Factors influencing the use of electronic government services in Brazil/Fatores que influenciam o uso de servicos de governo eletronico no Brasil/Factores que influencian el uso de servicios de gobierno electronico en Brasil.
de Araujo, Marcelo Henrique ; Reinhard, Nicolau
1. INTRODUCTION
The development of the Information Society includes the risk of
creating a new form of social exclusion: that of individuals deprived of
digital resources. Although digital inclusion has been widely studied
(WILHELM, 2000; CASTELLS, 2001; 2010; SORJ; GUEDES, 2005; MORI;
ASSUMPCAO, 2007; MADON et al, 2009) it cannot be reduced to providing
physical access to the technological resources, but must consider user
diversity and ability for the different uses (entertainment,
communication, education, e-commerce, e-government, etc.).
The Brazilian Internet Steering Committee (CGI.br, in Portuguese)
and other international institutions (UNO, OECD, World Bank and others)
have developed indicators and metrics of the appropriation of ICTs, in
order to understand the multiple dimensions of digital inclusion.
Since 2005 CGI has sponsored a yearly large nationwide survey of
the access and use of ICT in households and enterprises. CGI.br designed
its survey in accordance with OECD, Eurostat and Partnership on
Measuring ICT for Development methodology, thus allowing international
comparisons (CGI, 2012). The survey statistics and methodology are
available in Portuguese and English in
http://www.cgi.br/publicacoes/index.htm.
The access to the survey's microdata allows the in-depth
analysis of different aspects of internet users ' behavior. For the
present paper, the research question chosen is: How is the
individuals' adoption and use of e-government services related to
their preferred location of access to the internet and their usage
capabilities?
Answers to these questions should help in evaluating the
effectiveness of (usually very high cost of nation-wide) public policies
related to promoting the provision of internet access in public
locations or at home and the need for user information and training. In
fact, many of the once ubiquitous lan-houses (estimated at 108,000 in
2009) are going out of business despite government support, while the
demand falls for the about 20,000 public telecenters (ABCID, 2013; CGI,
2012).
The results of this research should contributeing to an improved
understanding of the factors that influence the usage of e-gov services,
in order to orient the definition of public policies for digital
inclusion (in this case, the usage of e-gov services).
The paper is organized as follows: section 2 presents a brief
literature review and the research reference model. Section 3 describes
the research design and the methodology employed. Data Analysis and
discussions, contributions are contained in section 4; final
considerations are presented in section 5.
2. LITERATURE REVIEW
2.1. Digital Inclusion
Digital Exclusion is a major theme of Information Society research,
dealing with the social, economic and cultural consequences of the
unequal distribution of access to computers and the internet, thus
Digital Exclusion is one facets of social exclusion (BROADBENT;
PAPADOPOULOS, 2013). There is the recognition that public policies are
needed to overcome these problems through the dissemination of digital
technology, such as the Brazilian Information Society Program
(TAKAHASHI, 2000), also aiming at improving citizens' access to
government services and democratic participation.
Restricting the problem to the dichotomy between "having"
or "not having" access to computers and the internet is an
oversimplification. In fact, research focusing only on citizens'
access to technological artifacts, according to (AVGEROU, 2003) has a
"technological determinism bias".
This indicates that digital exclusion is a complex issue, requiring
considering other dimensions beyond the dichotomy of included and
excluded individuals (SORJ; GUEDES, 2005).
In this line, the present paper will not focus on the access to
digital resources, but on its qualified use, focusing on the factors
contributing to the use of e-government services. Although E-government
may have different definitions, our research considers the use of
internet to improve the provision of government services to citizens,
information and democratic participation.
2.2 Electronic Government Services
Governments have made extensive use of these technological
resources in order to increase its offer of services to citizens and
also improving their effectiveness and quality. These systems, based on
the use of Information and Communication Technologies, and, in
particular, the subsystems that provide the interface with citizens, are
studied under the generic name of electronic government, or, in short,
e-gov (DINIZ et al., 2009; SANTOS; REINHARD, 2011).
Electronic Government as a research area, besides studying the use
of Information and Communication Technologies (ICT) for the interaction
between citizens and private organizations with public administration
(the socalled "front office ", does also include the
"back office ": automation and integration of the different
public administration processes and interorganizational systems
communication. Haldenwang (2004:418) understand e-gov as the strategic
and co-ordinated use of Information and Communication Technologies (ICT)
in the public administration and political decision making.
