Hung Et Chang_2005

8/14/2019 Hung Et Chang_2005

1/12

User acceptance of WAP services: test of competing theories

Shin-Yuan Hung*, Chia-Ming Chang

Department of Information Management, National Chung Cheng University, 160 San-Hsin Village, Ming Hsiung, Chia-Yi, Taiwan, ROC

Available online 4 November 2004

Abstract

Although wireless application protocol (WAP) service acceptance has long attracted considerable interest, the problem of

identifying the best theoretical model among the various prevalent models has been relatively neglected. Recently, a few

studies have attempted to examine this issue using the decomposed TPB model. It is rare for one model to be superior to all of

the other models in all criteria. WAP service acceptance involves competition among three well-established theoretical models,

as follows: the Technology Acceptance Model (TAM), the Theory of Planned Behavior (TPB), and the decomposed TPB

model. This study compares the effectiveness of these three models in understanding WAP services acceptance. Empirical data

were obtained from a field survey in Taiwan. Notable findings were reported for the three competing models, as follows: (1)

TPB and decomposed TPB are superior to TAM in terms of their ability to explain user acceptance of WAP services and (2)

while the decomposed TPB model provided more easily understood and managerially relevant factors, the TPB model was

more parsimonious and had very similar explanatory power to the decomposed TPB model. Finally, the implications of thisstudy are discussed.

D 2004 Elsevier B.V. All rights reserved.

Keywords: Wireless application protocol; Technology Acceptance Model; Theory of Planned Behavior; Decomposed Theory of Planned

Behavior; Information technology acceptance

1. Introduction

Wireless application protocol (WAP) service accept-

ance is crucial for WAP survival in the highlycompetitive mobile commerce market. WAP is partic-

ularly one of widespread technical standards to extend

Internet technologies to wireless networks. Since 1997,

Ericsson, Motorola, Nokia, and Unwired Planet have

taken the initiative to found the WAP Forum [25,26].

WAP has become an open, global specification,

enabling mobile users with wireless devices to easily

and instantly access and interact with information andservices [27]. Among the general public, WAP should

be held in very high esteem, owing to support from

numerous key industry players. However, problems for

low usage of WAP services do exist[17,21,24]. Clearly,

user acceptance is required for ensuring productivity

payoffs from any investments in IT services [10,19,23].

Thus, from a pragmatic perspective, WAP service

acceptance needs to be explored.

0920-5489/$ - see front matterD 2004 Elsevier B.V. All rights reserved.

doi:10.1016/j.csi.2004.10.004

* Corresponding author. Tel.: +886 5 2720411x34601; fax:

+886 5 2721501.

E-mail address: [email protected] (S.-Y. Hung).

Computer Standards & Interfaces 27 (2005) 359370

www.elsevier.com/locate/csi

8/14/2019 Hung Et Chang_2005

2/12

One of numerous approaches for WAP services

involves assessing which model is best for under-

standing user acceptance. Early studies, focused on

examining WAP service acceptance, mostly exploredthe influence of critical factors on user acceptance. For

example, Teo and Pok [24] or Hung et al. [17] both

adopted similar approaches. However, previous studies

neglected to examine whether this model is the best

among the previous theoretical models. To consider

analysis build on the individual level and the WAP

services acceptance unit requires examining three

competing theoretical models, namely: the Technology

Acceptance Model (TAM) [10,11], the Theory of

Planned Behavior (TPB) [2,4,5], and the decomposed

TPB model [23].Simultaneous testing of competing theoretical mod-

els offers a helpful approach to understanding user

acceptance of WAP services. Numerous similar exam-

ples of testing simultaneously competing models exist.

For example, Mathieson [19] found that TPB is

superior to TAM in its ability to predict behavioral

intention. Professional healthcare provides another

example. Chau and Hu [8] found that TAM or TPB is

more limited in its explanatory ability [8]. Another

example has demonstrated that the three models (TAM,

TPB, Decomposed TPB model) are roughly equivalent

[23]. All these examples make it clear that (1)

simultaneous testing of competing models is a well-

established approach and (2) each theoretical model

has its own distinct advantages.

