Master Thesis
Company Use of Social Media—A Study on Tasks and
Communication Performance
Ziyan Zong
10389733
11th December 2014
Faculty of Science
Master Information Science – BIS
Supervisor: dr. D. Heinhuis
1 TABLE OF CONTENTS ACKNOWLEDGEMENT .................................................................................................................................. 3 ABSTRACT ........................................................................................................................................................ 4 1. INTRODUCTION ......................................................................................................................................... 5 1.1 BACKGROUND ........................................................................................................................................................... 5 1.2 PROBLEM STATEMENT ........................................................................................................................................... 5 1.3 PRACTICAL RELEVANCE ........................................................................................................................................ 6 1.4 ACADEMIC RELEVANCE ........................................................................................................................................ 6 1.5 THE STRUCTURE OF THE THESIS .......................................................................................................................... 6 2 LITERATURE REVIEW ............................................................................................................................... 7 2.1 CONCEPTIONS RELATED TO SOCIAL MEDIA .................................................................................................... 7 2.1.1 Facebook and Twitter ........................................................................................................................................ 7 2.1.2 Company Page ..................................................................................................................................................... 7 2.1.3 Company Activities on Facebook and Twitter ......................................................................................... 8 2.2 PRIOR MEDIA RESEARCH .................................................................................................................................... 11 2.2.1 Media Richness Theory ................................................................................................................................. 11 2.2.2 Media Synchronicity Theory ........................................................................................................................ 13 3. HYPOTHESIS DEVELOPMENT ............................................................................................................ 13 4. METHODOLOGY ...................................................................................................................................... 17 4.1 PRE-TEST .................................................................................................................................................................. 17 4.2 MAIN STUDY .......................................................................................................................................................... 19 4.2.1 SAMPLE DESCRIPTION AND PROCEDURE .................................................................................................. 19 4.2.2 Variables and Measurements ...................................................................................................................... 20 4.2.3 Data Analysis ..................................................................................................................................................... 20 5. RESULTS .................................................................................................................................................... 21 6. CONCLUSIONS AND DISCUSSIONS ..................................................................................................... 22 6.1 CONCLUSIONS ........................................................................................................................................................ 22 6.2 THEORETICAL IMPLICATIONS ........................................................................................................................... 23 6.3 MANAGERIAL IMPLICATIONS ........................................................................................................................... 23 6.4 LIMITATIONS AND FUTURE RESEARCH ......................................................................................................... 23 7. REFERENCE .............................................................................................................................................. 24 APPENDIX I: DIFFERENT TASKS .............................................................................................................................. 27 APPENDIX II ITEMS USED IN PRE-TEST .................................................................................................................. 29 APPENDIX III SURVEY QUESTIONS IN THE MAIN RESEARCH ......................................................................... 29 2 Acknowledgement
This thesis would not have been possible without the guidance and help several individuals who contributed or
extended their valuable assistance. First and foremost, I need to say thanks to Dr. Dick Heinhuis for acting as
my guide and mentor. His patience and encouragement has greatly contributed to my ability to complete this
thesis. I would also like to express my appreciation to the people who helped me to distribute my online survey
via their personal networks as well as all the respondents fill in that questionnaire. Last but not least, I would
like to thank all my family and friends for helping me and supporting me.
I am very pleased with the result, and hope you enjoy reading my thesis.
3 Abstract
Companies are shifting their communication with consumers to social websites, and Facebook and Twitter are
the most popular social websites. Facebook and Twitter allow companies to establish their own page and carry
out different types of tasks—story sharing task, promotional task, entertainment task and interaction task.
According to an observation on companies’ activities on Facebook and Twitter, some companies carry out the
same type of task on Facebook and Twitter, and, however, some other companies have a special preference on
different platforms. Based on this phenomenon, this research focuses on whether the communication
effectiveness of the same task on Facebook and Twitter is different.
A pre-test was conducted to see whether the four tasks (story sharing task, promotional task, entertainment task
and interaction task) are significantly different from each other. The conclusion from the pre-test was that the
four tasks are significantly different from each other.
For the main test, a questionnaire (N=258) was developed to test whether there is a communication
effectiveness difference across Facebook and Twitter. The results show that there is no significant
communication performance difference for all the four tasks (story sharing task, promotion task, entertainment
task, and interaction task) across Facebook and Twitter.
The results confirm the conclusion that implementing the same type of task on media with similar capabilities
will lead to similar communication performance. The results go along with both media richness theory and
media synchronicity theory. Moreover, the findings also suggest that there is no need for companies to have
different preferences on Facebook and Twitter.
4 1. Introduction
1.1 Background
Recently, Social web becomes an important part of people’s everyday life: people contact friends, extract news,
and share their own life on social websites. The business also takes advantage of the social web for branding. A
lot of companies established their own Facebook (fun) page and Twitter account in order to have better
communication with their customers. Companies place brand posts (containing videos, messages, quizzes,
information, and other material) on their company pages. According to Mccarthy & Williamson (2012),
companies could spend about $10.93 billion for marketing on social websites in 2014. The social websites have
become a new battlefield for branding. The main reason for companies to add social media to their marketing
and communication strategy is to increase market exposure/brand awareness, increase store and/or website
traffic and increase customer engagement, which will also help the company to leverage the reach and multiplier
effect of social networks, identify and engage top influencers, and give consumers a good reason to share
brand-related content(Ryan & Zabin 2010) . Moreover, in 2012, there are about 55% of social media users who
follow brand on social websites (Moerdyck 2012). Hence, we can see that the Facebook brand page and brand
Twitter account are powerful tools for companies to build their brand.
1.2 Problem Statement
An observation on the brand pages of a number of companies from different industries was conducted. An
interesting phenomenon that some companies just post the same messages on Facebook and Twitter while other
companies publish different posts on Facebook and Twitter is then aroused. The first industry being explored is
fast food industry. Burger King, McDonald, KFC and Pizza Hut are explored at first. By surveying burger king
Facebook and Twitter page, it is noticed that the majority of Burger King Twitter postings are to amuse their
followers. Although their Facebook page also posts funny postings, the other kinds of posts, like new product
introduction, promotion and question asking, hold the same portion. KFC UK and McDonald’s UK are similar
to Burger King: they post more funny messages on Twitter than on Facebook. Pizza Hut UK is different from
BK, KFC and McDonald. The posts of Pizza Hut UK on Facebook are mostly promotional posts (e.g. special
offer and coupon). However, all different kinds of messages can be found from its Twitter and each type holds a
relatively equal portion. Some other companies from food/drink industry are also researched, such as Starbucks
UK and Subway UK&Ireland. For those companies, they just post the same messages on Facebook and Twitter.
