IEEE Technology and Society Magazine - Fall 2013 - 58

Exogenous Moderating Variables
Moderating Anchors
Past
Computer
Experience Skill Level

Context

Age

Gender

Social
Influence

External Variables
Anchors

Object Based
Beliefs

Object Based Attitudes

Application
Space

Application
Perceptions

Attitude
Toward
Application

Technology
Space

Technology
Perceptions

Attitude
Toward
Technology

Adjusters

Facilitating
Conditions

New
Experience
Information

Environment

Role

Culture

Behavior Based
Attitudes

Attitude Toward
Behaviour

Behavior
Intention

Time

Fig. 1. The perception of system attributes - behavioral intention model (based on [1]).

level of access, which in turn may
influence their perceptions of privacy invasion. The system characteristics themselves will not directly
influence behavior, but will do so
only through a user's perceptions of
those characteristics.
A number of exogenous factors will influence how a user perceives the system, ranging from
their age and gender, to their past
experiences and the social context within which the data collection takes place [11]. A number
of "adjusters" will also influence
a user's perception of the system,
including the passage of time and
experience. It is these perceptions,
or object based beliefs (the system
is the object) which act as a bridge
to modified TPB and UTAUT
models [12].
A user's perceptions, or object
based beliefs, will influence their
attitudes (positive or negative)
toward the object/system. Application and technology object based
attitudes are influenced by the preceding perceptions. Based on these
attitudes, a user will form attitudes
58

regarding a behavior related to the
system (e.g., acceptance, sharing of
specific data, use at work). A user
will also formulate their perception
of social influence. These perceptions include the social pressure
from people who are important to
them to perform the behavior and
facilitating conditions, i.e., whether
or not the conditions exist to give
them control over whether they perform the behavior (an easily accessible "off-switch" facilitates the
behavior of shutting a device down).
The combined influence of attitudes toward the behavior, social
influence and facilitating conditions affect a user's intention to
carry out the behavior. This in turn
is the direct antecedent and predictor of behavior itself.
The model has been empirically
tested using a series of questionnaires, and the results analyzed
using structural equation modeling
[1] to identify the regression coefficients between variables. These
were then used as a part of a simulation which propagated the effects
of input variables and accurately

made a prediction about a behavior
[1], [12], thus validating the model.
While the model has been applied
in a number of domains such as
ubiquitous computing [1], assistive
technologies [12], and persuasion
[13], the impact of culture as an
exogenous moderating variable has
yet to be explored. One of the motivations for exploring this variable
in particular (as opposed to age or
gender) is an anticipated strong contrast between people from different
countries and cultures in their views
of monitoring systems.

Study Design
Japan as a country has a unique
and intriguing culture, and as such
is an ideal environment to explore
the potential impact of culture on
user perceptions, particularly as
the PSA-BI model was based on
data collected primarily in the
U.K. One of the notable aspects of
Japanese culture is the general positive attitude towards technology
adoption, e.g., i-mode [14]. Given
that monitoring or surveillance in
the Japanese public sphere is less

IEEE TECHNOLOGY AND SOCIETY MAGAZINE

fALL 2013

Table of Contents for the Digital Edition of IEEE Technology and Society Magazine - Fall 2013