A Study on the User Acceptance Model of SNS Websites Based TAM*
Dan Jin1, Mei-mei Zhou1
1
School of Management and Economics, Beijing Institute of Technology, Beijing, China
(jindan@bit.edu.cn, zhoumm1008@163.com )
Abstract - Based on Davis’s TAM, combining with the
user satisfaction theory in information system and
motivation theory, and the SNS user behavior
characteristics, this study proposed the user acceptance
model on SNS websites. In this model, Perceived Usefulness
and Perceived Ease-of-Use were retained, and Perceived
Enjoyment and Perceived Connectivity were added. In
addition, the external variables affecting these key factors
were subdivided. The questionnaire was designed and
Structural Equation was used to validate the empirical
hypothesis. The results showed that TAM could apply to
user acceptance on SNS website basically, and Perceived
Enjoyment and Perceived Connectivity were all positively
correlated with Willingness, also, the subdivision of external
variable reflected the importance of user activity.
A.
Technology Acceptance Model (TAM)
Based on rational behavior theory, Fred
Davis(1986)put forward TAM. TAM adopts the
well-established causal chain of beliefs → attitude →
intention→behavior which has become known as the
Theory of Reasoned Action (TRA). Based on certain
beliefs, a person forms an attitude about a certain object,
on the basis of which he or she forms an intention to
behave with respect to that object. The intention to
behave is the sole determinant of actual behavior[2](fig.
1).In TAM applications, two key factors, Perceived
Usefulness and Perceived Ease-of-Use, can effectively
explain users’ behavior intention.
Perceived
Usefulness
Key Words - activity level, perceived enjoyment, SNS
websites, technology acceptance model
I.INTRODUCTION
SNS websites is a booming Internet applications,
based on the theory of “Six Degrees of Separation”,
taking the customer relationship as the core, designed to
help people build social networks. The large number of
Internet users makes a great contribution to the rapid
development of SNS sites. Various SNS websites rise
rapidly after 2006, and competition is fierce, causing
serious phenomenon of homogeneity.
MicroBlog, a Twitter-like service, has been rapidly
developed, and the registered users have increased
dramatically.SNS websites users are coincident with
those of MicroBlog to a great extent. Double pressures of
homogenous competition and MicroBlog’ rising, makes
SNS websites face a great challenge. SNS websites need
to absorb new users continuously and retain old ones.
SNS websites are facing with the problem of user
acceptance.
II.LITERATURE REVIEW
The user acceptance problem of SNS websites
belongs to information technology acceptance. The user’s
act in accepting technology is regarded as one of the most
mature research field of information systems[1]. The most
representative theories are theory of rational act
(TRA),theory of planning behavior (TPB), and
technology acceptance model (TAM).
____________________
*
Supported by National Natural Science Foundation of
China(No.70802008), Beijing Municipal Natural Science Foundation
(No. 9112011).
External
Variables
Attitude
Behavior
Intention
System
Use
Perceived
Ease of Use
Fig. 1 Technology Acceptance Model
B.Other Related Theory
Papaeharissi& Rubin(2000) summarized motivation
of Internet usage in the following: interpersonal
communication, killing time, achieving information,
convenience and entertainment[3]. Through the online
questionnaire survey in a German SNS website, Schaefer
&Cora(2008) discussed participating motivation and
running mode, considered the participating motivation
includes keeping in touch, searching for information,
entertainment, communicating, managing existing
relationship and so on[4]. From these motivations, some
other factors may also affect SNS websites usage, apart
from Perceived Usefulness and Perceived Ease-of-Use.
Wixom & Todd(2005) proposed that the user
satisfaction of information system could be united with
Davis’s TAM. Information quality and system quality
influence information satisfaction and system satisfaction
respectively, and information satisfaction and system
satisfaction exert influence on Perceived Usefulness and
Perceived Ease-of-Use respectively[5]. Delone& Mclean
(2003)added service quality in the improved D&M
information system success model, and proposed that the
SERVQUA scale in marketing field could be referred to
measure service quality[6]. As studying the relationship
between intimate degree and diving behavior, Rau(2008)
and others measured the member behavior of
participating in SNS websites with member activity
level[7]. These theories could provide a foundation for
further study on external variables subdivision in TAM.
Ⅲ.MODEL AND HYPOTHESIS
A. User acceptance model of SNS websites
In TAM, the external variables have not been
fractionized, which will make against further analysis the
influencing factors on user acceptance to SNS
websites.SNS websites provide an interactive platform for
friends, on which integrates basic Internet applications,
such as log, photo, video, community and game, and meet
users’ sociality demands through online interactive
among friends, information sharing, participating in
activities
and
other
ways.
