IEEE Technology and Society Magazine - Winter 2013 - 46

biquitous Monitoring (UM) describes
the continuous collection of data on a
large scale, enabled
by embedded, mobile, wireless,
and sensory technologies [1]. This
data will enable the envisioned
applications of Ubiquitous Computing. research has shown that
monitoring can affect user behavior [2], which is problematic for
ubiquitous computing because the
data collected may not fully reflect
the reality. Hence, any services
provided may not fully align with
user expectations or needs. One
proposed solution is the use of
deterministic models to predict the
behaviors of users prior to deployment, reducing the undesirable
effects of monitoring. The Perceptions of System Attributes-Behavioral Intention (PSA-BI) model was
specifically designed for this purpose [1]. while the model has been
validated, the moderating effect of
culture has not yet been explored.
As such, we present here results
from a study carried out in the U.K.
exploring the relationships in the
PSA-BI model. This is then compared with a structural model from
a previous study in Japan [3], [4],
allowing us to explore any potential
differences and similarities.

Existing Models
There are a number of existing
models designed to guide future
research or model the undesirable
effects of Ubiquitous Computing

Fig. 1. Wearable ubiquitous
monitoring device.
46

such as the Ubiquitous Computing Acceptance Model [5], and the
Awareness Monitoring Model [6].
while both are useful for conceptualizing the problem space, they
fail to consider many of the core
aspects of UM and behavioral
change. In contrast, the PSA-BI
model is specifically focused on
UM. The model is grounded in
the Theory of Planned Behavior
(TPB) [7], and can be found in its
entirety in [1] or [4]. The model
details how objective system characteristics (e.g., data types, degrees
of user control) relate to, and can
influence, user perceptions of a
UM system. These perceptions are
then used as a theoretical bridge
to the TPB, acting as antecedents
of attitudes, which in turn precede
behavioral intentions and ultimately behavior [7].

Study Design
To explore the influence of cultural
background on the components of
the PSA-BI model, a study has been
designed that uses data from two
different countries, Japan and the
U.K. These countries are ideal for
comparison due to the established
differences in perceptions of personal space, ideas surrounding the
concept of privacy [8], overall attitudes toward technology [9], and
the ubiquity, or lack thereof, of surveillance [10]. Of particular interest
are users salient perceptions, which
are the immediate perceptions (or
attitudes) that a user has about a
technology based purely on their
previous experiences, with no other
information available. Salient perceptions are of critical importance
because they will likely influence
the users subsequent experiences
with the technology, and thus play
a role in determining system acceptance and use [11]. To explore the
relationships in the model, a questionnaire was designed to measure
salient perceptions and attitudes
toward the hypothetical introduction of a monitoring system into a
workplace. The image in Fig. 1 was

used to invoke participant's salient
perceptions based purely on what
the device affords. Beyond the
description of the device as "wearable" and "deployable in their work
environment," no other information was presented to participants.
This was deliberate, in an attempt
to retain the salience of the participant's perceptions and reactions.
The benefit of this approach
is that the device is presented and
introduced in the same way for all
participants, allowing them to cognitively place the device in their
ownwork environment. The questions were centered on a series of
select prominent perceptions and
attitudes from the PSA-BI model
[1], and only those that showed statistically significant relationships
are presented (due to space constraints (for full details see [1])):
■ Perceived Natural Border Crossings (PNC): the degree to which
a person feels that any natural
borders have been crossed.
■ Perceived
Privacy Invasion
(PPI): the degree to which monitoring is felt to invade privacy.
■ Attitude
Toward Technology
(ATT): a positive or negative view
of technology's affordances.
■ Attitude Toward Application
(ATA): a positive or negative
view of the application of a
technology.
■ Attitude
Toward Behavior
(ATB): a positive or negative
view toward performing a specific behavior related to the
technology, e.g., use.
■ Facilitating Conditions (FC):
the degree to which an individual believes conditions
exist that give them control (or
choice) over whether they perform a behavior [7]. For example, if the behavior were use
of a wearable device, then the
facilitating conditions would
be related to whether or not a
person is able to remove it.
■ Behavioral
Intention (BI):
defined as an individual's
readiness to perform a given

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