Synthesizing Success Factors for e-Government Initiative

By using Meta-Ethnography, this study attempt to synthesize some studies to get the generic list of success factors for e-Government initiative. The initiative to develop an e-Government system has been proliferated in several countries. However, a lot of e-Government initiatives are fail. Several success factors should be accommodated to avoid the failures. There have been some researchers who tried to formulate various kinds of success factors that related to e-Government initiative. However, all of those success factors are scattered in various studies in form of conference papers or journal articles. There were 46 studies were included in this study. All of them are considered to be related in reciprocal translation. There are 335 concepts of success factors that obtained from the included studies. Those concepts further be translated and synthesized. As the foremost result, 36 success factors for e-Government initiative are obtained. Those 36 success factor should be accommodated by all parties that involved in the e-Government initiative.


INTRODUCTION
E-Government is relatively a new research area (Al-Shehry et al., 2006).e-Government is still an exploratory knowledge field and is consequently difficult to define it accurately.Nowadays, there are a lot of institutions that define what e-Government is.The United Nation (UN) defined e-Government as the use of Information and Communication Technology (ICT) and its application by the government for the provision of information and public services to the people (UN, 2005).The European Union (EU) defined e-Government as about using the tools and systems made possible by ICTs to provide better public services to citizens and businesses (EU, 2012).
Some researchers also have defined what e-Government is.Heeks (2006) said that e-Government is the use of Information Technology (IT) by public sector organizations.Another definition come from Shahkooh and Abdollahi (2007), they said that e-government is a use of IT to provide better and faster online services in addition to information for citizens, businesses and employees by government.Heeks (2006) said that e-Government is also an information system.However, e-Government is different from ordinary information system that is generally targeting the private sector.The main orientation of e-Government is the accessibility of information by the public, rather than financial income (Heeks, 2006).
Because of its relation with ICT, then most people thought that e-Government is part of computer science.However, in addition to computer science, there are many other scientific fields in e-Government, for example public administration, management, politics, socio culture, etc. e-Government research topics can also include technical, organisational, social and economic issues (Wicander, 2001).
e-Government has become an emergent multidisciplinary field of research (Assar et al., 2011).e-Government is not simply introducing web-based technologies to government, but it is also considered as a complicated social system which covers main social issues (Fasanghari and Habibipour, 2009).e-Government has become a global phenomenon that consumes the attention of, e.g., governments, politicians, policy makers, businesses, citizens, as well as researchers from different research disciplines (Lofstedt, 2008).The research field of e-Government is rather broad and several researchers have involved in a range of different research projects on different topics within the field (Lofstedt, 2008).
Although theoretical ground is still under construction, e-Government certainly qualifies as a legitimate emerging scientific discipline (Assar et al., 2011).As technological innovations are continuously grow, the frontiers of the e-government discipline are moving and its multidisciplinary nature is confirmed (Assar et al., 2011).
Currently, the initiative to develop an e-Government system has been proliferated in several countries, both in developing countries and developed countries.The development of e-Government system can support the government's performance in serving the public.
It is implied by Heeks (2006) that a lot of e-Government system development initiative are fail.Therefore, we propose that in order to avoid failure, developers of an e-Government system should accommodate various kinds of success factors.In accordance with the multidisciplinary nature of e-Government, the success factors are not only related to ICT.Some success factor can be derived from social science, economics, politics and so forth.
Until now, there have been several researchers who tried to formulate various kinds of success factors in e-Government initiative.However, all of the success factors are scattered in various conference papers and journal articles.Therefore, in this study, by using Meta-Ethnography, we attempt to synthesize several related conference papers and journal articles to get the generic list of success factors for e-Government initiative.

