VISUAL ANALYSIS OF RESEARCH ON ACCEPTANCE
OF INFORMATION TECHNOLOGY
Qian-jin Zong, Qin-jian Yuan, Ling-yu Tong and Hong-zhou Shen
Department of Information Management, Nanjing University, No.22 Hankou Road, Nanjing, China
Keywords: Acceptance of information technology, User acceptance, Research focus, Frontier, Knowledge mapping
domains.
Abstract: This paper collected 1696 literatures of acceptance of information technology (IT) as the data sample, which
were cited by Web of Science (SCI-EXPANDED, SSCI, A&HCI, CPCI-S, CPCI-SSH) from 1985 to 2010.
Based on the method of mapping knowledge domains, this article used keyword frequency analysis, burst
terms detecting, and co-citation analysis to analyse the research focus, frontier and theoretical foundation of
acceptance of IT research, and draw the knowledge mapping of them.
1 INTRODUCTION
Information technology (IT) influences every aspect
of our society, and has become an indispensable part
of one’s life and work. Information Technologies are
designed for the purposes of supporting productivity
and communication in social settings, their values
can be realized only if they are accepted/adopted,
used, and used continuously by intended users
(Zhang and Sun, 2009). Obviously, users’
acceptance of IT is the crucial key to the information
systems (IS). Scholars have done lots of research on
the acceptance and using of IT in the past many
years, and this research area has been a hot topic.
Moreover, for improving the working efficiency
though IT, managers in the organizations pay more
attention to the acceptance of IT in recent years too.
For such a rapidly-developing and important area
of research, it is necessary to understand the whole
view of the research, such as what are the key topics
being heavily focused on? And what are the frontiers
of the research? And what are the theoretical
foundations it is established on? However, there is
still no study making efforts to answer these
questions. In order to make up this void, this study,
based on knowledge mapping domains, is attempting
to give a whole view of acceptance of information
technology research.
2 METHODOLOGY AND DATA
2.1 Methodology
“Mapping knowledge domains” describes a newly
evolving interdisciplinary area of science aimed at
the process of charting, mining, analyzing, sorting,
enabling navigation of, and displaying knowledge.
This field is aimed at easing information access,
making evident the structure of knowledge, and
allowing seekers of knowledge to succeed in their
endeavours (Shiffrin and Börner, 2004).Except
combing with the idea of bibliometrics, social
network, etc., mapping knowledge domains uses
information visualization which developed rapidly
recent years. Mapping knowledge domains can be
used to find the foundation of the research by
citation analysis and to reveal the research
focus ,their relations by keyword analysis, such as
frequency, centrality and so on .Moreover , it can
display the research frontier by detecting burst terms.
Because of the vast increases in computational
capacity and processing speed, the tools of mapping
knowledge domains can deal with massive
information, and various analysis tools are available
for free, such as Pajek (Batagelj and Mrvar, 1998),
UCINET (Borgatti et al., 1999), Netdraw (Borgatti,
2002), and HistCite (Garfield et al., 2006) etc. In this
study, CitespaceII (Chen, 2006) and Bibexcel
(Persson et al., 2009) are employed.
415
Zong Q., Yuan Q., Tong L. and Shen H..
VISUAL ANALYSIS OF RESEARCH ON ACCEPTANCE OF INFORMATION TECHNOLOGY.
DOI: 10.5220/0003561804150420
In Proceedings of the 13th International Conference on Enterprise Information Systems (EIT-2011), pages 415-420
ISBN: 978-989-8425-55-3
Copyright
c
 2011 SCITEPRESS (Science and Technology Publications, Lda.)

2.2 Data
This study collects 1696 documents related to
acceptance of IT from SCI-EXPANDED, SSCI,
A&HCI, CPCI-S, and CPCI-SSH in ISI Web of
Science. (The results were obtained on 25
th
Jan.
2011.) The date range of these collected documents
is from 1985 to 2010. Then we merge these records
into one txt file, and use BibExcel to analyse the
source publications. The papers are published in 597
publications and table 1 shows the top 10 source
publications of these recordings, and they are mainly
about the Computer, Information, Behaviour and
Management.
Table 1: The top 10 source publications in acceptance of
IT.