Webster&Martocchio(1995)thought entertainment was an
intrinsic motivation using computers in workplaces[8].
Scholars put forward Perceived Enjoyment as doing
Internet empirical study, which refers to entertainment
degree by using SNS websites. Moreover, Perceived
Connectivity refers to being connected with friends in
passions and is not confined by time or location. During
using SNS websites, users may have the feeling of
satisfaction or happiness, which makes users to accept
SNS websites in further [9].
Based on TAM, the user acceptance model for SNS
websites is shown in fig.2.Perceived Usefulness and
Perceived Ease-of-Use are retained in the model, and
Perceived Enjoyment and Perceived Connectivity are
added as another two key factors affecting users to accept
SNS websites. In addition, external variables of the above
factors are further divided into the information quality,
quality system, active degree and the service quality and
related factors.
Service Quality
Individuation
Communication
Perceived
Enjoyment
Innovation
Activitylevel
Participation
Sharing
Sociability
Perceived
Connectivity
Game Interactive
InformationQuality
Accuracy
Timeliness
Perceived
Usefulness
Behavior
Willingness
Integrity
System Quality
Security
Interface
Perceived
Ease-of-Use
Social Impact
Fig.2Prototype of user acceptance model for SNS websites
B. Assumptions of model
The related assumptions in TAM are still established
in this model. And new assumptions about Perceived
Enjoyment and Perceived Connectivity are proposed.
(1) Perceived Ease-of-Use and related assumptions
Basedon customer satisfaction theory and with the
previous empirical data support, Seddon(1997)also
confirmed that system quality has a positive effect on
Perceived Ease-of-Use[10]. In addition, the system security
is much important to users, which means to promise
personal information safety. Moreover, both user
interface and interactive process will affect users to
accept SNS websites.
H1: System quality positive effect on this term
H1a: Security positive effect on it
H1b: Interface positive effect on it
H2: Perceived Ease-of-Use positive effect on this item
(2) Perceived Usefulness and related assumptions
H3: Information Quality positive effect on this item
H3a: Accuracy positive effect on it
H3b: Timeliness positive effect on it
H3c: Integrity positive effect on it
H4: Activity level positive effect on this item
H4a: Participation positive effect on it
H4b: Sharing positive effect on it
H4c: Sociability positive effect on it
H4d: Game interactive positive effect on it
H5: Perceived Ease-of-Use positive effect on this item
H6: Perceived Usefulness positive effect on this item
(3) Perceived Connectivity and related assumptions
H7: Activity level positive effect on this item
H7a: Participation positive effect on it
H7b: Sharing positive effect on it
H7c: Sociability positive effect on it
H7d: Game interactive positive effect on it
H8: Perceived Connectivity positive effect on this item
(4) Perceived Enjoyment and related assumptions
As a community website where users’ activities are
based on group, SNS website should pay much attention
to users’ activity involvement, which can tell the
influence of Perceived Connectivity to Perceived
Enjoyment.
H9: Service quality positive effect on this item
H9a: Individuality positive effect on it
H9b: Communication positive effect on it
H9c: Innovation positive effect on it
H10: Activity level positive effect on this item
H10a: Participation positive effect on it
H10b: Sharing positive effect on it
H10c: Sociability positive effect on it
H10d: Game interactive positive effect on it
H11: Perceived Connectivity positive effect on this item
H12: Perceived Enjoyment positive effect on this item
(5) social impact and related assumptions
Social impact refers to others influence on
individual for using SNS websites. Similar to the TRA
subjective enorms, people are very conscious of others
view about their particular behavior willing. Whether
individual uses SNS websites would be influenced by
others recommendation or evaluation.
H13: Social impact positive effect on this item
Ⅳ. RESEARCH METHODS
A. Survey questionnaire design
In order to verify the model assumptions, a
questionnaire is used to collect data. The questionnaire
uses a standard 7-point Likert-typescale. The 7 point are
"completely disagree", "relatively disagree", "some
disagree", "not sure" ,"some agree", "relatively agree" and
"completely agree". According to actual situation,
respondent shave the right to choose from 1(completely
disagree) to 7 (completely agree). As the final
questionnaire data is analyzed and tested by using
structural equation model, it need to meet the
requirements that structural equation model to observed
variables and characteristics of measuring factors, so
three or more items are used to measure each factor. All
the measure items use the mature scales which have been
used in empirical study by researchers at home and
abroad, and are adjusted according to SNS websites
characteristics and questionnaire’s semantic environment.
