ACCEPTANCE BY THE USERS OF SERVICES INTEGRATED IN
THE HOME ENVIRONMENT
Michele Cornacchia, Vittorio Baroncini
Fondazione Ugo Bordoni, Via Baldassarre Castiglione, 59 - 00142, Rome, Italy
Stefano Livi
Facoltà di Psicologia 2, Università degli Studi “La Sapienza”, Via dei Marsi, 78 – 00185, Rome, Italy
Keywords: Acceptance, assessment, controlled environment, ease of use, end users, evaluation, home control, home
networking, home services, integration of ICT, intention of use, interoperability, laboratory home platform,
laboratory trial, perceived usefulness, predictive model of user, services integration, usability.
Abstract: Whether or not ICT represents the most important vehicle to transform the society seems to be out of
discussion. The point of interest diverts from how people do really feel with these services and from the way
they perceive the advantages as acceptable to improve the quality of life and work. It is matter of fact that
the technical innovation is characterized by a certain risk, the problem of how to implement the technology
for sure and, ahead of this phase, the problem of predicting its influence on the social, working and private
life in view of the high costs effort to produce. This study applies a predictive model for the acceptance to a
services integrated home environment properly set-up in a special laboratory. A class of users was selected
from the employees of the company which hosted the trial in order to participate at the evaluation sessions.
The tasks were designed to point out the main innovative features of the services presented. The
questionnaires were suitably designed and submitted to collect the end-users opinions. The analysis was
carried out to assess the performance by the side of the real users and to predict their intentions of use.
1 INTRODUCTION
The study here presented is part of the work carried
out in order to investigate the user perception of the
ePerSpace (EPS, IST Project N° 506775) personal
services for the Home and Everywhere that were set
up at the laboratories of a big telephone company,
partner in the project.
The general aim was to measure the quality of
the delivered services, by verifying the usefulness
and ease of use as perceived by the real users, then
the amount of added value provided by each service,
even in a high technology reproduced environment.
The basic references given by the Unified Theory of
Acceptance and Use of Technology (Venkatesh et
al, 2003) were applied to define a model to forecast
the user acceptance (intention as predictor of usage)
and arrange the scales (questionnaires) to measure
the performance constructs.
2 THE ACCEPTANCE MODEL
Information Technology represents today a primary
way of transforming society but each application is
assumed to achieve specific benefits. The new
technologies actually can be applied to achieve a
wide variety of benefits (e.g. improve quality of the
life, of the work, etc.) and have influences in the
organisational change (e.g. improve productivity,
enhance work, effectiveness, etc.).
Because any kind of technical innovation is
characterized by a certain risk, there is the problem
of how to implement the technology and, ahead of
this phase, the problem of predict its influence (in a
short: “success or failure?”) in view of the high costs
effort to produce. If we look at some evidence about
the success or failure rates of information
technology projects, we firstly see that is very
difficult to attain data as the high complexity and
variability of the whole socio-technical system to
75
Cornacchia M., Baroncini V. and Livi S. (2007).
ACCEPTANCE BY THE USERS OF SERVICES INTEGRATED IN THE HOME ENVIRONMENT.
In Proceedings of the Third International Conference on Web Information Systems and Technologies - Web Interfaces and Applications, pages 75-82
DOI: 10.5220/0001280600750082
Copyright
c
 SciTePress

consider (Eason, 1988). The ordinary criticisms are
that the technology is being oversold (Cornacchia,
2003) and that it is regularly subject of changes
within short periods of time. Nevertheless, there are
some studies, named in the following, that give an
indication of the scale of the problem and the nature
of the possible outcomes. These studies are aiming
to support those organisations that accept risky
investment decisions for instance in order to get a
better competitive position. Many examples of the
emerging information technologies have been
publicized with consistent investment market
projections, but they remain strongly fastened by a
broad alone of uncertainty as for their effectiveness.
At the last, the most important questions rising up
the mind of the decision makers are about which of
these technologies will succeed and what the useful
applications have to be.