Having decided to adopt the simultaneous test

approach, it is beneficial to clarify the similarity and

differences among three competing models. Compar-

ison of the three theoretical models reveals the

following two similarities: (1) all three are intention-

based theoretical models and are grounded from social

psychology; (2) each one provides an appropriate

perspective for understanding individual IT serviceacceptance. Notable differences among the three

competing models include the following: (1) TAM,

proposed by Davis [10], is an adaptation of the Theory

of Reasoned Action (TRA) [3]; TPB extends the TRA

to explain behavioral conditions not entirely under

volitional control [2,4,5]; the decomposed TPB model

deconstructs belief structures of TPB into several

factors [23]; (2) to represent the antecedents of user

acceptance, TAM focuses on two factors, perceived

usefulness and ease of use [10,11]; TPB stresses the

influence of perceived behavioral control beliefs on

behavioral intention and actual behavior [2,5]; the

decomposed TPB model focuses on identifying various

beliefs factors that influence three determinants ofintention (namely attitude, subjective norm and per-

ceived behavioral control). Decomposition of belief

sets can identify more stable, easily understood, and

managerially relevant factors [23].

This investigation compares the three competing

models in terms of the extent to which they can be used

to better clarify user acceptance of WAP services. This

study uses overall model fit, explanatory power and

path significance to assess and compare models using

structural equation modeling (SEM). This investigation

established a sampling frame with the assistance ofseveral Taiwanese telecom companies and collected

data using a systematic sampling method. Empirical

self-reported data were obtained from 267 voluntary

users. Users indicate individuals that have registered in

the database of telecom companies and have heard of

WAP services, as well as those with actual use

experience.

The remainder of this study is organized as follows.

Section 2 reviews the related literature, especially the

literature on WAP and the three competing theoretical

models. Next, Section 3 describes the research

method. Meanwhile, the analytical results are reported

in Section 4. Finally, Section 5 discusses the results,

presents conclusions, and indicates the implications of

the study findings.

2. Literature review

2.1. WAP services

In mobile commerce, WAP is just one of many

competing technical standards. Competitors to WAPinclude GPRS, 3G, etc. In 1997, an industry organ-

ization known as the WAP Forum was established to

devise technical standards for bridging the gap between

mobile and Internet networks. Forum members include

Ericsson, Motorola, Nokia, and several key industry

players [25,26]. The development of WAP brought the

wireless world closer to the Internet via a set of

specifications based on technologies that improve the

experience of wireless users [26,27]. In technical

improvement, various newly released features include

S.-Y. Hung, C.-M. Chang / Computer Standards & Interfaces 27 (2005) 359370360

8/14/2019 Hung Et Chang_2005

3/12

Push Services, User Agent Profile, WDP Tunneling,

WMLscript, CryptoLibrary, Wireless Telephony

Application, Wireless Application Environment, Mul-

timedia Message Service, Pictogram, etc. [26,27].However, support from key industry players and

technical improvements have not altered the problem

of lower user acceptance.

The Greater China economic region is a rapidly

growing market for WAP services. Numerous western

telecommunications enterprises are extremely inter-

ested in providing wireless services in Shanghai,

Hong Kong, Taipei, etc. Since these cities largely

share a common culture and language, the analytical

results and conclusions may provide a good reference

for global telecommunication enterprises to use inestablishing a development strategy for their far

eastern operations. Because of the importance of this

region, some previous studies of WAP services

acceptance have also focused on this area, including

Hung et al. [17] who investigated in Taiwan, and Teo

and Pok [24] who focused on Singapore.

2.2. Competing theories

The application of theoretical models to under-

stand user acceptance of any new IT services is a

well-established approach. Pursuing numerous theo-

retical models, for considering the analysis unit and

level of each theoretical model, three models

(namely TAM, TPB, and the Decomposed TPB

model) have been applied to examine the individual

acceptance of new IT services and suitable for WAP

services. The features of each theoretical model are

presented as follows.

2.2.1. Technology Acceptance Model (TAM)

TAM is a very powerful and parsimonious model

for explaining and predicting much of the variancein new IT acceptance [10,11]. TAM is an adaptation

of the Theory of Reasoned Action (TRA) [13].

TAM has the following features:

(1) TAM excludes the influence of social norm and

perceived behavioral control on behavioral

intention.

(2) Two belief factors (perceived usefulness and

perceived ease of use) determine attitude

towards behavioral intention.

