Adoption of WAP-enabled mobile phones among Internet users
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Available online at www.sciencedirect.com
Omega 31 (2003) 483 – 498
www.elsevier.com/locate/dsw
Adoption of WAP-enabled mobile phones among Internet
users
T.S.H. Teo∗ , Siau Heong Pok
Department of Decision Sciences, School of Business, National University of Singapore, 1 Business Link, Singapore 117 592, Singapore
Received 29 March 2002; accepted 8 August 2003
Abstract
This paper examines the attitudinal, social and perceived behavior control factors that are associated with the adoption of
WAP-enabled mobile phones among Internet users. An online questionnaire is used to gather data. The results show that
attitudinal and social factors rather than perceived behavioral control factors play a signi2cant role in in3uencing intentions to
adopt a WAP-enabled mobile phone. In particular, perceptions of relative advantage, risk, and image are found to in3uence
adoption intentions. In addition, reference groups too play an important role in shaping adoption intentions. Implications of
results and directions for future research are examined.
? 2003 Elsevier Ltd. All rights reserved.
Keywords: WAP; Wireless application protocol; Mobile phones; Adoption
1. Introduction global mobile phone penetration increased from 91 million
in 1995 to 1.16 billion in 2002 [3]. Research 2rms have
Wireless application protocol (WAP) is perhaps one of also predicted that all mobile phone shipped by mid-2001
the few technologies that comes close to emulating the suc- will be WAP-enabled [4]. By 2003, the number of mobile
cess of the Internet. Backed by the entire telecommunica- devices able to access the Internet will exceed the number
tion industry (through the WAP forum), coupled with the of PCs. The mobile phone will also likely become the stan-
fact that it combines two of the hottest innovations in recent dard device for e-commerce transactions with mobile com-
times (mobile phone and the Internet), WAP is poised to merce (m-commerce) revenue expected to reach more than
succeed the Internet as the next big thing. US$200 billion by the end of 2005 [5].
WAP is hot for several reasons. First, WAP provides a Despite the hype generated by WAP, i-mode, the wireless
standardized way to link the Internet to mobile phone, thus, technology pioneered by NTT Docomo, is thus far the only
linking two of the hottest sectors in the telecommunica- true demonstration of the potential of mobile Internet. With
tion industry [1]. Second, WAP receives widespread support more than 40 million subscribers, i-mode is a showcase to
from major players in the telecommunication industry. As the world on the many wonderful opportunities that existed
the result, in the matter of just 8 months (January–August within the wireless industry [6]. i-mode’s success has not
2000), the number of WAP pages grew from almost zero just fueled the expectations of industry players but also that
to 4.4 million pages. The rate of growth is much faster than of consumers. Together with the constant barrage of adver-
the initial growth of Web pages, which grew from zero to tisements from WAP content providers and telecommunica-
only about one million pages in 8 months [2]. tion service providers, the expectation of WAP has reached
Thus, it came as no surprise when many analysts and a dizzying height. The great hype has turned into great hope
market research 2rms painted a rosy future for WAP. The for consumers so much so that it has now reached a stage
of relative oversell [4].
∗ Tel.: +65-687-43-036; fax: +65-677-92-621. As a result, early adopters of WAP-enabled devices
E-mail address: bizteosh@nus.edu.sg (T.S.H. Teo). (mainly mobile phones) experience cognitive dissonance
0305-0483/$ - see front matter ? 2003 Elsevier Ltd. All rights reserved.
doi:10.1016/j.omega.2003.08.005484 T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498
which fuels the market with criticism on the new wireless innovation’s perceived characteristics, the individual’s at-
protocol. Worse still, telecommunication service providers titude and beliefs, and communication received by the in-
have wrongfully associated WAP with the GSM net- dividual from his/her social environment. Of the proposed
work in their marketing campaign. Thus, early adopters factors by Rogers, relative advantage, complexity (ease of
of WAP-enabled devices have blamed WAP for its slow use) and compatibility were consistently related to adoption
mobile Internet access speed, further tarnishing the im- decisions [9].
age of WAP. With the announcement of General Packet Theory of reasoned action (TRA):
Radio Service (GPRS) and 3rd Generation (3G) networks TRA (Fig. 1) is based on the proposition that an individ-
arrival in the near future, potential adopters have adopted ual’s actual behavior is determined by the person’s intention
a wait-and-see attitude in the adoption of WAP-enabled to perform the behavior, and this intention is in3uenced
devices in the near term. jointly by the individual’s attitude and subjective norm.
Singapore, with its excellent telecommunications infra- Taylor and Todd [10] de2nes attitude as “an individual
structure, has what it takes to succeed in mobile Internet. positive or negative feeling towards performing the target
With a mobile phone penetration rate of 79.7% and an Inter- behavior” (p. 149). A person’s attitude towards a behavior is
net penetration rate of 49% in May 2003 [7], Singapore is an in turn determined by salient beliefs about the consequences
ideal site for our study which examines the factors associated of that behavior and the evaluation of the desirability of the
with the adoption of WAP-enabled mobile phone among consequences [11]. Beliefs are de2ned as the “individual’s
Internet users. Our results will be useful to practitioners in subjective probability that performance of a given behavior
the telecommunication industry who can then better decide will result in a given consequence”. Subjective norm is de-
on appropriate policies to encourage adoption. Researchers 2ned as “the person’s perception that most people who are
will also 2nd the results useful in determining whether sim- important to him think he should or should not perform the
ilar factors that aKect the adoption of other innovations are behavior in question” [12].
also associated with the adoption of WAP-enabled mobile TRA also theorizes that an individual’s subjective norm
phones. is determined by a multiplicative function of his or her nor-
mative beliefs, i.e., perceived expectations of speci2c ref-
erence individuals or groups, and his or her motivation to
2. Literature review comply with these expectations. To conclude, TRA asserts
that any other factors that in3uence behavior do so through
In general, there exist several technology diKu- indirectly in3uencing attitude, subjective norm or their rela-
sion/acceptance models such as innovation diKusion theory, tive weights. These will include factors like user character-
theory of reasoned action (TRA), technology acceptance istics, system design and task characteristics, etc.
model (TAM) and theory of planned behavior (TPB) that Technology acceptance model (TAM):
may be used to examine the adoption of WAP-enabled The technology acceptance model (TAM) is an adaptation
mobile phones. In the following paragraphs, we examine of the theory of reasoned action (TRA) [10]. It speci2es
the various diKusion models that provide the background to two beliefs, perceived ease of use and perceived usefulness
our research model. as determinants of attitude towards usage intentions and IT
Innovation di4usion theory: usage [13]. TAM (Fig. 2) departs from TRA in two ways:
The innovation diKusion process can be conceptualized 2rst, subjective norm is excluded as a determinant of usage
as a chronological sequence of events through which an in- intention and secondly, a direct path exists from perceived
dividual passes from initial knowledge of an innovation, to usefulness to usage intention [10].
forming a favorable or unfavorable attitude toward it, to a Perceived usefulness is de2ned as the degree to which
decision to either adopt or reject it, to utilizing the innova- “a person believes that use of the system will enhance his
tion, and to 2nally seeking reinforcement of the adoption or her performance”. Perceived ease of use is de2ned as the
decision made [8]. Key elements in the entire process are the degree to which “a person believes that using the system
Attitudinal Beliefs Attitude
and Evaluations
Behavioral
Behavior
Intention
Normative Beliefs
and Motivation Subjective Norm
to Comply
Fig. 1. Theory of reasoned action.T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498 485
Perceived
Usefulness
Behavioral Behavior
Attitude
Intention
Perceived Ease
of Use
Fig. 2. Technology acceptance model.
