The Impact of Social Media Platforms to Online Consumers...

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

www.globalbizresearch.org

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,




Michael B. De Mesa,




Marie Jessica V. Buenaventura,




Jaypy T. Tenerife,




___________________________________________________________________________

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

mailto:[email protected]








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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




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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




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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%




577


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




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Appendix 2: How Often Do You Go Online


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


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


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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