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The Determinants of the Mobile Instant Message Usage by Alan Liu Eric Tai Sanyar Cheng Terena Kuo Tiffany Liu 2013 GPAC Business Administration Group 1 National Cheng-Chi University, Taiwan
The Determinants of the Mobile Instant Message Usage
by
Alan Liu
Eric Tai
Sanyar Cheng
Terena Kuo
Tiffany Liu
2013 GPAC
Business Administration Group 1
National Cheng-Chi University, Taiwan
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Content
I. INTRODUCTION ......................................................................................................................... 1
I-1. MOTIVATION AND BACKGROUND................................................................................................... 1
I-2. MOBILE INSTANT MESSAGE (MIM) ............................................................................................... 2
I-3. PURPOSE OF STUDY ........................................................................................................................ 3
II. LITERATURE REVIEW ............................................................................................................. 3
II-1. DEVELOPMENT OF SHORT MESSAGE SERVICE (SMS)................................................................... 3
II-2. SMS VS. MIM ............................................................................................................................... 4
II-3.ADDITIONAL FUNCTIONS: AUDIO MESSAGE AND LAST LOGIN TIME............................................. 5
II-4.SOCIAL TENDENCY ........................................................................................................................ 5
III. METHODOLOGY ........................................................................................................................ 6
III-1. RESEARCH FRAMEWORK ............................................................................................................. 6
III-2. DATA COLLECTION...................................................................................................................... 7
III-2-1. Pilot Study........................................................................................................................... 7
III-2-2. Questionnaire...................................................................................................................... 7
III-3. RESEARCH MODEL....................................................................................................................... 8
Y = β0 + β1 IT + β2SMS + β3AM + β4LL + β5SO+ β6SI+ β7SS+ β8SA +β9SL +εi…………..…9
III-4. DATA ANALYSIS .......................................................................................................................... 9
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III-4-1. Factor Analysis ................................................................................................................... 9
III-4-2. Regression Model ............................................................................................................. 11
III-5. FOUR MAIN EFFECTS ...........................................................ERROR! BOOKMARK NOT DEFINED.
III-5-1. Usage of the Internet......................................................................................................... 12
III-5-2. Usage of SMS before the application of MIM .................................................................. 12
III-5-3. Audio Message .................................................................................................................. 12
III-5-4. Last Login Time ................................................................................................................ 12
III-6. MODERATOR.............................................................................................................................. 13
IV. CONCLUSION AND SUGGESTIONS..................................................................................... 14
IV-1. CONCLUSION ............................................................................................................................. 14
IV-1-1. Main effects ....................................................................................................................... 14
IV-1-2. Moderator ......................................................................................................................... 14
IV-2. SUGGESTIONS ............................................................................................................................ 15
V. APPENDIX: QUESTIONNAIRE .................................................................................................I
VI. REFERENCES ............................................................................................................................. V
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I. Introduction
I-1. Motivation and Background
With surge of smartphones and prevalence of mobile Internet service, more and more
people are using mobile applications. An investigation done by FIND 2012 shows that
the number of 3G mobile handsets in Taiwan has increased for more than 5 years (see
graph 1). In the third quarter of 2012, the number of 3G mobile handsets has
amounted to 22.27 million, that is, 75.8% of total mobile handsets. Among all the
functions in smartphones, applications with social function are the most frequently
downloaded applications (see graph 2). (FIND, 2012) From these trends, we can
forecast that with the prevalence of 3G handsets, applications will become more and
more common, especially social network applications. Thus, we want to discover
more and find out the key determinants of the usage of mobile instant message
(MIM).
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Graph 1. Number of 3G Mobile Handsets in Taiwan
Graph 2. Applications Used in Taiwan
I-2. Mobile Instant Message (MIM)
Mobile Instant Message (MIM) is a presence enabled messaging service that aims to
transpose the Internet desktop messaging such as ICQ or MSN experience to the
usage scenario of being connected via a mobile/cellular device. (Kevin Roebuck,
2011) As wireless networks only have existed for a few decades, the history of mobile
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messaging is short and the history of MIM even shorter. In the new report stated by
Juniper Research, it talks about the prospects of MIM services, forecasting that the
number of users will exceed 1.3 billion by 2016. (Daniel Ashdown, 2011)
In other words, MIMs enable people to engage in instant message from a mobile
handset and these messages are sent and received in real-time via mobile handsets
without a stationary computer. The only prerequisite is having the Internet access on
the go - over GPRS, 3G or WiFi.
