Information technology adoption in small business confirmation of a proposed framework2013

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Information Technology Adoption in Small Business: Confirmation of a Proposed Framework

by ThuyUyen H Nguyen, Michael Newby, and Michael J Macaulay

This paper investigates which drivers affect information technology (IT) adoption and which factors relate to a successful IT implementation in small businesses, where the adoption rate is traditionally low and the failure rate is high The findings from this study suggest that customers are the main driving force of IT adoption When it comes to IT implementation, our results suggest that managers/owner–managers must engage with five factors: organization, internal IT resources, external IT consultants, supplier relations, and customer relations These findings give further insight into IT adoption in small businesses and highlight the importance of customer relations in the adoption process.

Introduction

Information technology (IT) adoption is

the stage at which a decision is made about

adopting particular hardware and/or

soft-ware technology (Thong 1999) and involves

various activities, including managerial and

professional/technical staff decision-making in

both the internal and external environment of

the organization, which must occur before the

given technology can have a physical presence

in the organization (Grover and Goslar 1993;

Preece 1995) There have been a number of

research studies on the determinants of IT

adop-tion in small businesses such as those by

Bharadwaj and Soni (2007), Fuller (1996), Irvine

and Anderson (2008), Lee and Runge (2001),

(2003), and Thong (1999), all of which focus on

searching for factors that affect the decision and

intention to adopt IT These factors include cost

benefits, management innovativeness, tion, knowledge and skills, employee attitudes,acceptances and contributions (the Theory ofPlanned Behavior and the Technology Accep-tance Model), IT skills and knowledge of man-agement and employees, and IT infrastructure.The decision to adopt is also influenced byexternal factors such as consultants, businesspartners, suppliers, and customers

percep-However, it is not always clear whethersmall businesses see new IT as an opportunity

or a threat Evidence suggests that IT adoptionrates in small business are low, and that failurerates are high: the question is why Some com-mentators have suggested that using IT is notalways going to be beneficial to such firms(Bull 2003; Oakey and Cooper 1991), whileothers have argued that IT is not appropriatefor every small firm (Macpherson et al 2003;Morgan, Colebourne, and Thomas 2006) Levy,Powell, and Yetton (2001) suggest that IT

ThuyUyen H Nguyen is Senior Lecturer in Business Analysis, Systems, and Supply Change Management

at Northumbria University, UK.

Michael Newby is Professor of Information Systems and Decision Sciences at California State University, Fullerton.

Michael J Macaulay is Associate Professor of Public Management at School of Government, Victoria University, New Zealand.

Address correspondence to: ThuyUyen H Nguyen, Newcastle Business School, Northumbria University, Newcastle upon Tyne NE1 8ST, UK E-mail: thuyuyen.nguyen@northumbria.ac.uk.

Journal of Small Business Management 2013 ••(••), pp ••–••

doi: 10.1111/jsbm.12058

adoption in small businesses often happens

without any proper planning, resulting in a low

According to Carson and Gilmore (2000), small

businesses, especially new ones, often

experi-ence ambiguity and uncertainty regarding IT

adoption Bhagwat and Sharma (2007) point

out that many difficulties are due to the lack of

resources (financial, technical, and managerial)

available to small businesses

This paper extends these debates and

sug-gests that there is no one single factor that

accounts for the low adoption rate or the high

failure rate of IT adoption in small businesses

Indeed, this paper will demonstrate, through

an empirical study of the IT adoption process in

small businesses, that there are five

intercon-nected factors that influence the success or

failure of IT adoption: organization, internal IT

resources, external IT consultants; supplier

relations, and customer relations In so doing,

this paper offers a twofold approach: first, it

investigates drivers to or reasons for IT

adop-tion in small businesses; second, it determines

factors relating to a successful implementation

in the specific context of three industries (retail,

financial services, and manufacturing) in Los

Angeles County and Orange County in

South-ern California

The remainder of this paper is structured as

follows: the next section presents a review of

key aspects of the cognate literature in this area

and an outline of the components of the study

research framework This is followed by the

research methodology, the results analysis, and

a discussion of the findings and implications

Limitations of the study are also discussed with

some suggestions for future research

Background and

Theoretical Framework

IT Adoption in Small Businesses

By changing the way staff capture and

dis-tribute information (Claessen 2005; Currie

2004), IT provides organizations with a number

of benefits—sustainable competitive advantage

(Bruque and Moyano 2007; Carbonara 2005;