Critical success factor and key success factor:
Currently, there are two terms that are often used by many researchers, i.e., Critical Success Factor (CSF) and Key Success Factor (KSF).In this section, we will try to do a review of the two terms.From the results of this review, then later we decided to use a more general term, which is "success factor".The term "success factor" is then will be used in the subsequent sections in this study.
Some researchers agree that the CSF term first appeared in the study of Daniel (1961), Geetika (2006) Horst (2007b) and Gates (2010).Furthermore, the CSF term was refined into a concept and popularized by John F. Rockart and the MIT Sloan School of Management in 1979 (Schelin, 2004;Geetika, 2006;Horst, 2007b;Gates, 2010;Azizan, 2011).Bullen and Rockart (1981) described in more detail about the CSF concept in their report entitled "A Primer on Critical Success Factors".In that report, the definition of CSF is "the limited number of areas in which satisfactory results will ensure successful competitive performance for the individual, department or organization" Bullen and Rockart (1981).They also said that CSFs are the few key areas where "things must go right" for the business to flourish and for the manager's goals to be attained (Bullen and Rockart, 1981).
Currently, there are several other researchers that also give the definition of CSF.Generally they linked CSF with an organization.Elmeziane et al. (2011) said that CSF is something that the organization must do well to succeed.CSFs are a means for organizations trying to reach success by fulfilling a set of important factors that previous experiences have shown to be decisive for success (Axelsson et al., 2011).CSFs are the indispensable business, technology and human factors that help to achieve the desired level of organizational goals and highly dependent on the company's situation (Icli, 2005).CSFs are used by organisations to focus on a number of factors that help to define and ensure the success of the business (Nfuka and Rusu, 2010).CSF is a business term for an element which is necessary for an organization or project to achieve its mission (Jha and Shivani, 2007).The different definitions of CSF's due to the ambiguity of the word "critical" when translated into other languages (Al-Kaabi, 2010).
Some researchers have linked the CSF with a project or initiative.For example, Schelin (2004) said that CSFs are those few items that must been handled correctly in order for a project to succeed.The similiar expressions are also stated by McMillan (2009) and Akhavan et al. (2010).
CSFs are important in the planning stages of a project or initiative (Geetika, 2006).As also revealed by Basahel (2009), that the main strength of CSF analysis is its planning support.Managers need to realise all of the CSFs in order to successfully complete an activity (Basahel, 2009).Thus, the identification of CSFs is generally done before a project or initiative is started.
Based on the above definitions, the CSF concept looks related to the management and business science.However, CSF concept can also be used in other disciplines, one of which is in information system.Elmeziane et al. (2011) revealed the need for CSF in information system projects.CSFs are also considered as factors those occurrences whose presence or absence determines the success of an ICT project (Gichoya, 2005).The absence of CSFs can cause failure and their presence can cause success (Gichoya, 2005).
Since e-Government is also information system, the CSF concept can also be used in the e-Government initiative.Microsoft Corporation (2010) stated that CSF is a checklist that every government organization must manage if it is to develop and deliver an effective program for citizen service transformation.
The term other than CSF is KSF.Some definitions of KSF are likely spesific to industral field, such as that have been revealed by Ho andWang (2009) andPatterson Jr andTonder (2009).Ho and Wang (2009) said that KSFs are defined as the characteristics, conditions, or managerial variables that need to be maintained to achieve prosperity in a given industry.Patterson Jr and Tonder (2009) said that KSFs are defined as those that directly impact the ability of a firm to be successful in its specific industry.However, Huang et al. (2011) said that KSF is also can be used in other fields.They said that KSF is a strategic tool that can be applied in a number of fields to detect issues that are important for a long-term success (Huang et al., 2011).Bacsich (2009) considered KSF as subordinate or the more specific term than CSF.However, in some other literatures, the terms CSF and KSF are often used interchangeably (Lin, 2007), for example that have been revealed by Kumar et al. (2002), Warda and Mitchell (2004), Tokdemir (2009), Gates (2010), Amiri et al. (2010) and Aziz and Salleh (2011).
A lot of researches Lin (2007), Jingjing (2006) and Wu et al. (2010) adopted the KSF term from the work of Grunert and Ellegaard (1992) defined KSF as "a skill or resource that a business can invest in, which, on the market the business is operating on, explains a major part of the observable differences in perceived value and/or relative costs".Interestingly, in that report, Grunert and Ellegaard (1992) refer to the research of Bullen and Rockart (1981).As explained at the beginning of this section, Bullen and Rockart use the CSF term in their study.Thus, it can be concluded that KSF is closely related to CSF.
Because KSF is closely related to the CSF, then in this study, we will not stuck to choose between one of them.We will not debating whether to use the term "key" or "critical".We will use the more general term that is "success factor".This more general term will be used in the later sections in this study.

