E-government effectiveness: assessment of contributing governments ICT usage factors. Mohammad I. Merhi* and Kai S. Koong

Transcription

1 Int. J. Business and Systems Research, Vol. 7, No. 1, E-government effectiveness: assessment of contributing governments ICT usage factors Mohammad I. Merhi* and Kai S. Koong Department of Computer Information Systems and Quantitative Methods, College of Business Administration, University of Texas Pan American, 1201 West University Drive, Edinburg, TX 78539, USA mmerhi@utpa.edu koongk@utpa.edu *Corresponding author Abstract: The usage of ICT by governments agencies, accessibility of digital content, and the availability of advanced technologies are among the crucial factors that affect the e-government process effectiveness. Based on secondary data derived from UNPAN and the World Economic Forum, Executive Opinion Survey, this study investigates the major factors that are essential to e-government success. Data were composed from ranks as well as scores that were both included in the analysis. Parametric and non-parametric tests were used for this aim. The results show that government online service index, presence of ICT in government agencies, and e-participation are significant factors for the effectiveness of e-government operations, represented by accessibility and availability. Moreover, results highlight the important factors that help countries be among the high e-government ranks. In general, this paper has important implications for government decision makers, e-government systems designers, and e-government researchers. Keywords: e-government systems; process effectiveness; information and communication technology; ICT; availability; accessibility; Spearman rho correlation; multiple regression. Reference to this paper should be made as follows: Merhi, M.I. and Koong, K.S. (2013) E-government effectiveness: assessment of contributing governments ICT usage factors, Int. J. Business and Systems Research, Vol. 7, No. 1, pp Biographical notes: Mohammad I. Merhi is a doctoral student in the Computer Information Systems Department at the University of Texas-Pan American. His main research interests include IT strategy initiatives in business and government, information security management, cyber-security, e-government development and implementation, and technology adoption and diffusion models. His work has been presented and published in regional, national, and international conferences such as SWDSI, DSI, and AMCIS. Kai S. Koong is Professor and Chair of the Department of Computer Information Systems and Quantitative Methods at the University of Texas Pan American. A recipient of many professional and institutional awards, he is well published and is an Editor-in-Chief of the International Journal of Services and Standards and the International Journal of Electronic Healthcare. He is also Program Chair and Board Member of a number of leading international, national and regional IT conferences. Copyright 2013 Inderscience Enterprises Ltd.

2 2 M.I. Merhi and K.S. Koong 1 Introduction The impact of information and communication technologies (ICTs) on the operations and performance of various sectors and industries at the firm, national, and international levels has been remarkably growing (Cilan et al., 2009; Fazlollahtabar, 2012) since the last three decades. ICT has become one of the main tools for organisational success (Abanumy et al., 2005; Choudhuri et al., 2009) since it has enabled and enhanced both public and private sectors in terms of their management and their services (Scholl, 2003). This made ICTs important tools for these organisations in their process of policy creation (Chen et al., 2009; Choudrie et al., 2010) as they started to invest an enormous amount of resources in ICT. This has been the case in e-commerce, e-learning, e-health, and e-government (Peters et al., 2004; Hackney et al., 2008). Specifically, in e-government, ICT offers the opportunity for more effective, integrated, and coordinated operations and processes between the government and the nation s citizens. In fact, not only does it enable flexible access to information generated and services provided by the government, but also e-government empowers citizens through providing them with more governance and participation. In this study, e-government will be viewed as a business process that should be well planned and carried out to ensure task accomplishment and effectiveness. This view is based on the fact that both e-government and business process management (BPM) aim to maximise efficiency, reduce waste, increase transparency, and simplify operations through effective use of technology. Through well-designed BPM strategies, a government can enjoy efficiency gains and respond promptly to changing demands. A business process is composed of a set of interconnected tasks which are joined together by control flow elements (Guo et al., 2008). The control flow specifies the order of various elements in order to execute and finish the task. In fact every process is composed of different elements that are organised in a specific way leading to success. For instance, in the case of e-services, the business process for submitting any payment consists of numerous steps such as: 1 check the availability of the system; sometimes systems encounter some problems that affect them 2 enter the user s information and validate that all required field are entered 3 validate the user s credit card. These steps simply show that e-government systems implement business processes and provide users with convenient electronic services from accessing the system through entering the data and finishing the task needed. Being a set of coordinated efforts to digitise the government s generated information and services and deliver them electronically to the public, e-government could be thought of as a process that requires effective planning and management to achieve its objectives. In fact, a process is a lateral or horizontal organisational form that encapsulates the interdependence of tasks, roles, people, departments, and functions required to provide a customer with a product or service [Earl, (1994), p.13], and it consists of a flow of activities (Hammer and Stanton, 1999). Thus, to be successful, e-government requires proper management of the flow of activities performed within the government s departments and planned strategies to be carefully aligned with the government and customers objectives. This could be achieved through the adoption of a citizen-centric

