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The widely shared definition of e-Government An exploratory study

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Purpose – This paper aims to provide details of a study on the widely shared definition of e-government and to help scholars – especially young scholars – to understand the scope and meaning of the field. Design/methodology/approach – From 1998-2007, a ten-year time-span, 632 articles from the three world-leading academic databases, including Wiley InterScience, Elsevier ScienceDirect, and SCI Expanded, were retrieved and 324 were analyzed using CATA software (Concordance 3.20), to identify the vocabulary that was used frequently by e-government scholars. Then the distinct vocabulary was used to construct the widely shared definition of e-government. Findings – In those 324 articles, 57 words generated from the text analysis formed the basis for imputing a widely shared definition of the field of e-government. The definition was conceptualized by six elements. Research limitations/implications – Two limitations of the pool of articles selected may be noted. First, articles were drawn from three leading academic databases in an effort to distinguish e-government from other fields; but such an approach omitted any consideration of how e-government definitions varied from different academic fields. Second, because the pool of articles was drawn only from these three, journals excluded by these databases were thus omitted. Originality/value – The study is unique in that it discusses the definition of e-government by an exploratory approach. The universal shared definition extracted could serve as either a screen or a magnet for future research. And the methodology could be applied to several academic fields, including administration and management, library and information science, e-records management, computer science, etc.
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The Widely Shared Definition of e-Government:
An Exploratory Study
Guangwei Hu, Department of Information Management, Nanjing University, Nanjing, China
Wenwen Pan, Department of Business Administration, Nanjing College for Population Program
Management, Nanjing, China
Mingxin Lu, Department of Information Management, Nanjing University, Nanjing, China
Jie Wang, Department of Computer Science, University of Kentucky, KY, USA
Abstract
Purpose The paper aims to provide details of a study on the widely shared definition of
e-government and to help scholars- especially young scholars- to understand the scope and
meaning of the field.
Design/methodology/approachFrom 1998 to 2007, 10 years time-span, 632 articles from the
three world-leading academic databases, including Wiley InterScience, Elsevier ScienceDirect,
and SCI Expanded, were retrieved and 324 were analyzed using CATA software, Concordance
3.20, to identify the vocabulary that was used frequently by e-government scholars. Then we used
the distinct vocabulary to construct the widely shared definition of e-government.
FindingsIn those 324 articles, 57 words generated from the text analysis formed the basis for
imputing a widely shared definition of the field of e-government. The definition was
conceptualized by six elements.
Originality/value This study is unique in discussion on the definition of e-government by an
exploratory approach. The universal shared definition we have extracted could serve either as a
screen or as a magnet for future research. And our methodology could be applied to several
academic fields, including administration science, library science, management science, computer
science, etc.
Keywords e-government, text analysis, widely shared definition, compared analysis, exploratory
study
Paper type Research paper
Introduction
An academic field has socially negotiated boundaries and only exists if a critical mass of scholars
believes it to exist and adopts a shared conception of its essential meaning (Astley, 1985).
However, such shared meaning is far from assured since various forces can dilute or blur its
consensus. These forces might include heterogeneity of members’ training, the intellectual pull
and hegemony of adjacent fields, and an ever-shifting body of knowledge and theory (Astley, 1985;
Whitley, 1984).
E-government represents a case of an academic field whose meaning might be blurry and lacking.
The field is comparatively young, having been re-conceptualized and relabeledfrom “reinventing
government’ movementby the National Performance Review (NPR) Report in 1993 (Yildiz, 2007).
Its disciplines of interest overlap with several other vigorous fields, including information science,
computer science, management science, software engineering, library science, etc., and its
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participant members have been trained in widely varying traditionssome in academic institutions,
some in government departments, some in enterprise departments, and so on. It is little surprise,
then, that the published, approbatory definitions of e-government are various. And we can
anticipate that asking e-government scholars to define the field might elicit an array of
responses.
How, then, does the field of e-government maintain its collective identity and distinctiveness?
The answer, we anticipate, is that there is a strong explicit essence of the field, even though
there may be ambiguity about its widely shared definition.
E-government really is a young, rapidly expanding field. However, there is a substantial need for
discussion and reflection regarding the very nature of the field; scholarsespecially young
scholarsneed a signpost to help them understand the scope and meaning of the field. What does
it mean to be doing research in e-government? What does it take to be seen as an e-government
scholar? While prior analyses have examined the rise and fall of specific theories or research
topics within e-government (e.g., Funtain, 2001, p.4; Hughes, 2004, pp. 75-78; Relyea, 2002; Yildiz,
2007; Anthopoulos, et al., 2007; Mnjama and Wamukoya, 2007), in this paper we pursue a more
fundamental objective: to identify the widely shared meaning of the field.
To achieve this objective, we conducted an exploratory study. In this study, we collected a large
number of e-government field articles from the three world-leading academic databases,
including Wiley InterScience (InterScience), Elsevier ScienceDirect (ScienceDirect), and SCI
Expanded (SCI-E), to retrieve 632 abstracts. As to whether the articles were in e-government or
not, then, we assessed them into four categories (clearly not an e-government article, probably
not an e-government article, probably an e-government article, and clearly an e-government article)
according to their titles, abstracts and key words. Subsequently, using automated text analysis,
we identified the distinctive lexicon of the field, which in turn allowed us to derive the widely
shared definition of e-government, as held by its members. Finally, we turned to existing
definitions of e-government to observe the conceptual elements used by field scholars and draw
the final definition of e-government from the distinctive lexicon of the field. We concluded the
paper by discussing the definition and implications of our analyses for the field and proposing
further research orientation.
This study is unique in discussion on the definition of e-government by an exploratory approach.