(3) Behavioral intention is directly affected by

perceived usefulness and attitude.

(4) Through two beliefs factors, numerous external

factors (i.e., system design characteristics, usecharacteristics, facilitating support, training, etc.)

can affect behavioral intention.

(5) Two belief factors are easy to understand and

manipulate in information system design and

implementation.

(6) The use of self-reported measurements may

cause low ability to predict actual behavior [11].

2.2.2. Theory of Planned Behavior (TPB)

TPB extends the TRA to consider perceived

behavioral control for reflecting user perceptions

regarding possible internal and external constraints

on behavior [2,5]. TPB emphasizes that behavior

includes non-volitional aspects under certain circum-

stances. Some TPB features and early study results are

described as follows:

(1) TPB includes the possible influence of perceived

behavioral control on behavioral intention and

actual behavior.

(2) Behavioral intention and perceived behavioral

control can directly affect behavior.

(3) Attitude and perceived behavioral control both

determine behavioral intention.

(4) In the early IT implementation phase, the factor

(subjective norm) is important for users with

limited direct experience [16].

(5) Monolithic belief sets in TPB may be inconsis-

t e nt l y r el a te d t o t h e t h re e d e te rm in a nt s

of intention and thus may be difficult to opera-

tionalize [23].

2.2.3. Decomposed Theory of Planned Behaviormodel (Decomposed TPB model)

The decomposed TPB model is created by Taylor

and Todd [23]. This model is focused on decom-

posing three sets of belief structures into a multi-

dimensional belief construct. The advantages of this

model include: (1) representing clear, easily under-

stood, and stable sets of beliefs; (2) easily oper-

ationalizing these beliefs; (3) focusing on more

managerially relevant beliefs, rather the two factors

proposed in TAM [23].

S.-Y. Hung, C.-M. Chang / Computer Standards & Interfaces 27 (2005) 359370 361

8/14/2019 Hung Et Chang_2005

4/12

A variety of early investigations [8,9,11,19,23] have

compared competing theoretical models. These pre-

vious works have demonstrated that tests among these

models have no consistent results. For example,Mathieson [19] found that TAM is superior to TPB

for predicting behavioral intention to use spreadsheet

packages. Taylor and Todd [23] observed that decom-

posed TPB is superior to TPB and TAM in under-

standing behavioral intention. For professional

workers, Chau and Hu [8] proposed that TAM is

superior to TPB for explaining behavioral intention.

The findings of these studies highlight the need to

develop simultaneous tests of these competing models

for user acceptance of new IT services.

3. Research method and design

3.1. Measures and pretests

Regarding instrument construction, the items used

to operationalize the constructs of each investigated

variable were mainly adopted from relevant previous

studies, with validation and wording changes as

necessary (see Table 1). Specifically, measures of

perceived usefulness and ease of use were adapted

from Davis [10], measures of user satisfaction adapted

from Doll and Torkzadeh [12], measures of personal

innovativeness adapted from Agarwal and Prasad [1],

and measures of subjective norms, perceived behav-

ioral control, and attitudes were derived from Taylor

and Todd [23]. Furthermore, measures of behavioral

intention were derived from both the above sources.

Additionally, constructs shared by different investi-

gated models were measured using the same items. All

items were measured on a seven-point Likert-type scale

with anchors ranging from bstrongly agreeQ tobstrongly disagreeQ. Appendix A lists the items used

to measure each variable. To achieve the desired

balance and randomness in the questionnaire, half of

the items were worded with proper negation and all

items in the questionnaire were randomly sequenced

to reduce the potential ceiling (or floor) effect, which

induces monotonous responses to the measures of a

particular construct. Furthermore, the final question-

naire was validated by two professional translators to

ensure no syntax and semantic errors during the

translation from English to Chinese. Appendix Acontains the questionnaire used in this study.

To ensure data validity and reliability, this study

first pre-tested the questionnaire through review by

several consumers and telecommunication professio-

nals. Following final survey administration, analysis

of the responses of 25 random respondents found the

survey design free of problems. Regarding reliability,

the survey exhibited strong internal consistency, with

all multiple-item constructs achieving Cronbachs

alpha of 0.73 or higher. Moreover, regarding validity,

previously validated measurements were used to

ensure the measurement validity. Factor analysis was

conducted to clarify convergent and discriminant

validity, after which all factors were extracted that

had an eigenvalue N1.0 and all items displayed

loading 0.63 or higher on their respective factors.

