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The Influence of Perceived Characteristics of
Innovating on e-Government Adoption
Lemuria Carter and France Belanger
Virginia Polytechnic Institute & State University, Blacksburg, USA
lecarter@vt.edu
belanger@vt.edu
Abstract: Government agencies around the world are making their services available online. The
success of e-Government initiatives is contingent upon citizens’ willingness to adopt these Web-enabled
services. This study uses Moore and Benbasat’s (1991) perceived characteristics of innovating
constructs to identify factors that influence citizen adoption of e-Government initiatives. To pilot test our
adoption model we administered a survey to 140 undergraduate students at an accredited research
university. This paper discusses the results of the study and their implications for research and practice.
Keywords: e-Government, electronic government services, diffusion of innovation, adoption
1. Introduction
e-Government is the use of information
technology, especially
telecommunications, to enable and
improve the efficiency with which
government services and information are
provided to citizens, employees,
businesses, and government agencies.
The United States federal, state and local
government agencies have implemented
numerous e-Government initiatives to
enable the purchase of goods and
services, the distribution of information
and forms, and the submission of bids and
proposals. There are predictions of more
than $600 billion of government fees and
taxes to be processed through the Web by
2006 (James 2000). In the U.S., federal
government spending is predicted to reach
$2.33 billion in 2005 (Gartner 2002).
While there seems to be substantial
growth in the development of e-
Government initiatives, it is not clear that
citizens will embrace the use of such
services. The success and acceptance of
e-Government initiatives, such as online
voting and license renewal, are contingent
upon citizens’ willingness to adopt these
services. Numerous studies have
analyzed user adoption of electronic
commerce (Gefen & Straub 2000; Gefen
et al. 2003; McKnight et al. 2002; Pavlou
2003). Yet, to date, few studies have
explored the core factors that influence
citizen adoption of e-Government services.
According to a survey conducted by the
International City/County Management
Association (ICMA) administered to chief
administrative officers (CAO) at
government agencies, 74.2 % of CAOs
reported that their government agency had
a Web site. However, 90.5 % of these
agencies have not conducted a survey to
see what online services citizens and
businesses actually want (ICMA 2002).
This study uses Moore and Benbasat’s
(1991) perceived characteristics of
innovating (PCI) to identify fundamental
elements of e-Government adoption1.
These constructs have been used in IT
research (Karahanna et al. 1999; Moon &
Kim 2001; Pavlou 2003) and e-Commerce
research (Van Slyke et al. 2004). Based
on similarities between e-Commerce and
e-Government, PCI constructs are
proposed as useful indicators of e-
Government adoption.
2. Theoretical foundations
2.1 e-Commerce and e-Government
2.1.1 Similarities
e-Commerce and e-Government are both
based on Internet technology designed to
facilitate the exchange of goods, services
and information between two or more
parties. e-Commerce refers to the
commercial use of Internet technology to
sell and purchase goods or services.
Laudon and Laudon (2003) identify three
major electronic commerce categories:
business-to-consumer (B2C), business-to-
business (B2B), and customer-to-
customer (C2C). B2C commerce refers to
the retailing of products or services from
businesses to individual shoppers. B2B
commerce is the sale of goods and
1 This study was presented at the First International
E-Services Workshop in September 2003 (Carter &
Belanger 2003).
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Electronic Journal of e-Government Volume 2 Issue 1 (11-20) 12
services among businesses. In C2C
commerce, consumers sell goods and
services to other consumers online.
Comparable categories for electronic
government - government-to-citizen
(G2C), government-to-employee (G2E),
government-to-government (G2G), and
government-to-business (G2B) - each of
which uses Internet technology to provide
government services online, have been
identified (General Accounting Office
2001). G2C government allows citizens to
retrieve information and complete
government transactions, such as license
renewal, online. G2E government takes
advantage of Internet technology by
allowing government agencies to interact
with their employees online. G2G
government supports online
communication and interaction among
government agencies. G2B government
allows businesses to retrieve timely
government information and complete
transactions with government agencies,
such as bid submission, online. Other
agencies and studies have identified
variations on these categories (Hiller &
Belanger 2001; Office of Management and
Budget, 2002).