Publication title Freq
1 Information &Management 69
2 Computers in Human Behavior 56
3 MIS Quarterly 52
4 Journal of Computer Information Systems 45
5 Behaviour & Information Technology 33
6 Computers & Education 32
7 European Journal of Information Systems 31
8 International Journal of Human-Computer Studies 27
9 Decision Support Systems 24
10 International Journal of Information Management 22
3 ANALYSIS AND RESULTS
3.1 Research Focus in Acceptance of IT
Keywords can reflect the research results and the
understanding of authors; it is the essence of an
article. Scholars can find the focus topic in a
research area by analysing keywords. We select
keyword as the node of network and set
(c,cc,ccv)=(4,2,10;6,4,15;6,4,15) as the threshold
value in Citespace II. Then, a network of keywords
in acceptance of IT research is generated as shown
in figure 1, with 79 nodes and 222 links totally.
Table 2 shows the keywords which freq are over 100.
In the network of keywords, it is clear that two
biggest nodes linking to numerous smaller nodes
take the centre place. And the two nodes represent
the keywords “information-technology” and “user
acceptance” whose freq are 827 and 674 respectively.
More over, these two keywords have high
centralities, with 0.23 for “information-technology”
and 0.19 for “user acceptance”. The index
“centrality” measures the frequency of a word
jointly appearing with other words. The higher the
jointly appearance frequency is, the higher the
centrality is.
Figure 1: Network of keywords used in acceptance of
information technology research.
Table 2: The keywords whose freq exceed 100 used in
acceptance of information technology research.
Keywords Freq Centrality
information-technology 827 0.19
user acceptance 674 0.23
information technology 436 0.19
Technology acceptance model 421 0.07
Model 330 0.12
acceptance 317 0.12
usage 298 0.16
perceived usefulness 296 0.1
adoption 275 0.23
ease 213 0.06
perceived ease 201 0.04
behavior 186 0.08
internet 164 0.07
systems 155 0.05
intrinsic motivation 137 0.02
performance 137 0.08
self-efficacy 125 0.02
attitudes 120 0.14
trust 118 0.08
models 116 0.08
technology acceptance 115 0.03
implementation 114 0.01
satisfaction 110 0.05
determinants 105 0.02
planned behavior 102 0.01
tam 100 0.04
These two keywords appear most frequently, and
are jointly used with other word to specify the
research directions of studies. Apart from these,
there are still other keywords used frequently in
acceptance of information technology research as
ICEIS 2011 - 13th International Conference on Enterprise Information Systems
416

shown in Table 2. Among these words, however,
some have the similar meanings or fail to make a
clear description of the studies. For example,
“model” and “models” almost have the same
meaning, and it is the same with “user acceptance”
and “acceptance” and so on. Furthermore, some
keywords are very broad terms, such as “information
technology”, “systems”, etc. Considering the above,
we extract the following three focused topics from
these keywords: “user acceptance/adoption”,
“technology acceptance model”, and “planned
behavior”.
3.1.1 Online User Acceptance
From the figure 1, the keywords “web”, “internet”,
“electronic commerce” are connected with the node
“user acceptance”. As the information technology
developed rapidly, the research of user acceptance
not only in the traditional IT environment such as
ERP, etc., but also in the online environment,
especially in the online shopping which is one of the
most important areas of electronic commerce. A
major problem facing online shopping service
providers is the heterogeneity of user profile, unlike
organizational systems that have a well-defined
universe of users and system boundary; these
shopping services are designed for public users with
very different cognitive and demographic profiles
(Chau et al., 2000).Thus, user acceptance of
electronic commerce has many problems for us to
solve and this area will be still a research focus in
the following years.
3.1.2 Research Focus related to User
Emotion
Another research focus is the area related to user
emotion. It concludes “intrinsic motivation”,
“perceived useless”, “performance”, “self-
efficiency”, “customer satisfaction”, “behavioural
intention”, and “experience”, etc. Based on these
topics, some models are proposed by researchers.
Taking performance and customer satisfaction for
example, the models of this research area are based
on the Expectation-Confirmation Theory (ECT), and
Expectation-Confirmation Model is a typical
representative. ECT assumes that expectations,
coupled with perceived performance, lead to post-
purchase satisfaction. Satisfaction is believed to
influence attitude change and purchase intention. If a
product outperforms expectations (positive
disconfirmation) post-purchase satisfaction will
result. If a product falls short of expectations
(negative disconfirmation) the consumer is likely to
be dissatisfied (Oliver, 1980; Spreng et al.,
1996).There are four main elements which conclude
expectation, performance, disconfirmation and
satisfaction in this theory.
