E-government diffusion in Iran: a public sector employees\' perspective

Int. J. Business Information Systems, Vol. 15, No. 2, 2014

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E-government diffusion in Iran: a public sector employees’ perspective Sarfaraz Hashemkhani Zolfani* Department of Management, Science and Technology, Technology Foresight Group, Amirkabir University of Technology (Tehran Polytechnic), P.O. Box 1585-4413, Tehran, Iran E-mail: [email protected] *Corresponding author

Maedeh Sedaghat Department of Management, Research Institute of Shakhes Pajouh, P.O. Box 81746-73441, Isfahan, Iran E-mail: [email protected]

Meysam Donyavi Rad Department of Industrial Management, Kar Institute of Higher Education, Qazvin, Iran E-mail: [email protected] Abstract: Governments worldwide, since the 1990s, have launched projects with the mission to simplify delivery of services through electronic means (Torres et al., 2005). E-government is a breakthrough of communication and transaction between a government and its citizens or government and industries. The purpose of this paper is to identify the most salient factors that are currently influencing the development and diffusion of e-government in Iran as perceived by government employees involved in e-government service delivery. After studying previous researches, seven effective e-government diffusion indicators are selected for prioritising using fuzzy AHP and based on the experts’ viewpoints who are the government employees involved in e-government service delivery. The findings reveal that accessibility, security and availability of public services are the first three most important criteria among citizens in relation to e-government adoption in Iran, respectively. This research strategy offers a new and more balanced perspective of e-government adoption and diffusion in Iran. Keywords: government; communication technologies; organisations; employee attitudes; fuzzy AHP; Iran.

public

sector

Reference to this paper should be made as follows: Hashemkhani Zolfani, S., Sedaghat, M. and Rad, M.D. (2014) ‘E-government diffusion in Iran: a public sector employees’ perspective’, Int. J. Business Information Systems, Vol. 15, No. 2, pp.205–221.

Copyright © 2014 Inderscience Enterprises Ltd.

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S. Hashemkhani Zolfani et al. Biographical notes: Sarfaraz Hashemkhani Zolfani is a PhD student of Technology Foresight in Amirkabir University of Technology (Tehran Polytechnic). He is working at Future Studies Research Institute of Amirkabir University of Technology (Tehran Polytechnic), Sustainability Office of Amirkabir University of Technology (Tehran Polytechnic) and Research Institute of the Internet and Intelligent Technologies, Vilnius Gediminas Technical University. He is a member of EURO Working Group OR in Sustainable Development and Civil Engineering. He is the author of more than 45 scientific papers that were presented, published or reviewed at/for international conferences and journals (including ISI-cited publications). His research interests include: performance evaluation, strategic management, decision-making theory, supply chain management, (fuzzy) multi criteria decision making, marketing, futures studies and sustainable development. Maedeh Sedaghat holds a BS in English Language Translation and MS in Executive Master of Business Administration (EMBA). She is a graduate of Payame Noor University, Babol, Iran. She is a PhD student in Human Resource Management at Research Institute of Shakhes Pajouh of Isfahan University. She graduated with high GPA in both her BS and MS courses. She was ranked as the top student in an MS course in Iran. She is the author of more than 15 scientific papers international journals which were published, accepted or under reviewing. Her research interests include sustainability, productivity improvement, performance evaluation, decision-making theory, and (fuzzy) multi criteria decision-making. Meysam Donyavi Rad received his BS in Industrial Management and MS in Industrial Management-Operation and Production Management. He is a graduate of Kar Institute of Higher Education, Qazvin, Iran. His research interests include performance evaluation, strategic management, (fuzzy) multi criteria decision-making, supply chain management (SCM).

1

Introduction

The explosion of digital connectivity and significant improvements in information and communication technologies (ICTs) is changing the way most governments interact with citizens, deliver their services and how they compete with other governments (Abanumy et al., 2005). The emphasis has now changed from internal government focused processes to more open and transparent citizen focused processes that aim to offer more accessible and user-friendly services to citizens. This shift has been facilitated largely as a result of the availability of innovative and cost effective ICT solutions and the evolution of the internet. While developed countries have exploited the power of the internet to successfully e-enable public services and entice citizens, developing countries have been comparatively slow in developing successful e-government strategies (Stoltzfus, 2004; Karunanada and Weerakkody, 2006; Weerakkody et al., 2007). In this respect, the potential benefits of the internet and e-government are yet to be fully exploited in many developing countries. E-government has been defined in several ways depending on the context and research objective of the researchers; it is referred to as digital government, online government and even transformational government (Riley, 2003). Gronlund and Horan (2004) defined e-government as “the use by government agencies of information

