1
The 11th Public Management Research Conference
June 2–4, 2011
Maxwell School of Syracuse University
TOWARD THE NEW PHASE OF E-GOVERNMENT: AN EMPIRICAL STUDY ON
CITIZENS’ ATTITUDE ABOUT OPEN GOVERNMENT AND GOVERNMENT 2.0
Taewoo Nam
Rockefeller College of Public Affairs and Policy
University at Albany, State University of New York
2
Abstract
This paper sees Open Government and Government 2.0 as a new goal and tool of e-
government in the United States. By conducting the structural equation model analysis on the
data from the Pew Internet and American Life Project’s national survey (2009 Government
Online), the study found what influences American citizens’ attitude about Open Government
and Government 2.0. The structural equation model estimation decomposes the causal
relationships among multiple variables into direct and indirect effects. The statistical analysis
suggests several noteworthy findings. Frequent users of e-government service are more likely to
have positive attitudes toward Open Government and Government 2.0. Citizens’ perceived
values of e-government affect their attitudes about the new goal and tool of e-government.
Citizens’ trust in government leads to a positive attitude concerning the new version of e-
government. Conventional determinants of the digital divide, socio-demographic conditions,
have indirect effects on citizens’ attitudes through e-government use.
Key Words
E-government; Open government; Government 2.0
3
TOWARD THE NEW PHASE OF E-GOVERNMENT: AN EMPIRICAL STUDY ON
CITIZENS’ ATTITUDE ABOUT OPEN GOVERNMENT AND GOVERNMENT 2.0
Something New for E-Government
Since taking office in January 2009, the Obama Administration has envisioned a new
direction for the U.S. government: Open Government. Labeling this term as ―new‖ may be
misleading because citizens have long felt the need for Open Government. In addition, for as
long as governments have existed, there have been efforts to create Open Government in a range
of contexts. This paper, nevertheless, addresses something different from ―government as usual‖
(Golembiewski & Gabris, 1995; Holzer & Halachmi, 1996). Today’s government is exposed to
new opportunities, enabled and facilitated by Information and Communication Technologies
(ICTs), to accommodate citizens’ values: e.g., accessibility to information and services,
efficiency and effectiveness of service delivery, and transparency and accountability in operation
and administration (Lathrop & Ruma, 2010).
Two buzzwords currently infiltrating the public sector are Open Government and Government
2.0. On the trajectory of e-government development, Open Government and Government 2.0
seem to be, respectively, the new ends and new means of e-government. This is true not only in
the U.S., but also in other advanced industrial democracies, as well as certain developing
countries. The platform and standard for technology-enabled government are moving from e-
government (Government 1.0) to Open Government and Government 2.0 (Parycek & Sachs,
2009).
This study spotlights the transition of e-government into new modes in terms of goals and
tools. The new aspects of e-government are not just for government but for the public as
4
customers and users. The focus of this paper is on citizens’ attitudes toward Open Government
and Government 2.0. Given this research focus, the following research question arises: ―What
influences citizens’ attitudes about Open Government and Government 2.0?‖. Previous research
found that citizens’ evaluation on the performance of new initiatives may vary and change with
their adoption of ICTs, usage of e-government services, trust in government, perceived value of
the role of e-government, and personal socio-demographic backgrounds. This study considers
those factors as potential determinants for attitudes toward the new aspects of e-government.
The paper will be structured into five sections, including the foregoing introduction. Drawing
on the extant literature, the paper explores both new (i.e., Open Government, Government 2.0)
and old (i.e., citizens’ attitudes and perceptions of e-government) themes culminating in current
discussions of e-government research, and then establishes a research model and several
hypotheses. After describing details of the data (2009 Government Online survey conducted by
the Pew Internet and American Life Project) and measurements, the paper presents results of the
structural equation model analysis and tests hypotheses. Finally, the last section addresses policy
implications and concluding remarks.
New Issues and Old Issues of E-government Research
New Goal: Open Government
As Open Government has been historically used in various contexts including freedom of
information, anti-corruption, and transparency (Birkinshaw, 1997; Dawes, 2010; Dawes &
Helbig, 2010; Parks, 1957; Rose-Ackerman, 2008), the concept, per se, cannot be considered
novel or recent. The U.S. government’s strong initiative, notwithstanding, is making Open
Government its new priority objective. On January 21, 2009, his very first day in the White
5
House, President Barack Obama signed the Memorandum on Transparency and Open
Government, ushering in a new era of open and accountable government meant to bridge the gap
between the American people and their government (Executive Office of the President, 2009a).
The Obama Administration seeks to create and institutionalize a culture of Open Government,
requiring that federal agencies’ Open Government plans address transparency, participation, and
collaboration, describe a flagship initiative, and offer various opportunities for public and agency
engagement (Executive Office of the President, 2009b). This study follows that practical
conceptualization of Open Government as an explicitly addressed governmental goal.
Through greater openness and new technologies, the Obama Administration hopes to
empower the public to influence the decisions that affect their lives (McDermott, 2010). The role
of ICTs is central and fundamental to opening government, though technology cannot account
for all recent changes in government (Dawes, 2008). The Open Government Initiative upholds
transparency, participation, and governance (through collaboration), which are the core values of
e-government. Changing technologies (social networking, visualization, and virtualization) may
offer the new means for electronically-mediated governance (Dawes, 2009). Now, with the
continual advancement of e-government, public values stated in the Open Government Directive
may become relatively more specific and tangible as goals, compared to earlier years of e-
government when researchers (Moon, 2002; Reddick, 2004b; West, 2004) reported no more than
rhetorical performance of e-government—the gap between the actual status of e-government
(limited utilization of e-government chiefly for cataloguing information on governmental
webpages) and the envisioned elevated and functioning stage (harnessing participatory,
democratic and communicative potential of e-government).
6
New Tool: Government 2.0
A variety of new technological instruments are available for the development of e-
government. The Obama Administration prioritizes the extensive technological support for Open
Government initiatives (Executive Office of the President, 2009b). Especially Web 2.0 is
considered a new tool for those government initiatives.
Contemporaries are seeing the ubiquitous, prevailing fashion of Web 2.0, which is the second
generation of Web access and use, characterized as participatory, pervasive and integrated
(Mintz, 2008). The second generation Web technologies have the potential to change the way
government delivers services and its relationship with the public. A suite of popular Web 2.0
technologies, such as social networking (Facebook, MySpace), wikis, blogs, micro blogs
(Twitter), mash-up, and multimedia sharing (YouTube, Flickr) can promote open and user-driven
governance (Bertot et al., 2010a, b, c; Millard, 2009).
Government 2.0—the government’s merger with Web 2.0 (Johannessen, 2010)—is a new
notion for describing the current use of Web 2.0 technologies to socialize government services,
processes, and data (DiMaio, 2009). The government’s use of collaborative technologies is at the
heart of Web 2.0. It permits a two-way interaction between government and citizens via online
comments, live chats, and message threads.