Hung and Tang 2008; Lee and Runge 2001),

lower production and labor costs, added value

to products and services (Corso et al 2003;

Nguyen, Sherif, and Newby 2007; Premkumar

2003)—while generally improving business

pro-cesses (Búrca, Fynes, and Marshall 2005; Levy,

Powell, and Yetton 2001) Despite these

poten-tial benefits, there have been numerous cases of

unsuccessful IT implementations in this sector(Acar et al 2005; Mole et al 2004; Ruiz-Mercader, Meroño-Cerdan, and Sabater-Sánchez2006), and the adoption rate can be very slow(Peltier, Schibrowsky, and Zhao 2009; Thong1999) A survey conducted by the research andadvisory firm Gartner, for example, found thatmore than half of the organizations that hadimplemented IT encountered difficulties afterimplementation (Baumeister 2002)

The key to this lack of success appears to be

a disconnection between vision and execution:organizations do not do enough research andplanning before implementing the new tech-nology, often because management is unclearabout how and why their firms are adopting

IT in the first place (Bull 2003;

2007) Added to this are other barriers to tion Some firms do not have the capabilities toexpand their IT resources (Acar et al 2005;Bharadwaj and Soni 2007; Claessen 2005) asthey lack business and IT strategies Othershave only limited access to capital resourcesand also have limited IT/Information Systemsskills (Ballantine, Levy, and Powell 1998;Bruque and Moyano 2007) There are, inevita-bly, financial barriers (Lema and Duréndez2007; Shin 2006) In addition, project executionoften failed or suffered from a lack of seniormanagement support, poor project manage-ment, or insufficient skills to complete theproject (Bull 2003; Näslund and Newby 2005)

adop-At the same time, there is a significant influencefrom major customers (Bhagwat and Sharma2007) who are becoming more demanding andexpect rising standards of IT excellence If cus-tomer influence goes unrecognized, and orga-nizations rush into implementing IT, they willexperience problems (Mazurencu-Marinescu,Mihaescu, and Niculescu-Aron 2007)

The present paper investigates the tendency

to adopt IT in small businesses using the

(Figure 1) Here, it is suggested that small firmsadopt IT for reasons that come from either theinternal or external pressures or forces These

reasons are known as drivers to adoption as

they are ultimately the cause of adoption of IT

in a business In addition, the framework grates four main aspects of small businesswhen it comes to IT adoption, and these are (1)organizational, which includes management,staff, culture, and knowledge; (2) networkorientation (or networking, as illustrated in

inte-Figure 1) that includes the relationship to the

suppliers, business partners, and customers; (3)

external IT consultants; and (4) internal IT

resources, which include the IT abilities,

capacities, and capabilities of the firm These

aspects will be referred to as factors, as they are

predicated to affect the success of IT adoption

and will be explored and expanded upon

after-ward In the context of this study, IT to be

adopted can range from the Microsoft Office

Suite (Microsoft, Redmond, WA, USA) to an

enterprise resources planning system or point

of sales (POS) system and is used to manage

resources and communications in daily ness operations

busi-Drivers to AdoptionThe report by the National Federation ofIndependent Business (2005) on the state oftechnology in small business indicates that themost common reason for technology to beupgraded in this sector is simply the desire toupgrade it, but it is not clear what drives this.Studies suggest that for many firms, the mostcommon objectives for IT adoption are toenhance organizational survival and/or growth

Figure 1 Conceptualized Framework for Small and Medium-Sized Enterprises

(SME) Information Technology Adoption

External expertise

Information technology resources

Life cycle/ Maturity

Growth stages

External

force

Factor(s)

Driver(s)

Source: Adapted from Nguyen, T H (2009) “Information Technology Adoption in SMEs:

An Integrated Framework,” International Journal of Entrepreneurial Behaviour and

Research 15(2), 164.