3 E-government effectiveness 3 model, with an emphasis on accessibility and efficiency as well as reliability and security (Koh et al., 2006; Du, 2011). Based on this business process perspective, e-government projects have emphasised internal effectiveness, efficiency, integration among departments, and integration among branches besides transferring information and public services to citizens (Scholl, 2003). The advantages of e-government cannot be underestimated. These include, among others, efficiency, citizen satisfaction, reduced waste, and reduced corruption. While it is true these advantages help both governments and citizens to achieve better levels of operations and satisfaction, they cannot be achieved unless a successful system is implemented (Xiao et al., 2011). Such system should contribute to the effectiveness of e-government through managing the process in way that enhances its alignment with the government agency s objectives and with the customers needs. In general the major ingredients of e-government systems are infrastructure, human resources and information (Ngulube, 2007). In fact, e-government systems are built on ICT tools that rely on the availability of inexpensive, high quality telecommunications services (Schware and Deane, 2003). Thus, a major reason behind the success or failure of e-government project is the extent to which the governments address technological infrastructure encouraged by appropriate telecommunications policies (Jaeger, 2003; Schware and Deane, 2003) to ensure accessibility and availability of services to citizens. 2 Statement of the problem In general, e-government enables its stakeholders to reach two benefits. The first is governments will be able to provide services and resources designed to meet the users needs, including citizens, residents, government employees, and such others. The second is that governments will gain economies of scale, reduce costs, and provide technology-enabled user services. The need and the excitement to achieve these two goals have led governments to spend huge amounts of resources on these systems (Peters et al., 2004; Hackney et al., 2008). As a matter of fact, the spending on these systems is still growing very fast (Peristeras et al., 2009). These huge amounts of resources are spent by governments in order to achieve success. Unfortunately, analyst reports still point out that the return on e-government investments is very low or negative in many cases (Accenture, 2005). Also, yet it is not clear whether the citizens will adopt and keep on using these systems for a long period (Bélanger and Hiller, 2006). This could be a result of one or more of these reasons. First, comparing public to private systems lead the users to not adopt the governments systems as it has been found in many cases that the rate of adoption of e-government to be much less than expected (Peters et al., 2004). Contrary to public sector, private sector is obliged to be always up-to-date with the new technologies due to the high level of competition among organisations. Thus, one can see that in general private sector is more advanced with technologies than public in many countries. This makes users less convinced in whether the public sector has the ability to satisfy their needs and give them the same results as the private sector does. Second is ignoring basic factors that directly affect the e-government systems. It is true that the governments need to succeed in this project and they are investing large amounts of money, but in fact the infrastructures are important for these systems as

4 4 M.I. Merhi and K.S. Koong mentioned previously. One of the main infrastructures that lead to the failure of e-government systems, which should be available in order for these systems to function, is the internet. It is noticed that even in the technologically advanced countries this problem exists. For instance, in the EU, and despite the significant increase in the access to ICT equipment and services the digital gap is quite significant. It is estimated that about one-fourth to a third of the EU population are still outside the pale of e-government services (eeurope Advisory Group, 2005). Another example could be in the USA where the access to the internet connections is still not distributed evenly across racial, regional and socio-economic lines. This is known as the digital divide. For instance, and according to Wright (2002) in 2001, in the USA 60% of white households had internet access, while only 34% of African American and 38% of Latino households did. Similarly, roughly 78% of households with income between $50,000 and $75,000 had internet access compared to only 40% of those with household incomes between $20,000 and $25,000 (as cited in Carter and Weerakkody, 2008). In a later study, statistics shows that only 55% of adult Americans have broadband internet connections at home (Horrigan, 2008). Another reason, and apart from the lack of infrastructure, the availability of ICT equipments and the price of internet broadband form barrier in front of users in the developing countries (ITU, 2009). Comparing users income to the price of internet and equipment, people do not have the ability to have these technologies and thus access these systems. 3 Statement of the objective The purpose of this study is to investigate the factors that would lead to the accomplishment of e-government operations in an efficient and effective way, including providing citizens with the proper levels of accessibility and availability. Governments from all over the world are looking for ways to achieve the objective of e-government especially after investing the enormous amount of resources in this project (Hackney et al., 2008; Peristeras et al., 2009). In order to achieve this aim, a preparation should be done before. It should be noted that the technology itself would not guarantee success of e-government. However, it is necessary that any e-government initiative should have support and must ensure that it has sufficient resources, adequate infrastructure, management support, capable IT staff, and effective IT training and support (Ebrahim and Irani, 2005). This study examines the usage of ICT by governments of 133 countries, and deals with the following research questions: 1 Is there any difference between the five indexes that are related to the usage of ICT by government from one side and availability and accessibility from the other side? 2 What are the factors that affect the e-government availability and accessibility? 3 What are the factors that help countries achieve high ranking? To answer these questions, this research deals with five indexes that form the ninth pillar (government usage of ICT) of The Global Information Technology Report In addition to these five indexes, the availability of latest technologies and the accessibility of digital content indexes were used. In particular, this study uses various quantitative techniques that would help in determining the factors that lead governments to achieve e-government systems objective and get a high ranking among the countries.