This phenomenon exists in other industry as well. For example, the airline companies (KLM UK and Esay Jet):
the two companies also differently manage their Facebook and Twitter. For KLM UK, it publishes more
promotional message on Twitter than on Facebook. However, Easy Jet is different from KLM and it post more
promotional message on Facebook than on Twitter. This phenomenon can also be found in smart phone industry.
Two companies in smart phone industry are surveyed—Samsung and Huawei. Samsung just publishes the
exactly same message on Facebook and Twitter, but Huawei manages Facebook and Twitter differently. Hence,
based on my observation on company pages from different industries, an interesting question is aroused whether
company need to differentiate their management of Facebook and Twitter and whether the same type of
message have the same effect on Facebook and Twitter.
Based on the phenomenon observed above, the research question is summarized as “is there a difference in
communication performance between Facebook and Twitter”. In order to answer this research question, a
number of sub-questions need to be answered. The sub-questions are as followings:
-
What kinds of tasks do companies fulfill on their company page?
5 -
Are Facebook and Twitter media with different media capabilities?
-
How to measure communication effectiveness on Facebook and Twitter?
1.3 Practical Relevance
As mentioned above, lots of companies have already realized the importance of social media for marketing and
maintaining customer relationships as mentioned already. The majority of companies has adopted more than one
social media sites—Facebook and Twitter are the most popular two. Through their official accounts on
Facebook/Twitter, the brands can communicate with their funs and interact with them through message, videos
or pictures. After explored a couple of brand pages on Facebook and Twitter, I noticed an interesting
phenomenon that some brands post the same messages on both Facebook and Twitter, while some brands post
different messages. As companies put more attention to social media theses days, it is important as well as
interesting to look into companies’ use of social media, such as the effectiveness of their posts.
1.4 Academic Relevance
A number of comparative studies on Facebook and Twitter have been conducted, but most the research just
compares Facebook and Twitter in a very superficial level without a structured framework. Meanwhile, these
comparisons are targeted at the individual use not at company use. For example, Hughes et al. (2012), studying
the individual use of Facebook and Twitter about whether a preference for Facebook or Twitter was associated
with differences in personality, just compared Facebook and Twitter on number of users and the individual
interaction mode: Twitter is different from Facebook as “Twitter reinstate some of the anonymity previously
sought in online communication”. Another example of this is Davenport et al. (2014)’s study on the role of
narcissism in the motives and usages of Twitter versus Facebook. Davenport et al. (2014) also compare
Facebook and Twitter from individual use dimension and the nature and functionality features, especially
adding contracts, of Facebook and Twitter. Hence, the comparison between Facebook and Twitter from
company usage perspective needs to be conducted and there is also a need to develop a framework to compare
Facebook and Twitter. This thesis will contribute to the literature on the comparison between Facebook and
Twitter，as a comparison framework will be developed in this study as well as the comparison will focus on
company use.
1.5 The structure of the thesis
The rest of the thesis is organized as follows. The first section depicts some basic definitions related to social
media, the activities companies conducted on their page, and some prior media researches can be used for the
comparison of Facebook and Twitter. In the first section, the sub-question on tasks that companies carry out on
Facebook and Twitter is answered and a number of media capabilities can be used for the comparison between
Facebook and Twitter are summarized. Then, in the second section, 8 hypotheses are conducted based on the
comparison between Facebook and Twitter. In this section, the media capabilities of Facebook and Twitter are
compared and some possible measures of communication performance are discussed. The third section
introduces the research methodology, including sample, measurements, and analysis method. Then the results of
data analysis will be explained. In the end, discussions, limitations and conclusions of this study will be
discussed.
6 2 Literature Review
In this research, the main focus is the communication between business and their customers via Facebook and
Twitter brand page/account. Hence, in order to show a clear conduct of this research, some basic concepts
related to social media, such as the concepts related to Facebook, Twitter and company fun page, will be
described at first. And then the tasks companies implementing on their pages are going to be discussed. In the
last part of this section, several media research is reviewed in order to extract media capabilities for the
comparison between Facebook and Twitter.
2.1 Conceptions related to social media
2.1.1 Facebook and Twitter
Facebook allows users to create their own profiles with their personal information, including personal
photograph, occupation, religion, political views, music and movie taste, etc. Another important function of
Facebook is that users can “friend” other site users (Smith et al. 2012). Facebook users also participate in a wide
range of activities such as writing on friends’ walls, commenting on links, participating in forum discussions,
and “liking” brands (Shaun W Davenport et al. 2014). Facebook also provides customized privacy settings in
detail. Facebook allows users to build and maintain social relationships, communicate with others, keep up with
other people’s movements, and discover rumors and gossips.
Twitter is an online social networking site providing users micro-blogging service. There are four major
characteristics of Twitter. Firstly, it provides various ways for message exchange, including SMS, RSS, instant
message, email, and third party applications. Secondly, users can post messages that are within 140 characters.
This message can contain hyperlinks to news stories, blogs, pictures, etc. Moreover, users are allowed to reply
to, forward (retweet) and favorite those posts. The last characteristic is that Twitter allows users to follow and
receive messages from other users unilaterally, which means that users do not need approval to follow other
people and receive their messages. Based on the characteristics of Twitter, people’s intention of using Twitter is
more on the sharing of opinion and information rather than on reciprocal social interaction (Hughes et al. 2012).
These characteristics also distinguish Twitter as an effective communication, industrial and marketing tool.
2.1.2 Company Page
Brand pages are non-user profiles, which are for business, brands and organization to share their stories and
connect with people. Brand pages reflect part of the customers’ attitude towards the brand, expand the
brand-customer relationship, and provide information and benefits to the users. On the brand page, companies
can publish brand posts containing text, photos, videos, and other materials; brand funs can then interact with
these brand posts by liking or commenting on them.
Several studies focus on why business creates brand fun page/account and publishes information on it. The
reasons can conclude as followings. Firstly, it helps companies generate exposure for their business in order to
increase the traffic of their websites (Stelzner 2011). The second reason is business wants to have a closer
distance with consumers. Establishing brand page/account on Facebook and Twitter will allow them to directly
connect with consumers (Zhao & Rosson 2009).
7 2.1.3 Company Activities on Facebook and Twitter
In this section, the tasks companies fulfilled on social media websites will be discussed. The major activity that
companies performed on their Facebook/Twitter page is to share content with their followers. Different content
types show the different tasks companies carried out on their company pages. Hence, in order to discuss
companies’ tasks embedded in social media on a more detailed level, the content types of company posts need
to be addressed at first. Table 1 shows a summary of research on posting categories (Ryan et al. 2013; Cvijikj &
Michahelles 2011; Hong 2011).
