Exploring Factors Relating to the Use of E-Government Services, as Perceived by Citizens in Trinidad and Tobago

“Exploring Factors Relating to the
Use of E-Government Services,
as Perceived by Citizens
in Trinidad and Tobago”
A Brief Presentation of Purpose and Findings
Distilled from: A Research Project, submitted in Partial Fulfilment of the Requirements
for the Degree of Master of Science in Management Studies, of The University of the West Indies
Abdullah H. Mohammed, 2010
Department of Management Studies, Faculty of Social Sciences, St. Augustine Campus
Contact: Abdullah Mohammed (abdullah.mohammed@gmail.com; 868-684-8789)

Abstract
From as early as 1999, the Government of Trinidad and Tobago recognized the
positive benefits that ICT could bring to its operations, to the private sector, and to
its citizens. Since then, much work has been done to lay the foundations for e-
Government and e-Business. Although the potential benefits are high, progress
has been slow, and because of this, citizens have had little exposure to local e-
Government and e-Commerce service offerings.
This study takes a first look at the factors that would affect Trinidad and Tobago
citizens’ intentions to use an online, transactional e-Government service using
constructs from the Technology Acceptance Model (Davis 1989), the Diffusions of
Innovations Theory (Rogers 1995), two forms of Trust (Carter and Bélanger 2005),
and user characteristics. Hypothesis testing revealed that the six constructs in the
model were significantly correlated with use intentions, along with three other
demographic variables. Interestingly, Gender, Age and Agent assistance were not
found to be statistically significant. Findings from correlations, the factor analysis
and the multiple regression model were presented, and the implications for e-
Government leaders and project implementers are discussed.
Keywords: e-Government, adoption, trust, Technology Acceptance Model,
Diffusion of Innovations theory, User Characteristics, Trinidad and Tobago
2Abdullah Mohammed (2010)

Acknowledgements
I am eternally grateful to God for giving me the guidance and the opportunity to
complete this work. It is said that whoever does not thank the people is not
thankful to God, and so I would like to thank the my loving parents, wife and
children for their support, patience and encouragement, my brother Riaaz for his
invaluable assistance with data collection, the management and staff at the IRD,
my Supervisor Mr. Terrence Brunton, my lecturer Mr. Surendra Arjoon, and Mr.
Tracy Hackshaw and Ms. Denyse White for allowing me to be part of the e-
Government efforts in Trinidad and Tobago. I would also like to acknowledge and
thank Dr. Ali at the KFU whose SPSS videos were extremely helpful, as they lead to
a fuller understanding of the texts and the readings. And finally I am grateful to the
creators of two exceptional and free “backup in the cloud” services, namely
Dropbox and Mendeley, which gave me incredible peace of mind during the
process.

E-Government
While there are many varying definitions (Palvia and Sharma, 2007), e-Government
can simply be defined as “the use of technology to enhance the access to and
delivery of Government services to benefit citizens, business partners and
employees” (Deloitte 2000). This definition is useful because it addresses many of
the fundamental issues a modern Government will face in the process of
delivering its services, including access, accessibility, the digital-divide, multi-
channel delivery of services (by means of the Internet, mobile phone services,
multi-service counters, etc.), and the management of multiple stakeholders (C.
Chan, Tan, and C. M. L. Chan, 2003), which includes service delivery to citizens
(G2C), business partners (G2B and G2G) and the Government’s own employees
(G2E). A modern Government must juggle all of this, while at the same time
proactively try to avoid expensive project failure and “Government failure” (R.
Heeks 2006).
What makes this definition further beneficial, in spite of its age, is that it implies
that citizens and other stakeholders must eventually derive benefit from e-
Government efforts. It thereby suggests that e-Government project leaders and
implementers must not only overcome supply-side challenges (such as new
technology and inherent Government bureaucracy), but they must at the same
time pay close attention to demand-side factors pertaining to adoption and usage
of the services they are striving to implement. Accenture (2007) recognized this,
by stating that high-performing Governments are those that not only maximize
public value based on inputs, but are also demand-driven, citizen-centered and
outcome-focused. Heeks et al. (2006) and Kumar et al. (2007) both agree that a
‘high-performance’ Government must focus on customer service delivery (i.e. the
demand-side) and the factors that affect it.
This dichotomy is found as well in the literature (Reece 2006). In their review on e-
Government adoption, Titah and Barki (2006) state that the two main challenges
that Governments were found to be facing were: (1) understanding the factors
influencing the adoption of e-Government systems, and (2) the integration of
various backend systems, referring to demand and supply respectively.

