Factors Affecting Information Communication Technology Acceptance in Public Organizations in Saudi...

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investing in technology projects at analarming rate, and the failure rateassociated with this investment call for theneed to investigate on this issue is evenmore critical Krigsman [9] affirms theworldwide cost of information technologyprojects failure over $6.2 trillion. Recentdevelopments in public technology haveheightened the need for study of thetechnology adoption factors. It isbecoming increasingly difficult to ignorethe factors cause the adoption failures inthe public organization and the lowproduction of the civil workers [10].

Although ICT acceptance is rarely themotivation for public workers in SaudiArabia, it is an essential activity for manyworkers. However, little is known about

public worker’s behaviours and their

preferences. This study will investigateacceptance factors of public workers andwill profile worker preferences.Organizations that target ICT can benefitfrom the understanding of employee’sbehaviour, and can gain advantages overthose organizations that are lessknowledgeable about their user.

Many researchers [11] [12] [13] [14]have argued research on how organizationsmanage problems associated withtechnology and e-services acceptance

needs to be undertaken before theassociation between the factors affectingthe technology acceptance, use and finally,the adoption of the e-services. Acommonly observed phenomenon, in e-services acceptance and adoption in SaudiArabia and developing countries, is thatSaudis seems apprehensive to accepttechnology [15]. Some studies had anemphasis for the need of direct measure of the effec t the social norm and culture onthe acceptance and the adoption of e-transactions in governments organizationsin Saudi Arabia [12] [16]. Richardsonstates one of the main streams of researchis the explanation and prediction of ICTadoption in the developing countries [17].

Turner, Kitchenham, Brereton,Charters [18] and Budgen [18] said thatTAM proposed in 1989 as a means of predicting technology usage, is thesuperlative tool that demonstrates

technology acceptance [19]. Dasgupta,Granger and Teo and McGarry emphasisthat many TAM studies generate diversehint’s base on the empirical facts,Inconsistent finding’s overflow in terms of

the direction and the scale of theassassination between TAM variables [20].Other studies showed unreliableassociations. Teo [21] and Ahmad et al,.[5] argued that using predicted use as analternative of actual use of ICT isdeteriorating TAM studies.

Lee, Kazor and Larsen [22] andYousafzai, Foxall and Pallister [23]conducted a meta-analysis of TAM andfound that one of the major problems withTAM research was that scholars wereperforming replication studies that providevery little incremental advancement to the

literature. Researchers were not reallyexpanding TAM. Lee et al,. [22] noted thatmany scholars felt that the concept of a"cumulative tradition" was carried too farin all the repetitious studies of TAM,because the model had become an inhibitorof more advanced theories of ICT use.

Acceptance of technology innovationsfor communication needs and factors thatinfluence the acceptance, and adoptionhave been studied for decades. Thetheoretical frameworks that were used to

inform the studies include the diffusion of innovation theory, the expectancy-valuemodel, and the technology acceptancemodel. The word ‘acceptance’ has beenused by different authors in differentmeanings and context. As a matter of fact,the expression does not have any unique orspecific description in literature. TAM hasdefined acceptance as user’s decisionabout how and when to use technology[24].

The theory of planned behaviour Ajzen[25] which developed out of the theory of

reasoned action Ajzen and Fishbein [26];Fishbein and Ajzen [27] [28], the model of readiness for organizational change(MROC) Holt, Armenakis, Feild andHarris [29] and TAM Davis, Bagozzi, andWarshaw [30] provide the foundation of the model which is integrated in thisdissertation into the proposed theoreticalmodel.

(IJCSIS) International Journal of Computer Science and Information Security,

Vol. 10, No. 2, February 2012

119 http://sites.google.com/site/ijcsis/

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The study of people's behaviour to ICTapplication has been a vital issue in ICTstudy in ICT research since the 1980s. Thetheoretical foundation for the study of whether a person is willing to use atechnology comes from research onadoption and diffusion [31]. Research inthis area has continued to develop over thedecades producing other theories includingthe theory of planned behaviour Mathieson[32] [33], social cognitive theory [34]andTAM [35] [24] [30] [36].

TPB has been used successfully forprediction purposes in various researchareas, including the use of structuredinterview techniques for selectionpurposes, the forecast of managers'personal motivation to enhance their ownproficiencies after receiving feedback,

readiness for organizational changeJimmieson, Peach and White [37]technology adoption, intent towardparticipating in a participation program[38].

The stated purpose of TAM is to"provide an explanation of thedeterminants of computer acceptance thatis general, capable of explaining userbehaviour across a broad range of end-usercomputing technologies and userpopulations, while at the same time being

both parsimonious and theoretically justified" [35]. It assumes rationalitywithin the decision-making process.Studies have provided empirical supportfor TAM [39]. TAM also comparesfavourably with other technologyacceptance theories [32]. Taylor and Todd[33] affirm that TAM customarilyannotates about forty percent of thediscrepancy in a persons' intentions toemploy the ICT and the true usage of it.