Not only are e-Commerce and e-
Government categorized in similar ways,
but they also provide similar services to
individuals and organizations. Both e-
Commerce and e-Government systems
support the electronic mediation of
transactions over potentially great
distances. Both services also require
consumer or citizen trust (Belanger et al.
2002; McKnight et al. 2002; Pavlou 2003;
Van Slyke et al. 2004; Warkentin et al.
2002) due to the absence of face-to-face
interaction.
2.1.2 Differences
Jorgenson and Cable (2002) identify three
major differences between e-Commerce
and e-Government: access, structure and
accountability. In e-Commerce ,
businesses are allowed to choose their
customers; however, in e-Government,
agencies are responsible for providing
access to information and services to the
entire eligible population, including
individuals with lower incomes and
disabilities. The digital divide makes this
task of providing universally accessible
online government services challenging.
Also, the structure of businesses in the
private sector is different from the
structure of agencies in the public sector.
Decision-making authority is less
centralized in government agencies than
in other businesses. This dispersion of
authority impedes the development and
implementation of new government
services. The third difference between e-
Commerce and e-Government identified
by Jorgensen and Cable (2002) is
accountability. In a democratic
government, public sector agencies are
constrained by the requirement to allocate
resources and provide services that are “in
the best interest of the public” (Jorgenson
& Cable 2002).
Warkentin et al. (2002) recognize the
political nature of government agencies as
a distinguishing feature of e-Government
from e-Commerce . They also note
mandatory relationships exist only in e-
Government. For instance, legislation,
such as the Government Paperwork
Elimination Act of 1998, obligates
government agencies to “give persons
who are required to maintain, submit, or
disclose information the option of doing so
electronically, when practicable, by
October 21, 2003” (Fletcher 2002).
2.1.3 Constructs
Previous research has found that PCI
factors play a role in user acceptance of
electronic commerce in the private sector
(Gefen et al. 2003; Van Slyke et al. 2004).
In the public sector, citizen adoption of e-
Government should be subject to similar
factors (Warkentin et al. 2002). Therefore,
considering the similarities between
electronic commerce and electronic
government, we use these constructs in
our study of e-Government adoption.
2.2 Perceived Characteristics of
Innovating (PCI)
Moore and Benbasat’s (1991) perceived
characteristics of innovating (PCI) are
based on Rogers’ (1995) Diffusion of
Innovation Theory (DOI), which is used
frequently in information systems research
to explain user adoption of technological
innovations. Diffusion refers to “the
process by which an innovation is
communicated through certain channels
over time among the members of a social
society (Rogers 1995).” An innovation is
“an idea, practice or object that is
perceived as new by an individual or other
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13 Lemuria Carter and France Belanger
unit of adoption (Rogers 1995).” Moore
and Benbasat (1991) identify eight PCI
factors that influence the diffusion of an
innovation: relative advantage,
compatibility, ease of use, result
demonstrability, image, visibility,
trialability, and voluntariness.
Based on previous research (Karahanna
1999; Moore & Benbasat 1991; Plouffe et
al. 2001; Tornatzky & Klein 1982; Van
Slyke et al. 2004) we study the effects of
relative advantage, compatibility, ease of
use and image on citizen intention to use a
state e-Government service. Tornatzky
and Klein (1982) suggest that relative
advantage, compatibility, and ease of use
are the most relevant constructs to
adoption research, thus we include these
three constructs in our study. Relative
advantage is “the degree to which an
innovation is seen as being superior to its
predecessor”; Compatibility refers to “the
degree to which an innovation is seen to
be compatible with existing values, beliefs,
experiences and needs of adopters”; and
perceived ease of use is “the degree to
which a person believes that using a
particular system would be free of effort
(Davis 1989).” Given the amount of
coverage Web-based systems have
received in the popular press, we also
include image in our model. Image refers
to the “degree to which the use of the
innovation is seen as enhancing to an
individual’s image or social status” (Van
Slyke et al. 2004).