3.1.3 Technology Acceptance Model
Technology acceptance model (TAM) which is
proposed by Davis and others on the basis of TRA is
currently the most widely user acceptance model.
TAM includes two major determinants: Perceived
Usefulness (PU) and Perceived Ease of Use (PEOU).
PU is defined as "the degree to which a person
believes that using a particular system would
enhance his or her job performance”. And PEOU is
defined as "the degree to which a person believes
that using a particular system would be free from
effort"(Davis, 1989). TAM postulates that user
behavior is determined by Behavior Intention, and
the Behavior Intention is jointly determined by the
Attitude Toward Using and Perceived Usefulness.
According to TAM, Attitude Toward Using is
jointly determined by PU and PEOU. The PU is
jointly determined by the PEOU and the External
Variables, and PEOU is also determined by external
variables. Table 3 and Figure 1 show that TAM is a
very hot topic in acceptance of IT. And many
scholars found a number of other influential factors
in technology acceptance research and optimized the
TAM.
3.1.4 Planned Behaviour
The Theory of Planed Behavior (TPB) is the
extension of Theory of Reasoned Action and adds
the concept of perceived behavioral control. After
being proposed by Ajzen in 1985, TPB (Ajzen, 1985)
has been widely used in the research of user
acceptance of information technology, and most of
researches support it. Moreover, some scholars
compared the TPB to TRA in the online marketing,
and found that TPB is more suit-able than TRA. One
research tests the ability of two consumer theories-
the Theory of Reasoned Action and the Theory of
Planned Behaviour-in predicting consumer online
grocery buying intention, and the results suggest that
the theory of planned behaviour (with the inclusion
of a path from subjective norm to attitude) provides
the best fit to the data and explains the highest
proportion of variation in online grocery buying
intention (Hansen et al., 2004).
3.2 Frontiers in Acceptance of IT
Citespace provides a technology and algorithm to
VISUAL ANALYSIS OF RESEARCH ON ACCEPTANCE OF INFORMATION TECHNOLOGY
417

find the research frontier by using burst terms
detecting. Burst term is the word whose frequency
changes rapidly in a time period, not just its
frequency is high or low. By using this function, we
find top 15 burst terms: originality value, perceived
risk, subjective norms, mobile commerce, computer
anxiety, performance expectancy, user adoption,
effort expectancy, behavioural intention, computer
based, relative advantage, acceptance research, web
site, electronic commerce, and consumer behavior as
shown in figure 2.
Figure 2: Network of frontiers in acceptance of
information technology research.
In the network of frontiers, the node “consumer
behavior” takes the centre place with numerous links
to other smaller nodes. With the frontiers above and
Figure2, we can see that online user research,
especially the research of user in electronic
commerce has attracted the scholars. Electronic
commerce has developed rapidly all over the world
in recent years. As the core of E-commerce, users
will have a significant impact on the continued
development of E-commerce. For this reason, the
study of user acceptance in E-commerce will be a
trend in acceptance of IT in the following years.
Applications of web2.0, especially the social
networking services (SNS) provide a different way
for people to communicate with each others, and
these services have become very popular in recent
years. From Figure 2, we can see that web2.0 is also
a frontier in acceptance in IT, such as social network,
online social, social support, etc.
In addition, as the mobile technology developed,
applications & services based on mobile Internet
have been used widely. The number of users in
mobile Internet has increased rapidly. Thus, the
research of user acceptance in the industries related
to mobile has gradually aroused the concern of
researchers. And this research area is a research
frontier. From the Figure2, mobile commerce,
mobile shopping, mobile TV, mobile data service,
(mobile) phone users, new mobile service, 3G
services, etc. deserves some attention.
3.3 Theoretical Foundations of
Acceptance of IT Research
References are the knowledge source of the research
work, and using citation analysis can find the
theoretical foundations. Citation analysis is one of
the most widely used methods of bibliometrics. In
this study, we use the function named “cited
reference analysis” of Citespace and set cited
reference as the node of network. By running the
tool, a network of cited references is generated as
shown in figure 3, with 147 nodes and 366 links
totally.
