A Study of Web 2.0 Website Usage Behavior Using TAM 2

Mei-Ying Wu Han-Ping Chou Yung-Chien Weng Yen-Han Huang Department of Information Management, Chung-Hua University, HsinChu, Taiwan, Republic of China

meiying@chu.edu.tw

Abstract Web 2.0 is a new Internet platform that allows users to

build personalized content through participation and sharing. The technologies used and business opportunities brought by this new platform have impacted many conventional websites. This paper aims to explore the relationships among constructs in Technology Acceptance Model 2(TAM 2) and survey the general users’ acceptance of Web 2.0 websites. The proposed hypotheses are further tested by Structural Equation Modeling (SEM). Based on the obtained results, users’ acceptance of Web 2.0 websites and factors affecting their acceptance are discussed to provide a substantial reference for Web 2.0 website operators. Keywords: Web 2.0, Technology Acceptance Model 2(TAM 2), Structural Equation Modeling (SEM) 1. Introduction

The era of Web 2.0 has come! Having got rid of constraints of the dot-com crisis in 2000, website providers now allow users to express their subconscious mind, using text, video, graphic, and even sound to convey and share their ideas. The number of communication channels, from Wikipedia and Windows Live to the present Web 2.0 websites, is always on the increase.

The current Internet has been revolutionized. Internet users no longer rely on the information provided on the websites. Many portal sites are now cooperating with one another to create their own values. Web 2.0 is attractive because it is free-of-charge, democratic, and innovative. For service providers ready to enter the Web 2.0 market, Web 2.0 means more competition and also revolution. What they need to understand include the basic functions of a Web 2.0 website, factors affecting user acceptance and needs, how to market the website and increase popularity, and “human” is the essential factor that generates the

business opportunities. Hence, they need to know the real demands of users so as to enjoy the benefits and values of Web 2.0.

However, TAM 2 has been seldom applied to explore user acceptance of websites. Considering the positive impact of Web 2.0 on the Internet, this study will employ the framework of TAM 2 proposed by Venkatesh and Davis [17] to explore users’ intention to use and usage behavior of Web 2.0 websites, in hope of identifying the potential business opportunities in Web 2.0 and providing them as a reference for Web 2.0 website builders. 2. Literature review

The following is a review of literatures pertaining to TAM 2 and Web 2.0. 2.1 Technology acceptance model 2

In 2000, Venkatesh and Davis extended TAM to develop TAM 2(as shown in Figure 1) and added two new processes into this extended model: social influence processes (subjective norm, voluntariness, and image) and cognitive instrumental processes(job relevance, output quality, result demonstrability, and perceived usefulness).

2.1.1 Social influence processes

TAM 2 can reflect mainly the impact of subjective norm, voluntariness, and image. The interactive relationships among the three constructs and users are important factors in any innovative system. “Subjective norm” will directly influence intention to use. In other words, no matter one’s behavior is conducted out of personal preference, his/her technology usage behavior will be affected by the attitudes and belief of others in groups to which he/she belongs to. As to “voluntariness”, it was found in the research of subjective norm that usage of innovative systems could be divided into mandatory and voluntary. TAM 2 assumes voluntariness as an interfering

2008 IEEE Asia-Pacific Services Computing Conference

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2008 IEEE Asia-Pacific Services Computing Conference

978-0-7695-3473-2/08 $25.00 © 2008 IEEE

DOI 10.1109/APSCC.2008.92

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variable and defines that “a potential adopter’s decision of using an innovative system depends on voluntariness instead of obligation” [1, 6, 10]. Besides, “image” refers to the belief of a group important to an individual that a certain behavior should be implemented and implementation of this behavior by the individual can persistently enhance the quality of internal works of the organization [3, 7, 12].

2.1.2 Cognitive instrumental processes

In TAM 2, perceived usefulness is determined by four factors, including job relevance, output quality, result demonstrability, and perceived ease of use. “Job Relevance” refers to an individual’s perception regarding the degree to which the target system is applicable to his or her job. Job relevance is an important function, as it can evaluate whether the system is capable of supporting the task set by an individual. “Output Quality” is defined as “the degree to which one perceives the effectiveness of an innovative system”. It is an individual’s perception about how well the system performs certain tasks [9]. Besides, according to Moore and Benbasat [10], “Result Demonstrability” is “tangibility of the results using the innovation, which will directly influence perceived usefulness”.

From TAM, TAM 2 reserves “perceived ease of use” as

a direct determinant of perceived usefulness. If an innovative system can be used without any effort, it complies with the definition of perceived ease of use. Many studies have empirically revealed that perceived ease of use is an important link for intention to use. No matter directly or indirectly, it is influential to perceived usefulness [4, 16].