5 E-government effectiveness 5 Specifically, this study and the reported outcomes are expected to be useful for both practitioners, as well as researchers. By practitioners, it is meant governments decision makers, IT departments in governments, governmental agencies who will find in this study a powerful means to identify the fundamental factors that lead to success. By identifying the important factors, governments can focus and invest in those factors in order to satisfy their citizens, achieve success in their projects by making e-government systems accessible and available to as many users as possible. More interestingly, this study is aimed to all countries, developed and developing, since as mentioned previously in the problem, governments are not succeeding in these projects all over the world. Different countries have different perspectives and different resources. Thus, based on the country level and its resources, government can now plan and invest in the significant factors. As for researchers, this study came about to test and assess two factors that have been identified by previous studies as important factors that affect the success and effectiveness of e-government systems. These factors are: availability and accessibility. In fact, these factors were mentioned in the literature but with no empirical assessment. 4 Literature review Previous research discussed e-government extensively. With the many advantages it provides the various stakeholders with, e-government became an interesting subject to many researchers in so many countries (Parent et al., 2005; Aydinli et al., 2009). In general, e-government has several advantages. First, it is a cost-effective means (Evan and Yen, 2006; Kumar et al., 2007) that helps in promoting openness and transparency (Abie et al., 2004) that leads to reduce corruption (Bertot et al., 2010). This in its turn enhances relationships between government employees and citizens (Evans and Yen, 2006). In addition, it allows citizens to track their activities (Prybutok et al., 2008) as well as to monitor the behaviours of government employees (Bertot et al., 2010). Thus, with all these mentioned benefits, e-government no longer appears to be a matter of choice for governments, but it is a necessity for any country willing to enter the 21st century as a competitive nation (Kumar et al., 2007; Yang et al., 2009). Consequently and based on the previously mentioned advantages, one can conclude that e-government systems have dual benefits, for governments as well as citizens. As for governments, it helps them to achieve significant cost reductions, provide faster service to clients, and eliminate redundant IT development across agencies (Evans and Yen, 2006; Tolbert et al., 2008). Whereas for citizens, e-government offers a number of potential benefits such as giving citizens more control on time and place to interact with the government especially the ability to access and submit the applications electronically. Moreover, it provides citizens a considerable saving of time and money (Kumar et al., 2007; Gallego-Álvarez et al., 2010). Furthermore, it allows citizens to participate in the democratic institutions and political processes (Tolbert and Mossberger, 2006), thereby perceiving governments as accessible, transparent, responsible, effective and participative (Bertot et al., 2010). Not only this, but previous studies (Abanumy et al., 2005; Henriksson et al., 2007; Bertot et al., 2010) also identified two other fundamental requirements for successful e-government, which are accessibility and availability. Accessibility refers to the ease of obtaining information from e-government systems. This information should be provided

