8 - empirical study on internet adoption among sme's.pdf

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8/14/2019 8 - Empirical Study on Internet Adoption among SME's.pdf http://slidepdf.com/reader/full/8-empirical-study-on-internet-adoption-among-smespdf 1/16      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 was designed to tap into the owner’s 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 using structural equation modeling (SEM) to test the causal and mediating effects amongst latent variables. From the analysis, the hypothesized model fit fails to be supported (p<.05). 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 millennium depend 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 (www.internetworldstats.com). 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 and credibility 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 & Fishbein, 1980; Fishbein & Ajzen, 1975) and theory of planned behavior (Ajzen,

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Page 1: 8 - Empirical Study on Internet Adoption among SME's.pdf

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

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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

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983113983118983124983109983122983118983105983124983113983119983118983105983116 983107983119983118983110983109983122983109983118983107983109 983119983118 983106983125983123983113983118983109983123983123 983105983118983108 983109983107983119983118983119983117983113983107 983122983109983123983109983105983122983107983112 983080983090983150983140

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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

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8142019 8 - Empirical Study on Internet Adoption among SMEspdf

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983090983150983140

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

Page 2: 8 - Empirical Study on Internet Adoption among SME's.pdf

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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

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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

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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)

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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

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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

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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

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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

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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

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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

Page 3: 8 - Empirical Study on Internet Adoption among SME's.pdf

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

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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)

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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

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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

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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

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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

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8142019 8 - Empirical Study on Internet Adoption among SMEspdf

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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

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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

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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

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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

Page 4: 8 - Empirical Study on Internet Adoption among SME's.pdf

8142019 8 - Empirical Study on Internet Adoption among SMEspdf

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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

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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

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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

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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

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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

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8142019 8 - Empirical Study on Internet Adoption among SMEspdf

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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

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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

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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

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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

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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

Page 5: 8 - Empirical Study on Internet Adoption among SME's.pdf

8142019 8 - Empirical Study on Internet Adoption among SMEspdf

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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

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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

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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

Page 6: 8 - Empirical Study on Internet Adoption among SME's.pdf

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

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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

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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

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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

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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

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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

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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

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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

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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

Page 7: 8 - Empirical Study on Internet Adoption among SME's.pdf

8142019 8 - Empirical Study on Internet Adoption among SMEspdf

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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

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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

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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

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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

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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

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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

Page 8: 8 - Empirical Study on Internet Adoption among SME's.pdf

8142019 8 - Empirical Study on Internet Adoption among SMEspdf

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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

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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

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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

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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

Page 9: 8 - Empirical Study on Internet Adoption among SME's.pdf

8142019 8 - Empirical Study on Internet Adoption among SMEspdf

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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

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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

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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

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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

Page 10: 8 - Empirical Study on Internet Adoption among SME's.pdf

8142019 8 - Empirical Study on Internet Adoption among SMEspdf

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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

Page 11: 8 - Empirical Study on Internet Adoption among SME's.pdf

8142019 8 - Empirical Study on Internet Adoption among SMEspdf

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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

Page 12: 8 - Empirical Study on Internet Adoption among SME's.pdf

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

Page 13: 8 - Empirical Study on Internet Adoption among SME's.pdf

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

Page 14: 8 - Empirical Study on Internet Adoption among SME's.pdf

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

Page 15: 8 - Empirical Study on Internet Adoption among SME's.pdf

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

Page 16: 8 - Empirical Study on Internet Adoption among SME's.pdf

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