Attitudinal Beliefs Attitude
and Evaluations
Normative Beliefs Behavioral
Subjective Norm Behavior
and Motivation Intention
to Comply
Control Beliefs
Perceived Behavioral
And Perceived
Control
Facilitation
Fig. 3. Theory of planned behavior.
will be free of eKort” [12]. According to TAM, usefulness Behavioral intention is formed by one’s attitude, subjective
and ease of use will have a signi2cant impact on a user’s at- norm and perceived behavioral control which re3ects per-
titude toward using the system, de2ned as feelings of favor- ceptions of internal and external constraints on behavior
ableness or unfavorableness toward the system. Behavioral (Ajzen, 1991). Both subjective norm and perceived behav-
intention to use the system is modeled as a function of at- ioral control have been found to have a signi2cant in3uence
titude and usefulness. Behavioral intention then determines on IT usage behavior (e.g. [16–20]). The following diagram
actual usage behavior. (Fig. 3) depicts the relationship in the TPB model:
Davis et al. [13] also state that all other factors not expli- Decomposed theory of planned behavior:
citly included in the model are expected to impact intentions The decomposed TPB (Fig. 4) draws upon constructs
and usage through perceived ease of use and usefulness. from the innovation diKusion literature, and more com-
These are the same external variables encountered in TRA. pletely explores the dimensions of attitude, subjective norm
In addition, Davis found that perceived ease of use acts pri- and perceived behavioral control by decomposing them into
marily through perceived usefulness to in3uence intentions speci2c belief dimensions [10].
to use. In summary, TAM theorizes that a technology that is As a model for research, decomposed TPB oKers several
easy to use, and is found to be particularly useful will have advantages over the other models. First, it has been noted
a positive in3uence on the intended user’s attitude and in- that it is unlikely that monolithic belief structures (found
tention towards using the technology. Correspondingly, the in TPB), representing a variety of dimensions will be con-
usage of the technology increases [10]. sistently related to the antecedents of intention [21,22]. In
Theory of planned behavior (TPB): addition, decomposed TPB faces fewer problems in oper-
The theory of planned behavior (TPB) is another variant ationalization as decomposition has provided a stable set
of the theory of reasoned action [11,14] made necessary by of beliefs which can be applied across a variety of settings
the original model’s limitation in dealing with behaviors in [23]. Moreover, by focusing on speci2c beliefs, the model
which people have incomplete volitional control [15]. To becomes more managerially relevant, pointing to speci2c
overcome the inadequacy, an additional factor, perceived factors that may in3uence adoption and usage. Last but not
behavioral control is added as a determinant of attitude and least, decomposed TPB, compared to TAM, is a better model
behavior. for the understanding of IT usage though both models shared
TPB holds that behavioral intention and perceived be- many similarities [10]. This is because decomposed TPB has
havioral control are direct determinants of actual behavior. incorporated several factors (such as in3uence of signi2cant486 T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498
Perceived
Usefulness
Ease of Use Attitude
Compatibility
Peer Influence
Behavioral Behavior
Subjective Norm
Intention
Superior’s Influence
Self Efficacy
Recourse Perceived
Facilitation Behavioral Control
Technology
Facilitation
Fig. 4. Decomposed theory of planned behavior.
others) that were found to be important determinants of be- With the availability of the Internet almost instanta-
havior [15], thus providing a more complete understanding neously at the users’ 2ngertips, users can easily access
of IT usage relative to TAM. Hence, we decided to adapt applications such as PIM (Personal Information Man-
the decomposed theory of planned behavior as our research agement), calendaring and scheduling. As such, with
model. In doing so, we are testing the model in a new con- WAP-enabled mobile phone, users can better manage
text (i.e., WAP adoption) to examine its generalizability as their daily lives. Finally, through WAP-enabled mobile
WAP and mobile commerce diKers from traditional systems phone, users can easily customize the Internet services
in that mobile devices are ubiquitous, portable and can be to suit their personal needs [26]. Though devices such
used to conveniently receive and disseminate personalized as PC and laptop oKer such facilitation, mobile phone
information [24]. remains an ideal device for personal services. This is be-
cause the probability of a person sharing his/her mobile
phone is de2nitely much lower compared to that of a PC
3. Research model and hypotheses terminal or laptop. In view of the advantages oKered by
WAP-enabled mobile phones, we propose the following
To derive the research model (Fig. 5), it is necessary to hypothesis:
decompose attitude, subjective norm and perceived behav- H1 : Relative advantage is positively associated with at-
ioral control into various belief dimensions. titude.
3.1. Attitudinal beliefs
3.1.2. Ease of use
3.1.1. Relative advantage Complexity represents the degree to which an innovation
Relative advantage refers to the degree to which adopting is perceived to be diOcult to understand, learn or operate
an innovation is perceived as being better than using the [8]. It is analogous to the “ease of use” construct in TAM
practice it supersedes. The most common advantage oKered [27]. In this research, the term “ease of use” is used instead
by WAP-enabled mobile phone over any other devices (such of “complexity”. It has being widely reported in the media
as notebook) capable of Internet access is its portability [25]. that sur2ng the Internet from a WAP-enabled mobile phone
The portability of the mobile phone made it possible for is itself a tedious task. Navigating current text-based mi-
consumers to access Internet services anyplace, anywhere crobrowser is diOcult [28]. Together with the small screen
and anytime. size (which supports only four- or eight-line of monochromeT.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498 487
Relative Advantage
H1
Ease Of Use
H2
Image H3
Attitude
H4
Compatibility
H5
H10
Risk
Significant Others H61 Subjective Norm H11 Behavioral
Intention
Self Efficacy H12
H7
H8 Perceived
Government Behavioral Control
H9
Mobile Operator
Fig. 5. Research model.
text) and the external miniaturized keypad, the overall usage 3.1.4. Compatibility
experience may be less than desired. Compatibility is the degree to which the innovation 2ts
In trying to resolve this issue, manufacturers of mobile with the potential adopter’s existing values, previous experi-
phones face the paradox of having to include user-friendly ences and current needs [8]. In the context of WAP-enabled
features without compromising the size of the phone [4]. mobile phone, a person’s lifestyle will strongly in3uenced
Several technologies such as voice recognition and touch his/her decision to adopt the technology. A person whose
screen are in the pipeline to improve usage experience. How- lifestyle revolves around the Internet will more likely
ever, the current situation will yet remain unchanged until a adopt WAP-enabled mobile phone since wireless Inter-
time when these new proposed technologies become com- net is in fact an extension of the Internet. Thus, a person
mercially viable. Thus, we propose the following hypothesis: who frequently access Internet activities such as Internet
H2 : Perceived ease of use is positively associated with banking may have less inhibitions adopting the wireless
attitude. version of Internet banking using a WAP-enabled mobile
phone.
