Employee’s Perceptions towards Electronic

European Journal of Scientific Research

ISSN 1450-216X Vol.48 No.2 (2010), pp.169-176

© EuroJournals Publishing, Inc. 2010

http://www.eurojournals.com/ejsr.htm

Employee’s Perceptions towards Electronic

Government in Jordan

Haitham Hmoud Al Shibly

Al Balqa Applied University

E-mail: [email protected]

Ibrahim H.Tadros

Al Balqa Applied University

E-mail: [email protected]

Abstract

This research designed to theoretically address and empirically examine research

issues related to the question of what factors impact electronic government acceptance by

Jordanian employees. Drawing from previous studies, we hypothesized seven constructs

(i.e., System Quality, Information Quality, Perceived Ease of Use, and perceived ease of

use) that may influence an Employee’s acceptance of electronic government. Two hundred

questionnaires were distributed to employees at a municipality in Jordan. Multiple

regressions were used to analyze the data. The results of this study show that System

Quality, Information Quality, and Perceived Ease of Use, all have significant effect on

electronic government acceptance. Practical implications are discussed.

Keywords: Electronic government, Information systems success, Technology acceptance

model, user satisfaction

1. Introduction Electronic government (EG), an Internet based system of information service and information process,

deals with internal government bodies, other government bodies, the businesses and the public (Dijk et

al, 2008). EG turning grade management structure into network management structure is fit for the

virtual, global, knowledge-based digital economy and the human-based notion of social running.

The development of EG is expected to bring about important benefits for public organizations,

which include lower transaction costs (Hamner and Al-Qahtani, 2009), increased responsiveness to

citizens’ needs (Badri and Alshare, 2008), and the facilitation of public involvement in support of

deliberative democracy (Dijk et al, 2008). The momentous potential of EG for enhancing public

service delivery has caused many governments across the globe to commit billions of dollars to its

development. Jordan is no exception to this phenomenon. EG in Jordan is a national program initiated

in September 2000 towards achieving the EG vision by 2005. The vision was that EG would be a

contributor to Jordan's economic and social development by providing access to EG services and

information for everyone in the Kingdom irrespective of location, economic status, IT ability, and

education.

In 2006 the Jordan admitted that the EG project had fallen short of achieving its vision by 2005

and it was admitted that EG was facing immense challenges (Al-Omari and Al-Omari, 2006). Success

stories have been limited to government agencies setting up their informative websites, presumably

Employee’s perceptions towards Electronic Government in Jordan 170

networking a number of government agencies together and offering government employees to IT based

training programs. Jordan deployed a new EG strategy in the year 2006 to achieve actual

transformation and online service by 2009 (MoICT, 2006). Accordingly, a study on factors that

influence the Jordanian employee’s acceptance of EG is timely.

The primary purpose of this research is to analyze and extend knowledge regarding

Influential factors that affect users to accept EG, in the light of technology acceptance model

(TAM), and to develop a model that can be used to analyze user acceptance in the context of

developing economy such as Jordan, furthermore, this research discusses the results of an empirical

investigation into employee perceptions toward EG in Jordan. The rest of the paper is organized into

four sections. In the first section, relevant literature is reviewed and the framework of the study

presented. The second section describes the methodology adapted for the study. The results are

presented and discussed in the third section. The summary of the key findings, implications and

research areas for further inquiry and understanding are presented in the concluding section.

2. Theoretical Background and Research Model Acceptance of a system is a measure of the proclivity to use that system. Without acceptance, there is

no inclination to accommodate and include the system within the management process (Venkatesh and

Davis, 2000).

The successful implementation of information systems (IS) is dependent on the extent to which

such a system is used and eventually adapted by potential users (Venkatesh and Davis, 2003). IS

implementation is not likely to be considered successful if users are unmotivated to use that type of

technology (Venkatesh and Davis, 2000). If users are not willing to accept the information system, it

will not bring full benefits to the organization (Davis, 1989; Venkatesh and Davis, 2000). The more

accepting of a new IS the users are, the more willing they are to make changes in their practices and

use their time and effort to actually start using the new IS (Venkatesh and Davis, 2000).

