Inf Syst Front (2017) 19:285–300

293

Table 7 Overall Impact
Frequency

Percent

By opening up data, government is driving the creation of
innovative business & services
Making data available supports the shaping of society

106

20.5

188

36.4

Transparency in data is more than open access

222

43.0

Total

516

100.0

When asked for their opinions on the accountability in
government functions, majority respondents (210 of 516)
thought accountability is not real, and corruption in the government continues to exist (Table 4). Running close to this
opinion, 207 people of the 516 surveyed believed that without
motivated citizens and journalists promoting the benefits of
open data, accountability would only remain a goal. There
was also a small set of people (99 of 516) who went along
the fact that nearly every time one finds accountability within
democracy, there is public knowledge empowering it.
In finding out about their participation and interaction with
open data, most respondents (225 of 516) complained that
there are no clear means of providing citizen feedback or input
on these open data platforms that effectively impact future
policy decisions (Table 5). On the other hand, 211 respondents
believed their participation will and does improve the quality
of policymaking, bringing greater accountability and transparency that helps deepen democracy. There were only 80 respondents who thought the government is taking enough measures to ensure that citizens have the tools/training to understand and make use of the information revealed on open data
websites.
In investigating how much insight citizens have on government spending, 205 of 516 respondents were happy about the
fact that the release of spending data has allowed them to see
more of Government’s accounts to establish value for money
on behalf of the taxpayer (Table 6). The next big chunk of
respondents (193 of 516) thought journalists and campaigning
organizations were mostly using the available government
spending data to highlight government decisions and support
associated campaigns. About 118 respondents believed that
government’s internal spending and management information
could be interrogated based on available open data.

Table 8

Reliability test

Constructs

Sample

Items

Cronbach’s α

Reliability

Relative Advantage
Compatibility
Complexity
Observability
Risk
Behavioral Intention

516
516
516
516
516
516

3
2
2
2
2
2

.812
.515
.359
.643
.666
.704

High
Moderate
Low
Moderate
Moderate
High

In gaining views about the overall impact of open data,
most respondents (222 of 516) were found to believe that
transparency in data is beyond just open access, and more
about sharing and reusing data that can be visualized and
analysed to question the present state of affairs (Table 7).
The next big set of respondents (188 of 216) believed that
making government data available supports the shaping of
society. Lastly, about 106 respondents thought that by opening
up data, government is driving the creation of innovative businesses and services, capable of delivering social and commercial value.
5.2 Construct reliability
While using survey instruments, it is always a good practice to
ensure that the instrument in use will consistently produce
reliable responses in all possibilities of the questions in the
instrument being replaced with analogous questions (Santos
1999). Cronbach‘s alpha is one such reliability statistic that
provides a measure of the internal consistency or an average
correlation among the items involved in the instrument to
estimate its reliability (Santos 1999). To begin with, all five
constructs had three items each, but during the reliability test it
was revealed that deleting certain items could increase the
reliability of some of the constructs. In the interest of achieving a well-fitting model, some constructs underwent item deletion to achieve stronger reliability (higher Cronbach‘s alpha
value). A reliability test was conducted on the survey instrument for this study (Table 8). As cited in Dwivedi (2005),
there are four points for Cronbach‘s alpha representative of
reliability (i) 0.90 and above indicating excellent reliability (ii)
0.70–0.90 for high reliability (iii) 0.50–0.70 reflecting moderate reliability, and (iv) 0.50 and below for low reliability.
Of the six attributes being used in the model, behavioural
intention and relative advantage showed high reliabilities.
Except complexity, the remaining three attributes showed
moderate reliabilities. Owing to its very poor reliability and
Model summary

Table 9
Model R
1

R Square Adjusted R Square Std. Error of the Estimate

.708a .501

.497

.81138

a
Predictors: (Constant), Compatibility, Risk, Relative Advantage,
Observability.

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