and to remain competitive and/or enhance

inno-vative capacity (Bridge and Peel 1999; Bruque

and Moyano 2007; Búrca, Fynes, and Marshall

2005) These can be the result of pressure from

both the internal and external environment

(Andries and Debackere 2006; Morel and

Ramanujam 1999; Winter et al 2003), from

either an emphasis on improving efficiency and

business expansion or a pressure to meet certain

requirements from customers and industry

stan-dards (Ballantine, Levy, and Powell 1998; Corso

et al 2003) Rogers (2003) refers to these drivers

as part of an innovation decision process, where

management and organizations assess the

advantage and disadvantage of the adoption

This is an important aspect of small and

medium-sized enterprises (SMEs), especially in

small businesses, where it has been noted that

insufficient finance is one of the sector’s

weak-nesses when it comes to investment (Eden,

Levitas, and Martinez 1997; Lema and Duréndez

2007) Most small businesses do not have

sufficient financial resources and often, they

mortgage their own personal possessions as

collateral (Fuller-Love 2006) As a result, these

organizations search for positive potential

ben-efits from any investment They have to see or at

least believe that new IT will bring advantages to

their firms (Eden, Levitas, and Martinez 1997;

Riemenschneider, Harrison, and Mykytyn 2003)

Hence, drivers to adoption can be viewed not

only as reasons for, but also as catalysts, triggers,

or prerequisites for IT adoption in small

busi-nesses (Nguyen 2009) The decision to adopt IT

is the result of these drivers However, it is not

part of the adoption process The next section

details our research model and study

hypoth-eses on the IT adoption process

Research Model and

Study Hypotheses

IT Success Implementation

The dependent variable measured here is

the IT success implementation As suggested

by Bruque and Moyano (2007), success can be

measured in terms of rapid and effective use

of the new technology, where the objective of

the adoption is to reach a desired outcome

The objective of a successful implementation

can range from the return on investment

(ROI), increase in revenue, increase in sales,

or improvement in quality of products and

services (Anderson and Huang 2006; Payne

and Frow 2005; Raymond 2005; Roberts, Liu,

and Hazard 2005) Thong (1999) suggests thatsuccess in implementation is directly influ-enced by organizational factors, particularlythe top management, and by IS externalexpertise Levy, Loebbecke, and Powell (2003)suggest that SMEs benefit from their externalenvironment when it comes to knowledgegenerated for the firms, whereas Caldeira andWard (2002) contend that the internal ITresources contribute to the success of theimplementation

In this study, the measure for the dependentvariable is on the five-point Likert scale(strongly agree to strongly disagree) Thismeasure indicates the degree to which therespondents rate their IT adoption to be suc-cessful Five items were used to measure the ITsuccess implementation scale The first andsecond items assess the ROI and increase inrevenue, the third item concerns the increase insales and services volumes, and the fourth andfifth items relate to the improvement in quality

of products and services

The dependent variable was hypothesized to

be dependent on four factors: organizational,network orientation, external IT consultants,and internal IT resources These four factorsconstruct an adoption environment, whichmeasures the overall preparedness (in terms of

capacities, and capabilities) of the business toadopt new IT The factors of the environmentare interrelated, and it is hypothesized that allcontribute to the success (or otherwise) of theimplementation

Figure 2 summarizes the stages of the tion process The drivers to adoption lead to adecision to adopt IT This decision affects theadoption environment within the business, andthe environment, in turn, affects whether theimplementation is successful or not, so thesuccess of the implementation is viewed as anoutcome of the adoption environment Figure 3gives details of our primary research model.The methodology used here follows that ofBaker and Sinkula (2009), which involvesdeveloping a survey instrument, then measur-ing and confirming the proposed researchmodel (see Figure 3)

adop-The Relationship between OrganizationalFactor and Successful ImplementationPrevious studies have identified a number oforganizational factors that influence the ITadoption process, including the size of the firm,

its goals, the knowledge, skills and experience

of staff, and the organizational culture and

structure It is suggested that a culture that is

flexible to change is more innovative than one

that is resistant to change (Denison, Lief, and

Ward 2004) Hence, in a flexible culture, the

adoption of IT is more likely to happen and is

more likely to succeed (Minguzzi and Passaro

Sabater-Sánchez 2006) Organizational culture

in small business is seen as being strongly

influenced by the owner–manager’s attitude,

personality, and values (Dibrell, Davis, and

Craig 2008; Gudmundson, Tower, and Hartman

2003; Riemenschneider and McKinney 2001/

2002) In small organizations, management or

owner–managers make most, if not all, of the

key decisions (Fuller-Love 2006; Stanworth and

Gray 1992), and these decisions are based on

their existing knowledge, personal judgment,

and communication skills (Carson and Gilmore

2000) It is not only their decisions that affectthe adoption of IT, but also their commitment

to the adoption process as well (Näslund andNewby 2005) At the same time, the employees’knowledge, and degree and form of involve-ment contribute to the success of the IT adop-tion (Anderson and Huang 2006; Igbaria et al.1997; Kotey and Folker 2007) In addition,employees should understand the purposebehind the adoption, their role within theadoption, and their contribution to it Hence,communication between the management andemployees regarding the change is essential.Failure to communication can lead to doubt inemployees about the usefulness of the newtechnology, resulting in a negative attitudetowards the change, fear about job security,and a low level of support Finally, small busi-nesses are viewed as knowledge generatorsand knowledge dispersion enterprises (Dew,