The universal shared definition we have extracted could serve either as a screen or as a magnet
for administrators, librarians, information specialists or other scholars in their future vocation or
research work. And our methodology could be applied to several academic fields, including
administration science, library science, computer science, information science, etc. It can also
help us understand the collective identity of the field that its members share the identity that
give members a fundamental sense of who they are as a community and how they differ from
other communities.
Literature Review: Past efforts to define the field
From 1998 to 2007, 10 years time-span, about 2000 articles (404 from SCI-E, 1483 from
ScienceDirect, and 52 from InterScience) discuss the subjects of “e-government”, which involve
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several sub-categories. However, because of lacking of subject analysis in ScienceDirect and
InterScience, we got the analysis result on 11/23/2007 from SCI-E as an example (See Fig. 1).
The figure indicates more than 59.65 percent articles belong to computer science, theory and
methods, nearly 10.50 percent are related to information science, 3.71 percent can be classified
to social science, nearly 3.22 and 1.50 percent separately belong to management and business, and
so on.
TAKE IN FIGURE 1
About the theory context of e-government, it is can be traced back to 1993. Since 1993, the
developments emerging from the recent government reinvention experience is so-called
electronic government”, “e-governmentor “e-Govcommonly called “e-government”.
Subsequently, the report of the National Performance Review (NPR) introduced the new term
(Relyea, 2002). Then, it oftentimes came to be used as a symbol, reference to both current
applications of IT in government operations and a goal of realizing more effective and less costly
performance of government functions (Yildiz, 2007). United Nations (UN) and professor West
(Brown University), from 2001 to 2008, continuously published their annual reports of global
e-government progress. And scholars have conducted numerous analyses of the field. These works
primarily have attempted to examine the intellectual ebbs and flows, research trends,
perspectives, philosophies, theories, methods, and practices of the field (Fountain, 2001, p. 4;
Allen, et al., 2001; Chen and Gant, 2001; Wimmer, 2002; Jaeger, 2002; Gronlund, 2003; Kersten,
2003; Vriens and Achterbergh, 2004; Gil-Garcia and Pard, 2005; Evans and Yen, 2006; Otjacques
et al., 2007; Yildiz, 2007; Huang and Shyu, 2008).
Among these various discussions, for example, Allen, et al. (2001) analyzes that the rise of
e-government referring to the new, possible patterns of decision-making, power sharing and
coordination. Heeks and Bailur (2007) use content analysis of 84 papers in e-government-specific
to research five main aspects: perspectives on the impacts of e-government, research philosophy,
use of theory, methodology and method, and practical recommendations.
However, there is not any widely shared definition of the field yet (Halchin, 2004). Similarly,
Wimmer (2007) debates that “Everybody talks about e-government, but all have different
interpretations”. In order to cover the variety of uses and the nuances sufficiently, several
definitions are presented below. E-government is defined as “utilizing the Internet and the
World-Wide-Web for delivering government information and services to citizens” (UN, 2002). It
may also include using other ICTs in addition to the Internet and the Web, such as “database,
networking, discussion support, multimedia, automation, tracking and tracing, and personal
identification technologies” (Jaeger, 2003).
E-government is also perceived differently in connection with its theoretical background.
According to Garson (1999), there are four theoretical frameworks within which e-government is
conceptualized. The first framework involves the potential of IT in decentralization and
democratization. The second normative/dystopian framework underlines the limitations and
contradictions of technology. Third, the socio-technical systems approach emphasizes the
continuous and two-way interaction of the technology and the organizationalinstitutional
environment. The fourth framework places e-government within theories of global integration.
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The Appendix presents a selected set of definitions including Fountain’s (2001, p. 4) definition of
public administrative field and institutional field.
As important as all these prior analyses have been, they have omitted any attention to a
fundamental question: is there one definition that could be widely accepted for domain experts?
Lack of attention to the essence of the field is noteworthy for a third reason: first, e-government
is a concept defined by the objective of the activity (i.e., transfer of government information and
services among governments, their customers and suppliers), rather than by the specific
technology used, provider of the service/information, or clear-cut activities of the related actors
(Yildiz, 2007). Hence, many definitions of e-government are rather loose and gloss over the
multiple meanings (Torres et al., 2005).
Secondly, e-government is one of those concepts that mean different things to different groups
(Grant and Chau, 2005). For instance, Professor Perri 6 (2001) identifies different parts of
e-government as e-service delivery, e-democracy, and e-governance. Rapid technological changes
also make it difficult to “fully grasp the meaning, opportunities and limits of the concept” (Prins,
2001, pp.1-5).
Thirdly, as if it is not enough for the real substance of the concept to be ambiguous, poorly
defined and/or context-dependent, e-government contains much hype and promotional
efforts/literature as well, similar to the concepts of “knowledge management” (Lev, 2000; Lissack,
2000) or “management by objectives” (Miller and Hartwick, 2002).
Although these definitions are not flatly incompatible with each other, they are sufficiently
divers as to convey ambiguity in what the field of e-government is all about, as well as how it
differs from other closely related fields. It is a puzzle, then, as to how the field can survive, much
less flourish. But flourish it does. E-government has its relevance highly regarded refereed
journals, such as
Government Information Quarterly
(GIQ),
Public Administration Review
(PAR),
Information System Research
(ISR)
, information & Management
(I&M)
, The Information Society
(TIS)
,
Journal of Librarianship and Information Science
(JLIS)
, Library & Information Science
Research
(LISR), and
Social Science Computer Review
(SSCR). How can an academic field that,
by all appearances, lacks a clear and agreed-upon definition maintain its momentum?
