Factors influencing Attitude and Intension of Playing Online
Computer Games: A Study of Thai Online Computer Gamers.
Ake Choonhachatrachai
Key words: Online Game, Consumer Behavior, Thailand, Game Industry
Abstract
Today, the online computer games have become one of the most popular leisure
among teenagers. The online computer game industry has developed continuously
and consistently in term of technology and marketing campaign. As such issues have
been frequently raised in the society, some other particular issue such as social
problem affected by playing online computer games still lacking. This study attempts
to find out the attitude of teenagers toward playing online computer games. The
theoretical model used in this study is Technology Acceptance Model (TAM). The
research participants which are Thai teenagers were examined in order to find out
their attitude toward the online computer games by basing on the factors like
perceived usefulness, perceived enjoyment, and perceived ease of use. This study used
quantitative method and deploys non-probability technique. The structure
questionnaire was used as an instrument to gather the data. This study also identified
the sampling frame by scoping down to undergraduate students in Bangkok (ages 1825). As this target respondents usually spends time playing online game at the internet
café. Thus, the survey will be conducted on them by using convenience sample of 1825 year old undergraduate students who come to play online computer games at the
internet café in Bangkok. This study examines factors adopted from Technology
Acceptance Model (TAM) and the factors from conducting an exploratory study. This
study gathering all of the factors together to see how they influence on the attitude
and intension of online computer games players. Combining Technology Acceptance
Model (TAM) with six additional variables, this study has provided both theoretical
and managerial contribution.
Global Markets (1999) estimated that the online user penetration rate has grown up to
39 per cent in non-US (worldwide) sector versus only 21 per cent in US online user.
However, study about online usage still mostly done on American people context.
Consequently, it is worthwhile for researchers to pay more attention to online
consumers in Asia-Pacific countries e.g. Thailand where online games market
continues to grow as local game providers have coordinated with Korean online game
markets to provide new online games in Thailand such as the first major hit online
game of Ragnarok Online (2002) gained 2.36 million subscribers worldwide (700,000
in Thailand), followed by MU Online (2003) that expect to attract 50,000 subscribers
in Thailand (Bangkok Post Data Base, 2003).
This paper focused on consumer’s attitude and intention toward using or playing
online computer games. Such specific technology context is different from other type
of internet usage in several aspects. Firstly, the nature of the product itself which
considerably unique in many characteristics. Unlike other products selling on internet,
online computer games are intangible and having less value compare to other types of
products. While regular online consumers are concerned about disclosing their private
and financial information (Park and Kim, 2003), online computer games consumers
do have less concern on such issue as they can make a purchase without using credit
card by make a payment through cell phone or pre-paid card (www.pangya.com).
Secondly, online computer games also require consumers to spend much more time
with computer than other internet shopping. The more playing time customers
purchased the more time consuming they will have to spend on computer. Some
people spend so much time online that they have not left their homes in more than two
years (Castronova, 2005). Moreover, online computer games also provide different
benefits to the customers as they offer imaginary world that enable people to act out
their dreams (Jennings, 2006). So, it can be said that instead of serving consumer who
have less leisure for store shopping, online computer games are serving those who
want to spend their leisure on the computer screen. Result from this, the past
researches that tried to explore the factors influencing the attitude of online users can
be somewhat differ from the factors influencing the attitude of online computer games
users.
Moreover, researches involving online computer games to date focused mainly on one
game only or asks subjects to respond based on viewing a particular game provided
(Elliot and Fowell, 2000; Fogarty, 2000; Lohse and Spiller, 1998; Jarvenpaa and
Todd, 1996-1997).
Academically, this paper will be expected to contribute a new knowledge about
consumer attitude toward the unique online product like online computer games and
theoretically, this study applies modified TAM model by adding six more correlates
variables namely appearance quality, game play, compatibility, trialability, self
efficacy, and socialization agents to better suit with particular tested product. In
managerial contribution, it will help e-tailers to develop effective strategies for online
computer game products. The information from the finding will also help marketing
managers to understand customer better and to effectively plan their marketing mixes.