3.1.3. Image In addition, a person who leads a busy life such that
Image can be de2ned as the degree to which the use of an he/she is always on the move, will be more likely to
innovation is perceived to enhance one’s image or status in adopt a WAP-enabled mobile phone compared to one
one’s social system [8]. It is likely that mobile phone may who leads a sedentary lifestyle. This follows that since
be, at present, more of a lifestyle product than a product of he/she is on the move all the time, accessing the In-
necessity. This fact has not been lost to mobile manufactur- ternet using a WAP-enabled mobile phone may be
ers. For instance, Motorola has identi2ed four user groups a better alternative compared to the bulky notebook.
when designing its mobile phones. They are the trend-setters, Moreover, a sedentary person who has ready access
the time manager, the technology enthusiasts and the social to the Internet through a PC either at home or of-
connectors [29]. Nokia, in the same capacity, has phones 2ce will 2nd mobile Internet less appealing. It follows
that target either young users (Nokia 3310) or fashion- and that:
image-conscious users (Nokia 8850 and Nokia 8250). Like- H4 : Compatibility is positively associated with attitude.
wise, the use of WAP-enabled mobile phone is often as-
sociated with certain social image. It is believed that early 3.1.5. Risk
adopters of WAP-enabled mobile phone are either trendy or Perceived risks can be de2ned as either the psychosocial
technology savvy [1]. Thus, if one wants to be associated risks or risks in general that are attributed to a product and/or
with the above groups, the following hypothesis will apply: its performance [30]. Psychosocial risks refer to purchasers’
H3 : Image is positively associated with attitude. concerns about other people opinions of using the item.488 T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498 It appears that two newer and better technologies (GPRS of tasks (e.g., accessing a Web site) rather than re3ect- and 3G) will eventually replace WAP. GPRS is currently ing simple component skills such as keying in the Web available while 3G is currently undergoing testing and its address. impending arrival has already been publicized to potential Several recent studies have found evidence of a rela- WAP-enabled mobile phone adopters by the over-zealous tionship between self-eOcacy and the adoption of high media. technology products [35] and innovations [36]. A person Comparison between WAP with either GPRS or 3G often with high self-eOcacy should be one that will more likely results in WAP being labeled as the inferior technology. adopt a technological innovation compared to one with low For instance, one such negative review suggests that current self-eOcacy [37]. Therefore, the following hypothesis is WAP-enabled phones will not support the fastest transfer proposed: rates of upcoming GPRS [25]. As such, we can assume H7 : Self-e
T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498 489
They are attitude, which describes a person’s perception as we are examining WAP-enabled mobile phones which
towards a WAP-enabled mobile phone; subjective norm, facilitate mobile Internet. Second, the Internet oKers the
which describes the social in3uence that may aKect a per- ability to easily reach out to potential respondents. Third,
son’s intention to adopt a WAP-enabled mobile phone; and by using programming tool such as Java Script, the in-
perceived behavioral control, which describes the beliefs tegrity of the data collected can be assured with in-built
about having the necessary resources and opportunities to data validation checks. Fourth, the cost of using the Internet
adopt the WAP-enabled mobile phone. In the context of is low compared to other data collection tools [40]. Fifth,
the framework, intention to adopt WAP-enabled mobile data from the electronic survey is automatically captured
phone is thus the dependent variable, while the indepen- in a database so that data need not be re-entered manu-
dent variables comprise attitude, subjective norm, and ally. This saves time and helps to eliminate errors of data
perceived behavioral control. Hence, the direct eKects of entry.
attitude, subjective norm and perceived behavioral control In using the Internet to administer the survey, we must
on behavioral intention will be tested by the following consider two major issues. With the Internet, there could be
hypotheses: anonymity as respondents could use pseudonyms for their
H10 : Attitude is positively associated with behavioral in- email addresses. Anonymity itself is actually a double-edge
tention. sword; without fear of revealing their identity, respondents
H11 : Subjective norm is positively associated with behav- may be forthcoming in answering the survey. However, the
ioral intention. system may be subjected to abuse if a respondent provides
H12 : Perceived behavioral control is positively associated multiple responses. This is a valid threat in the context of
with behavioral intention. this research as a mobile phone is oKered as a lucky draw
reward for participation in the online survey. To overcome
this threat, we removed responses that are either duplicates
4. Method (where respondents accidentally pressed the “Sent” button
twice) or responses where we detected deliberate fraud (for
This section provides an overview of the data collec- example, multiple responses in succession that have identi-
tion process. First, we describe the instrument used to mea- cal data in almost every 2eld but have diKerent email ad-
sure the constructs. Second, we discuss the issues and con- dresses).
cerns involving the use of the Internet as a tool for data The self-administrative nature of online survey is the
collection. second issue in contention. According to the Social Ex-
change Theory by Dillman [41], we act only when we
4.1. Instrument perceive the rewards to be greater than the costs of the
action. With regards to online survey, the major “costs” in
Items assessing various constructs are adapted from contention will be the time taken to complete the survey
past research as shown in Table 1. Note that to measure and the risk of revealing personal email address. Hence,
behavioral intention, respondents were asked to indicate in view of the above, we have taken precaution to ensure
the likelihood of them adopting a WAP-enabled mobile that the survey is both bearable and easy to complete.
phone in the next 6, 12 and 18 months. We adopted Further, we have tried to adhere to the guidelines pro-
the weights (3/6: 6 months, 2/6: 12 months, 1/6: 18 months) posed by Dillman et al. [42] to design a satisfactory online
similar to Tan and Teo’s [39] work. Thus, the summation survey.