Although the most visible dimension of electronic government
relates to the provision of government services in electronic form,
there are also other applications that studied under the name of e-gov.
The popularization and positive image of these electronic services,
such as the citizen's electronic filing of Income Tax Adjustments
(REINHARD; MOYA, 2002) and electronic voting system (AVGEROU et al.,
2009) have led to equate electronic government with electronic
citizen-facing service provision in current language. However Diniz et
al. (2009) point out that the field has to be expanded to include also
other application of the technology in Government activities.
One classification, used for several authors such as by Cunha and
Miranda (2008) and also Barbosa, Pozzebon and Diniz (2013) and
Haldenwang (2007), identifies three major categories of e-gov
applications:
* Public Management applications: the use of ICT to improve the
management of government activities, administrative processes and
resource usage and also the formulation, implementation, monitoring and
control of public policies.
* E-services: the use of ICT for the communication with and the
provision of services in electronic form to citizens and private
organizations.
* E-democracy: the use of ICT resources in order to allow citizens
to become better informed about government and facilitate their
increasing participation in forming public opinion and in decision
making processes.
2.3. Amartya Sen's Capability Approach
Amartya Sen proposed the Capability Approach as a reference for the
human development paradigm (SEN, 2001; REINHARD, 2010) having been used
as a basis for several development indicators, such as the Human
Development Index and the ICT Development Index (ITU, 2011).
The Capability Approach offers an objective basis for comparisons
of differences of well-being between individuals (PRENDERGAST, 2005),
thus overcoming the limitations of utilitarian approaches that do not
allow this comparison, basic for well-being economics.
For the Capability Approach, the properties or characteristics of
goods or resources have to be seen in terms "what they do to human
beings". By taking possession of an object (a commodity), the owner
is able to "command" these characteristics. However, (SEN,
2001) cautions that these characteristics do not inform in advance how
these goods will be utilized. Therefore, the possession of a good will
not necessarily result in an increase in the person's well-being
because its use cannot be determined beforehand. The change will only be
in the possibilities of achievements a person can obtain from these
characteristics.
Therefore, Sen (2001) argues that the well-being of a person should
consider its "functionings", that is, "what the person
succeeds in doing with the commodities and characteristics at his or her
command" (SEN, 1999:6).
The achieved functioning will depend both on the possessed resource
and on the way this resource is used. Thus, they have the freedom to
choose among different functionings. This set of functionings persons
can achieve is called their Capabilities.
According to Sen (2001), the process of conversion of the goods
' characteristics into functionings depends on many factors,
personal, cultural and social, that are called "conversion
factors". Different persons having access to the same resources can
end up with quite different functionings.
3. RESEARCH REFERENCE MODEL AND METHODOLOGY
There are multiple approaches to the study of technological
innovations adoption and use such as e-gov services by citizens. One
major line of research is based on the use of the Technological
Acceptance Model (TAM) (DAVIS, 1989) and related models, such as TAM 2
(VENKATESH; DAVIS, 2000); UTAUT (VENKATESH et al, 2003).
These models consider the perception of potential users regarding
the usefulness, ease of use and other attributes of the technology, in
order to predict the users' attitude toward using the technology.
[FIGURE 1 OMITTED]
The present study is based on secondary data that measure the
effective use of egov services, instead of just the users '
attitude (leading to the future decision to eventually use the services)
and therefore going one step further than those models. These models
also do not consider explicitly individual user preferences that are not
related to the model variables and therefore their freedom to possibly
choose not to use the services, despite favorable conditions identified
by the models.
The Capability Approach, presented in section 2.3, has therefore,
some advantages over those models for our study, as it allows
considering effective user actions instead of just perceptions, and
including the dimension of freedom and ability to choose among
alternatives.
Figure 1 is a schematic representation focusing on the specific
variables of the paper's reference model.
As research propositions we then present the following reasoning:
Starting with the comparison of preferred location of internet access
and its influence on the user's capabilities (conversion factor),
for which we propose as proxies the actual use of e-mail, e-commerce
(search function) and e-financial services (checking banking accounts).
The "use of email", as one of the main electronic
communication tools was used as one of the proxy variables, because it
is understood that this is a basic electronic communication competence,
being also a requirement for the use of some e-gov services (e.g.
filling police report). The inclusion of the "use of
e-commerce" variable is based on arguments presented by Diniz et
al. (2009) for whom the offer of e-government services began to grow in
Brazil with the diffusion of e-commerce usage, thus supporting the
assumption that the use of ecommerce competence contributes to the use
of egov. Finally, "financial services" is proposed as another
proxy variable for competence due to both its similarity with and its
direct use in e-gov services (e.g. paying taxes)
It should be noted that the choice of e-commerce and financial
services variables are restricted to consulting (searching) activities,
since some users may not possess credit cards or other necessary tools,
or have other reasons not to carry out the complete transaction, despite
their competence to interact with the system.