6 6 M.I. Merhi and K.S. Koong to all citizens equally. To do so, e-government systems should be designed and operated in an easy way so that even those persons who have limited knowledge in using computers can easily perform all e-government transactions (Schedler and Summermatter, 2007; Treiblmaier and Pinterits, 2010). Also, these systems should take into consideration the special needs of the disabled, and make it possible for them to use these systems as easily as the non-disabled (Henriksson et al., 2007). Otherwise, these systems fail to serve its full constituency. On the other hand, availability is the degree of information and services offered by the systems to the citizens. E-government systems should be designed in such a way to help citizens achieve what they want in an easy way without any complications. They should be available 24/7 in order to provide citizens, businesses, as well as governments employees the flexibility to achieve what they intend to do at any time they find it convenient for them. Also, governments should determine the level of the services that should be provided. Pushing information of no-importance to the citizens drives them to distrust, refrain from using the systems and look for other simple means to satisfy their needs. This will most likely negatively affect the successful use and implementation of e-government systems (Hussein et al., 2007). Similarly, not offering the needed information will have the same result. Thus, an effective system is the one that has only accurate information that citizens are in need for. Apart from the systems itself, the accessibility and availability of the systems are usually related to the infrastructure that was mentioned previously. For instance, internet access can be a major barrier for most ICTs, all over the world. In 2009 quarter of the world s population used the internet (ITU, 2009). Specifically, in the USA only 55% of adult Americans now have broadband internet connections at home (Horrigan, 2008) which in its turn is affecting the e-government systems usage such as e-voting (Yao et al., 2007). In fact, the more people have internet access, the more they could access government websites and demand an efficient and responsible digital government (Kim, 2007). Another issue is the cost of the technologies. Governments providing online transaction capabilities must consider the cost of access (Schware and Deane, 2003). While the concept of e-government is the same everywhere, and while the adoption of e-services by governments is increasing, the level of implementation and success differ from country to country. The reason for this is explained by the existing literature (Abanumy et al., 2005; Al-Fakhri et al., 2008; Hamner and Al-Qahtani, 2009; Schuppan, 2009) that takes into consideration the factors behind these differences concerning e-service development. These factors are privacy and security (trust) barriers, technological barriers, functionality barriers, and cultural barriers. Citizens confidence in the ability of government agencies to provide online services is necessary to the diffusion of e-government initiatives. Bélanger and Carter (2008) state that trust in the agency has a major impact on the use of a technology. Thus, in order to succeed in e-government implementations and let the citizens adopt it, first, they must believe that the government s agencies are capable and possess the technical skills necessary to execute and secure e-government systems. When it comes to personal information, people may doubt the accuracy of the system especially with the increasing number of identity theft. Therefore, transparent, accurate, reliable interaction with e-government service providers will increase citizens confidence and acceptance of e-government services. But it should be noted that this aim could not be achieved without the availability and accessibility of advanced technological infrastructures. Not only this but researchers (Hung et al., 2009; Khalil, 2011) have also indicated that the culture

7 E-government effectiveness 7 could be one of the barriers for e-service implementation. Indeed, not all cultures have the same values and perspectives for these or any systems. As a matter of fact, business processes are essential elements of almost all systems that support organisations (public or private) activities (Yasin et al., 2011). Large organisations may have hundreds of business processes that need to be managed and integrated with new systems in an effective way. One way to control these processes is the BPM. BPM is based on a process that captures the interrelationships between key business processes together with enabling support processes and their alignment with the strategies, goals and policies of an organisation (Armistead and Pritchard, 1999). According to van der Aalst et al. (2003), BPM can be defined as the supporting business processes using methods, techniques, and software to design, enact, control, and analyse operational processes involving humans, organisations, applications, documents and other sources of information. In another word, BPM is a management discipline that requires organisations to shift to process-centric thinking, and to reduce their reliance on traditional structures (Pynnönen et al., 2008). This is simply because BPM s aim is to integrate systems, automate routine activities, manage and organise all phases of processes. Managing business processes electronically gives organisations many advantages such as cost reduction and enhanced quality in administrative processing, faster case handling and enhanced customer satisfaction, faster process adjustment, enhanced reporting capabilities, and enhanced capacity planning, among others (Halstenbach, 2007). In the case of e-government operations, previous research found that emphasising the e-government business process change could be the reason behind the high success rate of public-sector projects as those of the private sector (Scholl, 2003). Previous research relating BPM to e-government showed that there is a lack of process orientation in public administrations. Additionally, existing processes are regularly not applicable to e-government. Therefore, e-government projects in practice are not always able to fully implement transactional processes. Part of the value potentially added by e-government is hence not exploited. One of the main reasons for the lack of process orientation is that there are few BPM methodologies applied and verified in public administrations (Becker et al., 2006). This emphasises the need for such methodologies and for a more strategic point of view based on which the electronic delivery of government services should take place (Affisco and Soliman, 2006). 5 Methodology The targeted population of this study consisted of 133 countries that are using ICT for governments usage. In particular, the data used in this study were obtained from two data sets: one is The Global Information Technology Report and the other is The Global Competitiveness Report It should be noted that the data sets used in these two reports were adapted from the World Economic Forum, Executive Opinion Survey and from the United Nations, UN e-government Survey These data fit the objective of the research and especially they fit for global studies since they cover large number of countries. Both surveys are gathered from different countries that have different level of development (developed and developing), besides they cover the five continents. Consequently, this enriches the current study.