Table 1 Summary of research on posting categories
Source
Category
Product(s)
announcement
Information
Design Question
Description
Targeted platform
Announcement of new product launch
Information regarding a sales location, number
of page fans, etc.
Posts in form of questions with a goal to engage
users in a dialog.
Cvijiki &
Michahelles
(2011)
Questioner
Competition
Advertisement
Statement
Entertainment
Postings
Information
Postings
Hong (2011)
Using the Facebook Poll to obtain answers on a
Facebook
specific question.
Posts related to competition, i.e. announcements,
rules winners, etc.
Advertisement of existing products (mostly used
in a form of photo post).
Posts in form of statement, stating opinion on
certain topic
Postings that amuse users.
Postings that provide information to the user
Postings that highlight a contest, promotion,
Promotional
coupon, or any type of offer intended to attract
Postings
attention from followers and encourage them to
Facebook
participate in some way.
Social Postings
Postings that foster user participation, usually by
asking a question or for direct feedback from
8 users.
Event
The post/tweet is promoting some time-based
activity (online or offline).
The post/tweet encourages participation from
Contest
online community by competing with each other
(whether or not there is a reward for winning)
Ryan, Peruta and
Chouman (2013)
Special
Promotion
Product
Promotion
Facebook and
The post/tweet promotes a special offer.
Twitter
A product or service is being advertised.
The post/tweet if it makes reference to the brand
Brand-Related
itself in some way (visual design, organization,
etc.)
Based on the research on message content types, tasks that companies performed on social media can be
concluded as story sharing task, entertainment task, promotional task, and interaction task. A thorough
discussion on every task is shown as followings：
Sharing Story. The aim of this task is to share
company/brand/product
information
based
on
company/brand/product itself. Several posing content
categories can fit this communication aim, i.e. product(s)
announcement, information post and advertisement post
(Cvijiki
&
Michahelles,
2011),
event,
product
promotion and brad related post (Ryan, Peruta and
Chouman, 2013), and information postings (Hong
2011). The image on the left shows an example of story
sharing task. This message says “Smooth and nutty –
Colombia Narino Origin Espresso is perfect with your
favorite chocolate treat”, which gives information on a
specific product. Hence, this one is categorized into the
storing sharing task.
9 Entertainment.
The
second
type
of
task
companies performed on their brand page is
amusing their funs, which is concluded from
entertainment posting (Hong 2011). The task of
entertainment provides followers a sense of
enjoyment and amusement. In order to entertain
the followers, companies may post some funny
movies or pictures that are not specifically
related to the company/brand. Figure 2 is an
example of entertainment task. As it contains a
funny picture that a bird-shaped bush is trying to
drink Frappuccino, this posting can be viewed as
a message that carries out the entertainment task.
Promotion. This task aims to share promotional
information to their followers, which is based on
the competition posts (Cvijikj & Michahelles 2011),
contest posting and special promotion post (Ryan et
al. 2013), and the promotional postings (Hong 2011)
The promotional information normally includes
contest
or
advertise
about
specific
product
promotions. One example of promotion task is
shown in figure 3. The message in figure 3 displays
a special offer that you can get a free coffee if you
say COCOA to your barista.
10 Interact with followers. Companies adopt the way of
asking
followers
questions
to
implement
the
task—interacting with followers. In Cvijiki &
Michahelles (2011), designed questions, questioner,
and statement all give followers a chance to answer
questions or give direct feedback to the postings, and
thus can be seen as messages that carry out the
interaction task. Similarly, the social postings from
Hong (2011) can also be viewed as post that requires
interaction. Figure 4 shows a message that gives the
followers a change to answer the question that how
do you like your latte. Hence it belongs to the task of
interacting with followers.
2.2 Prior media research
In order to explore whether companies need to differentiate the management of their official Facebook page and
Twitter account, literatures on media typologies are going to be studied.
Theses studies distinguish media
along different dimensions for example, channel characteristics (e.g. Daft & Lengel, 1986; Dennis, Fuller, &
Valacich, 2008; Dennis & Valacich, 1999; Trevino, Lengel, & Daft, 1987), social presence(e.g. R. E. Rice, 1993;
R. Rice, 1992), and uses and gratifications (e.g. Perse & Courtright, 1993). In this study, the channel objective
characteristics are adopted to differentiate Facebook and Twitter. Although the objective characteristics do not
provide a comparison of media on psychological dimensions, they do allow a classification based on the nature
of media, which is relatively error-free (Hoffman et al. 1996). Hence, in this section, some research on media
capability will be discussed.
In the studies that link media capabilities with communication performance, media richness theory should be the
most influential one (Daft & Lengel 1986). Originally, media richness theory is used to classify face-to-face,
telephone, personal documents, impersonal written documents and numeric documents (Daft & Lengel 1986).
Further research extended the original classifications to include email (Trevino et al. 1987), voice mail
(El-Shinnawy & Markus 1997), audio-video (Suh 1999) and computer mediated communication (Dennis &
Kinney 1998). It is clear that media richness is not designed for new media, initially. Dennis & Valacich (1999)
proposed the media synchronicity theory that is specifically designed for new media and can fill the gap of
media richness theory’s weak supporting to new media. Therefore, media richness theory and media
synchronicity are chosen as the fundamental theories for the comparison between Facebook and Twitter.
2.2.1 Media Richness Theory
The first theory going to be discussed here is media richness theory (MRT), proposed by Daft & Lengel (1986),
11 stating that communication media vary in their capacity to process rich information. MRT suggests that richness
(or leanness) is intrinsic objective property of information technologies that serve as communication media, and
managerial use of these media can be described and explained by the intrinsic property. Based on MRT, the
richness of a medium is determined by (1) the availability of instant feedback, making it possible for
communicators to coverage upon a common understanding; (2) the utilization of multiple cues such as body
language to convey interpretations and feelings; and (3) the use of natural language rather than numbers to
convey subtleties (Daft & Lengel 1986). Based on these criteria, the communication media is ranked from “very
rich” to “lean”. Face-to-face is described as the richest medium as it provides immediate feedback so that
interpretation can be checked. It also provides multiple cues via body language and tone of voice, and message
content is expressed in natural language.
According to media richness theory, the fit between task type and media richness will lead to a better
communication performance. For example, the rich media are more suitable for unanalyzable, difficult and
complex issues, such as bargaining, negotiating, complex problem solving, conflict resolving and getting to
know someone. However, lean media are more appropriate for routine activities, such as routine
decision-making, routine information exchanges and personal idea generation (Suh 1999; Rice 1992).
However, a number of studies tested media richness theory using new media, finding that the central proposition
of media richness theory is not supported. Theses studies are summarized in table 2. Hence, new theory needs to
be discussed for a better fit with new media.