of the responses multiplied by their respective weights Pre-testing was conducted to identify de2ciencies in
would produce a score representative of the behavioral the questionnaire design. The 2rst round of pre-testing
intention. was conducted on ten undergraduate Internet users (5
Most constructs are measured using a seven-point males, 5 females). Based on feedback, minor changes
Likert-type scale ranging from (1) strongly disagree to (7) were made to improve the clarity of the questions and
strongly disagree. Demographic data pertaining to gender, layout of the survey. The next round of pre-testing was
age, highest education, ethnic group, current profession and conducted on two working young adult Internet users
monthly income are also captured. (one male and one female). As there were no major
problems, the questionnaire was deemed ready for data
4.2. Using the Internet for data collection collection.
To overcome the perceived cost of participating in the
An online survey on the Internet is used for data col- online survey, a Nokia 3310 mobile phone is oKered as a
lection for the following reasons. First, using the Internet prize in a lucky draw for survey participants. The survey
to collect data 2ts well with the main objective of the re- was targeted at Internet users and publicized in newsgroups,
search i.e. to solicit information on factors in3uencing the personalized emails and forums. In addition, survey partici-
adoption of WAP-enabled mobile phone among Internet pants were promised an executive summary of the research
users. Note that the population sample is Internet users 2ndings.490 T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498
Table 1
List of constructs indicators
Construct Source
Behavioral intention
b01 If you are given the opportunity to adopt WAP-enabled
mobile phone, how likely would you adopt it in the next 6
months
b02 If you are given the opportunity to adopt WAP-enabled Taylor and Todd [10]
mobile phone, how likely would you adopt it in the next
12 months
b03 If you are given the opportunity to adopt WAP-enabled
mobile phone, how likely would you adopt it in the next
18 months
Attitude
a01 Using a WAP-enabled mobile phone is a good idea
a02 Using a WAP-enabled mobile phone is a wise idea Taylor and Todd [10]
a03 I like the idea of using a WAP-enabled mobile phone
a04 Using the WAP-enabled mobile phone would be pleasant
Subjective norm
n01 People who in3uence my behavior would think that I should Taylor and Todd [10]
use a WAP-enabled mobile phone
n02 People who are important to me would think that I should
use a WAP-enabled mobile phone
Perceived behavioral control
p01 I would be able to use a WAP-enabled mobile phone
p02 Using a WAP-enabled mobile phone is entirely within my Taylor and Todd [10]
control
p03 I have the knowledge and the ability to make use of the
WAP-enabled mobile phone
Relative advantage
adv01 Using WAP-enabled mobile phone enables me to better
manage my daily activities
adv02 WAP-enabled mobile phone can be con2gured to meet my
needs
adv03 WAP-enabled mobile phone oKers me personalized services
adv04 Using WAP-enabled mobile phone enables me to have ac- Mackenzie and O’Loughlin [1], Moore and Benbasat [19],
cess to timely information and services Siew [25], and IDA [26]
adv05 WAP-enabled mobile phone’s portability makes it an ideal
Internet sur2ng tool
Perceived ease of use
e01 I believe that WAP-enabled mobile phone is cumbersome
to use (R)
e02 I believe that it is easy to get WAP-enabled mobile phone Moore and Benbasat [19]
to do what I want it to do
e03 Overall, I believe that sur2ng the Internet using
WAP-enabled mobile phone is easy
e04 Learning to operate WAP-enabled mobile phone is easy for
me
Image
i01 Using WAP-enabled mobile phone improves my image
i02 People who use WAP-enabled mobile phone are IT savvy
i03 People who use WAP-enabled mobile phone are trendy Moore and Benbasat [19]
i04 Only young people use WAP-enabled mobile phone
i05 People who use WAP-enabled mobile phone have more
prestigeT.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498 491
Table 1 (continued)
Construct Source
Compatibility
v01 Using WAP-enabled mobile phone 2ts well with my
lifestyle
v02 I think that using WAP-enabled mobile phone 2ts well with Moore and Benbasat [19]
the way I live my life
v03 Using WAP-enabled mobile phone is completely compati-
ble with my current situation
v04 Using WAP-enabled mobile phone is compatible with all
aspects of my lifestyle
Risk
r01 I believe I will need to upgrade my WAP-enabled phone
constantly
r02 There exist newer technologies that can easily replaced Mackenzie and O’Loughlin [1]
WAP
r03 Current WAP-enabled mobile phone will become obsolete
soon
r04 WAP will be replaced by newer technology in the near
future
Signi:cant others
o01 My decisions to adopt WAP-enabled phone will be in3u-
enced by my Family members
o02 My decisions to adopt WAP-enabled phone will be in3u- Taylor and Todd [10]
enced by my friends
o03 My decisions to adopt WAP-enabled phone will be in3u-
enced by my colleagues/peers
E492 T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498
Table 2
Demographic pro2les of respondents
Newsgroup/forum Email Percent Chi-square
No. % No. %
Gender df = 1
Male 439 74.8 300 70.6 73.0 chi-sq = 2:2
Female 148 25.2 125 20.4 27.0 p = 0:14
Ethnic group
Chinese 551 93.9 390 91.8 93.0
Malay 13 2.2 10 2.4 2.0 df = 4
Indian 13 2.2 11 2.6 2.0 chi-sq = 3:6
Eurasian 2 0.3 5 1.2 1.3 p = 0:46
Others 8 1.4 9 2.1 1.7
Age
Under 15 5 0.9 7 1.7 1.2
15 –19 106 18.1 101 23.8 20.5
20 –24 274 46.7 211 49.7 47.9
25 –29 114 19.4 64 15.1 17.6 df = 8
30 –34 45 7.7 26 6.1 7.0 chi-sq = 23:2
35 –39 23 3.9 8 1.9 3.1 p = 0:003
40 – 44 13 2.2 5 1.2 1.8
45 – 49 7 1.2 0 0.0 0.7
Over 50 0 0.0 3 0.7 0.2
Highest education
Primary 8 1.4 9 2.1 1.7
Vocational institute 8 1.4 7 1.7 1.5
‘O’ Level 90 15.3 68 16.0 15.6
‘A’ Level 123 21.0 100 23.5 22.0 df = 8
Diploma 140 23.9 102 24.0 23.9 chi-sq = 7:3
Degree 185 31.5 120 28.2 30.1 p = 0:40
Postgraduate diploma 13 2.2 5 1.2 1.8
Masters 16 2.7 14 3.3 3.0
Doctorate 4 0.7 0 0.0 0.4
Current profession
Student 248 42.3 207 48.7 45.0
Part-time employee 14 2.4 7 1.7 2.1
Full-time employee 248 42.3 156 36.7 39.9
Home-maker 2 0.3 1 0.2 0.3 df = 7
Self-employed 20 3.4 11 2.6 3.1 chi-sq = 7:6
Retiree 2 0.3 1 0.2 0.3 p = 0:37
NSF 46 7.8 32 7.5 7.7
Unemployed 7 1.2 10 2.4 1.6
Income per month
Less than S$1500 147 25.0 121 28.5 26.5
S$1501 ∼ S$2999 153 26.1 111 26.1 26.1
S$3000 ∼ S$4499 69 11.8 25 5.9 9.3 df = 7
S$4500 ∼ S$5999 26 4.4 10 2.4 3.6 chi-sq = 18:4
S$6000 ∼ S$7499 12 2.0 7 1.7 1.9 p = 0:01
S$7500 ∼ S$8999 0 0.0 2 0.5 0.2
More than S$9000 8 1.4 4 0.9 1.2
No income 172 29.3 145 34.1 31.2
response samples (Table 2). The samples diKer signi2cantly The demographic pro2le in Table 2 indicates that respon-
from one another in both the age and income categories. As dents were predominantly young people from the age group
such, the samples are analyzed separately. of 20 –29 years (89%). This is slightly higher than 64.1%T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498 493
reported by Tan and Teo [39]. Further, comparing the two Table 3
samples revealed that email sample is made up of relatively Construct validity
younger respondents from the age group of 15 –24 (75.06% Constructs Loadings Cronbach Items
versus 65.59%). alpha eliminated
In addition, the respondents were mainly Chinese
(93.0%). Also, male is the dominant gender group (73.0%) Attitude 0.78– 0.85 0.84 —
in this research where females made up only 27.0%. More- Subjective norm 0.93 0.85 —
over, respondents with at least a junior colleague certi2cate PBC 0.80 – 0.89 0.81 —
Relative advantage 0.76 – 0.84 0.83 adv01,
or polytechnic diploma made up 81.2% of the respondents.