This puzzle is answered if, as we anticipate, e-government scholars have a widely shared meaning
of the field. Despite varied theoretical and methodological approaches, and despite an absence of
any agreed-upon extant definition, e-government scholars can be expected to have a widely
shared understanding, a common worldview, of what makes up their field. This universal
understanding, as we show in following study, can be used to impute a widely shared definition of
the field. It can also help us understand the collective identity of the field that its members
share the identity that give members a fundamental sense of who they are as a community and
how they differ from other communities.
Method
The philosophy of this study
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Our primary point of departure is the premise that a scientific field is a community of scholars
who share a common identity and language. Some have gone to the extent of describing academic
communities as “tribes”, or “intellectual villages”, replete with their own peculiar cultures, norms,
and language (Becher, 2001). Essential to the concept of paradigm is the existence of commonly
shared goals, values, and norms that demarcate the members of the community holding that
paradigm, from other scientific and non-scientific communities (Nag et al., 2007). The scope and
boundaries of a scientific community are strongly influenced by the specialist knowledge and
technical norms of its members (Shapin, 1995).
If we assume that scientific knowledge is socially constructed, then language, in the form of
scientific discourse, is the fundamental medium that makes that social construction possible
(Grace, 1987). Language provides the basis for the emergence of a distinctive identity shared by
members of a scientific community. Astley (1985) asserted that scientific fields are “word
systems” created and maintained by their members.
If it is through language that members of an academic field express their ideas, then it is also
through language that the very essence, or definition, of the field can be identified. Members of
an academic field should be able to examine a body of texteven out of contextand, using the
language in that text, conclude whether the text represents work in their field (Nag et al., 2007).
This is not to presume that all members of the field will favor the same theories, methods, and
styles of research, but rather that they will be able to conclude whether a given text is part of
their shared conception of the field. Then, other analysts should be able to work backwards: using
the members’ conclusions about whether individual texts come from their field, the analysts
should be able to identify and assess the distinctive language that gave rise to the members’
conclusions, thus imputing the members’ conceptions of what makes up their field. This is the logic
we applied in conducting following study.
Overview of method
The study involved multiple steps. First, we searched a large number of e-government papers with
key word “electronic government”, “e-government”, “eGovernment”, “e-Governance”,
“eGovernance”, “e-Gov” and “eGov” in those three world-leading academic databases. Then, we
selected 632 articles as samples to analysis. In InterScience, ScienceDirect and SCI-E, there are
52, 1482 and 404 articles published in time-span of 10 years. Based on the relevance degree
between keywords and article topics, in InterScience, 57.69 percent, 32 articles were selected; in
SCI-E, 74.26 percent, first 300 articles were draw to analysis; while in Elsevier, 1482 articles
were found, but these articles were indexed by not only key word “e-government” but also key
words including “government” and “e”, etc. So as to guarantee the articles selected suitably to
analysis, first 300, about 20.23 percent were chosen as analyzed objects. The summary of
searched and selected articles shows as table I.
TAKE IN TABLE I
As to those 632 articles, quite a few, according to our scanning, were not suitable for further
analysis because of their abstracts absence, titles repetition, topic irrelevance, etc. Filtering
works had been done and all of the articles were categorized into 4 categories (Cat. 1~Cat. 4) as
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following:
Cat. 1 :
Articles, whose abstracts were absence or purely about e-business, government
financing, government partnerships, online electronic banking system etc., clearly not
e-government articles, were rated “1” (including 232 articles).
Cat. 2:
Articles, which related to government spending, government electronic tendering
system, government information, federal information policy, information availability etc.,
probably not e-government ones, were rated “2” (including 36 articles).
Cat. 3:
Articles, which were relevant to government information system, web-based
government publications, data sharing among organizations, urban information integration,
E-disclosure laws, CRM in local government, etc., probably e-government ones, were rated “3”
(including 40 articles).
Cat. 4:
Articles, which topic were about e-government, government e-services, e-government
service, e-local government, digital government, government Web sites, E-Governance, etc.,
clearly e-government articles, were rated “4” (including 324 articles).
In this study, just the articles rated “4”, 324 (10 from InterScience, 109 from ScienceDirect, and
205 from SCI-E) were used for further analysis (See Table II).
TAKE IN TABLE II
Second, we random divided those 324 abstracts into two control groups (Group A and B) and one
group included 162 articles; then, using automated text analysis, we conducted a lexicographic
analysis of their abstracts, through which we identified the “widely used vocabulary” of the field
of e-governmenta set of 57 words that appeared in e-government abstracts with significantly
frequency. Then, moving iteratively between prior definitions of the field and our own
interpretation of how the 57 words could be placed into conceptual categories, we identified six
elements that constitute the final definition of e-government. Finally, we discussed the definition
and interpret the means of these six sub-elements.
Data Collection and Analysis
Identifying E-government Text
As noted earlier, we used a 10-year time-span (1998-2007) to allow a broad perspective on the
field’s research domain, and to avoid the problem of overemphasis on the research of a more
limited era. We were also interested in identifying the fundamental definition, not the momentary
fashions or cycles, of the field. Again, we selected articles from three leading academic
databases, which published papers on a wide districts of authors including US., EC, UK, AU, CA, CN,
etc., and which was the base to get a widely shared definition.
Our approach to selecting the pool of articles to be coded (i.e., all those that might very liberally,
or remotely, be considered as e-government) yielded two benefits. First, it helped to minimize the
analysis work and make our emphases on the definition making. Second, our pool of articles
spreading from America to Asia, Australia, Africa and Europe, had the most representative
means.
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Still, we should acknowledge two limitations of the pool of articles we selected. First, we drew
articles strictly from leading academic databases, in an effort to distinguish e-government from
other fields; but such an approach omitted any consideration of how e-government definition
varies from academic fields to application objectives. Second, our pool of articles was drawn
strictly from the three world-famous academic databases, while omitting journals excluded by
these databases. The two limitations provide opportunities for future research, which we will
discuss below.