To predict, explain and increase user acceptance, organizations need to better understand why

people accept or reject IS (Davis et al, 1986). In this regard, researchers have developed and used

various models to understand acceptance of users of IS. Among the different models proposed the

Technology Acceptance Model (TAM) (Davis 1989), adapted from the Theory of Reasoned Action

(TRA) (Venkatesh and Davis, 2003), appears to be the most widely accepted among the information

system researchers (Venkatesh et al. 2003; Wang et al. 2003).

The primary goal of TAM is to predict IS acceptance and diagnose design problems before user

have experience with the new system. TAM suggests that when user encounter new IS technologies the

two main factors influences how and when they will use the system. These two main constructs of

TAM are perceived usefulness (PU) and perceived ease of use (PEOU). Perceived usefulness is defined

as “the degree to which person believes that using a particular system would enhance his or her job

performance” (Davis 1989). Perceived ease of use is defined as “the degree to which a person believes

that using a particular system would be free from efforts” (Davis 1989). TAM proposes that two

particular constructs, that are of primary significance for IS acceptance, perceived usefulness (PU) and

perceived ease of use (PEOU) affect user’s’ attitude towards using the information system. Attitude

directly relates to user’s intention, which will in turn determine usage of the system.

TAM has much strength; including its specific focus on IS usage, the validity and reliability of

instruments, and its parsimony (Venkatesh and Davis, 2000).

While basic constructs of TAM, PU and PEOU, have been considered primary determinants of

individual’s acceptance and use of technology. IS researchers have investigated and replicated these

two constructs and agreed that they are valid in predicting user’s acceptance of various IS systems

(Venkatesh et al 2003). However, few of TAM studies have investigated the impact of system

characteristics as antecedents to ease of use or perceived usefulness (Wixom and Todd, 2005). In their

integration of the technology acceptance literature, Venkatesh et al. (2003) stress the need to extend

this literature by explicitly considering system and information characteristics and the way in which

171 Haitham Hmoud Al Shibly and Ibrahim H.Tadros

they might influence the core beliefs in TAM, and might indirectly shape system usage. Recent studies

that have used TAM as a theoretical framework have suggested to exclude attitude construct from the

TAM model since it does not mediate fully the effect of perceived usefulness and perceived ease of use

on behavioral intention as originally anticipated (Venkatesh, 2003).

Recently, DeLone and McLean, (2004) in a research study related to the dimension of IS

success suggested that system quality (i.e. information and system quality) affects perceived

usefulness, user satisfaction and system usage.

Further, Wixom and Todd (2005) developed an integrated model based on technology

acceptance and user satisfaction literature. The model was tested using a sample of 465 users from

seven different organizations regarding their use of data warehousing software. Findings showed that

information and system characteristics explained 75% variance for system and information quality.

They found that there was significant affect of information and system quality on PU and PEOU.

Moreover, they suggested investigating the effects of the IT artifacts itself as an antecedent to ease of

use and usefulness, and other related factors.

According to Wixom and Todd (2005), TAM provides limited guidance about how to influence

usage through design and implementation. They further elaborated that as PU and PEOU are abstract

concepts and provide general information to the designers. Therefore designers are unable to receive

actionable feedback about the important aspects of the IS artifacts itself. They identified information

and system quality significant constructs which can affect IS usage. Furthermore, Davis (1989) himself

noted that future technology acceptance research needs to address how variables affect usefulness, ease

of use, and user acceptance.

Huang, et al (2002) examined the adoption of e-government in Australian public citizens based

on TAM. Huang, et al’s research effort focused on an actual system usage with two constructs,

perceived usefulness and perceived ease of use. Their research indicated that the prediction of TAM

theory was not supported by the findings.