Problem Background (i)
The Government of the Republic of Trinidad and Tobago (GoRTT) began its e-
Government journey as early as 1999 with the Report of the National e-Commerce
Policy Committee (NECPC 1999) wherein it was recognized that information and
communications technology (ICT) can be effectively used to strategically transform
the business operations of Government. These “e-Government” transformations
would bring business-level effectiveness to the operations of what is essentially
the largest organization and employer in the country. Thereafter, efforts were
made at developing a more robust, comprehensive National Strategy for ICT
(Austin 2002) and by 2003, a comprehensive National ICT Plan (dubbed
‘FastForward’) was complete (MPA 2003). The five-year Plan contained ‘Path-
Finder’ projects with approved budgets, an organizational structure for delivery,
which was the National ICT (NICT) Division, under the oversight of the National
Chief Information Officer, in the Ministry of Public Administration (MPA). These
projects were aimed at establishing key policies, regulations and infrastructure for
the promotion of e-Commerce and e-Government in Trinidad and Tobago, and are
akin to the foundational elements established in the framework for building an
Information Society developed by Hilbert and Katz (2003).
By 2010, the NICT Division had completed several of these projects, the most
significant of which were its Government Information Portal and Centralized
Services Platform (at www.gov.tt), the establishment of satellite “ttConnect” multi-
service Service Centres, and the bringing to Parliament of two essential pieces of
legislation for e-Payments, and so by extension e-Business and e-Government.
These were the Data Protection Bill (GoRTT 2009a), and the Electronic
Transactions Bill (GoRTT 2009b). These Bills are core components of a country’s
enabling legislative framework (Hilbert and Katz 2003), which would effectively
allow businesses and the Government to safely transact with their stakeholders
online.

Problem Background (ii)
Apart from the efforts of the central NICT Division to lay the foundations for e-
Government, and to promote inter alia a centralized platform for Government
services, other Government entities are striving to make positive changes in their
own business operations using internet-based, transactional, ICT solutions that go
beyond mere static, information-based service offerings. The more noteworthy of
these to date remain the Inland Revenue Division’s online self-assessment (tax)
application (at www.ird.gov.tt), followed closely by the online Companies Name
Search and Reservation application (at www.legalaffairs.gov.tt), and the Bills and
Acts online database at www.ttparliament.org.
Notwithstanding these online applications, some Government entities have made
efforts at a complete overhaul of their backend operations in order to build back-
end e-Business/e-Government infrastructure to support their operations. The
most noteworthy of these would be the Government Services Portal Platform
(built on IBM’s WebSphere), the Ministry of Trade and Industry’s Trade Facilitation
Infrastructure Project (MTI 2010), the Ministry of Legal Affairs Civil Registry (Birth,
Adoptions, Marriages and Deaths), and the Government-wide HR/Payroll
application built on Oracle/PeopleSoft.
The Trinidad and Tobago Government is evidently laying the foundation for e-
Government by building and integrating its backend systems and providing
introductory online services. Unfortunately though, not much effort is being put
towards understanding the factors that will influence the usage and adoption of
these new services.

Statement of Problem (i)
Government processes that are digitized and offered online presents many
opportunities for both citizens and Governments, particularly for developing
countries (Ndou 2004), such as cost reduction, transparency and proliferation into
other sectors of the economy. The underlying objective from the supply-side is to
achieve connected, joined-up, “borderless” Government, often through extensive
process reengineering (UNDESA 2008). The gargantuan task of re-engineering
Government legacy applications and policies (where relevant “e-policies” even
exist), coupled with various informational, technological, managerial, regulatory
and institutional antecedents (Hilbert and Katz 2003) and challenges (Gil-Garcia
and TA Pardo 2005) add significant risk to e-Government projects, and greatly
lengthen the eventual delivery of the intended outcomes of the e-Government
project.
This conceivably is what has happened with GoRTT e-Government projects,
thereby resulting in very little transactional services being offered online. The
outcome therefore, is citizens and other stakeholders have little experience with
these redefined ways of interacting with their Government. Because of this lack of
exposure, it is possible that potential users of these services may be harbouring
negative perceptions and attitudes, affecting the use and adoption of these new
service-delivery channels. This can in the end affect the success of the
implementation, and the net benefits derived by the citizens. When transactional
services, such as e-Health and e-Tax filing, do eventually arrive in Trinidad and
Tobago, an unprepared Government may find itself after the fact having to strive
hard at convincing its users of the benefits (and perhaps safety) of transacting with
Government online. Complicating this, overall lack of trust and confidence in e-
Government can lead to low usage rates across all newly deployed e-Government
services.

Statement of Problem (ii)
Much can be done in tandem with development and reengineering of Government
systems, and it is imperative that citizens and other stakeholders at all levels be
included in the design and testing processes: the so-called “citizen-centric
practice” (Gupta, 2008; UNDESA, 2010). A prudent e-Government leader will
conduct several litmus tests to determine the perceptions of potential users
towards adoption of the system, before, during and after deployment, to ensure
maximum usage.
Furthermore, demand-side issues that relate to adoption are particularly
important for Trinidad and Tobago, which placed 46th of 70 countries on the EIU’s
e-readiness scales (EIU 2009) and earlier, 54th of 70 in the UN e-Government
readiness scale (UNDESA 2008). This low e-readiness rank indicates that much
needs to still be done not only in the development of online services,
telecommunications infrastructure and training and development, but also in the
promotion and participation in and use of these services.

Research Objectives: (i) Purpose of the Study
A scan of several research databases revealed that there is no empirical research
investigating the demand for e-Government services in Trinidad and Tobago. This
may be because the e-Government environment is still developing, and most
transactional services have yet to reach citizens in a real way. In addition, much of
the implementers’ focus is directed at hurdling foundational supply-side
challenges, such as legacy systems and Government bureaucracy. This study
proposes to formally examining the factors relating to the citizens’ use of e-
Government services in the Trinidad and Tobago context. The intention is to try to
identify the significant factors that e-Government leaders and implementers
should consider before, during and after deployment, to maximize the benefits to
both the Government and its stakeholders, and, to serve as a springboard for
further research in the field.