Literature review
There are three theories that often used by researchers in studying the behavioral
intention in technological products namely Technology Acceptance Model (TAM),
the Theory of Planned Behavior (TPB), and the Diffusion of Innovation Theory. Most
of these theories have been developed from the Theory of Reasoned Action originally
proposed by Fishbein and Ajzen (1975). For the theory of planned behavior (TPB)
(Azjen, 1985, 1991) is an extension of the theory of reasoned action (TRA) (Azjen
and Fishbein, 1980), made necessary by the latter model’s inability to deal with
behaviors over which individuals have incomplete volitional control. At the heart of
TPB, and TRA, is the individual’s intention to perform a given behavior. For TRA
and TPB, attitude toward the target behavior and subjective norms about engaging in
the behavior are thought to influence intention, but TPB includes perceived behavior
control engaging in the behavior as an additional factor influencing intention.
According to TPB, an individual’s performance of a certain behavior is determined by
his or her intent to perform that behavior. Another relevant theory of this study is
diffusion of innovation theory. DOI theory sees innovations as being communicated
through certain channels over time and within a particular social system (Rogers,
1995). Individuals are seen as processing different degrees of willingness to adopt
innovations and thus it is generally observed that the portion of the population
adopting an innovation is approximately normally distribution into segments leads to
the segregation of individuals into the following five categories of individual
innovativeness (from earliest to latest adopters): innovators, early adopters, early
majority, late majority laggards (Rogers, 1995). The rate of adoption of innovations is
impacted by five factors: relative advantage, compatibility, triability, observability,
and complexity (Rogers, 1995).
Anyway, this study will develop its constructs influencing attitude of online games
purchasers by choosing Technology Acceptance Model (TAM) as model base.
The reasons why TAM has been chosen as a model base for this study are TAM has
been specially built for applications that deal with adoption of information technology
and it is also easy to implement with less complications (Mathieson 1991; Davis,
Bagozzi & Warshaw, 1989). The measurement scales used in TAM of perceived ease
of use and perceived usefulness have also repeatedly been proven to have both high
reliability and validity (Adam, Nelson & Todd, 1992). In addition, TAM was found to
be the most popular theory used by most researchers for studying the behavioral
intention to use technological products and services (Venkatesh & Davis, 2000). As a
result, the Technology Acceptance Model (TAM) then is selected as a model used in
this research and since this study will investigate the factors influencing online game
player’s attitude and online game player’s intention toward online computer games,
the conceptual framework from Technology Acceptance Model (TAM) will be
applied (Figure 1).
Figure 1: Technology Acceptance Model (TAM)
Perceived
Usefulness
(U)
Attitude
toward
Using (A)
External
Variables
Perceived
Ease of
use (E)
Behavioral
Intention to
use
(BI)
Actual
System
Use
Source: Developed from Davis, Bagozzi & Warshaw (1989).
However, with two variables provided in TAM, this study found from the literature
review that there still several other external variable that seem to be interesting and
useful for the product like online computer games. Result from this, the exploratory
study has been conducted on college student age 18-25 that have experience playing
online computer games for at least 50 hours. This believed to strengthen the sources
of information found in the literature review.
Along with perceived usefulness and perceived ease of use that come with TAM,
literature review and exploratory study has provided six more variables in which
combined to be eight variables as follow:
-
Perceived usefulness (PU): "The degree to which a person believes that using
a particular system would enhance his or her job performance". (Davis, 1989)
-
Perceived ease-of-use (PEOU): "The degree to which a person believes that
using a particular system would be free from effort". (Davis, 1989).
-
Appearance quality: Refer to attractiveness, organization, proper use of
fonts, proper use of colours, and proper use of multimedia. (Aladwani, 2006)
-
Game play: A term most commonly used to rate, or score the quality of the
experience had by gamer while playing a game. The term game play is often
found in game reviews where a score is given based on player experiences
during the interaction with game. (www.webopedia.com)
-
Trialability: The ability to sample the product without a major commitment.