These capabilities mediate the user ability to choose the
functionings (in this case the decision to use or not to use e-gov
services). All conversion factors and subsequent choices are analyzed as
mediated by social class and preferred location to access the internet.
The actual use of e-mail, e-commerce (search function) and
financial services (checking banking accounts) are basic and frequent
activities of internet users and bear some similarity with the
competences needed to use e-gov services. We posit that these uses,
being performed with higher frequency, indicate users '
capabilities that function as enabling factors to the not so frequent
use of e-gov services. Table 1 describes the variables analyzed in this
paper.
The Capability Approach provides an appropriate framework to
explore this chain of enabling factors evidenced by users' choices
(preferred location for Internet Access) and actions (use of resources),
variables that are measured objectively in the survey. In this research
we use the data presented in Table 1 from the microdata of the above
mentioned CGI survey for the years 2007, 2009 and 2011.
The data refer to the respondents' demographic data, their
access to ICT resources and usage characteristics (use of e-mail,
financial services, e-commerce and e-government services). The sample
considers respondents over 15 years of age, residing in urban areas that
have used the internet during the last three months (See Table 2). The
survey, based on statistically valid samples, is representative of the
Brazilian population, with the following sample sizes.
The research uses the following selection of variables from the CGI
survey: (1) Demographic variables: age, economic data, access to
computers and internet, preferred location for internet access; (2)
Social Class constructed by CGI from the respondents' demographic
data, as defined by the Brazilian Census Bureau's (IBGE)
methodology.
The present inquiry is restricted to the analysis of Social Classes
C and DE, where digital inclusion issues and related public policies are
seen as a national priority and also due to the fact that the variance
and changes in digital competences and e-gov usage in these classes was
the largest during the period.
The category "Use of e-mail" refers to answers to the
survey question "have you sent or received e-mail in the last 3
months?" The category "use of e-commerce" refers to
answers to the question "have you searched the internet for
availability or prices of products or services in the last 12 months?
The category "use offinancial services" refers to answers to
the question "have you used Internet Banking for consultation in
the last 3 months?" These variables are used as proxies for user
competencies that will be considered as antecedents to e-gov usage.
The category "use of e-government" considers the use, in
the last 12 months, of any of a series of common e-government services
offered to citizens (requesting documents or personal information,
paying taxes or service fees, registering for educational or health
services, etc).
Binary Logistic Regressions are used to analyze the relationships
between the (dichotomous) variables (HAMILTON, 2009). The absence of
significant multicollinearity in the data set is verified through VIF
and tolerance statistical tests.
According to the research model (Figure 1) the first set of tested
relationships (posited as influences) considered the variables
"preferred location of access to the internet" (this
categorical variable was transformed into dummies variables) and proxies
for use competencies (E-commerce, E-mail and Financial Services). The
next set of logistic regressions aimed at assessing the relationships
between competencies and the use of e-gov services, followed by a
logistic regression of the use of egov services against the preferred
location of access to the internet.
The software Stata was used for the stepwise logistic regressions.
For data analysis, we considered only the odds ratio values that are
statistically significant at the 95% confidence level.
4. DATA ANALYSIS
Table 3 shows the location of preferred access to the Internet.
Percentages are calculated over the total population of internet users
in a social class. Classes A and B and also D and E are combined for
convenience of analysis.
The data show a general increase in access to the internet at home,
especially in the lower classes. The Country's favorable economic
situation during the period (growth of household income) and public
policies for the reduction of hardware and connection cost allowed the
increased affordance of ICT resources at home, leading to the
corresponding reduction of access in other locations. Especially
noteworthy is the dwindling demand for the once ubiquitous Lan-houses
(many of them already going out of business). Table 4 shows the
frequencies of E-mail, E-commerce (search) and Financial Services usage.