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technologies that have the ability to transform relations with citizens, businesses, and other arms of governments”. For this study, we discusses e-government as the manner in which governments make use of the exchange of information and services that are pertinent to citizens, individual businesses, and other governmental agencies (Welch et al., 2005) to name a few researchers such as Riley (2003), Irani et al. (2008) and Beynon-Davies (2007) have suggested that the successful implementation of e-government will ensure improvement in processes within government agencies, which will result in increased efficiency and better management and delivery of public services. The purpose of e-government according to Kostopoulos (2003) is to build a digital state where public services and information can be offered to citizens electronically. Choudrie et al. (2004) suggested that e-government has the potential to improve external and internal relationships among the various stakeholders involved in the government service delivery process (including citizens, government employees, external businesses, etc.) and facilitate sharing of knowledge among these stakeholders. One of the most important reasons of e-government implementation is to embrace citizens and businesses closer to their governments. Consequently, the interactions and transactions can be established anywhere and anytime (Hussein et al., 2011). The potential of e-government for use to reduce the cost of public service delivery, encourage social inclusion, encourage participatory and inclusive governance, etc., cannot be overemphasised. In addition, e-government can be a prerequisite to strategic initiatives avoiding corruption in public service delivery systems (Bwalya, 2009). This paper is organised as follows: the next section reviews the related literature. The following section presents the research model. The methodology section discusses the instrument, sample, and data analysis. The concluding sections present the results, implications and suggestions for future research.

2

Literature review

Although researchers have yet to agree on a common definition for e-government (e.g., Burn and Robins, 2003; Abie et al., 2004; Allan et al., 2006; Yildiz, 2007; Lee et al., 2008; Zhang et al., 2009), e-government can be viewed as a government’s efforts to provide constituencies – citizens, business, and public administration for which a wide range of ICTs including the internet will be needed. E-government plays a vital role not only in ameliorating services to customers, developing businesses, the economy, and society, but also in renewing the role of government itself (Lee et al., 2008). In this regard, e-government will assist in the innovation of governance processes and improved efficiency and effectiveness, while providing more participative opportunities for citizens. One of the critical requirements of a successful e-government initiative is changing organisational structure and processes to account for job and information flow changes (Becker et al., 2004; Bhatnagar, 2002). Moreover, emerging technologies, which have the potential to “open new forms of communication between a government and the people”, are viewed as key to this enterprise. The movement toward implementation of e-government in Iran has recently received the attention of the authorities and policy makers. In fact, the e-enabled government is a unique and unprecedented opportunity for developing countries like Iran to be used for

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improving and streamlining the government’s operations, providing a breakthrough in its performance, and reducing their distance with the developed world. Development of an e-government is a complicated task both technically and politically. The quality of an e-government depends on many factors; critical among these are the government’s information policy, the number of users and their educational level, and motivation (Sharifia and Zarei, 2004). Another survey has been conducted to observe the direct effects of several factors on e-government adoption in Iran. The demographic factors (i.e., age, gender and education), IT knowledge, internet access, trust, perceived usefulness, perceived ease of use and system and web characteristics (i.e., reliability, self-service and linkage) were examined and ultimately it was concluded that the public sector can attract citizens in using electronic services and enhance citizens’ perceptions about the services and increase their IT knowledge by improving their internet access (Rasouli et al., 2011). Various influential have been studied in different electronic contexts in countries around the world. In the following, some of them will be discussed. Perceived ease of use and perceived usefulness, trust of the government, image, compatibility and service quality are found to be significant predictors of citizens’ intention to use e-filing in the Malaysian context (Hussein et al., 2011). Four major dimensions of public value creation through e-government including the delivery of public services, the achievement of outcomes, the development of trust, and the effectiveness of public organisations are considered in evaluating the performance of the e-Sri Lanka programme (Karunasena et al., 2011). In other research, the complexities of e-government implementation and diffusion was classified under the themes of organisational, technological, political, and social contexts and associated challenges that surround e-government systems (Weerakkody et al., 2011). Improved accessibility (Moon, 2002; Martin and Byrne, 2003; Stoltzfus, 2004; Abanumy et al., 2005; Beynon-Davies, 2007; Weerakkody et al., 2007), efficiency (Riley, 2003; Carter and Bélanger, 2005; Abanumy et al., 2005) and availability of public services (Layne and Lee, 2001; Goings et al., 2003; Safari et al., 2004; Carter and Bélanger, 2005; Beynon-Davies, 2007) have been considered the most prominent factors influencing the development and diffusion of e-government which may lead to high levels of confidence among citizens in relation to e-government adoption in Oman. Moreover, it is found that information technology workforce capability has an indirect impact on citizens’ trust and confidence in using e-services (Al-Busaidy and Weerakkody, 2009a). The other affecting factors on e-government adoption studied in developing countries were effort expectancy, social influences, facilitating conditions and behavioural intention (Al-Shafi and Weerakkody, 2009b), the integration of a technology acceptance model, trust and previous e-government experience and perceived usefulness (Carter, 2008).