TAM proposes that the technology useis motivated by persons’ attitude toward

using the it, which is a function of theirbeliefs about using the technology and anevaluation of the value of actually using it.This stands on ''the cost-benefit paradigmfrom behavioural decision theory'' [24]p:321, which state that a person behaviouris based on his or her self-tradeoffsbetween the effort to performance a work and the cost of this action. Therefore,

TAM emphasizes that human will use atechnology if the reimbursement of doingso overshadowed the effort required to useit [24].

Among the behaviours commonlymeasured are: system usage [40], and usersatisfaction [41]. Some researchers havestudied both of these dimensions as acomposite [42]. User satisfaction actuallyrepresents a cognitive and affectiveoutcome that is less tangible in terms of classification as behaviour. Al-Gahtani andKing [43] came up to the conclusion thatICT usage is an accurate measurement of ICT acceptance.

The intention to use ICT depend on thebehaviour of actual use of it, sinceindividuals, perform as they planned to, so

long as they have control over theiractions. Sequentially, the attitude to useICT applications depend on thebehavioural intentions to use it. Followingthe logic of the TRA framework, users'attitudes are determined by beliefs aboutthe system and about the consequences of using it.

The model of readiness fororganizational change suggests that(intended and unintended) behaviouraloutcomes are due to intentions (andreactions) concerning those behaviours.Researchers have previously argued that apositive and favourable view towardorganizational change, based on the degreeworkers believe a change is likely tocontain positive beneficial implications forthem, and the organization will lead tobetter reactions to change [44]. In turn,these intentions and reactions are linkedwith the attitude called readiness forchange, which has been defined innumerous ways [29]. This attitude is, inturn, believed to be due to various change-related beliefs.

Several attempts have been made todefine change recipients' beliefs [29]. Inaddition, these change recipients' beliefsare related to various antecedents that fitwithin the aforementioned typology.Subjective norms play a crucial role. Theproposition that subjective norms helppredict intentions relating to supporting




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The quality of the output, particularlythe more precise and up-to-date theinformation provided, the greater the PU.In addition, the greater the ease of ICTaccessibility, comprehension, and analysis,the greater is the PU [48]. Goodwin [49]opined that perceived usefulness dependson the usability and the counting use of thetechnology, represented by PEU.Mathieson [32] and Szajna [47] reportedthat PEU accounts for a significant portionof the variance in PU. In TAM II, Henceaccording to Venkatesh and Davis [36]“PU’s significant antecedents haveincluded subjective norm, image, jobrelevance, output quality, and resultdemonstrability.” Li [50] discusses ICTadoption from the effects of the group.Herding occurs when an organizationadopts an ICT based on a “me too”

attitude. In many cases, the adoption of technology is in response to not being left

behind, the “herding effect.” The herdingeffect results when the first bureau adoptsa technology, and subsequent users adoptthe technology in order to minimize therisk of choosing an alternative technology.In situations of incompatible ICT abouttechnologies, committing to a technologyis more advantageous to the agency earlierrather than later, due to the commitmentpower when the choice is irreversible [51].

This herding behaviour may appearbecause of information flow, which occurswhen individuals of sound minds begin toignore their own findings and insteadcontinue in the footsteps of previousdecision makers [50]. In addition toinformational cascading, Li [50] also notesthat positive network feedback can causeleading technology to grow moredominant. They usually result in positivenetwork externalities that make an ICTadopter’s return positively correlated withthe number of adopters who have alreadycommitted themselves to the sametechnology. Therefore, herding is rewardedby increasing the payoffs of those ICTadopters who associated themselves withthe majority.

As technology advances, organizationsadopt newer tasks. This can result to thechange of the nature of work in theorganization. For instance, tasks that were

done manually are now done automaticallywith the aid of machines. Mostorganizations increase the readiness tochange because the nature of work ischanging [52] [53] [54].

Madsen, Miller and John [55] definechange as a transition from a stage toanother, and that existing structures arebroken down to create new ones.According to Armenakis et al,. [44], thereare certain features of a positive work environment; which generally tend toinclude both workplace as well asindividuals. These thus encourage positivebehaviours and attitudes for theorganizational readiness for change.

One of the most significant currentdiscussions in commitment to change is

work-related attitudes and behaviours.Perceived risk and habit is an importantcomponent in the resistance to userresistance to a new technology [56]. Inaddition, Mowday, Steers and Porter [57]argued that a relationship exists between job nature and affective organizationcommitment, is described as themotivation and desire of an employee tonot only continue working for anorganization but also work to his fullpotential to help achieve the saidorganizations’ goals [57] p:225.

As already discussed, technologicaladvancements lead to the need for changein the organization. Technology alsoinfluences the nature of work, for instance,from manual to automatic tasks. Adoptingnew technologies is mandatory forimproved performance and retaining acompetitive advantage for the organization[58]. However, the organizationalreadiness for change will depend on first,the availability of resources to adapt newtechnologies; and second the employees’ability to coexist with the introduced

technology [59]. New technologiesnecessitate the need for knowledge, skills,and expertise on how to use them. Whenemployees are unfamiliar with the newtechnology, intimidation may occur, andhence resistance towards change.

