Dauw-Song Zhu
Business Administration & Accounting Department, National Dong Hwa University
No. 1, Sec. 2, Da Hsueh Rd. Shou-Feng Hualien, Taiwan 974
Chih-Te Lin
Business Administration Department, National Dong Hwa University &
Lecturer of Food and Beverage Management Department, Taiwan Hospitality & Tourism College
No. 2, Lane 46, Jhongmei 3rd St, Hualien, Taiwan 970
Keywords: Online game, technology acceptance model (TAM), service quality.
Abstract: Many empirical studies have pointed out that the technology acceptance model (TAM) can be used to
explain whether users can accept a new information technology. Therefore, this study has adopted TAM to
investigate external factors that affect gamers’ acceptance of online games. In this study, system quality,
information quality, and service provider’s characteristics were taken as external variables. It was
discovered that in the aspect of perceptions, system quality had positive effects on perceived ease of use and
perceived usefulness. Service provider’s characteristics had positive effects on perceived usefulness and
perceived trust. Besides, in the relationship between user’s perception and attitude and intention, the
research finding was consistent with TAM has suggested; i.e. perceived ease of use had positive effects on
perceived usefulness and user’s attitude, and perceived usefulness had positive effect on user’s attitude.
Finally, user’s perceived trust and attitude would be positively correlated with user’s intention of use.
With the advancement of information technology,
popularity of the Internet, and the gradual prevalence
of broadband networks, the output value of online
games has been increasing in a fast speed. In fact,
Internet websites are accessible by consumers from
around the globe, and this has contributed to the
globalization of markets over the past three decades
(Yip, 2000), it is very common for researchers
studying the international environment to select one
country and use it as a basis for empirical inquiry.
Clearly, managers need to better understand the
growing use of Internet shopping sites and those
consumer characteristics that encourage repeat visits
to these sites. One key consumer characteristic is
their willingness to use and accept the new
technologies. Since researchers need a framework to
effectively evalue new online phenomena, the
technology acceptance model (TAM) is applicable in
this context (Savitskie, K, Marla B Royne
M.B., Persinger, E.S., Grunhagen., M., Witte,
C.L., 2007). The TAM model was derived from
Fishbein and Ajzen’s (1975) Theory of Reasoned
Action and has received considerable support by
many researchers (e.g. Jackson, Chow, & Leitch
1997; Venkatesh & Davis 1996). Further, a number
of researchers have examined Internet usage via the
Tam framework (Gefen & Staub 2000; Venkatesh, &
Massey 2003), and the current research use the TAM
to better understand individual attitudes toward
technology within the international Internet shopping
Moreover, the identified human factors are
mainly user perceptions about the utility of this type
of technology: perceived ease of use and perceived
usefulness (Davis, 1989).Some related studies have
also revealed that when one enters the fully
immersed state, he will feel totally involved in the
activity, his consciousness will be very narrow, his
attention is only focused on the activity, and his
awareness is partially lost (Webster et al., 1993;
Zhu D. and Lin C. (2008).
In Proceedings of the International Conference on e-Business, pages 384-389
DOI: 10.5220/0001908003840389
Koufaris, 2002). However, the gaming market is
very competitive, and several new games are
released every month. Thus, when players have a
certain degree of ‘flow’ experiences from a new
game, they may quit playing it due to awful external
quality of the game. As discussed above, the purpose
of this study is to investigate the effects of external
factors, such as system quality, information quality,
service provider’s characteristics on the perceptions
of online gamers, and find out whether gamers'
perceptions have positive effects on their attitude for
the game and intention of use, in hope of providing
the research result as a reference for online game
companies to enhance service quality for customers.
2.1 System Quality (SQ)
Website quality, system quality, and game quality are
significantly influential to gamer satisfaction. In the
I/S success model proposed by DeLone(1992), 12
empirical studies about system quality were
investigated, and 18 indicators of system quality
were proposed. These indicators include ease of use,
usefulness, system accuracy, system flexibility,
system reliability, response time, and etc. However,
Mckinney, Yoon, and Zahedi (2002) measured
system quality of Internet shops with the following
indicators, including access, usability, navigation,
and interactivity. In Negash (2003) which focused on
online customer service systems, it was argued that
some of DeLone’s system quality indicators are
already outdated. Thus, interactivity and access were
proposed as system quality indicators.