3

Research conceptual model

Based on studying literature area of this field, seven performance indicators are selected for e-government efforts to assess public online services in the province of Mazandaran (Iran) comprising of:

E-government diffusion in Iran 1

accessibility

2

security

3

efficiency

4

availability

5

private sector partnerships

6

IT worker skills

7

information exchange.

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These factors are presented in Table 1 and the focus of each factor described in table explicitly and details. Table 1

Framework of research

Factor

Focus

Literature

Accessibility

Accessibility refers to the ease of attaining information and services offered through an official e-government web site. Ease of access and use from different type of machines and platforms, allowing different type of users to access the service; actual possibility of usage from abroad.

Moon (2002), Martin and Byrne (2003), Stoltzfus (2004), Abanumy et al. (2005), Beynon-Davies (2007), Weerakkody et al. (2007), Al-Busaidy and Weerakkody (2008), and Al-Shafi, S. and Weerakkody (2008, 2010)

Security

Security refers to the degree of protection that e-government offer against various online threats. The situation/condition that prevents the data used or network resources from damage, destruction, non-protection, fraud, mismanagement, and abuse.

Gant and Gant (2002), Wilford et al. (2004), Ndou (2004), Al-Khouri and Bal (2004), Al-Jboori (2006), Bwoma and Huang (2003), and Al-Busaidy and Weerakkody (2008)

Efficiency

Efficiency refers to the accuracy and comprehensiveness with which users can achieve their needs. The accuracy and completeness with which users can achieve specific goals in the easies way, better output, reduce the time and increase the job performance using the online services.

Riley (2003), Carter and Bélanger (2005), Abanumy et al. (2005), Al-Busaidy and Weerakkody (2008), and Carter and Weerakkody (2008)

Availability

Availability refers to the types, levels, and number of services offered via an official e-government websites. Public online services for the citizens, businesses and government agencies are available, which in turn help to facilitate the implementation of e-services

Layne and Lee (2001), Goings et al. (2003), Safari et al. (2004), Carter and Bélanger (2005), Beynon-Davies (2007), and Al-Busaidy and Weerakkody (2008)

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Table 1

Framework of research (continued)

Factor

Focus

Literature

Private sector partnerships

Indicates the relationship between the public and private sectors within the same region, also it reflect the G-B relationship among e-government implementation.

Al-Busaidy and Weerakkody (2009b), and Al-Busaidy and Weerakkody (2008)

IT workforce capability

The skills of the IT employees of the public sector that would help in implementing better solutions and online services.

Al-Busaidy and Weerakkody (2008)

Information exchange

The ability of the government to exchange their needed information between various government agencies with the use of e-government services and the integrity of front-office e government layer applications with back-office activities to support the interaction of different level of information.

UN (2003), Charif and Ramadan (2003), Kamal et al. (2009), and Al-Busaidy and Weerakkody (2008)

Here, the research conceptual model is presented in Figure 1 for presenting factors in better framework. According to the aim of this research important factors in the e-government diffusion are identified and in the next step fuzzy AHP will be applied to evaluate criteria and to identify relative weights of each factor. Figure 1

Research conceptual model Accessibility Security Efficiency E-government diffusion