In the history the relevant literature describes the
development of several models of technology
acceptance (by the users) and many extensions to the
basic constructs (Malhotra & Galletta, 1999;
Venkatesh & Davis, 2000), mostly built with the
behavioural elements (Ajzen, 1996) of who is
forming an intention to act (Bandura, 1986) and the
inclusions of some kinds of constraints (limited
ability, learning and usage (Bagozzi et al, 1992),
time, environmental, organisational, unconscious
habits, and so on) which influence the individuals
actions (Compeau et al, 1999; Pierro et al, 2003).
Information technology acceptance research has
applied many competing models, each one with
different sets and very often overlapping of the
acceptance determinants (Davis, 1989). In their
paper Venkatesh and colleagues (2003) compared
eight competing models that were applied in order to
understand and predict user acceptance: Theory of
Reasoned Action (TRA), Technology Acceptance
Model (TAM), Motivational Model (MM), Theory
of Planned Behavior (TPB), Combined TAM and
TPB (C-TAM-TPB), Model of PC Utilization
(MPCU), Innovation Diffusion Theory (IDT), Social
Cognitive Theory (SCT). Those models were
originated from different disciplines mostly
connected with the behaviour prediction (Ajzen &
Fishbein, 1980) or specialized for the technology
use, from psychology to information system
literature. As a result, research on user acceptance
appear to be fragmented in different methods and
measures (Venkatesh & Davis, 1995).
For this reason the authors empirically compared
those concepts in order to formulate a Unified
Theory of Acceptance and Use of Technology model
(UTAUT) with four core determinants of intention
and usage, and up to four moderators of key
relationships (Figure 1): Performance Expectancy,
Effort expectancy, Social Influence and Facilitating
Conditions as well as other moderators variables
(such as Gender, Age, Experience and Voluntariness
of Use).
Figure 1: Theory of Acceptance and Use of Technology
model (UTAUT) from (Venkatesh et al, 2003).
Applied to the tested system, the Performance
Expectancy is defined as the believes that using the
new services will help him to attain gains in the
behavioural objectives. For the ePerSpace aim, this
variable will be made operative through the
Perceived Usefulness construct, relative advantage
of using the innovation compared to its precursor,
and outcome expectations.
The Effort Expectancy, defined as the degree of
ease associated with the use of the new system, has
as operative constructs the general perceived ease of
use as well as the perceived complexity of the
system.
The Social Influence, defined as the individual
perception of how individual social network believes
that he or she should use the new system, has as
operatives constructs Subjective norms, Social
factors and Social image and Identity similarity.
Finally, the Facilitating Conditions, are
represented by construct by Perceived Behavioral
control, general facilitating conditions (such as
objective environment factors) and compatibility
with existing values and experience of the potential
adopters.
One of the basic concept underlying the model of
user acceptance states that, in the domain of
“consuming the emerging technology”, the actual
use of information technology is influenced by the
intention to use and by the individual reactions to
using. And so, the greater are the positive reactions,
the greater is the intention and therefore the
possibility to engage in the use.
WEBIST 2007 - International Conference on Web Information Systems and Technologies
76

3 METHOD
3.1 Measurement Scales
The measurements scales of the acceptance applied
to the design of the questionnaire instrument are
mentioned in the following. All the scales were
tested and successfully used (high degree of
adaptability, high Cronbach alpha to denote the
consistence of the constructs, high variance
explained to denote independency of variables) in
several contexts or technological environments and
for different classes of users.
It is nevertheless important to call attention to the
fact that the questionnaires were adapted to the tasks
and that each subject participating to the evaluation
got first confidence with the innovating technology.
Said that, each questionnaire was referred to a
specific task and there were included, when
required, additional lines to purposely measure the
usability aspects of some significance (SUMI,
1998). Therefore, besides the central constructs of
the acceptance, the questionnaires included also
other high reliability scales, either for usability
(namely on efficiency, affect and control) either for
the identity-similarity or motivations (Perugini et al,
2000).