There are a variety of expectations on the performance and functions of Government 2.0.
Government 2.0 may facilitate achievement of e-government goals for efficiency, effectiveness,
and democracy (Eggers, 2005; DiMaio, 2009). It may heighten the public’s awareness of policy
and their ability to provide feedback on policymaking (Anttiroiko, 2010; Cho & Hwang, 2010;
DiMaio, 2009; Osimo, 2009). It can be a promising tool for transformation and innovation in
government (Eggers, 2005; Ferro & Molinary, 2009; Yong & Koon, 2005). It can also lead to an
7
enhanced level of transparency and anti-corruption in the public sector (Bertot et al., 2010a, b, c).
Those positive expectations are partially or substantially realized in some areas, but remain
illusive in others. Despite some hopeful expectations for Government 2.0, its status is somewhat
controversial. While DiMaio (2009) does not view Government 2.0 as a new kind of government,
but rather, as a means to an end, Tapscott et al. (2008) lauded Government 2.0 as the next
generation of e-government.
Several academics have raised concerns about the extent to which Government 2.0 is utilized.
The performance of Government 2.0 is still not so much fact or reality as fiction or hype (Mintz,
2008; Osimo, 2009). Millard (2009) sees current governmental adoption of Web 2.0 as
something between Government 1.0 and Government 2.0. Using the metaphor of Government
1.5, he compares his evaluation of governmental utilization of Web-based technologies to half-
full (positive expectation of current 1.5 status) and half-empty (negative expectation of current
1.5 status) glasses. The earlier recognition that the reality of e-government lags behind its
rhetoric (Moon, 2002) seems to recur with the rapid mushrooming of Government 2.0.
There are several reasons for the rhetoric-reality gap. The public sector is slow in utilizing
Web 2.0 due to privacy, security, and information policy, compared to businesses that are able
and enthusiastic to employ Web 2.0. Placing policies of Open Government into practice requires
a cultural shift as well as the operationalization of new policies yet undefined. Bertot et al.
(2009), recognizing the policy-technology gap, claim that the Obama Administration is now
seeking a Government 2.0 administration, while still residing in a Government 1.0 environment.
The fact that excessive enthusiasm for ICTs normally results in failure to develop and use
technology systems in government (Goldfinch, 2007) cannot be ignored, and e-government and
Government 2.0 may be no exception.
8
Citizens’ Attitudes about E-government
The attitudes of citizens may be influenced by services which are enabled and advanced by
the employment of new technologies implemented for government workings. Previous empirical
studies have surveyed citizens’ attitudes and/or perceptions of e-government in terms of trust,
satisfaction and values. There has been a gap between public expectation and perceived
governmental performance (Nye et al., 1997; Peters, 2009), which underlines the importance of
actual government performance since the objective—that is, the idea or notion—of performance
only raises citizens’ expectations, and if this objective is not achieved, the previously mentioned
gap widens. The public expectation-perception gap can lead to a decline in the public’s trust of
government, also applying to e-government (Welch et al., 2005).
Individuals’ longstanding perceptions on government may be unyielding, so that while
elaborate technology may positively affect some citizens’ attitudes, these advances may also fail
to influence even a slight change in others. Therefore, Open Government driven by Government
2.0 needs to be evaluated from the viewpoint of citizens. Combined with the continuous
expansion and progress of conventional e-government functions, various new initiatives of e-
government are believed to boost citizens’ positive expectations on government performance by
championing the core values of transparency, public participation, and collaboration.
Despite theoretical importance of the relationship between technology, governmental
workings and citizens’ perception, there is a weakness inherent in empirical research, since the
degree to which citizens recognize and are satisfied with e-government strategies is often not
clearly articulated as a measure of empirical investigation (Welch et al., 2005). The way by
which citizens view their government seems quite abstract in terms of conceptual validity and
9
measurability. Considering such a limitation, an array of prior studies have developed and
employed several effective strategies for measuring citizens’ perceptions and attitudes.
Empirical research can be conducted to determine how citizens view and use e-government,
for example, by evaluating perceptions, satisfaction, efficacy, trust, and confidence. Focusing on
these areas, existing research presents or assumes various causal models. Antecedents and
determinants of online political participation matter to the extent that use of e-government affects
citizens’ attitudes (Tolbert & Mossberger, 2003). In particular, attention to socio-demographic
conditions reveals that the impact of e-government varies across segments within the population
(Mossberger et al., 2003, 2008; Niehaves & Becker, 2008; Tolbert & Mossberger, 2003; Welch
et al., 2005; West, 2004). Drawing on the ―perceived usefulness‖ factor of the Technology
Acceptance Model (Davis, 1989), some empirical works found that individuals’ perception on
the usefulness of e-government (perceived use value of e-government) influences their
satisfaction with e-government (Kolsaker & Lee-Kelley, 2008) and consequently, continuous
usage of e-government and attitude about e-government adoption (Carter & Bélanger, 2005;
Wangpipatwong et al., 2008). Perceived risk of e-government use, the flip side of its perceived
usefulness, also affects intention to engage in e-government (Alsaghier et al., 2009). Frequent
use of e-government has a great impact on trust in government, attitudes toward e-government,
and expectation or perception of e-government use (Kolsaker & Lee-Kelley, 2008; Sweeney,
2007; Tolbert & Mossberger, 2003; Morgeson III et al., 2011).
Technological factors also deserve consideration. The disparity in degrees of Web use among
socio-demographic groups captures a digital divide, which fundamentally impedes the
nationwide spread of e-government use. Therefore, including Web use as an explanatory variable
aids in demonstrating the influence of the digital divide on citizens’ attitudes concerning e-
10
government. Another technological factor is the adoption of broadband Internet connectivity.
Since e-government services, especially Government 2.0-enabled functions, require a
(moderately) high level of Web connectivity, dial-up Internet users may lag behind high-speed
Internet users who can benefit by using any new features of e-government.
Research Model and Hypotheses
Drawing from the literature review, this study identifies the following factors which influence
citizens’ attitudes toward e-government: e-government usage intensity, perceived value of e-
government, general trust in government, and general use of the Internet. In light of those
primary factors, this study generates a path model illustrated in Figure 1.
[Insert Figure 1 about here]
A rich, accumulative body of empirical research on the digital divide has found the
determining effects of socio-demographic characteristics. Socio-demographic backgrounds in
terms of age, gender, race, the level of education and income (proxy for socioeconomic status or
SES), and residential place may influence the degree of Internet use and e-government use. As
well, the degrees may vary with whether individuals use high-speed Internet (broadband).
Frequent Internet users may become frequent e-government users.