I-3. Purpose of Study
In this paper, we want to investigate in and analyze the key factors that affect the
usage of MIM. Hopefully we can come up with suggestions that are helpful to MIM
developers.
II. Literature Review
II-1. Development of Short Message Service (SMS)
First appeared in 1992, and by now over 2.4 billion users, or nearly 75 percent of
mobile subscribers, use SMS. (Janssen, 2012) It is the most basic communications
technology for mobile data transfer. After its appearance, SMS has become
indispensable in daily life. Two main reasons contribute to the circumstance. First,
ubiquity: SMS can reach every mobile phone as long as we know the phone number,
no matter what country you are in, which telecommunication companies’ sender and
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receiver you are. Moreover, the prevalence of SMS is also an advantage between
Person-to-Person (P2P), as well as Application-to-Person (A2P). According to
International Telecommunication Union (ITU), 6.1 trillion SMS text messages were
sent in 2010. (ITU, 2010) SMS has become a massive commercial industry, earning
$114.6 billion globally in 2010.
II-2. SMS vs. MIM
MIM has been known to impact the revenue of SMS. Ovum, a technology research
company estimates that the operators’ messaging revenues lost over $23bn in 2012
alone. (Neha Dahlia, 2013) Moreover, MIM users send about 40% fewer text
messages than their non-MIM counterparts. (Gibbs Colin, 2008) According to the
survey results of TNS Global, which interviewed 17,000 respondents across 30
countries, once the mobile user adopt MIM, it overtakes other messaging tools, such
as SMS, to become the primary non-voice method of interacting. While SMS is used
by 55% of mobile phone users daily, MIM is used by 61% of them. The highest
number of MIM users is in Hong Kong (23%). In developing markets (China, 16%;
India, 15%; Brazil, 10%), there is evidence that MIM has leapfrogged other
messaging tools. (Cellular-news, 2013)
With all these developments, one might think this has left SMS out in the cold.
However, in the world of business SMS communications, this is not at all the case.
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According to Matthew Froggatt, Managing Director of Global Technology, there are
some notable exceptions to the ubiquity of SMS messages, like the US - where SMS
did not take off until relatively recently - and Japan - where consumers moved straight
to mobile email. (Cellular-news, 2013)
II-3. Additional Functions: Audio Message and Last Login Time
According to “Media Richness Theory”, a message with high media richness is easier
to understand by receivers. Media richness theory explores a media’s ability to change
receiver’s comprehension in a given time. Users can easily understand message
transmitted by media with high richness. Though low media richness media is also
able to achieve the same object, it takes more time to finish the process. (Daft &
Lengel, 1986) High media richness media provide real-time response, oral or non-oral
presentation and are capable of using natural language to express fact. (Trevino &
Colleagues, 1987) We think that the functions “audio message” and “last login time”
can be classified as high media richness media. Therefore, they can help MIM users to
receive messages more easily and affect the usage of MIM.
II-4. Social Tendency
In the increasingly user-generated Web, users’ personality traits may be crucial
factors leading them to engage in this participatory media. Extraversion and openness
to experiences were positively related to social media use. The relationship between
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extraversion and social media use was particularly important among the young adult
cohort. (Correa, Hinsley, Gil de Zúñiga, 2010) Besides, according to “Social
enhancement theory,” outgoing people often use Internet communication tools to
interact with people, in order to protect themselves in real life interpersonal strengths.
This theory also says that people with extroverted traits tend to use the Internet more
often. (Kraut, 2002) Consequently, outgoing people tend to spend more time on social
media.
III. Methodology
III-1. Research Framework
As stated in the previous chapters, the aim of this study is to find the factors that
explore the usage of MIM. In the former sections, a literature review was done to
explore factors influencing the usage of MIM. The main factors in the literature
review are captured and used in designing the questionnaire and model.
The following factors have been identified for investigation:
Usage of the Internet
Usage of SMS
Audio Message
Last login time
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Figure 4. Research Framework
III-2. Data Collection
The method we use to collect our data can be mainly divided into two parts, as
follows:
III-2-1. Pilot Study
In this study, we employ a pilot study beforehand. The focus of the pilot study is
primarily on the scale of the usage time. We aim at the time the respondents spend on
their smartphones and the time they spend on SMS before the acquisition of MIM. A
detailed questionnaire is developed subsequently, after knowing the approximate
range of the referring question.