adv05
The respondents were also asked to indicate their current EOU 0.68– 0.83 0.79 e04
profession. Majority of the respondents are either students Image 0.64 – 0.85 0.82 —
(45.0%) or working professionals (39.9%). Compatibility 0.80 – 0.82 0.92 —
Last but not least, data about respondents’ income indicate Risk 0.83– 0.85 0.81 r04
that the majority of the respondents may be relatively new Signi2cant others 0.82– 0.91 0.86 —
in the workforce given that majority of them have monthly Government 0.80 – 0.81 0.86 —
income of less than S$3000 (52.6%). Further comparison Mobile operator 0.79 – 0.83 0.89 —
between the two samples highlighted the fact that news- Self eOcacy 0.88– 0.95 0.94 —
group/forum sample has a higher proportion of respondents
whose monthly income exceed S$3000 per month (19.58
versus 11.29). The disparity in income distribution, in con-
junction with the existence of age gap between the sam- Table 4
Composite reliability analysis
ples, signi2es that the newsgroup/forum sample may have a
higher proportion of older respondents. Constructs Reliability Items eliminated
Attitude 0.83 a04
5.2. Structural equation modeling Subjective norm 0.86 —
Perceived behavioral control 0.81 —
The entire SEM process centers around two events: val- Relative advantage 0.83 —
idating the measurement model and 2tting the structural Ease of use 0.80 —
model. The measurement model speci2es how the latent Image 0.85 i04, i05
Compatibility 0.84 —
variables are measured in terms of their observed indica-
Risk 0.89 —
tors. In addition, it also de2nes the indicators’ measurement
Signi2cant others 0.88
properties such as validity and reliability. On the other hand, Government 0.86 —
2tting the structural model involves path analysis with latent Mobile operator 0.90 —
variables. Self eOcacy 0.94 —
5.2.1. The measurement model
The measurement model speci2es which observed vari-
ables de2ne a construct. While construct validity analysis In addition, we used composite reliability to evaluate the
ensures that the indicator items are actually measuring the reliability of the construct indicators. Hair et al. [45] sug-
latent variables as proposed in the research model, reliabil- gested that the composite reliability should be greater than
ity analysis ensures that the indicators are consistent [44]. 0.70. As the composite reliabilities of constructs in the initial
Before running AMOS, the various constructs were model are mostly above 0.80, they are deemed acceptable
tested for validity using principal component analysis with (Table 4).
varimax rotation. Several items were dropped due to cross
loadings and remaining items loaded on a single factor. In 5.2.2. Estimation and :t criteria
addition, reliability analysis was carried out using Cronbach For SEM, it is a common practice to evaluate the
alpha which is a measure of internal consistency. The results model using a few goodness-of-2t measures to assess the
indicate that all constructs are valid and reliable (Table 3). model in terms of model 2t and model parsimony. The
Next, using AMOS, we examine the individual indica- Goodness of Fit Index (GFI) measures the percent of
tor’s standardized loading (i.e. standardized estimates) and observed covariances explained by the covariances im-
test it for statistical signi2cance (to test if the estimate is plied by the model and should be equal to or greater than
signi2cantly diKerent from zero). Subsequently, we exam- 0.90 to accept the model [46,47]. The adjusted good-
ine the items’ R2 . Items that either fail to pass the statistical ness of 2t index (AGFI), is adjusted for the degrees
test or have R2 smaller than 0.4 are eliminated due to low of freedom of a model relative to the number of vari-
loading and explanatory power. ables and should be above 0.80 [48,49]. The root mean494 T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498
residuals (RMR) measures the residual variance of the ob- The rejection of H4 for the newsgroup/forum sample
served variables and how the residual variance correlates (newsgroup=forum = 0:11, p ¿ 0:05) suggests the lack of as-
with the residual variance of the other items. A RMR value sociation between compatibility and attitude. However, H4
of less than 0.05 will be ideal. is supported for the email group (email = 0:34, p ¡ 0:05).
Root Mean Square Error of Approximation (RMSEA) Since the email group tends to be younger and more tech-
measures the discrepancy per degree of freedom. Hu and nologically savvy, they may 2nd WAP-enabled phones
Bentler [50] suggested 0.06 as the cutoK point for a good compatible with their lifestyles.
2t. The Bentler–Bonett normed 2t index (NFI) compares Next, signi2cant others’ (H6 : newsgroup=forum = 0:87,
the existing model 2t with a null model which assumes the p ¡ 0:05; email = 0:90, p ¡ 0:05) positive association with
latent variables in the model are uncorrelated. NFI should be subjective norm is found to be statistically signi2cant for
above 0.90. Chi-square, though part of the 2t indices, is not both samples. This suggests that respondents tend to seek
an ideal indicator of good 2t when the sample size is large. information from their reference groups.
As chi-square measures the diKerences between the observed Findings for H7 (newsgroup=forum = 0:75, p ¡ 0:05;
model and the perfect-2t model, any tiny diKerences found email = 0:84, p ¡ 0:05) suggest positive association be-
in a large sample may be deemed signi2cant thus resulting tween self-eOcacy with perceived behavioral control in
in a Type II error [47]. both samples. The high s indicates that self-eOcacy
weights heavily on perceived behavioral control. In con-
5.2.3. The structural model trast, 2ndings for H8 (newsgroup=forum = 0:19, p ¡ 0:05;
In this research, the newsgroup/forum group (n1 = 587) email = 0:08, p ¿ 0:05) and H9 (newsgroup=forum = 0:10,
was chosen as the calibration sample while the email group p ¿ 0:05; email = 0:15, p ¡ 0:05) suggest that the associ-
(n2 = 425) formed the validation sample. The calibration ations between government’s facilitation and mobile oper-
sample was used to test and modify the initial hypothesized ator’s facilitation with perceived behavioral control diKer
model while the validation sample was used to test the re- between samples.