Availability Private sector partnerships IT worker skills Information exchange

4

Methodology

AHP is developed by Saaty (1980) maybe one of the famous, dazzling and most widely used models in decision-making. With the extension of this method in fuzzy set theory, fuzzy AHP was developed. In the proposed methodology, AHP with its fuzzy extension, namely fuzzy AHP, is applied to obtain more decisive judgements by prioritising the market segment selection criteria and weighting them in the presence of vagueness. There are numerous fuzzy AHP applications in the literature that propose systematic approaches for selection of alternatives and justification of the problem by using fuzzy set theory and

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hierarchical structure analysis (Efendigil et al., 2008; Önüt et al., 2010). DMs usually find it more convenient to express interval judgements than fixed value judgements due to the fuzzy nature of the comparison process (Bozdag et al., 2003). This study concentrates on a fuzzy AHP approach introduced by Chang (1992), in which triangular fuzzy numbers (TFNs) are preferred for pairwise comparison scale. Extent analysis method is selected for the synthetic extent values of the pairwise comparisons. Some published papers used the fuzzy AHP procedure based on the extent analysis method and showed how it can be applied to selection problems (Cebeci and Ruan, 2007; Kahraman et al., 2003, 2004). The outlines of the fuzzy sets and extent analysis method for fuzzy AHP are given below. A fuzzy number is a special fuzzy set F = {(x, μF(x)), x ∈ R}, where x takes its values on the real line, R: –∞ ≤ x ≤ ∞ and μF(x) is a continuous mapping from R to the closed interval [0, 1]. A TFN expresses the relative strength of each pair of elements in the same hierarchy and can be denoted as M = (l, m, u), where l ≤ m ≤ u. The parameters l; m; u indicate the smallest possible value, the most promising value, and the largest possible value respectively in a fuzzy event. The recent applications of the fuzzy AHP method in shortly are listed below: •

Hashemkhani Zolfani et al. (2012) applied fuzzy AHP for performance evaluating rural ICT centres (Telecenters).

•

Aghdaie et al. (2012) applied fuzzy AHP in market segment evaluation and selection.

•

Fouladgar et al. (2011) used fuzzy AHP and fuzzy TOPSIS for prioritising strategies of the Iranian mining sector.

•

Lin et al. (2011) used fuzzy Delphi method, fuzzy AHP and fuzzy theory to develop an evaluation system of knowledge management performance.

•

Hashemkhani Zolfani et al. (2011) utilised fuzzy AHP and VIKOR for evaluation of rock bands.

•

Kersuliene and Turskis (2011) applied fuzzy AHP and ARAS for architect selection.

•

Heo et al. (2010) used fuzzy AHP for analysis of the assessment factors for renewable energy dissemination programme evaluation.

•

Haghighi et al. (2010) applied fuzzy AHP on e-banking development in Iran.

The triangular type membership function of the M fuzzy number can be described as in equation (1). 0 x≺l ⎧ ⎪ ( x − l ) (m − l ) l ≤ x ≤ m ⎪ μM ( x ) = ⎨ ⎪ (u − x ) ( u − m ) m ≤ x ≤ u ⎪⎩ 0 x u

(1)

A linguistic variable is a variable whose values are expressed in linguistic terms (Önüt et al., 2008). The concept of a linguistic variable is very useful in dealing with situations, which are too complex or not well defined to be reasonably described in conventional quantitative expressions (Zadeh, 1965; Zimmermann, 1991; Kaufmann and Gupta, 1991).

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In this study, the linguistic variables that are utilised in the model can be expressed in positive TFNs for each criterion as in Figure 2. Figure 2

Linguistic variables for the importance weight of each criterion. Equally

μM

Moderately

Strongly

Very Strongly

Extremely

 

0 1

Table 2

3

5

7

9

Linguistic variables describing weights of the criteria and values of ratings

Linguistic scale of importance

Fuzzy numbers for fuzzy AHP

Membership function

Domain

Equal

Triangular fuzzy scale (l, m, u) (1.0, 1.0, 1.0)

Moderate

1

μM(x) = (3 – x) / (3 – 1)

1≤x≤3

(1.0, 1.0, 3.0)

Strong

3

μM(x) = (x – 1) / (3 – 1)

1≤x≤3

(1.0, 3.0, 5.0)

Very strong

μM(x) = (5 – x) / (5 – 3)

3≤x≤5

Extremely preferred

μM(x) = (x – 3) / (5 – 3)

3≤x≤5

Very strong importance Extremely preferred

5 7

9

μM(x) = (7 – x) / (7 – 5)

5≤x≤7

μM(x) = (x – 5) / (7 – 5)