2.2 Information Quality (IQ)
As online games will be constantly updated and
expanded, game information is very important for
online gamers. In the evaluation of information
quality, Lee, Strong, Kahn, and Wang (2002)
developed 15 indicators to assess the information
quality of an organization. These indicators are
accessibility, appropriate amount, believability,
completeness, concise representation, consistent
representation, ease of operation, free of error,
interpretability, objectivity, relevancy, reputation,
security, timeliness, and understandability. In
Mckinney et al. (2002), only 5 indicators, including
relevance, timeliness, reliability, and scope, were
adopted. Negash et al. (2003) proposed to use
informativeness and entertainment as system quality
2.3 Service Provider’s Characteristics
Saeed et al. (2003) conceived that service provider’s
characteristics are important because the Internet is a
virtual channel which creates more sense of
uncertainty to Internet users. Stronger service
providers characteristics will enhance users’ trust
and consumers’ perceptions will not be affected.
Saeed et al. further proposed the following indicators
to measure service provider's characteristics,
including size, reputation, and participation costs. In
Jarvenpaa, Tractinsky, and Vitale (2000), it was
proposed that perceived reputation and perceived
size of service providers will affect users’ trust for
service providers. Among domestic studies, Chen
Chuen-Liang (2002) pointed out that online game’s
brand image will positively affect users' intention of
use, and brand image can be evaluated by corporate
image, word of mouth, popularity, and reputation.
2.4 Technology Acceptance Model
Over the past 10 years, Technology Acceptance
Model (TAM) has been empirically proven to be an
important explanatory model for personal acceptance
or use of new information technology. TAM is a
behavior intention model developed based on the
Theory of Reasoned Action (TRA) by Davis in 1989.
It was intended to simplify TRA and find out an
effective behavior model that could be widely
applied to explain or predict the factors affecting the
use of information technology. In TAM, two definite
cognitive beliefs were proposed, namely perceived
usefulness and perceived ease of use. The two
beliefs determine an individuals behavior intention
for using technology through attitude. It has been
clearly pointed out that external variables will
directly influence perceived usefulness and
perceived ease of use and indirectly affect user's
attitude, intention, and practical use. Based on the
behaviors of information system users, Seddon et al.
(1997) developed a successful information system
model which definitely pointed out that system
quality and information quality would respectively
affect users perceived usefulness and perceived ease
of use. Lin and Lu (2000) probed into the behavior
intentions of World Wide Web (WWW) users, using
information system quality to measure users
behavior intention for using WWW. It was
discovered that system and information quality were
positively correlated with user’s cognition, attitude,
and willingness. In a review of studies related to
online consumer behaviors, Saeed, Hwang, and Yi
(2003) proposed a set of integrative structure, in
which system quality, information quality, service
quality, and service providers characteristics are
influential to users perceived ease of use, perceived
usefulness, and perceived trust.
In recent years, many empirical studies (David,
1989; Szajna, 1996, Lederer et al., 2000; Lin and Lu,
2000; Moon and Kim, 2001; Hsu and Lu, 2003) have
verified that perceived ease of use would affect
perceived usefulness, perceived usefulness and
perceived ease of use would affect users attitude,
and user’s attitude would further affect users
intention of use.
In this study, the questionnaires were mainly
distributed to players of a new online game available
for public test. The game was selected according to
the observation of popular forum topics on a
well-known game website “Bahamut”
( during one week (Apr
27~May 3 2005). The statistic result revealed that
the “RF Online” forum was almost always on the top
3. During that time, “RF Online” was available for
public test, so it was selected as the research focus.
Later, a web-based questionnaire was formed and
published on a professional web-based survey
website “MY3Q”. The survey link was also posted
on the online game forum of BBS at Dong Hwa
University, famous game forums "Bahamut” and
“Game Base”, and some game-related communities
on Yahoo for players to connect to the survey system.
The survey period started from May 5 till May 31
2005. A total of 319 valid samples were collected.
3.1 Measurement of Variable
According to Mckinny et al. (2002), system quality
was divided into three dimensions, including
“access”, “usability”, and “navigation”. Access was
defined as the connection response and access speed
of the game and the website. Usability refers to the
operations of the user interface in the game, and
navigation is defined as the operation of the user
interface on the website. Aladwani and Palvia (2002)
pointed out that security mechanism is also an
important element when users evaluate the quality of
a website. Thus, this study also incorporated
“security” as dimension of system quality and
defined it as the level of security of gamers’ personal
data and the gaming process.