More importantly, various causal relationships among key factors of interest are
interconnected. In this sense, those factors are endogenous, which means that they are
determined within a system. Frequent e-government use can lead to positive perception of e-
government value, general trust in government, and positive attitude about the new goal (Open
Government) and tool (Government 2.0) of e-government. Positive perception of e-government
value may contribute to trust in government and attitude about Government 2.0 and Open
11
Government. Those with trust in government may be more positive on what a government does
newly than their counterparts. The hypothetical relationship is thus the causality from trust in
government to attitude about Government 2.0 and Open Government. Trust in government and
attitude about Open Government may be substantially influenced by political affiliation (or
partisanship) as an exogenous factor, because Democrats may be more supportive of the
incumbent administration and its Open Government initiatives. Another causal possibility is
from attitude about Government 2.0 to attitude about Open Government. Positive attitude for
technological tools may lead to positive attitude for national policy enabled by the tools.
This path model has uniqueness, compared to usual linear regression. The nature of causal
relationships can be direct or indirect. The combined effects of both direct and indirect
causalities are of special interest in this study. For example, e-government use may directly
affect attitude about Government 2.0, and e-government value perception may mediates the
causal flow from e-government use to attitude about Government 2.0.
This study does not account for all relationships identified. Instead, corresponding to the
research question addressed in the introduction, the study hypothesizes the causal relationships
between key determinants derived from existing literature and citizens’ attitudes about
Government 2.0 and Open Government.
Hypothesis 1. Citizens’ frequent use of e-government positively influences their attitudes
concerning the new goal (Open Government) and tool (Government 2.0) of e-
government.
Hypothesis 2. Citizens’ perceived value of e-government as beneficial positively influences
their attitudes concerning the new goal (Open Government) and tool
(Government 2.0) of e-government.
12
Hypothesis 3. Citizens’ trust in government positively influences their attitudes concerning
the new goal (Open Government) and tool (Government 2.0) of e-government.
Hypothesis 4. Citizens’ attitudes about the new technological tool of e-government
(Government 2.0) positively influence their attitudes about the new goal of e-
government (Open Government).
Hypothesis 5. A set of conventional determinants (socio-demographic conditions) of the
digital divide significantly influence citizens’ attitudes concerning the new
goal (Open Government) and tool (Government 2.0) of e-government.
Measurements and Empirical Strategy
This study analyzes the publicly-available data (2009 Government Online) from the national
survey conducted by the Pew Internet and American Life Project via telephone interviews during
December 2009 (Data and interview questions are sourced from www.PewInternet.org/Shared-
Content/Data-Sets/2009/December-2009--Government-Online.aspx). By keeping only responses
pertinent to this analysis, the dataset (N=927), used in the study, was extracted from the original
random-sampled dataset (N=2,258). All respondents are Internet users, but the frequency of
Internet use varies among them.
[Insert Table 1 about here]
Table 1 exhibits the demographic distribution of the sample. When age is categorized into
four cohorts in terms of birth year—following generational divisions by Zukin et al. (2006)—
Baby Boomers take the largest proportion (40%). Education and household income fall into five
strata (and also valued in five-point ordinal scale). The dataset also includes residential contexts
to further classify respondents: urban, suburban, and rural area. When the category of high-speed
13
Internet users includes all other ways of networking faster than dial-up connection, eighty-nine
percent of the respondents adopt high-speed connection to the Internet (e.g., broadband adoption:
DSL, FiOS, or Wi-Fi). Self-identified partisanship is quite evenly distributed in the sample, but
the proportion of Republicans is somewhat smaller than that of Democrats and independents.
Measurements
Table 2 presents the descriptive statistics of all variables employed. While those personal
background characteristics are exogenous variables, a set of endogenous variables include
Internet use intensity (frequency of Internet use), use of e-government (transactions, information),
perceived value of e-government use, trust in government, attitude about Government 2.0, and
attitude about Open Government. Portrayed in Figure 1, an ultimate outcome variable is citizens’
attitudes about Open Government. Details of these measures are as follows.
[Insert Table 2 about here]
Internet use intensity Internet use intensity is measured as the frequency of Internet use
according to seven ordinal points: 1) Never (5%), 2) Less often (4%), 3) Every few weeks (4%),
4) 1–2 days a week (13%), 5) 3–5 days a week (15%), 6) About once a day (22%), and 7)
Several times a day (37%).
Attitude about Open Government This variable is measured in terms of the perception of
openness and accessibility of government. The original question is: ―Would you say government
is now more open and accessible, less open and accessible, or about the same as it was two years
ago?‖ The proportional results of three response options are: 1) Less open and accessible (16%),
2) About the same (46%), and 3) More open and accessible (38%).
14
Attitude about Government 2.0 Two variables are germane to citizens’ attitudes about
Government 2.0 tools, such as blogs and social networking sites (e.g., Facebook, MySpace, and
Twitter). Those variables measured on the Likert scale are responses to two statements:
―[Government 2.0] makes government accessible‖ and ―[Government 2.0] helps keep people
informed.‖ The proportional distribution of responses is: 1) Strongly disagree (10% for making
government accessible, 9% for keeping people informed), 2) Somewhat disagree (10% and 7%,
respectively), 3) Neutral (1%, 1%), 4) Somewhat agree (45%, 48%), and 5) Strongly agree (34%,
35%). The two variables are combined as a composite by principal component factor scoring
(eigen value=1.880, factor loading=0.889, uniqueness=0.199).
E-government use This variable is made by extracting a common factor (principal component
factor analysis) from the two composite measures: use of information service and use of
transactional service (eigen value=1.869, factor loading=0.886, uniqueness=0.215). The measure
for citizens’ use of informational service is the summation of binary (1 for Yes or 0 for No)
responses (Cronbach’s α=0.75). The data provides ten items related to information acquisition
through e-government: ―Information about a public policy or issue‖ (49% for Yes), ―Advice or
information about a health or safety issue‖ (26%), ―Recreational or tourist information‖ (33%),
―Official government documents or statistics‖ (37%), ―Information about benefits‖ (21%),
―Information about how to apply for a government job‖ (16%), ―Government data on data.gov,
recovery.gov or usaspending.gov‖ (17%), ―Information on who contributes to the campaigns of
elected officials‖ (14%), ―Text of any legislation‖ (24%), and ―How money from the recent
federal government stimulus package is being spent‖ (24%). The measure for citizens’ use of
transactional service is also an additive index of aggregating five binary variables (Cronbach’s
α=0.71). The collapsed items are: ―Renewing a driver’s license or auto registration‖ (32%),
15
―Applying for a fishing, hunting or other recreational license‖ (11%), ―Paying a fine such as a
parking ticket‖ (12%), ―Downloading government forms‖ (44%), and ―Looking up what services
a government agency provides‖ (47%).
Perception of e-government value Respondents’ perceptions of two statements—―A
government agency provides general information to the public on its website‖ and ―A
government agency allows people to complete tasks on the website, such as submitting
applications or renewing licenses‖—are measured on a four-point scale: 1) Not important at all
(74% for value on information, 70% for value on transaction), 2) Not too important (20% and
22%, respectively), 3) Somewhat important (4%, 4%), and 4) Very important (2%, 4%).