5≤x≤7

μM(x) = (9 – x) / (9 – 7)

7≤x≤9

μM(x) = (x – 7) / (9 – 7)

7≤x≤9

If factor i has one of the above numbers assigned to it when compared to factor j, then j has the reciprocal value after compared comparing with i

(3.0, 5.0, 7.0) (5.0, 7.0, 9.0) (7.0, 9.0, 9.0)

Reciprocals of above M 1−1 ≈ (1 / u1 , 1 / m1 , 1 / l1 )

The linguistic variables matching TFNs and the corresponding membership functions are provided in Table 2. Proposed methodology employs a Likert scale of fuzzy numbers starting from 1 to 9 symbolise with tilde (~) for the fuzzy AHP approach. Table 2 depicts AHP and fuzzy AHP comparison scale considering the linguistic variables that describe the importance of criteria and alternatives to improve the scaling scheme for the judgement matrices. By using TFNs via pairwise comparison, the fuzzy judgement matrix A ( a ij ) can be

expressed mathematically as in equation (2):

E-government diffusion in Iran ⎧ 1 ⎪ a ⎪ 21 ⎪⎪ A=⎨ ⎪ ⎪a( n −1)1 ⎪ ⎪⎩ an1

213

a13 a23

… a1( n −1) … a2( n −1)

a( n −1)2

a( n −1)3

an 2

an3

… … 1 … an ( n −1)

a12 1

a1n a2 n

(2) a( n −1) n 1

The judgement matrix A is an n × n fuzzy matrix containing fuzzy numbers aij . ⎧⎪1, i = j aij = ⎨ ⎪⎩1, 3, 5, 7, 9 or

1−1 , 3−1 , 5−1 , 7 −1 , 9−1 , i ≠ j

(3)

Let X = {x1, x2, …, xn} be an object set, whereas U = {u1, u2, …, un} is a goal set. According to fuzzy extent analysis, the method can be performed with respect to each object for each corresponding goal, gi, resulting in m extent analysis values for each object, given as M 1gi , M gi2 , ..., M gin , i = 1, 2, ..., n where all the M gij ( j = 1, 2, ..., m ) are TFNs representing the performance of the object xi with regard to each goal uj. The steps of Chang’s extent analysis (1992) can be detailed as follows (Kahraman et al., 2003, 2004; Bozbura et al., 2007): Step 1

The fuzzy synthetic extent value with respect to the ith object is defined as: m

Si =

∑M

⎡ n ⊗⎢ ⎢⎣ i =1

i =1

m

To obtain

m

∑∑ M

j gi

∑M

j gi ,

⎤

j gi ⎥

(4)

⎥⎦

j =1

perform the fuzzy addition operation m extent analysis

j =1

values for a particular matrix such that operation m extent analysis values for a particular matrix such that ⎛ M gij = ⎜ ⎜ j =1 ⎝ m

∑

m

m

m

∑ ∑ ∑u lj,

j =1

mj ,

j =1

⎡ n and obtain ⎢ ⎣⎢ i =1

m

∑∑

j

j =1

⎤

⎞ ⎟ ⎟ ⎠

(5)

−1

M gij ⎥

, perform the fuzzy addition operation of ⎦⎥ M gij ( j = 1, 2, ..., m) values and such that n

⎛ M gij = ⎜ ⎜ j =1 ⎝ m

∑∑ i =1

j =1

n

n

⎞

n

∑ ∑ ∑ u ⎟⎟⎠ li ,

i =1

mi ,

i =1

i

i =1

(6)

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S. Hashemkhani Zolfani et al. and then compute the inverse of the vector in equation (6) such that ⎡ n ⎢ ⎣⎢ i =1

m

∑∑

Step 2

j =1

⎤

M gij ⎥ ⎦⎥

−1

⎛ =⎜ ⎜ ⎜ ⎝

1

,

n

1

,

n

1 ⎞ ⎟ li ⎟ ⎟ i =1 ⎠ n

∑u ∑ m ∑ i

i =1

i

i =1

(7)

The degree of possibility of M2 ≥ M1 is defined as: V ( M 2 ≥ M 1 ) = sup ⎡⎣ min ( μM1 ( x), μM 2 ( y ) ) ⎤⎦