The variable "usage of electronic government services",
presented in Table 5, is used as the measure for the model's
"Functionings" (SEN, 2001)
Tables 6 to 10 present the results of the logistic regressions. The
"odds ratios" presented in these tables should be interpreted
as follows: the coefficient 2.5 in Table 6 (Class C, "at Home and
Work" in 2007) means that the probability to be a user of e-gov
services of a user that has access to the internet from home or work is
2.5 times more likely than that of a user that accesses the internet
from another location. Similarly, the coefficient 0.7, being lower than
1, indicates that a user that accesses the internet from a lan-house is
less likely to use e-gov, as compared to a user from another location.
Blank cells indicate that the corresponding coefficients are not
statistically significant.
Our focus in the analyses is on the usage of e-gov services in
Social Classes C and DE, since these classes are the main target of
public policies for digital inclusion and also because in these classes
there is a larger variation in the overall level of e-gov services
adoption and therefore the larger interest and implications of an
explanatory model.
Coefficients for "At Home and Work" access to the
internet in tables 6, 7 and 8, being significantly larger than 1, show
that access from these locations is significantly related to an increase
in internet usage competencies (as represented by the proxies e-mail,
e-commerce and e-finance usage), therefore supporting the first set of
propositions of the paper (access location being influencing the
capability conversion factor).
Tables 6 and 7 show also some larger than 1 coefficients for the
other access locations. In these cases, however, the value of the
coefficients falls over time, indicating a reduction of importance of
these locations, leading to values less than 1 or non-significant in the
last year 2011, thus supporting the proposition that the eventual users
of e-gov services from these locations may have migrated to more the
convenient access locations (at home and work).
Table 9 shows that the use of all three services (e-mail,
e-commerce and e-finance) contributes significantly to increase the
probability of their users being also users of e-government services,
with a special weight for e-finance services.
These findings thus support the second part of our research
propositions: the developed capabilities influencing the choice for the
functioning (use of e-gov services).
Lastly, the coefficients of Table 10 show that Access Location
alone, although consistent with the previous results, is a much weaker
predictor of e-gov services usage than the process mediated by the usage
competencies, indicating the contribution of the "mediating
chain" proposed by the Capability Approach, which concludes our
analysis.
5. CONCLUSIONS AND MANAGERIAL IMPLICATIONS
The data analyses support our propositions of the positive
contribution of internet access from home or work to the development of
internet usage competencies and the contribution of these factors to
e-government services usage, as answers to the paper's initial
research question.
Managerial and public policy implications: These results show that
public policies promoting home access to the internet, such as reducing
sales taxes on computers and internet access and low-interest financing
for home computers are more effective in leading to an increase in the
use of e-government than the effort to reorient lan-houses and
telecenters to become e-gov access points.
Home access to the internet contributes to the increase of citizens
' e-literacy, also in the lower social classes and has also an
impact on their e-gov use. Nevertheless, the lower percentage of
e-government services use among lower social classes indicates the need
for additional research to better understand the reasons for them not to
use these services, even among users that have internet access at home.
In the beginning of the last decade there was a nation-wide boom of
private lan-house (most of them very small family-run businesses). Many
of them have since closed due to the rapidly falling demand, as shown in
Table 3. The results of our study do not support government policies to
provide incentives for the still large number of lan-houses and
telecenters to become access and support points for e-government
services. The theoretical contribution of this paper is to demonstrate
the suitability and the development of a methodological approach
operationalizing Sen's Capabilities Approach, based on CGI's
Brazilian ICT usage variables in order to understand the factors and
processes that constrain and influence citizens' decision to use
e-gov services. On the other hand, as a contribution to practice, the
results of this inquiry could aid in the shaping of alternative public
policies for digital inclusion and the analysis of their effectiveness,
such as implementation of public telecenters vis-a-vis facilitation of
internet access from home and the understanding citizens' cultural
and educational constraints in the process.
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DOI: 10.5700/579
Recebido em: 16/10/2013
Aprovado em: 11/11/2014
Marcelo Henrique de Araujo
Doutorando em Administracao (Metodos Quantitativos e Informatica)
na Faculdade de
Economia, Administracao e Contabilidade da Universidade de Sao
Paulo (FEA/USP)--Sao Paulo-SP, Brasil
Mestre em Administracao pela FEA/USP e bacharel em Sistemas de
Informacao pela Escola da Artes, Ciencias e Humanidades (EACH/USP)
E-mail: marcelo.haraujo@gmail.com
Nicolau Reinhard
Professor Titular Senior da Faculdade de Economia, Administracao e
Contabilidade da USP--Sao Paulo-SP, Brasil
Coordenador do Programa MBA Gestao de Tecnologia da Informacao, da
Fundacao Instituto de Administracao--FIA
E-mail: reinhard@usp.br
Table 1--Variables
Variable Categories
Social Class A and B (combined), C, D
and E (combined)
Preferred Location for Home; Work; School; Other
Internet Access person's home; Lan House;
Free Public Telecenter;
Use of Electronic Government Yes/No
Use of E-mail Yes/No
Use of E-commerce (search for Yes/No
products and prices)
Use of Financial Services Yes/No
(checking banking accounts)
Source: Research data.