Loebbecke, and Powell 2003) Their ability toabsorb existing knowledge, transform it, use it,and generate new knowledge affects the ITadoption process (Gray 2006; Macpherson andHolt 2007; Zahra, Neubaum, and Larrañeta2007) Management should ensure that there isefficient knowledge sharing among individualswithin the firm, as the IT adoption processrequires teamwork and acceptance across allfunctions within a firm (Phelps, Adams, andBessant 2007; Smith 2007) Moreover, techno-logical learning and IT can promote entrepre-neurial development and growth (Carayannis

et al 2006) The discussion earlier leads us tothe following hypothesis:

H1: The organizational factor is directly and positively related to a successful implementation.

The Relationship between NetworkOrientation Factor and SuccessfulImplementation

A core characteristic of small businesses istheir relationship networks (Fletcher 2002;Lema and Duréndez 2007) These networksemerge through the numerous interactions,which take place between firms, businesspartners, vendors, suppliers, and customers.They can be personal networks (Lema andDuréndez 2007) or business networks (and onoccasions, it can be difficult, if not impossible,

to differentiate between the two), and they arenot restricted by organizational boundaries

Figure 2 Information Technology (IT)

IT Success Implementation

(Taylor and Pandza 2003) Through these

net-works, firms exchange, collaborate, and share

knowledge, information, and communication

(Pittaway et al 2004; Taylor and Pandza 2003)

Collaboration with customers or suppliers can

facilitate the development and improvement of

products and/or services (Levy, Loebbecke,

and Powell 2003; Rosenfeld 1996) According

to Rosenfeld (1996), this is where knowledge

Collaboration with these external networks

brings learning opportunities (Rothwell 1991),

knowledge creation (Dew, Velamuri, and

Venkataraman 2004), and competitive tage (Taylor and Pandza 2003) Because theyoften lack IT resources and skills (Carbonara2005; Chan and Chung 2002), small businessescan benefit from network membership when itcomes to IT adoption (Au and Enderwick2000), as networking can provide SMEs withnecessary resources (Fletcher 2002) Conse-quently, our second hypothesis is

advan-H2: Network orientation is directly and positively related to a successful implementation.

Figure 3 Information Technology (IT) Adoption Research Model

H1

H2

H4 H3

Adoption Environment

Drivers to Adoption-Internal forces

- External forces

IT Adoption

The Relationship between External IT

Consultants and Successful

Implementation

Because small businesses generally lack IT

expertise and skills (Izushi 2005), firms often

seek professional consultants when it comes

to IT adoption (Fuller 1996; Shin 2006) It has

been suggested that advice from professional

consultants or IT vendors can be useful for

managers, especially when they do not have

sufficient experience or understanding of IT

2003) Research by Thong, Yap, and Raman

(1996) suggests that external IT expertise

plays an important role in the IT

implemen-tation process Turban, Aronson, and Liang

acquired and absorbed knowledge from

assist-ing their clients, and therefore can offer this

knowledge to firms that seek their help

Although IT expertise has been perceived to

have benefit for small business when it comes

to IT adoption, not all small businesses utilize

these resources as the knowledge comes at a

cost, and some firms are not in a financial

position to accommodate such expenses (Bull

2003; Izushi 2005) Therefore, we propose the

following hypothesis:

H3: External IT consultants are directly

and positively related to a successful

implementation.