(8)

y≥x

and can be equivalently expressed as follows: V ( M 2 ≥ M 1 ) = hgt ( M 1 ∩ M 2 ) ⎧ 1, if ( m2 ≥ m1 ) , ⎪ 0, if ( l1 ≥ u2 ) , = μM 2 ( d ) = ⎪ ⎨ l1 − u2 ⎪ , otherwise ⎪⎩ ( m2 − u2 ) − ( m1 − l1 )

(9)

where d is the ordinate of the highest intersection point D between μM1 and μM 2 (see Figure 3). To compare M1 and M2, both the values of V(M1 ≥ M2) and V(M2 ≥ M1) are required. Step 3

The degree possibility of a convex fuzzy number to be greater than k convex fuzzy numbers Mi(i = 1, 2, …, k) can be defined by equation (10). V ( M ≥ M 1 , M 2 , ..., M k ) = V [ M ≥ M 1 ] and,

V [ M ≥ M 2 ] and...and, V [ M ≥ M k ] = min (V [ M ≥ M i ] , i = 1, 2, ..., k )

(10)

Assume that: d ′ ( Ai ) = min ( Si ≥ Sk )

(11)

For k = 1, 2, …, n; k ≠ i. Then, the weight vector is given by as in equation (12): W ′ = ( d ′ ( A1 ) , d ′ ( A2 ) , ..., d ′ ( An ) )

T

(12)

where Ai(i = 1, 2, …, n) has n elements. Step 4

The normalised weight vectors are defined as: W = ( d ( A1 ) , d ( A2 ) , ..., d ( An ) )

T

where W is a non-fuzzy number.

(13)

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Intersection point ‘d’ between two fuzzy numbers M1 and M2

Figure 3

1

V(M2 ≥ M1) d

5

Results

In this research for pairwise comparison decision-making in FAHP, a questionnaire was sent to a group of experts who were the researchers and managers in the whole area of e-government issues. Seven experts participated in this research and information about experts is shown in Table 3. Background information of experts

Table 3

Variable

1

2

Items

Education background Groups

No.

Bachelor

0

Master

5

PhD

2

Government

4

Researcher

3

Variable

3

4

Gender

Age

Items

No.

Male

6

Female

1

31–40

4

41–50

3

After all comparisons and weighing processes of fuzzy AHP were done, the overall priority weight of each criterion and sub-criterion were obtained which are shown in Table 4. Table 4

Priority weights of criteria C1

C2

C3

C4

C5

C6

C7

Priority weight (W)

C1

1, 1, 1

1, 1, 3

1, 1, 3

1, 3, 5

3, 5, 7

1, 3, 5

3, 5, 7

0.223

C2

1/3, 1, 1

1, 1, 1

1, 1, 1

1, 1, 3

1, 3, 5

1, 3, 5

1, 3, 5

0.194

C3

1/3, 1, 1

1, 1, 1

1, 1, 1

1, 3, 5

1, 1, 3

1, 1, 3

1, 1, 3

0.150

C4

1/5, 1/3, 1

1/3, 1, 1

1/5, 1/3, 1

1, 1, 1

3, 5, 7

1, 1, 3

1, 3, 5

0.171

C5

1/7, 1/5, 1/3

1/5, 1/3, 1

1/3, 1, 1

1/7, 1/5, 1/3

1, 1, 1

3, 5, 7

1/3, 1, 1

0.120

C6

1/5, 1/3, 1

1/5, 1/3, 1

1/3, 1, 1

1/3, 1, 1

1/7, 1/5, 1/3

1, 1, 1

1, 1, 3

0.071

C7

1/7, 1/5, 1/3

1/5, 1/3, 1

1/3, 1, 1

1/5, 1/3, 1

1, 1, 3

1/3, 1, 1

1, 1, 1

0.071

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Due to the results of Table 4, final ranking are presented in Table 5. Table 5

C1

Final ranking of criteria Criteria

Weights

Ranking

Accessibility

0.223

1

C2

Security

0.194

2

C3

Efficiency

0.150

4

C4

Availability

0.171

3

C5

Private sector partnerships

0.120

5

C6

IT workforce capability

0.071

6

C7

Information exchange

0.071

6

Based on the results of fuzzy AHP, accessibility is identified as the most important factor and after that security is placed on the second priority. Priority of each factor is shown in Table 5. Discussion and conclusion are based on the results of Table 5 and more explanation will be presented in these sections.