LITERATURE REVIEW
Currently, there are already some success factors for e-Government initiative that has been formulated by other researchers.However, all of those success factors are scattered throughout the various conference papers and journal articles.Those studies differ greatly in the sets of factors identified and provide no coherent overall picture.For example, Gil-Garcia and Pardo (2005) have formulated 23 CSFs that associated with the e-Government initiative.On the other hand, Yoon and Chae (2009) formulated 15 CSFs.Both of those studies were conducted on two different years, that is on 2005 (Gil-Garcia and Pardo, 2005) and the other is on 2009 (Yoon and Chae, 2009).
If we dig a little deeper, there are some CSFs were expressed by Gil-Garcia and Pardo (2005) shared the same essence with some CSFs that are expressed by Yoon and Chae (2009), though all of them have different name.For example, in the research of Gil-Garcia and Pardo (2005), there is CSF named "Wellskilled and respected IT leader (technical and social skills)" and in the research of Yoon and Chae (2009), there is CSF named "Human Capital".Although, both CSF has a different name, but the essence is the same, that is the need of "qualified technical staff in e-Government initiative".In addition to the the two previous CSFs, in both these journal articles, there are still some other CSFs, whose name are different but essentially the same.Thus, we can synthesize these two journal articles to obtain the general success factor from the two of them.
The above example is only of two journal articles.In fact, there are also many other conference papers or journal articles that also formulate success factors for e-Government initiative, such as that have been written by Gunasekarana and Ngai (2008), Meneklis and Douligeris (2009) and Rorissa and Demissie (2010), etc.Therefore, this study tried to make a synthesis of some conference papers and journal articles that have formulated success factor for e-Government initiative.Confererence papers and journal articles that are involved in this synthesis are drawn from ScienceDirect/Scopus database (for journal articles) and IEEE Xplorer (for conference papers).
It can be said that the literature review and interview method are produce qualitative data.Therefore, there are some researchers who add various qualitative mode of analysis to formulate their success factors.For example, Zarei and Ghapanchi (2008) use grounded action research (a modified form of original grounded theory) to process their interview data.Another example is by Reinwald and Kraemmergaard (2012), they use original grounded theory to process their data.On the other hand, data that resulted from questionnaire using likert scale method is quantitative data.Therefore, some researchers generally also add a variety of quantitative calculations to do the data analysis of their questionnaire results.For example, Hung et al. (2009) and Lin et al. (2011).They use Structural Equation Modeling (SEM) to process their questionnaire results.However, until now, there has been no study that uses Meta-Ethnography in formulating their success factors.Therefore, in this study, we will use Meta-Ethnography for synthesizing various success factors for e-Government initiative.

RESEARCH METHODOLOGY
The methodology that will be used in this study is Meta-Ethnography.This methodology was first introduced by Noblit and Hare (1988).Meta-Ethnography has origins in the interpretive paradigm (Noblit and Hare, 1988;Britten et al., 2002;Tuquero, 2011).This methodology is perhaps the most established and explicit form of interpretative review (Beck, 2002;Tuquero, 2011).
Meta-Ethnography included in the qualitative synthesis and is not the same as ordinary literature review (McDermott et al., 2004).A literature review summarises findings to make an informed assessment about the current state of a field of knowledge (McDermott et al., 2004).However, the goal of qualitative synthesis is to go beyond (Britten et al., 2002).Qualitative synthesis is done to draw out and integrate findings across studies in ways that generate new insights and understandings (McDermott et al., 2004).
Meta-Ethnography involves the translation of studies into one another.The translation of studies takes the form of an analogy between and/or among the studies (Noblit and Hare, 1988).In Meta-Ethnography, the studies to be synthesised are treated in a similar way to primary data (Malpass et al., 2009).Meta-Ethnograpy has allowed us to take concepts that often appear in isolation in research papers to be linked together and put into a meaningful theoretical model (Tuquero, 2011).
Meta-Ethnography originally is used specifically for studies that are qualitative (Noblit and Hare, 1988;Dixon-Woods et al., 2005).However, it now can also be used to quantitative study or mixed of them.Examples of study that using Meta-Ethnography for both qualitative studies and quantitative studieas is a study that conducted by Ardal et al. (2011).In their study, Ardal et al. (2011) determined that the most relevant method to synthesize the studies was to focus on the findings or conclusions of the articles, keeping in mind the context in which the conclusions were made.Treating the findings in this way (especially for quantitative studies) allowed them to use Meta-Ethnography (Ardal et al., 2011).
Meta-Ethnography is interpretive and more widely used in the social sciences.However, Meta-Ethnography now begun accepted and can be used in computer science related study, for example that have been conducted by Tuquero (2011), Ardal et al. (2011) and Shahkooh et al. (2011).
Meta-Ethnography consists of seven steps.i.e., (Noblit and Hare, 1988): • Getting started: The meta-ethnographer have to identify an intellectual interest (Noblit and Hare, 1988).Its about identifying the research topic (Britten and Pope, 2012) or the main interest of his/her study (Tuquero, 2011).