(Holak and Lehmann, 1990)
-
Internet self efficacy: The belief in one’s capabilities to organize and execute
courses of internet actions required to produce given attainments. (Hsu, et al,
2004)
-
Compatibility: The ability of the consumer to use it in a way consistent with
past behaviour. (Rogers, 1983)
-
Socialization agent: person or an organization that provides influence through
frequent interaction with an individual, primacy over the individual, or control
over rewards and punishments given to the individual (Brim, 1966)
The above variables were used to test the attitude and intension of playing online
computer games. The expectation of this modified TAM is to help understand the
online computer gamers better. As it expected to contribute both theoretical and
managerial implication, this study has hypothesized that attitude and intension toward
online computer games can be influenced by all of the above factors as follow:
Hypotheses
H1. An online game player’s perceived usefulness has a positive impact on his/her attitude toward
online computer games.
H2. An online game player’s perceived ease of use has a positive impact on his/her attitude toward
online computer games.
H3. An online game player’s perceived ease of use has a positive impact on his/her perceived
usefulness.
H4. An online game player’s perceived usefulness has a positive impact on his/her intension to
play online computer games.
H5. An online game player’s attitude has a positive impact on his/her intension to play online
computer games.
H6. The appearance quality of online computer game has a positive impact on online game
player’s attitude toward online computer games.
H7. The appearance quality of online computer game has a positive impact on online game
player’s intension to play online computer games.
H8. An online game player’s perception of game play has positive impact on his/her attitude
toward online computer games.
H9. An online game player’s perception of game play has positive impact on his/her intension to
play online computer games.
H10. An online game player’s perception of compatibility has positive impact on his/her perceived
usefulness.
H11. An online game player’s perception of compatibility has positive impact on his/her attitude
toward online computer games.
H12. An online game player’s perception of compatibility has positive impact on his/her intension
to play online computer games.
H13. An online game player’s perception of trialability has positive impact on his/her attitude
toward online computer games.
H14. An online game player’s perception of trialability has positive impact on his/her intension to
play online computer games.
H15. An online game player’s internet self efficacy has positive impact on his/her attitude toward
online computer games.
H16. An online game player’s internet self efficacy has positive impact on his/her intension to play
online computer games.
H17. The socialization agent (peers) has positive impact on online game player’s attitude toward
online computer games.
H18. The socialization agent (peers) has positive impact on online game player’s intension to play
online computer games.
Method and methodology
This study uses quantitative techniques. The research design of this study consisted of
six stages which are exploratory research, research instrument construction, testing
the research instruments, selection of participants and data collection methods, data
editing and data analysis. The explanation of each stage is as follows:
Stage 1 The Exploratory Research:
This study has used the exploratory research as the first stage of the research process.
By using the exploratory research, this study expects to better the understanding of
online computer game player’s perception. Exploratory research is normally used as
the first stage of a research process. It is conducted to identify and clarify problems
(Zikmund, 1997). Zikmund (2003) also claimed that exploratory research can help
researchers reach a better understanding of the extent of the research problem.
Similarly, Sekaran (2000) stated that the exploratory study is conducted to clarify the
nature of the research problems. The main objective of the exploratory research is to
narrow the scope of the study and to discover the research problems in order to
specify research objectives (Churchill and Iacobucci, 2002). However, the exploratory
research does have some limitation as Zikmund (1997) stated that it cannot provide
quantitative measurements, the interpretation is based on a research’s judgment and
the sample is not representative of the population. Hence, the exploratory research
was used as an initial stage for this study.
Zikmund (1997) classified techniques for gaining clearer ideas of research problems
into four basic categories: experience surveys, secondary data analysis, case study
method and pilot study. Anyway, according to the appropriateness of this study, the
exploratory research has adopted two techniques which are secondary data analysis
and experience surveys.
Stage 2 Research Instruments Construction:
This research adopts the sample survey method. The data were gathered through a
structured questionnaire using closed-end questions style including variables based on
prior literature and exploratory work. The questions listed in the questionnaire were
listed below:
No.
Questions
Variables
Sources (Authors)
1
Playing on-line computer games
Attitude
Cheong, J.H., and Park,
give me good feeling.
2
I find playing on-line computer
games give me new ideas and
M.C. (2005)
Attitude
experiences.
3
To me, playing on-line computer
Attitude
games is not a waste of time.
4
5
The likelihood of my online
Intension to
computer games playing is high.
play
Something inside pushes me to
Intension to
go and play online computer
play
games.
6
7
Instead of going out shopping or
Perceived
Pikkarainen,T.,
partying, playing an online
usefulness
Pikkarainen, K..,
computer games give me a better
Karjaluoto, H., and
use of time.