Based on Mckinny et al. (2002) and Lee et al.
(2002), this study proposed 4 dimensions of
information quality, namely “relevance”,
“timeliness”, “reliability", and “scope”. Relevance
refers to the applicability of the game information
provided by the website. Timeliness indicates
whether the website can provide latest game
information. Reliability is defined as the correctness
of the game information, and scope refers to the
coverage of the provided game information.
As suggested in Jarvenpaa et al. (2000), service
provider’s characteristics included two dimensions,
reputation and perceived size. Reputation is defined
as the prestige of the firm, and perceived size refers
to the scale of the company in this industry.
According to TAM and the study of online guys by
Hsu and Lu (2003), perceived ease of use was
defined as the level of easiness that users feel about
the functions of an online game. Based on TAM and
Hsu and Lu (2003), perceived usefulness was
defined as the level to which users feel that the
online game can achieve the gaming objective. In
Hsu and Lu (2003), gaming objectives included fun,
recreation, messaging, information exchange,
making friends, chatting, team work, fantasy, hobby,
work, and transaction. This study employed TAM
and Hsu and Lu (2003) to define attitude as the level
of user's preference for an online game. Based on
TAM and Hsu and Lu (2003), this study defined the
intention of use as the intensity of users intention to
use an online game. After all the questionnaires were
collected, we analyze the data and verify the
hypotheses with structured equation model (SEM).
The analysis procedure included two parts, basic
analysis and overall model analysis. In the basic
analysis, descriptive analysis and reliability analysis
would be processed on SPSS 10. In the overall
model analysis, confirmatory factor analysis and
structural equation model analysis would be
performed on Amos 4.0.
In the gender distribution among collected samples,
male players accounted for 84.9% and female ones
only 15%. Players aged between 19-23 took the
largest proportion by 37.9%. 45.4% of them had a
university or college education background, and
38.8% had a high school or vocational school
education background. In terms of occupation,
66.7% of them were students. This sample structure
was similar to those observed in other studies of
ICE-B 2008 - International Conference on e-Business
online games but not in the studies of behaviors on
the Internet. As to gender distribution, the ratio of
male and female online gamers was 7:3. In the
aspect of online shopping, female shoppers
outnumbered male ones, by a ratio of 6:4. Other
activities, such as the use of portal sites and Internet
phone, had a relatively even ratio of male to female
users. In the age distribution, if age 24 was viewed
as a barrier, the ratio of those above 24 to those
under 24 was 7:3.
Table 1: Path coefficients of the proposed model and
verification of hypotheses.
Variables Beta Ha Result
SQ perceived
ease of use
1.375** H1
IQ perceived
ease of use
0.303* H2
SQ perceived
NA H3 ×
IQ perceived
NA H4 ×
SPC perceived
ease of use
0.859** H5
Perceived ease of
use perceived
0.424** H6
Perceived ease of
use users
0.363** H7
users attitude
0.314** H8
intention of use
0.833** H9
Users attitude
intention of use
0.168** H10
However, the ratio was reversed in the aspect of
online shopping, where those above 24 took the
largest proportion (6:4). In other activities on the
Internet, both groups had an even distribution. In
terms of occupation, most of the online gamers were
students. The ratio of student gamers to non-student
gamers was 6:4. But in the aspect of online shopping,
those of other occupations took a larger proportion,
and students only accounted for 30%. Besides, no
significant difference between the two groups was
observed in other activities. Finally, in terms of
education background, the majority of online gamers
received college education. It can be discovered that
every dimension had a mean larger than 3, and
attitude and intention of use even had 4.26 and 4.28,
respectively, indicating that players had a high level
of preference for the online game.
In this study, AMOS 4.0 was used to process the
structural equation model analysis and verify the
proposed causal path model. After the path was
established and the samples were applied into the
model, it was discovered that many relationships
among latent variables were not significant. Thus,
the structure was modified to remove the
insignificant path between exogenous and
endogenous variables.