3.2. Survey respondents

Two-hundred and sixty-seven survey respondents

were usable data. Only 50 respondents had actual

experience of using WAP services. A large proportion

of the respondents had only heard of WAP services buthad not used them. While such respondents were

considered usable respondents in the data analysis, the

representativeness of such data is questionable. The

authors were conscious of this problem before data

collection. To avoid this problem, during the research

design phase, two supplementary works were consid-

ered, as follows:

(1) The sampling frame is built with the assistance

of several telecommunication companies. Thus,

Table 1

Research variables and measurements

Construct Source

User satisfaction Doll and Torkzadeh [12]

Personal innovativeness Agarwal and Prasad [1]

Ease of use Davis [10]

Usefulness Davis [10]

Peer influence Taylor and Todd [23]

External influence Taylor and Todd [23]

Self-efficacy Taylor and Todd [23]

Facilitating condition Taylor and Todd [23]

Attitude Taylor and Todd [23]

Subjective norm Taylor and Todd [23]

Perceived behavior control Taylor and Todd [23]

Intention Taylor and Todd [23]


8/14/2019 Hung Et Chang_2005

5/12

all survey respondents are registered WAP

users.

(2) To check the understanding of respondents of

WAP services, this study added the questionsbHave ever heard of the following mobile

services: (1) WAP, (2) GPRS, (3) 3G, (4) GSM, Q

to the first part of questionnaire. All survey

respondents had heard of WAP services and other

competing options.

3.3. Statistical analysis

This investigation used the structural equation

modeling (SEM) for hypotheses testing. Following

the two-stage approach proposed by Anderson andGerbing [6], data from 267 samples was analyzed in

two stages. First, the measurement model was

estimated using confirmatory factor analysis to test

whether the constructs possessed sufficient validation

and reliability. To ensure data validity and reliability,

internal consistency, convergent validity, and dis-

criminant validity were demonstrated. Second, the

structural model that best fitted the data was

identified, and then the hypotheses were tested.

SEM has been identified as an appropriate cova-

riance-based approach in studies with a strong basis

on a priori theory [18,7]. This study is well suited

for confirmatory testing of the fit of the proposed

theoretical model to observed data using SEM.

This study chose AMOS for windows (version

4)as the SEM software for model estimation.

AMOS is a covariance-based approach similar to

LISREL, in which the covariance structure obtained

from the observed data is used to simultaneously fit

measurement and structural equations specified in

the model. AMOS estimated both the measurement

and structural models using the full information

maximum likelihood estimator.

3.4. Data collection and sample representativeness

Using a systematic sampling method, 500 ques-

tionnaires were mailed to individuals. Initially, the

questionnaires were mailed to respondents who were

given 15 days to respond. After 15 days, follow-ups

were sent to the non-respondents. Following a

further 10-day wait, responses were solicited from

remaining non-respondents via telephone.

Of the 280 returned questionnaires, 13 were

excluded due to incomplete answers, leaving 267

usable responses (profiled in Table 2). The response

rate thus was 53.4%, comparing favorably with similarmail surveys.

The chi-square goodness-of-fit test was used to test

whether the sample data ratio, including WAP users

and non-users, derived from the population with a

specific distribution. The results indicated that this

sample was representative of the WAP user popula-

tion of Taiwan (v2=0.11, p=0.745). Furthermore, this

study also tested for response bias between the

responses and non-responses using the independent

sample t-test. The analytical results demonstrated no

significant differences among the respondent andnon-respondent groups in terms of gender, age,

education level, annual income, and marriage status.

Thus, no response bias existed in this study.

4. Results

4.1. Measurement model results

Following the two-step approach suggested by

Anderson and Gerbing [6], the first stage measures

Table 2

Profile of the respondents

Variable Count Percentage

Gender Male 166 62.2

Female 101 37.8

Age b20 years old 10 3.7

2130 years old 132 49.4

3140 years old 90 33.7

4150 years old 32 12.0

N50 years old 3 1.1

Education Junior high school 2 0.7

Senior high school 26 9.7Bachelor 209 78.3

Master or above 30 11.2

Annual income b NT$240,000 44 16.5

NT$240,000NT$480,000 108 40.4

NT$480,000NT$720,000 85 31.8

NT$720,000NT$960,000 20 7.5

N NT$960,000 10 3.7

Marriage status Single 155 58.1

Married 112 41.9

WAP use Non-users 217 81.3

Users 50 18.7

US$ 1cNT$34.90.