Extracting the distinctive lexicon of e-government
It is a common approach using content analysis of the abstracts to identify the distinctive lexicon
of one field (Nag et al., 2007). Nowadays, computer-aided text analysis (CATA) has been used to
process large amounts of text for systematic investigation of a range of social phenomena,
including managerial and organizational cognition (Porac et al., 1999), team mental models (Carley,
1997), and institutional isomorphism (Abrahamson and Hambrick, 1997). Using CATA software,
Concordance 3.20 (Watt, 2004), we analyzed two control groups of 324 abstracts to identify the
frequently recurring, distinctive lexiconor vocabularyof the field of e-government.
We chose to examine individual words (and their various forms) rather than entire phrases or
word relationships. Analysis of individual words is a common approach to automated text coding,
including for studies in the organizational sciences (Nag et al., 2007), such as Abrahamson and
Hambrick (1997), Walsh, Weber and Margolis (2003).
The alternative of examining groups of words or phrases has the advantage of considering the
context within which words are used, but it also has notable drawbacks (Singleton, 2000). A focus
on word strings or word pairs either leads to such a great number of combinations as to be
analytically intractable or it requires the researcher to inject a priori judgments as to what kinds
of word combinations might be sought out. For example, we might anticipate that such phrases as
“one-stop government”, “delivery public services”, “government information”, and “government
data sharing” are commonly used in e-government, but the very act of predetermining such
phrases introduces significant bias to the analytic endeavor. Therefore, to minimize such biases,
we examined the appearance of individual words, or lexemes, as our primary analytical approach.
There were of course thousands of unique words contained in all the abstracts. To make this large
body of text analytically tractable, we needed to impose some restrictions on the words we would
examine, but in a way that would not bias the results. The most significant restriction was that we
excluded all words that appeared less than 10 times among one group of 162 abstracts; these
words were used so rarely that they could not be thought of as part of any distinctive lexicon.
Next, we excluded proper nouns, prepositions, adverbs, articles, and certain common descriptors
such as “various”, “term”, “set”, “order”, and words used frequently in all subject academic
abstracts, such as “discuss”, “draw (on)”, “examine”, “study”, “survey”, and “show”. For some word,
for example “IS”, we checked whether it referred to copular verb “is” or abbreviations of
“Information System” and treated as different word. Finally, we consolidated all variations of a
root word and treated them collectively. For example, the words “provide”, “provision”, and
“providing” were all treated as the same word; we reported them by referring to the most common
variant (in this case, “provide”). Turn around, we analyzed its context and found its suitable root
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word. Through several rounds of analysis to group A and B, some non-relevant words were deleted
carefully. This multistage process yielded a total of 172 and 202 root words in Group A and B, or
lexemes, which became our basis for analysis.
Our objective, again, was to identify the distinctive lexicon of the field of e-governmentthe
vocabulary that was used frequently by e-government scholars and consistently between Group A
and B. As our next step, then, we sought to identify words that were much more prevalent in those
abstracts. So, in Group A 88 words were extracted, in Group B 86 words were extracted and the
words, which frequencies were less than 0.003, were excluded. Finally, a 57 same words’
vocabulary (vocabulary A and B) from Group A and Group B were extracted (See Table III).
TAKE IN TABLE III
Validating the distinctive lexicon of e-government
For those two groups of words, if they are not same (or similitude) on the frequency, we should
question the accuracy of the results and the feasibility of the methodology. And if they are same
(or similitude) on the frequency, we can consider those words are prevalently used by the
e-government field scholars. And those words should be the components of the definition. We
used Paired Samples T-Test method of SPSS 11.5 to test the differentiation between Group A
and B, the results showed vocabulary of Group A was strong positive correlation (r=0.9476,
p<0.001) with vocabulary of Group B (See Table IV). And the difference test between the two
vocabularies shows the significant of the T-value is more than 0.05. So, there is no significant
difference between Group A and Group B (Yu and He, 2005, pp.136-138). We can accept the
conclusion that those words are the components of the widely shared definition of e-government.
TAKE IN TABLE IV
Imputing the widely shared definition of the field
The 57 words generated from the text analysis formed the basis for imputing a widely shared
definition of the field of e-government. We conducted this inductive exercise in an iterative
manner. First, we developed some tentative categories, based upon conceptual clusters of words.
For example, several of the words dealt with an involved actors (e.g., “government”, “citizen”,
“business”); some dealt clearly with initiatives taken by those actors (e.g., “provide”, “develop”,
“administration”); some referred to the contents what were the objects of such initiatives (e.g.
“information”, “service”, “policy”); some implicated method how to realize such initiatives (e.g.
“internet”, “system”, “website”, “application”); and other words fell into other tentative
categories.
TAKE IN TABLE V
Next, we turned to existing definitions of e-government, including those presented in the
Appendix, as a way to observe the conceptual elements that recurred when scholars defined the
field. Despite the variety among these definitions, as highlighted earlier, they do carry some
common elements. For example, several refer to government sector, several refer to information
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or service, and several specify public or business as the objects of serving, and so on. By examining
these existing definitions and comparing them to our tentative conceptual categories, we were
able to take the third step in this inductive process: identifying the major elements that
constituted the widely shared definition of the field.
We engaged in multi-way discussions to assign the 57 words to conceptual categories, seeking to
balance several considerations. We attempted to use the conceptual nomenclature from existing
definitions whenever possible; at the same time, we did not want to be constrained by prior
definitions. For the sake of parsimony, we wanted to develop as few definitional elements as
possible, but it was also important that all the words assigned to a category genuinely cohere and
fit together. Finally, as a way to maintain simplicity, we only allowed a given word, or lexeme, to be
assigned to one category, even though their various forms might reasonably belong in additional
categories.