III-2-2. Questionnaire
We carry on an on-line questionnaire that is composed of four sections as a structured
survey to collect the primary information. (See Appendix) The questionnaire is
conducted on the website MySurvey. We receive 310 samples and 293 of them are
Y: Usage of MIM
(Measured in minutes)
Usage of SMS
Last Login Time
Audio Message
Usage of the Internet
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valid. The survey was launched on May 22nd 2013 and closed on June 11th 2013, that
is, 21 days in total.
The questionnaire consists of four parts. The first part includes whether the
respondent uses the smartphone and MIM. Only people who have a smartphone and
use the MIM are qualified to fulfill the whole questionnaire. In the second part, the
respondents are asked about the time they spend on the Internet via smartphone and
SMS before the acquisition of MIM deliberately, as well as the functions of MIM they
regard necessary. The third part includes the function “Last login time,” which is
measured by Likert scale. The following part focuses on the traits of the respondents
and is also measured by Likert scale. Take the chosen question for social tendency as
an example; we include talkativeness, number of friends and how much fun a person
enjoys in a party, the referring answers direct to the degree of a person’s social
tendency. The forth part is an open question referring to the MIM usage, including
how much time the respondent spends on MIM in a day and how many people he or
she contacts. The last part of the questionnaire includes certain basic demographic
information.
III-3. Research Model
Regression analysis is used to analyze the linear relationship between the variables.
We construct a multiple regression equation as our model and use the quantified data
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to measure the coefficients:
Y = β0 + β1 IT + β2SMS + β3AM + β4LL + β5SO+ β6SI+ β7SS+ β8SA +β9SL +εi
Where: Y is the usage of MIM (measured in minutes)
IT stands for the usage of the Internet
SMS is the usage of Short Message Service before the adoption of MIM
AM stands for the function “Audio message”
LL stands for the function “Last login time”
SO stands for Social tendency
SI stands for Social tendency x Usage of Internet
SS stands for Social tendency x Usage of SMS
SA stands for Social tendency x Audio message
SL stands for Social tendency x Last login time
εi is the standard error.
The data obtained from the on-line questionnaires are coded and entered into the
SPSS system for further analysis.
III-4. Data Analysis
We use factor analysis and regression model to investigate the results.
III-4-1. Factor Analysis
In the questionnaire, we use nine questions to discuss how different traits might
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influence the usage of MIM. The nine questions are stated below.
I am a talkative person.
I have fun in parties.
I have many friends.
I often check notifications in my phone.
I feel anxious if my phone is not with me.
I always notice the news of new technology products.
I always use new technology products earlier than my friends.
I have the illusion of phone vibration.
It is attractive that I can try the newest version of software.
To come up with a better combination of questions, we use SPSS system to conduct
factors analysis, and the results are shown below.
Components Factor Analysis
1 2
I am a talkative person. 0.877
I have fun in parties. 0.868
I have many friends. 0.954
I always notice the news of new technology products.
0.462
I always use new technology products
earlier than my friends. 0.906
It is attractive that I can try the newest
version of software.
1111
I often check notifications in my phone. 0.831
I have the illusion of phone vibration. 0.627
I feel anxious if my phone is not with me. 0.758
Table 1. Factor analysis for traits
Apparently, we can find that in component 1, there are some questions highly
correlated to each other, which are “I am a talkative person”, “I have fun in parties”,
“I have many friends”, “I often check notifications in my phone”and “I feel anxious if
my phone is not with me.” We conclude these 5 factors and name it “Social
Tendency.” The higher the figure, the higher social tendency the person has.
III-4-2. Regression Model
Y = 0.472 IT +0.141 SMS +0.132 AM +0.089 LL -0.017 SO +0.113 SI -0.045 SS
+0.038 SV -0.029 SL
Coefficient (Significant level=0.1)
Standardized coefficients Adjusted R-Square=31.5%
Beta distribution P-Value
Internet time .472 .000
SMS time .141 .009
Audio message .132 .008
Last login time .089 .072
Social tendency -.017 .749
Social tendency x Usage of Internet .113 .055
Social tendency x Usage of SMS -.045 .405
Social tendency x Audio message .038 .441
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Social tendency x Last login time -.029 .568
Dependent Variable: MIM time
The model shows that there are four determinants, namely the Internet time, SMS
time, audio message and last login time. Moreover, the factor “social tendency” is
considered as a moderator and positively related to the usage of the Internet despite
that it is not significant enough to be an independent variable.