Research Objectives: (ii) Nature of the Study
To adequately examine the factors of e-Government demand and usage, a
Government service with e-Government potential needed to be selected. Ideally,
the service needed to be transactional (that is, it should go beyond merely
providing static information online), should have the potential for electronic
payments (‘e-payments’), and should be common to a large majority of citizens.
Filing state taxes is one of the most essential of Government services and has great
potential as an e-Government service, although at the same time being one of the
most difficult to implement successfully (Rocheleau and Wu 2005). E-Payments, in
particular G2B tax remittances and G2C tax returns, are on the Trinidad and
Tobago’s e-Government agenda (MPA 2003). Studying the factors that will affect
the end-user take-up of an e-Tax filing service therefore has significant benefits to
the e-Government planners and implementers of this and other e-Government
services with e-payment components.
At present, the Inland Revenue Division (IRD) of the Ministry of Finance offers an
online e-Tax Assessment service. This service is offered at the Division’s website
(www.ird.gov.tt), and at present it allows citizens to calculate their tax obligations,
and print the return, which then needs to be physically submitted to the IRD
Office. The main limitation to the service is that it does not allow the transaction
to be fulfilled online, so there is no e-payment and the transaction must be
completed offline. A user may only use the service to obtain an estimate for their
tax return. According to the Division’s IT Director, the backend application is
actually capable of fulfilling the online transaction, inclusive of accepting
payments, but the Division is yet to deploy this component because of Trinidad
and Tobago’s weak e-Commerce legislative and regulatory environment. In view of
the Government’s push for the aforementioned enabling legislation, once the two
main Bills are passed and enacted, the Division will strongly consider bringing the
full tax-filing service online.
Building on the seminal work of Carter and Bélanger (2005) in the area of e-
Government use intentions, the study therefore aims at investigating the
significant factors relating to citizens’ use intentions of the future tax-filing service
at the IRD.

Research Objectives: (iii) Research Question
The research question is a fact-oriented, information gathering question that best
states the objectives of the research study (Cooper and Schindler 2003). The
research question for this study was: What attitudinal factors relating to the use of
Trinidad and Tobago e-Government services should planners and implementers be
concerned with in order to maximize citizens’ usage and adoption? Carter and
Bélanger (2005) proposed a model for examining Use Intentions (the dependent
variable), which is built on the Technology Acceptance Model (FD Davis 1989), the
Diffusions of Innovation Theory (Rogers 1995), and other two other Trust
variables, Trust of the Internet and Trust of the Government. Their regression
model (Figure 1) explained 85.9% of the variance (adjusted R2). Image and
Complexity were found to be not significant, and so were left out in this study also.
Figure 1 The Research Model, adopted from Carter and Bélanger (2005)
Diffusion of Innovations (Rogers 1995)
Compatibility ComplexityImage
Relative
Advantage
Technology Acceptance Model (Davis 1989)
Perceived
Usefulness
Perceived Ease of
Use
Trustworthiness
Trust of the
Internet
Trust of
Government
Intention to Use (DV)

Research Objectives: (iv) Hypotheses
Fourteen hypotheses were posed to answer the research question, which follows
closely with the model and instrument proposed by Carter and Bélanger (2005),
but which also includes demographic questions for further analysis, including
Gender, Income Level, Age, Internet Access, Access to a Credit Card that is able to
make international purchases, Computer Experience, and e-Commerce Experience.
As it is an exploratory study, a correlational (descriptive) study design will be used
to determine which variables significantly correlate with each other (Cooper and
Schindler 2003), based on the following hypotheses.
H01: Citizens’ perceptions of usefulness of the web-application are not related to the use of e-Government
services (Perceived Usefulness).
H02: Citizens’ perceptions of ease of use of the web-application are not related to the use of e-Government
services (Perceived Ease of Use).
H03: Citizens’ perceptions of relative advantage by using the web-application are not related to the use of e-
Government services (Perceived Relative Advantage).
H04: Citizens’ perceptions of compatibility with the web-application are not related to the use of e-
Government services (Perceived Compatibility).
H05: Citizens’ trust in the Internet is not related to the use of e-Government services (Trust in the Internet).
H06: Citizens’ trust in Government is not related to the use of e-Government services (Trust in Government).
H07: Citizens’ Gender is not related to the use of e-Government services (Gender).
H08: Citizens’ Age is not related to the use of e-Government services (Age).
H09: Citizens’ Household Income Level is not related to the use of e-Government services (Income Level).
H010: Citizens’ Level of Internet Access is not related to the use of e-Government services (Internet Access).
H011: Citizens’ Level of Computer experience is not related to the use of e-Government services (Computer
Experience).
H012: Citizens’ Level of access to a Credit Card is not related to the use of e-Government services (Credit Card
Access).
H013: Citizens’ Level of e-Commerce (online shopping) experience is not related to the use of e-Government
services (e-Commerce Experience).
H014: Citizens’ use of an Agent to file taxes is not related to the use of e-Government services (Agent filing).
A principal component analysis was conducted to determine how well the scales
load together, and the results of a multiple regression similar to Carter and
Bélanger (2005) will be presented for comparison, under additional findings
(Section 4.8).
Abdullah Mohammed (2010) 12

