-making and purchase intention.
The focus of this study is the restaurant industry, a similar study about the impact of social
media marketing on decision-making in the restaurant industry showed that conversation and
information sharing in social media platforms are the most important factors (Pattachanai,
2017). Conversation on social media platforms by engagers and sharing of information by
networkers and socializers play a vital role in the decision-making of restaurant industry
consumers.
Based on monthly active users, Kallas (2017) compiled the top social networking sites
worldwide, Facebook leads the top social networking site with more than two billion monthly
Global Journal of Emerging Trends in e-Business, Marketing and Consumer Psychology (GJETeMCP)
An Online International Research Journal (ISSN: 2311-3170)
2018 Vol: 4 Issue: 1
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active users followed by Youtube with 1.5 billion, Instagram with 700 million and Twitter
with 328 million monthly active users as of September of 2017. On a daily basis at present-
day, 100,000 tweets are sent, 684,478 pieces of content are shared on Facebook, 2 million
search queries are made on Google, 48 hours of video are uploaded to YouTube, 3,600 photos
are shared on Instagram, and 571 websites are created (James 2012). A more recent literature
from a digital marketing agency suggested that as of January 2018, 500 million tweets are
sent per day, 95 million photos are uploaded on Instagram daily, 300 hours of video are
uploaded to Youtube per minute, and there are currently over 3.2 billion active users of
Facebook (Aslam, 2018).
The classification of social media consumers is a vital part of this research to be able to
understand which type of consumer will significantly contribute to online convergence and
highly influence purchase intention in the restaurant industry. Based on Vinerean et al. (2013)
there are four types of social media consumers namely Engagers, Expressers and Informers,
Networkers, and Watchers and Listeners.
Although there were disadvantages of social media as identified by Timilsina (2017) such
as improper relevant work, lack of skills in customer relationship management, time
consumption and negative reviews in the social site which hampers business as well as image.
Most of the present literature suggest that in the 21st Century, Social Media has become the
method of statement to express opinions, ideas, and modus in a totally new way. This new
kind of media also has a massive impact on corporation because it helps in the realization that
without a right plan and an accurate social media strategy, corporations will not stand out in
the information revolution and in the fast-changing digital era (Saravanakumar &
SuganthaLakshmi, 2012).
3. Background of the study Figure 1: Research Model
Social
Media
Engagers
Expressers
and
Informers
Networkers
and
Socializers
Watchers
and
Listeners
Online
Convergen
ce
Influence to
Purchase
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This study aimed to provide a deeper understanding of how social media and social media
users affect purchase intention in the restaurant industry. The study suggests an explanation
on how social media platforms and various types of social media users through online
convergence influence purchase intention in the restaurant industry (see Fig. 1). The study is
affixed to the idea that the use of various social media platforms and the activities of various
social media users form online convergence that ultimately influences purchase intention in
the restaurant industry. Hajli (2014) reported that through social media (e.g., online forums,
communities, ratings, reviews, and recommendations) developments, a new stream of e-
commerce, called social commerce, influences consumers to create content and encourage
others thereby significantly affecting intention to buy. Another literature suggests that reviews
on social media either induce or dissuade purchases (Yogesh & Yesha, 2014). These findings
suggested that social media and online convergence through online communities, forums, and
reviews directly affect purchase intention of consumers. Social influencers’ who are people
with large followers on social media, content has a huge effect on purchasing decisions
(Barker, 2017). On Richard and Guppy (2014) paper, Facebook was highlighted as one of the
most used social media platforms. It also plays an important role in consumers’ purchase
intention.
4. Methodology
4.1 Methods
Using a developed questionnaire of online activities and social media presence to
consumers, constructs were validated through factor analysis using Statistical Package for
Social Science (SPSS). Reliability of the identified constructs was reported using Cronbach's
alpha. Descriptive statistics and multivariate analysis were used to examine the basic
variables and concepts of the impact of social media platforms to online consumers’ intention
to purchase in the restaurant industry. Path analysis was used to test the relationship between
the variables. Using factor analysis the research aimed to identify and validate constructs
from the following: Engagers; Expressers and Informers; Socializers and Networkers; and
Watchers and Listeners as the type of online consumers. The validated constructs were used
as measures in evaluating the impact of Social Media platforms to online consumers’
intention to purchase in the restaurant industry.