III-5-1. Usage of the Internet
Hypothesis: The usage of the Internet is positively related to the usage of MIM.
Result: β=0.472. Positive.
III-5-2. Usage of SMS before applying MIM
Hypothesis: The usage of SMS before applying MIM is positively related to the
usage of MIM.
Result: β=0.141. Positive.
III-5-3. Audio Message:
Audio message is a kind of message that is formed by recording rather than texting.
Hypothesis: Audio message would facilitate the usage of MIM.
Result: β=0.132. Positive.
III-5-4. Last Login Time:
It is a function that helps the user know when the receiver last login in. Therefore, the
user can determine whether he or she has seen the message.
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Hypothesis: Last login time is positively related to the usage of MIM. People
who view it unacceptable would have less usage of MIM. If the user’s friends
know he or she has seen the message, the user might have the pressure to reply
instantly.
Result: β=0.089. Positive.
III-6. Moderator
The statistics result shows that “social tendency” is a moderator rather than an
independent variable, and has positive relationship with the usage of the Internet. It
implies that the more social a person is, the more time he or she spends on the Internet.
As a result, the more time he or she spends on MIM.
Figure 5. Moderator Graph
The aggregate line shows the whole population, which slope is positive since the
usage of the Internet is positively related to the usage of MIM. The upper line, which
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represents people who socialize more, is steeper (or has a larger slope) and means that
under the same usage of the Internet, these people would have a much higher usage of
MIM. On the other hand, the lower line with smaller slope indicates that under same
usage of the Internet, these people would have less usage of MIM than the average
since they are less social.
IV. Conclusion and Suggestions
IV-1. Conclusion
After analyzing and verifying all the information obtained, it can be concluded that
four main effects and one moderator determine the usage of MIM.
IV-1-1. Main effects
Usage of the Internet: The more Internet usage a user used, the more MIM usage
the user has.
Usage of SMS: The more SMS sent before the adoption of MIM, the higher
MIM usage the user has.
Audio message: Audio message would facilitate the usage of MIM.
Last login time: People who dislike this function tend to have lower usage of
MIM.
IV-1-2. Moderator
Social tendency:
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The more social tendency a person has, the more time he or she spends on the Internet.
Hence, the more time he or she spends on MIM.
All of the main effects are confirmed to be positively related to the usage of MIM and
consistent with the hypotheses we assumed at the beginning of the study. As for social
tendency, we at first assumed it to be a positive factor that directly affects the usage of
MIM. However, it turned out to be a moderator that affects the usage of the Internet
and which in turn affects the usage of MIM.
IV-2. Suggestions
Based on the results of the study, we come up with several suggestions for the MIM
developers. Firstly, we suggest them to target the marketing strategies on heavy
mobile Internet users. Secondly, the developers can improve audio message with a
better quality such as extending the time limit of the recording time. As to last login
time, we think that the developers should make the function enabled manually turned
on or turned off by users, because not everyone likes to let people know the time they
last log in the MIM application. Lastly, according to the research we conducted,
people with higher social tendency have higher usage of MIM. Thus, we recommend
MIM developers corporate with clubs, bars, or places where people gather for group
activities or social support and provide incentives such as free trials or giveaways to
attract potential MIM users to use their MIM application.
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V. Appendix: Questionnaire
PART1: The Using and Understanding of Mobile Instant Message
1. Do you have a smartphone?
□Yes □No
2. Do you use any Mobile Instant Message applications (MIM, will be shown as MIM in the following content), like Line, Whatsapp?
□Yes □No
3. How many hours do you spend on the Internet via smartphone in a typical day?
□ Less than 1 hour □ 1~3 hours □ 3~5 hours □ 5~10 hours □ More than 10
hours
4. How much time do you spend on Short Messages Service a day before the adoption of MIM?
□ 0~15 minutes □ 16~30 minutes □ 31~45 minutes
□ 45~60 minutes □ Above 1 hour
5. Which functions of the MIM do you consider necessary? (Multiple choice)
□ Stickers □ File Attachment □ Group talk □ Audio message
We are students from National Cheng-chi University and this is a questionnaire for
academic research. Our purpose is to find the main determinants of the usage of the
Mobile Instant Message (MIM), such as WeChat, Line, Whatsapp, Facebook
Messenger, etc. You can help us build more information by filling out this
questionnaire. This study is being conducted for research purpose only, your
answers will remain confidential. Thank you!
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PART2: Please mark your level of agreement or disagreement with the following
statements.