This multistep process led us to the following definition of e-government, as imputed from the
distinctive lexicon of the field: “The field of e-government deals with (a) the major initiatives of
management and delivery information and public services (b) taken by all levels of governments
(including agencies, sectors) (c) on behave of citizens, business (d) involving using multi-ways of
internet, website, system integration, and interoperability (e) to enhance the services
(information, communication, policy making) quality and security (f) as a new key (main, important)
strategy or approach”. Table V shows the assignment of the 57 distinctive words to these six
elements.
Discussion, Implications and Future Research
Discussion and implications of the definition
Kuhn asserted that a scientific community does not need a unifying paradigm in order to exist, but
that it does need a shared identity (Nag, Hambrick, and Chen, 2007). Our efforts contribute to an
understanding of what constitutes the shared identity of the field of e-government. However, the
vitality of e-government is also probably due to the fact that the field’s intellectual content
consists of numerous conceptual elements, thus allowing exploration of a wide array of theoretical
and practical issues. According to our analysis, the widely shared definition of the field consists
of six elements.
These six elements make up the widely shared definition of the field of e-government because
those elements are conceptualized by the most popularly used words of the field scholars. This
definition differs fundamentally from others, because it represents, de facto, the way members
(researchers, scholars etc.) think about the field, rather than the way they should or might or
want to think about the field. However, we should acknowledge that this imputed definition is not
elegantly worded or graceful in its syntax. Rather, it represents our best effort to integrate the
six elements into sentence form.
The first definitional element, “the major initiatives”, as shown in Table V, is represented by
words such as “administration”, “management”, “provideand “support”, which refer to the
government fundamental missions, such as “public administration”, “economy management”,
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“providing public services”; but it also includes such words as “delivery”, “use”, “change”, “develop”,
“make”, “implementation” and “design”, which represent the related activities in a government unit
for completing its mission. The second element of the definition, “taken by all levels of
governments”, concerns the key actors who are the remarkable focus in e-government research.
Terms such as “government”, “country”, “state”, “sector”, and “agency” represent the related
actors from all levels of governments. The third element of the definition, “on behave of public
and business”, refers to all actions taken by government are to meet the need of “public”, “citizen”,
“business” or other stakeholders. The fourth definitional element, “involving utilization of
multi-ways”, pertains to the applications, methods and tools that governments use in their
e-government initiatives; words such as “system”, “framework”, “project”, “model” and “case”
represent the tools that are primarily adopted by government sectors and entities, otherwise
terms such as “IT”, “Internet”, “Website” refer to the approaches government can utilize. The
fifth element, “to enhance the services quality and security”, conceptualizes the key objectives or
outcomes that are of interest to e-government scholars; words such as “information”, “data” and
“knowledge” represent one kind of the government services commonly namely “government
information services”, and words such as “communication” and “process” refer to the interaction
between government and public or business, whereas “policy making” is commonly recognized
better participation of public in policy amendment and decision making, otherwise words like
“security” and “quality” reflect the trait of the key objectives. Finally, the sixth element, “as a
new key (main, important) approach or strategy”, is represented by words such as “strategy”,
“initiative”, “approach”, “method” and “resource”, which refer to the viewpoint of government on
the importance of e-government, and words “new”, “important” and “key”, which indicate the
anchor point of strategy or approach.
Having extracted a universal shared definition of the field, the obvious question is, “So what?”
Perhaps the greatest benefit of having this definition is that it allows e-government scholars to
frame the debate about what they want the field to become, or how they want it to change. In
this vein, for example, the widely shared definition of the field appears to give primacy to
providing services rather than other governmental activities, such as administration or
management. Similarly, the definition emphasizes “integration”, “interoperability” rather than
other types of application such as solo-OA (Office Automation), high quality MIS. With the widely
shared definition now in front of us, members can ask whether such biases about the field are
desirable and/or inevitable.
At the most basic level, the universal shared definition we have extracted could serve either as a
screen or as a magnet for future research. If the field of e-government adheres to its own
concept of distinctive competence, then the definition might be seen as a screen or filter; and
scholarly work that does not fit this definition would be treated as outside the field, beyond the
realm of e-government. If, however, we treat the definition as a magnet, which attracts or invites
related work, then the shape of the fieldincluding the definition itselfmight change over time.
Under this perspective, one of the distinctive competences of the field might be seen as its
abilityand willingnessto broker, reconcile, and integrate the works of multiple other fields
(Hargadon and Sutton, 1997; Nag et al., 2007).
Future Research
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Our study makes up the universal shared definition of the field of e-government. However,
limitations of the study still exist objectively. These indicate a number of opportunities for
future research. First, the field of e-government could be examined from different approach. We
based our analysis on the lexical analysis to the high rated e-government articles. But
e-government also might be the same vocabulary system with other academic filed.
A second research possibility is to replicate our assessment of the field of e-government in the
future, in essence exploring how domain members might have debated the definition and altered
their conceptions of the field over time. It might be very interesting to examine how members
view the field, say, in 5 or 10 yearsin terms of what is inside, what is outside, and what their
consensus definition is of the field.
A third research opportunity is to examine the cross-influence of the definition between
e-government field and the other field. For example, in computer science field, the scholars might
be with different perspective on the definition of e-government. Using citation analysis, for
example, one could explore whether works that adhere closely, or centrally. Or researchers could
work the other way, by exploring how highly cited works shape the basic definition and language of
a field.
Fourth, our methodology could be applied to other academic fields, including those in the
management sciences. For example, our empirical approach, based on the systematic measurement
and analysis of community members’ views, could be used to comprehend the distinctions between
sociology and organizational theory, and between computer science and information science. Thus,
our study not only sheds new light on the field of e-government as a social entity, but also provides
an analytic roadmap for conducting such inquiries in other fields.