4.2 Participants
The demographic profile of the participants included age, gender, employment status,
level of education, and range of total monthly household income. There were 100 total
respondents. The Participants are online users that went to a restaurant or food stall that the
participant saw on the internet. The deployment process is composed of two phases. First, the
questionnaire was deployed to participants who are in the food stalls and admitted that they
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are online users. Secondly, a questionnaire was deployed to individuals who posted reviews
of their experience in food stalls.
The participants were composed of 45.40% male and 54.60% female recruited via
convenience sampling. The average age of the participants is 25 years old. Of the 100
participants, about 38.10% are employed, 12.40% self-employed, 17.50% unemployed, 32%
student. In terms of the level of education, 8.20% of the participants were below high school
graduate, 6.20% high school graduate, 3.10% vocational degree holder, 41.20% college
undergraduate and 41.20% college graduate. Based on the participants total monthly income,
about 40.20% were under Php20,000, 36.10% under Php50,000 and 23.70% higher than
Php50,000.
4.3 Measures
Vinerean et al.,(2013) mentioned that there are four types of online users, these were used
as constructs in the study. The first construct is the Engagers because they seek and read
different forums and reviews, but they also get involved by posting comments and reviews,
rate sites, products, and services. Engagers always want to know more, but they also want to
let others know about their opinions regarding different subjects. The second construct is the
Expressers and Informers. They get involved in the online environment but they are mostly
focused on their experiences and not of others. Expressers and Informers provide information
about themselves through blogging, Twitter and uploading wiki articles. However, Expressers
and Informers are individuals who stay current, particularly by using the Rich Site Summary
(RSS) which allows users to access updates to online content in a standardized, computer-readable
format, and then by staying current with different sources of information. The third construct
is the Networkers or Socializers because they are particularly involved in social media sites
like Facebook, Twitter, Instagram, and YouTube. The Networkers are very vocal and engage
in actions like updating their profiles regularly, posting comments to their friends and tagging
pictures. The last construct is the Watchers and Listeners, it consists of internet users who
have a minimum activity online. Watchers and Listeners, only choose to engage in online
activity that is entertainment-driven (e.g., watching movies, TV shows, videos, listening to
music, and downloading music or video).
Table 1: Research Questions Used to Measure What Types of Online Users are the Respondents
Constructs Research Questions loading in each construct
Networkers or
Socializers
10 questions
Adding labels or tags to photos online.
Updating profile on other social networks.
Adding comments to other people’s social media.
Liking other people’s social media posts.
Sharing other people’s posts.
Updating personal account.
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Reading reviews and ratings in social media.
Reading blogs.
Engagers
4 questions
Watching a video.
Voting on various sites.
Scrolling through social media news feeds.
Updating personal blog.
Expressers and Informers
4 questions
Uploading articles and news on social media.
Uploading Videos on YouTube and/or other video streaming websites.
Contributing to online forums and discussion on groups.
Watchers and Listeners
3 questions
Downloading music.
Downloading videos.
Listening to music.
Note: Participants were requested rate the questions using a six-point Likert scale.
The questionnaire used in the study is composed of three parts. The first part is the
respondents’ personal information, the second part is the consumers’ Social Media usage
information, and the third part is the consumers’ Social Media activity. The questionnaire is
designed to determine which social media platform and social media activities influence the
purchase of food and dine-in to restaurants. The premise is that social media users can be
classified based on the different activities they perform online.
4.4 Procedure for Data Gathering
Convenience sampling was used in the study. The first part was designed to get the profile
of the respondents. Participants were given a survey question during their stay on the
restaurants or if they have been into purchasing food or dining in restaurants that they saw on
social media. First, the questionnaire was deployed to participants who are in the food stalls
and admitted that they are online users. Secondly, a questionnaire was deployed to individuals
who posted reviews of their experience in food stalls. All the respondents were given the
same instruction to determine their social media usage and their social media activity. The
respondents were also assured that the responses would be held highly confidential.