The results by the submission of such scales in
the evaluation provided the empirical evidence of a
large effect of personal identity on different
behavioural intentions. As for the home services
tested, the consumer behaviours may had a symbolic
meaning beyond their practical and objective
features and consequences. For example, buying a
certain equipment/system could have been an
associated behaviour with an image of “idealized
people” or with the “prototype” of the persons who
perform these behaviours.
The constructs used in the assessment were:
Performance Expectancy, Effort Expectancy, Social
Influence, Facilitating conditions, Attitudes toward
Using Technology, Attitudes (towards home
environment solutions), Intentions, Identity-
Similarity, Usability.
They corresponded to the questionnaire sections:
A - Perceived Usefulness in the home environment
B.1 - Perceived ease of use
B.2 - Complexity
B.3 - Ease of use
C.2 - Social factors
C.3 - Image
D.1 - Perceived behavioural control
D.2 - Facilitating conditions
D.3 - Compatibility
E.1 - Attitudes towards behaviour
E.2 – Intrinsic motivation
E.3 – Affect towards use
E.4 – Affect
F - Attitudes towards EPS solutions
G – Intentions
3.2 The Home Services Evaluated
The home environment services evaluated by the
users were selected from those that were set-up
within the Home Platform Portal. An outlook of the
services portal made available is shown in the
following Figure 2.
Figure 2: The home page to access the ePerSpace services
at Home and Everywhere.
The Home platform services available in the
portal are exposed in the Table 1.
Table 1: Home platform services of ePerSpace.
HOME
PLATFORM
SERVICE
Indoor elements
Outdoor
elements
Appliances,
actuators and
white
appliances
management
Residential Gateway,
home automation
networks, home devices
and white appliances,
personal devices for
service interface
(PDA/smart phone/PC/TV)
Service
and
network
provider
Alarms
Handling
Residential Gateway,
home automation
networks, personal devices
for service interface
(PDA/smart
phone/PC/TV), network
cameras
Service and
network
provider
Access control Residential Gateway,
RFID reader; RFID
personal cards, home
automation network, smart
phone/PC/TV
Service and
network
provider
ACCEPTANCE BY THE USERS OF SERVICES INTEGRATED IN THE HOME ENVIRONMENT
77

The control of the automated home appliances
and devices includes the management of:
- Lonwork actuators and sensors over twisted pair:
lights, water valve, blinds, canopies, door lock,
fire/gas/water detectors, etc.
- Lonwork white appliances over power line: oven
and washing machine.
- Actuators and sensors: lights and small motors
attached to a demo panel.
- Network cameras.
3.3 The Tasks
A set of tasks was properly designed for the class of
users profiled for the trial and the services to
evaluate. The services were accessed by the user
from any PC or PDA wired or wirelessly connected
to the LAN of the home. In both cases, the user
started the browser of the access terminal to initially
authenticate him/herself by username and password.
After that, the user was admitted to the home portal
and enabled to select from the list of the personal
services.
In case of being using the web access, a map of
the house displayed icons representing the home
appliances that can be actuated, as well as its current
state (i.e., on/off). At the user click on each icon a
menu of the possible actions appeared. For example,
in the case of a light, currently on, the user was
offered to switch it off and adjust the light intensity.
In case of using the PDA access, instead of a map of
the house, the user found a list showing the rooms in
the house. At the user click on one of the rooms, the
list of automated devices to be controlled in that
room displayed. The running was similar to the web
access, but the graphical interface was more simple
to adjust to the limited screen size.
3.4 Set-Up of the Test Bed
All the HAN of the test-bed were connected to the
RG (Residential Gateway) which run an OSGi
(Open Services Gateway initiative) framework over
which the home platform services are managed and
activated. A Personal Computer or Laptop or a
Personal Digital Assistant (PDA), inside the house,
were used either to access the web interface of the
services and also to provide the I/O for the tasks
planned to be accomplished by the users in the
assessment. The PDA was connected to the HAN via
WiFi in the house for the demonstration. A Set Top
Box (STB) was connected to the TV set and could
run also home environment services, controlled by
the RG Middleware.