Assumptions and Limitations
With every study there are assumptions, parameters and limitations in scope. For
the purposes of this study the assumptions were as follows.
• The selected sample of patrons at the IRD office are representative of
potential users of an end-to-end e-Government service;
• The selected Government service is near enough to a typical end-to-end
online service that users should find convenient or beneficial to use
(compared with the manual over-the-counter service);
• Respondents answered the questionnaire to the best of their ability
regarding their attitudes on online Government and their use intentions.
• Based on its use as a dependent variable in many other Information Systems
(IS) studies (F. D. Davis, 1989; Moore and Benbasat, 1991; Taylor and Todd,
1995; Venkatesh, Morris, G. B. Davis, and F. D. Davis, 2003; Delone and
McLean, 2003), “use intentions” is taken as the dependent variable.
Regarding the limitations of the study, it must be stated that this is an exploratory,
correlational study, attempting to examine the significance of various constructs
on the dependent variable in the current Trinidad and Tobago context. It should be
noted also that correlations do not imply causation, only that either X causes Y, Y
causes X, X and Y are activated by one or more other variables, or X and Y
influence each other reciprocally (Cooper and Schindler 2003). However there are
benefits in examining the significance of the variables in the first instance, and
more in-depth analysis could be the subject of future research.
Additionally, as sampling was conducted at the IRD office, time was limited, so
data was collected for two days using convenience sampling (Cooper and Schindler
2003), which is to say, as many patrons entering who were willing to participate on
those two days were sampled. During this time 90 valid cases were returned,
thereby somewhat limiting the statistical power of the exercise (Cohen 1992).

Significance of the Study
Despite its limitations, the cross-sectional study does bring insight to Trinidad and
Tobago e-Government planners and implementers. As mentioned in Accenture
(2007) and built upon in Heeks et al. (2006) and Kumar et al. (2007), and others,
‘high-performance’ Governments, and their leaders, must focus on customers and
customer service delivery, and the factors that affect them. Much money has
already been spent on ICT in Government since 2003, and the return on this
investment will be gauged by the actual take-up of the people the services are
designed to serve. Despite this, there is little evidence that the Government’s ICT
leaders adequately address the specific needs of its users, by carefully examining
the factors that can affect usage and adoption. Research into the factors that
affect user adoption of e-Government services in Trinidad and Tobago represents
an early look into the demand side of the Government’s potential online offerings,
and the beginnings of developing an understanding the Government’s client-base,
which to date has not been done in a systematic, empirical way. Understanding
what can cause stakeholders to either use or not use a service can help ICT leaders
develop proactive measures to reduce user deterrents, and thereby sidestepping
major usage and adoption issues. Research such as this also contributes to the
growing body of e-Government research, particularly in developing regions.

Summary of Data Analysis Procedures
After coding and the initial analysis, the data was first examined according to the
recommendations found in (Hair et al. 2008). The primary focus was to understand
the data and test the assumptions for further analysis, such as normality. Missing
data was not necessarily an issue, though outliers posed somewhat of a problem.
Attempts at their removal (both univariate and multivariate) did not improve
normality results. One-sample Kolmogorov-Smirnov (non-parametric) tests were
used to test for normality (the population is expected to be normal). The data was
mostly negatively skewed and so had to be transformed. Several transformations
were attempted using SPSS as recommended by Hair et al. (2008). Though the
number of cases could have been improved, a principle component analysis (factor
analysis) was still performed to see how well the data would load onto the factors,
and to compare this with the results found in Carter and Bélanger (2005). The
results loaded better on six factors (rather than seven), even after VARIMAX and
EQUAMAX rotations, and so were very close to Carter and Bélanger (2005).
Hypothesis testing was conducted using Pearson’s r for the scale variables, and
Kendall’s tau for the remaining demographic and user-characteristic variables.
Finally, a test multiple regression was conducted to extend the findings. The
resultant model was found to be significant.

Data Analysis: Nominals and Ordinals
From descriptives, and the pie charts in below, we see that more than half of the
respondents were not aware that the IRD had an online self-assessment service
that would help them prepare their assessment beforehand. There was more or
less an even number of males and females, and approximately 69% of the
respondents were 40 years old or less. Household income had the most non-
responsiveness with the mode in the $5001-$10000 bracket. The majority of the
respondents (63%) accessed the internet most frequently at home followed by at
the office (27%). Interestingly, 79% of the respondents had over 6 years of
computer experience, 60% of the respondents had a valid international credit card
and just under half of the respondents made a successful online (e-commerce)
purchase . These statistics seem to bode well for the adoption of a web-based
transactional service.