Table 2 Summary of literature—Media Richness
Source
Media
E-mail, telephone,
Suh (1999)
video conferencing,
face to face
Tasks
Findings
No task-medium interaction effects were found
Intellective and
on either decision quality or decision time.
Negotiation tasks
Decision quality was the same for both tasks
among the four different media.
Dennis&
Audio-Video,
Low equivocality
Kinney
computer-mediated
and High
(1998)
communication
Equivocality tasks
Matching media richness (set of cues and
feedback time) to task equivocality did not
improve decision quality, decision consensus
change or communication satisfaction.
Face to face,
videophone,
Mennecke et
telephone and
Negotiation task
al. (2000)
synchronous
and intellectual task
computer mediated
The result of negotiation task supported MRT.
However, the result of intellectual task did not
support MRT.
communication
Information
El-Shinnawy
& Markus
(1997)
E-mail and voice
mail
processing in
response to
equivocality and
uncertainty
Media richness theory is supported in situations
involving uncertainty reduction, but in
situations with equivocality reduction it is not
supported.
12 2.2.2 Media Synchronicity Theory
Dennis & Valacich (1999) developed Media Synchronicity Theory, which is a new theory that fills the gap of
media richness theory’s weak findings with new media (Dennis et al. 2008). Instead of focusing on task types,
Media Synchronicity Theory argued that communication is composed of two primary processes: conveyance
and convergence. The level of synchronicity media supports will have different effects on the two processes. For
convergence processes, use of media supporting higher synchronicity will result in better communication
performance (Dennis et al. 2008). However, for conveyance processes, using a medium with lower
synchronicity should bring to a better communication performance (Dennis et al. 2008). Hence, the
communication performance is determined by the fit between a medium’s synchronicity and the fundamental
communication processes being performed. Five media capabilities (symbol sets, parallelism, transmission
velocity, rehersability, and reprocessability) are identified to discover the development of synchronicity and thus
the performance of conveyance and convergence communication. This study finds that the variety of symbol
sets and transmission velocity both have a positive impact on media synchronicity. However, the other three
media capabilities affect media synchronicity negatively. MST can explain some of the unexplained results from
MRT studies. For example, Dennis & Kinney (1998) found that using richer media for equivocal tasks did not
lead to better performance, which does not support MRT. By using MST, this result can be explained:
“When meeting as a group, they had greater need to convey differences in information and their positions
on the task, and less (although not nonexistent) need to converge on decision. In this context, MST
predicts that media emphasizing information transmission more than processing would enable superior
performance. Since the media provided were similar regarding information transmission, on difference in
results would expected. (Dennis et al. 2008)”
Moreover, MST also got support from empirical test. Murthy & Kerr (2003) empirically tested MST in a team
context. They compared the effectiveness of computer-mediated communication and face-to-face
communication on two different tasks—idea generation (the conveyance of information) and problem solving
(requiring information convergence). Their results reveal a general support on MST.
Based on the discussion of media theories, a couple of media capabilities can be summarized: they are symbol
sets, immediacy of interaction, parallelism, rehearsability and reprecessability. The detailed description and
discussion on each capability will be presented in the next section.
3. Hypothesis development
Based on these studies (media richness, and media synchronicity), a number of media characteristics are
extracted to compare Facebook and Twitter. Table 3 shows the comparison between Facebook and Twitter with
respect to 5 objective characteristics.
Table 3 Summary of Trait Comparison Between Facebook and Twitter
Symbol
Sets
Immediacy of
Parallelism
Rehearsability
Reprocessability
Variety
Interaction
Facebook
Medium
Low
Medium
High
High
Twitter
Medium
Low
Medium
High
High
Symbol Sets. This element is extracted from all two theories (R. L. Daft & Lengel 1986; Dennis & Valacich
1999; Dennis et al. 2008). Although both media richness theory and media naturalness theory do not directly
mention this item, they did mention some elements of symbol sets：in media richness, the utilization of multiple
13 cues and, in media naturalness theory, the ability of the media to transmission body languages and facial
expressions. In the MST theory, a more clear and comprehensive definition is carried out—symbol sets. Based
on (Dennis & Valacich 1999), symbol sets are the number of ways in which a medium allows information to be
encoded for communication. Symbol sets may affect the synchronicity supported by a medium in two
fundamental ways. Firstly, the time and effort required to encode and to decode a message using a specific
symbol set might impose production costs (Dennis et al. 2008). The more nature symbols a message carries, the
less effort is needed to encode and decode. Secondly, some information may be more precisely encoded and
decode in one symbol set than another (Dennis et al. 2008).
For both Facebook and Twitter, companies are
able to post texts, pictures, videos, and links. Thus, the overall symbol sets the two media can carry are the same.
However, unlike Facebook, Twitter has limitations on the number of pictures (4 pictures maximize) and
message length (less than 140 characteristics).
Immediacy of Interaction.
Based on Daft & Lengel, (1986), Dennis, Fuller, & Valacich (2008), and Dennis &
Valacich, (1999), immediacy of feedback is the extent to which the media allows the message receiver to give a
fast feedback. The quicker the feedback is, a better behavior coordination and shared focus will exist between
individuals working together. Face-to-face communication holds the highest capability on immediacy of
feedback. Under the context of Facebook and Twitter, immediacy of interaction can be used to express
immediacy of feedback. The term interaction is not just limited to reply (feedback). Some other reactions, such
as “Like” and “share”, are also belongs to interaction. For both Facebook and Twitter, the brand page followers
can choose whether to interact with the post (like, reply or share) or not and when to interact with the post.
Hence, Facebook and Twitter have the same capability (a relatively low level) of enabling fast interaction.
Parallelism. According to (Dennis & Valacich 1999), it is refereed to the number of simultaneous transmissions
that can effectively take place, which is also seen as the width of the medium. In other words, it is the extent to
which signals from multiple senders can be transmitted over the medium simultaneously. The medium with the
highest parallelism is written mail (Dennis et al. 2008), as the sender can send written mails simultaneously and,
meanwhile, these mails can be delivered to the receiver at the same time. For Facebook and Twitter, messages
can be sent by different senders simultaneously, but reach the receiver in a time order. Hence, Facebook and
Twitter share the same level of parallelism and have a medium level capability of parallelism compared with
written letter.
Rehearsability. Rehearsability is the extent to which media enable the sender to rehearse or fine tune a message
during encoding, before sending, which allows message sender to re-edit the message before sending it and
makes sure that the meaning of the message is expressed precisely (Dennis et al. 2008; Dennis & Valacich
1999). Both Facebook and Twitter enable companies to re-edit the post. Company page administrators can
re-edit the message, change a picture or adjust the structure of the post as long as they did not press the sending
button. For Facebook, they can even re-edit your post after you already published it. Hence, Facebook has a
relatively higher level of rehearsability compared with Twitter.