4.5 Data Analysis
There are many social media platforms that are available today but the study considered
some of the most used. And based on the 100 respondents, 67% of them used Facebook the
most, 8.20% Instagram, 6.20% Twitter, 17.5% Youtube and only 1% who used other social
media platform (see Appendix 1). Also, the frequency of social media profiles of the 100
participants tend to log in and about 70.10% are always connected, 3.10% are every three
days, 20.60% are online several times a day, and 3.10 % answered they were online once a
week and occasionally (see Appendix 2). Based on the participants engagement in social
media, only 1% have been using social media platforms for 1 to 6 months and also 6 months
to 1 year, 4.10% were using social media for 1 to 2 years and 2 to 3 years, and 89.70% are
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using social media for more than 3 years (see Appendix 3). The participants were also
influenced by social media to dine in restaurants. Out of 100 participants, 21.60% are Highly
Influenced by social media to visit and dine in restaurants, 49.50% Influenced, 10.30%
Indifferent and Somewhat Not Influenced, and 8.20% Not Influenced at All (see Appendix 4).
The research methodology involved the use of descriptive statistics in describing the
demographic profile of the participants. Pearson’s correlation was used to identify the
relationship of constructs validated. In this study, Pearson's correlation was used to test the
linear relationship between the variables and to identify if a positive or negative relationship
is present. The correlation was used to testing within groups and as the basis for the statistical
model. In testing the research hypothesis, Structural Equation Modelling (SEM) using path
analysis was used to determine the online user's underlying characteristics in terms of social
media convergence leading to purchase intention in the restaurant industry. The SEM was
used to show the causal relationships between the variables. The relationships shown in SEM
represent the hypotheses of the study. Exploratory Factor Analysis (EFA) was used to
determine the constructs in the questionnaire which resulted to networkers and socializers;
engagers; expressers and informers; watchers and listeners. The EFA was used to identify
latent variables and/or constructs. It was used to reduce many individual items into a fewer
number of dimensions and was used to simplify data, by reducing the number of variables in
regression models.
4. Results and Discussion
Data gathered from the modified social media impact to purchase intention
questionnaire was subject to correlation to find the relationship between the constructs. The
instrument underwent construct validity in SPSS which can perform highly complex data
manipulation and analysis. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy
indicates that there is an adequate sample (.770). The Bartlett's Test of Sphericity also
indicates sufficient correlations, thus factor analysis can be used. No problem variables were
seen in the generated pattern matrix. Coefficients were suppressed to 0.46. Table 2 shows that
there are four factors loading labeled as Networkers and socializers; engager; expressers and
informers; watchers and listeners. The reliability of factors for networkers and socializers,
engagers, expressers and informers, watchers and listeners were .829, .725, .728, and .728,
respectively. Table 2 also shows that there are six items loading in networkers and socializers,
five items were loading in engagers, four items were loading under expressers and informers,
and three items were loading under watchers and listeners. There were 18 items in the
modified instrument, and all the 18 items loaded. Principal components with varimax rotation
were used to determine the factor loadings. The factors achieved construct validity as there
were no two items loading in the same factor. Reliability was moderate for all factors.
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Table 3 shows the descriptive statistics. Networkers and Socializers has a mean score of
4.010 (SD=1.010), engager, expressers, and informers, and watchers and listeners obtained a
mean score of 4.369, 2.503, and 4.357 with a standard deviation of .824, 1.115, and 1.217
respectively. Table 3 shows that the distribution of the sample is skewed.
Table 2: Results of the Principal Components, Varimax Rotation, Factor Loadings > 0.46, N=100
Networkers
and
Socializers
Engagers
Expressers
and
Informers
Watchers and
Listeners
Adding labels or tags to photos online .821
Updating profile on other social
networks .753
Adding comments to other people’s
social media .688
Liking other people’s social media posts .660
Sharing other people’s posts .611
Updating personal account .577
Reading reviews and ratings in social
media .761
Reading blogs .729
Watching a video .631
Voting on various sites .549
Scrolling through social media news
feeds .532
Updating personal blog .831
Uploading articles and news on social
media .781
Uploading Videos on YouTube and/or
other video streaming websites .612
Contributing to online forums and
discussion on groups .493
Downloading music .865
Downloading videos .862
Listening to music .516
Cronbach's alpha .829 .725 .728 .728
Table 3: Descriptive Statistics of Measures, N=100
Measures Mean Std. Deviation Skewness
Networkers and Socializers 4.010 1.010 -0.345
Engagers 4.369 0.824 -0.564
Expressers and Informers 2.503 1.115 0.500
Watchers and Listeners 4.357 1.217 -0.168
Note: Participants were requested rate the questions using a six-point Likert scale.