The organizational readiness to changecan therefore be achieved depending on




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MROC Individual Differences Technology

User Believes

H4b

TAM

Perceived

Ease of Use

Perceived

Usefulness

Behavioural

Intention

“Attitude tochange”

Use Behaviour Person actualusage of the

technology and

continues to use

System characters

Individual Differences(Valance, Principle

Support, Appreciation)H7a & b, H6 a & b and

H5 a & b

Social Influence

Facilitating condition

Subjective norm

Volunteer

Training

Work

Nature

ICT

Usage

H4a

H3

H1a

H1b

H2a

H2b

H1

Figure -1 The Research model

H1a: Subjective norms mediate therelationship between Attitude tochange and BI.

H1b: Perceived voluntariness mediatethe relationship between Attitude tochange and BI.

H2: Usage “performance” positively

and directly influences the intention tochange.

H2a: Training mediates the relationshipbetween usage and attitude to change.

H2b: The nature of work mediates therelationship between usage and attitudeto change.

H3: Usage mediates the relationship

between Perceived usefulness andattitude.

H4: Perceived ease of use positivelyand directly influences Perceivedusefulness.

H4a: Usage mediates the relationshipbetween Perceived ease of use andattitude.

H5a: Principal Support positively anddirectly influences perceived ease of use.

H5b: Principal Support positively and

directly influences perceivedusefulness.

H6a: Valence negatively and directlyinfluences perceived usefulness.

H6b: Valence negatively and directlyinfluences perceived ease of use.

H7a: Appropriateness positively anddirectly influences perceived ease of use.

H7b: Appropriateness positively anddirectly influences perceivedusefulness.

ICT acceptance is rarely the motivation forpublic workers in Saudi Arabia; it is anessential activity for many workers. However,

little is known about public worker’sbehaviours and their preferences to use ICT.This study will investigate acceptance factorsof public worker and will profile workerpreferences. Organizations that target ICT can

benefit from the understanding of employee’sbehaviour, and can gain advantages over thoseorganizations that are less knowledgeableabout their user.

The study aims to answer the mainresearch question “what factors affect

employee behaviour to accept and adopt ICTin the Saudi public industries?” and to whatextend the performance affect the ICTacceptance and adoption.




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III. METHODOLOGY AND FRAMEWORK

For this paper, the MROC presented byHolt and colleagues [29] was combined withcomponents of TAM III [72], the thirditeration of TAM [24]. The theoretical

framework proposed specifies potentialrelationships among variables from both TAMand the model of organizational readiness of change with other factors from the literaturesubjective norm and volunteer Figure 1. Forthe theoretical model, the MROC serves as thetemplate and technology acceptance variablesare included into the model. The change-related beliefs chosen for this research consistof nine interrelated variables. The three beliefsreferred to as the organizational changerecipients' beliefs (OCRBs) include:appropriateness, "is this the right change";principal support, "has everyone bought into

making the change happen"; valence, "what isin it for me" and commitment to change [73][53]. In addition to the three change-relatedbeliefs, the four primary beliefs of TAM,seeming easiness in terms of the usage,seeming usability, are also taken into account.

In addition to four factors which are natureof work, training, perceived voluntariness andsubjective norm as moderators. Thesevariables are not explained in this sectionsince each one is focused on in greater detailin the sections that follow within this literature

review. It is proposed that these beliefs are theresult of sense making as it concerns anynumber of antecedents that could be related tothe organizational change involvingtechnology.

Finally, current usage the discrepancybetween the desired and the currentperformance levels can trigger the call forchange in the organizations. Specifically, if the current performance is faced withperceived dissatisfaction, the organizationalconstruct suggests that changes occur in theorganization [59]. Yousafzai, et al,. [23] arguethat the variance in the type of method,subject, technology and utilization aretypically prone to moderating the links thathave been hypothesized.

IV. PARTICIPANTS AND PROCEDURES

Participants were 757 employees who areworking at public organization in Saudi

Arabia. A letter of consent was obtained, andthe questionnaires were issued. Theparticipants in this study were 100% male,majorities 46% of them are graduated. The agegroup between 30- 34 is the majorities of therespondents. The survey would be highlyinfluenced by supervisors with incomebetween SR 6000 -7999. Most of therespondents have no training and almost 20%of the trainees got their training in thedepartment for less than one week.

Before issuing the questionnaire, a brief explanation (verbal introduction) about thepurpose of visit, objective of the study andhow to fill the questionnaire were allinstructed to the employees. Questionnaire wastranslated to Arabic and back translated againto English. All the questionnaires were issued,filled and collected on the day of the visit or

sent by mail. After that the questionnaires,data was typed in manually into excel file,then transfer to PASW 18.0 file format andcoded.