Reprocessability. This characteristic is also extracted from Dennis et al. (2008) and Dennis & Valacich (1999).
It refers to “the extent to which a message can be reexamined or processed again, during decoding, either within
the context of the communication event or after the event has passed”. The information companies published on
Facebook and Twitter will also display on the senders’ page. And the sender can review the past postings
whenever he/she wants if they did not delete them. Face-to-face communication and telephone are media with
weak capability of reprocessability, as the message sender cannot reexamine the message comprehensively after
sending it. Compared with face-to-face communication and telephone, Facebook and Twitter deploy a similar
14 high level of reprocessability as the message will still display on the sender’s page if the sender does not delete
that message.
Based on the comparison above, we can see that Facebook and Twitter carry the same level of capabilities on
Immediacy of Interaction, parallelism and reprocessability. Facebook only has a very slight advantage on the
symbol sets variety and rehearsability. Thus, I propose that Facebook and Twitter are media with the same
media capabilities.
According to media richness theory, the fit between task type and media richness will lead to a better
communication performance (Trevino et al. 1987). In other words, using media with different level of richness
to fulfill the same communication task will lead to different performance. For example, for a bargaining task,
using face-to-face will contribute to a better performance than using e-mail. Facebook brand page and Twitter
brand account are used by business to share their stories and connect with users. The main task of Facebook
page and Twitter account administrators is to publish information and gather user opinion towards their brand or
their products, which can be viewed as routine tasks. Because Facebook and Twitter brand page/account have
same media capabilities and fulfill the same task, the fit between media capabilities and task also share the
similar level. Hence, based on media richness theory, carrying out the same task via Facebook and Twitter will
lead to the same communication performance.
According to MST, the communication performance is determined by the fit between a medium’s synchronicity
and the fundamental communication processes being performed. In the case of communication via brand
page/account, information processing is the fundamental communication process. The synchronicity of media is
determined by media characteristics. Based on table 1 and previous discussion on MST in literature review part,
Facebook and Twitter are poor on synchronicity as they carry a high level of rehearsability, reprocessability, and
parallelism and have relatively weak capabilities to support symbol sets variety and transmission velocity.
Brand page/account of Facebook and Twitter have the same level of synchronicity and focus on the same
fundamental communication process—information processing, which will lead to similar communication
performance. Hence, based on MST, I can also conclude that carrying out the same task via Facebook and
Twitter will lead to the same communication performance.
Hence, based on MRT and MST, a conclusion can be drawn:
Conclusion: the fulfillment of the same task via Facebook and Twitter will lead to the same communication
performance
The communication effectiveness, the dependent variable in this study, is not a specific variable. In previous
research, decision time and decision quality are always used as measures of internal communication
effectiveness (Suh 1999; Dennis & Kinney 1998; Mennecke et al. 2000). However, in this study, instead of
internal communication, external communication is the focus and the communication tasks are also different
from the tasks of internal communication. Hence, some new measures of communication effectiveness need to
be developed.
Attitudes towards the Task. This measure is adopted from advertising literatures. Advertising and company
brand page are both belong to business marketing communication. Hence advertising and company brand page
are similar in nature. The measure of advertising performance can be used as measures of communication
performance on social web sites. Based on Oxford Dictionaries, the word attitude means “A settled way of
thinking or feeling about something. According to the explanation in the dictionary, we can see that “attitude”
belongs to psychological category. Under psychology, one commonly agreed description of “attitude” is that
one person’s attitude represents one person’s evaluation of an entity in question (Ajzen & Fishbein 1977).
15 Constantly with the definition in psychology, attitude towards ads is defined as “pre-disposition to respond in a
favorable or unfavorable manner to a particular advertising stimulus during particular exposure occasion”
(Lutz 1985; MacKenzie & Lutz 1989). And studies on the effectiveness of advertising do show that attitude
towards adverting has an effect on advertising effectiveness. MacKenzie et al. (1986) found that attitude toward
advertising has a mediation effect on the performance of advertising on brand attitude and purchase intention.
Moreover, Lavidge & Steiner (1961) categorized advertising measurements into: 1) Over-all or “global”
measurements, concerned with measuring the results—the consumers’ positions and movement on the purchase
steps; 2) Segment or component measurements, concerned with measuring the relative effectiveness of various
means of moving people up the purchase steps. According to this statement, attitudes toward ads have a mediate
effect on the final purchasing and hence can be viewed as advertising effectiveness measures that belongs to the
second category. Hence, based on advertising literatures, attitudes towards task is defined as pre-disposition to
respond in a favorable or unfavorable manner to a particular message stimulus during particular exposure
occasion. Users’ attitude toward tasks has a direct effect on brand consumer relationship. Thus, attitudes toward
task can also be viewed as the secondary measurements of communication effectiveness via Facebook and
Twitter. Based on the conclusion on communication effectiveness drawn above, user attitude towards the same
task will be similar across Facebook and Twitter. The four hypotheses are as follows:
Hypothesis 1: Sharing story via Facebook and Twitter will lead to the similar user attitudes.
Hypothesis 2: Entertain followers via Facebook and Twitter will lead to the similar user attitudes.
Hypothesis 3: Promotion via Facebook and Twitter will lead to the similar user attitudes.
Hypothesis 4: Interacting with followers via Facebook and Twitter will lead to similar user attitudes.
Engagement Rate. The other measure introduced is engagement rate. Engagement rate is a specific measure of
the communication effectiveness of social media. The concept of engagement rate comes from relationship
marketing literature—consumer engagement. Consumer engagement is defined as the intensity of customer’s
participation in and connection with an organization’s offerings and/or activities that are initiated by either the
consumer or the organization (Vivek et al. 2012). A high level of customer engagement shows customer trust
towards brand, brand loyalty, satisfaction, and emotional connection with the brand (Brodie et al. 2013). Wirtz
et al. (2013) pointed out that consumer online brand community engagement could bring the brand a number of
benefits: idea generation for improved products and services, firm structure integration and adjustment, and the
improvement of brand image and relationship with customers. Similarly, Brodie et al. (2013) studied consumer
engagement under the context of online community and found that a high level of consumer engagement may
lead to consumer loyalty and satisfaction, consumer empowerment, connection and emotional bonding, trust and
commitment. Additionally, Gummerus et al. (2012) addressed that consumers engage in online brand
community in order to get the following benefits: practical benefits (informational and instrumental benefits),
social benefits (recognition or even friendship), entertainment benefits (relaxation and fun) and economic
benefits (discounts and time savings). In other words, from the customer perspective, higher customer
engagement means higher level of perceived benefits and the company page can provide the benefits they
required. Hence, engagement rate can be treated as a measurement of communication effectiveness via
Facebook and Twitter.