It can be argued that basic constructs of TAM, perceived usefulness and perceived ease of use,

may not fully determine users’ acceptance of EG, which therefore brings in the need to search for

additional factors that may better predict and enhance the user acceptance of EG.

Another point that has not been explored well in TAM research is the role of system

characteristics as external variables. Davis et al. (1989) did not include other factors explicitly into the

TAM model that are expected to impact intentions and usage through PU and PEOU. These external

variables could be system characteristics, organizational structure, training, and the like (Davis et al.,

1989). According to Davis (1989), external stimuli influence a person’s attitude toward behavior

indirectly by influencing his/her salient beliefs about the consequences of performing the behavior.

Since system characteristics are external stimuli, they should influence beliefs (PU & PEOU) about

using a system.

Besides, most of these empirical studies using TAM were conducted in developed countries and

in industrialized world. Very few studies related to electronic government technologies were carried

out to test the applicability of the model outside these regions , Therefore, it would be erroneous to

assume that IS acceptance theories and models predict equally well in other cultural settings, especially

in developing countries. The robustness of the models may vary across different cultures and thus need

to be empirically tested.

3. Research Model and Hypotheses The proposed research model is presented in Figure (1). According to Wixom and Todd (2005), TAM

provides limited guidance about how to influence usage through design and implementation. They

further elaborated that as PU and PEOU are abstract concepts and provide general information to the

designers. Therefore designers are unable to receive actionable feedback about the important aspects of

the IT artifacts itself. They identified information and system quality significant constructs, which can

affect IS usage.


Based on the literature review a model of factors that influence users’ acceptance of EG has

been proposed. The model consists of system characteristics (Information and System quality),

Perceived Usefulness, Perceived Ease of Use, and acceptance, that author posits will have an effect on

EG acceptance in the context of Jordan. The incorporation of quality into the acceptance model must

describe the dependency of user acceptance on system quality and information quality.

A positive relationship was anticipated for all the hypotheses, (see Figure 1). The research

methodology employed to test these hypotheses is described in the next section.

Figure 1: Research Model

EG System Quality

EG Information Quality

EG Perceived Usefulness

EG Perceived Ease of Use

EG Acceptance

EG System Quality

System quality refers to the technical details of the information system interface and quality of system

that produces information output (Delone and Mclean, 1992). Davis (1989) did not include system

characteristics into TAM model, but he suggested including judicious system characteristics.

According to DeLone and McLean (1992) technology characteristics singularly or jointly affect

subsequent use and user satisfaction. Hence, it is assumed that system quality directly or indirectly

through PU and PEOU, positively effects user acceptance of EG. Thus, this study postulates the

following hypotheses:

H1 EG System quality will have positive effect on user acceptance of the EG.

EG Information Quality

Information quality is related to the quality of information that the EG delivers to its users (DeLone

and McLean, 2004). Information quality determines the success of a website design (Shih, 2003). As

EG provide users means to access information systems directly by performing transactions. Therefore,

EG can be viewed as information systems. Previous studies used information quality to measure IS

success (Iivari, 2005), measuring e-commerce success (DeLone and McLean, 2004), and e-shopping

acceptance (Shih, 2003). Shih (2003) postulated that perceived information quality positively affect

PEOU, PU, attitude, and user acceptance of e-shopping. Therefore, based on theoretical and empirical

support from IS literature, it is assumed that information quality positively affects PU, PEOU, and user

acceptance of EG, this study leads to the following hypotheses:

H2. EG Information quality will have positive effect on user acceptance of the EG.

EG Perceived Usefulness

Perceived usefulness (PU) defined as “the degree to which a person believes that using a particular

system would enhance his/her job performance” (Davis, 1989). According to TAM PU is a significant

factor that affects user acceptance of information system (Davis, 1889; Davis et al., 1989). Several

researchers provide evidence of significant effect of PU on IS acceptance and usage (Davis, 1989;

Pikkarainen et al., 2003; Wang et al., 2003). Hence, EG that users think are useful are more likely to be

accepted by the users. Therefore, this study proposes the following hypothesis:


H3. Perceived usefulness will have positive effect on user acceptance of the EG.