Principal component factor analysis creates a composite of the two ordinal variables (eigen
value=1.588, factor loading=0.812, uniqueness=0.324).
Trust in government Citizens’ trust in federal, state and local government is measured on a
four-point scale. The level of trust in government (an answer to the question ―How much of the
time can you trust?‖) is: 1) Never (17% for federal, 13% for state, and 11% for local), 2) Some of
the time (55%, 51%, and 45%, respectively), 3) Most of the time (25%, 32%, and 38%), and 4)
Just about always (3%, 4%, and 6%). While other composites are produced by principal
component factor scoring, the composite of trust in government is created by simply summing
raw scores. The more parsimonious measure that estimates less parameters (based on Tau-
equivalent assumption) is preferred over a more complicated measure or factored score (based on
congeneric assumption), given statistically little difference between both measures in terms of
the likelihood ratio test (χ2
Tau-equivalent – χ2
Congeneric = 4.23, where the degree of freedom as the
difference in the number of parameters estimated = 2). The simple summation of the four-battery
responses represents the general level of citizens’ trust in government (Cronbach’s α=0.77).
16
Method
This study suggests a structural equation model to examine the complicated relationships
among multiple composite indices and tests a model fit of the path analysis by LISREL 8.8
software package. Constructing the structural model is based on maximum likelihood estimation.
An advantage from the path analysis is the decomposability of the causal effect into direct and
indirect one (Kelloway, 1998). Total effects are produced through path decomposition, where
direct path coefficients and indirect effects mediating through other variable(s) are multiplied
and summed. All causal effects are standardized and thus presented with standardized
coefficients. Standardized total effects offer insight into which variables are relatively more
important in determining an ultimate outcome variable—attitude about Open Government.
Intervening variables can substantially change the interpretation of a direct effect if an indirect
effect is significantly large (Kline, 2005).
Results
This paper views the new direction of e-government through the lens of citizens’ attitudes,
which are shaped by perception of Open Government performance and efficacy of Government
2.0. To test hypotheses, this structural equation model analysis examines causal effects among
multiple factors identified in the literature review section. The results of the analysis are
presented in three tables (correlation matrix, structural equation model estimation, and
decomposed causal effects) and one diagram (illustration of total causal effects).
[Insert Table 3, 4, 5 and Figure 2 about here]
Before discussing the results of hypothesis test, model fit measures merit consideration. Three
types of goodness-of-fit measures are usually employed. Exhibited in Table 4, absolute,
17
incremental, and parsimonious model fit statistics all pass rule-of-thumb cutoff criteria. Each
structural equation shows varying levels of squared multiple correlation or R2. Thirty percent of
the variance in scores of attitude about Open Government is significantly explained by other
endogenous variables such as e-government use intensity, e-government perceived value, trust in
government, and attitude about Government 2.0. The decomposition of causal effects (Table 5)
reveals that indirect effects reinforce direct effects in causal relationships that have both effects.
While indirect effects are smaller in magnitude in most relationships, some between-variable
relationships show larger indirect effects over direct ones. Such cases will be explained with
discussion of hypothesis test.
Hypothesis 1. Citizens’ frequent use of e-government positively influences their attitudes
concerning the new goal (Open Government) and tool (Government 2.0) of e-
government.
The direct effect shows different results between attitudes about Government 2.0 and Open
Government. While the frequent use of existing e-government services leads to positive attitude
about the new tool of e-government, citizens’ e-government use itself does not contribute to
attitude about Open Government. However, it is notable that the indirect effect of e-government
use on Government 2.0 and Open Government is larger than the direct effect. The extent to
which e-government use influences attitude about the new modes of e-government is estimated
more indirectly—mediated through e-government value perception and trust in government—
than directly. Decomposed causal effects indicate that current e-government users, especially
heavy users, can ultimately have more positive attitude about the new goal and tool of e-
government, but the degree to which e-government use intensity turns to positive attitude about
18
Government 2.0 and Open Government depends on perceived value on e-government and
general trust in government to a substantial extent.
Hypothesis 2. Citizens’ perceived value of e-government as beneficial positively influences
their attitudes concerning the new goal (Open Government) and tool
(Government 2.0) of e-government.
This study employs a composite measure of citizens’ perceived value on e-government—
availability of information on government webpages, and seamless and satisfactory transaction
via e-government. Higher expectations on e-government performance would likely lead to
positive attitude about Open Government and Government 2.0. It is intriguing that decomposed
effects distinguish between attitude about Open Government and attitude about Government 2.0.
E-government value perception has a larger direct effect on attitude about Government 2.0 than
an indirect effect. By contrast, the indirect effect on attitude about Open Government
overwhelms the direct effect. The effect of e-government value perception on attitudes toward
Open Government and Government 2.0 is mediated through trust in government. Trust in
government boosts the direct effect of e-government value perception. The direct effect of e-
government value perception on attitude about Open Government is also mediated through
attitude about Government 2.0. Thus the effect of attitude about government 2.0 on attitude
about Open Government magnifies the total effect of perceived value on attitude about Open
Government.
Hypothesis 3. Citizens’ trust in government positively influences their attitudes concerning
the new goal (Open Government) and tool (Government 2.0) of e-government.
19
The level of citizens’ general trust in government positively affects their attitude toward Open
Government and Government 2.0. Those with a high level of general trust in government tend to
maintain that trust, despite changes in public policies and environments (Putnam, 2000). Such
people are likely to have positive attitude about Open Government and Government 2.0. E-
government use does not have a direct effect on trust in government, but perceived usefulness of
e-government use contributes to increasing trust in government. Sketched in Figure 2, the role of
trust in government is not only directly causal to attitudes toward Open Government and
Government 2.0 but also mediating from e-government use and value perception to the attitudes.
Hypothesis 4. Citizens’ attitudes about the new technological tool of e-government
(Government 2.0) positively influence their attitudes about the new goal of e-
government (Open Government).
The path model sets attitude about Government 2.0 not only as an outcome variable but as a
mediating and explanatory variable. The analysis result shows that positive attitude toward new
technologies in e-government is translated to positive attitude toward the new direction of e-
government. The causal effect specified in this hypothesis reflects complexity in the
relationships among variables, capturing the multifaceted effects of e-government use, e-
government value perception and trust in government on attitude toward technological
innovation in the public sector.
Hypothesis 5. A set of conventional determinants (socio-demographic conditions) of the
digital divide significantly influence citizens’ attitudes concerning the new
goal (Open Government) and tool (Government 2.0) of e-government.
