Upload
mohammad-zandi
View
220
Download
0
Embed Size (px)
Citation preview
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1067
EMPIRICAL STUDY OF INTERNET ADOPTION AMONG SMALL AND
MEDIUM ENTREPRENEURS (SMES) IN MALAYSIA
(A STRUCTURAL EQUATION MODELING APPROACH)
Ilham Sentosa
Hadi Nejatian
Shishi Kumar Piaralal
Ahmad Faisal(Limkokwing University of Creative Technology of Malaysia)
Abstract
This paper seeks to examine empirically the antecedents of internet intention and adoption of small and medium
scale enterprises (SME) by applying the conceptual theory of technology acceptance model (TAM) The
respondents comprise of 237 owners of food related SMEs in an eastern state of Malaysia A questionnaire wasdesigned to tap into the ownerrsquos perception on perceived usefulness of the internet perceived ease of use of the
internet and perceived credibility on technology intention to use the technology and adoption of the internet
itself Seven hypothesized relationships were tested in the structural model The data was analyzed usingstructural equation modeling (SEM) to test the causal and mediating effects amongst latent variables From the
analysis the hypothesized model fit fails to be supported (plt05) The findings support the TAM theory
extremely well whereby all the hypothesized paths were asserted The generated model found three significant
direct paths between perceived usefulness perceived credibility and intention as well as between intention and
adoption The re-specified model produces two significant direct paths (perceived usefulness to intention and
intention to adoption) and also introduces three new paths (direct paths from perceived usefulness perceived
ease of use and perceived credibility to adoption) The models also manage to establish partial mediating effects
of intention on the said relationships between exogenous and internet adoption The finding is discussed in the
context of SME intention and adoption of the internet in East Malaysia
1 Introduction
Small and medium scale enterprises (SME) have been increasing rapidly in Malaysia For the food related
SMEs the challenge for survival is even greater Much of the reasons for survival of SME in this millenniumdepend on how information technology (IT) has been used in the daily operations of the SME Information
communication technology (ICT) is something that must be learnt and practiced by SME in order to be
successful IT literate SMEs owners are needed especially in the usage of the internet for business
enhancement
The numbers of internet users in Malaysia has increased tremendously in recent years It has been indicated that
there is almost 15 million users of internet in 2008 an increase of three folds as compared to internet users in
the 2000 (wwwinternetworldstatscom) This could mean that there is a vast potential of internet marketing of
products and services for the SMEs in Malaysia alone However the scant empirical study and literature on
SME involvement in internet marketing and the like has impetus this study as deem necessary With that in
mind this study attempts to examine the empirical relationships between technology usage perception andcredibility with internet adoption Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized
2 Literature Review
Technology acceptance model (Davies 1989) or TAM as it is commonly known was adapted from the theory of
reasoned action (Ajzen amp Fishbein 1980 Fishbein amp Ajzen 1975) and theory of planned behavior (Ajzen
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1068
1985 Ajzen 1991) TAM proposes specifically to explain the determinants of information technology end-
userrsquos behavior towards information technology (Saade Nebebe amp Tan 2007) In TAM Davis (1989) proposes
that the influence of external variables on intention is mediated by perceived ease of use (PEU) and perceived
usefulness (PU) TAM also suggests that intention is directly related to actual usage behavior (Davis Bagozzi ampWarshaw 1989) Trust and perceived risks have also been examined in TAM previous studies but have shown
mixed findings (Kim et al 2001 Liao et al 1999 and Pavlou 2001) Perceived credibility is the first dimension
of trust and will be used interchangeably as defined by Lindskold (1978) Behavioral intentions may be defined
as a measure of the strength of onersquos intention to perform a specific behavior such as the use of an informationsystem (IS) (Fishbein amp Ajzen 1975) In general prior research has suggested a positive impact or influence
between experience with computing technology and a variety of outcomes such as an affect towards computers
and computer usage (Levin and Gordon 1989 Harrison and Rainer 1992 Agarwal and Prasad 1999)
Perceived usefulness and intention
Perceived usefulness is defined as the extent to which a person believes that using a particular system will
enhance his or her job performance There has been extensive research in the information systems (IS)
community that provides evidence of the significant effect of perceived usefulness on usage intention (PettyCacioppo amp Schumann 1983 Taylor amp Todd 1995 Venkatesh amp Davis 2000) Daviss (1989) found that
perceived usefulness has a stronger influence on usage Daviss study shows that users are driven to adopt a
technology primarily because of the functions it provides them and secondarily because of the easiness of
benefiting from those functions Customers are often willing to overlook some dif ficulties of usage if the
service provides critically needed functions
Perceived ease of use and intention
Extensive research over the past decade provides evidence of the significant effect of perceived ease of use on
usage intention either directly or indirectly through its effect on perceived usef ulness (Agarwal and Prasad
1999 Davis et al 1989 Hu et al 1999 Jackson et al 1997 Venkatesh 1999 2000 Venkatesh and Davis
1996 2000 Venkatesh and Morris 2000) In order to prevent the ldquounder-usedrdquo useful system probleminformation systems need to be both easy to learn and easy to use If the system was easy to use it will be less
threatening to the individual (Moon and Kim 2001) This implies that perceived ease of use is expected to have
a positive influence on usersrsquo perception of credibility and intention of using internet banking systems
Perceived credibility and intention
Perceived credibility of the internet banking will also contribute to the increase in usage of internet banking
Perceived credibility is defined as to which one partner believes that the other partner has the required expertise
to perform the job eff ectively and reliably (Ganesan 1994) This is to say that trust based on a partnerrsquos
expertise and reliability focuses on the objective credibility of an exchange partner ie expectancy that the
word or written statement of the partner can be relied on (Lindskold 1978) According to Morgan and Hunt
(1994) confidence stems in a part from the belief that the trustworthy party is reliable and has high integrity
An effective customer-company relationship requires trust (Morgan and Hunt 1994) and for the company such
relationships are crucial to managing trust because a customer typically must buy a service before experiencing
it (Berry amp Parasuraman 1986) The importance of including trust has been pointed out by Polatoglu and Ekin
(2001) in their qualitative study and also by Kardaras and Papathanassiou (2001) who researched corporate
customers Perceived credibility also refers to two important dimensions which are security and privacy
Security is defined as the protection of information or systems from unsanctioned intrusions or outflows whileprivacy is the protection of various types of data that are collected (with or without the knowledge of the users)
during usersrsquo interactions with the internet (Hoffman et al 1999) The usage intention of internet banking could
be affected by usersrsquo perceptions of credibility regarding security and privacy issues Daniel (1999) predicted
security to be one of the determinants of customer acceptance of internet banking
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 316
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1070
Samples and sampling
Owners of Small and medium sized entrepreneurs (SME) who operated their businesses in an eastern state of
Malaysia were the main respondents A total of 305 owners from various products were requested to complete a
questionnaire that contained measures of the constructs of concern The questionnaires were distributed to the
respondents by using simple random sampling method Out of the desired sample size of 305 245 were
returned This gives a response rate of 8032 As such the response rate for this study is adequate for SEM
analysis whereby after outliersrsquo deletion 237 questionnaires were subsequently used for analysis
Instrument
A total of 31 observed variables made up the measurement of exogenous independent varibles such as perceivedusefulness (6 items) perceived ease of use (6 items) perceived credibility (8 items) internet intention (5 items)
and internet adoption (8 items) adapted and modified from Wang et al (2003) The scaling used in this research
is the 7-point Likert scale of 1-strongly disagree 2-disagree 3-slightly disagree 4-neutral 5- slightly agree 6-
agree and 7-strongly agree The demographic variables asked are gender race age education and monthly
income of the respondent
Data Screening
A rigorous data screening procedures were implemented on the raw SPSS data such as outliers detection
reliability normality test and validity tests The 245 dataset were coded and saved into SPSS version 16 and
analyzed using AMOS version 70 In this study a test for multivariate outliers is conducted using the
techniques described by Tabachnick and Fidell (2007) The Mahalanobis distance was calculated based on a
total of 31 observed items The criterion of plt0001 and critical value of χ 2 = 5970 is used The tests conductedidentified 8 cases with Mahalanobis values (D2) above 5970 The Mahalanobis analysis succeeded in
identifying the multivariate outliers which were deleted permanently leaving 237 datasets to be used for further
analysis
Hypotheses Results
The hypothesized model shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the data
to the re-specified model Finally a re-specified model was generated with pgt05 (Figure 5) Thus the re-
specified model indicates a better goodness of fit indices (See table 9) Further analysis of competing model ororiginal model (TAM) shows a goodness of fit structure with pgt05 The R2 of hypothesized model on adoption
shows a high value of 86 Hence it indicates that this model can be explained by variance of exogenous
variables (PEU PU and PC Intention) of 86 Similarly intention can only explain 751 variance in the
model while adoption explains 899 variance in the model Direct influences of the exogenous and
endogenous variables are shown in Table (10) Thus H1 H3 and H4 are asserted Only H2 is not significant
thus failed to be asserted
Several statistical validity tests and analysis were then conducted such as reliability test and composite
reliability tests validity tests using confirmatory factor analysis (CFA) for construct validity discriminant
validity for multi-collinearity treatment descriptive analysis correlation and structural equation modeling
analysis The step in SEM analysis were CFA analysis measurement exogenous (Figure 2) and endogenousanalysis (Figure 3) discriminant analysis composite reliability analysis and directindirect impact analysis
(mediating effect) and finally testing the goodness of fit for the hypothesized and generated model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1071
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
80
88
78
58
PU5
e05
76
58
PU4
e04
76
69
PU3
e03
83
52
PU2
e02
72
62
EOU6e12
7962
EOU5e11
78
59
EOU4e10
77
61
EOU3e0978
59
EOU2e0877
20
CRE6e18
44
24
CRE4e16
49
50
CRE3e1571
27
CRE2e1452
22
CRE1e13
46
Standardized estimatesChi-Square 90378
Df 75
Ratio 1205
P Value 109
GFI 949
RMSEA 029
Figure 2 Confirmatory Factor Analysis of Exogenous Measurements
Internet
Adoption
Internet
Intention
INT1 e2455
INT2 e2544
INT3 e2652
INT4 e27
46
INT5 e28
65
IA8
e36
70
IA7
e35
28
IA6
e34
53
IA5
e33
78
IA4
e32
83
IA3
e31
68
IA2
e30
67
IA1
e29
78
Standardized estimates
Chi-Square 80083
Df 64
Ratio 1251
P Value 085
GFI 952RMSEA 033
83
Figure 3 Confirmatory Factor Analysis of Endogenous Measurements
4 Results
Profile of the RespondentsThe profile of the companies involved in this study indicates that the SMEs utilize internet products
predominantly for financial services such as paying bills salaries and invoicing (35) making order
information (241) electronic email (236) marketing (236) submitting tenders to customers (236)
document transferring (19) purchasing raw materials (84) interaction with government (51) voice or
audio communication (51) and video conferencing (51) Most of the respondents are in the following
business sectors health or pharmaceutical (295) IT business services (295) and others (241) retail
government (156) public services (135) education (68) manufacturing (51) and insurance (51)
The SMEs in the respondent list mostly have number of employee in the category of less than 10 employees
(844) 11 to 50 (135) and more than 51 employee (17) Most of the SME Company is located in urbanarea (755) suburban (177) and rural area (68) There are slightly more female (608) than male
respondents (392) The kind of technology the SMEs used are communication systems (eg groupware e-
mail) (342) transactional systems for accounting finance marketing etc (245) desktop suites (eg Wordprocessing productivity)-(152) interorganisational information systems (EDI Electronic Business) (156)
decision support systems for accounting finance marketing etc (122) enterprise systems (ERP CRM)
(34) and other (84) The job positions of the respondents are owners (207) CEO (34) operation
manager (51) line manager (118) and staff (591) The respondentsrsquo ages are less than 25 year old
(477) 26 ndash 40 year old (439) and more than 41 year old (84) Their education background are high
school (38) diploma (308) bachelor degree (194) and master degree (118) Those respondents with
professional qualification in IT are 228 The total business capital of the SMEs are in the following
categories less than leRM5000 (278) RM5000ndashRM10000 (173) RM10000ndashRM20000 (118)
RM20000ndashRM50000 (122) and RM50000ndashRM100000 (308)
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1072
Table 3 Profiles of Respondents (N=237)
Demographics Frequency Valid Percent
Company utilize the Internet product for
1
Electronic mail2 Document transferring
3 Financial paying bills salaries invoicing etc
4 Marketing5 Submitting tenders to customers
6 Purchasing raw materials office supplies etc
7 Making order information available to customers8 Interaction with government
9 VoiceAudio communication (VOIP)
10 Video conferencing
5645
83
5616
20
5712
12
12
23619
350
23668
84
24151
51
51
Business sector1 Education
2 Manufacturing3 Retail Government
4 Public Services
5 BankingFinance
6 Insurance
7 Construction8 HealthPharmaceutical
9 Business ServicesIT business services
10 Other
16
1237
32
-
12
-25
70
57
68
51156
135
-
51
-105
295
241
Number of Employee 1 Less than 102 11 ndash 50
3 More than 51
20132
4
848135
17
Company location1 Urban
2 Sub Urban
3 Rural
179
42
16
755
177
68
Gender 1 Male
2 Female
93
144
392
608
Level of applications
1 Desktop suites (eg Word processing productivity)2 Communication systems (eg groupware e-mail)
3 Transactional systems for accounting finance marketing etc4 Decision support systems for accounting finance marketing etc
5 Enterprise systems (ERP CRM)
6 Interorganisational Information systems (EDI Electronic Business)7 Other
3681
5829
8
3720
152342
245122
34
15684
Job Position1 Owner
2 CEO
3 Operation Manager
4 Line Manager5 Staff
49
8
12
28140
207
34
51
118591
Age
1 Less than 25 year old2 26 ndash 40 year old
3 More than 41 year old
113104
20
477439
84 Education Background
1 High School
2 Diploma3 Bachelor Degree
4 Master Degree
5 Doctoral Degree
90
7346
28
-
380
308194
118
-
Professional qualification in IT1 No
2 Yes
183
54
772
228
The amounts of business capital
1 leRM5000
2 gtRM5000ndash10000
3 gtRM10000ndash20000
4 gtRM20000ndash50000
5 gtRM50000ndash100000
66
41
28
29
723
278
173
118
122
308
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 716
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1073
Descriptive Analysis of Variables
The research framework consists of three exogenous and two endogenous variables (Table 4) Each construct
shows Cronbach alpha readings of acceptable values of above 060 (Nunnally 1970) The composite reliabilityalso shows exceptional high values of above 080
Table 4 Descriptive Statistics of Variables
Variable NameNo of
Items
Mean
(Std Dev)
Cronbachrsquos
Alpha
Composite
Reliability
Endo 1
Endo 2
Exo 1Exo 2
Exo 3
Internet Intention
Internet Adoption
Perceived UsefulnessPerceived Ease of Use
Perceived Credibility
5
8
66
6
4063(0895)
3938(0901)
3888(0833)3804(0789)
3857(0861)
0661
0863
08960903
0692
0897
0972
09730976
0860
Total items 31
Convergent validity
From the confirmatory factor analysis result in Table 5 we observed that the factor loadings of all observedvariables or items are adequate ranging from 0392 to 0873 The factor loadings or regression estimates of
latent to observed variable should be above 050 (Hair et al 2006)This indicates that most of the constructs
conform to the convergent validity test The remaining numbers of items for each construct are as follows
Perceived Usefulness (4 items) Perceived ease of use (5 items) perceived credibility (5 items) internet
intention (5 items) and internet adoption (6 items)
Table 5 Final Confirmatory Factor Analysis Results of Construct Variables