A. Data analysis

The research at hand makes use of structural equation modelling (SEM), in orderto construct a framework that showcases thelinks in terms of the four variables that havebeen included in this research. These variablesinclude intent to use, behaviour towards usingtechnology, seeming utility, and seeming

easiness in terms of use. Data was gathered viaa survey questionnaire which consisted of queries regarding respondents attribute andvarious things for every single one of the fourvariables included in the research. SEM waspicked up for the research and not a regressionanalysis. This is because it as a parallelanalysis running which allows an assessmentof links in terms of the different variablesincluded along with the errors and issues thatevery variable has, which are to be measuredindependently, and this is not possible with theregression analysis.

AMOS (Analysis of MOment Structures)was used as the data analysis tool. AMOS isthe more recent analysis package which isuser-friendly graphical interface, and it hasgained popularity as a much more easy mannerof adding specifications to structuredimensions. AMOS additionally has aninterface an alternate option known as BASIC[74].




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The sample was a convenience sample of atleast 200 of civic employees who work inwestern Saudi Arabia. A self-administeredsurvey was used to collect data at Medina,Jeddah, and Yanbu. The study was conductedat different organization and ministries officesto reduce bias.

The instrument for data collection wasdeveloped based on the review of the literatureon technology acceptance studies changebehaviour and TAM I, TAM II and TAM III,Model of organization readiness of change.

Steps which involved SEM are as follows:Data was checked to see whether there wasanything missing or left over. After this, thedata was validated and discriminate andconvergent validities of the information athand was developed. After this the problems

associated with SEM itself were looked into.For instance, in order to make sure thatnormality existed within the data, [74]suggested the view of kurtosis indices alongwith skews shouldn’t go beyond the value of 10.0 and 3.0 respectively. For the results fromSEM to be reliable it is important that the sizeof the sample be kept at 100-150 [75]. Thesize of the sample within the current study at

hand has been kept at 429 in order to ensurethat it fall within the specified requirements.

B. Result

The analyses within the current section areof a statistical nature and look into the

descriptive statistics for the purpose of measuring objective and examining how validthe measurement is within the scope of thecurrent study. Subsequent to this, the model istested in terms of the various fit indices andpreviously developed hypotheses.

C. Descriptive Statistics

Table-1 contains all constructs fordescriptive statistics. The means lie above3.00; however, this is not true for the principlesupport which at 2.7 holds a different mean.Standard deviations lie within the range of

0.77-1.24; this shows that the mean has arelatively narrow spread around it. In terms of the Skew we can see that the index liesbetween -0.6 - 2.0, along with which theKurtosis also exhibited an index which rangedfrom -0.1 – 4.6. The data is normal in termsof the SEM as per the recommendations putforth by [74].

Table -1 Descriptive Statistics of the Study Constructs

Variables Item Mean ST.D Skewness Kurtosis

Principle support 4 2.68 0.77 -0.9 0.1Motivation Valance 4 4.02 1.03 -0.6 -0.4

Appreciation 5 4.24 0.99 -1.3 -0.9

Perceive Ease of Use 4 4.22 1.09 -0.4 -1.1

Perceive Usefulness 5 4.05 0.82 -1.2 1.6

Attitude to change 4 3.70 0.80 -2.0 5.5

Subjective Norm 2 4.11 0.83 -2.0 4.6

Volunteer 4 3.81 1.00 -1.1 1.3

Behaviour Intention 5 3.90 1.08 -1.0 0.4

D. Convergent Validity

In assessing for convergent validity of themeasurement items, the item reliability of eachmeasure, composite reliability of each constructs,and the average variance extracted are examined.The item reliability of an item was assessed by itsfactor loading onto the underlying construct. In thisstudy, the composite reliability was used instead of the Cronbach’s alpha because the latter tends tounderstate reliability [75]. For composite reliabilityto be adequate, a value of 0.70 and higher was

recommended [76]. The third indicator of convergent validity, average variance extracted, is a

measure of the overall amount of variance that isattributed to the construct in relation to the amountof variance attributable to measurement error [77].Convergent validity is judged to be adequate whenaverage variance extracted equals or exceeds 0.50.From Table-2, the average variance extracted andcomposite reliability met the recommendedguidelines, indicating that the convergent validityfor the proposed items and constructs in this studyare adequate.