Conclusion
Some e-government scholars have bemoaned the field’s ambiguous and ever-changing nature. But
how can such concerns be reconciled with the substantial success that e-government has
experienced over the past two decades or so? E-government’s apparent weakness seems to be its
strength. Its amorphous boundaries and inherent pluralism act as a common ground for scholars to
thrive as a community, without being constrained by a dominant theoretical or methodological
strait-jacket.
Our study, relying on a large-scale survey of e-government field articles, extracted a widely
shared definition of the field held by its members. The definition includes six elements, and as
the further analysis, the study interprets its six elements. The implications and future research
orientations are proposed finally. As a byproduct, our study suggests that e-government acts as
an intellectual brokering entity, which thrives by enabling the simultaneous pursuit of multiple
research orientations by members who hail from a wide variety of disciplinary and philosophical
regimes. At the same time, however, these diverse community members seem to be linked by a
fundamental consensus that helps the field to cohere and maintain its identity. The success of
e-government thus suggests an alternative view of academic communitiesas entities that are
dynamic and malleable, yet at the same time held together by a common, underlying, but permeable
core.
12
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Biographical details
Guangwei Hu is Associate Professor of MIS in the Department of Information Management at
Nanjing University, China. He spent 8 years as a practicing IT professional, including serving as
CIO at Anyuan Co. Ltd. He received his Ph. D. in the School of Economic and Management at
Southeast University of China. His research has focused on issues of MIS, E-Gov and Strategic
Management. He has published in Journal of
the Int. J. of Electronic Governance, China society
for scientific and technical information
,
China Soft Science, Journal of management science in
China
and
Journal of Southeast University
.
Address: No. 22, Hankou Road, Nanjing; Tel: +86 13912989476; E-mail: hugw@nju.edu.cn
Wenwen Pan is lecturer of Department of Business Administration, Nanjing College for
Population Program Management. Her research has focused on E-government, E-business and
MIS. She received her M. A. in the School of Economic and Management at Southeast University
15
of China. She has published in
Journal of Modern Management Science in China, etc
.
E-mail: jsnjpwwen@126.com
Mingxin Lu is Associate Professor of MIS in the Department of Information Management at
Nanjing University of China. He received his Ph. D in Xidian University of China. His research
interests include cryptography and information security. He has published in Journal of
Chinese
Science Bulletin, Science in China Series E: Technological Sciences, etc.
E-mail: mxlu@nju.edu.cn
Jie Wang is currently a PhD candidate in Computer Science and a member of the Laboratory for
High Performance Computing and Computer Simulation in the Department of Computer Science at
the University of Kentucky, USA. Her research interests include data mining and knowledge
discovery, information security and privacy, bioinformatics, information retrieval and
inter-organizational collaboration mechanism. She has published in
International Journal of
Information and Computer Security, Journal of Applied Mathematics and Computation, Knowledge
and Information Systems Journal, Journal of Nanjing University of Chemical Technology, etc
.
E-mail: aiky903@126.com
TAKE IN APPENDIX
16
Figure and Tables
Figure 1. Subject categories of “e-government”
17
Table I. The List of Selected Articles
NO. Database Number of articles
Selected Articles
(Sorted by Relevance
a
)
Percentage (%)
1 InterScience 52 First 32 57.69
2
ScienceDirect
1,482
First 300
20.23
3 SCI-E 404 First 300 74.26
a “Relevance” means sorting retrieved records based on a ranking system that considers how many of the
search terms are found in each record, how frequently the search terms appear, and how close together the
occurrences are. Records with the highest ranking appear at the top of the list.
18
Table II. The Detail of Articles Used for Analysis
Database Categories 1 to 4 Sum
1 2 3 4(Percent*)
InterScience 8 6 8 10(31.25) 32
ScienceDirect 153 20 18 109(36.33) 300
SCI-E 71 10 14 205(68.33) 300
Sum
82
36
40
324(51 . 27)
632
*Percent =Number of Cat. 4 / Sum.