The questionnaire has 18 variables to measure,
including13external variables, such as accuracy,
timeliness, integrity, security, interface, individuality,
innovation, communication, participation, sociability,
sharing, game interactive and social impact, and 5
internal variables, as Perceived Usefulness, Perceived
Ease-of-Use, Perceived Enjoyment and Perceived
Connectivity and Willingness. Above all, the total
number to be measured is 58.
B. pre -test Questionnaire
In order to ensure the effectiveness of the survey
questionnaire, it is necessary to pretest it before actually
using it. This paper uses SPSS 18 to do reliability and
validity analysis on the test results. The reliability
analysis results showed that Cronbach's Alpha value of
every measured factor was greater than 0.5, while the
overall questionnaire reliability was 0.959, indicating the
internal consistency of the questionnaire was acceptable.
In the validity analysis, separate factor analysis was made
on corresponding measured items of independent
variables, mediating variables and dependent variables.
The factor analysis result showed that other factors were
all better classified in the corresponding dimension apart
from two factors measured items, sociability and social
impact of the independent variables. So sociability factor
and social impact factor were deleted.
A.
Second order confirmatory factor analysis
Second order confirmatory factor analysis (CFA) is
put forward as there is high degree relevance among
original first order factors in the first order CFA, and the
first order CFA can be in agreement with sample data. In
the model, information quality, system quality, service
quality and activity level are measured with the
multidimensional method, so AMOS 17 would be used
respectively during their second order factor analysis. The
analysis results show, all the first order factors to second
order factors of information quality, system quality,
service quality, and activity level, the load capacity value
lie between 0.5 and 0.95, and the Significance Probability
and C.R. are greater than 1.96, and decision criteria is
achieved totally. Meanwhile, compared with the
goodness-of-fit standard, the whole goodness-of-fit
reaches the basic standard. So we can conclude that the
first order factors of information quality, system quality,
service quality and activity level would measure these
second order factors well.
B.
Model analysis and revision
According to the validity inspection and analysis
results of second order CFA above, social impact and
sociality factors are removed from the original hypothesis
model, the goodness-of-fit indexes of the model are
summarized as table 1. The ratio chi-square/freedom
degree of the model is 1.828<2, RMSEA is
0.074<0.080,two goodness-of-fit indexes meet the
standard. But other goodness-of-fit indexes, such as
GFI(0.658<0.9),
AGFI(0.62<0.8),
CFI(0.828<0.9),
TLI(0.816<0.9) and NFI(0.689<0.8), are not up to the
standards, thus the model need to be modified and
optimized.
AMOS offers two model modification indexes, in
which modification index MI is used for model
expanding, and the critical ratio C.R. is used for model
restricting. According to the value of critical ratio and
modification indexes, following the principle of
modifying one parameter once, the final revised model is
shown in fig.3.
ActivityDegree
Participation
Sharing
Perceived
Enjoyment
GameInteractive
C.Data collection
Information Quality
According to the pre -test results, the questionnaire
were modified in final two ways, electronic and paper
questionnaire. On the principle of simple random
sampling, questionnaires were distributed. 170 electronic
questionnaires and 68 paper questionnaire were
distributed, altogether 202 questionnaires were returned.
After moving the data obviously not meeting the
requirements, 153valid questionnaires were remained.
Perceived
Connectivity
Behavior
Intention
Accuracy
Timeliness
Integrality
System Quality
Security
Interface
Perceived
Usefulness
Perceived
Ease-of-Use
Fig.3 SNS websites user acceptance model based on TAM
Ⅴ. MODEL ANALYSIS
 2 df
TABEL Ⅰ Goodness-of-fit Indexes of Full Model
Absolute goodness-of-fit index
Relative goodness-of-fit index
GFI
AGFI
RMSEA
CFI
NFI
TLI
（1, 5）
>=0.9
>=0.8
<0.08
>=0.9
>=0.8
>=0.9
1.828
0.658
0.621
0.074
0.828
0.689
0.816
Path
connectedness <--- activity
usefulness <--- information
easiness <--- system
entertainment <--- activity
usefulness <--- activity
entertainment <--- connectedness
willingness <--- usefulness
willingness <--- entertainment
willingness <--- easiness
willingness <--- connectedness
easiness4 <--- easiness
easiness3 <--- easiness
easiness2 <--- easiness
easiness1 <--- easiness
willingness4<--- willingness
willingness3<--- willingness
willingness2<--- willingness
willingness1<--- willingness
usefulness4<--- usefulness
usefulness3<--- usefulness
usefulness2<--- usefulness
usefulness1<--- usefulness
entertainment4 <--- entertainment
entertainment3 <--- entertainment
entertainment2 <--- entertainment
entertainment1 <--- entertainment
connectedness3<--connectedness
connectedness2<--connectedness
connectedness1<--connectedness
where *** p<0.001
TABEL Ⅱ The Path Coefficient of Revised Full Model
Estimated
Standard Deviation Critical Ratio Significant Probability
Coefficient
(S.E.)