8/14/2019 Hung Et Chang_2005

6/12

8/14/2019 Hung Et Chang_2005

7/12

variance in attitude, and 44% of the variance in

perceived usefulness.

4.4. Model 2the Theory of Planned Behavior

As indicated in Fig. 2, most path coefficients were as

hypothesized. The path from perceived behavioral

control to intention unexpectedly was insignificant.

Fig. 2 also showed that the TPB model can explain 11%

of the variance in WAP service use and 38% of the

variance in behavioral intention. The path coefficient

(0.107) between perceived behavioral control and

use indicated that perceived behavioral control signifi-

cantly suppresses actual WAP services use.

4.5. Model 3The Decomposed TPB

Fig. 3 showed that the decomposed TPB model

explains 12% of the variance in WAP services use, 38%

of the variance in behavioral intention, 54% of the

variance in attitude, 63% of the variance in subjective

norm, and 52% of the variance in perceived behavioral

control. This figure exhibited the same significant path

as the TPB model in Fig. 2. For example, in these two

models, the path from perceived behavioral control tointention is insignificant. Additionally, through the

decomposing approach used in this model, the follow-

ing observations can be made:

(1) For attitude, connection speed, user satisfaction,

personal innovativeness, and two factors (per-

ceived usefulness and ease of use) are significant

determinants of attitude towards WAP services.

Meanwhile, the path from current service costs

(usage charge) to attitude is insignificant.

(2) For subjective norm, the significant determi-

nant is peer influence, while the path fromexternal influence to subjective norm is insig-

nificant.

(3) Self-efficacy is a significant determinant of

perceived behavioral control. In comparison,

the path from facilitating condition to perceived

behavioral control is insignificant.

From comparison of three competing models, the

following discussions demonstrate how each model

provides understanding of user acceptance of WAP

services.

5. Discussion and conclusions

This study performs a model comparison among

three competing theoretical models (TAM, TPB,

Decomposed TPB model) for explaining user accept-

ance of WAP services. In terms of overall model fit

criteria, all models provide comparable fit to the data,

with a few exceptions. Consequently, by comparing the

models with one another, reflections on comparative

findings in the Results section clarify that:

(1) The comparative results in the explained variance

of use demonstrate that TPB and decomposed

TPB model have better explanation ability than

TAM (R2=0.12 for decomposed TPB, R2=0.11

for TPB, R2=0.08 for TAM). However, explan-

ation ability is low for all three models. The

possible reasons of low explanation ability are

that: (a) Self-reported measures of WAP services

use. Some empirical studies [11,22,23] have

Fig. 1. Results of TAM model.


8/14/2019 Hung Et Chang_2005

8/12

pointed this method problem. For example, Davis

et al. [11] reports that the explained variance of

self-reported IT usage is just 12%. Szajna [22] or

Taylor and Todd [23] both emphasize self-

reported measures problem. (b) Training or direct

usage experience. For example, owing to actual

usage experience over a 15-week period in the

study of Szajna [22], the explained variance of

usage increases from 8% to 32%.

(2) In all models, behavioral intention is the neces-

sary precursor to use of WAP services, and in the

decomposed TPB and TPB models, perceived

behavioral control is an additional precursor of

use. Ajzen [2,5] suggested that the link between

Fig. 3. Results of the decomposed TPB model.

Fig. 2. Results of TPB model.


8/14/2019 Hung Et Chang_2005

9/12

perceived behavioral control and use is actual

control rather than perceived control. Addition-

ally, the improvement in explained variance of

use by considering perceived behavioral controlwas small. Consequently, actual use of WAP

services is a relatively straightforward task and is

affected mainly by attitude and subjective norm

rather than perceived behavioral control.

(3) Regarding the explanatory power of behavioral

intention among three models, both models (TPB

and decomposed TPB) exhibit the same explan-

ation ability (R2=0.38), TAM reveal lower

explanation ability (R2=0.32). Thus, in terms of

behavioral intention, both the decomposed TPB

and TPB models can provide better understand-ing of intentions than TAM in WAP services.