Variable Code AttributesFactor
Loadings
Factor 1
Perceived
Usefulness
(4 items)
PU2
PU3PU4
PU5
Using internet would improve my job performance
Using internet would increase my productivityUsing internet would enhance my effectiveness on the job
Using internet would make it easier to do my job
0723
08730754
0756
Factor 2PerceivedEase of Use
(5 items)
EOU2EOU3
EOU4EOU5
EOU6
I would find it easy to use internet to obtain decision-making informationMy interaction with the internet was clear and understandable
I found the internet to be flexible to interact withIt would be easy for me to become skillful at using internet
I found the internet easy to use
07640787
07630788
0785
Factor 3
Perceived
Credibility(5 items)
CRE1
CRE2
CRE3
CRE4
CRE6
Internet has privacy
I feel confident in my activities with internet
When using internet I am sure that certain managerial and technical proceduresexist to secure all the data on this system
Internet has a good security system
When using internet I am sure of the consistency of information processing on this
system
0467
0511
0727
0525
0392
Factor 4
Internet
Intention
(5 items)
INT1
INT2
INT3
INT4
INT5
I think it would be very good to use the Internet for my company activities in
addition to traditional methods
In my opinion it would be very desirable to use the Internet for my companyactivities in addition to traditional methods
It would be much better for me to use the Internet for my company activities inaddition to traditional methodsUsing the Internet for my company activities is a good idea
Overall I like using the Internet for my company activities
0495
0425
0506
0422
0588
Factor 5Internet
Adoption
(6 items)
IA1IA2
IA3
IA4IA5
IA6
The internet now day is prominent strategyThe internet is safe
The internet saving cost and time
The internet applications supporting the company business processesHow much would you say your profitearn of your business through internet each
month
I have been using internet
07950650
0686
08240793
0495
TOTAL 25 Items
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 816
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1074
Discriminant Validity of Constructs
Table 6 shows the result of the calculated variance extracted (VE) to support discriminant validity of constructs
Average variance extracted (AVE) is the average VE values of two constructs (Table 7) According to Fornell
amp Larcker (1981) average variance extracted (AVE) should be more than the correlation squared of the two
constructs to support discriminant validity (compare table 6 and table 7) Each AVE value is found to be more
than correlation squared (see Table 8) thus discriminant validity is supported or multicollinearity is seemingly
absent In other words each construct could be considered distinct
Table 6 Variance Extracted of Variables
Observe
Variables
Std Regressions
WeightSMC error ε j Composite reliability Variance Extracted
PU2
PU3
PU4PU5
0723
0837
07540756
0523
0700
05690572
0086
0087
00890097
0973 0955
total 307 2364 0262
EOU2
EOU3EOU4
EOU5
EOU6
0764
07870763
0788
0785
0584
06190582
0621
0616
0070
00770078
0072
0078
0976 0961
total 3887 3022 0375
CRE1CRE2
CRE3
CRE4CRE6
04670511
0729
05250392
02180261
0532
02760153
02460214
0212
02600189
0860 0649
total 2624 144 1121
INT1
INT2
INT3INT4
INT5
0495
0425
05060422
0588
0245
0180
02560178
0346
0130
0157
01740166
0187
0897 0680
total 2436 1205 0684
IA1IA2
IA3
IA4IA5
IA6
07950650
0686
08240793
0495
06320423
0471
06790628
0245
00720082
0083
00730115
0087
0972 0949
total 4243 3078 0512
Table 7 Average Variance Extracted (AVE) Matrix of Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)
Perceived Easy of Use (2)
Perceived Credibility (3)
100
0974
0916
100
0918 100
Table 8 Correlation amp Correlation square Matrix among Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)Perceived Easy of Use (2)
Perceived Credibility (3)
1000799 (0638)
0765 (0585)
100
0868 (0753) 100
Correlation is significant at 001 level (2-tailed) values in brackets indicate correlation squared
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 916
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1075
Goodness of Fit Indices
Confirmatory factor analysis (CFA) was conducted on every construct and measurement models (see Table 9)
The data fit the construct measurement and structural models based on assessment criteria such as GFI CFI
TLI RMSEA (Bagozzi amp Yi 1988) All CFAs of constructs produced a relatively good fit as indicated by the
goodness of fit indices such as CMINdf ratio (lt2) p-value (gt005) Goodness of Fit Index (GFI) of gt95 and
root mean square error of approximation (RMSEA) of values less than 08 (lt08) Later four structural models
were tested for goodness of fit (hypothesized generated re-specified and competing models) Table 9 shows
that the goodness of fit of structural models (generated model re-specified and competing models) achieved
better goodness of fit compared to the hypothesized model Between the three models re-specified modelachieved the highest absolute fit because its p-value is the highest (p=0144)
Table 9 Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=237)
Finals
Models
Perceived
Usefulness
Ease of
UseCredibility
Internet
Intention
Internet
Adoption
Exogenous
Measurement
Endogenous
Measurement
Hypothesized
Model
Generated
Model
Re-Specified
ModelCompeting
Model
Items
remain
6 6 6 5 8 14 13 31 25 25 17
CMIN 11170 13745 11643 8769 30990 90378 80083 540394 299122 289512 141000
Df 9 9 9 5 20 75 64 427 268 265 115
CMIN
df
1241 1527 1294 1754 1550 1205 1251 1266 1116 1092 1226
p-value 0264 0132 0234 0119 0055 0109 0085 0000 0093 0144 0050
GFI 0985 0980 0989 0985 0968 0949 0952 0874 0910 0913 0937
CFI 0997 0994 0990 0972 0985 0989 0984 0967 0987 0990 0987
TLI 0995 0990 0983 0943 0979 0987 0980 0964 0986 0989 0984
RMSEA 0032 0047 0035 0057 0048 0029 0033 0034 0022 0020 0031
Structural Models Generated
The hypothesized model in Figure 4 shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the datato the generated model Subsequently a generated model (same paths as hypothesized model) was derived with
a goodness of fit been achieved (pgt05) Thus the generated model indicates a better goodness of fit indiceswhen some observed variables were deleted (Figure 5) Additionally a re-specified model has also been derived
whereby new paths have been suggested by modification indices and goodness of fit has also been achieved
(pgt05) (Figure 6) The hypotheses tested are based on the findings from the generated and re-specified model
Additionally analysis of competing model or original model (TAM) was also conducted to test the soundness
of the root model which shows a goodness of fit structure with pgt05 as well (Figure 7)
Figure 4 Hypothesized Model
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
86
Internet
Adoption
78
Internet
Intention
79
83
76
93
58
PU6
e06
76
60
PU5
e05
77
58
PU4
e04
76
68
PU3
e03
83
51
PU2
e02
72
60
PU1
e01
78
62
EOU6e12
7861
EOU5e11
78
61
EOU4e10
78
60
EOU3e0977
59
EOU2e0877
62
EOU1e07
79
13
CRE6e18
3654
CRE5e17
74
29
CRE4e16
54
59
CRE3e1577
24
CRE2e1449
21
CRE1e13
46
25
INT1 e2450
17
INT2 e254125
INT3 e2650
19
INT4 e27
43
34
INT5 e28
59
48
IA8
e36
69
09
IA7
e35
29
27
IA6
e34
52
62
IA5
e33
7968
IA4
e32
8248
IA3
e31
69
43
IA2
e30
66
62
IA1
e29
79
R01
R02
Standardized estimates
Chi-Square 540394
Df 427
Ratio 1266
P Value 000GFI 874
RMSEA 034
31
20
44
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1016
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1068
1985 Ajzen 1991) TAM proposes specifically to explain the determinants of information technology end-
userrsquos behavior towards information technology (Saade Nebebe amp Tan 2007) In TAM Davis (1989) proposes
that the influence of external variables on intention is mediated by perceived ease of use (PEU) and perceived
usefulness (PU) TAM also suggests that intention is directly related to actual usage behavior (Davis Bagozzi ampWarshaw 1989) Trust and perceived risks have also been examined in TAM previous studies but have shown
mixed findings (Kim et al 2001 Liao et al 1999 and Pavlou 2001) Perceived credibility is the first dimension
of trust and will be used interchangeably as defined by Lindskold (1978) Behavioral intentions may be defined
as a measure of the strength of onersquos intention to perform a specific behavior such as the use of an informationsystem (IS) (Fishbein amp Ajzen 1975) In general prior research has suggested a positive impact or influence
between experience with computing technology and a variety of outcomes such as an affect towards computers
and computer usage (Levin and Gordon 1989 Harrison and Rainer 1992 Agarwal and Prasad 1999)
Perceived usefulness and intention
Perceived usefulness is defined as the extent to which a person believes that using a particular system will
enhance his or her job performance There has been extensive research in the information systems (IS)
community that provides evidence of the significant effect of perceived usefulness on usage intention (PettyCacioppo amp Schumann 1983 Taylor amp Todd 1995 Venkatesh amp Davis 2000) Daviss (1989) found that
perceived usefulness has a stronger influence on usage Daviss study shows that users are driven to adopt a
technology primarily because of the functions it provides them and secondarily because of the easiness of
benefiting from those functions Customers are often willing to overlook some dif ficulties of usage if the
service provides critically needed functions
Perceived ease of use and intention
Extensive research over the past decade provides evidence of the significant effect of perceived ease of use on
usage intention either directly or indirectly through its effect on perceived usef ulness (Agarwal and Prasad
1999 Davis et al 1989 Hu et al 1999 Jackson et al 1997 Venkatesh 1999 2000 Venkatesh and Davis
1996 2000 Venkatesh and Morris 2000) In order to prevent the ldquounder-usedrdquo useful system probleminformation systems need to be both easy to learn and easy to use If the system was easy to use it will be less
threatening to the individual (Moon and Kim 2001) This implies that perceived ease of use is expected to have
a positive influence on usersrsquo perception of credibility and intention of using internet banking systems
Perceived credibility and intention
Perceived credibility of the internet banking will also contribute to the increase in usage of internet banking
Perceived credibility is defined as to which one partner believes that the other partner has the required expertise
to perform the job eff ectively and reliably (Ganesan 1994) This is to say that trust based on a partnerrsquos
expertise and reliability focuses on the objective credibility of an exchange partner ie expectancy that the
word or written statement of the partner can be relied on (Lindskold 1978) According to Morgan and Hunt
(1994) confidence stems in a part from the belief that the trustworthy party is reliable and has high integrity
An effective customer-company relationship requires trust (Morgan and Hunt 1994) and for the company such
relationships are crucial to managing trust because a customer typically must buy a service before experiencing
it (Berry amp Parasuraman 1986) The importance of including trust has been pointed out by Polatoglu and Ekin
(2001) in their qualitative study and also by Kardaras and Papathanassiou (2001) who researched corporate
customers Perceived credibility also refers to two important dimensions which are security and privacy
Security is defined as the protection of information or systems from unsanctioned intrusions or outflows whileprivacy is the protection of various types of data that are collected (with or without the knowledge of the users)
during usersrsquo interactions with the internet (Hoffman et al 1999) The usage intention of internet banking could
be affected by usersrsquo perceptions of credibility regarding security and privacy issues Daniel (1999) predicted
security to be one of the determinants of customer acceptance of internet banking
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 316
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1070
Samples and sampling
Owners of Small and medium sized entrepreneurs (SME) who operated their businesses in an eastern state of
Malaysia were the main respondents A total of 305 owners from various products were requested to complete a
questionnaire that contained measures of the constructs of concern The questionnaires were distributed to the
respondents by using simple random sampling method Out of the desired sample size of 305 245 were
returned This gives a response rate of 8032 As such the response rate for this study is adequate for SEM
analysis whereby after outliersrsquo deletion 237 questionnaires were subsequently used for analysis
Instrument
A total of 31 observed variables made up the measurement of exogenous independent varibles such as perceivedusefulness (6 items) perceived ease of use (6 items) perceived credibility (8 items) internet intention (5 items)
and internet adoption (8 items) adapted and modified from Wang et al (2003) The scaling used in this research
is the 7-point Likert scale of 1-strongly disagree 2-disagree 3-slightly disagree 4-neutral 5- slightly agree 6-
agree and 7-strongly agree The demographic variables asked are gender race age education and monthly
income of the respondent
Data Screening
A rigorous data screening procedures were implemented on the raw SPSS data such as outliers detection
reliability normality test and validity tests The 245 dataset were coded and saved into SPSS version 16 and
analyzed using AMOS version 70 In this study a test for multivariate outliers is conducted using the
techniques described by Tabachnick and Fidell (2007) The Mahalanobis distance was calculated based on a
total of 31 observed items The criterion of plt0001 and critical value of χ 2 = 5970 is used The tests conductedidentified 8 cases with Mahalanobis values (D2) above 5970 The Mahalanobis analysis succeeded in
identifying the multivariate outliers which were deleted permanently leaving 237 datasets to be used for further
analysis
Hypotheses Results
The hypothesized model shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the data
to the re-specified model Finally a re-specified model was generated with pgt05 (Figure 5) Thus the re-
specified model indicates a better goodness of fit indices (See table 9) Further analysis of competing model ororiginal model (TAM) shows a goodness of fit structure with pgt05 The R2 of hypothesized model on adoption
shows a high value of 86 Hence it indicates that this model can be explained by variance of exogenous
variables (PEU PU and PC Intention) of 86 Similarly intention can only explain 751 variance in the
model while adoption explains 899 variance in the model Direct influences of the exogenous and
endogenous variables are shown in Table (10) Thus H1 H3 and H4 are asserted Only H2 is not significant
thus failed to be asserted
Several statistical validity tests and analysis were then conducted such as reliability test and composite
reliability tests validity tests using confirmatory factor analysis (CFA) for construct validity discriminant
validity for multi-collinearity treatment descriptive analysis correlation and structural equation modeling
analysis The step in SEM analysis were CFA analysis measurement exogenous (Figure 2) and endogenousanalysis (Figure 3) discriminant analysis composite reliability analysis and directindirect impact analysis
(mediating effect) and finally testing the goodness of fit for the hypothesized and generated model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1071
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
80
88
78
58
PU5
e05
76
58
PU4
e04
76
69
PU3
e03
83
52
PU2
e02
72
62
EOU6e12
7962
EOU5e11
78
59
EOU4e10
77
61
EOU3e0978
59
EOU2e0877
20
CRE6e18
44
24
CRE4e16
49
50
CRE3e1571
27
CRE2e1452
22
CRE1e13
46
Standardized estimatesChi-Square 90378
Df 75
Ratio 1205
P Value 109
GFI 949
RMSEA 029
Figure 2 Confirmatory Factor Analysis of Exogenous Measurements
Internet
Adoption
Internet
Intention
INT1 e2455
INT2 e2544
INT3 e2652
INT4 e27
46
INT5 e28
65
IA8
e36
70
IA7
e35
28
IA6
e34
53
IA5
e33
78
IA4
e32
83
IA3
e31
68
IA2
e30
67
IA1
e29
78
Standardized estimates
Chi-Square 80083
Df 64
Ratio 1251
P Value 085
GFI 952RMSEA 033
83
Figure 3 Confirmatory Factor Analysis of Endogenous Measurements
4 Results
Profile of the RespondentsThe profile of the companies involved in this study indicates that the SMEs utilize internet products
predominantly for financial services such as paying bills salaries and invoicing (35) making order
information (241) electronic email (236) marketing (236) submitting tenders to customers (236)
document transferring (19) purchasing raw materials (84) interaction with government (51) voice or
audio communication (51) and video conferencing (51) Most of the respondents are in the following
business sectors health or pharmaceutical (295) IT business services (295) and others (241) retail
government (156) public services (135) education (68) manufacturing (51) and insurance (51)
The SMEs in the respondent list mostly have number of employee in the category of less than 10 employees
(844) 11 to 50 (135) and more than 51 employee (17) Most of the SME Company is located in urbanarea (755) suburban (177) and rural area (68) There are slightly more female (608) than male
respondents (392) The kind of technology the SMEs used are communication systems (eg groupware e-
mail) (342) transactional systems for accounting finance marketing etc (245) desktop suites (eg Wordprocessing productivity)-(152) interorganisational information systems (EDI Electronic Business) (156)
decision support systems for accounting finance marketing etc (122) enterprise systems (ERP CRM)
(34) and other (84) The job positions of the respondents are owners (207) CEO (34) operation