20
The new modes of e-government are not free from conventional concerns over the digital
divide. The indirect effect of typical determinants of the digital divide (socioeconomic and
demographic characteristics) on attitude about the new version of e-government is not trifle. That
effect is mediated through internet use and e-government use, which shows the digital divide
driven by personal backgrounds. Shown in Table 5, younger people, men, the better-educated,
and the more affluent are likely to have more positive attitude about Government 2.0 and Open
Government. This result inevitably supports extant empirical findings (the heavy leverage of
socio-demographic conditions on e-government use) in much research on e-government use
(Akman et al., 2005; Bélanger & Carter 2006a, b; Becker et al., 2008; Goldfinch et al., 2009;
Mossberger et al., 2003, 2008; Niehaves & Becker, 2008; Reddick, 2004a; Sipior & Ward, 2005;
Tolbert & Mossberger, 2003). The further extension of e-government faces the challenge of a
participation or usage divide in regard to adopting the new modes of e-government.
By the structural equation model analysis, all hypotheses turn out to become valid arguments.
However, the path model includes relationships that have not been hypothesized. Attention to
those relationships is worthwhile as well. Two findings merit consideration. First, access to high-
speed Internet has an indirect effect on citizens’ attitudes toward Open Government and
Government 2.0 through e-government use and perceived usefulness of e-government. Second,
the analysis result reports an obvious attitudinal gap between Republicans and Democrats in self-
identified partisanship. Whereas Open Government retains strong support from individuals who
identify as Democrats, Republicans have significantly negative attitude on the level of openness
in the current administration. Almost half of respondents said that their feelings were ―about the
same‖ concerning governmental openness between the Obama Administration and its
predecessor. Most of those people may come from individuals self-identified as Republicans.
21
Positive attitude about Government 2.0 is also only significant for Democrats. Government use
of ICTs for openness is not yet appealing enough to the large population to significantly affect
their attitudes about government.
Findings and Implications
This concluding section presents implications for government practitioners and researchers.
The statistical analysis carried some hope while presenting a challenge in extending to Open
Government beyond the existing e-government. Along with testing hypothetical causal effects,
the analysis also highlighted likely advocates of Open Government and Government 2.0. While
certain users of conventional e-government services perceive potential benefits of e-government
and would translate their positive attitude toward e-government directly to support of Open
Government and Government 2.0, others, who neither use e-government services nor value e-
government use, do not have much interest in the new options of e-government. Practitioners and
academics of e-government need to be aware of the overarching findings and their further
implications.
First, citizens’ perception of potential value on e-government use is as important as actual
experience of e-government in shaping attitude about the new direction of e-government. Those
who value potential benefits of currently available services through e-government are supportive
of Open Government and Government 2.0. A distinction for policy exists between those who
have used e-government services and those who perceive potential value of the services. If a
government should care about its citizens’ attitudes toward their government, then it is crucial to
identify what shapes the citizens’ perceived values of government. Since e-government value
perception is key to creating positive attitude toward Open Government, a government needs to
22
educate citizens (especially, the service-needy, the technology-illiterate, and the
socioeconomically disadvantaged) about the value of e-government (potential benefits) so that
citizens keep aware of usefulness of e-government (Jaeger & Thompson, 2003).
Second, any government should know that trust in standard government (government without
―e-‖) heavily influences citizens’ attitudes about e-government. If governmental efforts to change
citizens’ attitudes hinge only on technological innovation, government would overlook the more
fundamental factor that affects attitudes about government—namely, citizens’ trust in
government itself. The fact that citizens’ trust in government anchors their support for the new
initiative of e-government requires government to consider factors for inspiring general trust, as
well as to improve technological convenience for using e-government. However, trust is not
simply based on a feeling or emotion easily and quickly altered by external stimuli. Trust-
building requires a long-term investment by government because trust is established through
longstanding relationships (van de Walle et al., 2008; Warkentin et al., 2002). While both Open
Government and Government 2.0 are new to most individuals, e-government can also be a still
unfamiliar channel to some people. It is rare that the adoption of new technologies in government
will exert a radical impact on the level of trust in government. To those who have little trust in
government, the new ends and means of e-government may seem illusive. General trust in
government is central to attitude toward the new direction of (e-)government.
Last but not least, a crucial policy concern for Open Government and Government 2.0 is to
identify who advocates are and are not—policy targets. Personal political affiliation heavily
affects attitude toward Open Government. Socioeconomically disadvantaged and thus
technologically marginalized segments of the population are less likely to be positive toward
23
Open Government and Government 2.0. In this sense, the existing gap in adoption and use of e-
government induces the attitudinal difference.
Conclusively, this study offers practical insight into contributors to positive attitude for the
new direction of e-government. For government practitioners, the result of the analysis makes
reasonable sense. However, its underlying message is that their job of making citizens’ attitude
positive or turning their current negative attitude to enthusiasm is not easy, even though Open
Government as a new ends of government in the Obama Administration is a positive objective
for both government and society as a new norm for public values such as accessibility,
transparency, and citizen engagement. To that end, improving the level of e-government
adoption is an initial job for government. Then letting people aware of potential usefulness of e-
government is important for creating their positive attitudes. Facing the continuous decline of
trust in government (Putnam, 2000), enhancing that trust is the most difficult work but still
pivotal to obtaining compliance to new policy direction. Government priorities necessitate
considerable popular support from the generic public. To reach the larger populace of citizens
and secure support from them, government needs to implement strategies to ensure effectiveness
of new technological tools and turn new e-government initiatives from hype and rhetoric into
hope and actual achievement.
24
References
Akman, İ., Yazici, A., Mishra, A., & Arifoglu, A. (2005). E-Government: A global view and an
empirical evaluation of some attributes of citizens. Government Information Quarterly, 22(2),
239–257.
Alsaghier, H., Ford, M., Nguyen, A., & Hexel, R. (2009). Conceptualising citizen’s trust in e-
government: Application of Q methodology. Electronic Journal of e-Government, 7(4), 295–
310.
Anttiroiko, A. (2010). Innovation in democratic e-governance: Benefitting from Web 2.0
applications in the public sector. In Reddick, C. G. (Ed.) Citizens and E-Government:
Evaluating Policy and Management. Hershey, PA: IGI Publishing, 110–130.
Becker. J., Niehaves, B., Bergener, P., & Räckers, M. (2008). Digital divide in eGovernment:
The eInclusion gap model. In Wimmer, M. A., Scholl, H. J., & Ferro, E. (Eds.) Electronic
Government: Proceedings of the 7th International Conference, EGOV 2008.
Berlin/Heidelberg, Germany: Springer, 231–242.
Bélanger, F., & Carter, L. (2006a). The effects of the digital divide on e-government: An
empirical evaluation. In Proceedings of the 39th Hawaii International Conference on System
Sciences, Kauai, Hawaii, January 4–7.
Bélanger, F., & Carter, L. (2006b). The impact of the digital divide on e-government use.
Communications of the ACM, 52(4), 132–135.
Bertot, J. C., Jaeger, P. T., & Grimes, J. M. (2010a). Crowd-sourcing transparency: ICTs, social
media, and government transparency initiatives. In Proceedings of the 11th Annual
International Conference on Digital Government Research, Pueblo, Mexico, May 17–20.