Pahnila, S. (2004)
I think that playing an online
Perceived
computer games is helpful to
usefulness
improve my computer skill in
general.
8
I think that playing an online
Perceived
computer games help me explore
usefulness
to the modern technology.
9
10
I think that playing an online
Perceived
computer games is costly.
usefulness
I think that playing an online
Perceived
computer games give a sense of
usefulness
accomplishment.
11
I think that playing an online
Perceived
computer games is mentally
usefulness
challenging.
12
13
I think that playing an online
Perceived
computer game is addictive.
usefulness
I think access into online
Perceived
Cheong, J.H., and Park,
computer games through internet
ease of use
M.C. (2005)
is easy.
14
I think that learning to play online Perceived
computer games through internet
ease of use
is easy to understand.
15
I think that the payment process
Perceived
of playing online computer games ease of use
is easy.
16
I could explain the rules of how
Perceived
to play online computer games to
ease of use
a friend in a few minutes.
17
It is not necessarily easy to
Perceived
understand the rules of how to
ease of use
play online computer games.
18
Beautiful cartoon character in the
Appearance
online computer game’s website
quality
Aladwani, A.M. (2006)
is important.
19
Beautiful background image of
Appearance
the online computer game’s
quality
website is important.
20
The use of proper color scheme in Appearance
the online computer game’s
quality
website is important.
21
There is no time for yawning
Gameplay
when playing online computer
Gagnon, K. (2007)
games.
22
Most online computer games go
Gameplay
on and on.
23
Online computer games should be Gameplay
difficult.
24
To play online computer games is
D’Astous, A., and
Gameplay
like escaping from everything.
25
When I play online computer
Gameplay
games, I am totally focused.
26
Online computer games should be Gameplay
easy.
27
When I play online computer
Gameplay
games, I feel that I am in another
world.
28
When I play online computer
Gameplay
games, I may become so involved
that I forgot everything.
29
Playing online computer games is
Compatibility Park, Y, and Chen, J.V.
compatible with all aspects of my
(2007)
regular computer use.
30
I think that playing online
Compatibility
computer games fits will with the
way I like to spend time.
31
Before deciding on whether or
Trialability
not to play the online computer
game, I would need to play it on a
trail basis.
32
I would be permitted to play
Trialability
online computer games on a trail
basis long enough to see what it
can do.
33
I know where I can go to
Trialability
satisfactorily try out various
features of online computer
games.
34
I feel confident visiting a web site Internet self-
Hsu, M.H., Chiu, C.M.,
by entering its address (URL) in
and Ju, T.L. (2004)
the browser.
efficacy
35
I feel confident going backward
Internet self
and forward to previously visited
efficacy
web pages without being lost in
the hyperspace (cyberspace).
36
37
38
39
40
I feel confident receiving e-mail
Internet self
messages.
efficacy
I feel confident sending e-mail
Internet self
messages.
efficacy
I feel confident downloading files
Internet self
and software.
efficacy
I feel confident installing an
Internet self
application or software.
efficacy
It bothers me when my friends do
Socialization
Dotson, M.J., and
something I don’t know how to
agent
Hyatt, E.M. (2005)
do.
41
42
43
It is important for me to fit in
Socialization
with my friends.
agent
I want to have the same activity
Socialization
as my friends.
agent
What my friends think is more
Socialization
important than what my parents
agent
think.
The self administered questionnaires technique was selected as the data collection
method. The strength of self administered questionnaires will help avoid or at least
reduce the non-responses problem. A self administered questionnaire is employed to
collect data since not only the researcher can collect all the completed responses
within a short period of time, but any queries are answered immediately thereby
reducing response errors (Cavana et al, 2001). Prior to the data collection method, 30
set of questionnaires has already been distributed to the sampling group as a pre-test
process. Result from this, it expects to be able to assess the validity and refine the
questionnaires. The questionnaires were distributed by the third party to the students
on a convenience basis. All of the respondents have been given the outline of what the
questionnaire is about and instruction on how to proceeds the questionnaire. Both
outline and instruction will be presented to the respondents by both written and verbal
explanation after three screening questions concerning age, educational background,
and online computer game playing experience. Once the respondents complete the
questionnaire, they will have to return it to the data collector.
