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Figure 1. Taking user evaluations from the laboratory to the field makes it possible to evaluate user
acceptance on new services
commercial failures can be traced back to the
wrongly assessed value of the services to the users
(Kaasinen, 2005b).
User evaluations of mobile services often have
to be taken into the field as the service would not
function properly otherwise or it would not make
sense to evaluate it in laboratory conditions. This
would be the case, for instance, with GPS systems
and route guidance systems. In long-term field
trials with users, it is possible to gather feedback
on the adoption of the service in the users' every-
day lives. Such studies gather usage data beyond
mere usability and pre-defined test tasks (Figure
1). Field trials help in studying which features
the users start using, how they use them and how
often, and which factors affect user acceptance
of the service.
Business and marketing research already have
approaches whereby new technology is studied
on a wider scale. The Technology Acceptance
Model by Davis (1989) defines a framework to
study user acceptance of a new technology based
on perceived utility and perceived ease of use.
Each user perceives the characteristics of the
technology in his/her own way, based for instance
on his/her personal characteristics, his/her atti-
tudes, his/her previous experiences and his/her
social environment. The Technology Acceptance
Model has evolved and been applied widely, but
mainly in the context of introducing ready-made
products rather than in designing new technolo-
gies.
The Technology Acceptance Model for Mobile
Services is an extension to the Technology Ac-
ceptance Model. The model is based on a series
of field trials and other evaluation activities with
different mobile Internet and personal navigation
services and over 200 test users (Kaasinen, 2005b).
The Technology Acceptance Model for Mobile
Services constitutes a framework for the design
and evaluation of mobile services.
BACKGROUND
Technology acceptance models aim at studying
how individual perceptions affect the intentions
to use information technology as well as actual
usage (Figure 2).
In 1989 Fred Davis presented the initial Tech-
nology Acceptance Model (TAM) to explain the
determinants of user acceptance of a wide range
of end-user computing technologies (Davis 1989).
The model is based on the Theory of Reasoned
Action by Ajzen and Fishbein (1980). TAM points
out that perceived ease of use and perceived use-
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