Based on the conclusion on communication effectiveness drawn above, the engagement rate the same task will
be similar on Facebook and Twitter. The four hypotheses are as follows:
Hypothesis 5: Sharing story via Facebook and Twitter will lead to the similar user engagement rate.
16 Hypothesis 6: Entertain followers via Facebook and Twitter will lead to the similar user engagement rate.
Hypothesis 7: Promotion via Facebook and Twitter will lead to the similar user engagement rate.
Hypothesis 8: Interacting with followers via Facebook and Twitter will lead to similar user engagement rate.
4. Methodology
In this thesis, the brand, Starbucks, is used. Starbucks was chosen because it is a well-known brand—an
international coffee company with thousands of chain coffeehouses. They communicate with their customers via
both Facebook and Twitter. The messages I extracted are from Starbucks United Kingdom Facebook and
Twitter page. The reason I chose Starbucks UK is as followings. Firstly, based on the observation described in
introduction section, the phenomenon of posting different types of messages on Facebook and Twitter
commonly exists in food/drink industry and Starbucks belongs to food/drink industry. Secondly, Starbucks is a
world famous brand and has stores in over 65 countries1. And it is well known for its coffee products. In the
Netherlands, you can also find Starbucks coffeehouses at major railway stations, airport and city center. Hence,
people live in the Netherlands are familiar with the products of Starbucks. Thirdly, the reason I chose Starbucks
UK page instead of Starbuck global page is that it is difficult to find the promotional information on the global
website due to regional differences. Additionally, another reason for choosing UK instead of other countries is
UK is an English speaking country.
4.1 Pre-test
A pre-test was conducted to see if the content of the four different tasks were significantly different from each
other, and if they were perceived as story sharing, entrainment, promotion and interaction tasks. The terms used
in the pre-test are shown in Appendix (II). In the pre-test, four different types of tasks are shown with a picture
and some text. Each task displayed the one of the four types (story sharing, entertainment, promotion and
interaction). The participants need to evaluate every task by using the items in Appendix (II). Based on this
logic, if a task is perceived as story sharing task, then it should score highest on the information scale. There are
four pre-tests in total. Kruskal-Wallis Test post hoc is adopted to test the difference of the four types of task.
Kruskal-Wallis Test is adopted at first. The results are shown in table 4. Kruskal-Wallis Test is non-parametric
method to test whether there are any significant differences between the median/means of two or more
independent groups. From the results, it is easy to find that story sharing scores highest on the information scale,
entertainment task scores highest on the entertainment scale, promotion task scores highest on the promotion
scale and interaction task scores highest on the social scale. Moreover, the results also show that there is a
significant difference among the four types of tasks in all four dimensions. However, the two tests can only tell
whether there is a significant difference between groups not which of the specific groups differed. The post hoc
analysis conducts multiple comparisons to test how groups different from each other. The results of
Kruskal-Wallis Test post hoc analysis are shown in table 5. The following paragraphs provide explanations to
the results listed in table 5.
1 See http://www.starbucks.com/business/international-­‐stores 17 Table 4. Kruskal-Wallis Test
Dependent Variables
Task Type
Information scale
Entertainment
Promotion
Interaction
Mean Rank
Story Sharing
14.50
Entertainment
9.00
Interaction
3.50
Promotion
7.00
Story Sharing
7.75
Entertainment
14.50
Interaction
2.50
Promotion
9.25
Story Sharing
9.00
Entertainment
7.75
Interaction
2.75
Promotion
14.5
Story Sharing
8.13
Entertainment
5.38
Interaction
14.38
Promotion
6.13
p
0.008**
0.005**
0.005**
0.027**
* Significant at p<0.05 level
** Significant at p<0.01 level
Table 5. Kruskal-Wallis Test Post Hoc
Scale
Interaction Scale
Story Sharing Scale
Promotional Scale
Entertainment Scale
Task Type I
Interaction
Story Sharing
Promotional
Entertainment
Task Type J
p
Story Sharing
0.027**
Entertainment
0.019**
Promotional
0.020**
Entertainment
0.019**
Interaction
0.019**
Promotional
0.017**
Story Sharing
0.019**
Entertainment
0.019**
Interaction
0.019**
Story Sharing
0.019**
Interaction
0.019**
Promotional
0.019**
* Significant at p<0.05 level
** Significant at p<0.01 level
Story Sharing task vs. promotional, entertainment and interaction task. The story-sharing task is significantly
different from interaction (p<0.01), entertainment (p<0.01) and promotion (p<0.01) tasks on the interaction
scale.
18 Interaction task vs. story sharing, promotional and entertainment task. Interaction task is significantly different
from story sharing (p<0.01), entertainment (p<0.01) and promotion (p<0.01) tasks on the interaction scale.
Promotional task vs. story sharing, entertainment and interaction task. There is also a significant difference
among promotion tasks, story sharing task (p<0.01), interaction task (p<0.01), and entertainment task (p<0.01)
on the promotion scale.
Entertainment task vs. story sharing, promotional and interaction task. The entertainment task also differ from
the other three tasks—story sharing (p<0.01), promotion (p<0.01) and interaction (p<0.01)—on the
entertainment scale.
In summary, the results of pre-tests do reveal that every task scores highest on its own scale and the mean value
of that task on its own scale is significantly greater than the other three tasks, indicating that the participants do
perceive them as different tasks and also perceive them as story sharing, promotion, entertainment and
interaction tasks. Therefore the four examples I extracted from Starbucks UK can be viewed as representatives
of story sharing task, entertainment task, promotional task and interaction task.
4.2 Main Study
4.2.1 Sample Description and Procedure
Participants of this study were invited to fill in the questionnaire via a link displayed on personal social
networks. Snowball sampling method is deployed in this study. 10 initial informants are selected. The ten initial
informants contain both students and working professionals with different backgrounds—information science,
business administration, finance, biology and chemistry. They not only post the link on their own timeline, but
also post it to Facebook groups, such as their study groups, working groups and community groups. The
questionnaire was online for two weeks. In this research, a total of 260 started the survey, and 258 of them
finished the survey. After cleaning the invalid data, the sample size of this study is N=258. Gender was divided
in 48.4% male (N=125) and 51.6% female (N=133). Most of the respondents fit in the age range from 18 to 28
(89.9% and N=232). The demographic also showed that most of the respondents are highly educated—46.9% of
them are Bachelor (N=121) and 41.9% of them got their masters (N=108). Table 6 shows a summary of
respondent’s social demographic data.