manager (51) line manager (118) and staff (591) The respondentsrsquo ages are less than 25 year old
(477) 26 ndash 40 year old (439) and more than 41 year old (84) Their education background are high
school (38) diploma (308) bachelor degree (194) and master degree (118) Those respondents with
professional qualification in IT are 228 The total business capital of the SMEs are in the following
categories less than leRM5000 (278) RM5000ndashRM10000 (173) RM10000ndashRM20000 (118)
RM20000ndashRM50000 (122) and RM50000ndashRM100000 (308)
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1072
Table 3 Profiles of Respondents (N=237)
Demographics Frequency Valid Percent
Company utilize the Internet product for
1
Electronic mail2 Document transferring
3 Financial paying bills salaries invoicing etc
4 Marketing5 Submitting tenders to customers
6 Purchasing raw materials office supplies etc
7 Making order information available to customers8 Interaction with government
9 VoiceAudio communication (VOIP)
10 Video conferencing
5645
83
5616
20
5712
12
12
23619
350
23668
84
24151
51
51
Business sector1 Education
2 Manufacturing3 Retail Government
4 Public Services
5 BankingFinance
6 Insurance
7 Construction8 HealthPharmaceutical
9 Business ServicesIT business services
10 Other
16
1237
32
-
12
-25
70
57
68
51156
135
-
51
-105
295
241
Number of Employee 1 Less than 102 11 ndash 50
3 More than 51
20132
4
848135
17
Company location1 Urban
2 Sub Urban
3 Rural
179
42
16
755
177
68
Gender 1 Male
2 Female
93
144
392
608
Level of applications
1 Desktop suites (eg Word processing productivity)2 Communication systems (eg groupware e-mail)
3 Transactional systems for accounting finance marketing etc4 Decision support systems for accounting finance marketing etc
5 Enterprise systems (ERP CRM)
6 Interorganisational Information systems (EDI Electronic Business)7 Other
3681
5829
8
3720
152342
245122
34
15684
Job Position1 Owner
2 CEO
3 Operation Manager
4 Line Manager5 Staff
49
8
12
28140
207
34
51
118591
Age
1 Less than 25 year old2 26 ndash 40 year old
3 More than 41 year old
113104
20
477439
84 Education Background
1 High School
2 Diploma3 Bachelor Degree
4 Master Degree
5 Doctoral Degree
90
7346
28
-
380
308194
118
-
Professional qualification in IT1 No
2 Yes
183
54
772
228
The amounts of business capital
1 leRM5000
2 gtRM5000ndash10000
3 gtRM10000ndash20000
4 gtRM20000ndash50000
5 gtRM50000ndash100000
66
41
28
29
723
278
173
118
122
308
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 716
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1073
Descriptive Analysis of Variables
The research framework consists of three exogenous and two endogenous variables (Table 4) Each construct
shows Cronbach alpha readings of acceptable values of above 060 (Nunnally 1970) The composite reliabilityalso shows exceptional high values of above 080
Table 4 Descriptive Statistics of Variables
Variable NameNo of
Items
Mean
(Std Dev)
Cronbachrsquos
Alpha
Composite
Reliability
Endo 1
Endo 2
Exo 1Exo 2
Exo 3
Internet Intention
Internet Adoption
Perceived UsefulnessPerceived Ease of Use
Perceived Credibility
5
8
66
6
4063(0895)
3938(0901)
3888(0833)3804(0789)
3857(0861)
0661
0863
08960903
0692
0897
0972
09730976
0860
Total items 31
Convergent validity
From the confirmatory factor analysis result in Table 5 we observed that the factor loadings of all observedvariables or items are adequate ranging from 0392 to 0873 The factor loadings or regression estimates of
latent to observed variable should be above 050 (Hair et al 2006)This indicates that most of the constructs
conform to the convergent validity test The remaining numbers of items for each construct are as follows
Perceived Usefulness (4 items) Perceived ease of use (5 items) perceived credibility (5 items) internet
intention (5 items) and internet adoption (6 items)
Table 5 Final Confirmatory Factor Analysis Results of Construct Variables
Variable Code AttributesFactor
Loadings
Factor 1
Perceived
Usefulness
(4 items)
PU2
PU3PU4
PU5
Using internet would improve my job performance
Using internet would increase my productivityUsing internet would enhance my effectiveness on the job
Using internet would make it easier to do my job
0723
08730754
0756
Factor 2PerceivedEase of Use
(5 items)
EOU2EOU3
EOU4EOU5
EOU6
I would find it easy to use internet to obtain decision-making informationMy interaction with the internet was clear and understandable
I found the internet to be flexible to interact withIt would be easy for me to become skillful at using internet
I found the internet easy to use
07640787
07630788
0785
Factor 3
Perceived
Credibility(5 items)
CRE1
CRE2
CRE3
CRE4
CRE6
Internet has privacy
I feel confident in my activities with internet
When using internet I am sure that certain managerial and technical proceduresexist to secure all the data on this system
Internet has a good security system
When using internet I am sure of the consistency of information processing on this
system
0467
0511
0727
0525
0392
Factor 4
Internet
Intention
(5 items)
INT1
INT2
INT3
INT4
INT5
I think it would be very good to use the Internet for my company activities in
addition to traditional methods
In my opinion it would be very desirable to use the Internet for my companyactivities in addition to traditional methods
It would be much better for me to use the Internet for my company activities inaddition to traditional methodsUsing the Internet for my company activities is a good idea
Overall I like using the Internet for my company activities
0495
0425
0506
0422
0588
Factor 5Internet
Adoption
(6 items)
IA1IA2
IA3
IA4IA5
IA6
The internet now day is prominent strategyThe internet is safe
The internet saving cost and time
The internet applications supporting the company business processesHow much would you say your profitearn of your business through internet each
month
I have been using internet
07950650
0686
08240793
0495
TOTAL 25 Items
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 816
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1074
Discriminant Validity of Constructs
Table 6 shows the result of the calculated variance extracted (VE) to support discriminant validity of constructs
Average variance extracted (AVE) is the average VE values of two constructs (Table 7) According to Fornell
amp Larcker (1981) average variance extracted (AVE) should be more than the correlation squared of the two
constructs to support discriminant validity (compare table 6 and table 7) Each AVE value is found to be more
than correlation squared (see Table 8) thus discriminant validity is supported or multicollinearity is seemingly
absent In other words each construct could be considered distinct
Table 6 Variance Extracted of Variables
Observe
Variables
Std Regressions
WeightSMC error ε j Composite reliability Variance Extracted
PU2
PU3
PU4PU5
0723
0837
07540756
0523
0700
05690572
0086
0087
00890097
0973 0955
total 307 2364 0262
EOU2
EOU3EOU4
EOU5
EOU6
0764
07870763
0788
0785
0584
06190582
0621
0616
0070
00770078
0072
0078
0976 0961
total 3887 3022 0375
CRE1CRE2
CRE3
CRE4CRE6
04670511
0729
05250392
02180261
0532
02760153
02460214
0212
02600189
0860 0649
total 2624 144 1121
INT1
INT2
INT3INT4
INT5
0495
0425
05060422
0588
0245
0180
02560178
0346
0130
0157
01740166
0187
0897 0680
total 2436 1205 0684
IA1IA2
IA3
IA4IA5
IA6
07950650
0686
08240793
0495
06320423
0471
06790628
0245
00720082
0083
00730115
0087
0972 0949
total 4243 3078 0512
Table 7 Average Variance Extracted (AVE) Matrix of Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)
Perceived Easy of Use (2)
Perceived Credibility (3)
100
0974
0916
100
0918 100
Table 8 Correlation amp Correlation square Matrix among Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)Perceived Easy of Use (2)
Perceived Credibility (3)
1000799 (0638)
0765 (0585)
100
0868 (0753) 100
Correlation is significant at 001 level (2-tailed) values in brackets indicate correlation squared
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 916
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1075
Goodness of Fit Indices
Confirmatory factor analysis (CFA) was conducted on every construct and measurement models (see Table 9)
The data fit the construct measurement and structural models based on assessment criteria such as GFI CFI
TLI RMSEA (Bagozzi amp Yi 1988) All CFAs of constructs produced a relatively good fit as indicated by the
goodness of fit indices such as CMINdf ratio (lt2) p-value (gt005) Goodness of Fit Index (GFI) of gt95 and
root mean square error of approximation (RMSEA) of values less than 08 (lt08) Later four structural models
were tested for goodness of fit (hypothesized generated re-specified and competing models) Table 9 shows
that the goodness of fit of structural models (generated model re-specified and competing models) achieved
better goodness of fit compared to the hypothesized model Between the three models re-specified modelachieved the highest absolute fit because its p-value is the highest (p=0144)
Table 9 Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=237)
Finals
Models
Perceived
Usefulness
Ease of
UseCredibility
Internet
Intention
Internet
Adoption
Exogenous
Measurement
Endogenous
Measurement
Hypothesized
Model
Generated
Model
Re-Specified
ModelCompeting
Model
Items
remain
6 6 6 5 8 14 13 31 25 25 17
CMIN 11170 13745 11643 8769 30990 90378 80083 540394 299122 289512 141000
Df 9 9 9 5 20 75 64 427 268 265 115
CMIN
df
1241 1527 1294 1754 1550 1205 1251 1266 1116 1092 1226
p-value 0264 0132 0234 0119 0055 0109 0085 0000 0093 0144 0050
GFI 0985 0980 0989 0985 0968 0949 0952 0874 0910 0913 0937
CFI 0997 0994 0990 0972 0985 0989 0984 0967 0987 0990 0987
TLI 0995 0990 0983 0943 0979 0987 0980 0964 0986 0989 0984
RMSEA 0032 0047 0035 0057 0048 0029 0033 0034 0022 0020 0031
Structural Models Generated
The hypothesized model in Figure 4 shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the datato the generated model Subsequently a generated model (same paths as hypothesized model) was derived with
a goodness of fit been achieved (pgt05) Thus the generated model indicates a better goodness of fit indiceswhen some observed variables were deleted (Figure 5) Additionally a re-specified model has also been derived
whereby new paths have been suggested by modification indices and goodness of fit has also been achieved
(pgt05) (Figure 6) The hypotheses tested are based on the findings from the generated and re-specified model
Additionally analysis of competing model or original model (TAM) was also conducted to test the soundness
of the root model which shows a goodness of fit structure with pgt05 as well (Figure 7)
Figure 4 Hypothesized Model
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
86
Internet
Adoption
78
Internet
Intention
79
83
76
93
58
PU6
e06
76
60
PU5
e05
77
58
PU4
e04
76
68
PU3
e03
83
51
PU2
e02
72
60
PU1
e01
78
62
EOU6e12
7861
EOU5e11
78
61
EOU4e10
78
60
EOU3e0977
59
EOU2e0877
62
EOU1e07
79
13
CRE6e18
3654
CRE5e17
74
29
CRE4e16
54
59
CRE3e1577
24
CRE2e1449
21
CRE1e13
46
25
INT1 e2450
17
INT2 e254125
INT3 e2650
19
INT4 e27
43
34
INT5 e28
59
48
IA8
e36
69
09
IA7
e35
29
27
IA6
e34
52
62
IA5
e33
7968
IA4
e32
8248
IA3
e31
69
43
IA2
e30
66
62
IA1
e29
79
R01
R02
Standardized estimates
Chi-Square 540394
Df 427
Ratio 1266
P Value 000GFI 874
RMSEA 034
31
20
44
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1016
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 316
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1070
Samples and sampling
Owners of Small and medium sized entrepreneurs (SME) who operated their businesses in an eastern state of
Malaysia were the main respondents A total of 305 owners from various products were requested to complete a
questionnaire that contained measures of the constructs of concern The questionnaires were distributed to the
respondents by using simple random sampling method Out of the desired sample size of 305 245 were
returned This gives a response rate of 8032 As such the response rate for this study is adequate for SEM
analysis whereby after outliersrsquo deletion 237 questionnaires were subsequently used for analysis
Instrument
A total of 31 observed variables made up the measurement of exogenous independent varibles such as perceivedusefulness (6 items) perceived ease of use (6 items) perceived credibility (8 items) internet intention (5 items)
and internet adoption (8 items) adapted and modified from Wang et al (2003) The scaling used in this research
is the 7-point Likert scale of 1-strongly disagree 2-disagree 3-slightly disagree 4-neutral 5- slightly agree 6-
agree and 7-strongly agree The demographic variables asked are gender race age education and monthly
income of the respondent
Data Screening
A rigorous data screening procedures were implemented on the raw SPSS data such as outliers detection
reliability normality test and validity tests The 245 dataset were coded and saved into SPSS version 16 and
analyzed using AMOS version 70 In this study a test for multivariate outliers is conducted using the
techniques described by Tabachnick and Fidell (2007) The Mahalanobis distance was calculated based on a
total of 31 observed items The criterion of plt0001 and critical value of χ 2 = 5970 is used The tests conductedidentified 8 cases with Mahalanobis values (D2) above 5970 The Mahalanobis analysis succeeded in
identifying the multivariate outliers which were deleted permanently leaving 237 datasets to be used for further
analysis
Hypotheses Results
The hypothesized model shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the data
to the re-specified model Finally a re-specified model was generated with pgt05 (Figure 5) Thus the re-
specified model indicates a better goodness of fit indices (See table 9) Further analysis of competing model ororiginal model (TAM) shows a goodness of fit structure with pgt05 The R2 of hypothesized model on adoption
shows a high value of 86 Hence it indicates that this model can be explained by variance of exogenous
variables (PEU PU and PC Intention) of 86 Similarly intention can only explain 751 variance in the
model while adoption explains 899 variance in the model Direct influences of the exogenous and
endogenous variables are shown in Table (10) Thus H1 H3 and H4 are asserted Only H2 is not significant
thus failed to be asserted
Several statistical validity tests and analysis were then conducted such as reliability test and composite
reliability tests validity tests using confirmatory factor analysis (CFA) for construct validity discriminant
validity for multi-collinearity treatment descriptive analysis correlation and structural equation modeling
analysis The step in SEM analysis were CFA analysis measurement exogenous (Figure 2) and endogenousanalysis (Figure 3) discriminant analysis composite reliability analysis and directindirect impact analysis
(mediating effect) and finally testing the goodness of fit for the hypothesized and generated model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1071
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
80
88
78
58
PU5
e05
76
58
PU4
e04
76
69
PU3
e03
83
52
PU2
e02
72
62
EOU6e12
7962
EOU5e11
78
59
EOU4e10
77
61
EOU3e0978
59
EOU2e0877
20
CRE6e18
44
24
CRE4e16
49
50
CRE3e1571
27
CRE2e1452
22
CRE1e13
46
Standardized estimatesChi-Square 90378
Df 75
Ratio 1205
P Value 109
GFI 949
RMSEA 029
Figure 2 Confirmatory Factor Analysis of Exogenous Measurements
Internet
Adoption
Internet
Intention
INT1 e2455
INT2 e2544
INT3 e2652
INT4 e27
46
INT5 e28
65
IA8
e36
70
IA7
e35
28
IA6
e34
53
IA5
e33
78
IA4
e32
83
IA3
e31
68
IA2
e30
67
IA1
e29
78
Standardized estimates
Chi-Square 80083
Df 64
Ratio 1251
P Value 085
GFI 952RMSEA 033
83
Figure 3 Confirmatory Factor Analysis of Endogenous Measurements
4 Results
Profile of the RespondentsThe profile of the companies involved in this study indicates that the SMEs utilize internet products
predominantly for financial services such as paying bills salaries and invoicing (35) making order
information (241) electronic email (236) marketing (236) submitting tenders to customers (236)
document transferring (19) purchasing raw materials (84) interaction with government (51) voice or
audio communication (51) and video conferencing (51) Most of the respondents are in the following
business sectors health or pharmaceutical (295) IT business services (295) and others (241) retail
government (156) public services (135) education (68) manufacturing (51) and insurance (51)
The SMEs in the respondent list mostly have number of employee in the category of less than 10 employees
(844) 11 to 50 (135) and more than 51 employee (17) Most of the SME Company is located in urbanarea (755) suburban (177) and rural area (68) There are slightly more female (608) than male
respondents (392) The kind of technology the SMEs used are communication systems (eg groupware e-
mail) (342) transactional systems for accounting finance marketing etc (245) desktop suites (eg Wordprocessing productivity)-(152) interorganisational information systems (EDI Electronic Business) (156)
decision support systems for accounting finance marketing etc (122) enterprise systems (ERP CRM)
(34) and other (84) The job positions of the respondents are owners (207) CEO (34) operation
manager (51) line manager (118) and staff (591) The respondentsrsquo ages are less than 25 year old
(477) 26 ndash 40 year old (439) and more than 41 year old (84) Their education background are high
school (38) diploma (308) bachelor degree (194) and master degree (118) Those respondents with
professional qualification in IT are 228 The total business capital of the SMEs are in the following
categories less than leRM5000 (278) RM5000ndashRM10000 (173) RM10000ndashRM20000 (118)
RM20000ndashRM50000 (122) and RM50000ndashRM100000 (308)
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1072
Table 3 Profiles of Respondents (N=237)
