Summarize from:
Prediction of Internet and World Wide
Web usage at work: a test of an
extended Triandis model
Waiman Cheung , Man Kit Chang ,
Vincent S. Lai
Decision Support Systems 30 (2000)83–100
986220 Kent
986223 Allen
1
Introduction(1/3)
• The Internet and World Wide Web/(WWW) have
impacted every facet of our lives: communication,
entertainment, social activities, shopping, etc. For
organizations, the Internet/(WWW) has created a host of
opportunities, ranging from support for existing work
practices to business process reengineering, as well as
the creation of new business possibilities.
2
Introduction(2/3)
• The factor that the study believe to be important is
facilitating conditions (i.e., the availability of the
necessary resources and supports while using the
Internet.)
• In order to provide smooth access to the Internet, a large
number of elements must work closely together. These
elements include the internal network, connections to the
external Internet, as well as a variety of Internet software,
such as email clients and Web browsers.
• Therefore, the study decided to adopt a more
comprehensive social psychological model, the extended
Triandis model.
3
Introduction(3/3)
• The Triandis model has been successfully used in a
number of technology adoption studies. However, some
important relationships such as how complexity affects
short- and long-term consequences.
• Therefore, the study attempted to incorporate these
relationships into the Triandis model to form a new
research framework for the investigation of factors
affecting the use of the Internet/WWW at work.
4
Research framework: a modified Triandis
model
• Triandis proposes a theoretical network relating attitude
and behavior to many constructs.
• The study were interested in the prediction of actual
behavior, ”intention” was dropped from the model.
Instead, this paper studied the direct effects of social
factors, affect, and perceived consequences on current
behavior.
• Habit was also excluded from this investigation because
in a past study measurements for habit and actual
behavior are the same.
5
Subset of the Triandis model
Complexity
×
Near-term
consequenc
e
×
Long-term
consequence
6
Research framework showing the
hypotheses
7
Hypotheses(1/7)
-affect
• Affect is the direct emotional response to the thought of
a behavior and is referred to as the “feelings of joy,
elation, or pleasure, or depression, disgust, displeasure,
or hate associated by an individual with a particular act.”
• Affect has also been found to be significant in predicting
other behaviors. Therefore, the paper hypothesize that
affect will have a positive impact on Internet and WWW
usage.
8
Hypotheses(2/7)
-social factor
• Some studies in psychology and management, have
confirmed the important role of social norms in
determining human behavior.
• The use of the Internet and the WWW is currently a hot
topic. Therefore, social pressure may cause those who
are not using the Internet to feel that they have been ‘left
behind’, so the study predict that there is a positive
relationship between the social factor and Internet/WWW
usage.
• Previous studies have also found that the social norm
has a positive impact on a person’s feeling toward
his/her behavior. Therefore, the paper add a path from
the social factor to affect in our model and hypothesize
that the social factor will have a positive impact on affect.
9
Hypotheses(3/7)
-perceived consequences
• The perceived consequences of a behavior is defined in
past studies as:
• Where C=the value of the perceived consequences,
P =the subjective probability that a particular
consequence will follow a behavior, V =the value of that
consequence, and n=the number of consequences that
a subject perceives as likely to follow a particular
behavior.
10
Hypotheses(4/7)
-near-term consequences
• Perceived near-term consequences are defined as the
extent to which an individual believes that using the
Internet/WWW can enhance the performance of his/her
job. The impacts are on the individual’s current job.
• Past studies have consistently found that this factor is an
important determinant of intention and behavior. Thus,
this paper predict that there is a positive relationship
between perceived near-term consequences and
Internet/WWW usage.
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Hypotheses(5/7)
-long-term consequences
• Long-term consequences include the increased
flexibility to change job or increased
opportunities to have a more meaningful job.
• Past studies indicated that when predicting the
behavioral intention to use MS Word and Excel,
found long-term consequences to have a
significant impact. Therefore, this paper
hypothesize that perceived long-term
consequences are positively related to
Internet/WWW usage.
12
Hypotheses(6/7)
-complexity
• Complexity is defined as “the degree to which an
innovation is perceived as relatively difficult to
understand and use”.
• In past studies, users feel happier using a technology
that is easy to use.
• The impact of complexity is multifaceted. In this model,
the paper hypothesize that perceived complexity
negatively affects usage, perceived short-term and longterm consequences, and affect.
13
Hypotheses(7/7)
-facilitating conditions
• In the study, the facilitating conditions include hardware,
software, network connections, etc., that allow
individuals to access the Internet when they want to, as
well as the supports provided by a company to facilitate
the use of the Internet and the WWW at work.
• Although using the Internet or the WWW may not be
very difficult from the user’s point of view, it is more
complex than facilitating PC use from the supporting
personnel’s point of view. Thus, the effect of support on
Internet and WWW usage may be more significant than
for PC usage. Therefore, the paper predict that there is a
positive relationship between Internet/WWW usage and
facilitating conditions.
14
Method
• A total of 290 questionnaires were distributed to parttime diploma and MBA students in two universities in
Hong Kong.
• This yielded a total of 241 usable questionnaires (net
response rate 83%).
• They came from a wide variety of industries.
• The mean age of the respondents was 32.6 with a
standard deviation of 6.5 years.