To have a sizeable sample size, a total of 400 questionnaires were distributed to
potential respondents. The expected number of questionnaires return is 50%.
Multiple-item scales are used to measure each component to enable testing for
measurement error. All of the initial scales adopted were found to be reliable
measures for their respective constructs as the Cronbach’s alphas exceed 0.80. (Please
see appendix 7) All constructs are measured by interval scale in the form of a five
points likert scale (1 = highly disagree to 7 = highly agree).
Statistical Package of the Social Science (SPSS) will be used to in the part of data
analysis. According to the research questions in this study that has already specify an
explicit relationship between dependent variables namely online game player’s
attitude and intension and independent variables namely perceived usefulness,
perceived ease of use, appearance quality, game play, compatibility, trialability,
internet self-efficacy and socialization agents (peers) as well as the purpose of the
research questions that try to examine the simultaneous effects of independent
variable on a dependent variable, this study has adopted the regression analysis to
examine the influencing factors and adopt the correlation analysis to examine the
relationship between two factors.
Stage 3 Validity and Reliability of Research Instruments:
In order to ensure the effectiveness of measures used in this study, the pre-test of
research instruments was used to examine validity and reliability of each item in the
questionnaire before conducting the real survey. The testing process is divided into
two types which are the test of validity and the test of reliability.
The Test of Validity
After building the model, constructing research instruments and selecting the
participants, it is necessary to assure that participants understand all of the questions
in the research instrument. This is usually called the “validity” of the instrument
(Nunnally, 1978).
The Test of Reliability
The reliability tests give information about consistency and stability through a series
of research measure (Cronbach, 1965). Reliability can be tested in both quantitative
and qualitative research (Cohen, Manion and Morrison, 2000). The reliability of
measure refers to the extent that the measurement process is free from error (Garrett,
1966; Kinnear and Taylor, 1996). Reliability can be classified into two dimensions:
stability and consistency (Sekaran, 2000).
Stage 4 Selections of Participants and Data Collection Methods
For the process of data collection, this study has used the sampling technique to
recruit the participants. The terminology of “sampling” involves the process of
choosing a small percentage of the whole population as its representatives (Zikmund,
1997). There are 2 main types of sampling techniques: First, probability technique and
second, non-probability technique. For probability sampling all units in the population
have the same chance of being chosen as part of the sample. For non-probability
sampling the units do not have an equal chance of being chosen as part of the sample
(Sekaran, 2000).
This study deploys non-probability because there is no name list of Thai online gamer
available. This study identified the sampling frame by scoping down to undergraduate
students in Bangkok (ages 18-25). As this target respondents usually spends time
playing online game at the internet café. Thus, the survey will be conducted on them
by using convenience sample of 18-25 year old undergraduate students who come to
play online computer games at the internet café in Bangkok. Carrier Market
Development (2003) reported that there are 72 percent of people aged 15-19 play
online games in the United States and 50 percent of people aged 15-24 play online
games in Europe. In addition, the study by Gao (2004) pointed out that the appropriate
sampling units that can be used as internet surfer population are those whose age is
between 16-30. Thus, this target population considering as appropriate subjects for
this research. However, to focus particularly on college students, it will also allow this
study to be able to control the homogeneity of respondents’ attitude. Homogeneous
respondents are desired for two reasons. First they permit more exact theoretical
predictions than may be possible with a heterogeneous group (Cook and Campbell
1975). Secondly, heterogeneous respondents constitute a threat to statistical
conclusion validity (Cook and Campbell 1975). The research participants will be
approached in Bangkok because the research conducted by National Electric and
Technology of Thailand (NETEC) in 2001 has shown that there are estimated about
3.5 million internet users in Thailand and 54 percent of internet user’s population is in
Bangkok.
Malhotra (1999) stated that determining the sample size is very complicated and
involves several quantitative and qualitative considerations. These considerations
include the importance of the decision, the nature of research, the number of
variables, the nature of the analysis, sample size used in similar studies, incidence
rates, completion rates and resource constraints (Malhotra, 1999). Quantitatively, a
sample size of 200-500 persons is recommended to be sufficient for data analysis
(Hair et al. 1998). The sample size in this study then set to be 400 undergraduate
students aged between 18-25. Anyway, the possibility of getting back all 400
questionnaires from participants is not easy. Thus, this study has the expected number
of returned questionnaires which is 50%.