19
Table III. The Distinctive Lexicon of E-government
Words
Group A
Group B
Average of
Percent 1,2
Frequency 1 Percent 1
a
Frequency 2 Percent 2
a
E-government
545
0.1146
565
0.1023
0.1085
Government
285
0.0599
275
0.0498
0.0549
Service
174
0.0366
260
0.0471
0.0419
Website
168
0.0353
48
0.0087
0.0220
Information
152
0.0320
139
0.0252
0.0286
Develop
119
0.0250
113
0.0205
0.0228
Citizen
105
0.0221
86
0.0156
0.0189
Public
96
0.0202
165
0.0299
0.0251
Use
95
0.0200
169
0.0306
0.0253
System
90
0.0189
93
0.0168
0.0179
Technology
87
0.0183
89
0.0161
0.0172
Process
79
0.0166
81
0.0147
0.0157
Electronic
73
0.0153
73
0.0132
0.0143
Policy
71
0.0149
62
0.0112
0.0131
Administration
60
0.0126
67
0.0121
0.0124
Model
59
0.0124
92
0.0167
0.0146
Provide
57
0.0120
81
0.0147
0.0134
Security
54
0.0114
29
0.0052
0.0083
Approach
54
0.0114
73
0.0132
0.0123
Implementation
52
0.0109
52
0.0094
0.0102
Framework
50
0.0105
60
0.0109
0.0107
Application
49
0.0103
42
0.0076
0.0090
Management
48
0.0101
71
0.0129
0.0115
Country
43
0.0090
37
0.0067
0.0079
Case
43
0.0090
48
0.0087
0.0089
Initiative
42
0.0088
51
0.0092
0.0090
Project
41
0.0086
83
0.0150
0.0118
Data
41
0.0086
42
0.0076
0.0081
Online
40
0.0084
48
0.0087
0.0086
State
38
0.0080
20
0.0036
0.0058
Business
36
0.0076
57
0.0103
0.0090
New
36
0.0076
50
0.0091
0.0084
Communication
35
0.0074
29
0.0052
0.0063
Integration
33
0.0069
33
0.0060
0.0065
Social
31
0.0065
28
0.0051
0.0058
Make
31
0.0065
37
0.0067
0.0066
Agency
29
0.0061
19
0.0034
0.0048
Internet
29
0.0061
49
0.0089
0.0075
Organization
28
0.0059
70
0.0127
0.0093
Strategy
28
0.0059
34
0.0062
0.0061
Knowledge
27
0.0057
37
0.0067
0.0062
Important
26
0.0055
38
0.0069
0.0062
Method
26
0.0055
28
0.0051
0.0053
Way
26
0.0055
21
0.0038
0.0047
Support
25
0.0053
21
0.0038
0.0046
Delivery
23
0.0048
27
0.0049
0.0049
Sector
23
0.0048
46
0.0083
0.0066
IT
22
0.0046
22
0.0040
0.0043
Key
22
0.0046
18
0.0033
0.0040
Design
21
0.0044
33
0.0060
0.0052
Digital
20
0.0042
37
0.0067
0.0055
Quality
20
0.0042
38
0.0069
0.0056
Benefit
20
0.0042
21
0.0038
0.0040
Interoperability
19
0.0040
17
0.0031
0.0036
Main
18
0.0038
21
0.0038
0.0038
Change
16
0.0034
35
0.0063
0.0049
Resource
16
0.0034
21
0.0038
0.0036
a Percent 1 and 2= Frequency of a root word / Sum of frequency of all root words. Here, The frequency of a
root word includes its various forms.
20
Table IV. Differentiation Compare between Vocabulary Group A and Group B
Paired Samples T-test Statistic
Pair 1
Pair 2
Frequency1 -
Frequency2
Percent1 - Percent2
Paired Samples Correlations
N
57
57
Correlation
.9476***
.9476***
Paired Differences
Mean
-7.1053
0.0006
Std. Deviation
27.0639
0.0055
Std. Error Mean
3.5847
0.0007
t
-1.9821
0.7596
df
56
56
Sig. (2-tailed)
.0524
.4507
***p<0.001
21
Table V. The distinctive lexicon of e-government
Distinctive words
b
Definitional elements (“The
field of e-Gov deals with …”)
Distinctive words
b
Definitional elements (“The
field of e-Gov deals with …”)
Initiative
Administration
Management
Provide
Delivery
Support
Use
Change
Develop
Make
Implementation
Design
…the major initiatives
IT
System
Application
Project
Case
Technology
Electronic
Digital
Online
Internet
Website
Framework
Integration
Model
Interoperability
…involving using multi-ways
Government
Country
State
Social
Sector
Agency
…taken by all levels of
governments
Service
Information
Policy
Communication
Data
Knowledge
Security
Quality
Benefit
Process
...to enhance the services
quality and security…
Citizen
Public
Business
Organization
…on behave of public and
business
New
Important
Main
Key
Strategy
Resource
Method
Approach
Way
...as a new key (main,
important) approach or
strategy.
b We included all words that appeared significantly frequently in e-government abstracts.
22
Appendix: Selected Definitions of E-government
Author
Definition
Hernon (1998)
e-government is “…Simply using information technology to deliver government
services directly to the customer 24/7.
McClure (2000) Electronic government refers to government’s use of technology, particularly
web-based Internet applications to enhance the access to and delivery of
government information and service to citizens, business partners,
employees, other agencies, and government entities.
Fountain (2001)
“E-government” is a government that is organized increasingly in terms of
virtual agencies, cross-agency and public-private networks whose structure
and capacity depend on the Internet and Web.
Brown and Brudney
(2001)
E-government is the use of technology, especially Web-based applications to
enhance access to and efficiently deliver government information and
services.
Kaylor et al. (2001)
E-government is taken to be the ability for citizens to communicate and/or
interact with the city via the Internet in any way more sophisticated than a
simple email letter to the generic city (or Webmaster) or e-mail address
provided at the site.
Relyea (2002) “E-government” oftentimes came to be used as a symbol, an ambiguous
reference to both current applications of IT to government operations and a
goal of realizing more effective and less costly performance of government
functions.
World Bank (2003)
“E-Government” refers to the use by government agencies of information
technologies (such as Wide Area Networks, the Internet, and mobile
computing) that have the ability to transform relations with citizens,
businesses, and other arms of government.
Jaeger and Thompson
(2004)
e-government is the provision of government information through the
Internet to citizens and businesses and among government agencies
Gil-Garcia and Pardo
(2005)
e-government as the intensive or generalized use of information technologies
in government for the provision of public services, the improvement of
managerial effectiveness, and the promotion of democratic values and
mechanisms
Tung and Rieck (2005) E-Government is believed to lead to better delivery of government services,
improved interaction with business and industry, citizen empowerment
through access to information, or more efficient government management.
Evans et al. (2006)
E-Government means the communication between the government and its
citizens via computers and a Web-enabled presence.
Vassilakis et al. (2007) Electronic government (e-government) can be defined as an ever-increasing
and pervasive use of information and communication technologies in the
context of the Information Society, which more and more affects the public
sector; the importance of this development is increasingly acknowledged in
many countries around the world and experiments are being conducted at all
levels of government … to improve the functioning of public services
concerned and to extend their interaction with the outside world.