• Deciding what is relevant to the initial interest:
In this step, the meta-ethnographer decides what is relevant to initial interests, including what studies to include (Vermeire et al., 2007).Some of the searching process using a variety of electronic scientific databases can be done in this step, as illustrated by Beck (2002), Barnett-Page and Thomas (2009), Gagne and Walters (2009) and Tuquero (2011).Searching can be performed using a variety of keywords that associated with the initial interest.• Reading the studies: This step is about the repeated reading of the selected literature and the noting of the interpretative metaphors (Noblit and Hare, 1988).Those interpretive metaphors are can be in the form of concepts (Campbell et al., 2003).
Those concepts become the raw data for the synthesis (Campbell et al., 2003;McDermott et al., 2004).• Determining how the studies are related: In doing a synthesis, the various studies must be "put together."This requires determining the relationships between the studies to be synthesized (Noblit and Hare, 1988).This step involve creating a list of the key metaphors, phrases, ideas and/or concepts (and their relations) used in each account and to juxtapose them (Noblit and Hare, 1988).
Near the end of this phase, an initial assumption about the relationship between studies can be made (Noblit and Hare, 1988).Those asumstions are: reciprocal translation, refutational translation or line of argument (Noblit and Hare, 1988).o Reciprocal translation: This assumption applies when the accounts (concepts) of the studies are directly comparable and similar (Noblit and Hare, 1988;Edwards et al., 2009).o Refutational translation: That is where accounts may conflict (Edwards et al., 2009).They stand in relative opposition to each other (Noblit and Hare, 1988).o Line of argument: This assumption applies when the accounts of the studies are: not directly comparable, doesn't opposite each other and about so different topics (Noblit and Hare, 1988).A lines-of-argument synthesis is essentially about inference: "What can we say of the whole (organization, culture, etc.), based on selective studies of the parts?"Noblit and Hare (1988).
Once the initial strategy yields a tentative assumption about the relationships between the studies, the next strategy is to construct translations based on this assumption (Noblit and Hare, 1988).• Translating the studies into one another: In its simplest form, translation involves treating the accounts as analogies: "One program is like another except…" Noblit and Hare (1988).On the other hand, translation is more involved than an analogy (Noblit and Hare, 1988).Translations are especially unique syntheses, because they protect the particular, respect holism and enable comparison (Noblit and Hare, 1988).It entails with discovering the relationships between two existing texts (Noblit and Hare, 1988).In Meta-Ethnography, the concern of translation is primarily with idiomatic translations (Noblit and Hare, 1988).It is not literal (Noblit and Hare, 1988) or word-for-word translation (Campbell et al., 2003).It is about translating the meaning of the text (Noblit and Hare, 1988).Such idiomatic translation is what enables us to retain the holism so essential to interpretivism (Noblit and Hare, 1988).
It can be said that the term 'translating' can refers to the process of taking concepts from one study and recognising the same concepts in another study, though they may not be expressed using identical words (Thomas and Harden, 2007).The purpose is to try to derive concepts that encompass more than one of the studies being synthesised (Campbell et al., 2003).• Synthesizing translations: Synthesis refers to making a whole into something more than the parts alone imply (Noblit and Hare, 1988).Synthesis is the step of compiling the findings of the included studies (Ardal et al., 2011).When the number of studies is large and the resultant translations numerous, the various translations can be compared with one another to determine if there are types of translations or if some metaphors and/or concepts are able to encompass those of other accounts (Noblit and Hare, 1988) • Expressing the synthesis: Synthesis can be expressed in various ways, for example drama, video and text among them (Noblit and Hare, 1988).Nonetheless, most of meta-ethnograher will do this step be in the form of written texts (Noblit and Hare, 1988).As implied by Tuquero (2011), that writing a scientific paper is one of the ways to express the results of synthesis.

RESULTS AND DISCUSSION
Getting started: The purpose of this research is to obtain the generic list of success factors for e-Government initiative.Success factors will be synthesized from several related studies.There are the two groups of studies to be synthesized, i.e., journal articles or conference papers.Those studies are searched and retrieved from credible scientific databases.