Basically the automated control for the house
domestic devices from the PC in web interface
services of the Home Platform were evaluated. The
user accessed the options from a list of services
directly through the main page. The procedure to
carry out the evaluation followed a prearranged
scheme. Each subject was received in front of the
house door, informed about the overall session and
the services to be evaluated by means of
questionnaires. The questionnaires were arranged in
a labelled sequence, then submitted to the subject.
About 60 questions over the total amount of 193
were answered by each subject in the section of the
local services for the home (Figure 3).
Figure 3: “Home Control” sub-menu.
The evaluation process took place in two weeks
in total. The integration work lasted 6 months. The
test bed used for the user evaluation gave a
configuration and outlook of a real flat (Home).
3.5 The Users Profile
A two steps selection of final 40 users followed
some general criteria in order the final class of
subjects could be the most homogeneous possible
and provide consistent values of judgements.
The subjects selected for this evaluation were
chosen among the employees of the company
hosting the trial, as close as possible to an ideal type
of potential user, open minded enough towards ICT
solutions (neither too much enthusiastic neither to
much unwilling) and on an average skilled in using
electronic digital devices (e.g. the PC or other home
familiar devices).
The first step in the definition of a class of users
was mainly a rough skimming from a initial set of
about 70 individuals, preliminarily contacted in
order to be certain that:
WEBIST 2007 - International Conference on Web Information Systems and Technologies
78

1. the subjects characteristics were close to the
home services requirements of use;
2. the essential skills and the basic attitudes
towards ICT were not unacceptable;
3. the subjects were volunteers.
The second step was a selection of the final 40
users, among the several items relating about each
individual, to check whether:
1. the final group were sufficiently represent
males and females;
2. the age range (at least) were as narrow as
significant to the statistics to apply;
3. the availability to effectively participate to the
evaluation sessions were an actual statement.
The emerging final profile shows:
1. a proportion of frequencies about the 23% for
females while the 77% for males;
2. evident age crowding in the range 30-39 years,
3. equal occurrence of married and single
individuals;
4. medium-high level of education;
5. mostly technicians and engineers (respectively
70% and 15%);
6. high experience accrued with ordinary IT
technologies (PC, Email, Mobile, etc.);
7. proximity to household equipment with
communication means.
The users participating to the evaluation went
through an introduction of the Project and a training
session in order for them to use the system almost
without assistance in order to obtain valuable and
not-biased information from the questionnaires.
3.6 The Data Analysis
The questionnaires were coded and the data properly
wrapped up to be analysed by means of the SPSS
(Statistical Package for Social Science 13.0). Three
main groups of analyses were generated as output:
1. descriptive statistics for all cases and outliers
identification; the data were grouped in the way
that the scores of the home services appeared, for
each aspect of the Acceptance.
2. correlation study for the Home services relative
to the dependant variable “attitudes towards
behavior”.
3. extended correlation study of the service Home
Control in relation to the dependant variables
“attitudes towards EPS solutions” and
“intentions”.
4 RESULTS
The descriptive statistics (median, confidence
interval within ±σ, outlier rejection interval > ±2σ)
were shortly assembled in the 14 lines of Table 2, as
many as the cases were for the Home Control Panel
and the home services through it accessed.
Table 2: Descriptive statistics for the Home Services
accessed through the Home Control Panel.
HOME
CONTRO
L PANEL
min
ma
x
averag
e
standard
deviation
outliers
Perceived
Usefulness
in the home
environment
1.0
0
5.50 2.81 1.08 0
Perceived
ease of use
1.0
0
5.00 2.24 .88 1>max
Complexity
4.0
0
7.00 5.74 .86 0
Ease of use
1.0
0
5.00 1.88 .84 1>max
Social
factors
1.0
0
7.00 3.03 1.69 0
Image
1.0
0
7.00 3.33 1.64 0
Perceived
behavioural
control
2.0
0
6.33 3.56 .81
1<min,
2>max
Facilitating
conditions
1.0
0
7.00 4.17 1.77 0
Compatibilit
y
1.0
0
6.00 2.38 1.21 0
Attitudes
towards
behaviour
2.0
0
7.00 5.79 1.30 2<min
Intrinsic
motivation
1.0
0
7.00 2.56 1.27 2>max
Affect
towards use
2.0
0
7.00 5.54 1.34 0
Affect
2.5
0
7.00 4.63 .79 1>max
Attitudes
towards
EPS
solutions
2.5
0
7.00 5.13 .93
2<min,
2>max
4.1 Frequencies
The analysis of the frequencies gathered pointed out
that from a broad point of view the services were
well accepted by the users, as innovative for the
home and access from the elsewhere. The variables
used to define the constructs of the acceptance
model, all showed a definite tendency in positively
comparing the ICT solutions presented in the test-
bed with the already available personal services that
can be seen as a clear advantage and concrete
expectation for the home services to improve the life
style of its users.