Data Analysis: Histograms

Data Analysis: Scale Variable Plots

Data Analysis: Univariate and Multivariate Outliers

Data Analysis: Factor Analysis (i)
Factor analysis is a technique used for identifying groups or clusters of variables
(Field 2005). It has three main uses: (i) it helps researchers identify the structure of
the variables, (ii) in instrument development, and (iii) as a data-reduction
technique to reduce the number of factors in a model. For example, Carter and
Bélanger (2005) ran a factor analysis on their data before conducting the multiple
regression, and based on their results, were able to reduce their two Trust factors
into a single ‘TRUST’ variable for the regression. Principle Component Analysis was
used, though technically not a factor analysis, they often yield similar results (Field
2005).
Factor Analyses are extremely sensitive to sample size (Ford, MacCallum, and Tait
1986; Fabrigar et al. 1999; Costello and Osborne 2005) and Vanvoorhis and
Morgan (2007) suggest that the researcher start at 300. With a modest participant
amount of 90, factors were expected not to load properly, but the results of the
analysis are still presented for discussion. Despite only 90 cases though, the KMO
measure for sampling adequacy (which tests whether the partial correlations
among variables are small) was 0.855 (“meritorious”), and Bartlett’s Test for
Sphericity was significant, indicating that correlation matrix is an not identity
matrix and it is safe to proceed with a factor analysis.
The initial solution resulted in 6 factors, and forcing SPSS to use 7 factors did not
improve the factor loadings, even after rotation. Two rotations were attempted:
Varimax and Equamax with Varimax giving better loading results (Table 9). The
factors TRUS_S, PU, USE, TRUS_I loaded correctly with PEOU mixed with CT and
RA. The analysis conducted by Carter and Bélanger (2005) with similar variables
also resulted in CT and RA loading together.
As mentioned, because the number of cases was insufficient, the results of the
analysis cannot be relied upon completely, so for the remainder of the analysis the
initial 7 variables would be used, but the results are presented for future
consideration and research.

Data Analysis: Factor Analysis (ii)
Rotated Component Matrix (VARIMAX)
Factors PEOU
CT RA
TRUS_
S
PU USE CT/RA TRUS_
I
Perceived Ease of Use 5 .830
Relative Advantage 1 .730
Compatibility 1 .617
Trust of the Govt 4 .894
Perceived Usefulness 4 .774
Use Intentions 2 .890
Trust of the Internet 1 .800

Data Analysis: Correlations (TABLE 13)
Hyp. Variable Use Intentions Sig.
(2-tailed)
Sig. at
0.01 level
Reject
H0?
H01 Perceived Usefulness 0.621 0.000 ** YES
H02 Perceived Ease of Use 0.336 0.001 ** YES
H03 Relative Advantage 0.567 0.000 ** YES
H04 Compatibility 0.695 0.000 ** YES
H05 Trust of the Internet 0.386 0.000 ** YES
H06 Trust of the Govt 0.342 0.001 ** YES
H07 Gender 0.051 0.568 NO
H08 Age Group (yrs) 0.055 0.509 NO
H09 Household Income Group
(TT$/month)
-0.158 0.061 NO
H010 Access to the Internet -0.236 0.007 ** YES
H011 Computer Experience -0.158 0.060 NO
H012 International Credit Card 0.294 0.001 ** YES
H013 Successful Online Purchase 0.276 0.002 ** YES
H014 Agent Filing 0.016 0.862 NO
Correlations vary from -1 to 0 to +1. The nearer the absolute value is to 1, the
stronger the correlation. From Table 10, Perceived Usefulness, Relative
Advantage and Compatibility showed moderate to strong positive, statistically
significant correlations with Use Intentions (>0.5), while Perceived Ease of Use,
Trust of the Internet, Trust of the Government, Possession of an International
Credit Card, and having made an e-commerce purchase all had weaker though
positive statistically significant correlations. Access to the Internet had a weak,
but negative statistically significant correlation. The null hypotheses for these
variables were rejected. Correlations between Gender, Age Group, Computer
Experience and Agent filing to Use Intentions were not found to be statistically
significant, and so the null hypothesis was not rejected. A more detailed analysis
will be presented as a discussion in Section 5.
It should be noted that lower values for the Access to the Internet question
actually represents internet access in the Home and in the Office, as opposed to
other places such as at school or in a cybercafé (Table 1 Measurement scales and
encoding). As the variables correlate together, this could be interpreted that
users who access the internet more at home or in the office would be more
inclined to use the e-Government service.

Data Analysis: Multiple Regression Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig. Support?
B Std.
Error
Beta
(Constant) 0.329 0.115 2.857 0.005
Perceived Usefulness 0.362 0.118 0.32 3.073 0.003 YES
Perceived Ease of Use -0.284 0.139 -0.202 -2.037 0.045 YES
Relative Advantage -0.035 0.153 -0.032 -0.23 0.819
Compatibility 0.706 0.152 0.655 4.643 0 YES
Trust of the Internet -0.023 0.107 -0.021 -0.215 0.83
Trust of the Govt -0.028 0.127 -0.022 -0.225 0.823
The sample size was just barely sufficient to run
a multiple regression, to compare the results
with earlier similar research. Stepwise regression
is superior, but needs an adequate sample size
(Vanvoorhis and Morgan 2007), so the simpler
‘enter’ method was used. As there was some
ambiguity with the factor loadings in the factor
analysis, all the factors were entered together, as
opposed to entering them in groups according to
the research model.
The regression was interpreted using Hair et al. (2008). The resultant regression
model was significant (Table 11), with the regression model explaining more of the
variation than the residuals. The model explained 0.52 of the variation (Adjusted
R2 in Table 12), which is moderate, compared with 85.9% Carter and Bélanger
(2005). The variables that were significant in this study were Perceived Usefulness
(+0.36), Perceived Ease of Use (-0.28) and Compatibility (+0.71) with the intercept
at 0.329. It is also important to note that the standardized residuals were normally
distributed (Figure 12 and Figure 13) and were non-linear (Figure 14). From Table
12, the Durbin-Watson statistic d = 2.172 was near to d=2 indicating little
autocorrelation among residuals. There may have been some autocorrelation in
the model which caused the lower R2 result, but this is to be expected in
exploratory studies.