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Table – 2 Results for the Measurement Model

Latent

VariablesItem

Factor

loading

Ave. Variance

extracted (> .50)*

Composite

Reliability (> .70)*

Principle support

Ps1Ps2Ps3Ps4

0.70.80.70.5

0.6 0.7

Motivation ValanceMv1Mv2Mv3Mv4

2.20.60.50.5

0.6 0.7

Appreciation

Ap1Ap2Ap3Ap4

Ap5

1.80.80.80.7

0.6

0.7 0.7

Perceive Ease of Use

PEU1PEU2PEU3PEU4

2.30.70.50.3

0.7 0.8

Perceive Usefulness

PU1PU2PU3PU4PU5

2.50.90.60.50.3

0.7 0.7

Attitude to Change

At1At2At3

At4

2.70.70.5

0.3

0.7 0.8

Subjective NormSn1Sn2

1.80.9

0.5 0.9

Volunteer

Vl1Vl2Vl3Vl4

2.40.70.50.3

0.7 0.8

Behaviour Intention

Bi1Bi2Bi3Bi4Bi5

2.30.80.80.50.3

0.7 0.7

E. Test of the Measurement Model FitThe model of the research has been

developed through the structural equationmodal approach. The AMOS was used tocreate it [78]. Numerous different indices havebeen implemented in this research. Hair et al.[75] was of the view that utilizing fit indicesthat stemmed from different sets was a goodidea. The ones used were absolute fit indices

and gauged the extent of the inconsistency interms of the observed and implied covariance

matrices. The ( ) statistic is used byresearchers along with the SRMR, thestandardized root mean residual, which is notused within this research. Parsimoniousindices are closer to the indices that areabsolute fit, however, they are differentbecause they account for the complexity of the




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model. The RMSEA the room of mean squareerror of approximation is used in greatquantities across the research spectrum as aparsimonious fit index and P-CLOSE.

The third table reveals the limit of what isacceptable as a fit along with the fit indicesfor the projected model for research within thestudy at hand. The values were up to the levelsthat were recommended in terms of theacceptable fit. In terms of the χ2 it was seen as

highly sensitive to any augmentation in termsof the size of the sample along with theamount of variables that was to be examined[75]. This is the reason that the ratio of χ2 to

its extent of liberty to be calculated ( )was implemented, through a ratio of 3 orsmaller, which was an indication that anacceptable fit existed in terms of the sampledata, and the model developed through thehypothesis [79].

Table - 3 Fit Indices for the Research Model

Model Fit Indices ValueRecommended

Guide linesReferences

(

) 1.6 < 0.3 Kline and Littel 2010; Hair, 2010

CFI 0.9 > 0.9 McDonald and Ho, 2002; Hair, 2010

GFI 0.9 > 0.9 Klem, 2000; McDonald and Ho, 2002; Hair, 2010REMSA 0.04 < 0.05 McDonald and Ho, 2002

PCLOSE 0.81 > 0.5 Klem, 2000; Hair, 2010

F. Test of Structural Model

Overall, eight hypotheses were supportedby the data. At this point, of the assessment of the hypothesized path suggested in thestructure model Figure 2, in this step of theprocedure the researcher checks, whether thepath coefficients are significant and the same

direction assumes in the model. Also themediators are inspected and evaluated in thesame way based on the literature which therelationship has been constructed.Significantly, it is to check the affect of thenew variables on the model. In general fifteenhypothesizes were recognized in the model forthe study. Table-4 illustrates the standardizedregression weight of the model hypothesizes inFigure 2.

Table-4 shows appreciation and motivationvalance affected the PEF negatively, on theother hand, PS significantly affects the PEFpositively. PU found to be predicted byappreciation and MV negatively, andpositively with PS. Overall, PEF and PU havea significant direct positive relationship. PEUhas a positive association with current usage

which opposite to the association between PUand current usage. Current usage with theassociation to the intent of using along withthe intent of using in link to BI was found hasno effect or no significant effect. Themediators of the model were found to arbitratethe correlation.

Table- 4 Hypothesis Testing Results

Hypotheses PathStd Regr.

weightResult

H7a PEU Ap -0.29 Not supported

H7b PU Ap 0.20 Supported

H6b PEU Mv -0.78 Not supported

H6a PU Mv 0.36 Supported

H5b PEU PS 1.46 Supported

H5a PU PS -0.83 Not supported




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.

.

U S A G E

P E O U

.

A p p

.

o r k

B . I n t

l

T r a i n i n g

1.46

0.31

-1.01

0.81-0.78

0.36

0.2

-0.29

-0.83

0.68

0.03-0.191.22

-0.02

0.20

H4 PU PEU 1.22 Supported

H4a Usage PEU -1.01 Not supported

H3 Usage PU 0.81 Supported

H2 Att. B Usage -0.19 Not supported

H2a

Att. B Training

0.20 SupportedTraining Usage

H2b Att. B Work

-0.02 Not supportedWork Usage

H1 B I Att. B 0.03 Not supported

H1a B I SN

0.31 SupportedB I Att. B

H1b B I Vol

0.68B I Att. B Supported

V. DISCUSSION

This research was trying to: (1) forecastfactors affecting ICT in clearing up thebehaviour of accepting technology in a

developing Arab nation, especially SaudiArabia, (2) expand the TAM to expand on howICT is used behaviour wise, along with (3)scrutinize the part played by norm, volunteer,training time and work type as mediators of the ICT acceptance and adoption in terms of elaborating on the behaviour linked with ICTutilization. For the purpose of addressing theobjectives of the study the researcher hasmade used of a strategy for research as has

been outlined in the upcoming seconds. Thestudy worked by looking into how applicableantecedents of belief variables of (MORC) onTAM Technology user believes. Then thestudy examined the affect of current usage onTAM model. Finally, the study examined the

influence of training and work type on therelationship between current usage andattitude behaviour. Moreover, the studyexplored the affect of norm and volunteer onthe association between attitude behaviour andbehaviour intention to use.