25
Bertot, J. C., Jaeger, P. T., & Grimes, J. M. (2010b). Using ICTs to create a culture of
transparency: E-government and social media as openness and anti-corruption tools for
societies. Government Information Quarterly, 27(3), 264–271.
Bertot, J. C., Jaeger, P. T., Munson, S., & Glaisyer, T. (2010c). Social media technology and
government transparency. Computer, 43(11), 53–59.
Bertot, J. C., Jaeger, P. T., Shuler, J. A., Simmons, S. N., & Grimes, J. M. (2009). Reconciling
government documents and e-government: Government information in policy, librarianship,
and education. Government Information Quarterly, 26(3), 433–436.
Birkinshaw, P. (1997). Freedom of information. Parliamentary Affairs, 50(1), 164–181.
Carter, L., & Bélanger, F. (2005). The influence of perceived characteristics of innovating on e-
government adoption. The Electronic Journal of e-Government, 2(1), 11–20.
Cho, H., & Hwang, S. (2010). Government 2.0 in Korea: Focusing on e-participation services. In
Reddick, C. G. (Ed.) Politics, Democracy and E-Government: Participation and Service
Delivery, Hershey, PA: IGI Publishing, 94–114.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of
information technology. MIS Quarterly, 13(3), 319–340.
Dawes, S. S. (2008). The evolution and continuing challenges of e-governance. Public
Administration Review, 68(Supplement 1), S86–S102.
Dawes, S. S. (2009). Governance in the digital age: A research and action framework for an
uncertain future. Government Information Quarterly, 26(2), 257–264.
Dawes, S. S. (2010). Stewardship and usefulness: Policy principles for information-based
transparency. Government Information Quarterly, 27(4), 377–383.
26
Dawes, S. S., & Helbig, N. (2010). Information strategies for open government: Challenges and
prospects for deriving public value from government transparency. Presented at the 9th
International Federation for Information Processing (IFIP) WG 8.5 International Conference
(EGOV 2010), Lausanne, Switzerland, August 29 – September 2.
DiMaio, A. (2009). Government 2.0: A Gartner definition. Retrieved May 1, 2011, from
http://blogs.gartner.com/andrea_dimaio/2009/11/13/government-2-0-a-gartner-definition/.
Eggers, W. D. (2005). Government 2.0: Using Technology to Improve Education, Cut Red Tape,
Reduce Gridlock, and Enhance Democracy. Lanham, MA: Rowman & Littlefield Publishers.
Executive Office of the President (2009a, January 21). Memorandum for the Heads of Executive
Departments and Agencies: Transparency and Open Government. Retrieved May 1, 2011,
from www.WhiteHouse.gov/the_Press_Office/TransparencyandOpenGovernment/.
Executive Office of the President (2009b, December 8). Memorandum for the Heads of
Executive Departments and Agencies: Open Government Directive. Retrieved May 1, 2011,
from www.WhiteHouse.gov/Open/Documents/Open-Government-Directive.
Ferro, E., & Molinari, F. (2009). Framing Web 2.0 in the process of public sector innovation:
Going down the participation ladder. European Journal of ePractice, 9(1), 20–34.
Goldfinch, S. (2007). Pessimism, computer failure, and information systems development in the
public sector. Public Administration Review, 67(5), 917–929.
Goldfinch, S., Gauld, R., & Herbison, P. (2009). The participation divide? Political participation,
trust in government, and e-government in Australia and New Zealand. Australian Journal of
Public Administration, 68(3), 333–350.
Golembiewski, R. T., & Gabris, G. (1995). Tomorrow’s city management: Guides for avoiding
success-becoming-failure. Public Administration Review, 55(3), 240–246.
27
Holzer, M., & Halachmi, A. (1996). Measurement as a means of accountability. International
Journal of Public Administration, 19(11/12), 1921–1944.
Jaeger, P. T., & Thompson, K. M. (2003). E-government around the world: Lessons, challenges,
and future directions. Government Information Quarterly, 20(4), 389–394.
Johannessen, M. R. (2010). Different theory, different result: Examining how different theories
lead to different insights in government 2.0 research. In Proceedings of the 1st Scandinavian
Conference of Information Systems and the 33rd Information Systems Research in
Scandinavia (IRIS) Seminar, Skørping, Denmark, August 20–24.
Kelloway, E. K. (1998). Using LISREL for Structural Equation Modeling: A Researcher’s Guide.
Thousand Oaks, CA: Sage.
Kline, R. B. (2005). Principles and Practice of Structural Equation Modeling (2nd ed.). New
York: Guilford Press.
Kolsaker, A., & Lee-Kelley, L. (2008). Citizens’ attitudes towards e-government and e-
governance: A UK study. International Journal of Public Sector Management, 21(7), 723–
738.
Lathrop, D., & Ruma, L. (eds.) (2010). Open Government: Collaboration, Transparency, and
Participation in Practice. Sebastopol, CA: O’Reilly Media.
McDermott, P. (2010). Building open government. Government Information Quarterly, 27(4),
401–413.
Millard, J. (2009). Government 1.5: Is the bottle half full or half empty?. European Journal of
ePractice, 9(1), 35–50.
Mintz, D. (2008). Government 2.0: Fact or fiction?. Public Manager, 36(4), 21–24.
28
Moon, M. J. (2002). The evolution of e-government among municipalities: Rhetoric or reality?.
Public Administration Review, 62(4), 424–433.
Morgeson III, F. V., VanAmburg, D., & Mithas, S. (2011). Misplaced trust? Exploring the
structure of the e-government-citizen trust relationship. Journal of Public Administration
Research and Theory, 21(2), 257–283.
Mossberger, K., Tolbert, C. J., & McNeal, R. S. (2008). Digital Citizenship: The Internet,
Society, and Participation. Cambridge, MA: The MIT Press.
Mossberger, K., Tolbert, C. J., & Stansbury, M. (2003). Virtual Inequality: Beyond the Digital
Divide. Washington, DC: Georgetown University Press.
Niehaves, B., & Becker, J. (2008). The age-divide in e-government: Data, interpretations, theory
fragments. Paper presented at the 8th IFIP Conference on e-Business, e-Services, and e-
Society (I3E 2008), Tokyo, Japan, September 24–26.
Nye, J. S., Zelikow, P. D., & King, D. C. (eds.) (1997). Why People Don’t Trust Government.
Cambridge, MA: Harvard University Press.
Osimo, D. (2009). Editorial: Government 2.0 - hype, hope, or reality?. European Journal of
ePractice, 9(1), 2–4.
Parks, W. (1957). The open government principle: Applying the right to know under the
constitution. The George Washington Law Review, 26(1), 1–22.
Parycek, P., & Sachs, M. (2009). Open government: Information flow in Web 2.0. European
Journal of ePractice, 9(1), 59–70.