Table 6 Social demographic data of respondents
Gender
Age
Education
%
N
Male
48.4
125
Female
51.6
133
18-28
89.9
232
29-40
8.1
21
Above 40
1.9
5
High School
4.7
12
Bachelor
46.9
121
Master
41.9
108
6.6
17
PhD
The questionnaire was distributed online (Qualtrics.com). The questionnaire started with a short introduction
towards the purpose of this research. In the second part of the questionnaire, a number of demography questions
19 about age, gender, and education are asked. The third part of the questionnaire is the stimulus. The stimulus
consisted of the four types of messages from the two different platforms (Facebook and Twitter). Here, a 2x4
factorial design using between-subjects experiment is conducted. The participants were shown one of the four
types of messages from ether Facebook or Twitter, which is randomly assigned to participants.
For example,
one participant will see a screenshot of promotional message from Twitter and another may see a story sharing
task from Facebook, and they need to answer a couple of questions based on the message they saw. These
different tasks could be found from the Appendix (I).
4.2.2 Variables and Measurements
4.2.2.1 Dependent Variables
In this research, the effectiveness of communication for companies by using Facebook and Twitter is going to
be tested. Hence, the dependent variable of this research is communication effectiveness. However,
communication effectiveness is not a variable can be directly measured. Two sub variables—attitudes towards
task and user engagement rate are adopted to measure communication effectiveness. The items measure the
dependent variables can be found in Appendix III.
Attitudes toward the task. Based on MacKenzie & Lutz (1989), attitude towards the task is defined as
pre-disposition to respond in a favorable or unfavorable manner to a particular message stimulus during
particular exposure occasion. Followers’ attitudes toward brand posts shows their affective reactions on the
posts. People’s attitudes toward task are measured by 7-point likert scale with three items: good to bad,
favorable to unfavorable and positive to negative based on Burnkrant & Unnava (1995). The scale’s alpha
reliability is .919.
Engagement Rates. The second measure of communication effectiveness is engagement rate. User engagement
is a sign of cognitive commitment to the post. Engagement rate measures how well the followers interact with
the brand posting. Under the context of Facebook and Twitter, people can interact with the message by liking,
sharing and commenting. Hence, the users’ willingness to like, share or comment a message is used to measure
the engagement rate. A higher level of engagement rate indicates that the posts impressed more users. de Vries
et al. (2012) used the number of likes and comments to measure the popularity brand post. All questions
employed a 7-point likert scale from 1 (strongly disagree) to 7 (strongly agree). This scale’s alpha reliability
is .843.
4.2.2.2 Independent Variables
The independent variable of this research is different task types (story sharing, promotion, entertainment or
interaction) plus different platforms (Facebook or Twitter). Although the different tasks are already discussed in
previous section, here, I will also give a short description to every task type. The story-sharing task gives some
insights of the brand/product. Promotion task displays a special offer, coupon or contest. The entertainment task
is to use jokes, funny pictures or interesting videos to amuse users. In the last, the interaction task is to publish
something that calls for user participate and interact with that particular post.
4.2.3 Data Analysis
For the main study, Mann-Whitney test has been chosen as the method to test the hypotheses. Likert-scales are
used in this study to measure people’s attitudes toward the task and people’s engagement rate. There are four
main types of scales of measurement: nominal, ordinal, interval and ratio (Stevens 1946). For different types of
20 scales, different statistics can be applied to analysis. For example, mean and standard deviation can be applied to
the analysis of interval data, and median can be adopted for ordinal data (Stevens 1946). In the academic world,
the researchers hold controversial attitudes towards likert-scale. Some of them hold the point that like-scale data
are ordinal (e.g. Jamieson 2004 and Vaughan 2001), but still other scholars think that liket-scale data can be
treated as interval data and parametric methods can be applied to them (e.g. Baker et al. 1966 and Labovitz
1967). In this this study, the former point of view is adopted: likert-scale data are ordinal. The reasons are that 1)
likert scale shows the rank order of data and 2) the difference between 1 and 2 is not equal to the difference
between 2 and 3. Hence, a method that compares the median should be deployed. Based on Vaughan (2001),
Mann-Whitney test can be used to test the hypothesis of differences between two independent populations when
the data are in ordinal form. In other words, Mann-Whitney test is the nonparametric counterpart of the
independent t test. Therefore, a total of 8 Mann-Whitney tests are conducted in this study to test whether there is
a significant difference between Facebook and Twitter on consumer attitudes toward different tasks and
engagement rates. SPSS 20 is used for data analysis.
5. Results
For the main study, the effectiveness of each task (story sharing, entertainment, promotion, and interaction) on
Facebook and Twitter is compared. Table 7 and table 8 are results of the comparison between task type and
platform on attitudes toward tasks. Table 9 and table 10 are the results of comparison of people’s willingness to
engage with different tasks across Facebook and Twitter. In the following paragraphs, the hypotheses will be
discussed in pairs—the hypotheses with the same type of tasks will be discussed together.
Based on the results, Hypotheses on sharing story via Facebook and Twitter will lead to similar communication
performance is supported on both attitudes toward tasks scale (U=433.00, p>0.05) and engagement rate scale
(U=509.0, p>0.05). In other words, that there will be no difference on communication effectiveness when using
Facebook and Twitter for the story sharing tasks. Hence, hypothesis 1 and hypothesis 5 are both supported.
The results also showed that there is no difference between Facebook and Twitter on amusing users. People hold
similar attitude toward entertainment postings (U=441.50, p>0.05) and a similar level of engagement rate
(U=457.00, p>0.05). Therefore, hypothesis 2 and hypothesis 3, stating that amusing followers via Facebook and
Twitter will lead to similar user attitudes toward tasks and willingness to engage, are supported.
The 3rd and 7th hypothesis are related to promotional tasks. Results show that the effectiveness of fulfilling
promotional tasks on Facebook is not significantly different from conducting promotional task on Twitter,
meaning that people’s attitudes towards promotional tasks (U=552.00, p>0.05) and willingness to engage with it
(t=468.50, p>0.05) are not significantly different across Facebook and Twitter. Hereby, hypothesis 3 and
hypothesis 7 are supported.
The results of Mann Whitney U tests in table 8 and table 10 supported hypothesis 4 and hypothesis 8 that
interacting followers via Facebook and Twitter will lead to semblable effect—similar attitudes toward task and
engagement rates. Results (see table 8 and table 10) indicate that there is no performance difference, on both
attitudes scale (U=403.00, p>0.05) and engagement rate scale (U=449.50, p>0.05), between Facebook and
Twitter when implementing interaction tasks, so hypothesis 4 and hypothesis 8 are supported.
In summary, the results supported all eight hypotheses. More specifically, the communication performance of
the four different types of tasks (story sharing task, promotional task, entertainment task and interaction task) is
not significantly different across Facebook and Twitter.