Results (i)
The following null hypotheses were rejected at the 0.05 level, and are listed in the
descending order of their correlations:
• H04: Citizens’ perceptions of compatibility with the web-application (CT) are not related to the use
of e-Government services (r =0.695).
• H01: Citizens’ perceptions of usefulness of the web-application (PU) are not related to the use of e-
Government services. (r =0.621).
• H03: Citizens’ perceptions of relative advantage by using the web-application (RA) are not related
to the use of e-Government services. (r =0.567).
• H05: Citizens’ trust in the Internet (TRUS_I) is not related to the use of e-Government services. (r
=0.386).
• H06: Citizens’ trust in Government (TRUS_S) is not related to the use of e-Government services. (r
=0.342).
• H02: Citizens’ perceptions of ease of use of the web-application (PEOU) are not related to the use
of e-Government services. (r =0.336).
• H012: Citizens’ Level of access to a Credit Card is not related to the use of e-Government services.
(τ =0.294).
• H013: Citizens’ Level of e-Commerce (online shopping) experience is not related to the use of e-
Government services. (τ =0.276).
• H010: Citizens’ Level of Internet Access is not related to the use of e-Government services. (τ = –
0.236). Note that a negative correlation here is interpreted as Access to the Internet in the Home
and at Work correlates with Use intentions, though weakly.
In addition, at the 0.10 significance level, which is acceptable for exploratory
studies, the following null hypotheses are rejected: (i) H09: Citizens’ Household
Income Level is not related to the use of e-Government services (τ = -0.158), and
(ii) H011: Citizens’ Level of Computer experience is not related to the use of e-
Government services. (τ = -0.158).
It is therefore safe to assume that there are correlations between Use Intentions
and these preceding nine variables, and possibly also Household Income Level and
Level of Computer Experience. It is important to always mention that correlation
does not imply causality (Cooper and Schindler 2003). Notwithstanding this,
intentions to use and use itself have been studied as the dependent variables in
many IS models (F. D. Davis, 1989; Moore and Benbasat, 1991; Taylor and Todd,
1995; Venkatesh, Morris, G. B. Davis, and F. D. Davis, 2003; Delone and McLean,
2003), and so it may be safe to say the direction of the relationship is stronger in
the direction where the other variables impact use intentions, rather than the
other way around.

Results (ii): Correlations (TABLE 14)
Hypotheses USE
Sig. Sig.
0.01
Reject
H0?(2-t)
H04
Citizens’ perceptions of compatibility (CT) with the web-
application are not related to the use of e-Government services.
0.695 0.000 ** YES
H01
Citizens’ perceptions of usefulness (PU) of the web-application
are not related to the use of e-Government services.
0.621 0.000 ** YES
H03
Citizens’ perceptions of relative advantage (RA) by using the
web-application are not related to the use of e-Government
services.
0.567 0.000 ** YES
H05
Citizens’ trust in the Internet (TRUS_I) is not related to the
use of e-Government services.
0.386 0 ** YES
H06
Citizens’ trust in Government (TRUS_S) is not related to the
0.342 0.001 ** YES
H02
Citizens’ perceptions of ease of use (PEOU) of the web-
application are not related to the use of e-Government services.
0.336 0.001 ** YES
H012
Citizens’ Level of access to a Credit Card is not related to the
0.294 0.001 ** YES
H013
Citizens’ Level of e-Commerce (online shopping) experience is
not related to the use of e-Government services.
0.276 0.002 ** YES
H010
Citizens’ Level of Internet Access is not related to the use of e-
Government services.
-0.236 0.007 ** YES
H07
Citizens’ Gender is not related to the use of e-Government
services.
0.051 0.568 NO
H08 Citizens’ Age is not related to the use of e-Government services. 0.055 0.509 NO
H014
Citizens’ use of an Agent to file taxes is not related to the use of
e-Government services.
0.016 0.862 NO
H09
Citizens’ Household Income Level is not related to the use of e-
Government services.
-0.158 0.061 NO
H011
Citizens’ Level of Computer experience is not related to the
-0.158 0.06 NO

Discussion (i)
Firstly, the constructs taken from the TAM model and the DOI theory, and the two
Trust constructs all returned significant, though at different levels. The stronger
correlations (above 0.5) were Compatibility (CT), Perceived Usefulness (PU) and
Relative Advantage (RA), and the rest were weaker (below .4). Similar results were
seen in the multiple regression particularly for Compatibility, where the
standardized coefficient was +0.655, and Perceived Usefulness, where the
standardized coefficient was +0.32, though perceived ease of use had a negative
coefficient (Table 13).
Additionally, although initial factor analysis had too few cases to be effectively
relied upon, the factor scales making up RA and CT always seemed to be mixed
together, although the PU scales loaded correctly (Table 9). Carter and Bélanger
(2005) had a similar problem with these constructs in their study, which may point
to some latent similarity between CT and RA.
One might have expected Age to be significant, but they along with Gender and
Agent filing turned out not to be, and can be interpreted as not impacting on use
intentions.

