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Success and Failure of Local E-Government Projects: Lessons Learned

from Egypt Hisham Abdelsalam Associate Professor and Director, Decision Support and Future Studies Center, Faculty of Computers and Information, Cairo University, Cairo, Egypt. Christopher G. Reddick Associate Professor, Department of Public Administration, University of Texas at San Antonio, USA. Hatem ElKadi Assistant Professor, Faculty of Engineering, Cairo University, Cairo, Egypt. ABSTRACT This chapter examines the information systems success model in the Egyptian context. Much of the existing literature on information system success focuses primarily on the private sector. There are fewer studies that examine success in the context of the development of e-government. This study focuses specifically on local e-government development of projects in Egypt. A survey is administered in three local governments on actual users of information systems. The results of this study confirm much of the existing research on information system success, but highlight the importance of net benefit as a success factor which examines the organizational and managerial context of e-government development. The importance of this research indicates that managerial functions matter for the success of e-government projects. INTRODUCTION AND BACKGROUND The advancement of e-government projects is critical for the development of countries in Africa (Heeks, 2002a). This chapter examines the success and failure of e-government projects in Egyptian local governments. This chapter applies the Delone and Mclean (1992; 2003) model of information system success to the Egyptian context, something that has not been done in prior research. This chapter examines both the reasons for success and failure of e-government projects and applies an information systems framework using survey data of actual users of a local e-government investment project. E-Government in Africa shows significant promise according to the United Nations e-government surveys. Despite the fact that Africa falls below the world average in terms of rankings, there has been significant improvement in the region, with Northern African countries leading the continent. The top ranked countries in Africa were Tunisia, Mauritius, and Egypt (United Nations, 2010). The World Bank has recognized the importance of e-government for Africa and called for an e-Transformation, or using Information and Communication Technology (ICT) to promote the lives and well-being of citizens (World Bank, 2010).

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This chapter first examines the reasons for success and failure of e-government projects. This is followed by a discussion of the information systems success model and how this model can be translated into testable hypothesis examining e-government projects in Egypt. It also includes background information provided on a local e-government investment service project Egypt. Finally, it involves a testing of the model of information systems success on actual users of this e-government project. SUCCESS AND FAILURE OF E-GOVERNMENT PROJECTS It is critical to know the unique challenges and opportunities facing an African country in order to determine the best way to align e-government with national development goals (Maumbe, Owei, & Alexander, 2008; Schuppan, 2009). For instance, there is a lot of “hype” about e-government implementation in Africa and in its ability to transform service delivery. However, these extremely advanced systems may not work in the context of a developing country and should be modified to fit the context of the country (Chen, Chen, Ching, & Huang, 2007). With the advancement of e-government in developed countries, it is increasingly important to know the reasons for successes and failures of e-government projects (Heeks, 2002a). Research shows that the success rates of African information systems projects have been low, compared to many Western industrial societies (Berman & Tettey, 2001). However, being progressively dependent upon IT development, the reform of African government is significant to study. (Peterson, 1998) On comparing the success rates of information systems in the public to the private sector, governments generally lag behind (Goldfinch, 2007). This is especially apparent in developing countries where there are many factors beyond the control of the project, most notably lack of bureaucratic inertia that prevents wholesale change from a new e-government system (Peterson, 1998). In addition, the larger the scale and scope of the IT project, the more likely for failure of the system (Pardo & Scholl, 2002; Heeks, 2002b; Goldfinch, 2007). There is also the issue of complexity of the system, and this increases the risk of failure of the system in its implementation (Melin & Axelsson, 2009). Besides the issues of bureaucratic culture that prevents the implementation of e-government projects in developing countries, some other common barriers are poor infrastructure, lack of finances, poor data systems and capability, lack of skilled personnel, and leadership styles (Gichoya, 2005). Drawing on Wilson & Howcroft (2002), Goldfinch (2007) summarizes three types of IT project failures: (1) Project failure: the project does not meet the specification agreed upon, including the functional requirements, budget, or completion deadline; (2) System failure: the system does not work properly, including expected performance, not being used in the way intended, or used as intended but does not deliver the expected benefits, or (3) User failure: the system is not used in the face of user resistance because of such things as lack of training, ability of staff, and the complexity of the new system (Wilson & Howcroft, 2002). Often in developing countries, the implementation of information systems fails to meet the objectives of the originally set goals (system failure), which is a high price for countries that lack resources for these systems (Heeks, 2002b; Krishna & Walsham, 2005). Information systems in general and e-government projects in particular, have many diverse and complex challenges that are not easy to overcome (Gil-Garcia & Pardo, 2005). The fact that systems are interconnected in e-government poses a unique challenge for implementation because it stretches across different organizations and through existing departments or agencies. Indeed,