8 8 M.I. Merhi and K.S. Koong Seven variables extracted from these two reports; five of them are under the ninth pillar of The Global Information Technology Report which are related to the government usage, in addition to accessibility and availability of latest technologies. The variables and their scales are presented in Table 1. Among these seven variables, five (government success in ICT, ICT use, presence of ICT in government, accessibility, and availability) are scores based on one question for each variable; whereas the remaining two (government online service, and e-participation) are calculated indexes by the United Nations. The following paragraphs give more details about the method that was used to calculate the scores. The countries national websites as well as the websites of the ministries of education, labour, social services, health and finance were assessed by the United Nations research teams in order to find a set of online service index values. The national sites were tested for a minimal level of web content accessibility as described in the web content accessibility guidelines of the World Wide Web Consortium. The survey instrument used to gather the data was composed of four sections corresponding to the four stages of e-government development (UN, 2010). The first includes questions relating to attributes that would be considered typical of an emerging online presence, the second to an enhanced presence, the third to a transactional presence and the fourth to a connected presence. Most of the questions in the survey have binary response. Table 1 Variables used in the study and their scales Variables name Government success in ICT promotion Government online service index ICT use and government efficiency Presence of ICT in government agencies E-participation index Accessibility of digital content Availability of latest technologies Scales How successful is the government in promoting the use of information and communication technologies in your country? (1 = not successful at all; 7 = extremely successful). This index assesses the quality of government s delivery of online services (it is calculated by UN). To what extent has the use of information and communication technologies by the government improved the efficiency of government services in your country? (1 = no effect; 7 = has generated considerable improvements). To what extent are information and communication technologies used by the government agencies in your country? (1 = not used at all; 7 = highly used). This index assesses the quality, relevance, usefulness of government websites in providing online information, participatory tools, and services to citizens (it is calculated by UN). In your country, how accessible is digital content (e.g., text and audiovisual content, software products) via multiple platforms (e.g., fixed-line internet, wireless internet, mobile network, satellite, etc.)? 1 = not accessible at all; 7 = widely accessible). To what extent are the latest technologies available in your country? (1 = not available; 7 = widely available). Similarly, another survey instrument was used by the United Nations research team in order to gather raw data to calculate the e-participation index. The instrument was composed of questions that focus on the use of the internet to facilitate provision of information by governments to citizens, interaction with stakeholders and engagement in decision making processes. A country s e-participation index value reflects how useful

9 E-government effectiveness 9 these features are and the extent to which they have been deployed by the government compared to all other countries. The purpose of this measure is not to prescribe any particular practice, but rather to offer insight into how different countries are using online tools to promote interaction between citizen and government, as well as among citizens, for the benefit of all (UN, 2010). On the other hand, the scores of the remaining five variables are the results drawn from the World Economic Forum s Executive Opinion Survey. Respondents were asked for responses on a scale of 1 to 7, where an answer of 1 corresponds to the lowest possible score and an answer of seven corresponds to the highest possible score. For each survey question, individual responses from the survey are combined and aggregated at the country level in order to produce country scores. It should be noted here that the scores are reported with a precision of two decimal points. After presenting this description of the variables and the source of the data set, a description of the methodology used in this study is presented next. To start with, data were entered and organised according to the country in a spreadsheet file. For each variable, both the score and the rank of the country were entered. A total of 133 countries were used in six of the variables; whereas the last variable Availability of latest technologies had 139 countries. Thus, the six countries which were not included in the other variables were deleted in order to get the same countries in all variables. Next, having entered the score and the rank of each country, a descriptive statistics are generated to examine the distribution of the variables. Descriptive statistics are used to describe the basic features of the data in a study. They provide simple summaries about the sample and the measures. Then, other parametric and non-parametric tests such as Spearman s rho, canonical correlation analysis, Friedman and Kendall s Tests and Ordinary Least Square (multiple regression analysis) are used to answer the study s research questions. The logic behind the use of these different statistical methods was that each statistical method provides one type of output that is different from the outputs of the other statistical methods and, at the same time, completes other statistical methods in terms of drawing a complete picture of the assessment. Simply put, each statistical method answers one of these questions and, at the same time play the role of a prerequisite of a second method. It should be noted that both the scores and the ranks were used due to the nature of the data sets since the variables have different scales; some are measured using 7 points scales, others are indexes measured from 0 to 1. To start the analysis, first, a Spearman s rho correlation was performed to evaluate the degree to which countries with high rankings on one variable were observed to have similar rankings on another variable. This test is usually used when researchers seek to evaluate the level of correlation between variables representing ordinal measures. The ordinal data is sometimes found in situations where the researcher has a data set of rankings which is similar to the case of this study. By using the ranks and not the scores and in order to test the correlation between the variables, a null hypothesis is set up: H1 There is no association between the variables in the population. This hypothesis is tested based on the p-values. In this study, the significant level used is Having p-values higher than 0.01 means that the null hypothesis is correct and there is no association between the variables in the population, otherwise an association exists.