(C.R.)
(p)
.562
.121
4.627
***
.913
.232
3.940
***
.702
.111
6.340
***
.758
.120
6.311
***
.343
.137
2.492
.013
.322
.102
3.147
.002
.229
.084
2.731
.006
.340
.084
4.070
***
.213
.084
2.530
.011
.307
.096
3.205
.001
1.342
.121
11.089
***
1.411
.125
11.283
***
1.000
1.128
.099
11.415
***
1.034
.076
13.592
***
.981
.068
14.359
***
.880
.070
12.591
***
1.000
.944
.100
9.440
***
.946
.103
9.225
***
1.000
1.193
.117
10.235
***
1.000
1.147
.061
18.711
***
1.016
.060
16.805
***
.923
.078
11.784
***
1.214
.183
6.651
***
Standard
Coefficient
.535
.641
.735
.620
.315
.277
.221
.368
.177
.285
.919
.942
.717
.790
.850
.876
.813
.864
.729
.716
.803
.779
.870
.966
.918
.762
.811
1.000
.685
.473
.149
The path of regression coefficients of each factor of
the revised full model has increased, the value of C.R. is
larger than 1.96, some of the path of significant
probability are larger than 0.05 that are sufficiently close
to the standard ,which shows the modification effect well.
Table 2is the path coefficient of the revised model for the
first time.
The goodness-of-fit of the revised model is shown as
table 3.The value of chi-square (1468.758) and freedom
(835) improve markedly than the preceding ones. The
ratio Chi-square/degree of freedom (1.759<2) and the
value of RMSEA (0.071<0.08) reach the standard both.
Several other goodness-of-fit indexes meet the standard
basically. For numbers of latent variables exist in the
model, the relationship between factors is relatively
complex and some indexes may be influenced greatly by
the sample size, the revised model can be regarded as the
final model.
3.171
.002
.296
TABEL Ⅲ Revised Goodness-of-fit Index of Full Model
Absolute Goodness-of-fit Index
Relative Goodness-of-fit Index
x2/df
GFI
AGFI RMSEA
CFI
NFI
TLI
（1, 5）
1.759
C.
>=0.9
0.717
>=0.8
0.680
<0.08
0.071
>=0.9
0.863
>=0.8
0.734
>=0.9
0.852
Test Results of Model Hypothesis
The model set up in this study originally uses
13level 1 hypothesis from H1to H13.As system quality,
information quality, service quality, and activity level use
multidimensional measure method, H1 to H6 each exists
level 2 hypothesis. The data analysis results support the
rest hypothesis apart from H4c, H5, H7c, H9, H9a, H9b,
H9c, H10c andH13.
Ⅵ. CONCLUSION AND PROSPECT
This study constructs SNS websites user acceptance
model based on TAM, and model hypothesis is verified
by the structure equation model. The conclusion can be
drawn as follows: (1)TAM is basically suitable to SNS
websites user acceptance study, but no evidence supports
the causality between Perceived Usefulness and
Perceived Ease-of-Use. (2)Both Perceived Enjoyment and
Perceived Connectivity have a positive correlation with
Usage Willingness, and Perceived Connectivity further
affects Perceived Enjoyment. (3)The subdivision of
external variables reflects the importance of user activity,
the activity level influences Perceived Usefulness,
Perceived Connectivity and Perceived Enjoyment
simultaneously, while the influence of service quality to
Perceived Enjoyment is deleted for path of regression
coefficients is too little.
Based on above study, some constructive
suggestions are proposed to SNS service providers:
perfect amusement and e-commerce functions to enhance
user’ viscidity, pay attention to interface operation to
optimize user’ experience; provide service in information
filtering, sorting and pushing, study deeply on promoting
user’ activity level.
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