Figure 3: Network of cited references in acceptance of IT
research.
In the Figure3, one node represents a cited
reference, and its size indicates the citation
frequency of the reference. The node and font is
bigger, the citation frequency (centrality) is higher
and this means that the literature is important. From
Figure 3, we can clearly see 6 biggest nodes and
other bigger nodes in the centre of the network, and
other smaller ones surround them. These big nodes
linked with each other closely. In other words, these
big nodes, or rather these classical literatures
establish most of the foundation of research. The top
6 most frequently cited references in Table 3 whose
cited frequency are all over 390. These references
are the key literatures in acceptance of IT research.
ICEIS 2011 - 13th International Conference on Enterprise Information Systems
418

In other words, these key literatures construct the
theoretical foundations of acceptance of IT research.
Table 3: The top 6 cited references in acceptance of IT
research.
Freq First Author Title Year
1072 DAVIS FD Perceived Usefulness,
Perceived Ease of Use,
and User Acceptance of
Information Technology
1989
798 DAVIS FD User acceptance of
computer technology: a
comparison of two
theoretical models
1989
635 VENKATESH V User Acceptance of
Information Technology:
Toward a Unified View
2003
576 VENKATESH V A Theoretical Extension of
the Technology
Acceptance Model: Four
Longitudinal Field Studies
2000
528 TAYLOR S Understanding information
technology usage: A test
of competing models.
Information Systems
Research
1995
489 Fishbein M Belief, attitude, intention,
and behavior : An
introduction to theory and
research
1975
The biggest node in Figure3 is “Perceived
Usefulness, Perceived Ease of Use, and User Acceptance
of Information Technology” written by Davis in 1989.
This study considers two specific variables,
perceived usefulness and perceived ease of use,
which are hypothesized to be fundamental
determinants of user acceptance. And in his another
article (Davis, et al., 1989) which is the second
biggest node in Figure3 , addresses the ability to
predict peoples' computer acceptance from a
measure of their intentions, and the ability to explain
their intentions in terms of their attitudes, subjective
norms, perceived usefulness, perceived ease of use,
and related variables. These two literatures are the
basis of the research in technology acceptance model
(TAM). Based on TAM, later scholars extended the
theory and developed some new model.
The literature in third and fourth place is written
by Venkatesh. These two literatures are the
knowledge source of TAM2 and UTAUT.
Researchers found that both social influence
processes (subjective norm, voluntariness, and
image) and cognitive instrumental processes (job
relevance, output quality, result demonstrability, and
perceived ease of use) significantly influenced user
acceptance, and a new model named TAM2 was
proposed in 2000. (Venkatesh and Davis, 2000). In
2003, one research gives a review and an empirical
study on the eight existing models of user
acceptance, then a unified model called the Unified
Theory of Acceptance and Use of Technology
(UTAUT) was proposed. Researchers theorize that
four constructs plays a significant role as direct
determinants of user acceptance and usage behavior:
performance expectancy, effort expectancy, social
influence, and facilitating conditions (Venkatesh et
al.2003).
The fifth biggest node is the article co-written by
Taylor and Todd in 1995. The TAM and two
variations of the Theory of Planned Behavior were
compared to assess which model best helps to
understand usage of information technology in this
study, and the results revealed that all three models
performed well in terms of fit and were roughly
equivalent in terms of their ability to explain
behaviour (Taylor and Todd, 1995).
The literature written by Fishbein and Ajzen is
the sixth biggest node in the Figure3.They
developed the theory of reasoned action (TRA) in
this literature in 1975. According to this theory,
attitudes toward a behavior and subjective norms are
the significant predictors of behavioral intention.
And the subjective norm is the person's perception
that most people who are important to him think he
should or should not perform the behavior in
question (Fishbein and Ajzen, 1975).
4 CONCLUSIONS
Acceptance of information technology is not a new
research area, but this research area is so important
that more and more people pay high attention to it
after its appearance. Based on the above analysis, we
draw such conclusions as followed:
1) User acceptance, user adoption, intrinsic
motivation, self-efficacy, satisfaction, planned
behaviour, technology acceptance model, etc. are the
focus research topic in acceptance of IT.
2) As the technology developed, the research
frontiers appeared some new developing trends.