ACCEPTANCE BY THE USERS OF SERVICES INTEGRATED IN THE HOME ENVIRONMENT
79

This important result was first attained by the
Perceived Usefulness, and then it was supported by
the plain scores gathered by Effort Expectancy (i.e.
very high of ease to learning and low perception of
complexity) and Social Influence (i.e. the family
view coherent and close to a doable real use). At
last, the external conditions tested were compatible
with the life style of the subjects and as a matter of
fact not opposed to the potential adoption, as well as
the wide-ranging attitudes towards the new home
solutions.
4.2 Correlation
The Pearson correlations were computed to look for
significant linear links between the variables of the
Predictive Model of the Acceptance, i.e. for the
Home Service and the dependent variable (positive)
“Attitudes towards behavior” (item of section E1 in
the questionnaire), as resulted in Table 3 analysis.
Table 3: Attitudes towards the new solutions for the Home
Control.
Valid cases
Attitudes towards
solutions for HOME
CONTROL
Perceived Usefulness in
Home Environment
.35(*)
Perceived ease of use .17
Complexity -.19
Ease of use .06
Social factors
.42(**)
Image -.05
Perceived behavior control -.03
Facilitating conditions .05
Compatibility
.46(**)
Attitudes towards behavior
.53(**)
Intrinsic Motivation
.42(**)
Affect towards Use .30
Affect -.01
*. Correlation significant at the degree of 0,05 (2-tails).
**. Correlation significant at the degree of 0,01 (2-tails).
As given in the Table 3, all values in bold and
with one/two asterisks indicate the presence of a
high/higher degree of correlation between the
variables. Having a look to the links in the picture of
the predictive model of acceptance, it means that, for
the home services, there were good probabilities that
the positive attitude of a user-consumer were
influenced by those variables. Taken for example the
Home Control “Perceived Usefulness: effectiveness
in home activities”, it can be said that: either “the
greater is the effectiveness in the home activities the
greater is this influence on the “positive attitude
towards solutions”, or it can be said “the significant
Pearson correlation provides evidence that the
variable “perceived usefulness” stimulates the
perception of positive attitude towards solutions”.
4.3 Extended Correlation
The Pearson correlations were computed in order to
look for significant linear links between the
variables of the Predictive Model of the Acceptance,
for the Home Control alone, and the two dependent
variables “Attitudes towards EPS solutions” and
“Intentions” (respectively sections F and G of the
questionnaire). The results are shortened in Table 4.
Table 4: Home Control correlations with “Attitudes
towards EPS solutions” and “Intentions”.
HOME CONTROL
Attitudes
towards EPS
solutions
Intentio
ns
Perceived Usefulness in the
Home Environment
.45(**) .33(*)
Perceived ease of use .31 .16
Complexity -.27 -.30
Ease of use
.35(*) .33(*)
Subjective norms
.33(*) .40(*)
Social factors
.41(*) .64(**)
Image .24 .31
Perceived behavioural
control
.29 .13
Facilitating conditions .14 .07
Compatibility
.54(**) .47(**)
Attitudes towards behaviour
.62(**) .43(**)
Intrinsic Motivation
.63(**) .45(**)
Affect towards Use
.39(*)
.12
Affect .29 .30
*. Correlation significant at the degree of 0,05 (2-tails).