10 10 M.I. Merhi and K.S. Koong Second, canonical correlation analysis was executed in order to answer the first question. That is to test if there is any difference between the five indexes that are related to the usage of ICT by government from one side and availability and accessibility from the other side. Basically, this method provides a simultaneous analysis of set of dependent variables and set of independent variables. In general, it determines whether two sets of variables are independent of each other in a linear sense (Hair et al., 2006). This is done by finding a composite for the multiple dependent variables and a composite for the multiple independent variables. Then these composites are correlated simultaneously in order to obtain a canonical function. This process continues until all the correlations between the two sets are included. Thus, the null hypothesis for this test: H2 The sets of variables are not linearly related. Again, this hypothesis can be evaluated based on the p-values of the multivariate tests. Having p-values higher than 0.05 means that the null hypothesis is correct and the sets of variables are not linearly related, otherwise a linear relationship exists between the sets of variables. Third, the Friedman and Kendall s Tests were conducted. These tests are non-parametric tests for the significance of the variation among the distributions of many variables. Simply, they are alternatives for ANOVA. Like many other non-parametric tests, these tests use the ranks of the data rather than their raw values to calculate the statistic. The main objective of the Friedman and Kendall s tests is to examine whether there is a difference or no difference in mean ranks for repeated measures. In other way, the null hypothesis for these tests is: H3 There is no significant difference between the dependent samples and the population from which they have been drawn. This hypothesis can be evaluated based on the significance of the p-values. Having p-values higher than 0.05 means that the null hypothesis is correct and there is no difference between the variables, otherwise a significant difference exists between the variables. Finally, in order to answer the last two questions multiple regression method (OLS) was used. This method is a useful technique that can be used to analyse the relationship between a single dependent variable and several independent variables at one time. Basically, in this analysis a set of independent variables is weighted to form the regression variate that can be used to explain the relative contribution of each independent variable toward the dependent variables. In order to check for contribution of these variables a null hypothesis should be set, which is: H4 There is no significant correlation at all between the dependent and independent variables. That is, all of the coefficients are zero and none of the variables belong in the model. This hypothesis can be checked using the p-value as well as the t value. Having p-values less than the significance level which is 0.05 in this study and having value higher than t critical, mean that the particular independent variable is a good contributor for the model. The regression coefficients are interpreted as the change in the expected value of the dependent variable associated with a one-unit increase in an independent variable, with the other independent variables held constant. The main goal of OLS is to closely fit a

11 E-government effectiveness 11 function with the data. It does so by minimising the sum of squared errors from the data. The OLS estimator is consistent when the regressors are exogenous and there is no multicollinearity, and optimal in the class of linear unbiased estimators when the errors are homoscedastic and serially uncorrelated. Moreover, OLS can be derived as a maximum likelihood estimator under the assumption that the errors are normally distributed. In order to check for these assumptions different tests are performed in this study using SPSS and STATA 11. To check for normality, the descriptive statistics table (Table 2) includes the skewness and kurtosis value. Based on these values one can conclude whether normality exists or not. Moreover, each of the regression tables has a VIF range and a value for the heteroscedasticity. The VIF (Variance Inflation factor) is a test for multicollinearity; values below than ten indicate that multicollinearity does not exist (Hair et al., 2006). As for the heteroscedasticity, it was calculated using The Breusch-Pagan test which is designed to detect any linear form of heteroscedasticity. If this value is less than 0.05 (< 0.05); this means heteroscedasticity is present otherwise the errors are homoscedastic. In this study, four tests were conducted. First, a test was applied to check and identify the factors that affect the rank average of accessibility and availability. For this aim, the five variables (Government online service index, Government success in ICT promotion, ICT use and government efficiency, Presence of ICT in government agencies, and e-participation index) were considered as the independent variables, and the average rank of accessibility and availability was considered as the dependent variable. A second test was performed to identify the factors that affect the availability. Again the five variables (Government online service index, Government success in ICT promotion, ICT use and government efficiency, Presence of ICT in government agencies, and e-participation index) were considered as the independent variables, and the availability was considered as the dependent variable. Next, a test was conducted to identify the factors that affect the accessibility. Again the five variables (Government online service index, Government success in ICT promotion, ICT use and government efficiency, Presence of ICT in government agencies, and e-participation index) were considered as the independent variables, and the accessibility was considered as the dependent variable. Finally, and in order to answer the third question specifically, a test was performed to identify the factors that affect the rank average. On this test, the five variables (Government online service index, Government success in ICT promotion, ICT use and government efficiency, Presence of ICT in government agencies, and e-participation index) were considered as the independent variables; whereas, the average of ranks of these five variables was considered as the dependent variable. 6 Findings ICT s usage by governments and especially e-government systems is not stable. In fact, one can observe the change in the ranking from a year to another. This is due to the abilities of the governments to adopt the new technologies. As mentioned previously, different countries have different resources, infrastructures, and priorities, etc. In order to get a better idea about the disparity of the data used in this study, a descriptive statistics