Deciding what is relevant to the initial interest:
Studies in the form of journal articles are searched and Fig. 1: Ilustration of the seraching and filtering results retrieved from ScienceDirect/Scopus database, while studies in the form of conference papers are searched and retrieved from IEEE Xplorer.We only retrieve some studies that are significantly related to the success factor for e-Government initiative.
When performing the search, there are some key words/phrases are used, such as "e-Government" and "success factor".As outlined in Section II of this study, we do not distinguish between CSF and KSF, so that the two terms (i.e., "CSF" and "KSF"), are also involved in the key words of the search.
It has outlined in Section III of this study, that researchers can use qualitative approach or quantitative approach to formulate their e-Government success factor.Therefore, in this study, both studies that using qualitative approach and/or quantitative approach will be included.This conforms with the example of Ardal et al. (2011) that Meta-Ethnography can be used for qualitative and quantitative research.
Based on the results of the searching process, we obtain 278 studies.Two hundred and thirty two of them are journal articles and the other 46 are conference papers.Then, we further filter the searching results by reading their title, abstract, result and conclusion.As a result of this filtering process, we obtain 28 journal articles and 18 confererence paper which we think are relevant to the main interest of this study.All of the 46 studies that resulted form filtering process are then used in the next step.The illustration of the searching and filtering results can be seen in Fig. 1.

Reading the studies:
In their book, Noblit and Hare (1988) pointed out that there could be some key concepts exist in a study that using Meta-Ethnography.However, in this study we only focus on one key concept, that is "succes factor".
In this step, we read all the 46 studies repeatedly and we note some concepts that related to the key concept ("success factor").Eventually, we obtain 335 concepts from those 46 studies.In addition, we also mark the reasons or explanations of each authors about why their concept can be considered as success factor for e-Government initiative.Those reasons or explanations will be very useful in subsequent steps.
Determining how the studies are related: At this stage, we follow what has suggested by Noblit and Hare (1988), that is to create a table that contains the key concept and concepts from 46 studies.The list of concepts from those 46 studies can be seen in Table 1.Noblit and Hare (1988) imply that the metaphoric reductions can be done as long as it has ability to portray the essence of the texts.Therefore, some of the words used in the concepts in Table 1 is the result of the modification and adoption of their original words.Nevertheless, some of the other concepts are still using their original words.
In this step, we also do some comparations among the emerging concepts accross the studies.In this case, we also use the reasons or the explanations that given by each author to understand the relationship among their studies.In can be conclude that a lot of their concepts are relatively similiar, so that we determine that all of the studies are related in reciprocal translation.
Translating the studies into one another and synthesizing translations: As suggested by Noblit and Hare (1988) that in practice, some of the Meta-Ethnography steps are overlapping and may be parallel.Therefore, in this study, we will perform the fifth step (translating) and the sixth step (synthesizing) simultaneously.In this step, we also still consider all the reasons or the explanations of each author on their success factors.
By using the similar way with the above example, then we do the translation and the synthesization process to all of the other concepts.As the result, we get 36 new sythesized concepts.These 36 new sythesized concepts are the success factors for e-Government initiatives.The result of this translation and synthesization process can be seen in Table 2.
Expressing the synthesis: This study is an expression of the synthesis, including what have been resulted in Table 2.In that table, the rows indicate the studies, while the columns indicate the synthesized success factor.In order for the Table 2 is not too wide, then we represent every study by a number.That number is associated with the number in Table 1.We also represent each success factor by a code.List of the codes of success factors and their meanings can be seen in Table 3.
Every success factors in Table 2 are supported by some of the concepts within and across the studies.The numbers listed in each cell in Table 2, shows concepts of a study that support a particular success factor.We can figure out the literal word of those concepts by referring back to Table 1.All of the success factor that depicted in Table 3, have the same degree.No one is more important and less important, all of them are equal.

CONCLUSION
By using Meta-Ethnography, a lot of relevant previous studies has been synthesized to get a generic list of 36 success factor for e-Government initiative.This is the foremost contribution of this study.In practice, the synthesized success factors of this study can assist all parties that involved in the e-Government initiative.
This study has successfully demonstrated that Meta-Ethnography can be used in e-Government research.It advances the body of knowledge in e-Government research.The way we use to implement the each step of Meta-Ethnography, can be considered by other researchers to conduct similar research.
This study can lead to a lot of further research.For example, as empirical study, a case study research can be conducted to test whether all success factors in this study occur in an e-Government initative.On the other hand, a pilot project of e-Government inititiave can also be conducted by considering all of the success factors of this study, the results of the pilot project are analyzed.

Table 1 :
The concepts across 46 studies

Table 2 :
The result of translation and synthesis Code of the success factor -