Demographics Frequency Valid Percent
Company utilize the Internet product for
1
Electronic mail2 Document transferring
3 Financial paying bills salaries invoicing etc
4 Marketing5 Submitting tenders to customers
6 Purchasing raw materials office supplies etc
7 Making order information available to customers8 Interaction with government
9 VoiceAudio communication (VOIP)
10 Video conferencing
5645
83
5616
20
5712
12
12
23619
350
23668
84
24151
51
51
Business sector1 Education
2 Manufacturing3 Retail Government
4 Public Services
5 BankingFinance
6 Insurance
7 Construction8 HealthPharmaceutical
9 Business ServicesIT business services
10 Other
16
1237
32
-
12
-25
70
57
68
51156
135
-
51
-105
295
241
Number of Employee 1 Less than 102 11 ndash 50
3 More than 51
20132
4
848135
17
Company location1 Urban
2 Sub Urban
3 Rural
179
42
16
755
177
68
Gender 1 Male
2 Female
93
144
392
608
Level of applications
1 Desktop suites (eg Word processing productivity)2 Communication systems (eg groupware e-mail)
3 Transactional systems for accounting finance marketing etc4 Decision support systems for accounting finance marketing etc
5 Enterprise systems (ERP CRM)
6 Interorganisational Information systems (EDI Electronic Business)7 Other
3681
5829
8
3720
152342
245122
34
15684
Job Position1 Owner
2 CEO
3 Operation Manager
4 Line Manager5 Staff
49
8
12
28140
207
34
51
118591
Age
1 Less than 25 year old2 26 ndash 40 year old
3 More than 41 year old
113104
20
477439
84 Education Background
1 High School
2 Diploma3 Bachelor Degree
4 Master Degree
5 Doctoral Degree
90
7346
28
-
380
308194
118
-
Professional qualification in IT1 No
2 Yes
183
54
772
228
The amounts of business capital
1 leRM5000
2 gtRM5000ndash10000
3 gtRM10000ndash20000
4 gtRM20000ndash50000
5 gtRM50000ndash100000
66
41
28
29
723
278
173
118
122
308
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 716
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1073
Descriptive Analysis of Variables
The research framework consists of three exogenous and two endogenous variables (Table 4) Each construct
shows Cronbach alpha readings of acceptable values of above 060 (Nunnally 1970) The composite reliabilityalso shows exceptional high values of above 080
Table 4 Descriptive Statistics of Variables
Variable NameNo of
Items
Mean
(Std Dev)
Cronbachrsquos
Alpha
Composite
Reliability
Endo 1
Endo 2
Exo 1Exo 2
Exo 3
Internet Intention
Internet Adoption
Perceived UsefulnessPerceived Ease of Use
Perceived Credibility
5
8
66
6
4063(0895)
3938(0901)
3888(0833)3804(0789)
3857(0861)
0661
0863
08960903
0692
0897
0972
09730976
0860
Total items 31
Convergent validity
From the confirmatory factor analysis result in Table 5 we observed that the factor loadings of all observedvariables or items are adequate ranging from 0392 to 0873 The factor loadings or regression estimates of
latent to observed variable should be above 050 (Hair et al 2006)This indicates that most of the constructs
conform to the convergent validity test The remaining numbers of items for each construct are as follows
Perceived Usefulness (4 items) Perceived ease of use (5 items) perceived credibility (5 items) internet
intention (5 items) and internet adoption (6 items)
Table 5 Final Confirmatory Factor Analysis Results of Construct Variables
Variable Code AttributesFactor
Loadings
Factor 1
Perceived
Usefulness
(4 items)
PU2
PU3PU4
PU5
Using internet would improve my job performance
Using internet would increase my productivityUsing internet would enhance my effectiveness on the job
Using internet would make it easier to do my job
0723
08730754
0756
Factor 2PerceivedEase of Use
(5 items)
EOU2EOU3
EOU4EOU5
EOU6
I would find it easy to use internet to obtain decision-making informationMy interaction with the internet was clear and understandable
I found the internet to be flexible to interact withIt would be easy for me to become skillful at using internet
I found the internet easy to use
07640787
07630788
0785
Factor 3
Perceived
Credibility(5 items)
CRE1
CRE2
CRE3
CRE4
CRE6
Internet has privacy
I feel confident in my activities with internet
When using internet I am sure that certain managerial and technical proceduresexist to secure all the data on this system
Internet has a good security system
When using internet I am sure of the consistency of information processing on this
system
0467
0511
0727
0525
0392
Factor 4
Internet
Intention
(5 items)
INT1
INT2
INT3
INT4
INT5
I think it would be very good to use the Internet for my company activities in
addition to traditional methods
In my opinion it would be very desirable to use the Internet for my companyactivities in addition to traditional methods
It would be much better for me to use the Internet for my company activities inaddition to traditional methodsUsing the Internet for my company activities is a good idea
Overall I like using the Internet for my company activities
0495
0425
0506
0422
0588
Factor 5Internet
Adoption
(6 items)
IA1IA2
IA3
IA4IA5
IA6
The internet now day is prominent strategyThe internet is safe
The internet saving cost and time
The internet applications supporting the company business processesHow much would you say your profitearn of your business through internet each
month
I have been using internet
07950650
0686
08240793
0495
TOTAL 25 Items
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 816
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1074
Discriminant Validity of Constructs
Table 6 shows the result of the calculated variance extracted (VE) to support discriminant validity of constructs
Average variance extracted (AVE) is the average VE values of two constructs (Table 7) According to Fornell
amp Larcker (1981) average variance extracted (AVE) should be more than the correlation squared of the two
constructs to support discriminant validity (compare table 6 and table 7) Each AVE value is found to be more
than correlation squared (see Table 8) thus discriminant validity is supported or multicollinearity is seemingly
absent In other words each construct could be considered distinct
Table 6 Variance Extracted of Variables
Observe
Variables
Std Regressions
WeightSMC error ε j Composite reliability Variance Extracted
PU2
PU3
PU4PU5
0723
0837
07540756
0523
0700
05690572
0086
0087
00890097
0973 0955
total 307 2364 0262
EOU2
EOU3EOU4
EOU5
EOU6
0764
07870763
0788
0785
0584
06190582
0621
0616
0070
00770078
0072
0078
0976 0961
total 3887 3022 0375
CRE1CRE2
CRE3
CRE4CRE6
04670511
0729
05250392
02180261
0532
02760153
02460214
0212
02600189
0860 0649
total 2624 144 1121
INT1
INT2
INT3INT4
INT5
0495
0425
05060422
0588
0245
0180
02560178
0346
0130
0157
01740166
0187
0897 0680
total 2436 1205 0684
IA1IA2
IA3
IA4IA5
IA6
07950650
0686
08240793
0495
06320423
0471
06790628
0245
00720082
0083
00730115
0087
0972 0949
total 4243 3078 0512
Table 7 Average Variance Extracted (AVE) Matrix of Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)
Perceived Easy of Use (2)
Perceived Credibility (3)
100
0974
0916
100
0918 100
Table 8 Correlation amp Correlation square Matrix among Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)Perceived Easy of Use (2)
Perceived Credibility (3)
1000799 (0638)
0765 (0585)
100
0868 (0753) 100
Correlation is significant at 001 level (2-tailed) values in brackets indicate correlation squared
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 916
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1075
Goodness of Fit Indices
Confirmatory factor analysis (CFA) was conducted on every construct and measurement models (see Table 9)
The data fit the construct measurement and structural models based on assessment criteria such as GFI CFI
TLI RMSEA (Bagozzi amp Yi 1988) All CFAs of constructs produced a relatively good fit as indicated by the
goodness of fit indices such as CMINdf ratio (lt2) p-value (gt005) Goodness of Fit Index (GFI) of gt95 and
root mean square error of approximation (RMSEA) of values less than 08 (lt08) Later four structural models
were tested for goodness of fit (hypothesized generated re-specified and competing models) Table 9 shows
that the goodness of fit of structural models (generated model re-specified and competing models) achieved
better goodness of fit compared to the hypothesized model Between the three models re-specified modelachieved the highest absolute fit because its p-value is the highest (p=0144)
Table 9 Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=237)
Finals
Models
Perceived
Usefulness
Ease of
UseCredibility
Internet
Intention
Internet
Adoption
Exogenous
Measurement
Endogenous
Measurement
Hypothesized
Model
Generated
Model
Re-Specified
ModelCompeting
Model
Items
remain
6 6 6 5 8 14 13 31 25 25 17
CMIN 11170 13745 11643 8769 30990 90378 80083 540394 299122 289512 141000
Df 9 9 9 5 20 75 64 427 268 265 115
CMIN
df
1241 1527 1294 1754 1550 1205 1251 1266 1116 1092 1226
p-value 0264 0132 0234 0119 0055 0109 0085 0000 0093 0144 0050
GFI 0985 0980 0989 0985 0968 0949 0952 0874 0910 0913 0937
CFI 0997 0994 0990 0972 0985 0989 0984 0967 0987 0990 0987
TLI 0995 0990 0983 0943 0979 0987 0980 0964 0986 0989 0984
RMSEA 0032 0047 0035 0057 0048 0029 0033 0034 0022 0020 0031
Structural Models Generated
The hypothesized model in Figure 4 shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the datato the generated model Subsequently a generated model (same paths as hypothesized model) was derived with
a goodness of fit been achieved (pgt05) Thus the generated model indicates a better goodness of fit indiceswhen some observed variables were deleted (Figure 5) Additionally a re-specified model has also been derived
whereby new paths have been suggested by modification indices and goodness of fit has also been achieved
(pgt05) (Figure 6) The hypotheses tested are based on the findings from the generated and re-specified model
Additionally analysis of competing model or original model (TAM) was also conducted to test the soundness
of the root model which shows a goodness of fit structure with pgt05 as well (Figure 7)
Figure 4 Hypothesized Model
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
86
Internet
Adoption
78
Internet
Intention
79
83
76
93
58
PU6
e06
76
60
PU5
e05
77
58
PU4
e04
76
68
PU3
e03
83
51
PU2
e02
72
60
PU1
e01
78
62
EOU6e12
7861
EOU5e11
78
61
EOU4e10
78
60
EOU3e0977
59
EOU2e0877
62
EOU1e07
79
13
CRE6e18
3654
CRE5e17
74
29
CRE4e16
54
59
CRE3e1577
24
CRE2e1449
21
CRE1e13
46
25
INT1 e2450
17
INT2 e254125
INT3 e2650
19
INT4 e27
43
34
INT5 e28
59
48
IA8
e36
69
09
IA7
e35
29
27
IA6
e34
52
62
IA5
e33
7968
IA4
e32
8248
IA3
e31
69
43
IA2
e30
66
62
IA1
e29
79
R01
R02
Standardized estimates
Chi-Square 540394
Df 427
Ratio 1266
P Value 000GFI 874
RMSEA 034
31
20
44
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1016
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1070
Samples and sampling
Owners of Small and medium sized entrepreneurs (SME) who operated their businesses in an eastern state of
Malaysia were the main respondents A total of 305 owners from various products were requested to complete a
questionnaire that contained measures of the constructs of concern The questionnaires were distributed to the
respondents by using simple random sampling method Out of the desired sample size of 305 245 were
returned This gives a response rate of 8032 As such the response rate for this study is adequate for SEM
analysis whereby after outliersrsquo deletion 237 questionnaires were subsequently used for analysis
Instrument
A total of 31 observed variables made up the measurement of exogenous independent varibles such as perceivedusefulness (6 items) perceived ease of use (6 items) perceived credibility (8 items) internet intention (5 items)
and internet adoption (8 items) adapted and modified from Wang et al (2003) The scaling used in this research
is the 7-point Likert scale of 1-strongly disagree 2-disagree 3-slightly disagree 4-neutral 5- slightly agree 6-
agree and 7-strongly agree The demographic variables asked are gender race age education and monthly
income of the respondent
Data Screening
A rigorous data screening procedures were implemented on the raw SPSS data such as outliers detection
reliability normality test and validity tests The 245 dataset were coded and saved into SPSS version 16 and
analyzed using AMOS version 70 In this study a test for multivariate outliers is conducted using the
techniques described by Tabachnick and Fidell (2007) The Mahalanobis distance was calculated based on a
total of 31 observed items The criterion of plt0001 and critical value of χ 2 = 5970 is used The tests conductedidentified 8 cases with Mahalanobis values (D2) above 5970 The Mahalanobis analysis succeeded in
identifying the multivariate outliers which were deleted permanently leaving 237 datasets to be used for further
analysis
Hypotheses Results
The hypothesized model shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the data
to the re-specified model Finally a re-specified model was generated with pgt05 (Figure 5) Thus the re-
specified model indicates a better goodness of fit indices (See table 9) Further analysis of competing model ororiginal model (TAM) shows a goodness of fit structure with pgt05 The R2 of hypothesized model on adoption
shows a high value of 86 Hence it indicates that this model can be explained by variance of exogenous
variables (PEU PU and PC Intention) of 86 Similarly intention can only explain 751 variance in the
model while adoption explains 899 variance in the model Direct influences of the exogenous and
endogenous variables are shown in Table (10) Thus H1 H3 and H4 are asserted Only H2 is not significant
thus failed to be asserted
Several statistical validity tests and analysis were then conducted such as reliability test and composite
reliability tests validity tests using confirmatory factor analysis (CFA) for construct validity discriminant
validity for multi-collinearity treatment descriptive analysis correlation and structural equation modeling
analysis The step in SEM analysis were CFA analysis measurement exogenous (Figure 2) and endogenousanalysis (Figure 3) discriminant analysis composite reliability analysis and directindirect impact analysis
(mediating effect) and finally testing the goodness of fit for the hypothesized and generated model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1071
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
80
88
78
58
PU5
e05
76
58
PU4
e04
76
69
PU3
e03
83
52
PU2
e02
72
62
EOU6e12
7962
EOU5e11
78
59
EOU4e10
77
61
EOU3e0978
59
EOU2e0877
20
CRE6e18
44
24
CRE4e16
49
50
CRE3e1571
27
CRE2e1452
22
CRE1e13
46
Standardized estimatesChi-Square 90378
Df 75
Ratio 1205
P Value 109
GFI 949
RMSEA 029
Figure 2 Confirmatory Factor Analysis of Exogenous Measurements
Internet
Adoption
Internet
Intention
INT1 e2455
INT2 e2544
INT3 e2652
INT4 e27
46
INT5 e28
65
IA8
e36
70
IA7
e35
28
IA6
e34
53
IA5
e33
78
IA4
e32
83
IA3
e31
68
IA2
e30
67
IA1
e29
78
Standardized estimates
Chi-Square 80083
Df 64
Ratio 1251
P Value 085
GFI 952RMSEA 033
83
Figure 3 Confirmatory Factor Analysis of Endogenous Measurements
4 Results
Profile of the RespondentsThe profile of the companies involved in this study indicates that the SMEs utilize internet products
predominantly for financial services such as paying bills salaries and invoicing (35) making order
information (241) electronic email (236) marketing (236) submitting tenders to customers (236)
document transferring (19) purchasing raw materials (84) interaction with government (51) voice or
audio communication (51) and video conferencing (51) Most of the respondents are in the following
business sectors health or pharmaceutical (295) IT business services (295) and others (241) retail
government (156) public services (135) education (68) manufacturing (51) and insurance (51)
The SMEs in the respondent list mostly have number of employee in the category of less than 10 employees
(844) 11 to 50 (135) and more than 51 employee (17) Most of the SME Company is located in urbanarea (755) suburban (177) and rural area (68) There are slightly more female (608) than male
respondents (392) The kind of technology the SMEs used are communication systems (eg groupware e-
mail) (342) transactional systems for accounting finance marketing etc (245) desktop suites (eg Wordprocessing productivity)-(152) interorganisational information systems (EDI Electronic Business) (156)
decision support systems for accounting finance marketing etc (122) enterprise systems (ERP CRM)
(34) and other (84) The job positions of the respondents are owners (207) CEO (34) operation
manager (51) line manager (118) and staff (591) The respondentsrsquo ages are less than 25 year old
(477) 26 ndash 40 year old (439) and more than 41 year old (84) Their education background are high
school (38) diploma (308) bachelor degree (194) and master degree (118) Those respondents with
professional qualification in IT are 228 The total business capital of the SMEs are in the following
categories less than leRM5000 (278) RM5000ndashRM10000 (173) RM10000ndashRM20000 (118)
RM20000ndashRM50000 (122) and RM50000ndashRM100000 (308)
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1072
Table 3 Profiles of Respondents (N=237)
Demographics Frequency Valid Percent
Company utilize the Internet product for
1
Electronic mail2 Document transferring
3 Financial paying bills salaries invoicing etc
4 Marketing5 Submitting tenders to customers
6 Purchasing raw materials office supplies etc
7 Making order information available to customers8 Interaction with government
9 VoiceAudio communication (VOIP)
10 Video conferencing
5645
83
5616
20
5712
12
12
23619
350
23668
84
24151
51
51
Business sector1 Education
2 Manufacturing3 Retail Government
4 Public Services
5 BankingFinance
6 Insurance
7 Construction8 HealthPharmaceutical
9 Business ServicesIT business services
10 Other
16
1237
32
-
12
-25
70
57
68
51156
135
-
51
-105
295
241