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successful project management is seen as the larger effort to transform government through e-government efforts (Furlong & Al-Karaghouli, 2010). It is important to study project success and failure in the public sector bearing in mind six unique differences to the private sector (Sarantis, Smithson, Charalabidis, & Askounis, 2010). First, the goals of public sector organizations are usually vague compared to the private sector. Second, the project dimensions have much more complex interactions than most private sector initiatives. Third, for the public sector the planning horizon, due to budget restrictions and electoral processes, makes this longer than the private sector. Fourth, the legal and regulatory issues are much more pronounced in the public sector. Fifth, the political nature of decision making in the public sector makes project management of e-government much more difficult. Finally, since the public sector does not make a profit, the return on investment is much more difficult to determine than in the private sector counterparts (Gupta & Jana, 2003). Therefore, it is critical to study IT project management in the context of the public sector, and this is done through a commonly used information systems success model. INFORMATION SYSTEMS SUCCESS MODEL One of the most commonly used information system success model is that of the Delone and Mclean (1992; 2003) and extensions of this model (Seddon, 1997). However, two alternative models that could have been applied to this case study of e-government project management in Egypt should be briefly mentioned. The oldest theory is the diffusion of innovations. According to Rogers’ (2003) theory e-government would be an innovation with different types of adopters, with each of them having unique characteristics. While the Technology Acceptance Model (TAM) has been used in the study of management information systems, there is some similarity to the diffusion of innovations model, but there is more emphasis on social-psychological influences on innovation (Davis, 1986). The important component of the TAM is the perceived usefulness of the new technology, the higher the more likely there will be adoption (Dimitrova & Chen, 2006). The TAM model has been used to explain e-government in developing countries, through the perceived usefulness of technology enhancing job performance (Hamner & Qazi, 2009). Research has integrated the TAM and diffusion of innovations theory and found significant evidence of both having an impact on e-government services (Carter & Belanger, 2005; Dimitrova & Chen, 2006). Following are the six attributes of successful information systems according to the Petter, DeLone, and McLean model (2008): System Quality: This is the desirable characteristics of an information system such as its ease of use system flexibility, system reliability, and ease of learning. Information Quality: The desirable characteristics of system outputs such as relevance of information, understandability, accuracy, completeness, and usability of information. Service Quality: The quality of system support that users get from the IT department such as responsiveness, accuracy, and technical competence from personnel staff. System Use: The manner in which staff and customers use the capabilities of an information system such as the amount of use, frequency of use, extent of use, and purpose of use. User Satisfaction: The users level of satisfaction with the information system such as the reports it generates, and support services provided. Net Benefits: This is the extent in which the e-government information system is contributing to the success of the individuals that are using the system such as improved decision making, improved

productivity, and greater efficiency.

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This model has been applied to the development of information system success in e-government taxation systems (Hu, Brown, Thong, et al., 2009; Floropoulos, Spathis, Halvatzis, & Tsipouridou, 2010) and in e-government in Taiwan (Wang & Liao, 2008).There are also different applications of the model to collaborative e-government (Gil-Garcia, Chengalur-Smith, & Duchessi, 2007), IT leadership and e-government (Prybutok, Zhang, & Ryan, 2008), and examining technological factors of e-government development (Hussein, Shahriza, Karim, & Selamat, 2007). The Delone and Mclean (1992; 2003) model has been successfully applied to information systems in the private sector, and to selected countries and e-government systems. However, it has not been applied to e-government project management in Egypt before as this chapter will explore. RESEARCH MODEL AND HYPOTHESES This study builds on the comprehensive multidimensional model (Figure 1) of an e-government systems success model proposed by Wang & Liao (2008). Their model was developed in accordance with DeLone & McLean (2003), and suggested six success variables in e-government systems: information quality, system quality, service quality, use, user satisfaction, and perceived net benefit. To enhance work done by Wang & Liao (2008), this research tests the following nine hypotheses: H1. Information quality will positively affect use in the e-government context. H2. System quality will positively affect use in the e-government context. H3. Service quality will positively affect use in the e-government context. H4. Information quality will positively affect user satisfaction in the e-government context. H5. System quality will positively affect user satisfaction in the e-government context. H6. Service quality will positively affect user satisfaction in the e-government context. H7. Use will positively affect user satisfaction in the e-government context. H8. Use will positively affect perceived net benefit in the e-government context. H9. User satisfaction will positively affect perceived net benefit in the e-government context.