(4) In terms of the determinants of behavioral

intention, one similarity of three models is that

behavioral intention is directly influenced by

attitude. To consider attitude, all three models are

suitable for explaining WAP service acceptance.

To consider the role of subjective norm in WAP

services acceptance, TPB and the decomposed

TPB are superior to TAM. To consider simulta-

neously two determinants (attitude and perceived

usefulness), TAM is the best choice. Additionally,

in TPB or decomposed TPB, the path from

perceived behavioral control to intention is

insignificant. More research needs to be con-

ducted to examine this path in WAP service

setting.

(5) Regarding the ability to explain attitude, TAM

predicted attitude towards WAP services better

than the decomposed TPB model (R2=0.58 for

TAM and R2=0.54 decomposed TPB model).

Good evidence exists that TAM is more parsimo-

nious [11] and provides a more efficient method

of assessing individual attitude regarding WAPservices.

(6) In terms of determinants of attitude towards

WAP services, the decomposed TPB model has

its advantage. By contrast, the decomposed

TPB model indicates connection speed, user

satisfaction, personal innovativeness, and two

factors in TAM (perceived usefulness and ease

of use) are significant determinants of attitude,

while TAM indicates just perceived usefulness

is significant determinant. To consider approach

to affecting attitude, the decomposed TPB

model provides more easily understood and

managerially relevant information to guide

WAP services design efforts. Additionally,regarding the determinants of subjective norm

or perceived behavioral control, the decom-

posed TPB model is also superior to the other

two models. From this model, peer influence

can directly affect subjective norm and self-

efficacy can directly influence perceived behav-

ioral control. Consequently, in WAP service

setting, the decomposed TPB model can pro-

vide leverage points to guide WAP services

design efforts. The implications for WAP

service design are that peer referents opinionshave priority over external media advisements,

and individual self-efficacy precedes facilitating

resources.

Finally, interpreting the results of this is limited by

the fact that the study was conducted in Taiwan.

Although the cultural and linguistic similarities exist

within the Greater China economic region, threats to

external validity of this investigation in Taiwan cannot

be avoided. The current study suggests that further

research should be anticipated to further extend the

population of WAP service users to the Greater China

economic region. This study could be also expanded in

the other direction. Although this investigation has

argued that modeling WAP service acceptance is

appropriate based on the three competing theories, it

is also important to extend current research to clarify

why WAP users either continue or discontinue using

WAP services. Additionally, longitudinal research

conducted in field settings is also necessary because

technical and environmental changes of WAP services

take place over time.

Acknowledgment

The authors would like to thank the National

Science Council (NSC) of the Republic of China,

Taiwan under Contract No. NSC 90-2416-H-194-

0 32 a nd t he M in is tr y o f E du ca ti on ( MO E)

Program for Promoting Academic Excellence of

Universities under grant number 91-H-FA08-1-4 for

their financial support.


8/14/2019 Hung Et Chang_2005

10/12

Gender (1) Male (2) Female

Age (1) 20 or less (2) 2130 (3) 3140 (4) 4150 (5) 51 or aboveEducation (1) Junior high school (2) Senior high school (3) Bachelor (4) Master or above

Annual Income (thousand NT dollars) (1) 239 or less (2) 240480 (3) 480720 (4) 720960 (5) 961 or above

Marriage status (1) Single (2) Married

Computer experience (years) (1) 1 or less (2) 23 (3) 45 (4) 67 (5) 8 or above

Average times you use WAP services in a week (1) None (2) 1 or less (3) 24 (4) 57 (5) 8 or above

Item Rating scale

Extremely

Likely

Quite

Likely

Slightly

Likely

Neither Slightly

Unlikely

Quite

Unlikely

Extremely

Unlikely

Connection speed

I would accept current connection speed of WAP services.

Usage cost

I would accept current charge for WAP services.

User satisfaction

The WAP services provide the precise information I need.

The information content of the WAP services meets I need.

The WAP services provide reports that seem to be just about

exactly what I need.

The WAP services provide sufficient information.

Personal innovativeness

I am generally cautious about accepting new ideas.

I find it stimulating to be original in my thinking and behavior.

I am challenged by ambiguities and unsolved problems.