12 12 M.I. Merhi and K.S. Koong was applied. The results are presented in Table 2. First, by checking the range values of all variables, it can be found that the values are close to each other for both scales used. Interestingly, the results show that there is disparity among the ranks. That is true since the data are composed from different countries that belong to different levels of development and advancement in the technology. Some countries are developed, others are developing. Not only this, but the disparity between variables is almost equal; about three points for the seven scale variables, and 0.9 for the indexes variables. Importantly, the usage of this data enriches the study and decrease the bias since it is not focused on only one group. Moreover from Table 2, the skewness and kurtosis measures show that the data of Government success in ICT promotion, Government online service index, ICT use and government efficiency, Presence of ICT in government agencies, and Accessibility are normally distributed. Normality is one of the assumptions that should be tested before running multivariate analysis. The results yielded in this table, ensure that other multivariate tests could be executed later. Besides, more information about the shape of the distribution could be found in the results. Most of the skewness values are positive which means that the mass of the distribution is concentrated to the left. At the same time, most of the kurtosis values are negative which means that the shape of the distribution is not peaked. Table 2 Descriptive statistics GS GO ICT ICT Gov E part Avail Access N Range Minimum Maximum Mean Std deviation Skewness Kurtosis Notes: GS = government success in ICT promotion; GO = government online service index; ICT = ICT use and government efficiency; ICT Gov = presence of ICT in government agencies; E part = E-participation index; Avail = Availability; and Access = Accessibility. After checking the data used in the study, a next step comes to check the relationship between the used variables. Checking the correlation coefficients helps the researcher to find out whether a relationship exist between the dependent variable and the independents variables or not. Of course, the aim is to find a relationship which means that the independent variables can account for the dependent variable. At the same time a low correlation coefficients should be found among the independent variables; otherwise, multicollinearity might exist among the independent variables. The Spearman rho correlation coefficient was performed to determine if a statistically significant relationship existed between the ranks of all seven variables. Results are displayed in Table 3. As one can see, all the correlation coefficients are statistically significant at 0.01 level which means that significant relationships exist among these variables. Also, it should be noted that all of the coefficients are high except for two relationships; one between government success in ICT promotion and government online service index, and

13 E-government effectiveness 13 the second between government success in ICT promotion and e-participation. Another interesting finding is the high relationships between availability and accessibility and the other five variables. Simply these results assure the objective of this study, and one can conclude that availability of latest technologies and accessibility of digital content do affect the usage of ICT in governments. This result is logical and one can expect it. An example that could be given in this case to explain more the findings is the case of the radio or cell phones and the tower to broadcast. In fact both are important and they should be available in order to use them and get the service, but which one should come first? For sure the tower of broadcast should be found first. The same rule can be applied in this case, the availability of infrastructure and accessibility of new technologies should be found first in order to be able to use e-government systems properly. Also, the result indicates that all other factors are highly important and related to each other. Table 3 Non-parametric correlations: the Spearman s rho test GS GOS ICT ICT Gov E-part Avail Access Gov t success 1 Gov t online.393(**) 1 service ICT and gov.874(**).549(**) 1 efficiency Presence of ICT.817(**).635(**).926(**) 1 E-participation.372(**).862(**).488(**).582(**) 1 Availability.653(**).688(**).764(**).803(**).615(**) 1 Accessibility.604(**).767(**).728(**).810(**).660(**).871(**) Notes: GS = government success in ICT promotion; GOS = government online service index; ICT = ICT use and government efficiency; ICT Gov = presence of ICT in government agencies; E-part = e-participation index; Avail = availability; and Access = accessibility; (**) significant at the 0.01 level. By checking the bivariate correlation analysis, one can conclude that there is a strong relationship between the individual variables used in this study. But more interestingly would be to examine whether a relationship exist between the set of variables that are related to ICT usage by government (Government success in ICT promotion, government online service index, ICT use and government efficiency, presence of ICT in government agencies, e-participation index) and the set of variables that is composed from accessibility and availability. The canonical correlation analysis was used for this aim and the results are presented in Table 4. Since one of the variables set is composed from two variables only, two canonical functions were obtained. Importantly, the results show that the two sets of variables as groups are significantly related to each other and a correlation exists between them. This can be seen by the results of both functions; one is significant at 0.01 level and the other at 0.05 level. Moreover, by checking the canonical loadings one can see that there are strong relationships since all loadings exceed.73 on the first function. Consequently, these results answer the first research question by indicating that there is a significant difference between the set of ICT usage from one side and accessibility and availability from the other side. These results clearly indicate that there are two different parties benefiting from e-government which are government (private) and citizens (private). Having e-government systems and ICTs at the