Information Quality

System Quality

Service Quality

Use

User Satisfaction

Perceived Net Benefit

H1

H2 H8

H9

H7 H3

H4 H5

H6

Figure1. Theoretical Research Model Similar to Wang & Liao (2008), this study considers the use of e-government system. However, “the challenge for the researcher is to define clearly and carefully the stakeholders and context in which net benefit are to be measured” (DeLone & McLean, 2003, p. 23). Different stakeholders may have different opinions as to what constitutes a benefit to them (Seddon, Staples, Patnayakuni, & Bowtell, 1999). Thus, given the nature of the project being investigated, the focus of this study is on the measurement of e-government systems success from the perspective of employees who are the users of the information system. This chapter will examine users and evaluate the system and its net benefit for the e-government project in the Egyptian context.

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CONTEXT Egypt Egypt is considered to be one of the oldest states in history (Daly & Petry, 1998), and it has always been a unitary country that evolved around the water of the river Nile. Currently, the country is divided into 29 administrative sections – called governorates – of varying natures, their sizes, populations, and resources. Governorates are, in turn administratively divided into cities and districts. Local governments – governorates – abide by regulations created by the central government. They only have a limited level of autonomy in the way they provide their services to citizens and the way they manage their administrative processes. Consequently, as reflected in their organizational structure, different governorates might be administratively organized slightly different than others. In general, departments within a governorate deal directly to citizens and can be logically categorized in four major sections: internal services, external services, administrative departments, and top management. Internal services departments provide services pertinent to the municipalities, covering housing, construction permits, commercial licenses, and that are directly managed by the mayor/district council director. External services departments provide the specialized services such as education, health, social security, agricultural services, and report administratively to the mayor, and technically to the relevant ministries. The city/district councils exert their authority over these departments through committees in which all these departments are members and not through direct management. Administrative departments are the supporting departments that perform the necessary administrative tasks required for the council, such as human resources, accounting, transportation, and they do not provide services to the public. Finally, the top management directs and monitors the progress of services and operation in the different departments as well as set the targets and plans for the community. The investment department is one of the departments that exists only at the governorate level (i.e. does not exist in cities and districts). Its functions are preparing studies to promote investment in the governorate, ensuring the alignment of investments projects with the community development track, the approval of investment projects proposed by investors, allocation of the required lands to these projects, and tracking the conformity of ongoing projects with their originally set objectives and rules. Due to the critical nature of its functions, this department has been one of the focusing areas of Egypt government administrative reform initiatives examined in this study. Local E-Government Program Egypt Information and Communication Technology (ICT) strategy was established in 2001 in what was called the Egyptian Information Society Initiative (EISI). EISI was divided into seven tracks; one of which is e-government. The e-government program in Egypt started in 2001 within the Ministry of Communication and Information Technology (MCIT). In 2004, the program was transferred to the Ministry of State for Administrative Development (MSAD), where the appointed minister was the former e-government Program Director (Dr. Ahmed Darwish). This reflects the Egyptian perception of e-government as an element of administrative reform and development. In fact, the other mandate of MSAD is the institutional reform of public administration. Initially, the e-government program consisted of four major tracks: (1) e-government legislative and technical standards infrastructure; (2) e-government services delivery; (3) enterprise resource planning (Accounting, Stock Control, and Personnel); and (4) integration of national databases. Later, each of these tracks was transformed into programs within the e-government framework. The

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services program was later renamed as Egyptian Government Services Development Program; part of which is the Egyptian Local Government Development Project (ELGDP): a super-project with three main projects. The first focuses on service enhancement in municipalities through the automation of citizen services and the establishment of the so-called Smart “Citizen-Service-Centers”. The second is concerned with the development of web portals for the governorates and the third is the citizen relationship management (CRM) systems. The present case is concerned with the first project. ELGDP uses IT and modern management systems to enhance both the quality and efficiency of government systems, reduce service delivery time, and overcome corruption within public administration. ELGDP projects do not aim to fully automate the services, but rather to provide better transparency and equity through enhanced operations, reduced delivery time using a rigorous monitoring and control system. This chapter examines the critical success – or failure – factors derived from the deployment of an integrated Management Information System and Geographical Information System (MIS-GIS) as a part of the “governorate investment services’ enhancement” project that was carried out in three different sites (governorates) in Egypt. The following subsection will briefly introduce and compare the three sites to familiarize the reader with the context. Three Sites Figure 2 shows the locations of the governorates in Egypt where this project has been implemented. Project sites are the capital cities of the three governorates: Matrouh (governorate of Matrouh), Al Tor (governorate of South Sinai), and Port Said (governorate of Port Said).