EG Perceived Ease of Use

Perceived ease of use (PEOU) is defined as “the degree to which a person believes that using a

particular system would be free of efforts” (Davis, 1989). TAM posits that PEOU is important factor

that effect IS acceptance, either directly or indirectly through perceived usefulness (Davis et al., 1989).

Venkatesh and Davis (2000) found that PEOU have positive direct effect on user acceptance of IS.

Thus, if online banking systems are easy to use they are more likely to be accepted by the intended

users. Thus, this study postulates the following hypotheses:

H4. Perceived ease of use will have positive effect on perceived usefulness of the EG.

4. Methodology In this section we discuss sample and data collection procedures and operational measures of variables

used in the study as well as the statistical tests used to evaluate the hypothesis.

Population and Sample

The population of study consisted of employees at greater Amman municipality, Greater Amman

municipality has around 18,000 full time staff members in general and serving the needs of a 2.2

million population, district accounts for 40% of Jordan's population, spread over an area of 688 km2.

27 administrative regions make up the municipality Amman's. The questionnaire was to be

administered to all employees who use the municipality e-Government portal.

Measures and Data Collection

To ensure the content validity of a scale, the items selected must represent the concept about which

generalizations are to be made. Therefore, validated instruments adapted from prior studies were used

to measure the study variables. The items used to measure usefulness and ease of use were adapted

from Davis (1989) and Sun and Zhang (2006). The items used to measure system quality and

information quality were adapted and refined from Seddon and Yip (1992) and Wixom and Todd

(2005).

The study used a self-administered questionnaire to measure the study variables. The

questionnaires were pre-tested and distributed to members of the postgraduate students and academics

who are in the information systems area of specialization. The respondents were asked to critically

evaluate the questionnaire with regards to its objective, contents, clarity and ease of completion, and

they also assist in translation and validating the Arabic version of the survey. Prior to the actual

fieldwork, the questionnaires were refined and rephrased accordingly.

The modified questionnaires were then mailed to employees of the municipality.

A covering letter explaining the purpose of this study was attached together, assuring them of

the confidentiality of their responses, and instructing them to complete the questions, seal and return

the completed questionnaires using the attached envelope.

Out of the 300 questionnaires distributed to the employees, 200 usable questionnaires were

returned, yielding a response rate of 67 percent, which is considered acceptable. There were 137 male

and 63 female respondents. The age range of the sample was from ages 21 to 45 years with a mean of

age 33 years. Out of 200 respondents, over 35 percent had achieved at least a high school qualification.

Approximately 87% of the participants had more than 5 years experience in using computers

A Cronbach’s alpha of more than 0.6 implies that the construct measurements are reliable (Hair

et al., 2008). Table 1 shows that the Cronbach’s alpha values obtained in this study ranged between

0.869 and 0.937, suggesting that the measurement used in this study was reliable.


Table 1: Reliability Results

Construct No. of Items Cronbach’s Alpha

EG System Quality 3 0.920

EG Information Quality 4 0.869

EG Perceived Ease of Use 3 0.937

EG Perceived Usefulness 3 0.922

Factor analysis was performed to evaluate the constructs’ validity. Table 2 shows the output of

factor analysis using principle components with varimax rotation. As shown, all items load well on

their respective construct.

Table 2: Rotated Component Matrix

Items F1 F2 F3 F4

SQ1 .848

SQ2 .912

SQ3 .883

SQ4 .858

IQ1 .775

IQ2 .689

IQ3 .735

IQ4 .790

PU 1 .736

PU 2 .798

PU 3 .830

PEOU1 .759

PEOU2 .817

PEOU3 .738

Notes: Only loading > 0.5 are shown; Extraction Method: Principal Component Analysis;

Rotation Method: Varimax with Kaiser Normalization; Rotation converged in 4 iterations.