Discussion (ii): Internet-based Lifestyle-
Compatibility, and the Perceived Advantage
and Usefulness of the Internet-based Service
The Compatibility (CT) construct contained questions such as “using the Internet would
fit well with the way that I would like to gather information”, or “…file my taxes and
make tax payment.” or using the internet to file taxes would “fit into my lifestyle” (see
Appendix in Section 8).The strong correlation with this construct and Use Intentions, and
significance in the multiple regression model, indicate that there may be a strong
tendency for citizens who have the internet as an integral part of their lifestyle to intend
to use an e-Government service.
This is commensurate with the statistical significance of the three significant
demographic variables, namely Access to an International Credit Card (τ=0.294), those
who made a Success e-Commerce Purchase (τ=0.276), and Level of Internet Access (τ =-
0.236). Although weaker, these correlations point towards internet-based lifestyle
choices impacting on the intention to use an internet-based Government service, even
with an e-payment component. Note that a negative correlation for Internet Access
should be interpreted as users who use the internet more ‘at home’ or ‘in the office’
correlate more with Use intentions (see histogram in Figure 5), adding strength to the
argument.
Relative Advantage (RA) is also from the DOI model (Rogers 1995) along with
Compatibility, and it points to the Internet as an enabler of greater efficiency and
control, specifically for using the e-Government service. Here there was a moderate
relationship with Use Intentions (r = 0.567), although it was not significant in the
regression model. Users who perceive the internet as an advantage over other access
channels, such as the manual over-the-counter service, or single-counter combined
services, will potentially have higher use intentions to use or switch to the e-Government
service.
Finally, the correlation between Use and Perceived Usefulness (PU) was also significant
(r = 0.621), indicating that perceptions of the internet being enabling and useful
correlate with intentions to use the e-Government service. Perceived Usefulness was
also significant in the multiple regression model.
These three constructs, along with the supporting demographic variables seem to
indicate that users whose perceptions of the use of the Internet as enabling, useful and
advantageous, and who also perceived the internet fit with their lifestyle would be
inclined to use the e-Government service.

Discussion (iii):
Perceptions of Future Ease of Use
Questions in Perceived Ease of Use (PEOU) asked about the respondents’
perceptions of future ease of use, as the IRD e-filing and e-payment service is not
yet implemented. PEOU showed the least correlation of the scale variables. In the
regression model (Table 13), it returned with a negative coefficient (-0.28), though
it was just barely significant (.045), whereas with the correlation, the direction was
positive with a significance of .001. The regression model seems to suggest that
the more difficult the perceived future ease of use, the greater the eventual
intention to use, and this is counter-intuitive, and so the correlation may be
perceived as being more reliable. On further investigation, PEOU also negatively
correlated with Computer Experience (τ= - 0.191; Sig = .027), though weakly. This
might suggest that those with greater computer experience may find or expect
that the future service would be difficult to use or difficult to learn, or perhaps not
well implemented. The takeaway here is that respondents had statistically
significant perceptions about ease of use and the “learnibility” of the future e-
Government service, and so good design and training should on the implementers’
agenda.

Discussion (iv): Trust towards Internet Security,
Government’s Capacity to Implement, and the
Regulatory Framework
For the Trust of the Internet construct (TRUS_I), respondents were asked mainly
about their perceptions of Internet security and the Trinidad and Tobago
regulatory framework vis-à-vis making e-payments. This construct had the lowest
mean at 4.789 (Table 4) and highest standard deviation (Table 5), and there were
no reported outliers (Table 6). Despite the already-stated concerns with sample
size, this construct loaded correctly in the factor analysis (Table 9). What this
reflects is that there are still many varying perceptions about internet security for
electronic transactions and payments, and the preparedness of the local
regulatory framework. This may be due in no small way to the delays in the
implementation of the Electronic Transactions and Data Protection and Privacy
Bills that are still to be enacted.
As for Trust of Government (TRUS_S), respondents were asked specifically about
the IRD and not about the Government as a whole because political biases may
have tainted the responses. The correlation was similar to that of Trust of the
Internet although with a higher mean (5.161) and smaller standard deviation
(1.176). Three of the questions asked about the IRD’s trustworthiness, and one
(Question 38 or TRUS_S2) asked about the respondent’s trust in the IRD’s ability to
carry out online tax-filing and payment transactions. The three questions averaged
5.21 whereas the TRUS_S2’s value was 5.02 which is noticeably lower with their
standard deviations all about the same. One can interpret this as respondents (and
potential users) had trust of the IRD generally, though they were less sure about
the IRD’s getting the service right, and this should be noted.