Figure 2. Location of project sites.

Matrouh is a border governorate and one of the vastest governorates in Egypt; it stretches over 450 km along the Mediterranean Sea with a large area that forms 16.6% of the total area of Egypt. Matrouh is mainly a desert with limited economic activities in the fields of tourism, olive cultivation and processing, as well as other handicraft activities. The majority of investment project in Matrouh is in tourism. In contrast, South Sinai is much smaller than Matrouh with area representing 3.1% of the total area of Egypt. South Sinai is one of the most touristic governorates in Egypt; it contains historical places like Mount Sinai and St. Catherine's Monastery, in addition to recreational areas with its diving paradise and its reserves. It attracts the investors to establish touristic projects like hotels and resorts, and it contains 14.7% of the total number of hotels in Egypt.

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Port Said differs from the two above governorates in the fact that it is basically an urban governorate with the city of Port Said at its center. The city of Port Said is a Free Zone Port on the Mediterranean, at the entrance of the Suez Canal. Its economic activities are basically trade, commerce, maritime service and industries as well as national tourism. It is quite limited in area and population. The city had several institutes that were part of the Suez Canal Universities, out of which emerged the University of Port Said. The governorate of Port Said mainly consists of the city of Port Said divided into five districts and the city of Port Fouad. Matrouh and South Sinai governorates are similar in many aspects: they are both sparse governorates with vast unused desert lands and extended coasts. The main investments in both governorates are in tourism, local and international. Land allocation for projects is usually faced by the informal land appropriation by local Bedouins, who tend to obstruct the establishment of projects on these lands. In addition to being urban in nature, Port Said differs from both governorates in the nature of investment which concentrates on commerce and trade. Table 1 compares the three governorates with respect to some key indicators. As the table depicts, telecommunication infrastructure in the three governorates is rather primitive, and it is the main concern of governors to develop the basic region infrastructure, including roads, water, sewage, as well as health and educational services. This is quite difficult in vast sparse regions, with limited active resources. Table 1. Key numbers of the three governorates.

Matrouh South Sinai Port said

Population (thousands) 323,381 150,088 ٥٧٠,٦٠٣ (% of Egypt’s population) 2.21 0.21 1.25 Area (1000km2) 166,563 31,272 ١٫٣٥١١ (% of Egypt’s Area) 16.6 3.1 0.13 No. of phone centrals 20 20 ٩ No. of post offices 37 94 ٣٦ Illiteracy as a % 26.2 10.1 ١٣٫٥

Project Description This section provides a brief description of the system. The main objective of the project is to assist the local authorities to properly plan, assign, and manage different investment projects on the governorate level. This is to be achieved through an integration of, MIS, GIS, and workflow software application used by the relevant departments, connected over a Local Area Network. Figure 3 shows the conceptual relations structure of the system. The GIS spatially maintains the available and used lands and ongoing projects, while the workflow maintains the related administrative processes and the related archives. Work performed in this project supports the view as the fundamental transition and redefinition of information management in government with a strong institutional impact (Fountain, 2001). Without ICT, the local authorities would poorly plan and manage its developmental projects. The system covers all the service related procedure bypassing the cumbersome paper-based activities. Most of the investment department activities require human intervention and insight. Thus, the

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integrated system does not completely replace the manual system, but rather complements it since original supporting documents are required by law.

Figure 3. Conceptual System Relations

The GIS implemented in this project (Figure 4) contains layers representing the land topology, usage, the available utilities and services, the current and contracted projects and their types as well as satellite image of the region. The GIS represents a central component in enhancing decision making. While spatial information is managed through the GIS unit, this information is availed to other departments and the public. The system simplifies the identification of vacant parcels of land both for staff and decision makers. A query builder, assisted by GIS features, allows the easy identification of all land parcels answering the project requirements. Administrative and Spatial data are consolidated in one system to be jointly analyzed and support the decision making within the governorate.