vised model [51]. The rejection of mobile operator’s facilitation by
The hypothesized model (Fig. 6a) was 2rst tested based the newsgroup/forum sample indicates that the current
on the newsgroup/forum sample using the maximum likeli- WAP-enabled mobile phone’s packaging by the mobile
hood estimation (MLE). The model yields GFI (0.90), AGFI operators fails to arouse the interest of the older respon-
(0.88), NFI (0.92) and RMSEA (0.04) which are within the dents. The signi2cant association between government’s
accepted values. facilitation and perceived behavioral control in the news-
Cross-validation ensures that the model does not just 2t group/forum sample suggest that this group (being older
the calibration dataset but is general enough to be applica- and more cautious) looks to the government for possible di-
ble across diKerent datasets. In this research, a tight cross rection on whether it is worthwhile to adopt this technology.
validation approach was used where all parameters obtained In addition, the hypothesized relationships between be-
from the newsgroup/forum sample were 2xed for the email havioral intention with attitude (H10 : newsgroup=forum = 0:21,
sample. The model (Fig. 6b) scored highly in GFI (0.88), p ¡ 0:05; email = 0:30, p ¡ 0:05) and subjective norm
AGFI (0.85), NFI (0.89) and RMSEA (0.05) indicating its (H11 : newsgroup=forum = 0:22, p ¡ 0:05; email = 0:28,
generalizability. p ¡ 0:05) are found to be statistically signi2cant. This
indicates that consumers’ intention towards adopting a
5.3. Hypotheses testing WAP-enabled mobile phone is positively related to their
attitude and subjective norm.
The standardized coeOcients for each path closely ap- The rejection of H12 ( newsgroup=forum = 0:10, p ¿ 0:05;
proximate the eKect magnitude usually shown by beta email = 0:07, p ¿ 0:05) highlighted perceived behavioral
weights in regression. Thus low coeOcients have limited control has little eKect on respondents’ adoption inten-
substantive eKect [45]. In Figs. 6a and b, supportive 2nd- tions. As perceived behavioral control is heavily in3uenced
ings for H1 (newsgroup=forum = 0:26, p ¡ 0:05; email = 0:31, by self eOcacy (as evidence in the high relative the
p ¡ 0:05), H3 (newsgroup=forum = 0:28, p ¡ 0:05; email = 0:30, other variables), perceived behavioral control’s rejection
p ¡ 0:05), H5 (newsgroup=forum = − 0:17, p ¡ 0:05; email = could mean that despite the in3uence of external factors,
−0:27, p ¡ 0:05) in both samples suggest an association respondents may perceive the adoption of WAP-enabled
of relative advantage, image and risk with attitude (towards mobile phone as a trivial matter which is entirely within
the WAP-enabled mobile phone). their control. On the whole, the model explains 10.6%
Findings for H2 (newsgroup=forum = 0:22, p ¡ 0:05; and 17.2% of the variance in behavioral intention in the
email = 0:02, p ¿ 0:05), suggest positive association be- newsgroups/forums and emails samples, respectively. One
tween perceived ease of use with attitude for the news- possible reason for the relatively low variance values is
group/forum sample but not the email sample. Since the that there are newer technologies such as GPRS and 3G
email group tends to be younger, they may be more IT-savvy that are likely to supersede WAP. Further, users may need
and hence less concerned about perceived ease of use. to pay extra to use the various mobile applications enabledT.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498 495
Relative Advantage
0.26* GFI: 0.90
EOU AGFI: 0.88
0.22* NFI: 0.92
RMSEA: 0.04
Image 0.28* n2: 587
Attitude
0.11
Compatibility
-0.17*
0.21*
Risk
Significant Others H1
0.87* Subjective Norm 0.22* BI
Self Efficacy 0.10
0.75*
Government 0.19* PBC
0.10
Mobile Operator
(a)
Relative Advantage
0.31*
EOU GFI: 0.88
AGFI: 0.85
0.02 NFI: 0.89
Image RMSEA: 0.05
0.30* n2: 425
Attitude
0.34*
Compatibility
-0.27*
0.30*
Risk
Significant Others H1
0.90* Subjective Norm 0.28* BI
Self Efficacy 0.07
0.84*
Government 0.08 PBC
0.15*
Mobile Operator
(b)
Fig. 6. (a) Structural model (newsgroup/forum sample). (b) Structural model (email sample).
by WAP. Consequently, users may adopt a “wait and see” normative factor, but not perceived behavioral control fac-
attitude and hope that costs decrease over time before they tors. In previous adoption studies, attitude has also been
intend to use WAP-enabled phones. found to be a determinant of behavioral intention [10,13,18].
The attitudinal factors that are found to have signi2cant in-
3uence on behavioral intention in both samples are relative
6. Discussion advantage, social image and perceived risk. Compatibility
is found to have signi2cant in3uence only in the email
The 2ndings show that intention to adopt a WAP-enabled sample whereas perceived ease of use is found to have
mobile phone is associated with attitudinal factors and signi2cant in3uence only in the newsgroup/forum sample.496 T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498 The support for relative advantage is expected since past studies [17,18]. One possible explanation could be that literature has consistently showed that it has a signi2cant potential users view the decision to adopt a WAP-enabled and positive in3uence on the adoption of new innovations mobile phone as a personal and trivial matter that is within [9,52]. In the same vein, social image is expected to have a their own control boundary. signi2cant in3uence on attitude [8,9,53]. Mobile phone has Of the perceived behavioral control beliefs, government since evolved to become a lifestyle product so much so that facilitation is signi2cant for the newsgroup/forum sample the possession of a particular brand/model projects a certain while mobile operator’s facilitation is signi2cant for the image [29]. Likewise, perceived risk is expected to have a email sample. One possible explanation is that since govern- signi2cant in3uence on attitude. This 2nding re3ects similar ment’s facilitation (through IDA) is directed at the mobile results reported in other innovation adoption studies [30,39]. Internet industry as a whole, its eKect on younger individu- Though past research has shown that perceived com- als is not that prominent compared to mobile operators who patibility of an innovation has a positive in3uence on tends to target the young. the adoption of an innovation [9,54], the 2ndings for the Self eOcacy is expected to have a signi2cant in3uence newsgroup/forum sample prove otherwise. One possible on perceived behavioral control. This is consistent with the explanation could be that the current promotional eKorts 2ndings of previous studies [35,36,39], which found that for WAP-enabled mobile phones target explicitly at the self-eOcacy has a signi2cant eKect on intention to adopt young and technologically savvy group. Thus, this group new innovations. may view the WAP-enabled mobile phone as being com- plementary to their lifestyle. As such, newsgroup/forum sample, with relatively older respondents, may tend to view 7. Limitation WAP-enabled mobile phone as being complimentary to their lifestyle to a lesser extent. The main limitation is that the use of online survey re- Conversely, the lack of support for perceived ease of use stricts us to a pool of Internet users as respondents. Hence, in the Email group is in contrast with previous 2ndings the results obtained may not be generalizable to non-Internet [54–56], which indicated that the more complex an innova- users and the general public. However, the sample of In- tion is to use, and the greater the skill and eKort needed to ternet users may be a better representation of potential adopt it, the less likely that it will be adopted. The news- WAP-enabled mobile phone adopters than non-Internet group/forum group’s perception of WAP-enabled mobile users. This assumption is made on the basis that a per- phone’s ease of use may be shaped by the recent spate son will more readily adopt mobile Internet (through a of negative reports published in the media. As a result, WAP-enabled mobile phone) when he has experienced the WAP-enabled mobile phone’s ease of use has a signi2cant bene2ts of the Internet. in3uence on their adoption intentions. Hence, this group will adopt WAP-enabled mobile phone only when their percep- tion of WAP-enabled mobile phone’s ease of use improves. 