5. Presentation of Findings Multiple regression analysis was used to test the hypothesized relationships. The independent

variables were regressed on the measures of EIS acceptance. The multiple regression model used to

test each of the hypotheses was as follows:

Yi = α + β1Xi 1 + β2Xi 2 + β3Xi 3 + β4Xi 4+ εi

Where,

Yi = EG acceptance

Xi 1 = EG System Quality

Xi 2 = EG Information Quality

Xi 3 = EG Perceived Ease of Use

Xi 4 = EG Perceived Usefulness

The F-test was used and all significance was tested for p < .05. In each analysis, the

significance of the beta weights were also examined. In addition, the regression equations were

investigated for aptness of model by analyzing the residuals. No problems were found with the

normality of residuals. The results from hypotheses testing appears in table 3.

Table 3: Regression Results

Variables B Std. Error Beta t p-value

EG System Quality 0.604 0.051 0.563 11.772 0.000*

EG Information Quality 0.257 0.053 0.220 4.799 0.000*

EG Perceived Usefulness 0.049 0,038 0.090 1.318 0.042*

EG Perceived Ease of Use 0.088 0.044 0.055 2.043 0.189

R2(adj)= 0.559 F=74.085

Note: * denotes significant below .05 level


EG System Quality, EG Information Quality, and EG Perceived Ease of Use, were found to

have significant standardised regression coefficients (p-value= 0.000), in which PU has the smallest

weighting. EG Perceived Usefulness, however, do not have a significant relationship with the EG

acceptance. From the values of Beta weights and t-ratios for each independent variable, it becomes

clear that system quality, followed by information quality factor had the highest contribution to the

prediction of the dependent variable. However, perceived usefulness has the least (though still

significant) contribution to the prediction. In conclusion, the results indicate support for the hypothesis

H1, H2, and H4, while H3 were rejected.

6. Discussion, Conclusion, and Implication for Further Research This study was designed to break new ground and explore the determinants that influence the user

acceptance of EG. This research tested the thesis that that EG acceptance is a joint function of system

and information characteristics, usefulness, and Ease of Use. Earlier studies have not framed the user

acceptance determinants based on the four dimensions collectively. Hence, our study has established

the significance of examining the user acceptance by framing determinants according to the relevant

quality dimensions in a collective manner and thus, ensuring that the user acceptance can be better

explained in an electronic context such as the EG.

System quality is the most significant determinant affecting acceptance of EG acceptance.

Researchers in the area of conventional IS are generally regard system quality to be a highly important

characteristics of all interactive computer systems (Rai et al, 2002), independent of the specific

application the system was designed to support. In turn, the finding of this research suggests that the

greater the perceived system quality of an EG, the higher is the EG acceptance, agreeing with the

literature noted above. However, there were no past studies about the impact of system quality of EG

on user acceptance. Therefore, this research contributes to some extent to the current knowledge about

the impact of system quality on user acceptance.

The finding showed that information quality is significantly related to EG acceptance. There

were no past studies which link information quality with EG acceptance. Nevertheless, Delone and

Mclean (2004) put forward information quality as a major dimension for evaluating the success of IS.

Our research adds to the literatures by identifying that level of EG information quality is significantly

associated with users' acceptance in the EG context.

The results showed that perceived ease of use is positively related to EG acceptance. This

finding was consistent with past studies (Davis et al., 1989; Venkatesh and Davis, 2000). Our results

suggest that in contexts where effective task execution substantially depends on the system such as the

case with EG, beliefs about the system Ease of Use usefulness are more dominant in shaping user

acceptance than beliefs about usefulness.

A competing model that strengthens the theoretical and empirical foundations has been

developed. Our study has been carried out in an eastern setting unlike earlier studies and this makes

research in the area of technology user acceptance more comprehensive.

