294
Table 10
Model

Inf Syst Front (2017) 19:285–300
ANOVAa
Sum of Squares df

1 Regression 337.579
Residual
336.415
Total
a

673.994

Mean Square F

4
84.395
511 .658

Sig.

128.192 .000b

515

Dependent Variable: Behavioral Intention.

b

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

in the interest of satisfactory model performance, it was decided that complexity (α = .359) should be eliminated from
the model. Therefore, the effects of relative advantage, compatibility, observability, and risk on behavioural intention will
be examined using regression analysis.
5.3 Regression analysis
Linear regression analysis provides an estimate of the linear
equation coefficients, concerning one or more independent variables that result in the best prediction of the dependent variable
value (Draper and Smith 1998). Regression analysis was thus
carried out for the 516 gathered cases in accordance with the
proposed conceptual model for this study. In this model, four
independent variables - relative advantage, compatibility,
observability, and risk were examined for their influences on one dependent variable, behavioural intention.
The results from this regression run have been captured
in tables 9, 10 and 11. The analysis divulges a momentous model: (F (4, 516) =128.192, p = .000) with an
adjusted R square value of 0.497. As seen in Table 11,
the variables, relative advantage (Beta = .382, p = .000), compatibility (Beta = .294, p = .000), and observability
(Beta = .186, p = .000) were captured as the significant predictor variables, whereas, risk (Beta = −.059, p = .070) turned
out have no significant effect on citizens’ intentions.
It is clear from linear regression analysis that predictors of
the modified and extended DOI model accounted for 49.7 %
variability (Table 9) of behavioural intention to use open data
platforms. Relative advantage (Beta = .382, p = .000) and

compatibility (Beta = .294, p = .000) are the strongest predictors of citizens’ intentions to use open data (Table 11).
The functional value of open data was measured using
relative advantage (Fig. 2). In rating the relative advantage
of open data, about 36 % slightly agreed that knowledge of
government, available in the form of open data, creates accountability (RA1). While 26 % respondents were neutral
about the idea, 23 % showed agreement, and only 8 % were
in extreme agreement. While 36 % people were neutral about
the idea that open data offered flexibility in their daily decision-making, 53 % respondents showed agreement (RA2).
About 65 % people believed that open data helped them better
understand the governmental affairs, directly affecting them
on a daily basis (RA3, Table 12).
About 33 % respondents were neutral about the statement I believe, open data will fit my needs to access information
affecting my lifestyle, such as statistics on housing, crime
rates, accidents, flood maps, food hygiene, transport etc., with
only 29 % people agreeing with it (CT1). There were only
11.6 % respondents who believed that using open data
websites will not be compatible with their information needs
(CT2). In addition, only 18 % people thought that not all their
devices (mobiles, tablets, desktops, laptops & others) were
compatible with open data websites (CT3, Table 13).
About 40 % respondents agreed that organizations worldwide are working towards openness and transparency in
governments, and more involvement of citizens in political
decisions (O1). Not many respondents (31 %) witnessed
other people make well informed decisions on the basis
of open data (O2). About 72 % people agreed that individuals using open data were not visible in their social circles (O3, Table 14).
About 42 % respondents were only neutral about the statement that the information available on open data websites is
reliable and accurate, with about 25 % respondents
disagreeing to it (R1). About half of the respondent sample
was concerned about making a wrong decision based on the
available data (R2). While 36 % respondents remained neutral, around 42 % agreed that transparent data on such open
data websites clashes with ethics of privacy, leaks, and is a
threat to the overall national security (R3, Table 15).

Table 11 Coefficientsa
Model

(Constant)
Relative Advantage
Risk
Observability
Compatibility
a

Unstandardized Coefficients

Standardized Coefficients

B

Std. Error

Beta

.224
.464
−.062
.186
.355

.232
.047
.034
.040
.049

.382
−.059
.186
.294

Dependent Variable: Behavioral Intention.

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t

Sig.

.965
9.966
−1.818
4.667
7.259

.335
.000
.070
.000
.000