8. Implications On the other hand, the email group, being younger and per- haps more technologically savvy, may not be overly in3u- The 2ndings in this research will facilitate practition- enced by the negative reviews reported in the media since ers in formulating measures to improve the diKusion of the desire to adopt a new technology may override any fears WAP-enabled mobile phones. For instance, WAP-enabled of the technology being diOcult to use. mobile phones should be marketed as a lifestyle product Like attitude, subjective norm has signi2cant in3uence on rather than a technological innovation since our 2ndings behavioral intention in both samples [13,18]. Hartwick and show that compatibility with one’s values, lifestyle and Barki [17] concluded in their research that subjective norm norms is positively associated with adoption intention. In- is an important determinant of behavioral intention espe- stead of focusing on the functionalities of a WAP-enabled cially in the early stages of the innovation diKusion cycle. In mobile phone, the marketing campaign should emphasize the early stages (as in WAP-enabled mobile phones), where the compatibility of WAP phones (and their assorted ser- information on the innovation may be incomplete, potential vices) with one’s lifestyle. In addition, practitioners may adopters have to rely on their referent groups for informa- consider using opinion leaders as spokesperson for their tion. Moreover, since its inception, WAP has received bad WAP-enabled mobile phones. Since image is found to have reviews from the media. Hence, potential adopters may turn a signi2cant eKect on adoption intention, portraying opinion to what they perceived as trusted information source (their leaders as WAP-enabled mobile phone users may improve referent groups) for second opinion before taking any con- the overall image of the WAP concept. crete actions towards adoption. The 2ndings have also suggested that potential adopters Perceived behavioral control is found to have an in- rely on reference groups for information on WAP-enabled signi2cant in3uence on behavioral intention to adopt a mobile phones. Given that no other external factors WAP-enabled mobile phone in both samples. This 2nd- (perceived behavioral control) are found to have any sig- ing is diKerent from the results reported in most adoption ni2cant eKect on behavioral intention further reinforces
T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498 497
the importance of referent groups in the adoption process. Third, the study of WAP-enabled mobile phone could
Working with the intuitive assumption that mobile Internet be extended to include other wireless devices such as per-
users should 2rst be users of the Internet, the importance sonal digital assistants (PDA) and tablet personal comput-
of cyber reference groups should not be neglected. Cyber ers (PCs). The wireless experience may be better enhanced
reference groups may be crucial in disseminating infor- with other modes of delivery. For instance, PDA, with a
mation to individuals. Since members of these groups are bigger screen and Web-friendly user interface, could be a
technologically more advanced than their peers, their opin- better alternative for mobile Internet access.
ions may go a long way in shaping the adoption intentions
of others by skewing their perceptions of WAP. Hence, it
will be prudent for practitioners to monitor such groups
References
to either correct any misconceptions about the technology
or gather feedbacks from this group to further fuel the
[1] Mackenzie M, O’Loughlin MA. WAP market strategies.
adoption process.
London: Ovum Ltd; 2000.
Mobile operators have always taken every opportunity to [2] The Straits Times. Tech & science—WAP’s up: page content.
promote the relative advantages of using a WAP-enabled 2000; September 18.
mobile phone in accessing the Internet over a 2xed terminal [3] International Telecommunication Union (ITU). Key glo-
such as PC. This is essential since our 2ndings have shown bal indicators for the world telecommunication service
that relative advantage has a signi2cant in3uence on adop- sector, 2003. http://www.itu.int/ITU-D/ict/statistics/at glance/
tion intention. However, without complementary mobile KeyTelecom99.html
applications, the promise of WAP-enabled mobile phone’s [4] WAPworkz. The truth about WAP: concept, business model
relative advantages is likely to be insuOcient. Thus, mobile and implementation strategy, 2000 (http://www.wapworkz.
operators and content providers should seek to deliver com- com/pdf/The%20Truth%20About%20WAP%20210800.pdf).
plementary applications to improve the adoption rate. These [5] Davison J, Walsh A, Brown D. As good as gold. Mobile Asia
Paci2c 2000;8(3):11–4.
applications must be 3exible enough to be personalized
[6] RatliK JM. NTT DoCoMo and its i-mode success: origins
to suit individual needs. In addition, the application must
and implications. California Management Review 2002;44(3):
oKer utmost convenience to the users. The ability to access 55–71.
the Internet anywhere, anyplace and anytime will only be [7] Info-Communications Development Authority of Singapore
useful if doing so serves a purpose such as meeting a spe- (IDA) 2003, Infocomm Facts and Figures 2003: Statistics on
ci2c time schedule. For example, potential adopters may Telecom Services for 2003, 2003. http://www.ida.gov.sg.
have no qualms buying movie tickets using a WAP-enabled [8] Rogers EM. DiKusion of innovations, 3rd ed. New York: The
mobile phone but will be less than enthusiastic when the Free Press; 1983.
object is changed to that of books. Though both activi- [9] Tornatzky LG, Klein KJ. Innovation characteristics and
ties are similar in nature, one (buying movie tickets for a innovation adoption implementation: a metal analysis of
particular show at a particular time slot) is more sensitive 2ndings. IEEE Transactions on Engineering Management
to time than the other. Thus, the convenience oKered by 1982;29(11):28–45.
WAP-enabled mobile phone will be much more appreciated [10] Taylor S, Todd PA. Understanding information technology
usage: a test of competing models. Information System
by the person buying movie tickets rather than the one buy-
Research 1995;6(2):144–76.
ing a book. Hence, from the above illustrations, we can see
[11] Fishbein M, Ajzen I. Belief, attitude, intention and behavior:
that selling the relative advantages of WAP-enabled mo- an introduction to theory and research. Reading, MA:
bile phone alone is not enough to entice potential adopters. Addison-Wesley; 1975.
The availability of complementary applications is equally [12] Dillon A, Morris M. User acceptance of information
important. technology: theories and models. Journal of the American
There are several directions for future research that this Society for Information Science 1996;31:3–32.
study facilitates. First, there may exist other factors that [13] Davis FD, Bagozzi RP, Warshaw PR. User acceptance of
could further explain potential adopter’s behavioral inten- computer technology: a comparison of two theoretical models.
tion towards the adoption of a WAP-enabled mobile phone. Management Science 1989;35:982–1003.
Second, the study of adoption intention could be extended [14] Ajzen I, Fishbein M. Understanding attitudes and predicting
to GPRS phones. Since the hype generated by WAP has social behavior. Englewoods CliKs, NJ: Prentice-Hall; 1980.