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Results(1/8)
-Construct validity and reliability
• Discriminant validity is assessed using factor
analysis. The 28 items measuring the seven
constructs in the research model.
• Factor loadings should all higher than 0.5 on its
own factors.
• Only the third item of near-term consequences,
has a cross-loading of 0.42 on the long-term
consequences factor. Since it still loaded higher
on its own factor, we decided to keep it.
16
Results(2/8)
-Construct validity and reliability
17
Results(3/8)
-Construct validity and reliability
18
Results(4/8)
-Construct validity and reliability
• Cronbach’s alphas are used to assess the
internal consistency reliability, As shown in the
last column of Table 1, the reliability coefficients
ranged from 0.83 to 0.91, which was significantly
higher than the acceptable level of 0.7.
• These results confirm that the scales used are
both valid( factor loading>0.5) and
reliable( Cronbach’s alphas >0.7).
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Results(5/8)
-Testing of the model
• A series of least square multiple
regressions were performed to test the
hypotheses and to obtain the path
coefficients of the model as follow.
20
Results(6/8)
-Testing of the model
21
Results(7/8)
-Testing of the model
• As shown in the table2:
positively related to the
current Internet/WWW
usage
– facilitating conditions
β= 0.296.
– social factors β= 0.263
– near-term consequences
β=0.221.
negatively related
– complexity β=-0.149.
22
Results(8/8)
-Testing of the model
• Table 3 :
column 2 shows the
effect of social factors
and complexity on affect
– social factors β=0.201
– Complexity β=-0.291
columns 3 and 4 shows
the effect of complexity
on short-term and longterm consequences
– near-term β=-0.274
– long-term β=-0.186
23
Discussion(1/7)
-facilitating conditions
• Facilitating conditions have the most significant positive
impact on Internet usage.
• Therefore more external support is necessary from an
organization’s IS department to provide smooth to the
Internet.
–
–
–
–
Establishing and maintaining connections to the Internet.
Making sure the Internet server and the gateway work together.
setting up e-mail accounts and web browsers.
providing multimedia viewing facilities.
24
Discussion(2/7)
-social factors
• Social factors are the second most important
determinant affecting the use of the Internet/WWW.
• This means that when the social environment encourage
the use of the Internet/WWW, users feel more positive
about using it.
25
Discussion(3/7)
-perceived near-term consequences
• Perceived near-term consequences, which measure the
belief that the quality and efficiency of the users’ job will
be enhanced after using the Internet/WWW, have a
positive effect on Internet usage.
• Previous studies have shown that near-term
consequences are the most important determinant for
PC usage, it ranks third in our study.
• Using the Internet/WWW seems to be a trendy activity
right now for both work and pleasure; thus, social
pressure seems to surpass near-term consequences as
a determinant of Internet usage.
26
Discussion(4/7)
-affect
• Despite the effect of affect on Internet usage is found to
be insignificant, it does not mean it is unimportant.
• Past studies have shown that affect does not
significantly affect current behavior. However, it does
have a significant impact on the formation of intention.
• Because the combination of social pressure and the
usefulness of Internet/WWW may lead to increased use,
whether the users enjoy becomes less important.
27
Discussion(5/7)
-perceived long-term consequences
• Perceived long-term consequences do not have a
significant effect on Internet/WWW usage.
• Our finding is the same as Thompson et al. found for
inexperienced PC users. Long-term consequences
mainly measure effect on career.
• Since most of the respondents are not in the field of IS/IT,
the Internet/WWW generally only plays a supportive role
in their jobs. Thus, long-term consequences become
insignificant.
28
Discussion(6/7)
-complexity
• The complexity of Internet/WWW technology does
discourage users.
• Which is found to have a significant negative effect on
Internet usage, near-term consequences, long-term
consequences, and affect.
• Thus, complexity not only directly affects usage, it also
affects usage indirectly through near-term consequences.
29
Discussion(7/7)
• Organizations, which are trying to promote the use of the
Internet/WWW for job related activities can create a
supportive social atmosphere and provide physical
support.
• Companies should communicate the positive impacts of
using the Internet on an employee’s future job prospects
and also provide more learning opportunities for
employees or training courses and experience sharing.
30
Limitation
• The respondents’ education level is on the high side. As
the user base rapidly expands, future research should
include subjects with various levels of educational
attainment.
• In the original Triandis model, social factors, affect, and
perceived consequences affect actual behavior through
the formation of behavioral intention; therefore,
behavioral intention should be included in future studies.
• The limitation of using self-reported measures of usage
is that method variance may contribute in part to the
correlation between two constructs.
31
Whether the paper is related to the MIS
field
• Facilitating conditions must be considered completely to
improve the ERP system implement and design in the
organization.
• Using this extended Triandis model may further predict
the usage of the system.
32
The contributions found in the paper
• Because the complexity factor have the discourage
effect to many other factors, companies should seriously
care about whether the system is easy to use when they
construct or buy a new system.
• Using the near-term consequences and long-term
consequences factors to evaluate a product whether its
capability is significant in short time or its capability is
significant on a long time. Therefore, we can use the two
factors to analyze customers’ purchase desire. For
instance, if the performance can appear immediately,
sometimes customers may have more desire to buy the
product.
33