... In the academic field, Hu et al., (2009) prepared a robust exploratory study. This study has collected 632 articles from the computer science, the social science, the management science and the information science fields (from 1987 to 2007) and has filtered them according to their relevance to the e-Government field. ...
... They have distinguished 57 words or "widely used vocabulary" among the e-Government abstracts with significant frequency and have compared them to the known definition in e-Government. As a result, a definition was chosen as the most appropriate one in the academic field because "it represents, de facto, the way members (researchers, scholars etc.) think about the field, rather than the way they should or might or want to think about the field" (Hu et al., 2009). These two definitions are analysed according to a number of criteria (objectives, benefits, stakeholders, main applications and level of maturity stage) as shown in Table 2. ...
... The Hu et al., (2009) objectives are less ambitious (enhance is less efficient than transform). The World Bank definition has a higher maturity stage. ...
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... Malgré le développement théorique et pratique de l'e-gouvernent, le concept reste encore sans définition standard qui est largement accepté (Halchin 2004, p. 407;Hu et al. 2009;Liu et al. 2010, p. 419;Yildiz 2007). Tout le monde parle de l'e-gouv, mais avec des interprétations différentes (Wimmer et al. 2007). ...
... Tout le monde parle de l'e-gouv, mais avec des interprétations différentes (Wimmer et al. 2007). Selon Hu et al. (2009), le chevauchement qui existe entre les disciplines d'intérêt de l'egouv et les autres domaines tel que la science de l'information, l'informatique, la science de gestion et autres, ainsi que la diversité des intervenants dans le domaine expliquent la diversité des définitions du concept 'e-gouv'. Alors que d'autres expliquent cette diversité de définitions par la nature dynamique du concept qui évolue avec le temps (Bayona et Morales 2016, p. 48;Halchin 2004, p. 407). ...
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L'e-gouvernement est reconnu comme un moyen pour transformer le fonctionnement de l'administration publique en termes de gouvernance, d'efficience ou de qualité des prestations offertes aux citoyens. Malgré le développement des services e-gouvernement, l'exploration et l'évaluation de son succès reste limitée surtout dans les pays en développement. Le succès de ce genre de systèmes dépend de la satisfaction des utilisateurs pour lesquels elle est destinée. Par conséquent, une meilleure compréhension de la satisfaction et de la disposition des citoyens à l'égard des sites web e-gouvernement peut contribuer au succès d'e-gouvernement. Cette étude envisage d'amorcer la discussion sur ce sujet en proposant un modèle conceptuel qui se base sur le modèle du succès des SI et sur d'autres concepts tels que la confiance des utilisateurs vis-à-vis de l'e-gouvernement et l'influence sociale. L'objectif de cette recherche est donc de déterminer les facteurs susceptibles d'influencer la satisfaction des citoyens Marocains à l'égard du système e-gouvernement. Pour identifier ces facteurs, nous avons procédé par une synthèse pertinente de littérature. Abstract: E-government is recognized as a means of transforming the functioning of public administration in terms of governance, efficiency or the quality of services offered to citizens. Despite the development of e-government services, exploration and evaluation of its success remains limited especially in developing countries. The success of this kind of systems depends on the satisfaction of the users for whom it is intended. Consequently, a better understanding of citizen satisfaction and disposition towards e-government websites can contribute to the e-government success. This study intends to initiate the discussion on this topic by proposing a conceptual model which is based on the model of the information systems success and on other concepts such as the confidence of the users towards e-government and social influence. The aim of this research is to determine the factors that influence likely the satisfaction of Moroccan citizens with the e-government system. To identify these factors, we proceeded by a relevant literature synthesis.
... 23). DG does not have one settled definition; extracting the "perfect" one emerges as a scientific activity on its own [3], and circulating definitions vary in terms of scope-from information supply to e-democracy; subject-from citizens to all public stakeholders; and technology family-from personal computers to the Internet [4] (p. 9). To make things worse, DG is also called by various synonyms or near synonyms, such as "electronic government," "electronic governance," "transformational government," and others. ...
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International bodies and numerous authors advocate a key role for Digital Government (DG) in improving public governance and achieving other policy outcomes. Today, a particularly relevant outcome is advancing Sustainable Governance (SG), i.e., the capacity to steer and coordinate public action towards sustainable development. This article performs an empirical study of the relationship between DG and SG using data about 41 OECD/EU countries from the United Nations’ E-Government Survey and the Bertelsmann’s Sustainable Governance Indicators project, covering the period from 2014 to 2020. We examine if DG progress pairs with SG progress, apply a DEA model to find out which countries are efficient in using DG for better SG, and uncover cases of imbalance where high DG pairs with poor SG and vice versa. The results show that the efficiency in using DG for SG strongly varies, and that some DG leaders persistently fail to advance or even regress their SG. These findings refute the claims about the benign role of DG and points at democracy as the “weak link” in the analyzed relation.
... Prior researches introduced philosophical approaches or perspectives (Heeks and Bailur, 2007), critically analysed the progress and various definitions of electronic government (Yildiz, 2007), focused on specific contexts or countries (Zheng and Zheng, 2013), examined models or themes such as qualitative meta-syntheses of electronic government stage models (Lee, 2010), extracted electronic government lexicons (Hu et al., 2009), and analysed methods used (Irani et al., 2012). The present research is different from earlier studies in four different areas. ...
... Prior researches introduced philosophical approaches or perspectives (Heeks and Bailur, 2007), critically analysed the progress and various definitions of electronic government (Yildiz, 2007), focused on specific contexts or countries (Zheng and Zheng, 2013), examined models or themes such as qualitative meta-syntheses of electronic government stage models (Lee, 2010), extracted electronic government lexicons (Hu et al., 2009), and analysed methods used (Irani et al., 2012). The present research is different from earlier studies in four different areas. ...
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