Number of Employee 1 Less than 102 11 ndash 50
3 More than 51
20132
4
848135
17
Company location1 Urban
2 Sub Urban
3 Rural
179
42
16
755
177
68
Gender 1 Male
2 Female
93
144
392
608
Level of applications
1 Desktop suites (eg Word processing productivity)2 Communication systems (eg groupware e-mail)
3 Transactional systems for accounting finance marketing etc4 Decision support systems for accounting finance marketing etc
5 Enterprise systems (ERP CRM)
6 Interorganisational Information systems (EDI Electronic Business)7 Other
3681
5829
8
3720
152342
245122
34
15684
Job Position1 Owner
2 CEO
3 Operation Manager
4 Line Manager5 Staff
49
8
12
28140
207
34
51
118591
Age
1 Less than 25 year old2 26 ndash 40 year old
3 More than 41 year old
113104
20
477439
84 Education Background
1 High School
2 Diploma3 Bachelor Degree
4 Master Degree
5 Doctoral Degree
90
7346
28
-
380
308194
118
-
Professional qualification in IT1 No
2 Yes
183
54
772
228
The amounts of business capital
1 leRM5000
2 gtRM5000ndash10000
3 gtRM10000ndash20000
4 gtRM20000ndash50000
5 gtRM50000ndash100000
66
41
28
29
723
278
173
118
122
308
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 716
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1073
Descriptive Analysis of Variables
The research framework consists of three exogenous and two endogenous variables (Table 4) Each construct
shows Cronbach alpha readings of acceptable values of above 060 (Nunnally 1970) The composite reliabilityalso shows exceptional high values of above 080
Table 4 Descriptive Statistics of Variables
Variable NameNo of
Items
Mean
(Std Dev)
Cronbachrsquos
Alpha
Composite
Reliability
Endo 1
Endo 2
Exo 1Exo 2
Exo 3
Internet Intention
Internet Adoption
Perceived UsefulnessPerceived Ease of Use
Perceived Credibility
5
8
66
6
4063(0895)
3938(0901)
3888(0833)3804(0789)
3857(0861)
0661
0863
08960903
0692
0897
0972
09730976
0860
Total items 31
Convergent validity
From the confirmatory factor analysis result in Table 5 we observed that the factor loadings of all observedvariables or items are adequate ranging from 0392 to 0873 The factor loadings or regression estimates of
latent to observed variable should be above 050 (Hair et al 2006)This indicates that most of the constructs
conform to the convergent validity test The remaining numbers of items for each construct are as follows
Perceived Usefulness (4 items) Perceived ease of use (5 items) perceived credibility (5 items) internet
intention (5 items) and internet adoption (6 items)
Table 5 Final Confirmatory Factor Analysis Results of Construct Variables
Variable Code AttributesFactor
Loadings
Factor 1
Perceived
Usefulness
(4 items)
PU2
PU3PU4
PU5
Using internet would improve my job performance
Using internet would increase my productivityUsing internet would enhance my effectiveness on the job
Using internet would make it easier to do my job
0723
08730754
0756
Factor 2PerceivedEase of Use
(5 items)
EOU2EOU3
EOU4EOU5
EOU6
I would find it easy to use internet to obtain decision-making informationMy interaction with the internet was clear and understandable
I found the internet to be flexible to interact withIt would be easy for me to become skillful at using internet
I found the internet easy to use
07640787
07630788
0785
Factor 3
Perceived
Credibility(5 items)
CRE1
CRE2
CRE3
CRE4
CRE6
Internet has privacy
I feel confident in my activities with internet
When using internet I am sure that certain managerial and technical proceduresexist to secure all the data on this system
Internet has a good security system
When using internet I am sure of the consistency of information processing on this
system
0467
0511
0727
0525
0392
Factor 4
Internet
Intention
(5 items)
INT1
INT2
INT3
INT4
INT5
I think it would be very good to use the Internet for my company activities in
addition to traditional methods
In my opinion it would be very desirable to use the Internet for my companyactivities in addition to traditional methods
It would be much better for me to use the Internet for my company activities inaddition to traditional methodsUsing the Internet for my company activities is a good idea
Overall I like using the Internet for my company activities
0495
0425
0506
0422
0588
Factor 5Internet
Adoption
(6 items)
IA1IA2
IA3
IA4IA5
IA6
The internet now day is prominent strategyThe internet is safe
The internet saving cost and time
The internet applications supporting the company business processesHow much would you say your profitearn of your business through internet each
month
I have been using internet
07950650
0686
08240793
0495
TOTAL 25 Items
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 816
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1074
Discriminant Validity of Constructs
Table 6 shows the result of the calculated variance extracted (VE) to support discriminant validity of constructs
Average variance extracted (AVE) is the average VE values of two constructs (Table 7) According to Fornell
amp Larcker (1981) average variance extracted (AVE) should be more than the correlation squared of the two
constructs to support discriminant validity (compare table 6 and table 7) Each AVE value is found to be more
than correlation squared (see Table 8) thus discriminant validity is supported or multicollinearity is seemingly
absent In other words each construct could be considered distinct
Table 6 Variance Extracted of Variables
Observe
Variables
Std Regressions
WeightSMC error ε j Composite reliability Variance Extracted
PU2
PU3
PU4PU5
0723
0837
07540756
0523
0700
05690572
0086
0087
00890097
0973 0955
total 307 2364 0262
EOU2
EOU3EOU4
EOU5
EOU6
0764
07870763
0788
0785
0584
06190582
0621
0616
0070
00770078
0072
0078
0976 0961
total 3887 3022 0375
CRE1CRE2
CRE3
CRE4CRE6
04670511
0729
05250392
02180261
0532
02760153
02460214
0212
02600189
0860 0649
total 2624 144 1121
INT1
INT2
INT3INT4
INT5
0495
0425
05060422
0588
0245
0180
02560178
0346
0130
0157
01740166
0187
0897 0680
total 2436 1205 0684
IA1IA2
IA3
IA4IA5
IA6
07950650
0686
08240793
0495
06320423
0471
06790628
0245
00720082
0083
00730115
0087
0972 0949
total 4243 3078 0512
Table 7 Average Variance Extracted (AVE) Matrix of Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)
Perceived Easy of Use (2)
Perceived Credibility (3)
100
0974
0916
100
0918 100
Table 8 Correlation amp Correlation square Matrix among Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)Perceived Easy of Use (2)
Perceived Credibility (3)
1000799 (0638)
0765 (0585)
100
0868 (0753) 100
Correlation is significant at 001 level (2-tailed) values in brackets indicate correlation squared
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 916
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1075
Goodness of Fit Indices
Confirmatory factor analysis (CFA) was conducted on every construct and measurement models (see Table 9)
The data fit the construct measurement and structural models based on assessment criteria such as GFI CFI
TLI RMSEA (Bagozzi amp Yi 1988) All CFAs of constructs produced a relatively good fit as indicated by the
goodness of fit indices such as CMINdf ratio (lt2) p-value (gt005) Goodness of Fit Index (GFI) of gt95 and
root mean square error of approximation (RMSEA) of values less than 08 (lt08) Later four structural models
were tested for goodness of fit (hypothesized generated re-specified and competing models) Table 9 shows
that the goodness of fit of structural models (generated model re-specified and competing models) achieved
better goodness of fit compared to the hypothesized model Between the three models re-specified modelachieved the highest absolute fit because its p-value is the highest (p=0144)
Table 9 Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=237)
Finals
Models
Perceived
Usefulness
Ease of
UseCredibility
Internet
Intention
Internet
Adoption
Exogenous
Measurement
Endogenous
Measurement
Hypothesized
Model
Generated
Model
Re-Specified
ModelCompeting
Model
Items
remain
6 6 6 5 8 14 13 31 25 25 17
CMIN 11170 13745 11643 8769 30990 90378 80083 540394 299122 289512 141000
Df 9 9 9 5 20 75 64 427 268 265 115
CMIN
df
1241 1527 1294 1754 1550 1205 1251 1266 1116 1092 1226
p-value 0264 0132 0234 0119 0055 0109 0085 0000 0093 0144 0050
GFI 0985 0980 0989 0985 0968 0949 0952 0874 0910 0913 0937
CFI 0997 0994 0990 0972 0985 0989 0984 0967 0987 0990 0987
TLI 0995 0990 0983 0943 0979 0987 0980 0964 0986 0989 0984
RMSEA 0032 0047 0035 0057 0048 0029 0033 0034 0022 0020 0031
Structural Models Generated
The hypothesized model in Figure 4 shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the datato the generated model Subsequently a generated model (same paths as hypothesized model) was derived with
a goodness of fit been achieved (pgt05) Thus the generated model indicates a better goodness of fit indiceswhen some observed variables were deleted (Figure 5) Additionally a re-specified model has also been derived
whereby new paths have been suggested by modification indices and goodness of fit has also been achieved
(pgt05) (Figure 6) The hypotheses tested are based on the findings from the generated and re-specified model
Additionally analysis of competing model or original model (TAM) was also conducted to test the soundness
of the root model which shows a goodness of fit structure with pgt05 as well (Figure 7)
Figure 4 Hypothesized Model
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
86
Internet
Adoption
78
Internet
Intention
79
83
76
93
58
PU6
e06
76
60
PU5
e05
77
58
PU4
e04
76
68
PU3
e03
83
51
PU2
e02
72
60
PU1
e01
78
62
EOU6e12
7861
EOU5e11
78
61
EOU4e10
78
60
EOU3e0977
59
EOU2e0877
62
EOU1e07
79
13
CRE6e18
3654
CRE5e17
74
29
CRE4e16
54
59
CRE3e1577
24
CRE2e1449
21
CRE1e13
46
25
INT1 e2450
17
INT2 e254125
INT3 e2650
19
INT4 e27
43
34
INT5 e28
59
48
IA8
e36
69
09
IA7
e35
29
27
IA6
e34
52
62
IA5
e33
7968
IA4
e32
8248
IA3
e31
69
43
IA2
e30
66
62
IA1
e29
79
R01
R02
Standardized estimates
Chi-Square 540394
Df 427
Ratio 1266
P Value 000GFI 874
RMSEA 034
31
20
44
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1016
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1071
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
80
88
78
58
PU5
e05
76
58
PU4
e04
76
69
PU3
e03
83
52
PU2
e02
72
62
EOU6e12
7962
EOU5e11
78
59
EOU4e10
77
61
EOU3e0978
59
EOU2e0877
20
CRE6e18
44
24
CRE4e16
49
50
CRE3e1571
27
CRE2e1452
22
CRE1e13
46
Standardized estimatesChi-Square 90378
Df 75
Ratio 1205
P Value 109
GFI 949
RMSEA 029
Figure 2 Confirmatory Factor Analysis of Exogenous Measurements
Internet
Adoption
Internet
Intention
INT1 e2455
INT2 e2544
INT3 e2652
INT4 e27
46
INT5 e28
65
IA8
e36
70
IA7
e35
28
IA6
e34
53
IA5
e33
78
IA4
e32
83
IA3
e31
68
IA2
e30
67
IA1
e29
78
Standardized estimates
Chi-Square 80083
Df 64
Ratio 1251
P Value 085
GFI 952RMSEA 033
83
Figure 3 Confirmatory Factor Analysis of Endogenous Measurements
4 Results
Profile of the RespondentsThe profile of the companies involved in this study indicates that the SMEs utilize internet products
predominantly for financial services such as paying bills salaries and invoicing (35) making order
information (241) electronic email (236) marketing (236) submitting tenders to customers (236)
document transferring (19) purchasing raw materials (84) interaction with government (51) voice or
audio communication (51) and video conferencing (51) Most of the respondents are in the following
business sectors health or pharmaceutical (295) IT business services (295) and others (241) retail
government (156) public services (135) education (68) manufacturing (51) and insurance (51)
The SMEs in the respondent list mostly have number of employee in the category of less than 10 employees
(844) 11 to 50 (135) and more than 51 employee (17) Most of the SME Company is located in urbanarea (755) suburban (177) and rural area (68) There are slightly more female (608) than male
respondents (392) The kind of technology the SMEs used are communication systems (eg groupware e-
mail) (342) transactional systems for accounting finance marketing etc (245) desktop suites (eg Wordprocessing productivity)-(152) interorganisational information systems (EDI Electronic Business) (156)
decision support systems for accounting finance marketing etc (122) enterprise systems (ERP CRM)
(34) and other (84) The job positions of the respondents are owners (207) CEO (34) operation
manager (51) line manager (118) and staff (591) The respondentsrsquo ages are less than 25 year old
(477) 26 ndash 40 year old (439) and more than 41 year old (84) Their education background are high
school (38) diploma (308) bachelor degree (194) and master degree (118) Those respondents with
professional qualification in IT are 228 The total business capital of the SMEs are in the following
categories less than leRM5000 (278) RM5000ndashRM10000 (173) RM10000ndashRM20000 (118)
RM20000ndashRM50000 (122) and RM50000ndashRM100000 (308)
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1072
Table 3 Profiles of Respondents (N=237)
Demographics Frequency Valid Percent
Company utilize the Internet product for
1
Electronic mail2 Document transferring
3 Financial paying bills salaries invoicing etc
4 Marketing5 Submitting tenders to customers
6 Purchasing raw materials office supplies etc
7 Making order information available to customers8 Interaction with government
9 VoiceAudio communication (VOIP)
10 Video conferencing
5645
83
5616
20
5712
12
12
23619
350
23668
84
24151
51
51
Business sector1 Education
2 Manufacturing3 Retail Government
4 Public Services
5 BankingFinance
6 Insurance
7 Construction8 HealthPharmaceutical
9 Business ServicesIT business services
10 Other
16
1237
32
-
12
-25
70
57
68
51156
135
-
51
-105
295
241
Number of Employee 1 Less than 102 11 ndash 50
3 More than 51
20132
4
848135
17
Company location1 Urban
2 Sub Urban
3 Rural
179
42
16
755
177
68
Gender 1 Male
2 Female
93
144
392
608
Level of applications
1 Desktop suites (eg Word processing productivity)2 Communication systems (eg groupware e-mail)
3 Transactional systems for accounting finance marketing etc4 Decision support systems for accounting finance marketing etc
5 Enterprise systems (ERP CRM)
6 Interorganisational Information systems (EDI Electronic Business)7 Other
3681
5829
8
3720
152342
245122
34
15684
Job Position1 Owner
2 CEO
3 Operation Manager
4 Line Manager5 Staff
49
8
12
28140
207
34
51
118591
Age
1 Less than 25 year old2 26 ndash 40 year old
3 More than 41 year old
113104
20
477439
84 Education Background
1 High School
2 Diploma3 Bachelor Degree
4 Master Degree
5 Doctoral Degree
90
7346
28
-
380
308194
118
-
Professional qualification in IT1 No
2 Yes
183
54
772
228
The amounts of business capital
1 leRM5000
2 gtRM5000ndash10000
3 gtRM10000ndash20000
4 gtRM20000ndash50000
5 gtRM50000ndash100000
66
41
28
29
723
278
173
118
122
308
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 716
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1073
Descriptive Analysis of Variables
The research framework consists of three exogenous and two endogenous variables (Table 4) Each construct
shows Cronbach alpha readings of acceptable values of above 060 (Nunnally 1970) The composite reliabilityalso shows exceptional high values of above 080
Table 4 Descriptive Statistics of Variables
Variable NameNo of
Items
Mean
(Std Dev)
Cronbachrsquos
Alpha
Composite
Reliability
Endo 1
Endo 2
Exo 1Exo 2
Exo 3
Internet Intention
Internet Adoption
Perceived UsefulnessPerceived Ease of Use
Perceived Credibility
5
8
66
6
4063(0895)
3938(0901)
3888(0833)3804(0789)
3857(0861)
0661
0863
08960903
0692
0897
0972
09730976
0860
Total items 31
Convergent validity
From the confirmatory factor analysis result in Table 5 we observed that the factor loadings of all observedvariables or items are adequate ranging from 0392 to 0873 The factor loadings or regression estimates of
latent to observed variable should be above 050 (Hair et al 2006)This indicates that most of the constructs
conform to the convergent validity test The remaining numbers of items for each construct are as follows
Perceived Usefulness (4 items) Perceived ease of use (5 items) perceived credibility (5 items) internet
intention (5 items) and internet adoption (6 items)
Table 5 Final Confirmatory Factor Analysis Results of Construct Variables
Variable Code AttributesFactor
Loadings
Factor 1
Perceived
Usefulness
(4 items)
PU2
PU3PU4
PU5
Using internet would improve my job performance
Using internet would increase my productivityUsing internet would enhance my effectiveness on the job
Using internet would make it easier to do my job
0723
08730754
0756
Factor 2PerceivedEase of Use
(5 items)
EOU2EOU3
EOU4EOU5
EOU6
I would find it easy to use internet to obtain decision-making informationMy interaction with the internet was clear and understandable
I found the internet to be flexible to interact withIt would be easy for me to become skillful at using internet
I found the internet easy to use
07640787
07630788
0785
Factor 3
Perceived
Credibility(5 items)
CRE1
CRE2
CRE3
CRE4
CRE6
Internet has privacy
I feel confident in my activities with internet
When using internet I am sure that certain managerial and technical proceduresexist to secure all the data on this system
Internet has a good security system
When using internet I am sure of the consistency of information processing on this
system
0467
0511
0727
0525
0392
Factor 4
Internet
Intention
(5 items)
INT1
INT2
INT3
INT4
INT5
I think it would be very good to use the Internet for my company activities in
addition to traditional methods
In my opinion it would be very desirable to use the Internet for my companyactivities in addition to traditional methods
It would be much better for me to use the Internet for my company activities inaddition to traditional methodsUsing the Internet for my company activities is a good idea
Overall I like using the Internet for my company activities
0495
0425
0506
0422
0588
Factor 5Internet
Adoption
(6 items)