3. Research model
Figure 1 presents a high-level research
model that summarizes the constructs
discussed above.
Ease of Use
Relative
Advantage
Image
DOI
I
ntention to
Use
Compatibility
H1
H2
H3
H4
Figure 1: DOI and e-Government adoption
4. Hypotheses
In prior technology adoption literature
(Karahanna et al. 1999; Moon & Kim 2001;
Trinkle 2001) the factors illustrated in
Figure 1 all demonstrate a positive
relationship with use intentions. We expect
the nature of these relationships to remain
the same in the context of electronic
government. Therefore, based on prior
research in e-Commerce and information
technology adoption, four hypotheses are
posited (Table 1).
Table 1: Hypotheses
Name Hypothesis Construct
H1. Higher levels of perceived relative advantage will be positively related to
higher levels of intention to use a state e-Government service.
Relative
Advantage (RA)
H2. Higher levels of perceived image will be positively related to higher
levels of intention to use a state e-Government service.
Image (IM)
H3. Higher levels of perceived compatibility will be positively related to
higher levels of intention to use a state e-Government service.
Compatibility (CT)
H4. Higher levels of perceived ease of use will be positively related to higher
levels of intention to use a state e-Government service.
Ease of Use
(EOU)
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Electronic Journal of e-Government Volume 2 Issue 1 (11-20) 14
5. Methodology
5.1 Sample
To pilot test our model, we administered a
survey instrument to 140 undergraduate
students at a southeastern research
university. Of the 140 surveys
administered, 136 were complete and
used in the analyses. The subjects had an
average of 9 years of experience using a
computer; the average age was 19; and,
63% were male. 98% of the sample uses
the Web everyday; however, the majority
(52%) use the Web to gather information
about or from the government less than
once a month, and 32 % have never used
the Web to gather information about or
from the government. Also, 89% have
never used the Web to complete a
government transaction, such as a license
renewal.
5.2 Instrument development
The items used in this survey were
adapted from previous studies. The
measures of compatibility, relative
advantage, and image were adapted from
Van Slyke et al. (2004). Ease of use was
measured using items adapted from Davis’
TAM model (Davis 1989). The items used
to measure use intentions were adapted
from Pavlou (2003) and Gefen and Straub
(2000). A list of the items is provided in the
appendix. Each item is rated on a scale of
1 to 7 (Strongly Disagree to Neutral to
Strongly Agree).
The reliability of the items was evaluated
using Cronbach’s alpha (Cronbach 1970).
Table 2 presents the results of the
reliability analysis, demonstrating
acceptable reliabilities (above 0.70) for all
scales.
Table 2: Reliability Analysis
Construct # of
Items
Reliability
Relative
Advantage
(RA)
5 .7773
Image (IM) 4* .7824
Compatibility
(CT)
4 .7469
Ease of Use
(EOU)
4* .7222
* Originally this construct was
measured with five items. One
reverse worded item was dropped
to improve reliability.
Factor analysis using principle
components with Promax rotation was
used to evaluate construct validity. As
shown in Table 3, most items loaded
properly on their expected factors.
However, relative advantage items and
compatibility items loaded together.
Table 3: Factor Analysis
Factor Loading
Item
USE RA/CT IM EOU
USE1 .754
USE2 .833
USE3 .778
USE5 .723
RA1 .796
RA2 .836
RA4 .842
RA5 .765
IM1 .832
IM2 .400
IM3 .837
IM5 .828
CT1 .713
CT2 .537
CT3 .741
CT4 .510
EOU1 .701
EOU3 .697
EOU4 .680
EOU5 .697
Relative advantage and compatibility items
also loaded together in other IT adoption
research (Karahanna et al. 1999; Moore &
Benbasat’s 1991) study. Moore and
Benbasat conducted a rigorous study
using multiple judges and multiple sorting
rounds to develop reliable measures of
diffusion of innovation constructs (Rogers
1995). Although the items for RA and CT
were identified separately by the judges
and sorters, all the items for these two
constructs loaded together. Moore and
Benbasat concluded, “this may mean that,
while conceptually different, they are being
viewed identically by respondents, or that
there is a causal relationship between the
two (Moore & Benbasat 1991). ” For
example, “it is unlikely that respondents
would perceive the various advantages of
using [state e-Government services], if its
use were in fact not compatible with the
respondents’ experience or [life] style
(Moore & Benbasat 1991).”