Table 2--The survey household segment sample size
for urban respondents over age 15
2007 2009 2011
Respondents--Total 5638 7158 8661
Class AB (combined) 2231 2992 4099
Class C 2751 3556 4022
Class DE (combined) 656 610 540
E-gov users 4046 4964 5879
E-mail users 4599 5969 7203
E-commerce (search for 3244 4661 6143
products and prices)
Financial Services (checking 1051 1256 2491
banking accounts)
Source: Research data.
Table 3--Preferred location of access to the
Internet of E-gov users' (percentage)
AB C
2007 2009 2011 2007 2009
At Home 53.0 63.0 72.7 29.3 36.4
At Work 26.5 22.6 20.4 21.2 17.3
At school 2.8 1.2 0.5 3.6 3.5
At someone else's home 4.1 4.8 1.6 11.5 10.0
Telecenter 0.6 0.7 0.3 1.9 1.2
Lan-House 12.8 7.4 3.2 31.8 31.0
C DE
2011 2007 2009 2011
At Home 58.5 9.3 16.2 27.2
At Work 16.1 8.9 5.3 10.9
At school 1.4 4.4 4.8 2.5
At someone else's home 6.8 14.2 17.4 15.5
Telecenter 0.4 2.2 1.1 2.9
Lan-House 14.7 58.1 54.1 34.7
Source: Research data.
Table 4--Use competences by
social class (percentage)
AB C
2007 2009 2011 2007 2009
E-mail 88.1 89.8 90.1 78.3 80.1
E-commerce (search) 71.2 77.1 80.6 50.5 59.2
Financial Services (checks) 27.9 27.1 37.7 13.7 11.6
C DE
2011 2007 2009 2011
E-mail 78.4 73.3 71.2 65.5
E-commerce (search) 64.3 40.4 40.7 47.2
Financial Services (checks) 21.8 8.1 5.4 12.5
Source: Research data.
Table 5--Percentage of E-gov users' (percentage)
2007 2009 2011
Class A and B (combined) 78.4 77.5 77.7
Class C 69.3 65.4 61.0
Class D and E (combined) 59.4 52.3 44.3
Source: Research data.
Table 6--Contribution of access location
to e-commerce usage (odds ratios)
C DE
2007 2009 2011 2007 2009 2011
At Home and Work 2.5 2.5 2.1 5.3 2.8 3.4
At someone else's home 1.9
Telecenter 4.9
Lan House 0.7
Lan House 0.7
Source: Research data.
Table 7--Contribution of access location to
e-mail usage (odds ratios)
C DE
2007 2009 2011 2007 2009 2011
At Home and Work 3.4 4.7 2.8 7.1 3.8
At someone else's 1.8 1.6 5.7 0.5
home
Telecenter 3.2 0.5
Lan House 1.8 2.5 3.8
Source: Research data.
Table 8--Contribution of access location to
e-finance usage (odds ratios)
C DE
2007 2009 2011 2007 2009 2011
At Home and Work 2.3 3.8 2.2 2.2 3.3 4.0
At someone else's home 2.7
Telecenter
Lan House 0.7
Source: Research data.
Table 9--Contribution of Capabilities to
Functionings (usage of e-gov) (odds ratios)
C
2007 2009 2011
uses E-commerce (search) 3.3 2.0 2.2
uses E-mail 2.0 1.4 2.7
uses Financial Services 5.2 4.1 3.2
(checks)
DE
2007 2009 2011
uses E-commerce (search) 2.4 1.9 1.9
uses E-mail 3.1 7.1
uses Financial Services 3.1 5.9
(checks)
Source: Research data.
Table 10--Contribution of the Location of Access to the
Internet to the use of E-gov services (odds ratios
C
2007 2009 2011
At Home and Work 3.5 1.7 1.8
At someone else's home 1.7
Telecenter 3.4 2.9
Lan House
DE
2007 2009 2011
At Home and Work 3.4 2.0
At someone else's home 2.4 2.4 0.4
Telecenter 0.3
Lan House 0.5
Source: Rearch data.