21 Table 7. Summary of ranks on attitudes toward tasks
N
Entertainment Task
Story Sharing
Promotion
Interaction Task
Mean Ranks
Sum of Ranks
Facebook
26
34.52
897.50
Twitter
38
31.12
1182.50
Facebook
34
30.24
1028.00
Twitter
31
36.03
1117.00
Facebook
32
36.19
1158.00
Twitter
36
33.00
1188.00
Facebook
31
29.00
899.00
Twitter
30
33.07
992.00
Table 8. Mann-Whitney test of Attitude towards tasks
Mann-Whitney U
Sig.
Entertainment
441.50
.464
Story Sharing
433.00
.209
Promotion
552.00
.501
Interaction
403.00
.363
Table 9. Summary of Ranks on Engagement Rate
N
Entertainment Task
Story Sharing
Promotion
Interaction Task
Mean Rank
Sun of Ranks
Facebook
26
31.08
808.00
Twitter
38
33.47
1272.00
Facebook
34
33.53
1140.00
Twitter
31
32.42
1005.00
Facebook
32
31.14
996.50
Twitter
36
37.49
1349.50
Facebook
31
30.50
945.50
Twitter
30
31.52
945.50
Table 10. Mann-Whitney test on Engagement Rate
Mann-Whitney U
Sig.
Entertainment
457.00
.610
Story Sharing
509.00
.812
Promotion
468.50
.185
Interaction
449.50
.821
6. Conclusions and Discussions
6.1 Conclusions
In this study, the communication effectiveness of different types of tasks across Facebook and Twitter is
discussed. Based on literatures on message content types of Facebook and Twitter, four different types of tasks
22 that companies carried out on their company page are summarized—story sharing tasks, promotional tasks,
entertainment tasks and interaction tasks. And then a conceptual framework for the comparison between
Facebook and Twitter is developed. According to the framework, the conclusion that Facebook and Twitter are
media with the same media capabilities is drawn, deducting that the communication effectiveness will not be
significantly different when implementing the same task on Facebook and Twitter. User’s attitudes toward tasks
and engagement rate are used to measure communication effectiveness. The results of our study show that
people’s attitude towards the same task and willingness to engage with that task are not significantly different
across Facebook and Twitter.
6.2 Theoretical Implications
The first theoretical implication is that the results support media richness theory and media synchronicity theory.
Different from previous studies proving the ineffectiveness of media richness theory on new media (e.g. Suh
1999; Dennis & Kinney 1998), the findings of this study go along with media richness theory. One possible
explanation is that this study compared the communication effectiveness of two media with similar capabilities,
however the other studies drew on media with different capabilities. Moreover, this study also goes along with
media synchronicity theory, providing empirical support to Dennis & Valacich (1999).
Secondly, based on media theories, the media capabilities of Facebook and Twitter are compared. The results
show that Facebook and Twitter are similar media platform. This finding goes against previous comparison
between Facebook and Twitter (e.g. Hughes et al. 2012; Shaun W. Davenport et al. 2014; Kwon et al. 2014),
stating that Facebook and Twitter are different. The previous comparisons major focused on the functionality
differences between Facebook and Twitter, such as the anonymity attributes of Twitter, however the focus of
this study is on media capabilities. One possible explanation to this is that the difference in functionalities will
not affect media capabilities. Moreover, most of those previous comparisons are focused on the individual use
of Facebook and Twitter, but the focus of this study is company use of Facebook and Twitter, which may also
explain the different results of the comparison.
6.3 Managerial Implications
Managers of brands that operate company pages can be guided by our research with respect to what they post to
Facebook and Twitter. In reality, different company pages have different communication styles and strategies.
For example, Burger King implements more entertainment task on Twitter than on Facebook. However,
Starbuck UK just carries out the same task on its Facebook and Twitter. This research shows that different types
of task have the same effectiveness on Facebook and Twitter, meaning that users have similar attitudes towards
and similar level of willingness to engage with the same tasks on Facebook and Twitter. This finding indicates
that companies do not need to have different task preferences on Facebook and Twitter. Hence, companies do
not need to differentiate on the management of their Facebook and Twitter page. They just need to carry out
tasks that can best reflect their distinct brand traits and that users like the most.
6.4 Limitations and Future Research
This study had several limitations. First, the sample size of this study is relatively modest, and the respondents
are recruited via snowball sampling, resulting in the over-representation of young people. The phenomenon of
over-representation of young respondents may cause that it is questionable to apply these findings to other
populations.
23 The second limitation is related to the data analysis method adopted in this study. According to Vaughan (2001,
153~154), the power of nonparametric tests is relatively lower compared with their corresponding parametric
tests. In other words, nonparametric tests are less likely to find a difference when do have one, indicating that
there is a chance that the difference is not figured out. However, if the parametric method is applied, the result
may also not be accurate as likert-scale is ordinal data.
In the end, in this study, Starbuck UK is chosen mainly because the phenomenon of conducting different tasks
on Facebook and Twitter page is commonly existed in food and drink industry. However, based on the survey
describe in introduction section, you can also find this phenomenon among airline companies (KLM and Easy
Jet) and mobile communication companies (Huawei and Samsung). Hence, future research can focus on other
company to further validate my study.
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8. Appendix
Appendix I: Different tasks
Story Sharing task:
27 Entertainment Task:
Promotion Task:
28 Interaction Task:
Appendix II Items used in pre-test
Story sharing (Jourdan 1999, 5-point Likert Scale, strongly disagree to strongly agree):
-
This message provide me something about the product/brand
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After reading this message, I feel more capable and competent to choose and evaluate this type of
products.
Entertainment (Ducoffe 1995, 5-point Likert Scale, strongly disagree to strongly agree):
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This message is funny.
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This message is enjoyable
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This message is cool
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This message is exciting
Promotional(Rog 2014, 7-point likert scale, strongly disagree to strongly agree):
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This message shows the information of a contest.
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This message shows an offer.
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This message displays a coupon.
Interaction (Gao et al. 2010, 5-point Likert Scale, strongly disagree to strongly agree):
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The message makes me feel that the company wants to listen to me.
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The message gives me a chance to respond in more than one way (like, share, comment).
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The message provides me an opportunity to give feedback.
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This message can create a conversation between the company and the customer.
Appendix III Survey questions in the main research
Demography questions
29 -
Gender
-
Age
-
Where do you live?
-
Education Background
Attitude towards the post (7-point Likert Scale):
How do you like the message?
-
Bad – Good
-
Unfavorable – Favorable
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Negative - Positive
Engagement Rate (7-point Likert Scale, strongly disagree to strongly agree):
-
If I saw this message on my timeline/wall, I would like to like the message.
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If I saw this message on my timeline/wall, I would like to leave a comment.
-
If I saw this message on my timeline/wall, I would like to share/retweet this message.
30