Andam, [80] proclaim that with theappreciation in ICT, in particular in publicorganization, it has a positive influence.

Figure -2 CFA Of the Research Model




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Unexpectedly, the Table-4 shows therelationship between perceive ease of use, andappreciation is significantly negatively. Thisdue to the motivation method explains howindividuals’ goals influence their efforts.

Davis [24]and Venkatesh [40] argue thatappreciation is the increasing value of the useof ICT. As well, it is the ways individualsappreciate the use of ICT. After looking at theprincipal of appreciation, it is important toconsider reviewing perceive usefulness.Perceive usefulness helps to determine thereason why people in an organization accept orreject information technology. Eventually, thisresearch renders a similar result as Davis [24]and Venkatesh [40]claimed, Table-4 showsthat appreciation has a direct positive relationwith perceive usefulness.

The definition of valance is an individualstrength of performance for a reward. Thenexpectance is the probabilities of a particularaction leading to a desired rewardinstrumentality indicate individuals estimatethat performance will result in achieving thereward. This means that if an individual has aparticular goal to achieve, the individual mustproduce certain behaviour in order to achievethis goal. Individuals also need to weigh thelike hood that various behaviours will help inachieving the desired goals. If it needs certainbehaviour as an expectation of more success,

individuals will, then prefer a new particularbehaviour [81].

The table surprisingly shows direct positiverelationship between motivation valances andperceive usefulness. For the purpose of developing better comprehension in terms of the issue of valance, the expectancy, describeat time it is the performance rewardproverbially. The expectancy theory gives theprobability the performance that will lead to adesired goal or outcome [82].

To some extent, motivation becomes

valance, instrumentality and expectancy. Thethree factors in the expectancy model can existin an infinite number of contributionsdepending on the range of valance and thedegree of expectancy and instrumentality. Theachievement of high positive valance comesout, when there is a combination that producesa high motivation. When the three values are

high and produce a high motivation value, thevalance will then be a positive value [83].

On evaluating valance as a way of motivating employees, the research found outthat valance does not take in a specific meansof motivation. There are various ways of motivation valance [84]. This means thatmotivation does not come from the activityalone, but from other external factors [85][86]. This study supported the valanceinstrumentality expectance claim of the zeroeffects or negative effect as Table-4 illustratesthe direct negative relationship betweenmotivation valance and perceive ease of use.

Davis [24] and Venkatesh [40] notice aftermaking a careful observation of both principalsupport and perceive ease of use, we can seethat they are all deriving to the ICT

implementation. There is an essence of improving the ICT systems in order to providean ease to the users. With the ease, theorganization finds that implementation of ICTis enhanced [40]. In fact, in this study theprinciple support has a direct significantpositive effect on perceive ease of use asTable-4 shows. The relationship in this studyis supported.

Researches affirm that there is the urge of learning the new ICT within the employees;yet, there is lack of commitment from the topmanagement [87]. At such a situation, themanagement has not acknowledged theimportance of ICT causing the organizationmember’s reluctance as well. With theprincipal of support such, an organizationrequires to establish its weakness towardsaccepting the new information system in orderto come up with good implementation of ICT[87].

Yet Table-4 shows that principle support isnegatively affects the perceive usefulness,which confirm what Bjorn and Fathul [1]showed in their study that the lack of leaders

or high officials support contributes to sixtyper cent of e-government initiative’s failure.

Perceive ease of use determines individualbehaviour intention to use informationtechnology. Perceive ease of use falls under abroad topic called TAM. This is a theoreticalframework that outlines the manner in whichusers can acknowledge a particulartechnology. The theory goes on to state that




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the presentation of a new technology to theusers, there are numerous elements that canimpact their decision making process in termsof the time and manner of their usage [88].

PEU has shown a direct positive significanteffect on perceived usefulness in many studies[89]. After all, this study came up with thesame output of the old studies which isillustrated in Table-4. The level of significantof regression weight is very low.

Rogers confirmed that perceive ease of useis not only the perception of inform a systemby people but also is the extent where theinnovation has been seen by the user as easy tounderstand, use and learn [31]. In contrary, thestudy shows Table-4, the association betweencurrent usage “performances” and perceiveease of use, is direct negative relationship.

This confirms the most recently study done byNagli, Rahmat, Samsudin, Hamid, Ramli, MDZaini and Jusoff [90] which confirm thatperceive ease of use has no significant intoday operation Table-4.

On the other hand, the table shows therelationship between perceive usefulness andusage is a direct positive relation, with highlevel of significant regression weight. Theoutcome of the study affirms the claim of Nagli et al,. [90] that perceive usefulness has adirect positive relationship with performanceand current usage.