In summary, model and hypotheses
testing was conducted with four
independent variables - perceived relative
advantage, perceived image, perceived
compatibility and perceived ease of use -
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15 Lemuria Carter and France Belanger
and one dependent variable – use
intentions. The basic characteristics of
these variables are presented in Table 4.
Table 4: Final Regression Variables
Variable # Items Mean Stand.
Dev.
RA 4 5.0821 0.9240
IM 3 2.9333 1.1686
CT 2 4.6000 1.0217
EOU 2 5.6179 1.0047
Use 3 4.8714 1.0492
6. Results
The data were analyzed using multiple
linear regression analysis. The purpose of
a regression analysis is to relate a
dependent variable to a set of independent
variables (Mendenhal & Sincich 1993).
Regression analysis was seen as the most
appropriate analytical technique since the
goal of this study was to determine the
relationship between use intention
(dependent variable) and citizen
perceptions of state e-Government
initiatives (independent variables).
Assumptions of multivariate normal
distribution, independence of errors, and
equality of variance were first tested.
There were no violations of these
assumptions. Multicollinearity was not a
concern with this data set as confirmed by
the main effect regression models with
variance inflation factors (VIF range from
1.012 to 2.310). Outlier influential
observations were identified with leverage,
studentized residuals, and Cook’s D-
statistic. This analysis indicated that there
were no problems with respect to
influential outliers.
The model explains 50 percent of the
variance in citizen adoption of e-
Government; adjusted R Square is .500,
F=35.714, p<.0001. Three of the four
adoption factors - relative advantage,
image and compatibility - were found to be
significant in predicting citizen intention to
use state e-Government services. Table 5
presents the results of the individual
hypotheses being tested.
Table 5: Hypothesis Testing
Variable Coeff. t-
value
Sig. Supported
H1 RA .255 2.671 .009 YES
H2 IM .206 3.421 .001 YES
H3 CT .439 4.811 .000 YES
H4 EOU .066 .817 .416 NO
7. Discussion
The purpose of this research was to use
PCI constructs to test a model of e-
Government adoption. Perceived relative
advantage, image, and compatibility were
found to be significant in predicting citizen
intention to use state e-Government
services. These factors are summarized in
Figure 2. We discuss the results in this
section, and present suggestions for
practitioners with respect to what can be
done to improve citizens’ perceptions in
section 9.2 (Implications for Practice).
Relative
Advantage
Image Intention to
Use
Compatibility
.255
.206
.439
Figure 2: DOI and e-Government
adoption
7.1 Relative advantage
Higher levels of perceived relative
advantage increase citizens’ intentions to
use state e-Government services. State
government agencies should identify and
communicate to citizens the advantages of
using online services as opposed to other
means of retrieving information from and
completing transactions with state
government agencies. As a result of e-
Government services, citizens receive
faster, more convenient services from a
more responsive and informed
government (Trinkle 2001). For example,
state agencies could encourage the
adoption of online license renewal by
emphasizing its convenience and speed
compared to the traditional method of
visiting the brick-and-motor Department of
Motor Vehicles (DMV) office. Online
license renewal can be completed from
the home or office 24 hours a day, seven
days a week. The availability of the service
isn’t limited to standard business hours.
The citizen can complete this transaction
whenever and from wherever it is most
convenient. The online service is also
quicker than the traditional method since
citizens don’t have to travel to a physical
branch of the DMV and then wait in line.