User acceptance in electronic commerce, mobile
services, and social network (web2.0), etc. are the
research frontiers in acceptance of IT.
3) The literatures about TAM, TAM2, TPB, TRA,
etc. are the knowledge resource, or rather, the
theoretical foundations of acceptance of IT. And the
VISUAL ANALYSIS OF RESEARCH ON ACCEPTANCE OF INFORMATION TECHNOLOGY
419

authors Davis F. D., Venkatesh V., Taylor S.,
Fishbein M. and Ajzen I., etc are the main
contributors to this research field.
ACKNOWLEDGEMENTS
This research is included in the programme
“Research on the Marketing Model of Digital
Publication” supported by National Funds of Social
Science. And the number of the programme is
07BTQ003.
REFERENCES
Zhang, P., Sun, H. (2009).The complexity of different
types of attitudes in initial and continued ICT use.
Journal of the American Society for Information
Science and Technology, 60, 2048–2063.
Shiffrin, R. M., & Börner, K. (Eds.). (2004). Mapping
knowledge domains. Proceedings of the National
Academy of Sciences, USA, 101(Suppl. 1), 5183–
5310.
Batagelj, V., Mrvar, A. (1998). Pajek – A Program for
large network analysis. Connections, 21 (2), 47–57.
Persson, O., Danell, R. & Schneider, J. W. (2009). How to
use Bibexcel for various types of bibliometric
analysis. Celebrating Scholarly Communication
Studies: A Festschrift for Olle Persson at his 60th
Birthday. Ed.
Fredrik Åström. Special volume of the e-zine of the ISSI,
05-S, 5-89.
Borgatti, S. P., Everett, M. G., & Freeman, L. C. (1999).
UCINET 5.0 Version 1.00. Natick: Analytic
Technologies.
Borgatti, S. P. (2002). NetDraw: Graph Visualization
Software. Harvard: Analytic Technologies.
Garfield, E., Paris, S. & Stock, W. G., (2006).
HistCited™: A Software Tool for Informatic Analysis
of Citation Linkage. Information Wissenschaft und
Praxis, 57, 391–400.
Chen C. (2006) .CiteSpace II: detecting and visualizing
emerging trends and transient patterns in scientific
literature. Journal of the American Society for
Information Science and Technology, 3,359–377.
Chau, P. Y. K., Au, G. & Tam, K. Y. (2000) .Impact of
information presentation modes on online shopping:
an empirical evaluation of a broadband interactive
shopping service. Journal of Organisational
Computing and Electronic Commerce, 10(1), 1–22.
Oliver R. L. (1980). A Cognitive Model of the
Antecedents and Consequences of Satisfaction
Decisions. Journal of Marketing Research, 17(3),
460–469.
Spreng R. A, MacKenzie, S. B. & Olshavsky R. W.
(1996). A reexamination of the determinants of
consumer satisfaction. Journal of Marketing, 60(3),
15–32.
Davis, F. D. (1989).Perceived usefulness, perceived ease
of use, and user acceptance of information technology.
MIS Quarterly, 13(3), 319–340.
Davis, F. D, Bagozzi, R. P. & Warshaw, P. R. (1989).User
acceptance of computer technology: a comparison of
two theoretical models. Management Science 35(8),
982–1003.
Ajzen, I. (1985). From intentions to actions: A theory of
planned behavior. In J. Kuhl & J. Beckman (Eds.),
Action-control: From cognition to behavior.
Heidelberg, Germany: Springer.
Hansen, T., Jensen, J. M., & Solgaard, H. S. (2004).
Predicting online grocery buying intention: A
comparison of the theory of reasoned action and the
theory of planned behavior. International Journal of
Information Management, 24(6), 539–550.
Venkatesh, V., Davis, F. D. (2000). A theoretical
extension of the technology acceptance model: four
longitudinal field studies. Management Science, 46(2),
186–204.
Taylor, S., Todd, P. (1995).Understanding information
technology usage: a test of competing models.
Information Systems Research, 6(2), 144–176.
Fishbein, M., Ajzen, I. (1975). Belief, attitude, intention,
and behavior: an introduction to theory and research.
Reading, Mass: Addison-Wesley Pub.
ICEIS 2011 - 13th International Conference on Enterprise Information Systems
420