Finally, this study suffers from a number of limitations. First, this study merely developed and

validated an EG acceptance model using user perspective as the level of analysis. Future research may

develop EG acceptance models using other stakeholders and levels of analysis.

Second, the use of self-report scales to measure study variables suggests the possibility of a

common method bias for some of the results. Future research should employ both objective and

subjective measures, and examine the correspondence (or lack thereof) between them.

Future research is needed to identify other factor that may impact EG acceptance, such as trust

and satisfaction. Despite these limitations, the present study provides valuable insights into the study of

EG acceptance.


References [1] Al-Omari, A., and H., Al-Omari. (2006) e-Government Readiness Assessment Model, Journal

of Computer Science, v.2, n.11, p.841-845"

[2] Badri, M. and Alshare,K. (2008) A path analytic model and measurement of the business value

of e-government: An international perspective, International Journal of Information

Management 28 (2008) 524–535

[3] Davis, F. D. (1989), "Perceived Usefulness, Perceived Ease of Use, and User Acceptance of

Information Technology," MIS Quarterly, 13 (3), 319-40.

[4] Delone, W. H. and Mclean, E. R. (1992), "Information Systems Success: The Quest for the

Dependent Variable," Information Systems Research, 3 (1), 60-93.

[5] DeLone, W.H., McLean, E.R., 2004, “Measuring e-Commerce Success: Applying the DeLone

& McLean Information Systems Success Model”, International Journal of Electronic

Commerce, Vol. 9, No. 1, pp. 31-47.

[6] Dijk,J., Peters, O., Ebbers, W. (2008) Explaining the acceptance and use of government

Internet services: A multivariate analysis of 2006 survey data in the Netherlands, Government

Information Quarterly 25 (2008) 379–399.

[7] Hair, J. F., Black, W. C., J.Babin, B., Rolph E. Anderson, and Tatham, R. L. (2008),

Multivariate Data Analysis (6 Ed.). Upper Saddle River- New Jersey: Pearson Educational

International -Prentice Hall

[8] Hamner, M. and Al-Qahtani,F.(2009), Enhancing the case for Electronic Government in

developing nations: A people-centric study focused in Saudi Arabia, Government Information

Quarterly 26 (2009) 137–143.

[9] Huang, W., D’Ambra, J., & Bhalla, V. (2002). An empirical investigation of the adoption of e-

government in Australian citizens: Some unexpected research findings. Journal of Computer

Information Systems, 43(1), 15-22.

[10] Iivari J, (2005), “An Empirical test of the DeLone-McLean Model of Information System

Success”, The DATA BASE of Advances in Information Systems, Vol. 36, No. 2, pp. 8-27.

[11] MoICT. e-Government Strategy, Jordan, Amman , 2006"

[12] Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., Pahnila, S., (2004), “Consumer acceptance of

online banking: an extension of the technology acceptance model”, Internet Research, Vol. 14,

No. 3, pp. 224-235.

[13] Seddon, P. and Yip, S. K. (1992), "An Empirical Evaluation of User Information Satisfaction

(UIS) Measures for Use with General Ledger Account Software," Journal of Information

Systems, 6(spring), pp.75-92.

[14] Shih, H., (2003), “An empirical study on predicting user acceptance of e-shopping on the web”,

Information & Management, Vol. 41, pp. 351-368.

[15] Sun, H and Zhang, P (2006), " Causal Relationships between Perceived Enjoyment and

Perceived Ease of Use: An Alternative Approach", Journal of the Association for Information

Systems Vol. 7 No. 9, pp. 618-645/September

[16] Venkatesh, V. and Davis, F. D. (2000). "A Theoretical Extension of the Technology

Acceptance Model: Four Longitudinal Field Studies." Management Science Vol. 46, No. 2, pp.

186-204

Documents

Employee’s Perceptions towards Electronic