The online service is immediately available
to each citizen individually. The
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Electronic Journal of e-Government Volume 2 Issue 1 (11-20) 16
www.ejeg.com ©Academic Conferences Ltd
comparative benefits of other online
services such as license renewal or tax
filing should be shared with citizens by
appropriate agencies to increase adoption
of these services.
7.2 Image
Higher levels of perceived image
enhancing value of e-Government
increase citizens’ intention to use state
government services online. In other
words, those who regard the use of state
e-Government services as prestigious will
have higher intention to use state e-
Government services than those who do
not. For example, citizens who view the
adoption of e-Government services as a
way to appear technically savvy and/or
politically progressive will demonstrate a
higher intention to use e-Government
services.
7.3 Compatibility
Higher levels of perceived compatibility
are associated with increased intentions to
adopt state e-Government initiatives.
Many cultures now embrace Internet
technology in business (e-Commerce and
e-business) and leisure (instant
messaging and virtual communities).
Citizens who’ve adopted these Internet-
supported initiatives are likely to adopt
state e-Government services as well.
Citizens who have adopted e-Commerce
initiatives can be expected to view e-
Government initiatives as compatible with
their lifestyle. E-Commerce adopters are
comfortable searching for information and
services, providing personal information
and conducting transactions electronically.
These citizens will have higher intentions
to use e-Government services than those
who view these services as incompatible
with their lifestyle.
7.4 Ease of use
Contrary to hypothesis 4, higher levels of
perceived ease of use are not significantly
associated with increased use intentions
of e-Government services. This
unpredicted outcome could be the result of
the use of college students as subjects.
Our sample consisted of experienced
computer users whose perceptions of
ease of use probably differ from the overall
population of citizens. The subjects have
an average of nine years of experience
using a computer and 98 % of the sample
uses the Web everyday. Since these
college students are confident in their
ability to use online services,
apprehension provoked by potential
complexity is not a significant deterrent of
e-Government adoption.
8. Limitations
Our sample consisted of undergraduate
students and the use of student subjects
may limit the generalizability of the results.
Although several studies in technology
acceptance have used student subjects
(Davis 1989; Gefen & Straub 2000; Moon
& Kim 2001; Trinkle 2001) college student
demographics, such as experience using
the Internet, differ from the demographics
of the overall population of citizens. A
majority of college students frequently use
and have easy access to Internet services.
However, there are many citizens who are
members of the digital divide, in the United
States and other countries, who do not
have easy access to or much experience
with Internet technology. This study is the
pilot of a larger scale study of citizen
adoption of e-Government initiatives. The
next phase of data collection will elicit
participation from a broad diversity of
citizens in age, gender, ethnicity, and
social groups.
9. Implications
9.1 Implications for research
This study presents an introductory model
that explains 50 percent of the variance in
citizen adoption of state e-Government
initiatives. This model can serve as a
starting point for other e-Government
adoption research, while encouraging
further exploration and integration of
additional adoption constructs. In the
future, we plan to integrate constructs from
the technology acceptance model (Davis
1989) and the Web trust literature
(Belanger et al. 2002; Gefen et al. 2003;
McKnight et al. 2002) to develop a more
comprehensive, yet parsimonious model
of e-Government adoption.
9.2 Implications for practice
The study reveals three significant
indicators of citizens’ intention to use state
government services online. State
agencies should promote citizen
acceptance and use of e-Government
services by manipulating these factors:
17 Lemuria Carter and France Belanger
perceived relative advantage, perceived
image, and perceived compatibility.
Specifically, state government agencies
should capitalize on the unique benefits of
online services, promoting their use as a
status symbol, and indicating the services’
congruence with a citizen’s lifestyle. They
could send citizens a letter explaining the
speed, convenience and accessibility of
online government services. In this letter,
government agencies could also increase
citizens’ perceptions of compatibility by
noting the similarities between traditional
government services and online
government services. For instance, online
license renewal may utilize the same form
used in the manual process to allow
citizens to easily incorporate e-
Government services usage into their life.
Another way to enhance perceived
compatibility could be to provide tangible
verification of transaction completion.
