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Master Thesis

Company Use of Social Media—A Study on Tasks and

Communication Performance

Ziyan Zong

10389733

11

th

December 2014

Faculty of Science

Master Information Science – BIS

Supervisor: dr. D. Heinhuis

 

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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

 

 

 

 

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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.

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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.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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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:

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- 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.

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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).

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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 Description Targeted platform

Cvijiki & Michahelles

(2011)

Product(s)

announcement Announcement of new product launch

Facebook

Information Information regarding a sales location, number

of page fans, etc.

Design Question Posts in form of questions with a goal to engage

users in a dialog.

Questioner Using the Facebook Poll to obtain answers on a

specific question.

Competition Posts related to competition, i.e. announcements,

rules winners, etc.

Advertisement Advertisement of existing products (mostly used

in a form of photo post).

Statement Posts in form of statement, stating opinion on

certain topic

Hong (2011)

Entertainment

Postings Postings that amuse users.

Facebook Information

Postings Postings that provide information to the user

Promotional Postings

Postings that highlight a contest, promotion, coupon, or any type of offer intended to attract attention from followers and encourage them to participate in some way.

Social Postings Postings that foster user participation, usually by

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users.

Ryan, Peruta and Chouman (2013)

Event The post/tweet is promoting some time-based

activity (online or offline).

Facebook and Twitter Contest

The post/tweet encourages participation from online community by competing with each other (whether or not there is a reward for winning) Special

Promotion The post/tweet promotes a special offer.

Product

Promotion A product or service is being advertised.

Brand-Related

The post/tweet if it makes reference to the brand 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.

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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.

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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

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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 Tasks Findings

Suh (1999) E-mail, telephone, video conferencing, face to face Intellective and Negotiation tasks

No task-medium interaction effects were found on either decision quality or decision time. Decision quality was the same for both tasks among the four different media.

Dennis& Kinney (1998) Audio-Video, computer-mediated communication Low equivocality and High 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.

Mennecke et al. (2000) Face to face, videophone, telephone and synchronous computer mediated communication Negotiation task and intellectual task

The result of negotiation task supported MRT. However, the result of intellectual task did not support MRT.

El-Shinnawy & Markus (1997)

E-mail and voice mail Information 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.

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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 Variety

Immediacy of Interaction

Parallelism Rehearsability Reprocessability

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

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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

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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).

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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:

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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  

   

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Table 4. Kruskal-Wallis Test

Dependent Variables Task Type Mean Rank p

Information scale Story Sharing 14.50

0.008**

Entertainment 9.00

Interaction 3.50

Promotion 7.00

Entertainment Story Sharing 7.75

0.005**

Entertainment 14.50

Interaction 2.50

Promotion 9.25

Promotion Story Sharing 9.00

0.005**

Entertainment 7.75

Interaction 2.75

Promotion 14.5

Interaction Story Sharing 8.13

0.027** Entertainment 5.38 Interaction 14.38 Promotion 6.13 * Significant at p<0.05 level ** Significant at p<0.01 level

Table 5. Kruskal-Wallis Test Post Hoc

Scale Task Type I Task Type J p

Interaction Scale Interaction

Story Sharing 0.027**

Entertainment 0.019**

Promotional 0.020**

Story Sharing Scale Story Sharing

Entertainment 0.019**

Interaction 0.019**

Promotional 0.017**

Promotional Scale Promotional

Story Sharing 0.019**

Entertainment 0.019**

Interaction 0.019**

Entertainment Scale Entertainment

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.

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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

% N Gender Male 48.4 125 Female 51.6 133 Age 18-28 89.9 232 29-40 8.1 21 Above 40 1.9 5

Education High School 4.7 12

Bachelor 46.9 121

Master 41.9 108

PhD 6.6 17

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

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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

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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.