Figure 4. Integrated MIS-GIS

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Current Project Status The first implementation of the project was in Matrouh in 2006. Back then, the system was brought to operation with a noticeably successful implementation that led to plan for its roll-out in several other sites (Abdelsalam & ElKadi, 2007). However, by the end of 2007, the system began to face some difficulties that led to the complete cancellation of the system early 2008. These troubles were discussed in Abdelsalam, ElKadi, & Gamal (2010). Currently, the system is working only in the latter two sites of South Sinai and Port Said. Matrouh project started and remained functional for several months; after which the system went out of operation until revived with the new Matrouh management. The case, thus, can be classified as a ‘user failure’ (as discussed previously) demonstrating that technology is not the immediate reason of the setback. As will be shown in the following discussion, the staff and management can be the main cause of the setback. On the contrary, the implementation in Al-Tor is successful as it is, after more than one year, still running under the same management, maintaining the driving force behind the system. This is what drives the staff to properly manage the system, and promptly remedy problems to avoid failures. As this chapter is being prepared, Port Said implementation is still at start up with few months of operation, and enjoys the strong support of the top management, and thus seems to be a promising success. RESEARCH DESIGN AND METHOD Data collection procedure As indicated earlier, the focus of this study is on the measurement of e-government systems success from the perspective of employees who are the users of the system under consideration. Therefore, they represent the targeted population of this research. Given that the system was implemented in three governorates, all the 48 employees in the investment departments in these governorates were asked to participate in the survey. The data used to test the research model were obtained from 48 employees representing a 100% sample of users of the system. Data collection was done on-site via a group of student researchers. Employees who are using the system (or have used it in the case of Matrouh) were asked to fill in the questionnaire. The questionnaire requested the respondents to relate to their experience in using the system and to answer the questions in view of that experience. The respondents were instructed to answer the questions by assessing the system as is – not based on their expectations of an ideal system. For each question, respondents were asked to circle the response which best described their level of agreement. The student researchers proctored the process of filling-in the questionnaires to make sure all questions were clear. A total of 48 usable responses were obtained. Detailed descriptive statistics related to the respondents' characteristics are shown in Table 2. The male and female respondents were equal in number. Furthermore, the younger respondents in the age range of 20-30 years outnumbered the other respondents (35.6%). Most of the users of the systems had a university degree (79.2%). There was an even mix of respondents from each of the three governorates.

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Table 2. Sample characteristics Valid Percentage Number Characteristic Gender 50.0 24 Female 50.0 24 Male Age 35.6 16 20-30 20.0 9 31-40 20.0 9 41-50 24.4 11 >51 Education 20.8 10 High School/diploma 79.2 38 University 0.0 0 Master 0.0 0 Ph.D. Governorate 35.4 17 South Sinai 31.3 15 Matrouh 33.3 16 Port Said

Measures of the constructs, validity and reliability The validation process for the survey instrument has gone through three steps: content validity; construct validity, and reliability. The literature review and in-depth interviews conducted with Small and Medium-Sized Enterprises (SMEs) established the basis of content validity for the survey instrument. As in Wang & Liao (2008), to ensure the content validity of the scales used in the study, this chapter tries to adapt, as much as possible, items for the constructs from prior studies. However, the targeted sample/stakeholder is different from DeLone and McLean (2003), since new items drawn from Heeks & Bhatnagar (1999) are included. For the information quality construct, two items (IQ2 and IQ3) are adapted from Doll & Torkzadeh (1988) to capture the two attributes of information quality of an e-government system of the content and timeliness. Additionally, one item (SQ 6) from Doll & Torkzadeh (1988) – as adapted by Wang & Liao (2008) – is selected to measure system quality in an e-government system. One item (SV 4), selected from Wang & Tang (2003) EC-SERVQUAL scale, is used in the service quality construct. Use is measured by a two-item scale adapted by DeLone and McLean (2003) from previous studies (Heo & Han, 2003; Rai, Lang, & Welker, 2002)). Two items (US1 and US3) are taken from Wang & Liao (2008) and included to measure user satisfaction. Finally, two items (NB 5 and NB 7) adapted by Wang & Liao (2008) from Etezadi-Amoli & Farhoomand (1996) user performance scale, are included to measure perceived net benefit. Items used in this study are listed in Appendix A. The measurement in this study relies on Likert-scales measurement with the 5 point scale: Strongly Agree, Agree, Neutral, Disagree, Strongly Disagree, on a numerical scale from 1 to 5. A summary of the survey statistics is shown in Table 3.