Part of the study is to provide how currentusage positively affects the attitude to change.The increasing and continuous use of ICTaffects the attitude to change positively.

Primarily, this study shows Table-4 thatcurrent performance is negatively affects theattitude behaviour with a very low level of significant. Due to Change management hasbecome critical in the modern world of business. All organizations are lookingforward to manage change in order to achieve

their objectives. Even if change is importantfor the improvement of the organizationperformance, employees at time have resistedchange. The reason of change resistanceamong the employees is the fear of losing their job positions. Not all organization memberswill take this positively.

Some organization members may not becomputer literate and will think the

introduction of computers will threaten their job since they can use the system [91]. AlsoWinters, Chudoba, and Gutek and Teo, Leeand Chai indicate that one’s attitude has aconsiderable amount of impact in terms of being a forecaster of how some technologywould be used if the user is given the libertyto choose if he should or shouldn’t usecomputers [92] [93].

Management may not fully grasp the actuallevel of expertise required for organizationalmembers use the technology effectively. Assuch, they often underestimate the trainingrequired and the time that it will take inimplementing the new ICT [36].

The organization has to provide training toits employees about the use of informationsystems. Besides that, the organization as well

is required to train the organization membersabout ICT at large. Given the opportunity tolearn about information systems (IS) and ICTat large, the members will develop interest [5].

Attitude to change is not always positive.To the organization, change is something vital

but the employee’s change is a threat. Many at

times the organizations may be glad tointroduce change to their daily servicesactivities but organization members willalways be ready to resist the ICT applications.Theory of planned behaviour is significant forthe understanding of these variables. Theoryof planned behaviour specifies the natures of relation between believe and attitude.Individuals’ evaluations of attitudes towardsbehaviour usually are determined byaccessible believes about behaviour [94].

A belief is basically one’s own concept of

what will most likely going to happen i.e. acertain act or behaviour will lead to a specificresult. To be specific, the assessment of aresult is a part and parcel to the behaviour andis positively linked to someone’s subjectivelikelihood that produces the outcome in

question [27]. Davis confirmed the relationbetween attitude and behaviour intention as adirect positive relationship [24], this study didnot confirm the hypotheses as the table showspositive non significant weight relationshipwith the level of significant is 0.7.

The stated purpose of TAM is to "providean explanation of the determinants of computer acceptance that is general, capable




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of explaining user behaviour across a broadrange of end-user computing technologies anduser populations, while at the same time beingboth parsimonious and theoretically justified"[35]. It assumes rationality within thedecision-making process. Studies haveprovided empirical support for TAM [39].

Subjective Norm in relation to aninnovation was hypothesized to influencesignificantly the user’s behavioural intent toadopt the innovation. The study showssubjective norm mediates the relationshipbetween attitude and behaviour intention, eventhough the influence is not significant p levelis smaller than 0.08 as according to Hair [75].

Perceived voluntariness towards aninnovation was hypothesized to influencesignificantly the user’s behavioural intent to

adopt that innovation. The table shows thatvolunteer mediate the relation between attitudeand behaviour the direct path has weight 0.81,and P-level 0.3, which is significant tomediate the relationship according to Hair[75].

The table shows that training mediate therelationship between current usage andattitude behaviour the direct path is 0.14 forthe relationship between training and attitudebehaviour, and it is negative relation betweenusage and attitude behaviour. According toHair [75] the value of a path must be greaterthan 0.08 in order to be significant. The studyconcludes that Table-4 the nature of work didnot mediate the relationship between usageand attitude with a significant level of 0.9.

VI. IMPLICATION FOR THE THEORY

This study demonstrated association amongTAM variables. Yet, It could be observed fromthe research analysis that ICT usage hasaffected the relationship between TAMvariables.

Second, the research technology beliefsPEOU and PU have an opposite impact on theICT usage. The PEOU has a direct negativeeffect on usage (-1.1). The PU effect on usageis -0.8. Therefore, PU is a deciding factor onICT acceptance. What is less clear is if thecurrent usage has a motivation effect onattitude behaviour due to a low level of usageand training.

Third, this study expands the understandingof TAM, and shows that it is very applicableto Arab countries (Saudi Arabia). However,this argument needs more investigation andexamination.

Fourth, the research examined therelationship between TAM behaviouralfactors. The analysis revealed a prototype thatis related to the Saudi public industries.

Fifth, Lin and Lee [46]mention thatsubjective norm moderate ICT acceptance.Also, Quaddus, Xu and Hoque [95] noted thatthat perceived volunteer influence the ICTusage. This study confirms this allegation andcomes to similar result.

Sixth, this study found that traininginsignificantly increase employee readiness

for change, this finding support Lan and Cayer[58] and Davis and Bostrom [96] argumentwith insignificant influence, due to 80 % of the respondents had no training.