Many citizens are accustomed to receiving
a paper receipt that can be utilized to
verify a transaction. The lack of this
tangible record may make many citizens
reluctant to engage in electronic
transactions. Agencies could still make
paper receipts available to citizens upon
request via mail or fax. To enhance the
perceived image of e-Government
adopters, agencies could pursue
endorsements from local celebrities or
well-respected citizens in the community
advocating the use of state e-Government
services.
10. Conclusion
This study uses constructs from Moore
and Benbasat’s (1991) perceived
characteristics of innovating to develop a
parsimonious model of citizen adoption of
state e-Government services. Perceived
relative advantage, perceived image, and
perceived compatibility are significant
elements of e-Government adoption. The
model explains 50 percent of the variance
in citizen intention to use e-Government
services. As e-Government grows in
importance and priority for governments
worldwide, an understanding of the factors
that influence citizen adoption of these
online services is invaluable.
11. Acknowledgements
We would like to extend a special thanks
to Marijn Janssen, chair of the
eGovernment Services Workshop of the
5th International Conference on Electronic
Commerce (ICEC) 2003, for his
involvement in the publication of this
study. We would also like to extend our
gratitude to the Accounting and
Information Systems Department at
Virginia Tech for its support of this study.
References
Bélanger, F, J Hiller, and W J Smith
‘Trustworthiness in Electronic
Commerce: The Role of Privacy,
Security, and Site Attributes’
Journal of Strategic Information
Systems, Vol 11 No 3/4
(December 2002) pp 245-270.
Carter, L and Belanger, F ‘Diffusion of
Innovation and Citizen Adoption of
E-Government Services’ The
Proceedings of the First
International E-Services
Workshop Vol 1 No 1 (September
2003) pp 57-63.
Cronbach, L, Essentials of Psychology
Testing, Harper and Row, New
York (1970).
Davis, F D ‘Perceived Usefulness,
Perceived Ease of Use and User
Acceptance of Information
Technology’ MIS Quarterly, Vol 13
No 3 (September 1989) pp 319-
340.
Fletcher P.D. ‘The Government Paperwork
Elimination Act: Operating
instructions for an electronic
government’ International Journal
of Public Administration, Vol 25
No 5 (May 2002) pp 723-736.
Gartner Group. ‘E-Government strategy:
Cubing the circle. Research
Notes, Strategic Planning
Assumption’ (April 2000).
Gefen, D and D Straub. ‘The Relative
Importance of Perceived Ease of
Use in IS Adoption: A Study of E-
Commerce Adoption’ Journal of
the Association for Information
Systems. Vol 1 No 8 (October
2000) pp 1-28.
Gefen, D, E Karahanna and D Straub
‘Trust and TAM in Online
Shopping: An Integrated Model’
MIS Quarterly. Vol 27 No 1 (March
2003) pp 51-90.
GAO. General Accounting Office. D.
McClure. ‘Electronic Government:
Challenges Must Be Addressed
with Effective Leadership and
Management’ (July 2001).
www.ejeg.com ©Academic Conferences Ltd
Electronic Journal of e-Government Volume 2 Issue 1 (11-20) 18
Hiller, J S and F Belanger ‘Privacy
Strategies for Electronic
Government’ E-Government
Series, The Pricewaterhouse
Coopers Endowment for The
Business of Government.
(January 2001).
Pavlou, P. A. (2003). Consumer
Acceptance of Electronic
Commerce: Integrating Trust and
Risk with the Technology
Acceptance Model. International
Journal of Electronic Commerce. 7
(3), 69-103.
ICMA Electronic Government Survey
Findings. (October 2002).
eNewsletter
http://egov.e21corp.com/site/html/
eNewsletter/oct2002/survey.html.
Accessed on 3/20/2003.
Plouffe, C R, J Hulland and M
Vandenbosch ‘Research Report:
Richness Versus Parsimony in
Modeling Technology Adoption
Decisions –Understanding
Merchant Adoption of a Smart
Card-Based Payment System’
Information Systems Research.
Vol 12 No 2 (2001) pp 208-222.