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The purpose of construct validity is to show that the items measure what they purport to measure. Unidimensionality is established with exploratory factor analysis, where 0.30 is generally considered to be the lowest significant factor loading to define the construct (Hair, Tatham, & Anderson , 1998). Table 4 shows that all factor loadings meet the criterion of larger than 0.3 and all constructs satisfy the unidimensionality requirement. The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy revealed values of at least 0.5 which is appropriate. Taken together with the Bartlett's Test of Sphericity the factor analysis could be conducted. Reliability is the extent to which a variable or set of variables is consistent in what it is intended to measure. If multiple measurements are taken, the reliable measures will all be very consistent in their values (Hair, Tatham, & Anderson, 1998). This research uses Cronbach’s alpha, as it is the most popular technique and most suitable for the study. The Cronbach alpha (Cronbach, 1951) is a reliability coefficient that indicates how well the item is positively correlated to one another. It is computed in terms of the average inter-correlations among the item measuring the concept. The closer Cronbach alpha is to 1 the higher the internal consistency reliability (Sekaran, 2003). The widely-accepted social science cut-off is that alpha should be 0.7 or higher for a set of items to be considered a scale, but some use 0.75 or 0.8 while others are as lenient as 0.5 (Garson, 2008; Schraga, Morleyb, Quinnb, & Jahanshahib , 2004; Bullinger, Power, Aaronson, Cella, & Anderson, 1996). Cuieford (1965) also thought that the Cronbach’s value higher than 0.7 indicates high validity, the value between 0.7 and 0.35 means acceptable validity, and the value lower than 0.35 means rejected validity. Hence, due to the fact that a number of the items were not tested before with regards to e-government systems, we can consider alpha > 0.5 reliable. With exception of the ‘Service Quality’ scale, the reported Cronbach’s Alpha for all the analyzed data indicates a high degree of consistency and stability among the respondents replies to the questionnaire. Table 5 provides a list of all the alpha values obtained at the factor level. Table 3. Questionnaire summary statistics

Standard deviation Mean Question Information Quality 1.41 2.04 IQ 1 1.32 1.96 IQ 2 1.41 2.06 IQ 3 1.29 2.04 IQ 4 0.41 2.13 IQ 5 System Quality 1.52 3.31 SQ 1 1.65 3.21 SQ 2 1.89 2.69 SQ 3 1.49 2.17 SQ 4 1.35 1.75 SQ 5 1.27 1.85 SQ 6 Service Quality 1.52 2.44 SV 1 1.5 2.13 SV 2 0.43 0.77 SV 3 1.53 2.33 SV 4 Use 1.44 2.19 U 1 1.42 2.38 U 2 User Satisfaction

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1.33 2.27 US 1 1.38 1.94 US 2 1.28 2.4 US 3 1.43 1.69 US 4 Perceived Net Benefit 1.79 2.19 NB 1 1.61 2.13 NB 2 1.91 3.08 NB 3 1.35 2.21 NB 4 1.4 20.4 NB 5 1.87 2.35 NB 6 1.31 2.02 NB 7

Table 4. Factor Analysis Scale KMO Barlett’s Factors Questions Factor loading Information Quality 0.88 0.000 1 5 IQ1 0.744 IQ2 0.938 IQ3 0.876 IQ4 0.947 IQ5 0.902 System Quality 0.68 0.000 1 6 SQ1 0.551 SQ2 0.462 SQ3 0.592 SQ4 0.874 SQ5 0.830 SQ6 0.658 Service Quality 0.55 0.000 1 4 SV1 0.814 SV2 0.899 SV3 0.305 SV4 0.591 Use 0.50 0.000 1 2 U1 0.906 U2 0.906 User Satisfaction 0.81 0.000 1 4 US1 0.906 US2 0.871 US3 0.787 US4 0.828 Perceived Net Benefit 0.81 0.000 1 7 NB1 0.745 NB2 0.864 NB3 0.622 NB4 0.666 NB5 0.909 NB6 0.458 NB7 0.909

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Table 5. Reported Values of Cronbach’s Alpha Scale Items Reliability alpha Information Quality 5 0.927 System Quality 6 0.732 Service Quality 4 0.575 Use 2 0.781 User Satisfaction 4 0.870 Perceived Net Benefit 7 0.849 RESULTS Measurement model Since data is collected from three groups (representing three governorates) ANOVA test is performed to the hypothesis (Ha: employees did not differ in their perception of system success factors in South Sinai, Matrouh, and Port Said). As the results in Table 6 show, the study is able to reject the null hypothesis. Thus, data from all respondents can be grouped and analyzed as one group. Table 7 presents the correlation among different model factors. As shown, significant correlations (p<0.01) are found among all model factors with strength varying from 0.5 to 0.9. Table 6. ANOVA results Factor Sum of

Squares Df Mean

Square F Sig.