Seventh, this research found that currentusage has an insignificant negative impact onthe attitude behaviour, which validateManagement Hub argument that some of theemployees are not familiar in using ICT andmay think that such change may disturb theirwork.

Finally, work type did not moderate the

relationship between usage and attitudebehaviour, this contrasting Al-Adwani [56]and Modway, Steers and Porter [57] argumentthat a relationship exists between job natureand affective attitude to change.

VII. IMPLICATION FOR THEORGANIZATION

The objectives of this investigation areknowledge the typologies of employees andtheir preferences of ICT acceptance andadoption. And to identify the factors behind

the ICT acceptance and adoption failure. Sothat the public organizations have upper handover ICT acceptance and adoption failure inthe future.

In this part the study will provide someunderstanding of the obstacles to ICT adoptionin GO’s in Saudi Arabia. Seven important

issues were identified in the survey’s out-come given as follows: At the first, the most




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important concern for the public organizationto deal with is had to do with the question of:will the worker be able to use the new system?Are they prepared to use it? Have they had thesuitable training? The employee’s willingness

and the organizations’ readiness were

observed to be near to the ground indeveloping countries. These two issues impactsignificantly the ICT acceptance and soonafter the adoption of ICT. The researchinstrument showed that approximately 80 % of the workers had no training.

Therefore, employees should be trained onthe way the system works on the parts that areassociated with their jobs. In a nutshell,achieving a close understanding into the howthe whole system work is imperative than whatthe user needs as a part.

Second, the resistance of change issue, thismatter related to the low e-readiness amongemployees. Research affirms that workers failto use the new ICT system due to the lack of training, which cause workers to oppose theICT applications. Consequently, providing abetter solution for the ICT applications usesis a necessity to reduce the resistance.

Third issue is language barrier associatedwith the new technologies. According to theundersecretary of the Ministry of Commerce,language is an important barrier to any e-systems where the majority of people speak Arabic.

Fourth, skilled workers are required tolevel up the ICT Knowledge. According to thesurvey less educated workers have low ICTacceptance. It was also reported by theofficials that absence of adequate know-howhinders governments to adopt and start ICT-based projects.

Fifth, Porter and Lawler [84] propose theconstruction of the job environment keeping inmind the objective of internal and external

rewards to create fulfilment work and could befollowed by the growth of the job, which willmake the job more motivating. It is moreinteresting and thus become more satisfyingfundamentally. Reward in the mean of highsalary which, consequently provides theemployees’ a motivation to work.

Sixth, according to the top administrator of the Ministry of Civil Status, most of the users

of e-government were females because of cultural issues in which women are expectedby custom to stay at home. Due to theirspending long time at home, they will likelyuse the e-services at home frequently for theconvenient sake.

Lastly is the issue of leadership support. Itwas reported by the head of the informationsystems department at the Ministry of Financethat having leadership support plays anessential role in the execution and spreadingof e-government. According to the official,there must be high priority for ICT, and itshould be considered as the major contributorto economy otherwise any importantdevelopment initiatives such as IT educationwill not be paid attention to. Leadershipsupport has great influence on the allocationof resources for technology and e-government

adoption. Furthermore, the undersecretary of the Ministry of Commerce also argued thatleadership and top officials’ commitment toICT is also crucial. Such has the capability of affecting the allocated budget for ICTadoption and development in any organisation.However, the official stated that budgetscannot just be raised to bring about theincrease in the awareness of ICT but someother institutions of government usuallybudgeted for ICT and have their top officialswilling to work hard with their time andenergy devoted to ICT. There are other

organisations with low budget allocation toICT while some such as Ministry of Educationhave a commitment to ICT.

VIII. LIMITATION AND FUTURE STUDY

The findings of this study have someimportant implications. One, TAM extended isvery relevant to a non-western nation wherethere is changing degree of explanatory power.However, more studies are still requiredparticularly when the explanatory power of themodel employed is not as high as TAM.

There is still needs for more investigationof additional probable variables, which likelygive high boast in analysing ICT in terms of the behaviour in different nations, apart fromthe west. Two, TAM extended or UTAUTmodel may be employed to analyse otherbehaviour of ICT. Three, the requirement forfuture inspection in terms of the part thatexperience plays when it comes to acceptance




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modelling for technology, and this was shownby the findings. Therefore, there is room forfuture research, particularly with respect totraining and compensation. Also needed forfuture study is an intensive study of usage as amediating variable. More research designs arelikely to strengthen the insight into theaggregated model. A cross-section of peoplewithin the ICT in government organizationusage context was investigated. Therefore,studies in the future might examine largersubsets of users in relation to pointing out thelimitations and exceptions. Also recommendedfor future research is the longitudinal studieswhich examine the hypothesised associationsas they were open for some time now. Theinclusion of an additional group of antecedentswhich includes being educated about thesystem.

Lastly, findings suggest that the formationof positive attitude of ICT should occur beforethe adoption of technology and as a result,researcher should investigate the trainingeffectiveness.

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