[15] Ajzen I. The theory of planned behavior. Organizational
fueled the expectations of GPRS, it will be interesting to
Behaviour and Human Decision Processes 1991;50:179–211.
compare the paths taken by these two seemingly similar in-
[16] Barclay D, Higgins C, Thompson R. The partial least square
novations in their respective adoption process. Like WAP, approach to casual modelling: personal computer adoption
GPRS is also being hyped up. The media has often labeled and use as an illustration. Technology Studies 1995;2(2):
GPRS as the savior of mobile Internet. An adoption study 285–309.
on GPRS phone in the near future will determine if GPRS [17] Hartwick J, Barki H. Explaining the role of user
truly lives up to its early promises or whether GPRS is just participation in information system use. Management Science
like WAP—a “spectacular” failure. 1994;40(4):440–65.498 T.S.H. Teo, S.H. Pok / Omega 31 (2003) 483 – 498
[18] Mathieson K. Predicting user intentions: comparing the [37] Compeau DR, Higgins CA. Computer self-eOcacy:
technology acceptance model with theory of planned behavior. development of a measure and initial test. MIS Quarterly
Information System Research 1991;2(3):173–91. 1995;19(2):189–211.
[19] Moore GC, Benbasat I. Development of an instrument [38] Gopinath S. What’s wrong with WAP? Computer Times 2000,
to measure the perceptions of adopting an information July 12:8.
technology innovation. Information System Research [39] Tan M, Teo TSH. Factors in3uencing the adoption of internet
1991;2(3):192–222. banking. Journal of the Associations for Information Systems
[20] Thompson RL, Higgins CA, Howell JM. Personal computing: 2000;1:1–44.
toward a conceptual model of utilization. MIS Quarterly [40] Witt KJ. Best practices in interviewing via the internet.
1991;15(1):125–43. Proceedings of Sawtooth Software Conference. Sequim,
[21] Bagozzi RP. Attitudes, intentions and behavior: a test of some Washington: Sawtooth Software, Inc.; 1998.
key hypotheses. Journal of Personality and Social Psychology [41] Dillman DA. Mail and telephone surveys: the total design
1981;41:607–27. method. New York: Wiley; 1978.
[22] Shimp T, Kavas A. The theory of reasoned action applied [42] Dillman DA, Tortora RD, Bowker D. Principles for
to coupon usage. Journal of Consumer Research 1984;11: constructing Web surveys, 1999 (http://survey.sesrc.wsu.
795–809. edu/dillman/papers/Websurveyppr.pdf).
[23] Berger I. A framework for understanding the relationship [43] Teo TSH, Yeong YD. Assessing the consumer decision
between environmental attitudes and consumer behaviors. In: process in the digital market place. Omega 2003;31(5):
Varadarjan R, Jaworski B, editors. Marketing theory and 349–63.
application, American Marketing Association, Chicago, IL, [44] Schumacker R, Lomax R. A beginner’s guide to structural
vol. 4, 1993. p. 157– 63. equation modelling. London: Lawrence Erlbaum; 1996.
[24] Siau K, Lim EP, Shen Z. Mobile commerce: promises, [45] Hair JF, Anderson RE, Tatham RL, Black WC. Multivariate
challenges, and research agenda. Journal of Database data analysis with readings, 5th ed. Englewood CliKs, NJ:
Management 2001;12(3) July–Sept: 4 –13. Prentice-Hall; 1998.
[25] Siew A. Not so wild after all: some connectivity [46] Gefen D, Straub DW, Boudreau M. Structural equation
issues and trends that will impact WAP services here. modelling and regression: guidelines for research practice.
Computer Times 2000; 14 (http://computertimes.asia1.com. Communications of the Association for Information Systems
sg/archive/2001-01-03/reviews/review10.htm). 2000;4:1–77.
[26] Info-communications Development Authority of Singapore, [47] Garson. PA 765: structural equation modeling, 2000
Infocomm Technology Roadmap (Broadband Access and (http://www2.chass.ncsu.edu/garson/pa765/structur.htm).
Mobile Wireless), 2000a, 22–51. [48] Chin WW, Todd PA. On the use, usefulness, and ease of use
[27] Davis FD. Perceived usefulness, perceived ease of use and of structural equation modeling in MIS research: a note of
user acceptance of information technology. MIS Quarterly caution. MIS Quarterly 1995;2(19):237–46.
1989;13(3):319–40. [49] Segars AH, Grover V. Re-examining perceived ease of use
[28] McCarthy A. The Forrester report: mobile Internet realities. and usefulness: a con2rmatory factor analysis. MIS Quarterly
Cambridge, MA: Forrester Research; 2000. 1993;4(17):517–25.
[29] Dawson S, Tan M. Get the one that best suits your lifestyle. [50] Hu L, Bentler PM. CutoK criteria for 2t indexes in
The Straits Time 2001, February 19. covariance structure analysis: conventional criteria versus new
[30] Bauer RA. Consumer behavior as risk taking. In: Hancock RS, alternatives. Structural Equation Modelling 1999;6(1):1–55.
editor. Dynamic marketing for a changing world. Chicago: [51] Crowley SL, Fan X. Structural equation modelling. In: Shinka
American Marketing Association; 1960. p. 389–98. J, Greene RL, editors. Emerging issues and methods in
[31] Triandis HC. Attitude and attitude change. New York: Wiley; personality assessment. Hillsdale, NJ: Lawrence Erlbaum;
1971. 1997. p. 285–308.
[32] Thompson RL, Higgins CA, Howell JM. In3uence of [52] Holak SL, Lehmann DR. Purchase intentions and dimensions
experience on personal computer utilization: testing a of innovation: an exploratory model. Journal of Product
conceptual model. Journal of MIS 1994;11(1):167–87. Innovation Management 1990;7:59–73.
[33] Karahanna E, Straub DW, Chervany NL. Information [53] Holloway RE. Perceptions of an innovation: syracuse
technology adoption across time: a cross-sectional comparison university project advance. Doctoral Dissertation, Syracuse
of pre-adoption and post-adoption beliefs. MIS Quarterly University, 1977 [unpublished].
1999;23(2):183–223. [54] Cooper RB, Zmud RW. Information technology
[34] Bandura A. Social foundations of thought and action. implementation research: a technological diKusion approach.
Englewood CliKs, NJ: Prentice-Hall; 1986. Management Science 1990;2(36):123–39.
[35] Hill T, Smith ND, Mann MF. Communicating innovations: [55] Dickerson MD, Gentry JW. Characteristics of adopters and
convincing computer phobics to adopt innovative non-adopters of home computers. Journal of Consumer
technologies. Advances in Consumer Research 1986;13: Research 1983;10:225–34.
419–22. [56] Moore GC. End user computing and oOce automation:
[36] Burkhardt ME, Brass DJ. Changing patterns or patterns a diKusion of innovations perspective. INFOR 1987;3(25):
of change: the eKects of a change in technology on 214–35.
social network structure and power. Administrative Science
Quarterly 1990;35(2):104–27.You can also read