6

Discussion

The presence of electronic technologies and their growing influences on implementing official affairs in the form of faster, easier and more convenient services, better quality and reduced turnaround times, and in some cases a reduction in the direct cost for the service is so obvious and undeniable. In addition, momentum is maintained through better integration of enterprise, work, information, application and technology architectures with and among agencies. The governments also attempt to inform the public about their role, responsibility, and strategies to combat corruption; this is an effort to keep the agenda of fighting corruption alive in the public mind as well as highlighting the benefits of e-government transactions in order to heighten the public’s intention to use and value the benefits of completing transactions online. Governments worldwide have been recognising that delivery of citizen-centric services is the key to the successful evolution of e-government. A more enlightened view has begun in the ranks of government to treat the citizen like a consumer where transaction satisfaction is important. Given that citizens throughout the world have come to expect 24 hours a day, seven days a week availability in their commercial interactions, it is only natural that they would expect the same from their government. While this access is efficient and expedient, there are some who do not embrace this change due to privacy and security concerns (Ndou, 2004; Al-Khouri and Bal, 2004; Al-Jboori, 2006). The other affecting factors are the technological knowledge and required skills by applying them among the citizens and IT workforces (Al-Busaidy and Weerakkody, 2008; UN, 2003; Charif and Ramadan, 2003; Kamal et al., 2009). The purpose of this research was to identify the most salient factors of e-government adoption and apply a methodology for assessing the most influencing to the least influencing element in the diffusion of e-government among citizens based on public employees which contributes to a better understanding of the e-government programmes’ status and find some solutions to remove the weaknesses. The results of this paper assist the authorities to establish consistent strategies in order to increase the efficiency of

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government functions while simultaneously lowering transaction costs and creating citizens’ satisfaction as well as attracting non-adopters. E-government will continue to be an important topic to monitor, as it will dramatically affect the life of the individual citizen and their governments on a global scale.

7

Conclusions

The research conceptualised the value of e-government factors that influence success in the context of the e-government in Iran, and the mutual interaction between the government and its citizens, that examined the government’s employee experience base and daily interaction with the citizens. Studying previous literature, seven performance indicators are captured for e-government efforts to assess public online services. According to the results and based on the experts’ viewpoints, accessibility, security and availability of public services are the first three most important criteria among citizens in relation to e-government adoption in Iran, respectively. It is obvious that if the citizens are satisfied with suitable services with the mentioned characteristics, they will trust and have confidence in using e-government and the government should continue to facilitate a high level of interaction and communication with citizens. This study proposed a model for evaluating the state of e-government within a country and how a government can improve its online services to citizens by considering the importance degree of influencing factors studied in this paper. In order to provide better and more worthwhile and user-friendly services that meet citizens’ high expectations of e-government, there are lots of efforts need to be made. Facilitating conditions, government’s success in creating trust, clear legislation, implementation guidelines and standards in terms of the technologies and closer collaboration between different local agencies and central government are recognised as key influencing factors on citizens’ use of e-government services. Since Iran as a developing country is not in the advanced stages of e-government due its lack of appropriate substructures and studying the progress of each stage of developing the programme, understanding e-government implementation and dispersal challenges can help the authorities to accelerate the progress of this programme, heighten the perceived usefulness and perceived ease of use among citizens and benefit its advantages. In order to realise the vision of implementing e-government in Iran, seven key factors are identified in this study that may serve as a starting point for decision-makers and implementers. Decision-makers and implementers in the region and the rest of the world can apply the seven factors discussed in the study to examine their performance on their e-government efforts and also investigate and analyse the strengths and weaknesses in each factor which lead to take some actions for improving their practices. This research had some limitations. Since the research focused on the views of government employees, one could argue that the results represent only the views of e-government service providers and therefore may be influenced by their own experience, background and attitude towards online services. Moreover, government employees probably tend to convey a positive image of their own ministries/agencies and officials. Therefore, further research could examine the influential factors identified in this study from Iranian citizens’ perspective; combining these two studies or perspectives will allow

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the researchers to offer a more balanced viewpoint of e-government adoption and diffusion in Iran. Furthermore, continued studies are needed to examine the progress of Iranian e-government in order to ensure that the future development and implementation of different stages of e-government are achieved in the progress of the Iranian vision 2020. This research was conducted in Mazandaran province; therefore, this research could be extended to ascertain the opinions of a wider section of employees of local government agencies from different provinces in Iran.

Acknowledgements We would like to thank the constructive suggestions of anonymous referees that have improved this work.

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