Discussion (v):
Outliers
USE PU PEOU RA CT TRUS_I TRUS_S
13 6.00 7.00 2.25 2.00 3.75 2.33 2.50
57 4.80 4.00 5.50 3.00 2.00 2.00 2.00
8 3.60 2.25 4.25 5.50 4.25 4.33 1.00
.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
13
57
8
Cases
An outlier is an observation with an extreme value that is substantially different
from the other observations (Hair et al. 2008). It should be mentioned that
there were univariate outliers in each of the variables except Trust of the
Internet (Section 4.4.1) and multivariate outliers identified with Mahalanobis D
(Section 4.4.2). Outliers must be treated carefully especially if they turn out to
be representative in the population. There were some cases with generally
lower collective responses the scale variables, resulting in higher Mahalanobis D
and Cook’s D values, such as cases 8, 13 and 57, illustrated in Figure 9. The actual
values of three cases are presented in Figure 15, showing lower and seemingly
related values for the variables, than the majority of the other respondents. Not
all citizens will find the e-Government service useful or trustworthy even in the
later stages of adoption, and implementers should find strategies to coax
increases in usage and adoption of these services, particularly where there is a
payment component, such as with financial incentives (Rocheleau and Wu
2005).

Implications (i)
Despite the limitations outlined earlier in Section 1.4.4, the results can be
generalized to the stated population, and can be relied upon for decision-making
and future research. The original purpose of the study was to determine the
factors relating to the citizens’ use of e-Government services in the Trinidad and
Tobago context, with the intention of trying to identify the significant factors that
e-Government leaders and implementers should consider before, during and after
deployment, to maximize the benefits to both the Government and its
stakeholders. The implications of the preceding discussion are presented in the
following Sections.

Implications (i): Policy Recommendations
From looking at the various Trust issues, it is clear that Trust is a major component
in online interaction (Warkentin et al. 2002). A Government’s the Regulatory
Framework, which includes Telecommunications regulation, the judicial framework
and intellectual property laws, reduces risk and uncertainty (increases trust) in
these new internet-mediated transactions, and is a fundamental “diagonal”
prerequisite for e-Government, and by extension the Information Society (Hilbert
and Katz 2003). The Government of Trinidad and Tobago must recognize the
urgency of passing enabling legislation, and creating foundational policy structures
for cross-agency coordination and development. Extra effort should be made to
develop and implement rigorous information-security policies and practices
among Government agencies, particularly those engaging in internet-based
transactions. Finally, in addition to providing e-Government services online, the
Government should also continue to promote its e-Business agenda. Because e-
Government and e-Business require many similar prerequisites, policies, practices
and lessons learnt through e-Government implementations can be extended into
the private sector making local businesses more competitive, such as through the
use of Public-Private Partnerships (PPPs).

Implications (ii): Leaders and Implementers
From a project leadership and implementation standpoint, it is clear that there
exists a great potential for usage and adoption of e-Government services in
Trinidad and Tobago, with high levels of use intentions, computer experience and
internet-based lifestyle compatibility. Mere focusing on service efficiency though is
not sufficient, as users may have pre-conceptions of the service and may never
even attempt to try the new service. And so, what may be worrying is that some
users may have negative pre-perceptions of ease of use, mistrust of the internet,
particularly with respect to financial transactions, and further the Government’s
ability to implement, all of which may negatively affect their usage and adoption
of a new e-Government service. The e-Government leader’s role therefore is to
ensure that the population of potential users, the so-called ‘market’ for the
service, is clearly understood, and ample market research is to be conducted
beforehand to ensure that the new e-service is in demand. High-impact-to-citizens
services (sometimes referred to as ‘low hanging fruits’) should be selected to be
reengineered into online offerings, and it is the leader’s role to clearly advocate
the benefits of the new service to the market, and other Government leaders.
Ample post-implementation research, similar to this study and others, should also
be conducted to ensure that beneficial attitudes are maintained, and pro-use
perceptions are developed and maintained.
From an application development’s standpoint, the implementer’s role is to ensure
that amble user/citizen acceptance testing is conducted before launching any new
service to ensure ease of use and to maintain trust in the system. The highest
levels of information security practices should be used in the development and
workings of all applications. Fundamental interoperability policies should be
developed to ensure that an end-user user experience is translatable from one e-
Government site to another, so as to maintain high levels of perceived ease of use,
and trust of Government as an implementer.

Implications (iii): Future Research
Although much work has already been done to develop of e-Government services
in Trinidad and Tobago, there is still much opportunity to conduct complementary
demand-side research. Such research will ultimately assist in the development,
deployment and eventual take-up and success of these services. The findings here
indicate that there are significant correlations between TAM, DOI and Trust
variables, which merit further and broader investigation into factors affecting e-
Government Use Intentions in Trinidad and Tobago.

Conclusion
Given that the Government of Trinidad and Tobago is in the midst of its e-
Government building efforts to supply e-Government services to its stakeholders,
the study set out to determine what demand-side factors leaders and
implementers should pay attention to, so as to maximize the benefits to both the
Government and the service users. It was found that potentials users of e-
Government services are generally those who found the Internet-based services
valuable and who found that it would fit in with their lifestyle, and who may find it
easy to use. It was also found that users generally would trust the Government
department but may be weary of transacting over the internet with Government,
possibly because of the lack of regulatory infrastructure in Trinidad and Tobago.
Finally, it was found that Gender, Age and Agent assistance did not significantly
correlate with use intentions. These potential factors should be considered in the
development and deployment of e-Government services in Trinidad and Tobago.

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Appendix: The Instrument (page i)

Appendix: The Instrument (page ii)

Exploring Factors Relating to the Use of E-Government Services, as Perceived by Citizens in Trinidad and Tobago

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