IA1IA2
IA3
IA4IA5
IA6
The internet now day is prominent strategyThe internet is safe
The internet saving cost and time
The internet applications supporting the company business processesHow much would you say your profitearn of your business through internet each
month
I have been using internet
07950650
0686
08240793
0495
TOTAL 25 Items
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 816
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1074
Discriminant Validity of Constructs
Table 6 shows the result of the calculated variance extracted (VE) to support discriminant validity of constructs
Average variance extracted (AVE) is the average VE values of two constructs (Table 7) According to Fornell
amp Larcker (1981) average variance extracted (AVE) should be more than the correlation squared of the two
constructs to support discriminant validity (compare table 6 and table 7) Each AVE value is found to be more
than correlation squared (see Table 8) thus discriminant validity is supported or multicollinearity is seemingly
absent In other words each construct could be considered distinct
Table 6 Variance Extracted of Variables
Observe
Variables
Std Regressions
WeightSMC error ε j Composite reliability Variance Extracted
PU2
PU3
PU4PU5
0723
0837
07540756
0523
0700
05690572
0086
0087
00890097
0973 0955
total 307 2364 0262
EOU2
EOU3EOU4
EOU5
EOU6
0764
07870763
0788
0785
0584
06190582
0621
0616
0070
00770078
0072
0078
0976 0961
total 3887 3022 0375
CRE1CRE2
CRE3
CRE4CRE6
04670511
0729
05250392
02180261
0532
02760153
02460214
0212
02600189
0860 0649
total 2624 144 1121
INT1
INT2
INT3INT4
INT5
0495
0425
05060422
0588
0245
0180
02560178
0346
0130
0157
01740166
0187
0897 0680
total 2436 1205 0684
IA1IA2
IA3
IA4IA5
IA6
07950650
0686
08240793
0495
06320423
0471
06790628
0245
00720082
0083
00730115
0087
0972 0949
total 4243 3078 0512
Table 7 Average Variance Extracted (AVE) Matrix of Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)
Perceived Easy of Use (2)
Perceived Credibility (3)
100
0974
0916
100
0918 100
Table 8 Correlation amp Correlation square Matrix among Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)Perceived Easy of Use (2)
Perceived Credibility (3)
1000799 (0638)
0765 (0585)
100
0868 (0753) 100
Correlation is significant at 001 level (2-tailed) values in brackets indicate correlation squared
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 916
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1075
Goodness of Fit Indices
Confirmatory factor analysis (CFA) was conducted on every construct and measurement models (see Table 9)
The data fit the construct measurement and structural models based on assessment criteria such as GFI CFI
TLI RMSEA (Bagozzi amp Yi 1988) All CFAs of constructs produced a relatively good fit as indicated by the
goodness of fit indices such as CMINdf ratio (lt2) p-value (gt005) Goodness of Fit Index (GFI) of gt95 and
root mean square error of approximation (RMSEA) of values less than 08 (lt08) Later four structural models
were tested for goodness of fit (hypothesized generated re-specified and competing models) Table 9 shows
that the goodness of fit of structural models (generated model re-specified and competing models) achieved
better goodness of fit compared to the hypothesized model Between the three models re-specified modelachieved the highest absolute fit because its p-value is the highest (p=0144)
Table 9 Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=237)
Finals
Models
Perceived
Usefulness
Ease of
UseCredibility
Internet
Intention
Internet
Adoption
Exogenous
Measurement
Endogenous
Measurement
Hypothesized
Model
Generated
Model
Re-Specified
ModelCompeting
Model
Items
remain
6 6 6 5 8 14 13 31 25 25 17
CMIN 11170 13745 11643 8769 30990 90378 80083 540394 299122 289512 141000
Df 9 9 9 5 20 75 64 427 268 265 115
CMIN
df
1241 1527 1294 1754 1550 1205 1251 1266 1116 1092 1226
p-value 0264 0132 0234 0119 0055 0109 0085 0000 0093 0144 0050
GFI 0985 0980 0989 0985 0968 0949 0952 0874 0910 0913 0937
CFI 0997 0994 0990 0972 0985 0989 0984 0967 0987 0990 0987
TLI 0995 0990 0983 0943 0979 0987 0980 0964 0986 0989 0984
RMSEA 0032 0047 0035 0057 0048 0029 0033 0034 0022 0020 0031
Structural Models Generated
The hypothesized model in Figure 4 shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the datato the generated model Subsequently a generated model (same paths as hypothesized model) was derived with
a goodness of fit been achieved (pgt05) Thus the generated model indicates a better goodness of fit indiceswhen some observed variables were deleted (Figure 5) Additionally a re-specified model has also been derived
whereby new paths have been suggested by modification indices and goodness of fit has also been achieved
(pgt05) (Figure 6) The hypotheses tested are based on the findings from the generated and re-specified model
Additionally analysis of competing model or original model (TAM) was also conducted to test the soundness
of the root model which shows a goodness of fit structure with pgt05 as well (Figure 7)
Figure 4 Hypothesized Model
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
86
Internet
Adoption
78
Internet
Intention
79
83
76
93
58
PU6
e06
76
60
PU5
e05
77
58
PU4
e04
76
68
PU3
e03
83
51
PU2
e02
72
60
PU1
e01
78
62
EOU6e12
7861
EOU5e11
78
61
EOU4e10
78
60
EOU3e0977
59
EOU2e0877
62
EOU1e07
79
13
CRE6e18
3654
CRE5e17
74
29
CRE4e16
54
59
CRE3e1577
24
CRE2e1449
21
CRE1e13
46
25
INT1 e2450
17
INT2 e254125
INT3 e2650
19
INT4 e27
43
34
INT5 e28
59
48
IA8
e36
69
09
IA7
e35
29
27
IA6
e34
52
62
IA5
e33
7968
IA4
e32
8248
IA3
e31
69
43
IA2
e30
66
62
IA1
e29
79
R01
R02
Standardized estimates
Chi-Square 540394
Df 427
Ratio 1266
P Value 000GFI 874
RMSEA 034
31
20
44
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1016
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1072
Table 3 Profiles of Respondents (N=237)
Demographics Frequency Valid Percent
Company utilize the Internet product for
1
Electronic mail2 Document transferring
3 Financial paying bills salaries invoicing etc
4 Marketing5 Submitting tenders to customers
6 Purchasing raw materials office supplies etc
7 Making order information available to customers8 Interaction with government
9 VoiceAudio communication (VOIP)
10 Video conferencing
5645
83
5616
20
5712
12
12
23619
350
23668
84
24151
51
51
Business sector1 Education
2 Manufacturing3 Retail Government
4 Public Services
5 BankingFinance
6 Insurance
7 Construction8 HealthPharmaceutical
9 Business ServicesIT business services
10 Other
16
1237
32
-
12
-25
70
57
68
51156
135
-
51
-105
295
241
Number of Employee 1 Less than 102 11 ndash 50
3 More than 51
20132
4
848135
17
Company location1 Urban
2 Sub Urban
3 Rural
179
42
16
755
177
68
Gender 1 Male
2 Female
93
144
392
608
Level of applications
1 Desktop suites (eg Word processing productivity)2 Communication systems (eg groupware e-mail)
3 Transactional systems for accounting finance marketing etc4 Decision support systems for accounting finance marketing etc
5 Enterprise systems (ERP CRM)
6 Interorganisational Information systems (EDI Electronic Business)7 Other
3681
5829
8
3720
152342
245122
34
15684
Job Position1 Owner
2 CEO
3 Operation Manager
4 Line Manager5 Staff
49
8
12
28140
207
34
51
118591
Age
1 Less than 25 year old2 26 ndash 40 year old
3 More than 41 year old
113104
20
477439
84 Education Background
1 High School
2 Diploma3 Bachelor Degree
4 Master Degree
5 Doctoral Degree
90
7346
28
-
380
308194
118
-
Professional qualification in IT1 No
2 Yes
183
54
772
228
The amounts of business capital
1 leRM5000
2 gtRM5000ndash10000
3 gtRM10000ndash20000
4 gtRM20000ndash50000
5 gtRM50000ndash100000
66
41
28
29
723
278
173
118
122
308
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 716
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1073
Descriptive Analysis of Variables
The research framework consists of three exogenous and two endogenous variables (Table 4) Each construct
shows Cronbach alpha readings of acceptable values of above 060 (Nunnally 1970) The composite reliabilityalso shows exceptional high values of above 080
Table 4 Descriptive Statistics of Variables
Variable NameNo of
Items
Mean
(Std Dev)
Cronbachrsquos
Alpha
Composite
Reliability
Endo 1
Endo 2
Exo 1Exo 2
Exo 3
Internet Intention
Internet Adoption
Perceived UsefulnessPerceived Ease of Use
Perceived Credibility
5
8
66
6
4063(0895)
3938(0901)
3888(0833)3804(0789)
3857(0861)
0661
0863
08960903
0692
0897
0972
09730976
0860
Total items 31
Convergent validity
From the confirmatory factor analysis result in Table 5 we observed that the factor loadings of all observedvariables or items are adequate ranging from 0392 to 0873 The factor loadings or regression estimates of
latent to observed variable should be above 050 (Hair et al 2006)This indicates that most of the constructs
conform to the convergent validity test The remaining numbers of items for each construct are as follows
Perceived Usefulness (4 items) Perceived ease of use (5 items) perceived credibility (5 items) internet
intention (5 items) and internet adoption (6 items)
Table 5 Final Confirmatory Factor Analysis Results of Construct Variables
Variable Code AttributesFactor
Loadings
Factor 1
Perceived
Usefulness
(4 items)
PU2
PU3PU4
PU5
Using internet would improve my job performance
Using internet would increase my productivityUsing internet would enhance my effectiveness on the job
Using internet would make it easier to do my job
0723
08730754
0756
Factor 2PerceivedEase of Use
(5 items)
EOU2EOU3
EOU4EOU5
EOU6
I would find it easy to use internet to obtain decision-making informationMy interaction with the internet was clear and understandable
I found the internet to be flexible to interact withIt would be easy for me to become skillful at using internet
I found the internet easy to use
07640787
07630788
0785
Factor 3
Perceived
Credibility(5 items)
CRE1
CRE2
CRE3
CRE4
CRE6
Internet has privacy
I feel confident in my activities with internet
When using internet I am sure that certain managerial and technical proceduresexist to secure all the data on this system
Internet has a good security system
When using internet I am sure of the consistency of information processing on this
system
0467
0511
0727
0525
0392
Factor 4
Internet
Intention
(5 items)
INT1
INT2
INT3
INT4
INT5
I think it would be very good to use the Internet for my company activities in
addition to traditional methods
In my opinion it would be very desirable to use the Internet for my companyactivities in addition to traditional methods
It would be much better for me to use the Internet for my company activities inaddition to traditional methodsUsing the Internet for my company activities is a good idea
Overall I like using the Internet for my company activities
0495
0425
0506
0422
0588
Factor 5Internet
Adoption
(6 items)
IA1IA2
IA3
IA4IA5
IA6
The internet now day is prominent strategyThe internet is safe
The internet saving cost and time
The internet applications supporting the company business processesHow much would you say your profitearn of your business through internet each
month
I have been using internet
07950650
0686
08240793
0495
TOTAL 25 Items
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 816
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1074
Discriminant Validity of Constructs
Table 6 shows the result of the calculated variance extracted (VE) to support discriminant validity of constructs
Average variance extracted (AVE) is the average VE values of two constructs (Table 7) According to Fornell
amp Larcker (1981) average variance extracted (AVE) should be more than the correlation squared of the two
constructs to support discriminant validity (compare table 6 and table 7) Each AVE value is found to be more
than correlation squared (see Table 8) thus discriminant validity is supported or multicollinearity is seemingly
absent In other words each construct could be considered distinct
Table 6 Variance Extracted of Variables
Observe
Variables
Std Regressions
WeightSMC error ε j Composite reliability Variance Extracted
PU2
PU3
PU4PU5
0723
0837
07540756
0523
0700
05690572
0086
0087
00890097
0973 0955
total 307 2364 0262
EOU2
EOU3EOU4
EOU5
EOU6
0764
07870763
0788
0785
0584
06190582
0621
0616
0070
00770078
0072
0078
0976 0961
total 3887 3022 0375
CRE1CRE2
CRE3
CRE4CRE6
04670511
0729
05250392
02180261
0532
02760153
02460214
0212
02600189
0860 0649
total 2624 144 1121
INT1
INT2
INT3INT4
INT5
0495
0425
05060422
0588
0245
0180
02560178
0346
0130
0157
01740166
0187
0897 0680
total 2436 1205 0684
IA1IA2
IA3
IA4IA5
IA6
07950650
0686
08240793
0495
06320423
0471
06790628
0245
00720082
0083
00730115
0087
0972 0949
total 4243 3078 0512
Table 7 Average Variance Extracted (AVE) Matrix of Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)
Perceived Easy of Use (2)
Perceived Credibility (3)
100
0974
0916
100
0918 100
Table 8 Correlation amp Correlation square Matrix among Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)Perceived Easy of Use (2)
Perceived Credibility (3)
1000799 (0638)
0765 (0585)
100
0868 (0753) 100
Correlation is significant at 001 level (2-tailed) values in brackets indicate correlation squared
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 916
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1075
Goodness of Fit Indices
Confirmatory factor analysis (CFA) was conducted on every construct and measurement models (see Table 9)
The data fit the construct measurement and structural models based on assessment criteria such as GFI CFI
TLI RMSEA (Bagozzi amp Yi 1988) All CFAs of constructs produced a relatively good fit as indicated by the
goodness of fit indices such as CMINdf ratio (lt2) p-value (gt005) Goodness of Fit Index (GFI) of gt95 and
root mean square error of approximation (RMSEA) of values less than 08 (lt08) Later four structural models
were tested for goodness of fit (hypothesized generated re-specified and competing models) Table 9 shows
that the goodness of fit of structural models (generated model re-specified and competing models) achieved
better goodness of fit compared to the hypothesized model Between the three models re-specified modelachieved the highest absolute fit because its p-value is the highest (p=0144)
Table 9 Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=237)
Finals
Models
Perceived
Usefulness
Ease of
UseCredibility
Internet
Intention
Internet
Adoption
Exogenous
Measurement
Endogenous
Measurement
Hypothesized
Model
Generated
Model
Re-Specified
ModelCompeting
Model
Items
remain
6 6 6 5 8 14 13 31 25 25 17
CMIN 11170 13745 11643 8769 30990 90378 80083 540394 299122 289512 141000
Df 9 9 9 5 20 75 64 427 268 265 115
CMIN
df
1241 1527 1294 1754 1550 1205 1251 1266 1116 1092 1226
p-value 0264 0132 0234 0119 0055 0109 0085 0000 0093 0144 0050
GFI 0985 0980 0989 0985 0968 0949 0952 0874 0910 0913 0937
CFI 0997 0994 0990 0972 0985 0989 0984 0967 0987 0990 0987
TLI 0995 0990 0983 0943 0979 0987 0980 0964 0986 0989 0984
RMSEA 0032 0047 0035 0057 0048 0029 0033 0034 0022 0020 0031
Structural Models Generated
The hypothesized model in Figure 4 shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the datato the generated model Subsequently a generated model (same paths as hypothesized model) was derived with
a goodness of fit been achieved (pgt05) Thus the generated model indicates a better goodness of fit indiceswhen some observed variables were deleted (Figure 5) Additionally a re-specified model has also been derived
whereby new paths have been suggested by modification indices and goodness of fit has also been achieved
(pgt05) (Figure 6) The hypotheses tested are based on the findings from the generated and re-specified model
Additionally analysis of competing model or original model (TAM) was also conducted to test the soundness
of the root model which shows a goodness of fit structure with pgt05 as well (Figure 7)
Figure 4 Hypothesized Model
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
86
Internet
Adoption
78
Internet
Intention
79
83
76
93
58
PU6
e06
76
60
PU5
e05
77
58
PU4
e04
76
68
PU3
e03
83
51
PU2
e02
72
60
PU1
e01
78
62
EOU6e12
7861
EOU5e11
78
61
EOU4e10
78
60
EOU3e0977
59
EOU2e0877
62
EOU1e07
79
13
CRE6e18
3654
CRE5e17
74
29
CRE4e16
54
59
CRE3e1577
24
CRE2e1449
21
CRE1e13
46
25
INT1 e2450
17
INT2 e254125
INT3 e2650
19
INT4 e27
43
34
INT5 e28
59
48
IA8
e36
69
09
IA7
e35
29
27
IA6
e34
52
62
IA5
e33
7968
IA4
e32
8248
IA3
e31
69
43
IA2
e30
66
62
IA1
e29
79
R01
R02
Standardized estimates
Chi-Square 540394
Df 427
Ratio 1266
P Value 000GFI 874
RMSEA 034
31
20
44
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1016
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 716
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1073
Descriptive Analysis of Variables
The research framework consists of three exogenous and two endogenous variables (Table 4) Each construct
shows Cronbach alpha readings of acceptable values of above 060 (Nunnally 1970) The composite reliabilityalso shows exceptional high values of above 080
Table 4 Descriptive Statistics of Variables
Variable NameNo of
Items
Mean
(Std Dev)
Cronbachrsquos
Alpha
Composite
Reliability
Endo 1
Endo 2
Exo 1Exo 2
Exo 3
Internet Intention
Internet Adoption
Perceived UsefulnessPerceived Ease of Use
Perceived Credibility
5
8
66
6
4063(0895)
3938(0901)
3888(0833)3804(0789)
3857(0861)
0661
0863
08960903
0692
0897
0972
09730976
0860
Total items 31
Convergent validity
From the confirmatory factor analysis result in Table 5 we observed that the factor loadings of all observedvariables or items are adequate ranging from 0392 to 0873 The factor loadings or regression estimates of
latent to observed variable should be above 050 (Hair et al 2006)This indicates that most of the constructs
conform to the convergent validity test The remaining numbers of items for each construct are as follows
Perceived Usefulness (4 items) Perceived ease of use (5 items) perceived credibility (5 items) internet