As to basic goodness of fit, the factor loading of
each indicator ranged between 0.5 and 0.95 and
reached the level of significance. Besides, there was
no negative deviation. Thus, overall, this model was
compliant with the standard of goodness of fit. As to
the fitness of overall model, the absolute fit
measures of the overall theoretic model: χ2/d.f=1.90,
GFI=0.87, RMR=0.04, and RMSEA=0.05, where
χ2/d.f, RMSEA, and RMR reached the ideal level,
and GFI also approached the acceptable level of 0.9.
In the aspect of incremental fit measures,
AGFI=0.84, NFI=0.90, CFI=0.95, NFI and CFI
exceeded the ideal level of 0.9., and AGFI was also
close to the acceptable level of 0.9. Among
parsimonious fit measures, PNFI=0.80 and
PGFI=0.72, all of which were compliant with the
The path coefficients in the path model and the
results of hypotheses verification were organized in
Table 1. In the aspect of the impact of external
factors on user’s perceptions, users perceived ease
of use was affected by system quality and
information quality. Thus H1 and H2 were supported.
In the aspect of perceived usefulness, the research
findings revealed that system quality and
information quality had no effect on perceived
usefulness, so H3 and H4 were not supported.
However, service providers characteristics and
perceived ease of use had positive effect on
perceived usefulness. Thus, H5 and H6 were
supported. Perceived ease of use and perceived
usefulness had positive influence on users attitude.
Thus, H7 and H8 were supported. Finally, perceived
usefulness and users attitude (H9, H10) would have
positive influence on intention of use at the same
System quality and information quality were
positively related to players perceived ease of use.
This indicates that when better and more stable
systems and correct and rich information are
provided to game players, game players will feel
perceive more ease of use and the entry obstacle of
the game can be reduced.
No significant effect of system quality and
information quality on gamer's perceived usefulness
was discovered. Unlike task-oriented information
systems, online games are entertainment-oriented
information systems. Thus, when players are
engaged in online games, they do not necessarily
play the game to enhance their game performance or
seek higher efficiency but simply kill some time,
make friends, get rid of the social bindings. This
explains why system quality and information quality
were not significantly related to perceived
Service providers characteristics had positive
effects on Perceived usefulness. In online games, it
would be time-consuming to accumulate
achievements or cultivate relationships, so if the
service provider is in a small scale or it does not
proper manage with players, the service provider
may shut down the game due to improper
In this study, TAM was adopted to investigate the
factors affecting online game players acceptance of
games. The research results were consistent with
those suggested in previous studies. This shows that
if gamers feel that a game is easy to be familiar with
and get involved in, they will have more preferences
for the game and further increase their intention to
carry on using it.
Most of the previous studies of TAM focused on the
second half of the model, i.e. the effect of user’s
perceptions on their attitude and intention. The main
contribution of this study is that it probed into the
first half of the TAM model to understand the impact
of external factors on users perceptions.
In the previous studies about evaluation of
information systems, external factors were mainly
touched upon in the discussion of the impact of
information quality and system quality on
information systems. However, with the fast
development of the Internet, many related online
information systems have been derived. Thus, the
past evaluation models are no longer applicable to
the evaluation of online information systems. In this
study, the importance of service providers
characteristics was empirically proven. Online users
cannot directly interact with service distributors or
providers, so trust becomes an important element in
the evaluation of online information systems, and
well-known and large-scale firms can usually lower
the level of uncertainty.
The research of online games is seldom across to
foreign nations, and no measurement scale for online
games is available. This study try to use the scales
designed for other information systems, and
incorporated the opinions of online gamers to
develop an integrated scale for online game systems.
The proposed model had compliant validity and
reliability. Thus, it can be a reference for further
Besides, in the aspect of brand image, a good
management mechanism is helpful for the
establishment of a brand. If game service providers
can make use of brand advantage, they can attract
more users to participate in their games and enhance
customer loyalty. Besides, a good brand image can
also help promote other games, create popularity,
and establish a good reputation. Finally, according to
the survey of this research, 54% of the gamers
reported to play other games in addition to the
selected game. This reveals that there are numerous
choices for online games in Taiwan, and the market
competition is very fierce. As a result, if game
service providers are imprudent in their management,
their games may be easily displaced.
In this study, a web-based survey was adopted and
the reference link was posted on some major forums
and discussion boards for game players to participate
in the survey at will. Thus, random sampling could
not be conducted, and deviation of the samples in the
representation of the population might occur and
possibly lead to a slight bias of the research results.