Table 4 shows that there is a low positive significant relationship between engagers and
networkers and socializers (r=.454). This means that if an online user is an engager, there is a
tendency that the individual is a networker and socializer. There is a low positive significant
relationship between expressers and informers, and networkers and socializers (r=.418) which
means that if an online user is an expresser and informer there is a chance that the individual
is a networker and socializer. There is also a low positive significant relationship between
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being watchers and listeners and networkers and socializers (r=.326) which means that if
an online user is a watcher and listener there is a possibility that the individual is a networker
and socializer. There is also a high positive significant relationship between frequency and
online convergence (r=.651). This means that the higher the frequency of use of social media
platforms, there is a higher contribution to online convergence. Additionally, there is a low
positive significant relationship between watchers and listeners and social media platforms
(r=.378), which means that when an online user is a watcher and listener there is a tendency
that the individual uses social media platform. Subsequently, social media platforms have a
high positive significant relationship with online convergence (r=.748) which means social
media platforms and online convergence shares the same features. Lastly, it is most important
to note that, online convergence has a low positive significant relationship with influence to
visit a restaurant or dine-in (r=.230). This means that the higher the online convergence, the
higher the tendency to visit a restaurant or dine-in.
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Tab
le 4
. P
ears
on’s
Corr
elat
ion A
mong M
easu
res,
N=
10
0
Net
wo
rker
s
and
So
cial
izer
s
1
En
gag
e
rs 1
-0.1
29
Ex
pre
sser
s an
d
Info
rmer
s
1
-0.0
94
0.1
39
Wat
cher
s an
d
Lis
ten
ers
1
.22
2*
-0.0
17
0.0
62
Onli
ne
Conver
gen
ce
1
.748**
.651**
0.2
03
.230*
Soci
a
l
Med
i
a 1
0.2
17
.387*
*
0.1
15
-
0.0
03
-
0.0
01
Fre
quen
cy
1
.256*
0.1
69
.219*
-0.0
14
0.1
22
-0.2
02
No
te. *
p<
0.0
5, ** p
< 0
.01
Engag
em
ent 1
.346**
.326**
0.1
32
0.1
46
-0.0
81
0.2
66
-0.2
59
Infl
uen
ced t
o
din
e-in
1
.45
4*
*
.42
8*
*
.32
6*
*
0.0
28
0.1
19
-0.0
47
.21
5*
-0.1
69
Net
wo
rker
s
and
So
cial
izer
s
En
gag
ers
Ex
pre
sser
s
and
Info
rmer
s
Wat
cher
s
and
Lis
ten
ers
On
lin
e
Co
nv
ergen
c
e
So
cial
Med
ia
Fre
qu
ency
En
gag
emen
t
Infl
uen
ced
to d
ine-
in
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Figure 2: Modified Model for Social Media Platforms To Online Consumers’ Intention
Figure 2 shows how social media user impacts other social media users and social media
platforms. The Figure 2 shows that Networkers and Socializers have a probability of being
Expressers and Informers, Engagers, and Watchers and Listeners by 17.47%, 20.21%,
10.63% respectively. Figure 2 also shows that Expressers and Informers is 11.97% of
Engagers, and Engagers is 10.63% of Watchers and Listeners. The Figure 2 also present that
Engagers has an impact of 7.07% on social media engagement, and Watchers and Listeners
have an impact of 14.98% on social media platforms. Subsequently, the frequency of use and
social media platforms impacts online convergence by 42.38% and 55.95%, respectively.
Lastly, online convergence impacts influence to purchase by 5.29%.