I must see other people using innovations before I will considerthem.

Ease of use

Learning to use WAP services would be easy for me.

I would find it easy to gather information using WAP services.

It would be easy for me to become skillful at using WAP services.

I would find WAP services easy to use.

Usefulness

Using WAP services would improve my performance in gathering

information.

Using WAP services would improve my productivity in gathering

information.

Using WAP services would enhance my effectiveness in gathering

information.

I would find WAP services useful in gathering information.Peer influence

My peers/colleagues/friends thought that I should use WAP

services for gathering information.

People I knew thought that using WAP services was a good idea.

People I knew influenced me to try out WAP services for gathering

information.

External influence

I read/saw news reports that using WAP services

was a good way of gathering information.

The popular press depicted a positive sentiment for using

WAP services.

Mass media reports influenced me to try out WAP services.

Appendix A. The Questionnaire

Please indicate your agreement with the next set of statements using the following rating scale.


8/14/2019 Hung Et Chang_2005

11/12

References

[1] R. Agarwal, J. Prasad, A conceptual and operational

definition of personal innovativeness in the domain of

information technology, Information Systems Research 9 (2)

(1998) 204215.

[2] I. Ajzen, From intentions to actions: a theory of planned

behavior, in: J. Kuhl, J. Beckmann (Eds.), In Action Control:

From Cognition to Behavior, Springer Verlag, New York, 1985,

pp. 1139.

[3] I. Ajzen, M. Fishbein, Understanding Attitudes and PredictingSocial Behavior, Prentice-Hall, Englewood Cliffs, NJ, 1980.

[4] I. Ajzen, Nature and operation of attitudes, Annual Review of

Psychology 52 (2001) 2758.

[5] I. Ajzen, The theory of planned behavior, Organizational

Behavior and Human Decision Processes 50 (2) (1991)

179211.

[6] J.C. Anderson, D.W. Gerbing, Structural equation modeling in

practice: a review and recommended two-step approach,

Psychological Bulletin 103 (3) (1988) 411423.

[7] A. Bhattacherjee, Acceptance of e-commerce services: the

case of electronic brokerages, IEEE Transactions on Systems,

Man, and Cybernetics 30 (4) (2000) 411420.

[8] P.Y.K. Chau, P.J.H. Hu, Information technology acceptance by

individual professionals: a model comparison approach,

Decision Sciences 32 (4) (2001) 699719.

[9] P.Y.K. Chau, P.J.H. Hu, Investigating healthcare professionals

decisions to accept telemedicine technology: an empirical test

of competing theories, Information and Management 39 (4)

(2002) 297311.

[10] F.D. Davis, Perceived usefulness, perceived ease of use, and

user acceptance of information technology, MIS Quarterly 13

(3) (1989) 319 340.

[11] F.D. Davis, R.P. Bagozzi, P.R. Warshaw, User acceptance ofcomputer technology: a comparison of two theoretical models,

Management Science 35 (8) (1989) 9821003.

[12] W.J. Doll, G. Torkzadeh, The measurement of end-user

computing satisfaction: theoretical and methodological issues,

MIS Quarterly 15 (1) (1991) 5 10.

[13] M. Fishbein, I. Ajzen, Belief, Attitude, Intention and Behavior:

An Introduction to Theory and Research, Addison-Wesley,

Reading, MA, 1975.

[14] C. Fornell, D.F. Larcker, Evaluating structural equation

model with unobservable variables and measurement

error, Journal of Marketing Research 18 (1) (1981)

3950.

Self-efficacy

I would feel comfortable using WAP services on my own.

I would be able to use WAP services reasonably well on my own.

I would be able to use WAP services even if there was no one around

to help me.

Facilitating conditions

Resources required to use WAP services were available to me.

I had access to hardware, software, and services needed to use

WAP services.

I was constrained by the lack of resources needed to use WAP services.

Attitude

Using WAP services would be a good idea.

Using WAP for gathering information would be a foolish idea.

I like the idea of using WAP services for gathering information.

Using WAP services would be a pleasant experience.

Subjective norm

People (peers and experts) important to me supported my use of

WAP services.People who influenced my behavior wanted me to use WAP

services instead of any alternative means.

People whose opinions I valued preferred that I use WAP services.

Perceived behavioral control

I would be able to use WAP services well.