Information Quality Between Groups 2.263 2 1.131 1.138 .329 Within Groups 44.737 45 .994 Total 47.000 47 System Quality Between Groups 2.389 2 1.194 1.205 .309 Within Groups 44.611 45 .991 Total 47.000 47 Service Quality Between Groups 2.610 2 1.305 1.323 .276 Within Groups 44.390 45 .986 Total 47.000 47 Use Between Groups 6.096 2 3.048 3.353 .044 Within Groups 40.904 45 .0909 Total 47.000 47 User Satisfaction Between Groups 3.416 2 1.708 1.764 .183 Within Groups 43.584 45 .969 Total 47.000 47 Perceived Net Benefit Between Groups 2.727 2 1.364 1.386 .261 Within Groups 44.274 45 .984 Total 47.000 47

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Table 7. Correlation between different factors Perceived

Net Benefit

User Satisfaction

Use Service Quality

System Quality

Information Quality

1 Information Quality 1 0.943** System Quality 1 0.638** 0.644** Service Quality 1 0.541** 0.686** 0.650** Use 1 0.759** 0.435** 0.807** 0.733** User Satisfaction 1 0.865** 0.826** 0.457** 0.796** 0.688** Perceived Net Benefit

**Correlation is significant at the 0.01 level (2-tailed) Structural model Structural Equation Modeling (SEM) is a powerful method of modeling the interactions among different variables. It has the benefit over multiple regressions in that it has the ability to construct latent variables, or variables which are not measured directly, but are estimated in the model which is predicted to influence the other variables. TETRAD is used to examine the path coefficients of the structural model. Properties of the causal paths, including standardized path coefficients, p-values, and variance explained for each equation in the hypothesized model are presented in Figure 5.

Information Quality

System Quality

Service Quality

Use

User Satisfaction

Perceived Net Benefit

-0.05

0.62***

0.18*

-0.19

0.81***

-0.20

0.43***

0.40***

0.56***

R2 = 0.4895

R2 = 0.7603

R2 = 0.8583

Figure 5. Hypotheses testing results. As the figures depicts, system quality has a significant influence on both use and user satisfaction. Thus, hypotheses H2 and H5 are supported (γ=0.62 and γ=0.81, respectively). The influences of information quality on both use and user satisfaction were not significant at p<.001. Thus, we have not been able to support hypotheses H1 and H4 at that level. As for service quality, H3 is supported with γ=0.18 at p<0.1. Use influence on user satisfaction was significant with β= 0.43 which supports H7. H8 and H9 were also supported with β=0.40 and β=0.56 respectively depicting the influence of use and user satisfaction on perceived net benefit.

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This model accounts for 86% of the variance in perceived net benefit, with user satisfaction exerting a stronger direct effect than use on perceived net benefit. In addition, 49% of the variance in use was explained by information quality, system quality, service quality, and use, while 76% of the variance in user satisfaction was explained by information quality, system quality, and service quality. DISCUSSION OF RESULTS The results of the SEM indicate that greater system quality leads to increased use and satisfaction by users of the investment systems for the three governorates. There are also important implications in that use and user satisfaction is connected to greater perceived net benefit of the information system. The managerial significance of these findings is important. Public managers need to be aware that the quality of the system determines its use. Therefore, systems designs that lower the quality would impede use and satisfaction and the ultimate success of the e-government project. It is especially crucial for a developing country like Egypt, whose resources are very restricted, to realize the importance of improving the system success through quality (Heeks, 2002a; Schuppan, 2009).

Comparing Wang and Liao’s (2008) application of the information systems success model to Taiwan indicates some different results in the context of Egypt. They have found a relationship between information quality and use as well as a relationship between service quality and user satisfaction. Neither of these findings is discovered by the present study. On the whole, most of the attributes for the model can be applied to the Egyptian context supporting its use in other countries.