5. Conclusions and Recommendations
The study revealed that influence to visit a restaurant or dine-in can be attributed to
different factors such as online convergence, social media platforms, the frequency of use and
types of social media user. The theoretical model developed in this study showed that
different social media users through online convergence can influence consumers to visit a
restaurant or dine-in. Social media not only impacts consumers but also businesses who
exploit its free-of-charge, and faster and accessible advantages. The study contributed to the
many untapped types of research in the area of consumer behavior, social media influences,
marketing and advertising, and food advertising.
The existing literature is suggesting that there are four types of online consumers.
However, the work of Vinerean et al (2013) focused on the participants from the western
context. When the constructs used by Vinerean et al (2013) were used in Southeast Asia, the
20.612%
10.628%
14.977%
7.076%
42.380% 11.972%
10.628%
17.472%
Frequency Expressers
and Informers
Networkers
and
Socializers
Engagers
Watchers and
Listeners
Engagement
Social Media
Online
Convergence
Influence to
Purchase
55.950%
5.29%
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study suggested that there are only one types of online social media user i.e., Watchers and
Listeners. This type of online user is basically composed of Networkers and Socializers,
Engagers, and Expressers and Informers. Although it may be true that social media users can
be categorized into four types such e.g. networkers and socializers, engagers, expressers and
informers, and watchers and listeners, the present research has a clear contribution in
redefining the type of online users in the Southeast Asian region. The study also revealed that
online convergence can be predicted by factors including different social media platforms and
its frequency of use. The watchers and listeners need to be influenced by other types of online
users for it to be active in online convergence.
6. Directions for Future Research
This study was subjected to limitations that can provide valuable advantages to future
research. Firstly, the research is only limited to participants who are consumers of the
restaurant industry. This area suggests that future research could expand by tapping other
industries (e.g., clothing, electronics, transportation etc.). Secondly, the study did not include
in its analysis the demographic variables, such as age, sex, monthly income, educational
attainment of the participants which could also be a factor to purchase intention. This can be
considered in future research.
Since the questionnaire was only made available in the Philippines, there is a possibility
that definitions of the four types of social media users can change depending on geographical
location and culture. Future research can test this hypothesis by deploying the questionnaire
in other regions (e.g., East Asia, South Asia). Lastly, since the study made use of the
quantitative research method, there are limitations that can be associated with this technique
which includes limited outcomes, inability to control the environment and difficulty in data
analysis. Future research could utilize the qualitative method in order to come up with more
details in human behavior, emotion, and personality as results.
Appendices
Appendix 1: Social Media
Valid Frequency Percent Valid
Percent
Cumulative
Percent
Facebook 65 67 67 67
Instagram 8 8.2 8.2 75.3
Twitter 6 6.2 6.2 81.4
YouTube 17 18.5 17.5 99
Others 1 1 1.2 100
Total 97 100 100
Global Journal of Emerging Trends in e-Business, Marketing and Consumer Psychology (GJETeMCP)
An Online International Research Journal (ISSN: 2311-3170)
2018 Vol: 4 Issue: 1
578
www.globalbizresearch.org
Appendix 2: How Often Do You Go Online
Valid Frequency Percent Valid
Percent
Cumulative
Percent
Always Connected 68 70.1 70.1 70.1
Every Three Days 3 3.1 3.1 73.2
Several Times A Day 20 20.6 20.6 93.8
Once A Week 3 3.1 3.1 96.9
Occasionally(Less Than
Once A Week) 3 3.1 3.1 100
Total 97 100 100
Appendix 3: For how long have you been using social media
Valid Frequency Percent Valid
Percent
Cumulative
Percent
1 to 6 Months 1 1 1 1
6 Months to 1 Year 1 1 1 2.1
1 to 2 Years 4 4.1 4.1 6.2
2 to 3 Years 4 4.1 4.1 10.3
More than 3 Years 87 89.7 89.7 100
Total 97 100 100
Appendix 4: Are you influenced by Social Media to visit and dine in restaurants
Valid Frequency Percent Valid
Percent
Cumulative
Percent
Highly Influenced 21 21.6 21.6 21.6
Influenced 48 49.5 49.5 71.1
Indifferent 10 10.3 10.3 81.4
Somewhat Not Influenced 10 10.3 10.3 91.8
Not Influenced At All 8 8.2 8.2 100
Total 97 100 100
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