Peters, B. G. (2009). American Public Policy: Promise and Performance (8th ed.). Washington,
DC: CQ Press.
29
Putnam, R. D. (2000). Bowling Alone: The Collapse and Revival of American Community. New
York: Touchstone.
Reddick, C. G. (2004a). Citizen interaction with e-government: From the streets to servers?.
Government Information Quarterly, 22(1), 38–57.
Reddick, C. G. (2004b). A two-stage model of e-government growth: Theories and empirical
evidence for U.S. cities. Government Information Quarterly, 21(1), 51–64.
Rose-Ackerman, S. (2008). Corruption and government. International Peacekeeping, 15(3),
328–343.
Sipior, J. C., & Ward, B. T. (2005). Bridging the digital divide for e-government inclusion: A
United States case study. The Electronic Journal of e-Government, 3(3), 137–146.
Sweeney, A. D. P. (2007). Electronic government-citizen relationships exploring citizen
perspectives. Journal of Information Technology & Politics, 4(2), 101–116.
Tapscott, D., Williams, A. D., & Herman, D. (2008). Government 2.0: Transforming
Government and Governance for the Twenty-First Century. Retrieved May 1, 2011, from
http://www.newparadigm.com/media/gov_transforminggovernment.pdf.
Tolbert, C. J., & Mossberger, K. (2003). The effects of e-government on trust and confidence in
government. Paper presented at the Annual National Conference on Digital Government
Research (dg.o 2003), Boston, May 18–21.
Van de Walle, S., van Roosbroek, S., & Bouckaert, G. (2008). Trust in the public sector: Is there
any evidence for a long-term decline?. International Review of Administrative Sciences, 74(1),
47–64.
Wangpipatwong, S., Chutimaskul, W., & Papasratorn, B. (2008). Understanding citizen’s
continuance intention to use e-government website: A composite view of technology
30
acceptance model and computer self-efficacy. The Electronic Journal of e-Government, 6(1),
55–64.
Warkentin, M., Gefen, D., Pavlou, P. A., & Rose, G. M. (2002). Encouraging citizen adoption of
e-government by building trust. Electronic Markets, 12(3), 157–162.
Welch, E. W., Hinnant, C. C., & Moon, M. J. (2005). Linking citizen satisfaction with e-
government and trust in government. Journal of Public Administration Research and Theory,
15(3), 371–391.
West, D. M. (2004). E-government and the transformation of service delivery and citizen
attitudes. Public Administration Review, 64(1), 15–27.
Yong, J. S., & Koon, L. (2005). E-government: Enabling public sector reform. In Yong, J. S.
(Ed.) E-government in Asia: Enabling Public Service Innovation in the 21st Century.
Singapore: Times Media, 3–21.
Zukin, C., Keeter, S., Andolina, M., Jenkins, K., & Delli Carpini, M. X. (2006). A New
Engagement? Political Participation, Civic Life, and the Changing American Citizen. New
York: Oxford University Press.
31
Figure 1. The Path Model
Demographics
Broadband
Adoption
Internet Use
E-Government
Use
E-government
Value Perception
Trust in
Government
Attitude about
Government 2.0
Attitude about
Open Government
Political
Affiliation
32
Figure 2. The Focused View of Total Causal Effects between Endogenous Variables
Internet Use
E-Government
Use E-government
Value Perception
Trust in
Government
Attitude about
Government 2.0
Attitude about
Open Government
Republican
Age
Male
Caucasian
Education
Income
Suburban
Urban
Broadband
Democrat
0.177*
0.107*
0.175*
0.055
0.131*
0.130*
0.216*
0.150*
0.177*
0.023
0.175*
-0.163*
0.282*
Note. * < 0.05, This diagram omits the description of the effects by socio-demographic exogenous variables.
33
Table 1. The Sample Distribution
N = 927 Categories Proportion
Generation DotNets (born after 1976) 24%
GenXers (born from 1965 to 1976) 18%
Baby Boomers (born from 1946 to 1964) 39%
Dutifuls (born before 1946) 19%
Gender Male 45%
Female 55%
Race Caucasian 80%
Non-Caucasian 20%
Education High school incomplete 5%
High school graduate 23%
Some college level 29%
Four-year college graduate 25%
Post-graduate education 18%
Annual Household Income $30,000 or less 24%
$30,001 up to $50,000 22%
$50,001 up to $75,000 18%
$75,001 up to $100,000 15%
$100,001 or more 21%
Residential Place Rural residence 21%
Suburban residence 52%
Urban residence 27%
Internet Connection Dial-up connection 11%
High-speed connection 89%
Self-reported Partisanship Republican 26%
Democrat 37%
Independent or others 37%
34
Table 2. The Descriptive Statistics
Variables Mean Std. Dev. Min Max
E-government Use 0.000 1.252 -1.628 4.278
E-government Perceived Value 0.000 1.178 -4.113 0.864
Trust in Government 6.804 1.895 3 12
Attitude about Government 2.0 0.000 1.000 -2.529 1.027
Attitude about Open Government 2.191 0.698 1 3
Age 51.363 18.238 18 95
Female or not 0.560 0.496 0 1
Caucasian or not 0.800 0.400 0 1
Education 4.550 1.669 1 7
Annual Household Income 4.910 2.334 1 9
Suburban Residence 0.513 0.500 0 1
Urban Residence 0.254 0.435 0 1
High-Speed Internet 0.893 0.309 0 1
Republican 0.243 0.429 0 1
Democrat 0.397 0.489 0 1
35
Table 3. The Correlation Matrix
[A] [B] [C] [D] [E] [F] [G] [H] [I] [J] [K] [L] [M] [N] [O]
[A] E-government Use 1.000
[B] E-government Value 0.356 1.000
[C] Trust in Government 0.062 0.146 1.000
[D] Attitude about Gov 2.0 0.176 0.289 0.190 1.000
[E] Attitude about Open Gov 0.120 0.183 0.288 0.266 1.000
[F] Age -0.071 -0.193 -0.091 -0.161 -0.072 1.000
[G] Female or not -0.100 0.044 -0.026 0.043 0.064 -0.033 1.000
[H] Caucasian or not -0.034 -0.037 0.024 -0.025 -0.090 0.165 -0.032 1.000