intention (5 items) and internet adoption (6 items)
Table 5 Final Confirmatory Factor Analysis Results of Construct Variables
Variable Code AttributesFactor
Loadings
Factor 1
Perceived
Usefulness
(4 items)
PU2
PU3PU4
PU5
Using internet would improve my job performance
Using internet would increase my productivityUsing internet would enhance my effectiveness on the job
Using internet would make it easier to do my job
0723
08730754
0756
Factor 2PerceivedEase of Use
(5 items)
EOU2EOU3
EOU4EOU5
EOU6
I would find it easy to use internet to obtain decision-making informationMy interaction with the internet was clear and understandable
I found the internet to be flexible to interact withIt would be easy for me to become skillful at using internet
I found the internet easy to use
07640787
07630788
0785
Factor 3
Perceived
Credibility(5 items)
CRE1
CRE2
CRE3
CRE4
CRE6
Internet has privacy
I feel confident in my activities with internet
When using internet I am sure that certain managerial and technical proceduresexist to secure all the data on this system
Internet has a good security system
When using internet I am sure of the consistency of information processing on this
system
0467
0511
0727
0525
0392
Factor 4
Internet
Intention
(5 items)
INT1
INT2
INT3
INT4
INT5
I think it would be very good to use the Internet for my company activities in
addition to traditional methods
In my opinion it would be very desirable to use the Internet for my companyactivities in addition to traditional methods
It would be much better for me to use the Internet for my company activities inaddition to traditional methodsUsing the Internet for my company activities is a good idea
Overall I like using the Internet for my company activities
0495
0425
0506
0422
0588
Factor 5Internet
Adoption
(6 items)
IA1IA2
IA3
IA4IA5
IA6
The internet now day is prominent strategyThe internet is safe
The internet saving cost and time
The internet applications supporting the company business processesHow much would you say your profitearn of your business through internet each
month
I have been using internet
07950650
0686
08240793
0495
TOTAL 25 Items
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 816
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1074
Discriminant Validity of Constructs
Table 6 shows the result of the calculated variance extracted (VE) to support discriminant validity of constructs
Average variance extracted (AVE) is the average VE values of two constructs (Table 7) According to Fornell
amp Larcker (1981) average variance extracted (AVE) should be more than the correlation squared of the two
constructs to support discriminant validity (compare table 6 and table 7) Each AVE value is found to be more
than correlation squared (see Table 8) thus discriminant validity is supported or multicollinearity is seemingly
absent In other words each construct could be considered distinct
Table 6 Variance Extracted of Variables
Observe
Variables
Std Regressions
WeightSMC error ε j Composite reliability Variance Extracted
PU2
PU3
PU4PU5
0723
0837
07540756
0523
0700
05690572
0086
0087
00890097
0973 0955
total 307 2364 0262
EOU2
EOU3EOU4
EOU5
EOU6
0764
07870763
0788
0785
0584
06190582
0621
0616
0070
00770078
0072
0078
0976 0961
total 3887 3022 0375
CRE1CRE2
CRE3
CRE4CRE6
04670511
0729
05250392
02180261
0532
02760153
02460214
0212
02600189
0860 0649
total 2624 144 1121
INT1
INT2
INT3INT4
INT5
0495
0425
05060422
0588
0245
0180
02560178
0346
0130
0157
01740166
0187
0897 0680
total 2436 1205 0684
IA1IA2
IA3
IA4IA5
IA6
07950650
0686
08240793
0495
06320423
0471
06790628
0245
00720082
0083
00730115
0087
0972 0949
total 4243 3078 0512
Table 7 Average Variance Extracted (AVE) Matrix of Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)
Perceived Easy of Use (2)
Perceived Credibility (3)
100
0974
0916
100
0918 100
Table 8 Correlation amp Correlation square Matrix among Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)Perceived Easy of Use (2)
Perceived Credibility (3)
1000799 (0638)
0765 (0585)
100
0868 (0753) 100
Correlation is significant at 001 level (2-tailed) values in brackets indicate correlation squared
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 916
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1075
Goodness of Fit Indices
Confirmatory factor analysis (CFA) was conducted on every construct and measurement models (see Table 9)
The data fit the construct measurement and structural models based on assessment criteria such as GFI CFI
TLI RMSEA (Bagozzi amp Yi 1988) All CFAs of constructs produced a relatively good fit as indicated by the
goodness of fit indices such as CMINdf ratio (lt2) p-value (gt005) Goodness of Fit Index (GFI) of gt95 and
root mean square error of approximation (RMSEA) of values less than 08 (lt08) Later four structural models
were tested for goodness of fit (hypothesized generated re-specified and competing models) Table 9 shows
that the goodness of fit of structural models (generated model re-specified and competing models) achieved
better goodness of fit compared to the hypothesized model Between the three models re-specified modelachieved the highest absolute fit because its p-value is the highest (p=0144)
Table 9 Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=237)
Finals
Models
Perceived
Usefulness
Ease of
UseCredibility
Internet
Intention
Internet
Adoption
Exogenous
Measurement
Endogenous
Measurement
Hypothesized
Model
Generated
Model
Re-Specified
ModelCompeting
Model
Items
remain
6 6 6 5 8 14 13 31 25 25 17
CMIN 11170 13745 11643 8769 30990 90378 80083 540394 299122 289512 141000
Df 9 9 9 5 20 75 64 427 268 265 115
CMIN
df
1241 1527 1294 1754 1550 1205 1251 1266 1116 1092 1226
p-value 0264 0132 0234 0119 0055 0109 0085 0000 0093 0144 0050
GFI 0985 0980 0989 0985 0968 0949 0952 0874 0910 0913 0937
CFI 0997 0994 0990 0972 0985 0989 0984 0967 0987 0990 0987
TLI 0995 0990 0983 0943 0979 0987 0980 0964 0986 0989 0984
RMSEA 0032 0047 0035 0057 0048 0029 0033 0034 0022 0020 0031
Structural Models Generated
The hypothesized model in Figure 4 shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the datato the generated model Subsequently a generated model (same paths as hypothesized model) was derived with
a goodness of fit been achieved (pgt05) Thus the generated model indicates a better goodness of fit indiceswhen some observed variables were deleted (Figure 5) Additionally a re-specified model has also been derived
whereby new paths have been suggested by modification indices and goodness of fit has also been achieved
(pgt05) (Figure 6) The hypotheses tested are based on the findings from the generated and re-specified model
Additionally analysis of competing model or original model (TAM) was also conducted to test the soundness
of the root model which shows a goodness of fit structure with pgt05 as well (Figure 7)
Figure 4 Hypothesized Model
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
86
Internet
Adoption
78
Internet
Intention
79
83
76
93
58
PU6
e06
76
60
PU5
e05
77
58
PU4
e04
76
68
PU3
e03
83
51
PU2
e02
72
60
PU1
e01
78
62
EOU6e12
7861
EOU5e11
78
61
EOU4e10
78
60
EOU3e0977
59
EOU2e0877
62
EOU1e07
79
13
CRE6e18
3654
CRE5e17
74
29
CRE4e16
54
59
CRE3e1577
24
CRE2e1449
21
CRE1e13
46
25
INT1 e2450
17
INT2 e254125
INT3 e2650
19
INT4 e27
43
34
INT5 e28
59
48
IA8
e36
69
09
IA7
e35
29
27
IA6
e34
52
62
IA5
e33
7968
IA4
e32
8248
IA3
e31
69
43
IA2
e30
66
62
IA1
e29
79
R01
R02
Standardized estimates
Chi-Square 540394
Df 427
Ratio 1266
P Value 000GFI 874
RMSEA 034
31
20
44
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1016
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 816
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1074
Discriminant Validity of Constructs
Table 6 shows the result of the calculated variance extracted (VE) to support discriminant validity of constructs
Average variance extracted (AVE) is the average VE values of two constructs (Table 7) According to Fornell
amp Larcker (1981) average variance extracted (AVE) should be more than the correlation squared of the two
constructs to support discriminant validity (compare table 6 and table 7) Each AVE value is found to be more
than correlation squared (see Table 8) thus discriminant validity is supported or multicollinearity is seemingly
absent In other words each construct could be considered distinct
Table 6 Variance Extracted of Variables
Observe
Variables
Std Regressions
WeightSMC error ε j Composite reliability Variance Extracted
PU2
PU3
PU4PU5
0723
0837
07540756
0523
0700
05690572
0086
0087
00890097
0973 0955
total 307 2364 0262
EOU2
EOU3EOU4
EOU5
EOU6
0764
07870763
0788
0785
0584
06190582
0621
0616
0070
00770078
0072
0078
0976 0961
total 3887 3022 0375
CRE1CRE2
CRE3
CRE4CRE6
04670511
0729
05250392
02180261
0532
02760153
02460214
0212
02600189
0860 0649
total 2624 144 1121
INT1
INT2
INT3INT4
INT5
0495
0425
05060422
0588
0245
0180
02560178
0346
0130
0157
01740166
0187
0897 0680
total 2436 1205 0684
IA1IA2
IA3
IA4IA5
IA6
07950650
0686
08240793
0495
06320423
0471
06790628
0245
00720082
0083
00730115
0087
0972 0949
total 4243 3078 0512
Table 7 Average Variance Extracted (AVE) Matrix of Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)
Perceived Easy of Use (2)
Perceived Credibility (3)
100
0974
0916
100
0918 100
Table 8 Correlation amp Correlation square Matrix among Exogenous Variables
Variable Name 1 2 3
Perceived Usefulness (1)Perceived Easy of Use (2)
Perceived Credibility (3)
1000799 (0638)
0765 (0585)
100
0868 (0753) 100
Correlation is significant at 001 level (2-tailed) values in brackets indicate correlation squared
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 916
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1075
Goodness of Fit Indices
Confirmatory factor analysis (CFA) was conducted on every construct and measurement models (see Table 9)
The data fit the construct measurement and structural models based on assessment criteria such as GFI CFI
TLI RMSEA (Bagozzi amp Yi 1988) All CFAs of constructs produced a relatively good fit as indicated by the
goodness of fit indices such as CMINdf ratio (lt2) p-value (gt005) Goodness of Fit Index (GFI) of gt95 and
root mean square error of approximation (RMSEA) of values less than 08 (lt08) Later four structural models
were tested for goodness of fit (hypothesized generated re-specified and competing models) Table 9 shows
that the goodness of fit of structural models (generated model re-specified and competing models) achieved
better goodness of fit compared to the hypothesized model Between the three models re-specified modelachieved the highest absolute fit because its p-value is the highest (p=0144)
Table 9 Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=237)
Finals
Models
Perceived
Usefulness
Ease of
UseCredibility
Internet
Intention
Internet
Adoption
Exogenous
Measurement
Endogenous
Measurement
Hypothesized
Model
Generated
Model
Re-Specified
ModelCompeting
Model
Items
remain
6 6 6 5 8 14 13 31 25 25 17
CMIN 11170 13745 11643 8769 30990 90378 80083 540394 299122 289512 141000
Df 9 9 9 5 20 75 64 427 268 265 115
CMIN
df
1241 1527 1294 1754 1550 1205 1251 1266 1116 1092 1226
p-value 0264 0132 0234 0119 0055 0109 0085 0000 0093 0144 0050
GFI 0985 0980 0989 0985 0968 0949 0952 0874 0910 0913 0937
CFI 0997 0994 0990 0972 0985 0989 0984 0967 0987 0990 0987
TLI 0995 0990 0983 0943 0979 0987 0980 0964 0986 0989 0984
RMSEA 0032 0047 0035 0057 0048 0029 0033 0034 0022 0020 0031
Structural Models Generated
The hypothesized model in Figure 4 shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the datato the generated model Subsequently a generated model (same paths as hypothesized model) was derived with
a goodness of fit been achieved (pgt05) Thus the generated model indicates a better goodness of fit indiceswhen some observed variables were deleted (Figure 5) Additionally a re-specified model has also been derived
whereby new paths have been suggested by modification indices and goodness of fit has also been achieved
(pgt05) (Figure 6) The hypotheses tested are based on the findings from the generated and re-specified model
Additionally analysis of competing model or original model (TAM) was also conducted to test the soundness
of the root model which shows a goodness of fit structure with pgt05 as well (Figure 7)
Figure 4 Hypothesized Model
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
86
Internet
Adoption
78
Internet
Intention
79
83
76
93
58
PU6
e06
76
60
PU5
e05
77
58
PU4
e04
76
68
PU3
e03
83
51
PU2
e02
72
60
PU1
e01
78
62
EOU6e12
7861
EOU5e11
78
61
EOU4e10
78
60
EOU3e0977
59
EOU2e0877
62
EOU1e07
79
13
CRE6e18
3654
CRE5e17
74
29
CRE4e16
54
59
CRE3e1577
24
CRE2e1449
21
CRE1e13
46
25
INT1 e2450
17
INT2 e254125
INT3 e2650
19
INT4 e27
43
34
INT5 e28
59
48
IA8
e36
69
09
IA7
e35
29
27
IA6
e34
52
62
IA5
e33
7968
IA4
e32
8248
IA3
e31
69
43
IA2
e30
66
62
IA1
e29
79
R01
R02
Standardized estimates
Chi-Square 540394
Df 427
Ratio 1266
P Value 000GFI 874
RMSEA 034
31
20
44
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1016
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 916
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1075
Goodness of Fit Indices
Confirmatory factor analysis (CFA) was conducted on every construct and measurement models (see Table 9)
The data fit the construct measurement and structural models based on assessment criteria such as GFI CFI
TLI RMSEA (Bagozzi amp Yi 1988) All CFAs of constructs produced a relatively good fit as indicated by the
goodness of fit indices such as CMINdf ratio (lt2) p-value (gt005) Goodness of Fit Index (GFI) of gt95 and
root mean square error of approximation (RMSEA) of values less than 08 (lt08) Later four structural models
were tested for goodness of fit (hypothesized generated re-specified and competing models) Table 9 shows
that the goodness of fit of structural models (generated model re-specified and competing models) achieved
better goodness of fit compared to the hypothesized model Between the three models re-specified modelachieved the highest absolute fit because its p-value is the highest (p=0144)
Table 9 Goodness of Fit Analysis-Confirmatory Factor Analysis (CFA) of Models (N=237)
Finals
Models
Perceived
Usefulness
Ease of
UseCredibility
Internet
Intention
Internet
Adoption
Exogenous
Measurement
Endogenous
Measurement
Hypothesized
Model
Generated
Model
Re-Specified
ModelCompeting
Model
Items
remain
6 6 6 5 8 14 13 31 25 25 17
CMIN 11170 13745 11643 8769 30990 90378 80083 540394 299122 289512 141000
Df 9 9 9 5 20 75 64 427 268 265 115
CMIN
df
1241 1527 1294 1754 1550 1205 1251 1266 1116 1092 1226
p-value 0264 0132 0234 0119 0055 0109 0085 0000 0093 0144 0050
GFI 0985 0980 0989 0985 0968 0949 0952 0874 0910 0913 0937
CFI 0997 0994 0990 0972 0985 0989 0984 0967 0987 0990 0987
TLI 0995 0990 0983 0943 0979 0987 0980 0964 0986 0989 0984
RMSEA 0032 0047 0035 0057 0048 0029 0033 0034 0022 0020 0031
Structural Models Generated
The hypothesized model in Figure 4 shows a result that do not support model fit (plt05) This is expected as the
hypothesized model is usually strictly confirmatory (Figure 4) Thus modification index was used to fit the datato the generated model Subsequently a generated model (same paths as hypothesized model) was derived with
a goodness of fit been achieved (pgt05) Thus the generated model indicates a better goodness of fit indiceswhen some observed variables were deleted (Figure 5) Additionally a re-specified model has also been derived
whereby new paths have been suggested by modification indices and goodness of fit has also been achieved
(pgt05) (Figure 6) The hypotheses tested are based on the findings from the generated and re-specified model
Additionally analysis of competing model or original model (TAM) was also conducted to test the soundness
of the root model which shows a goodness of fit structure with pgt05 as well (Figure 7)
Figure 4 Hypothesized Model
Perceived
Usefulness
Perceived
Ease of Use
Perceived
Credibility
86
Internet
Adoption
78
Internet
Intention
79
83
76
93
58
PU6
e06
76
60
PU5
e05
77
58
PU4
e04
76
68
PU3
e03
83
51
PU2
e02
72
60
PU1
e01
78
62
EOU6e12
7861
EOU5e11
78
61
EOU4e10
78
60
EOU3e0977
59
EOU2e0877
62
EOU1e07
79
13
CRE6e18
3654
CRE5e17
74
29
CRE4e16
54
59
CRE3e1577
24
CRE2e1449
21
CRE1e13
46
25
INT1 e2450
17
INT2 e254125
INT3 e2650
19
INT4 e27
43
34
INT5 e28
59
48
IA8
e36
69
09
IA7
e35
29
27
IA6
e34
52
62
IA5
e33
7968
IA4
e32
8248
IA3
e31
69
43
IA2
e30
66
62
IA1
e29
79
R01
R02
Standardized estimates
Chi-Square 540394
Df 427
Ratio 1266
P Value 000GFI 874
RMSEA 034
31
20
44
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1016
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1016
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1116
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1077
Hypotheses Results
Direct influences of the exogenous to the respective endogenous variables of the two structural models are
shown in Table 10a to Table 10c Based on Standardized Beta estimates and critical ration (CR=t-values) valuesof gt196 H1 H3 and H4 are asserted in all generated and re-specified models Therefore H1 Perceived
usefulness is significantly and positively related to intention H3 Perceived credibility is significantly and
positively related to intention and H4 Intention is significantly and positively related to internet adoption Only
H2 is not significantly related thus it fails to be asserted ie perceived ease of use is insignificantly but
positively related to intention
In the re-specified model we also found three new paths as suggested by modification index results These
three new paths are assigned as H1a H2a amp H3a respectively as in Table 10b However these three paths do
not show any significant impact on internet adoption Thus H1a H2a and H3a are not supported
Table 10a Direct Impact of Generated Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0340 0103 2943 0003