**. Correlation significant at the degree of 0,01 (2-tails).
The Home Control extended study was based on
the choice of a different (but close to the previous
set) couple of dependent variables to be used to
compute the Pearson correlations.
As given in the Table 4, all values in bold and
with one/two asterisks indicate the presence of a
high/higher degree of correlation between the
variables. Always having a look to the links figured
in the predictive model of acceptance, it mean that,
for the Home Control service, the “perception of
having intention to use” of the subjects was even
more demonstrated to be influenced.
The main difference from the other table is in the
availability of the “intention” as direct dependant
WEBIST 2007 - International Conference on Web Information Systems and Technologies
80

variable. This availability makes the accuracy of the
measure higher. As seen by simply comparing the
columns of the “attitudes towards EPS solutions” in
both Table 3 and Table 4, more accuracy made
possible the detection of more correlations.
As concerning the Home Control service, the
interpretation of the correlations is the same than in
the previous table. Taken for example the Home
Control “Perceived Usefulness: effectiveness in
home activities”, it can be said that: either “the
greater is the effectiveness in the home activities the
greater is this influence on the “intention of using”,
or it can be said “the significant Pearson correlation
provide evidence that the variable “perceived
usefulness” stimulates the perception of having
intention to use”. The Table 4 also provide a direct
read of the correlation to the intention in the second
column.
4.4 Gender Differences
In order to evaluate the differences between Male
and Female perception of the Home Control Panel,
was compared the mean of each sample and
performed an Analysis of Variance (ANOVA) to
verify if those differences were statistically
significant.
Results showed that, overall, male and female
perceived user acceptance in the same way for
almost all the dimensions explored. The only
noteworthy exception was pointed out for the
“Perceived Usefulness in The Home Environment”,
where females, differently from males, stated that
using the Home Control system would enhance their
job performance (
F(1,37)=6.10; p<.05).
In the following Table 5 there are the results for
the mentioned variable.
Table 5: Gender differences for the Perceived Usefulness
in the Home Environment.
Perceived Usefulness in the Home
Environment HOME CONTROL PANEL
Mean N
Standard
deviation
Male
2.62 30 .98
Mean N
Standard
deviation
Female
3.56 9 1.08
Mean N
Standard
deviation
Total
2.83 39 1.07
ANOVA: F(1,37)=6.10; p=.02
5 CONCLUSIONS
The new home services as provided in the trial were
on the whole accessed by the subjects with high
curiosity and interest. The adoption of a controlled
interactive session to present the services and their
innovative features was able to give to each single
participant the time necessary to understand and
quickly build a personal judge about.
Then the repeated sequence task-questionnaire to
gather data demonstrated to be appropriate in
catching the impulsive ideas about the added values
given by each service in comparison with the actual
home possibilities, as well as the possible adoption
in the own life. This is an excellent consequence of
the methodology proposed for the evaluation, then
proved by the reliable data obtained.
As for the acceptance items, this is a composite
variable that can be carefully expressed by
combinations of different results (and different
constructs).
Therefore, by considering the “perceived
usefulness” (Questionnaire Section A), the users
class received a positive feeling from the services.
This result is strongly powered by looking at the
values of the Questionnaire Sections B.1, B.2, B.3,
which indicate the clear easiness to operate and the
low perception of underneath complexity, even not
really so (this is and excellent result from the
usability point of view, better evident for the Home
Control).
The social factors (Questionnaire Sections C.2,
C.3) confirmed how the subjects view was also
shareable with the family and the close neigh
borough.
The facilitating condition “having the
resources/knowledge necessary to use the system”
(Questionnaire Sections D.1, D.2) resulted about
neutrally considered in relation with the acceptance,
while it was very encouraging the perception of the
“compatibility” (Questionnaire Section D.3),
actually close to the idea of lifestyle at home.
The rest of the items in the questionnaire directly
checked the attitudes of the subjects towards both
the service idea and the actual usage possibility at
home. The resultant Questionnaire Sections E.1, E.2,
E.3, E.4 scored high positive values, indicating that
there were clear intrinsic motivations in the thought
of acquiring these services for the home.