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Table 7. Summary of ranks on attitudes toward tasks

N Mean Ranks Sum of Ranks

Entertainment Task Facebook 26 34.52 897.50

Twitter 38 31.12 1182.50

Story Sharing Facebook 34 30.24 1028.00

Twitter 31 36.03 1117.00

Promotion Facebook 32 36.19 1158.00

Twitter 36 33.00 1188.00

Interaction Task 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 Mean Rank Sun of Ranks

Entertainment Task Facebook 26 31.08 808.00

Twitter 38 33.47 1272.00

Story Sharing Facebook 34 33.53 1140.00

Twitter 31 32.42 1005.00

Promotion Facebook 32 31.14 996.50

Twitter 36 37.49 1349.50

Interaction Task Facebook 31 30.50 945.50

Twitter 30 31.52 945.50

Table 10. Mann-Whitney test on Engagement Rate

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

Mann-Whitney U Sig.

Entertainment 457.00 .610

Story Sharing 509.00 .812

Promotion 468.50 .185

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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.

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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.

7. Reference

Ajzen, I. & Fishbein, M., 1977. Attitude-behavior relations: A theoretical analysis and review of empirical research. Psychological Bulletin, 84(5), pp.888–918.

Baker, B.O., Hardyck, C.D. & Petrinovich, L.F., 1966. Weak Measurements vs. Strong Statistics: An Empirical Critique of S. S. Stevens’ Proscriptions nn Statistics. Educational and Psychological Measurement, 26(2), pp.291–309. Available at: http://epm.sagepub.com/cgi/doi/10.1177/001316446602600204 [Accessed December 7, 2014].

Brodie, R.J. et al., 2013. Consumer engagement in a virtual brand community: An exploratory analysis. Journal

of Business Research, 66(1), pp.105–114. Available at:

http://linkinghub.elsevier.com/retrieve/pii/S0148296311002657 [Accessed July 11, 2014].

Burnkrant, R.E. & Unnava, H.R., 1995. Effects of Self-Referencing on Persuasion. Journal of Consumer

Research, 22(1), pp.17–26. Available at: http://www.jstor.org/stable/2489697.

Cvijikj, I. & Michahelles, F., 2011. A Case Study of the Effects of Moderator Posts within a Facebook Brand

Page, Springer-Verlag Berlin Heidelberg. Available at:

http://link.springer.com/chapter/10.1007/978-3-642-24704-0_21 [Accessed October 8, 2014].

Daft, R. & Lengel, R., 1986. ORGANIZATIONAL INFORMATION REQUIREMENTS , MEDIA RICHNESS AND STRUCTURAL DESIGN. Management science, 32(May 2014), pp.554–571. Available at:

http://pubsonline.informs.org/doi/abs/10.1287/mnsc.32.5.554 [Accessed July 10, 2014].

Daft, R.L. & Lengel, R.H., 1986. Organizational information requirements, media richness and structural design.

Management science, 32(5), pp.554–571.

Davenport, S.W. et al., 2014. Twitter versus Facebook: Exploring the role of narcissism in the motives and usage of different social media platforms. Computers in Human Behavior, 32, pp.212–220.

Davenport, S.W. et al., 2014. Twitter versus Facebook: Exploring the role of narcissism in the motives and usage of different social media platforms. Computers in Human Behavior, 32, pp.212–220. Available at: http://linkinghub.elsevier.com/retrieve/pii/S0747563213004536 [Accessed July 10, 2014].

Dennis, A., Fuller, R. & Valacich, J., 2008. Media, Tasks, and Communication Processes: A Theory of Media Synchronicity. MIS quarterly. Available at: http://dl.acm.org/citation.cfm?id=2017395 [Accessed September 18, 2014].

Dennis, A. & Kinney, S., 1998. Testing Media Richness Theory in the New Media: The Efects of Cues, Feedback, and Task Equivocality. Information Systems Research, 9(3), pp.256–274. Available at: http://pubsonline.informs.org/doi/abs/10.1287/isre.9.3.256 [Accessed September 18, 2014].

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