James, G ‘Empowering bureaucrats’ MC
Technology Marketing
Intelligence, Vol 20 No 12
(December 2000) pp 62-68. Rogers, E. M. Diffusion of Innovations,
The Free Press, New York,
(1995).
Jorgenson, D and S Cable ‘Facing the
Challenges of E-Government: A
Case Study of the City of Corpus
Christi, Texas’ SAM Advanced
Management Journal Vol 67 No 3
(Summer 2002) pp 15-21.
Tornatzky, L. G. and J.K. Klein ‘Innovation
characteristics and innovation
adoption-implementation: A meta-
analysis of findings’ IEEE
Transactions on Engineering
Management, Vol 29 No 1
(February 1982) pp 28-45.
Karahanna, E, D Straub, N Chervany
‘Information Technology Adoption
Across Time: A Cross-Sectional
Comparison of Pre-Adoption and
Post-Adoption Beliefs’ MIS
Quarterly Vol 23 No 2 (June 1999)
pp 183-213.
Trinkle, S. ‘Moving Citizens from in Line to
Online: How the Internet is
Changing How Government
Serves its Citizens’ (September
2001). Laudon, K and J Laudon Essentials of
Management Information Systems
Fifth Edition. Prentice Hall: New
Jersey (2003).
Van Slyke C, F Bélanger and C L
Comunale ‘Factors Influencing the
Adoption of Web-Based Shopping:
The Impact of Trust’ The Data
Base for Advances in Information
Systems, (Spring 2004) Vol 35 No
2.
McKnight, H, V Choudhury, and C Kacmar
‘Developing and Validating Trust
Measures for e-Commerce : An
Integrative Typology’ Information
Systems Research, Vol 13 No 3
(2002) pp 334 -359 .
Warkentin, M, D Gefen, P Pavlou and G
Rose ‘Encouraging Citizen
Adoption of e-Government by
Building Trust’ Electronic Markets.
Vol 12 No 3 (2002) pp 157-162.
Mendenhal, W. and T. Sincich ‘Second
Course in Business Statistics’
Dellen/Macmillian, New York.
(1993).
Moon, J M and Y G Kim ‘Extending the
TAM for a World-Wide-Web
Context’ Information &
Management (2001) Vol 28 pp
217-230.
Moore, G. C. and I. Benbasat
‘Development of an instrument to
measure the perceptions of
adopting an information
technology innovation’ Information
Systems Research Vol 2 No 3
(1991) pp 173-191.
OMB, Office of Management and Budget
‘E-Government Strategy’
(February 2002).
www.ejeg.com ©Academic Conferences Ltd
19 Lemuria Carter and France Belanger
Ease of Use (EOU)
12. Appendix Learning to interact with a state
government Website would be easy for
me.
State e-Government adoption items
I believe interacting with a state
government Website would be a clear and
understandable process.
Use Intentions (USE)
I would use the Web for gathering state
government information. I would find most state government
Websites to be flexible to interact with.
I would use state government services
provided over the Web. It would be easy for me to become skillful
at using a state government Website.
Interacting with the state government over
the Web is something that I would do.
I would use the Web to inquire about state
government services.
Relative Advantage (RA)
Using the Web would enhance my
efficiency in gathering information from
state government agencies.
Using the Web would enhance my
efficiency in interacting with state
government agencies.
Using the Web would make it easier to
interact with state government agencies.
Using the Web would give me greater
control over my interaction with state
government agencies.
Image (IM)
People who use the Web to gather
information from state government
agencies have a high profile.
People who use state government
services on the Web have a high profile.
People who use the Web to gather
information from state government
agencies have more prestige than those
who do not.
Interacting with state government
agencies over the Web enhances a
person’s social status.
Compatibility (CT)
I think using the Web would fit well with
the way that I like to gather information
from state government agencies.
I think using the Web would fit well with
the way that I like to interact with state
government agencies.
Using the Web to interact with state
government agencies would fit into my
lifestyle.
Using the Web to interact with state
government agencies would be
incompatible with how I like to do things.
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