[I] Education 0.305 0.171 0.121 0.032 0.039 0.132 0.045 0.008 1.000
[J] Income 0.233 0.064 0.019 -0.038 -0.030 0.085 -0.146 0.108 0.376 1.000
[K] Suburban residence 0.033 -0.040 -0.048 -0.015 0.038 -0.002 -0.014 0.040 0.013 0.085 1.000
[L] Urban residence 0.045 0.063 0.010 -0.018 0.006 -0.044 0.025 -0.128 0.026 -0.012 -0.630 1.000
[M] High-speed Internet 0.184 0.081 0.048 0.046 0.000 -0.065 -0.026 0.036 0.120 0.170 0.065 0.050 1.000
[N] Republican -0.007 -0.046 -0.064 -0.035 -0.302 0.027 -0.007 0.191 -0.002 0.113 -0.004 -0.059 0.049 1.000
[O] Democrat 0.041 0.080 0.176 0.089 0.378 0.018 0.091 -0.206 -0.022 -0.075 -0.088 0.121 -0.075 -0.462 1.000
36
Table 4. Structural Equation Model Estimation
N = 927
Independent variables
Internet Use
Intensity
E-government Use
E-government Value
Trust in Government
Attitude about Government 2.0
Attitude about Open
Government
Exogenous variables
Demographics
Age
-0.131*** (0.031)
-0.080* (0.031)
Female
-0.070* (0.031)
-0.086* (0.031)
Caucasian
0.006 (0.031)
-0.034 (0.031)
Education
0.189*** (0.033)
0.233*** (0.033)
Income
0.047 (0.034)
0.099** (0.034)
Suburban residence (vs. Rural residence)
0.080* (0.040)
0.036 (0.039)
Urban residence (vs. Rural residence)
0.049 (0.040)
0.050 (0.039)
Technology adoption
High-speed Internet
0.246*** (0.031)
0.076* (0.032)
Political affiliation
Republican (vs. Independent or others)
0.023
(0.036)
-0.168*** (0.032)
Democrat (vs. Independent or others)
0.175*** (0.036)
0.244*** (0.032)
Endogenous variables
Internet use intensity
0.177*** (0.032)
E-government use
0.356*** (0.031)
0.009 (0.034)
0.081* (0.033)
0.044 (0.031)
E-government value
0.130*** (0.034)
0.239*** (0.034)
0.061* (0.031)
Trust in government
0.150*** (0.031)
0.189*** (0.029)
Attitude about government 2.0
0.177***
(0.030)
R2 (Squared multiple correlation) 0.209 0.258 0.177 0.095 0.150 0.300
Absolute model fit statistics Normed χ2 test = Minimum fit function χ2 (131.90) / degree of freedom (44) = 2.99 (Cutoff is less than 5) Root mean Square Error of Approximation (RMSEA) = 0.05 (Cutoff is equal to or lower than 0.05) P-value for test of close fit (RMSEA < 0.05) = 0.77
Incremental model fit statistics
(Baseline model comparisons)
Bentler-Bonett Normed Fit Index (NFI) = 0.94 (Cutoff is larger than 0.9) Incremental Fit Index (IFI) = 0.96 (Cutoff is larger than 0.9) Comparative Fit Index (CFI) = 0.96 (Cutoff is larger than 0.9)
Parsimonious model fit statistics (Akaike Information Criterion)
Model AIC (311.77), Saturated AIC (272.00) < Independence CAIC (2397.94) Model CAIC (848.31), Saturated AIC (1065.15) < Independence CAIC (2491.25) (Criterion is that model and saturated parameters should be smaller than independence parameters)
Note. *** p < 0.001, ** p < 0.01, * p < 0.05, Standardized direct effects, Standard errors in parentheses
37
Table 5. Standardized Direct, Indirect, and Total Effects
N = 927
Independent variables
Internet Use
Intensity
E-government Use
E-government Value
Trust in Government
Attitude about Government
2.0
Attitude about Open
Government
Exogenous variables
Age a. -0.131*** b. c. -0.131***
a. -0.080* b. -0.023** c. -0.103**
a. b. -0.037** c. -0.037**
a. b. -0.006 c. -0.006
a. b. -0.018** c. -0.018**
a. b. -0.011* c. -0.011*
Female a. -0.070* b. c. -0.070*
a. -0.086* b. -0.012* c. -0.098**
a. b. -0.035** c. -0.035**
a. b. -0.005 c. -0.005
a. b. -0.017** c. -0.017**
a. b. -0.011* c. -0.011*
Caucasian a. 0.006 b. c. 0.006
a. -0.034 b. 0.001 c. -0.033
a. b. -0.012 c. -0.012
a. b. -0.002 c. -0.002
a. b. -0.006 c. -0.006
a. b. -0.004 c. -0.004
Education a. 0.189*** b. c. 0.189***
a. 0.233*** b. 0.033*** c. 0.266***
a. b. 0.095*** c. 0.095***
a. b. 0.015 c. 0.015
a. b. 0.047*** c. 0.047***
a. b. 0.029** c. 0.029**
Income a. 0.047 b. c. 0.047
a. 0.099** b. 0.008 c. 0.107**
a. b. 0.038** c. 0.038**
a. b. 0.006 c. 0.006
a. b. 0.019** c. 0.019**
a. b. 0.012* c. 0.012*
Suburban residence (vs. Rural residence)
a. 0.080* b. c. 0.080*
a. 0.036 b. 0.014 c. 0.050
a. b. 0.018 c. 0.018
a. b. 0.003 c. 0.003
a. b. 0.009 c. 0.009
a. b. 0.005 c. 0.005
Urban residence (vs. Rural residence)
a. 0.049 b. c. 0.049
a. 0.050 b. 0.009 c. 0.059
a. b. 0.021 c. 0.021
a. b. 0.003 c. 0.003
a. b. 0.010 c. 0.010
a. b. 0.006 c. 0.006
High-speed Internet a. 0.246*** b. c. 0.246***
a. 0.076* b. 0.044*** c. 0.120***
a. b. 0.043*** c. 0.043***
a. b. 0.007 c. 0.007
a. b. 0.021** c. 0.021**
a. b. 0.013* c. 0.013*
Republican (vs. Independent or others)
a. 0.023 b. c. 0.023
a. b. 0.003 c. 0.003
a. -0.168*** b. 0.005 c. -0.163***
Democrat (vs. Independent or others)
a. 0.175*** b. c. 0.175***
a. b. 0.026*** c. 0.026***
a. 0.244*** b. 0.038*** c. 0.282***
Endogenous variables
Internet use intensity a. 0.177*** b. c. 0.177***
a. b. 0.063*** c. 0.063***
a. b. 0.010 c. 0.010
a. b. 0.031*** c. 0.031***
a. b. 0.019** c. 0.019**
E-government use
a. 0.356*** b. c. 0.356***
a. 0.009 b. 0.046*** c. 0.055
a. 0.081* b. 0.093*** c. 0.174***
a. 0.044 b. 0.063*** c. 0.107***
E-government value
a. 0.130*** b. c. 0.130***
a. 0.239*** b. 0.019** c. 0.258***
a. 0.061* b. 0.070*** c. 0.131***
Trust in government
a. 0.150*** b. c. 0.150***
a. 0.189*** b. 0.027*** c. 0.216***
Attitude about government 2.0
a. 0.177***
b. c. 0.177***
Note. *** p < 0.001, ** p < 0.01, * p < 0.05, a: Standardized direct effects, b: Standardized indirect effects, c: Standardized total effects