Quality Evaluation Models - High Level Models and Methodologies for Information Systems - page 104

Fig. 6.9 The innovation decision process (adapted from Rogers 1983 )

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uncovered. The outcome of this process of collecting information, in order to
increase users

' con dence in the innovation they have to adopt, is what will deter-

mine the users approval or dismissal of that innovative technology (Nor et al. 2010 ).

According to the IDT, there are

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five attributes that innovations can have that will
determine user perception and adoption: relative advantage, compatibility, com-
plexity, trialability, and observability (Rogers 1983 ). Each of these elements has its
own importance and contributes to the users

opinion about an innovative tech-
nology. However, some studies have concluded that only three of these elements
can be unequivocally measured and linked to innovation adoption:

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relative

advantage, complexity, and compatibility (Tung et al. 2008 ).
The first of these traits, relative advantage, concerns the level of perceived

bene its that the new technology presents in relation to its antecessor. This notion is

comparable to the concept of performance expectancy. Complexity refers to the
degree of intricacy that the usage of the system will imply. It is in the same line as
the traditional de nition of effort expectancy. Finally, compatibility is the measure

of adequacy that a speci c technology possesses in relation to user values, work

practices, and beliefs (Bhattacherjee et al. 2012 ).
Besides innovation characteristics, the IDT model also accounts for leader
characteristics, particularly those that account for a leader s stance in relation to

change. Equally important are the internal features of the organization, such as
complexity, formality, size and organizational structure, as well as its external
features, like system openness (Sila 2013 ).

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