H2 Internet Intention lt--- Perceived Ease of Use 0186 0156 1050 0294
H3 Internet Intention lt--- Perceived Credibility 0425 0220 2078 0038
H4 Internet Adoption lt--- Internet Intention 0923 0191 7176 0000
Table 10b Direct Impact of Re-specified Model Standardized Regression Weights
HRelationships between
Exogenous and Endogenous
Std
EstimateSE CR P-value
H1 Internet Intention lt--- Perceived Usefulness 0316 0103 2943 0032
H2 Internet Intention lt--- Perceived Ease of Use 0137 0156 1050 0553
H3 Internet Intention lt--- Perceived Credibility 0392 0220 2078 0120
H4 Internet Adoption lt--- Internet Intention 0432 0191 7176 0001
H1a(new)
Internet Adoption lt--- Perceived Usefulness 0178 0144 1630 0103
H2a
(new)
Internet Adoptionlt--- Perceived Ease of Use 0135 0211 0840 0401
H3a
(new)
Internet Adoptionlt---
Perceived Credibility0218 0300 1170 0242
Table 10c Direct Impact of Competing Model of TAM (Standardized Regression Weight)
Exogenous EndogenousStd
EstimateSE CR P Relationships
Perceived Usefulness
Perceived Ease of UseInternet Intention
Internet Intention
Internet IntentionInternet Adoption
0418
04950947
0102
01040206
3578
41047093
0000
00000000
Sig
SigSig
Squared Multiple Correlation (SMC=R2) of structural model
The SMC or R2 of generated model on internet adoption shows a high value of 852 re-specified model of
772 and competing model of 898 respectively (Table 11) Hence the result indicates that all exogenous
variables perceived ease of use (EOU) perceived usefulness (PU) and perceived credibility (CRE) and Intention
(INT) explained the variance in internet adoption of above 77 Similarly intention can be explained by 789
variance in the generated model 624 in the re-specified model and 751 in the competing model
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1216
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1078
Table 11 The Comparison of SMC between Structural Models
Endogenous Hypothesized Model Generated Model Re-Specified Competing Model of TAM SMC (R
2) SMC (R
2) SMC (R
2) SMC (R
2)
Intention
Adoption
775
859
789
852
624
772 751
898
Mediating Effect Analysis of Structural Models
The indirect influences of exogenous variables to internet adoption through intention are shown in Table 12a to
Table 12c In generated model two indirect estimates are significant but reduced compared to direct impacts
(Table 10a-10c) Thus H5 and H7 are asserted This means that intention partially mediates the relationshipsbetween perceived usefulness as well as perceived credibility with internet adoption Thus H5 to H7 are
asserted or intention is a partial mediator Alternatively Intention do not mediates the relationship between
perceived ease of use and internet adoption
Table 12a Indirect Effect (Mediating Effect) of Internet Intention of Generated Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0340 0923)
0314Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0186 0923)0171
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0425 0923)
0392Partial
Mediating
Conversely from Table 12b there appear to be an absence of any mediating effects of intention on all linkages
hypothesized for re-specified model This is because the indirect effects are smaller compared to direct effects
(Table 10a-10c) Interestingly in competing TAM model intention only serves as a partial mediator not a full
mediator as suggested by Davis (1989)
Table 12b Indirect Effect (Mediating Effect) of Internet Intention of Re-specified Model
H Exogenous Mediated Endogenous Path
Indirect
Effect
Estimate
Mediating
Hypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0316 0432)
0136Not
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0137 0432)0059
Not
Mediating
H7PerceivedCredibility
InternetIntention
InternetAdoption
CRE Intention Adoption(0392 0432)
0169Not
Mediating
Table 12c Indirect Effect (Mediating Effect) of Internet Intention of Competing Model
H Exogenous Mediated Endogenous PathIndirectEffect
Estimate
MediatingHypothesis
H5PerceivedUsefulness
InternetIntention
InternetAdoption
PU Intention Adoption(0418 0947)
0395Partial
Mediating
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption
EOU Intention Adoption
(0495 0947)0468
Partial
Mediating
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1316
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1079
Overall Comparison between structural models
Table 13 illustrates the overall comparison between four structural models (hypothesized generated re-
specified and TAM competing models) derived from the study It shows that hypothesized and generated
models both produce three significant direct impacts (perceived usefulness and internet intention perceived
credibility and intention and internet intention and internet adoption) Re-specified model produces two
significant direct impacts (perceived usefulness and intention intention and internet adoption) It also indicates
that intention and adoption is consistently showing a positive significant effect in all structural models
Similarly TAM competing model supports all three direct impacts (all significant) perceived usefulness to
intention perceived ease of use to intention and intention to adoption
For indirect or mediating effects intention partially mediates the path between perceived usefulness and
adoption consistently three structural models (hypothesized generated and competing model) except in re-
specified model Intention acts as a partial mediator between perceived credibility and adoption in two structural
models ie hypothesized and generated model Intention is not a mediator between perceived ease of use and
adoption in all structural models except a partial mediator in competing TAM model
Table 13 also shows the nested model comparisons between the four structural models derived in this study All
Chi-square and DF change between models are more than 384 or gt 1df respectively Thus the nested model
tests could be substantiated (Hair et al 2006 Tabachnick amp Fidell 2007)
Table 13 Comparison between Hypothesized Generated Re-specified and Competing Model
H Endogenous Mediation Exogenous
Hypothesized Model Generated Model Re-Specified Competing Model of TAM Std
Estimate
P Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
Std
Estimate
p Hypothesis
Status
H1 Perceived
Usefulness
- Internet
Intention0305 Sig Asserted
0340Sig Asserted 0316 Sig Asserted 0418 Sig Asserted
H2 Perceived
Ease of Use
- Internet
Intention0203 Insig Rejected
0186Insig Rejected 0137 Insig Rejected 0495 Sig Asserted
H3 Perceived
Credibility
- Internet
Intention
0437 Sig Asserted
0425
Sig Asserted 0392 Insig Rejected - - -
H4 Internet
Intention
- Internet
Adoption0927 Sig Asserted
0923Sig Asserted 0432 Sig Asserted 0947 Sig Asserted
H5Perceived
Usefulness
Internet
Intention
Internet
Adoption0282
SigAsserted
0314Sig
Asserted
(Partial)
0136 Insig Rejected
(Not
Mediating)
0395 Sig Asserted
(Partial)
H6Perceived
Ease of Use
Internet
Intention
Internet
Adoption0188
InsigRejected
0171Insig
Rejected
(Not
Mediating)
0059 Insig Rejected
(Not
Mediating)
0468 Sig Asserted
(Partial)
H7Perceived
Credibility
Internet
Intention
Internet
Adoption0405 Sig Asserted
0392
Sig Asserted
(Partial)
0169 Insig Rejected
(Not
Mediating)
- - -
Goodness of Fit Index
Chi-Square
Chisquare ∆
Df
Df ∆
Ratio
P ValueGFI
RMSEA
SMC
Intention
Adoption
540394
427
1266
0000
0874
0034
775
859
299122
241272
268
159
1116
0093
0910
0022
789
852
289512
961
265
3
1092
0144
0913
0020
624
772
141000
148512
115
150
1226
0050
0937
0987
751
898
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1416
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1080
5 Discussions
This study attempts to examine the empirical relationships between technology usage perception and credibilitywith internet adoption in SME Additionally this study also investigates the mediating effect of intention on
those relationships as hypothesized based on the conceptual underpinning of Technology Acceptance Model
(TAM)
The finding indicates that perceived usefulness is significantly and positively related to internet intention
Besides Daviss (1989) extensive research in the information systems (IS) community provides evidence of the
significant effect of perceived usefulness on internet intention (Petty Cacioppo amp Schumann 1983 Taylor amp
Todd 1995 Venkatesh amp Davis 2000) This implies that SME have the intention to use internet for increasing
their productivity enhancing effectiveness and improving the SME business Perceived credibility is also found
to be significantly and positively related to intention This finding is supported by previous studies (Kardaras amp
Papathanassiou 2001 Polatoglu and Ekin (2001) Those SME owners who feel that the internet has high
security privacy and trustworthiness of information would definitely have high intention of using the internet
Lastly intention is found to be significantly and posit ively related to internet adoption Previous studies have
found similar findings (Limayem et al 2000 Lin 2007) Direct path from intention to adoption is the most
consistent finding across all models thus it can be deducted that those SMEs who has the intention to useinternet would definitely adopt the internet in the future Our study found perceived ease of use is
insignificantly but positively related to intention Polatoglu and Ekin (2001) found similar insignificant
relationship between perceived ease of use and intention They argue that ease of use may not be used if it is not
perceived as useful thus we conclude that the perceived usefulness of internet intention of SME is the key
construct for adoption among entrepreneurs (as we found above) Contrastingly numerous researches had found
positive and significant linkages (Agarwal and Prasad 1999 Davis et al 1989 Hu et al 1999 Jackson et al
1997 Venkatesh 1999 2000 Venkatesh and Davis 1996 2000 Venkatesh and Morris 2000 Moon amp Kim2001) The probable reason for this difference could be that most of the SME operators still find internet
technology difficult to understand Most likely the SME operators need to have more training and exposure to
internet knowledge to improve this situation
This study also found partial mediating effects of intention on linkages between perceived usefulness perceived
credibility and perceived ease of use with internet adoption The additional findings on the new paths in the re-
specified model support the presence of mediating effects for these relationships Our findings found substantial
partial mediating effect This could imply that the adoption of internet may not be a direct process More often
than not intention is profoundly necessary to enhance the relationship concerned
6 Conclusions
This research investigates the predictors and mediating effects of intention on internet adoption amongst small
and medium scale entrepreneurs using TAM conceptual underpinning theory The f indings support the TAM
theory extremely well whereby all the hypothesized paths were asserted The gen erated model found threesignificant direct paths between perceived usefulness perceived credibility and intention as well as between
intention and adoption The re-specified model produces two significant direct paths (perceived usef ulness tointention and intention to adoption) and also introduces three new paths (direct paths f rom perceived usefulness
perceived ease of use and perceived credibility to adoption) The model also manage to establish partial
mediating effects of intention on the said relationships between exogenous and internet adoption
7 Suggestion for Future Research
Future research should investigate other underpinning TAM theory such as TAM2 (Venkatesh and Davis (2000)
and extended TAM (Chiu 2004) The importance of the SME field cannot be denied and it is still very much
under-researched especially in Asian countries Similar cross- cultural studies could be conducted in the future
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1516
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1081
8 References
Ajzen I amp Fishbein M (1980) Understanding attitudes and predicting social behavior Englewood Cliffs NJ Prentice-Hall
Agarwal R and Prasad J (1999) ldquoAre individual differences germane to the acceptance of new information
technologiesrdquo Decision Sciences Vol 30 No 2 pp 361-91
Bagozzi RP and Y Yi 1988 On the evaluation of structural equation models Journal of the Academy of Marketing
Science 16 74-94
Chiu CM (2004) Determinants of continued use of the WWW an integration of two theoretical models Industrial
Management amp Data Systems Vol 104 No9 pp766-75
Daniel E (1999) Provision of electronic banking in the UK and the Republic of Ireland International Journal of Bank
Marketing Vol 17 No2 pp72-83
Davis FD (1989) ldquoPerceived usefulness perceived ease of use and user acceptance of information technologyrdquo MIS
quarterly Vol 13 No 3 pp 318-39
Davis F D Bagozzi R P amp Warshaw P R (1989) User acceptance of computer technology A comparison of two
theoretical models Management Science 35(8) 982-1003
Fishbein M amp Ajzen I (1975) Belief Attitude Intention and Behavior An Introduction to Theory and Research
Reading MA Addison-Wesley
Fornell amp Larcker (1981) Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research 48 39ndash50
Ganesan S (1994) Determinants of long-term orientation in buyer-seller relationships Journal of Marketing Vol 58
No2 pp1-19
Hair J Black B Babin B Anderson R and Tatham R (2006) Multivariate Data Analysis (6th
edition) Upper Saddle
River NJ Prentice-Hall
Harrison AW Rainer RK Jr (1992) The influence of individual differences on skill in end-user computing Journal
of Management Information Systems Vol 9 No1 pp93-111
Hoffman DL Novak TP and Peralta M (1999) ldquoBuilding consumer trust onlinerdquo Communications of the ACM Vol
42 No 4 pp 80-5
Jackson CM Chow S Leitch RA (1997) Toward an understanding of the behavioral intention to use an informationsystem Decision Sciences Vol 28 No2 pp357-89
Kardaras D amp Papathanassiou E (2001) ldquoElectronic commerce opportunities for improving corporate customer support
in banking in Greecerdquo International Journal of Bank Marketing (UK) Vol 19 No 7
Kim KK Prabhakar B Kim BH (2001)rdquoInitial Trust as a Determinant of the Adoption of Internet Bangkingrdquo available
at httpmriinhaackrarticle8-1banking5DPDF
Levin T and Gordon C (1989) ldquoEffect of gender and computer experience on attitudes towards computersrdquo Journal of
Educational Computing Research Vol 5 No 1 pp 69-88
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm
8142019 8 - Empirical Study on Internet Adoption among SMEspdf
httpslidepdfcomreaderfull8-empirical-study-on-internet-adoption-among-smespdf 1616
983090983150983140
983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140
983113983107983106983109983122 983090983088983089983089983081 983120983122983119983107983109983109983108983113983118983111
1082
Limayen M Khalifa K and Firni A (2000) lsquoWhat makes consumers buy from Internet A longitudinal study of online
shoppingrsquo IEEE Transactions on Systems Man and Cybernetics vol30 no4 pp421-432
Liao S Shao YP Wang H Chen A (1999) ldquoThe adoption of virtual banking an empirical studyrdquo InternationalJournal of Information Management Vol 19 No1 pp63-74
Lindskold S (1978) ldquoTrust development the GRIT proposal and the effects of conciliatory acts on conflict and
cooperationrdquo Psychological Bulletin Vol 85 No4 pp772-93
Mathieson K (1991) Predicting user intentions comparing the technology acceptance model with the theory of planned
behavior Information Systems Research Vol 2 No3 pp173-91
Morgan RM Hunt SD (1994)rdquoThe commitment-trust theory of relationship marketingrdquo Journal of marketing 58 20-
38
Moon J and Y Kim(2001) ldquoExtending the TAM for a World-Wide-Web Contextrdquo Information amp Management 38 217-
230
Nunnally JC Introduction to Psychological Measurement New York McGraw-Hill 1970
Pavlou PA (2001) ldquoConsumer Intention to adopt electronic commerce ndash Incorporating Trust and Risk in the Technology
Acceptance Modelrdquo in Proceedings of the Diffusion Interest Group in Information Technology Conference
(DIGIT2001) Sunday 16 December New Orleans LA
Polatoglu VN Ekin S (2001) An empirical investigation of the Turkish consumers acceptance of Internet banking
services International Journal of Bank Marketing Vol 19 No4 pp156-65
Petty R E Cacioppo J T amp Schumann D (1983) ldquoCentral amp Peripheral Routes to Advertising Effectiveness The
Moderating Role of Involvementrdquo Journal of Consumer Research 10 (2) 135-146
Saade RG Nabebe F and Tan W (2007) ldquoViability of the technology acceptance model in multimedia learning
environments A Comparative Studyrdquo International Journal of Knowledge and Learning Objects 3 175-184
Tabachnick B G and Fidell L S (2007) Using Multivariate Statistics 5th ed Boston Allyn and Bacon
Taylor S and Todd PA (1995) ldquoUnderstanding information technology usage a test of competing modelsrdquo Information
Systems Research Vol 6 No 2 pp 144-76
Venkatesh V and Davis FD (2000) ldquoA theoretical extension of the technology acceptance model four longitudinal field
studiesrdquo Management Science Vol 45 No 2 pp 186-204
Venkatesh V (2000)rdquo Determinants of perceived ease of use integrating control motivation and emotion
Venkatesh V (1999) ldquoCreation of favorable user perceptions exploring the role of intrinsic motivationrdquoMIS QuarterlyVol 23 No2 pp 239-60
Venkatesh V Morris MG Davis GB and Davis FD (2003) ldquoUser acceptance of information technology toward a
unified viewrdquo MIS Quarterly Vol 27 No 2 pp 425-78
Wang YS Wang YM Lin HH and Tang TI (2003) ldquoDeterminants of user acceptance of Internet banking An empirical
studyrdquo International Journal of Service Industry Management 145 501-519
httpwwwinternetworldstatscom
httpwwwairniniacomworldfactscountriesMalaysiapopulationhtm