In this study, the questionnaires were distributed to the participants by the researcher’
assistants in front of the internet cafes nearby any university in Bangkok. The
participants were approached right after they leave the internet café as this can
assumedly indicate that they are the internet users. Anyway, to ensure that they are the
right target participants, three screening questions concerning age, education
background, and online game playing experience have also asked.
Stage 5 Data Editing
For the frequency procedure in this study, the Statistical Package for Social Sciences
Windows version 10.0 (SPSS 10.0) was used to run all of the variables in order to
ensure accuracy, consistency and reliability of the data during the data entry.
Incomplete questionnaires were classified into two groups: the first group contained
questionnaires in which more than twenty-five percent of variables were not
completed (Sekaran, 2000). Questionnaires in this group were excluded from the data
analysis. The second group included incomplete questionnaires in which the number
of variables without response was less than twenty-five percent, these were identified
as having missing values in the data entry for the SPSS programme (Kinnear and
Taylor, 1996; Sekaran, 2000).
Stage 6 Data Analysis
As this study is quantitative research, both descriptive and inferential statistics were
used to analyze the data collected from the questionnaire survey with the use of the
Statistical Package for the Social Sciences, Window version 10.0 (SPSS 10.0).
Survey Questionnaire
Two major types of quantitative analysis techniques were chosen to analyze the data
in this study which are Descriptive and Inferential Statistical Analysis.
Descriptive statistics may be used to classify, review and explain the profile of all
respondents (Cohen and Holiday, 1982). The use of descriptive statistics has found in
many studies during the literature review stage of this study such as “Mobile internet
acceptance in Korea” (Cheong and Park, 2005) and “Consumer acceptance of online
banking: an extension of the technology acceptance model” (Pikkarainen et. al., 2004)
.
Moreover, the inferential statistical analysis has also been used in this study.
Inferential statistics may be used to predict population parameters from respondents
(sample) measures by using mathematical theories (Cohen and Holiday, 1982). To
analyze data from a sample, choosing between parametric and non-parametric
statistics must be considered. Parametric methods are the most commonly used
techniques for testing hypotheses and can be used when exact population units are
known (Cohen and Holiday, 1982). However, when it is difficult to make
assumptions, when the population distribution is not normal, non-parametric methods
are used to test hypotheses (Saengkaew, 2001). This may be called a “distribution
free” process (Cohen and holiday, 1982) and is used when nominal or ordinal scales
are used. For interval scales, they are converted to ordinal scales when non-parametric
methods are applied (Saengkaew, 2001; Wechasarn, 2003).
As the population that will be tested in this study expected to be not normal, therefore,
non-parametric methods were initially considered to test the hypotheses of this study.
Every questionnaire was distributed to the research participants by the third party, and
all completed questionnaires have also been collected by the third party as well.
Moreover, as this is an anonymous survey, no identification (names) of the
participants is indicated in the report. The data will be aggregated and no specific
reference to individual responses will be made. Before research participants will begin
doing the questionnaire, a cover sheet for the survey questionnaire explaining the
background and purpose of the research will be provided to them. This stage of the
study is entirely voluntary so if research participants feel that the study was intrusive
or they were reluctant to answer the questions, they could withdraw at any time of the
process.
The implication of the study
Academically, this paper will be expected to contribute a new knowledge about
consumer attitude toward the unique online product like online computer games and
theoretically, this study applies modified TAM model by adding six more correlates
variables namely appearance quality, game play, compatibility, trialability, self
efficacy, and socialization agents to better suit with particular tested product. In
managerial contribution, it will help e-tailers to develop effective strategies for online
computer game products. The information from the finding will also help marketing
managers to understand customer better and to effectively plan their marketing mixes.
The limitation of the study
Since, the behavior of consumer is changing overtime as well as product like online
computer games which considered being in the category of technological
advancement product. The existing study might not be valid when the time passed by.
The further study still needs to keep update with the up coming new trend as well as
focusing on the different group of customers.
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