The Relationship between Internal IT

Resources and Successful

Implementation

The IT resources factor focuses on the IT

abilities, capabilities, and capacities of a firm

The former refers to the skills, the second to

the resources and strategies, and the latter the

ability of firms to absorb, process, and present

the information the firm holds (Carbonara

2005; Guan et al 2006; Premkumar 2003)

According to Caldeira and Ward (2003),

orga-nizational competencies; orgaorga-nizational and

technical processes; technical, managerial, and

business skills; and the allocation of resources

within firms are the key ingredients for

under-standing IT adoption in the small enterprise

sector Other studies suggest that IT managers

should not only understand the reasons why IT

needs to be implemented in their businesses,

but also the importance of taking into account

the needs of their suppliers and customers

(Guan et al 2006; Mata, Fuerst, and Barney1995) As mentioned earlier, IT can assist firms

in enhancing their business practices, so a clearpurpose for pursuing new IT should be identi-fied before any key decision on IT adoption ismade Guan and Ma (2003) argue that the ITinnovation capability of a firm cannot be mea-sured by a single dimension alone, as it iscomprised of technology infrastructure, pro-duction, process, knowledge, experiences, and

between internal experience and experimentalacquisition and includes a wide variety ofassets and resources Hence, the IT abilities,capabilities, and capacities of the organizationplay a key role in the IT adoption process(Búrca, Fynes, and Marshall 2005), and wehypothesize that

H4: Internal IT resources are directly and positively related to a successful implementation.

Research Methodology

Sample and Data CollectionThe sample was taken from owners andmanagers of small businesses that are dealing

or participating in any IT adoption process inthe retail, financial services, and manufacturingsectors in Southern California With the help of

an employment agency, 437 employers werecontacted, and 284 agreed to participate in thesurvey The survey questionnaires were mailed,and there were 117 responses Five more com-pleted questionnaires were received afterfollow-up telephone calls, which gave aresponse rate of 43 percent Of the 122responses, 17 were excluded because therewere too much incomplete data This resulted

in 105 usable sets of data, which give an overallresponse rate of 37 percent This sample size isnot unusual for this type of study or for themethod used It is similar in size to those used

by Baker and Sinkula (2009), Brouthers andNakos (2005), and Werbel and Danes (2010)

Of the firms that responded to the survey,the industry breakdown is as follows: 36.6percent were from retail, 45.8 percent fromfinancial services, and 20.5 percent in manufac-turing In terms of size, 19.6 percent have 10employees or fewer, 30.8 percent between 11and 25 employees, 38.3 percent between 26and 50, and 11.2 percent more than 50 employ-ees Of the respondents, 58 percent were maleand 42 percent female The age distribution

was 9.8 percent under the age of 25, 40.0

percent between 25 and 34, 38.1 percent

between 35 and 44, and 12.4 percent over 45

years of age All respondents had more than

three years experience The data were tested

for potential effects associated with the specific

industry sector (retail, financial services, and

manufacturing) The results suggest that there

are no significant differences in the responses

due to industry sector

Research Instrument and

Measuring Scale

The survey questionnaire was developed

and structured on four scales that correspond

to the factors of the IT adoption environment

(see Figure 3) These scales are organizational,

network orientation, external IT consultants,

and internal IT resources Although this is the

first time this particular model has been tested,

scales and items from existing instruments

were used as much as possible Organizational

and external IT consultant scales were taken

from the IS effectiveness instrument of Thong,

Yap, and Raman (1996) This instrument was

Innovation Inventory An additional two items

in these two scales were taken from Özgener

and I˙raz (2006) and Payton and Zahay (2005)

The network orientation scale measures the

orientations of the organization and its

suppli-ers and customsuppli-ers It was adapted from the

REMARKOR (Clarkson 1998) This instrument

is an extension of the MARKOR instrument

by Kohli, Jaworski, and Kumar (1993), which

measures the relationship orientation The

REMARKOR instrument has seven scales These

scales have between two and 17 items per scale

with a total of 44 items Only items that are

relevant to the context of this study were used

The internal IT resource scale was derived from

Caldeira and Ward (2002) and Özgener and I˙raz

(2006)

All items are on a five-point Likert scale

(strongly agree, agree, neutral, disagree, or

strongly disagree) Table 1 gives descriptive

information for each constructed scale As the

number of items in each scale was different, the

mean score of each scale was calculated for

each individual response, so that for each scale,

the respondent had a score between 1 and 5

Questions for possible reasons/drivers to IT

adoption for small businesses were derived

from Caldeira and Ward (2002), Payton and

Zahay (2005) They include customer

require-ment, business expansion, quality ment, industry requirement, investment, andcost control These questions are not part of theinstrument because the drivers to adoption areseparate from the adoption environment (seeFigure 3) Questions on demographic informa-tion were also included