Aladwani, A.M, Palvia, P.C., (2002), Developing and
validating an instrument for measuring user-perceived
web quality., Information & Management, Vol. 39, No.
6, pp 467-476.
Davis, F. D, Bagozzi, R. P, Warshaw, P. R., (1989), User
Acceptance of Computer Technology: A Comparison
of Two Theoretical Models., Management Science,
Vol.35, No.8, pp. 982-1003.
ICE-B 2008 - International Conference on e-Business
DeLone, W. H., McLean, E. R., (1992), Information
System Success: The Quest for the Dependent Variable,
Information Systems Research, Vol. 3, No. 1, pp.
Fishbein, M., & Ajzen, I.(1975). Belief, attitude, intention,
and behavior: An introduction to theory and research,
Reading, MA: Addison-Wesley.
Gefen, D.& Larcker D.F (1981).Evaluating structural
equation model with unobservable variables and
measurement error. Journal of Marketing Research,
18(1), 1-30.
Hsu, C.L, Lu, H.P., (2004), Why do people play on-line
games: an extended TAM with social influences and
flow experience, Information and Management, Vol.
41, No. 7, pp. 853–868.
Jackson, C.M., Chow, S., & Leitch, R.A.(1997).Toward an
understanding of the behavioral intentions to use an
information system. Decision Sciences, 28(2),357-389
Jarvenpaa, S., Tractinsky, N., Vitale, M., (2000),
Consumer trust in an Internet store, Information
Technology and Management, 1, pp. 45-71.
Koufaris, M.( 2002). Applying the technology acceptance
model and flow theory to on-line consumer behavior.
Information System Research, 13(2), 205–223.
Lederer L. A, Maupin J. D., Sena P. M., Zhuang, Y., (2000),
The technology acceptance model and the World Wide
Web., Decision Support Systems, Vol.29, pp. 269-282.
Lee Y. W., Strong D. M., Kahn B. K., Wang R. Y., (2002),
AIMQ: A methodology for information quality
assessment, Information & Management; Vol. 42, No.
2, pp.133-146.
Lin, C-C. , Lu, H., (2000), Towards an understanding of
the behavioral intention to use a web site, International
Journal of Information Management, vol.20, pp.
Mckinney, V., Yoon, K., Zahedi, F.M., (2002), The
measurement of web-customer satisfaction: an
expectation and disconfirmation approach, Information
System Research, Vol. 13, No3, 296-315.
Moon, J.-W., Kim, Y-G., (2001), Extending the TAM for
World-Wide-Web context., Information &
Management, Vol. 38, No. 4, pp. 217-230.
Negash, S., Ryan, T., Igbaria, M., (2003), Quality and
effectiveness in Web-based customer support systems,
Information & Management, Vol. 40, pp. 757-768.
Saeed, K. A., Hwang, Y., Yi, M. Y., 2003, Toward an
Integrative Framework for Online Consumer Behavior
Research: A Meta-analysis Approach, Journal of End
User Computing. Vol.15, No.4, pp. 1-26.
Savitskie, K, Marla B Royne M.B., Persinger,
E.S., Grunhagen., M., Witte, C.L., (2007).
Norwegian Internet Shopping Sites: An Application &
Extension of the Technology Acceptance
Model. Journal of Global Information Technology
Management, 10(4), 54-73.
Seddon, P. B., (1997), A Respecification and Extension of
the Delone and Mclean Mode of IS Success.,
Information Systems Research, Vol. 8, No. 3, pp.
Szajna, B., (1996), Empirical Evaluation of the Revised
Technology Acceptance Model., Management Science,
Vol.42, No.1, pp. 85-92.
Venkatesh, V. & Davis, F.D. (1996). A model of the
antecedents of perceived ease of use: development and
test. Decision Sciences, 27(3),451-481
Venkatesh, V., Ramesh, V., & Massey, A.P. (2003).
Understanding usability in mobile commerce.
Communications of the ACM, 45(12),53-56
Webster, J., Trevino, L., and Ryan, L., (1993), “The
Dimensionality and Correlates of Flow in
Human–Computer Interactions,” Computers in Human
Behavior, Vol. 9, pp. 411–426.
Yip, G.S (2000). Global strategy in the Internet era.
Business Strategy Review, 11(4),1-14.