IEEE Technology and Society Magazine - Winter 2013 - 47

R 2 = 0.198
PNC
β = 0.485

PPI

R 2 = 0.519 R 2 = 0.819
ATT

β = -0.625

R 2 = 0.423

ATB
β = 0.750

BI
β = 0.792

β = -0.231

R 2 = 0.407 R 2 = 0.874
ATT

PPI

β = -0.874*

ATB

BI
β = 1.179

β = 0.873

β = 0.598

FC

p < 0.001, *p < 0.01

R 2 = 0.499

ATA
R 2 = 0.915

Fig. 2. Structural models of Kyoto (left/grey) and reading (right/white) data.

behavior, and acts as the direct
antecedent of behavior according to the TPB [7]. The intention under investigation in
this study is whether or not a
participant would wear the tag
presented in Fig. 1.
The tested relationships between
each of these components can be
seen in Fig. 2. These relationships
are grounded in evidence from the
Ubiquitous Computing and surveillance/monitoring literature. One of
the main hypotheses for this study
is that there are expected strong
differences between British and
Japanese participants, particularly
related to PPI and PNC.
Sample
For this study, an online questionnaire was distributed to a support
and administrative staff e-mailing
list at the University of reading,
U.K. with a total of 101 use able
responses. In a previous study [3],
[4], a paper based questionnaire
(using the same measures) was
distributed to office based administrative and support staff at Kyoto
University, Japan; where a total
of 164 use able responses were
received. The demographics for
each sample can be seen in Table I.
The samples have similar age, type
of employment, and supervision
of employees distributions. There
are some notable differences, with
most Japanese employees (92.7%)
working in open-plan environments.
The self-reported computer skill
level also appears to be higher in
the reading sample (Intermediate -
Advanced 92%), which is surprising

given the prominence of technology
in Japanese culture (which in our
view suggests a sense of modesty,
as the Japanese are often considered world leaders in technological
adoption and innovation).
Measure Assessment
A series of three 7-point Likert
items were re-used from our previous Japanese study [3], [4]. Convergent validity was demonstrated for
both the U.K. sample (see Table IV)
and in Japan with all factor loadings and average variance extracted
(AVE) values being > 0.5, and all
composite reliability and alphas are
$ 0.7 [12]. Alpha measures were
consistent across both the Japanese
and reading samples, adding validity to the translation (see Table IV).

IEEE TECHNOLOGY AND SOCIETY MAGAZINE

Some measures were removed for
ATA, PPI, ATB and BI to improve
reliability. Discriminant validity
was confirmed by values of AVE
> 0.5, and the AVE being higher
than all other correlations among
constructs [12] for reading (see
Table III) and Japan [3], [4].
Method of Analysis
Structural Equation Modeling
(SEM) is a technique that simplifies
the exploration of multiple hypotheses [12]. This makes it an ideal
approach to test the relationships
in the PSA-BI model. As the measures were not found to be normally
distributed, the Generalized Least
Squares (GLS) statistic was used
[12]. with recommendations of 15
respondents per parameter, both the

Table I
Sample Demographic

Item
Gender
Male
Female
Age
18 - 29
30 - 59
60+
Office
Open Plan
Environment
Shared Single
Individual
Type of
Full-Time
Employment
Part-Time
Supervise
Yes
Employees
No
Computer Skill Novice
Intermediate
Advanced
Expert

|

wINTEr 2013

Kyoto N = 164

Reading N = 101

Freq.
82
82
25
127
12
152
12
0
133
31
48
116
82
69
10
3

Freq.
14
87
23
67
11
42
34
25
82
19
40
61
2
47
46
6

%
50.0
50.0
15.2
77.4
7.3
92.7
7.3
0.0
81.1
18.9
29.3
70.7
50.0
42.1
6.1
1.8

%
13.9
86.1
22.8
66.3
10.9
41.6
33.7
24.8
81.2
18.8
39.6
63.4
2.0
46.5
45.5
5.9

|

47



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