Finally, the last variable (Questionnaire Section
F) of “attitudes towards EPS solutions” in a straight
line confirmed that the users should be willing to
introduce the new solutions at home, as they were
desirable, important, useful and agreeable.
ACCEPTANCE BY THE USERS OF SERVICES INTEGRATED IN THE HOME ENVIRONMENT
81

The ANOVA applied to find differences of
behaviour between males and females, pointed out
no statistical differences except one: the females
perceived differently the “usefulness at home” of the
services.
The analysis on the data gathered of course
didn’t investigate the cause of this “social”
difference, nonetheless, it is spontaneous to think at
the actual different condition of the women at home
in different countries and the different perception of
“the usual staying at home” they may have with
respect to the men.
ACKNOWLEDGEMENTS
Special thanks are due to the Spanish partners of the
ePerSpace Project without whom the experimental
sessions with the users couldn’t have taken place.
REFERENCES
Ajzen, I., Fishbein, M., 1980. Understanding attitudes and
predicting social behaviour, Eaglewood Cliffs, NJ:
Prentice-Hall.
Bagozzi, R. P., Davis, F. D., & Warshaw, P. R., 1992.
Development and test of a theory of technological
learning and usage, Human Relations, 45(7), 660-686.
Bandura, A., 1986. Social Foundation of Thought and
Action: A Social Cognitive Theory, Prentice Hall,
Englewood Cliffs, NJ.
Compeau, D. R., Higgins, C. A., and Huff, S., 1999.
Social Cognitive Theory and Individual Reactions to
Computing Technology: a Longitudinal Study, MIS
Quarterly (23:1), pp. 145-158.
Cornacchia, M., 2003. Usability, a way to distinguish from
the good, the bad, and the irrelevant in the web, Cost
269, Conference Proceedings, Media Centre Lume,
University of Art and Design, Helsinki (Finland),
pp.159-163, September.
Davis, F. D., 1989. Perceived usefulness, perceived ease
of use, and user acceptance of Information
Technology, MIS Quarterly, 13(3), 319-340,
September.
Eason, K., 1988. Information technology and
organisational change, Taylor & Francis.
Malhotra, Y., Galletta, D. F., 1999. Extending the
Technology Acceptance Model to Account for Social
Influence: Theoretical Bases and Empirical
Validation, Proceedings of the 32
th
Hawaii
International Conference on System Sciences (IEEE
99).
Perugini, M., Gallucci, M., Livi, S., 2000. Looking for a
Simple Big Five Factorial Structure in the Domain of
Adjectives, European Journal of Psychological
Assessment, Vol.16, Issue 2, pp. 87-97.
Pierro, A., Mannetti, M., Livi, S., 2003. Self-Identity and
the Theory of Planned Behavior in the Prediction of
Health Behavior and Leisure Activity, Self and
Identity, 2: 47-60.
SUMI, 1998. Software Usability Measurements Inventory
(7.38), Human Factors Research Group, Cork, Ireland.
Taylor S. and Todd, P. A., 1995. Assessing IT usage: The
role of prior experience, MIS Quarterly (19:2), pp.
561-570.
Thompson, R. L., Higgins, C. A., and Howell, J. M., 1991.
Personal computing: towards a conceptual model of
utilisation, MIS Quarterly (15:1), pp. 124-143.
Venkatesh, V., Davis, F. D., 1995. Measuring User
Acceptance of Emerging Technologies: An Assessment
of Possible Method Biases, Proceedings of the 28th
Annual Hawaii International Conference on System
Sciences (IEEE 95).
Venkatesh, V., Davis, F. D., 2000. A theoretical extension
of the technology acceptance model: Four longitudinal
field studies. Management Science, (46:2), 186-204.
Venkatesh, V., Morris, M. G., Davis, G. B., Davis, F. D.,
2003. User Acceptance of Information Technology:
Toward a Unified View, MIS Quarterly vol. 27 No. 3,
pp. 425-478, September.
WEBIST 2007 - International Conference on Web Information Systems and Technologies
82