improve-Results

Instrument ValidationExploratory factor analysis using principalcomponent analysis with varimax rotation wasperformed on the 105 cases to extract thefactors that were hypothesized According to anumber of authors, a sample size of 105 is morethan enough for four scales (Hair et al 2005;Kline 1994; Lawley and Maxwell 1971) TheKaiser–Meyer–Olkin sampling adequacy mea-surement (Kaiser 1958, 1974) was 0.823 This is

classed as meritorious (Norusis 1990) and cates that the matrix is factorable, and so, the

indi-assumptions for carrying out factor analysiswere met Using eigenvalues greater than 1.5 asthe criterion, five factors were extracted Three

of the factors were as postulated: these wereinternal IT resources, organizational, and exter-nal IT consultants; the other two both camefrom network orientation After examining theitems in the extracted components, it wasobserved that most items in internal ITresources, organizational, and external IT con-

sultants load onto their a priori scale with the

exception of two, “management involvement”and “management commitment.” These twoitems were originally hypothesized to be part ofthe organizational factor but load onto theinternal IT resources factor (see Table 2) Four

network orientation factor were extractedtogether composing a new factor (see Table 3).Examining this new factor, all items were seen

to be related to customers and the authors

named it customer relations The remaining

items within the original network orientationfactor were all related to suppliers, and so, it

was renamed as supplier relations Table 2

gives a summary of results of factor loadings,and Table 3 gives details of the new extractedcomponent

The findings indicate that there are fivefactors that contribute to the IT adoption envi-ronment in small businesses, and these fivefactors are hypothesized to be directly andpositively related to a successful implementa-tion outcome The extracted five factors explain

54.75 percent of the variance, which, according

to Kline (1994), is satisfactory for social

sci-ences studies as it is 60 percent or less Table 4

gives details of the new measurements, and

Figure 4 reflects the revised research model

As the items from this instrument were

derived from previous instruments, it was

nec-essary to test and evaluate the reliability of the

scales and examine the proposed factors The

reliability of each factor was evaluated by

assessing the internal consistency of the items

within each factor using Cronbach’s alpha The

results show the reliability values (see Table 5)

range between 0.70 and 0.87, which indicate

their internal consistency is reliable within each

scale (Cronbach 1951; Nunnally 1978) The test

for common method variance was conducted

on the five extracted factors using Pearson relation matrix The results indicated that mul-ticollinearity did not seem to be present in thesample, as all correlation coefficient values areless than 0.7 (Hair et al 2005)

cor-Model Validation and Hypothesis TestsFigure 4 illustrates a revised conceptualmodel based on the factor analysis results (seeTable 2) Structural equation modeling wasemployed to test the hypotheses, and Table 6reports its results The goodness of fit indices forthe revised model (model 2) are robust Thechi-square value is 6.16 with a significance of

p = 162 The chi-square degrees of freedom

ratio value of less than 2 (χ2/df = 1.23) is

con-sidered to show a very good fit (Marcoulides and

Table 1 Descriptive Information of the Developed Instrument

Items

information are exchanged withinand throughout the organization

Management and staff training,development, and contribution

Özgener and I˙raz (2006);Payton and Zahay (2005);Thong, Yap, and Raman(1996) derived from Kirton(1976)

Network

Orientation

the suppliers, business partners,and customers are developedfrom trust, shared benefits, andinvestment

Clarkson (1998) derived fromKohli, Jaworski, and Kumar(1993)

External IT

Consultants

and software vendors are usedand encouraged in terms of ease

of access and usefulness to theorganization

Thong, Yap, and Raman (1996)

Internal IT

Resources

knowledgeable with respect tothe technical application andbusiness functions within theorganization, as well as the ITinvestment and acquisition

Caldeira and Ward (2002)Özgener and I˙raz (2006)

Caldeira and Ward (2002);Payton and Zahay (2005)

IT, information technology

Hershberger 1997) This is supported by other

strong fit indices (comparative fit index = 0.984,

Tucker Lewis Index = 0.935, normal fit index =

0.972, root mean square error of approximation

model (Tabachnick and Fidell 2007)

In Table 6, the original model (model 1) alsoshows a reasonable fit with chi-square value of

10.52 but it is significant (p = 006), indicating

the fit is not as good The indices also show astrong fit but not as good as the revised model

In addition, the value of the RMSEA is too high

Table 2

Extraction method: principal component analysis

Rotation method: varimax with Kaiser normalization

aRotation converged in eight iterations

bVariable explained in percentage