14 14 M.I. Merhi and K.S. Koong governmental offices is not enough. In fact, the availability of the technologies and the accessibility to the systems from the citizens side is important as well. Table 4 Variables Results of canonical analysis Canonical loadings 1 2 Government success in ICT promotion Government online service index ICT use and government efficiency Presence of ICT in government agencies E-participation index Accessibility of digital content Availability of latest technologies Canonical R Degrees of freedom 10 4 Significance Table 5 Friedman and Kendall s W tests Chi-Sq df Sig. All ranks Gov t ranks Avail and access Gov t avg ranks and avg of avail and access Notes: All Ranks = (rank of government success in ICT promotion; rank of government online service index; rank of ICT use and government efficiency; rank of presence of ICT in government agencies; rank of e-participation index; rank of availability; and rank of accessibility), Gov t Ranks = (rank of government success in ICT promotion; rank of government online service index; rank of ICT use and government efficiency; rank of presence of ICT in government agencies; and rank of e-participation index), Gov t avg ranks and and avg of avail and access = (average of (rank of government success in ICT promotion; rank of government online service index; rank of ICT use and government efficiency; rank of presence of ICT in government agencies; rank of e-participation index) and average of (rank of availability; and rank of accessibility)). In order to assure the differences between the two sets, a second method was used. Table 5 presents the results of Friedman and Kendall s W tests. These tests were applied on the rank of the variables. The first row (All Ranks) contains the result of whether a difference among the distributions of all seven ranks exists or not. Results show that there is a statistically significant difference at the 0.05 level. Next, the second row contains the result of whether there is a difference among the ranks of the variables that are related to ICT usage by governments (Rank of Government success in ICT promotion; Rank of Government online service index; Rank of ICT use and government efficiency; Rank of Presence of ICT in government agencies; Rank of E-participation index). Result shows that there is no statistically significant difference among this set of ranks. Next, is the result of whether there is difference between the rank of availability and the rank of

15 E-government effectiveness 15 accessibility. Based on Table 5 there is no statistically significant difference among this set of variables. Whereas, the last row shows that there is a statistically significant difference between the average rank of the five variables that are related to ICT usage by governments and the average rank of accessibility and availability. These results simply confirm the fact that these two sets are separate. Thus, despite the correlations found between the variables, these results came about to ensure the results found in the canonical correlation which indicate that differences exist. After assuring the differences between the two sets, multiple regression method is used to answer the last two research question: 1 What are the factors that affect availability and accessibility? 2 What are the factors that affect the ranks of the countries? Table 6 shows the results of the first multiple regression test. The rank average of accessibility and availability was used as a dependent variable and the independent variables were: government success in ICT promotion; government online service index; ICT use and government efficiency; Presence of ICT in government agencies; e-participation index. The regression analysis had R 2 of and adjusted R 2 of 0.774, which is statistically translated to mean 77% contribution of the total variance are to rank average of accessibility and availability. Also, the F-statistics produced (F = ) which was significant at 0.01 level (Sig. F = 0.000), thus confirming the fitness for the model. Table 6 Multiple regression result Source Sum of square df Mean square F-ratio Significance Regression 141, , Residual 39, Total 180, Notes: R =.885; R 2 =.783; adjusted R 2 =.774; SE = Homoscedasticity = 0.98; VIF = Variables Unstandardised co-efficient Standardised coefficient B Std. error β t Significance Constant Gov t success Gov t online service ICT & gov efficiency Presence of ICT E-participation Notes: Dependent variable: (rank average of accessibility and availability); Independent variables: (government success in ICT promotion; government online service index; ICT use and government efficiency; presence of ICT in government agencies; e-participation index). Moreover, the results indicated that there were three variables that are associated with the rank average of accessibility and availability. These variables are namely, government online service index; presence of ICT in government agencies;