CONCLUSION This chapter applies the Delone and Mclean (1992; 2003) information systems success model to the development of an Egyptian investment projects in local governments. The results of this study confirm that factors found in the information systems success model were applicable to Egyptian e-government project management. There has been an especially strong indication that information success is related to the net benefit to the organization and user satisfaction. Therefore, management is critical for the development of e-government projects in Egypt. Management should spend more time on explaining how their e-government project impacts the organization, so that users have a broader understanding of the system. In addition, increased user satisfaction explains e-government project success; something that can be easily addressed by education and training in the workplace. Based on the results presented in this study, there are three management concerns that can be addressed. First, instituting a system of beta testing the software before implementation by a select group of users makes sense. Since information system success is related to systems quality making sure that this is adequately addressed through testing is imperative. A second recommendation for public managers is to have an adequate training program for users of the system. Since use and user satisfaction is related to the perceived net benefits, it is logical to have a system where experienced users train more novice users on the systems.

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FUTURE RESEARCH DIRECTIONS Future research should examine the information success model in the context of accounting for more political and managerial factors that might influence e-government projects. These issues have traditionally been underrepresented in these models. However, they need to come to the fore given the unique differences in public and private sector information systems. This study was also limited to a small sample size, and therefore, future research could examine multiple projects and the information system success model. ACKNOWLEDGMENTS This work is part of the research project “Local e-government in Egypt: Integrating Lessons into Planning,” financed by a grant from the International Development Research Center (IDRC-Canada). The authors would also like to express their gratitude to H.E. Dr. Ahmed Darwish, Minister of State for Administrative Development for his support of the research team. APPENDIX A. SURVEY ITEMS USED IN THIS STUDY Information quality

IQ1. Data needed for system operations is available IQ2. The System provides the precise information that I need (Doll & Torkzadeh, 1988) IQ3. The system provides up to-date information (Doll & Torkzadeh, 1988) IQ4. Data resulting from the system is suitable and matches business needs IQ5. The system presents output data in representative and suitable way IQ6. System quality

System quality SQ1. The system crashed several times SQ2. There is periodical maintenance of the hardware and software SQ3. There is obvious and complete integration of data coming from different departments SQ4. The system makes the process of land allocation more accurate SQ5. The system instantaneously informs me about the status of the investment projects SQ6. The system is easy to use (Doll & Torkzadeh, 1988)

Service quality SV1. The employees are qualified enough to use the system SV2. Employees transfer their experience about the system to each other SV3. I need more training to efficiently use the system SV4. I feel safe in my transactions with the system (Wang & Tang, 2003)

Use (Heo & Han, 2003; Rai, Lang, & Welker, 2002) U1. I depend on the system in performing my work U2. The frequency I use with the system is high

User satisfaction US1. I am satisfied with this system (Wang & Liao, 2008) US2. The system satisfies user requirements US3. The system has met my expectations (Wang & Liao, 2008) US4. I recommend using the system in other governments

Perceived net benefit NB1. The system facilitates the managerial process NB2. The system facilitates the process of decision making NB3. The system makes the land allocation process faster NB4. The employees had taken sufficient training to deal with the system professionally NB5. The system saves me time (Etezadi-Amoli & Farhoomand, 1996) NB6. The system provides better way of control

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NB7. The system makes my job easier (Etezadi-Amoli & Farhoomand, 1996) Note: All questions were scaled with Strongly Agree (1), Agree (2), Neutral (3), Disagree (4), and Strongly Disagree (5).

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KEY TERMS AND DEFINITIONS Information System Success: The examination of six criteria of success of information systems as developed by Delone and Mclean (1992; 2003). System Quality: This is the desirable characteristics of an information system such as its ease of use system flexibility, system reliability, and ease of learning. Information Quality: The desirable characteristics of system outputs such as relevance of information, understandability, accuracy, completeness, and usability of information. Service Quality: The quality of system support that users get from the IT department such as responsiveness, accuracy, and technical competence from personnel staff. System Use: The manner in which staff and customers use the capabilities of an information system such as the amount of use, frequency of use, extent of use, and purpose of use. User Satisfaction: The users level of satisfaction with the information system such as the reports it generates, and support services provided. Net Benefits: This is the extent in which the e-government information system is contributing to the success of the individuals that are using the system such as improved decision making, improved productivity, and greater efficiency. Project Failure: The project does not meet the specification agreed upon, including the functional requirements, budget, or completion deadline. System Failure: The system does not work properly, including expected performance, not being used in the way intended, or used as intended but does not deliver the expected benefits. User Failure: The system is not used in the face of user resistance because of such things as recalcitrance, lack of training and ability of staff, and the complexity of the new system.