6. Strongly
Agree Agree Neutral Disagree
Strongly
Disagree
The charging of MIM is acceptable. (NTD30 per year)
I like the function “Read”. I like the function “Last Login Time”.
It is inconvenient that messages cannot be sent between different MIM platforms.
7. Strongly
Agree Agree Neutral Disagree
Strongly
Disagree
I am a talkative person.
I have fun in parties.
I have many friends.
I often check notifications in my phone.
I feel anxious if my phone is not with me.
I always notice the news of new technology products.
I always use new technology products earlier than my friends.
I have the illusion of phone vibration.
It is attractive that I can try the newest version of software.
PART3: MIM Usage Survey
8. How much time do you spend on MIM a day on average? (On hour or minute
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basis)
______________________________
9. How many people do you contact with MIM in a day on average?
______________________________
PART4: Demographic Data
10. Gender
□ Male □ Female
11. Current location
□ The Northern region (Taipei, Keelung, Taoyuan, Hsinchu)
□ The Central region (Miali, Taichung, Nantou, Changhua, Yunlin)
□ The Southern region (Chiayi, Tainan, Kaoshung, Pingtung)
□ The Eastern region (Yilan, Hualien, Taitung)
12. Age
□ Under 15 years old □ 16~20 years old □ 21~25 years old □ 26~30 years old
□ 31~35 years old □ 36~40 years old □ 41~45 years old □ 46~50 years old
□ 51~55 years old □ 56~60 years old □ Above 60 years old
13. Occupation
□ Student □ Public employees □ IT Industry □ Business and financial industry
□ Service industry □ Manufacturing industry □ Freelance □ Others
14. Highest educational qualification
□ High school graduate □ Bachelor's degree □ Master's degree and above
15. What is your disposable income per month? (Includes allowance and earnings)
□ Less than NTD 6,000 □ NTD 6,001~12,000 □ NTD12,001~18,000
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□ NTD 18,001~24,000 □ NTD 24,001~30,000 □ NTD 30,001~36,000
□ NTD 36,001~42,000 □ NTD 42,001~50,000 □ NTD 50,001 or more
vv
VI. References
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Feb 08, 2013)
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“Who interacts on the Web? The intersection of users’ personality and social
media use.” Computers in Human Behavior, 247–253. Center for Journalism &
Communication Research, School of Journalism, University of Texas at Austin.
3. Daft, Richard L. and Lengel, Robert H. (1986) Organizational Information
Requirements, Media Richness and Structural Design. Journal of Management
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4. Institute for Information Industry. (2013) The Investigation of the application
in Wireless and mobile network in 2012, Taiwan.
http://www.find.org.tw/find/home.aspx?page=many&id=335
(accessed Feb 17, 2013)
5. ITU (International Telecommunication Union). “THE WORLD IN 2010 -
The rise of 3G” Paper presented at ITU.
6. Juniper research. (2013) Daniel Ashdown.
http://www.juniperresearch.com/viewpressrelease.php?pr=248
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(accessed February 16, 2013)
7. Kraut, R., Kiesler, S., Boneva, B., Cummings, J., Helgeson, V., and
Crawford, A. (2002) “Internet paradox revisited.” Journal of Social Issues, 58:
49-75.
8. Ovum. (2013) Neha Dharia. Ovum survey reveals that five services dominate
social messaging.
http://ovum.com/2013/01/04/ovum-survey-reveals-that-five-services-dominate-s
ocial-messaging/ (accessed Feb 08, 2013)
9. RCR Wireless News. (2013) Gibbs, Colin. SMS vs. MIM: Mobile IM usage
small, but growing.
http://www.rcrwireless.com/article/20080503/sub/sms-vs-mim/ (accessed Feb 08,
2013).
10. Roebuck, Kevin. (2011) Mobile Instant Messaging (MIM): High-Impact
Strategies - What You Need to Know: Definitions, Adoptions, Impact, Benefits,
Maturity, Vendors. Tebbo.
11. Statista. (2013) ITU (International Telecommunication Union)
http://www.statista.com/statistics/167048/number-of-sms-sent-per-second-world
wide-since-2007/ (accessed February 16, 2013)
12. Techopedia. (2013) Cory Janssen. Short Message Service (SMS)
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http://www.techopedia.com/definition/24275/short-message-service--sms
(accessed February 5, 2013)
13. Wu, Sheng-shi. (2008): The Study of IM impacts the enterprise employees’
performance. National Yunlin University of Science & Technology, Taiwan.