Using WAP services was entirely within my control.

Intention

I intend to use WAP services in the near future

(i.e., next three months).

It is likely that I will use WAP services in the near future


I expect to use WAP services in the near future



8/14/2019 Hung Et Chang_2005

12/12

[15] J.F. Hair, R.E. Anderson, R.L. Tatham, W.C. Black, Multi-

variate Data Analysis, Prentice-Hall, Englewood Cliffs, NJ,

1998.

[16] J. Hartwick, H. Barki, Explaining the role of user participation

in information system use, Management Science 40 (4) (1994)

440465.

[17] S.Y. Hung, C.Y. Ku, C.M. Chang, Critical factors of WAP

services adoption: an empirical study, Electronic Commerce

Research and Applications 2 (1) (2003) 4260.

[18] K. Joreskog, D. Sorbom, LISREL 8: Structural Equation

Modeling with the SIMPLIS Command Language, Erlbaum,

Hillsdale, NJ, 1993.

[19] K. Mathieson, Predicting user intentions: comparing the

technology acceptance model with the theory of planned

behavior, Information Systems Research 2 (3) (1991) 173 191.

[20] J.C. Nunnally, I.H. Bernstein, Psychometric Theory, 3rd ed.,

McGraw-Hill, New York, NY, 1994.

[21] J. Pearce, WAP for web developers, 2000 http://archive.devx.com/wireless/articles/WAP/WAPjp112000.asp .

[22] B. Szajna, Empirical evaluation of the revised technology

acceptance model, Management Science 42 (1) (1996) 85 92.

[23] S. Taylor, P.A. Todd, Understanding information technology

usage: a test of competing models, Information Systems

Research 6 (2) (1995) 144176.

[24] T.S.H. Teo, S.H. Pok, Adoption of WAP-enabled mobile

phones among Internet users, Omega 31 (6) (2003) 483498.

[25] WAP Forum, Official Wireless Application Protocol, John

Wiley & Sons, New York, 1999.

[26] WAP Forum, WAP 2.0 technical white paper, 2002 http://

www.wapforum.org/what/WAPWhite_Paper1.pdf.

[27] Web Pro Forum, Wireless application protocol tutorial, 2004

http://www.iec.org/online/tutorials/wap/.

Shin-Yuan Hung is an Associate Profes-

sor of Information Systems, and the Head

of Division of Information Management

of Computer Center at National Chung

Cheng University. He holds a Ph.D. in

Information Systems from the National

Sun Yat-sen University. His current

research interests include decision support

systems, electronic commerce, and knowl-

edge management. Dr. Hung has pub-

lished a number of papers in Information

and Management, Decision Support Systems, Electronic Com-

merce Research and Applications, Information Technology and

People, Computer Standard and Interfaces, Industrial Management

and Data Systems, International Journal of Management Theory

and Practice, Journal of Chinese Information Management, among

others.

Chia-Ming Chang is a Doctoral Student in

the MIS program at the National Chung

Cheng University. He received his Masters

degree in MIS from the same university.

His current research interests include deci-

sion support systems, electronic commerce,

and user interface design. He has published

articles in Electronic Commerce Research

and Applications, Information Management

& Computer Security, Journal of Chinese

Information Management, and so on.

http://www.archive.devx.com/wireless/articles/WAP/WAPjp112000.asphttp://www.wapforum.org/what/WAPWhite_Paper1.pdfhttp://www.iec.org/online/tutorials/wap/http://www.iec.org/online/tutorials/wap/http://www.iec.org/online/tutorials/wap/http://www.archive.devx.com/wireless/articles/WAP/WAPjp112000.asphttp://www.wapforum.org/what/WAPWhite_Paper1.pdfhttp://www.wapforum.org/what/WAPWhite_Paper1.pdfhttp://www.iec.org/online/tutorials/wap/http://www.wapforum.org/what/WAPWhite_Paper1.pdfhttp://www.archive.devx.com/wireless/articles/WAP/WAPjp112000.asphttp://www.iec.org/online/tutorials/wap/http://www.wapforum.org/what/WAPWhite_Paper1.pdfhttp://www.archive.devx.com/wireless/articles/WAP/WAPjp112000.asp

Hung Et Chang_2005

Documents

Transcript of Hung Et Chang_2005