2.2 Web 2.0 Tim O’Reilly [11] who first introduced the concept of

Web 2.0 defined it as “a network as platform, spanning all connected devices”. He mentioned that Web 2.0 websites are not confined to any specific boundary. The development of Web 2.0 can be attributed to users, but it also relies on innovative technologies. These technologies include AJAX, RSS/Atom, Mashup, Ruby on Rails, LAMP, P2P, and many other transmission and integration techniques. All of these can broaden users’ usage of the Internet. They are being more and more extensively used and will bring the Internet to an innovative model.

So far, domestic studies of Web 2.0 are still rare, and so are the studies of TAM 2. Most of the related studies have been more focused on the factors affecting user acceptance or using TRA, TPB, and TAM related theories to explore user’s behavioral models. Website user behaviors have been seldom explored from the perspective of TAM 2.

S u b j e c t i v e n o r m

I m a g e

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O u t p u t q u a l i t y

R e s u l t d e m o n s t r a b i l i t y

P e r c e i v e d u s e f u l n e s s

P e r c e i v e d e a s e o f u s e

I n t e n t i o n t o u s e U s a g e b e h a v i o r

E x p e r i e n c e V o l u n t a r i n e s s

T e c h n o l o g y A c c e p t a n c e M o d e l

Figure 1. Technology acceptance model 2 (TAM 2)

Source: Venkatesh and Davis [17]

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Therefore, this study will probe into Web 2.0 website user behaviors and provide some references for those wishing to create a business on the Internet. 3. Theoretic model and hypotheses

Based on previous studies and TAM 2 proposed by Venkatesh and Davis [17], this study will apply TAM 2 to Web 2.0 websites and extend the research by Wu and Huang [18] to explore usage behaviors of Web 2.0 website users. The focus of this study is to explore users’ intention and behavior to use Web 2.0 websites. Users can choose to use Web 2.0 websites at will, so it is not necessary to classify users into voluntary or non-voluntary users. Hence, the construct of “voluntariness” is excluded in this study. Besides, it is also assumed that all Web 2.0 website users are of an experienced group, so the construct of “experience” can be excluded. Through a review of previous literatures, the following hypotheses are proposed: H1: Users’ “subjective norm” has positive influence on

“intention to use” Web 2.0 websites.

In 1995, Taylor and Todd [15] discovered that subjective norm has significant effects on behavioral intention. Therefore, it is hypothesized that subjective norm directly affects intention to use. H2: Users’ “subjective norm” for using Web 2.0 websites

has positive influence on “perceived usefulness”.

Lin [9] employed TAM 2 as a theoretic foundation to probe into the intangible services provided on tourist websites. It was discovered that the beliefs of people important to consumers will affect consumers’ tendency of using the tourist websites. Hence, it can be inferred that if people important to a user consider it as necessary to use Web 2.0 websites, the user is more likely to perceive the Web 2.0 websites as useful. H3: Users’ “subjective norm” for using Web 2.0 websites

has positive influence on “image”.

H4: Users’ “image” for using Web 2.0 websites has

positive influence on “perceived usefulness”.

Moore and Benbasat [10] defined image as “the extent to which use of an innovation is perceived as enhancement of one’s status in a social system”. Venkatesh and Davis [17] defined perceived usefulness as “the extent to which

the object of adoption is thought to enhance the individual’s performance on the job”. No matter users share their blogs or photo albums on Web 2.0 websites, they can attract people having similar interests to post messages or share ideas on the websites. If more and more friends or peers important to these users believe it is necessary to use such Web 2.0 websites, the users are more likely to perceive the websites as useful. H5: “Job relevance” of Web 2.0 websites has positive

influence on users’ “perceived usefulness” of the

websites.

Kieras and Polson [8] and Polson [13] mentioned that users can enhance their work efficiency if they are clear about their job-related knowledge. Thus, it can be inferred that job relevance has direct influence on perceived usefulness. H6: “Output quality” of Web 2.0 websites has positive

influence on users’ “perceived usefulness” of the

websites.

Users will contemplate how the system can assist the execution of tasks, so their perception of work efficiency can be enhanced. Such perception is perceived output quality. Previous studies have empirically indicated that perceived output quality has a positive relationship with perceived usefulness [5]. H7: “Result demonstrability” of Web 2.0 websites has

positive influence on users’ “perceived usefulness”

of the websites.

In TAM 2, as defined by Moore and Benbasat [10], result demonstrability is “tangibility of the results using the innovation, which will directly influence perceived usefulness”. H8: Users’ “perceived ease of use” of Web 2.0 websites

has positive influence on their “perceived

usefulness” of the websites.

H9: Users’ “perceived usefulness” of Web 2.0 websites has

positive influence on their “intention to use” the

websites.

H10: Users’ “perceived ease of use” of Web 2.0 websites

has positive influence on their “intention to use” the

websites.

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Previous studies have empirically indicated that perceived ease of use has indirect influence on intention to use, and perceived ease of use influences intention to use through perceived usefulness [17]. Lin [9] employed TAM 2 to probe into consumer behaviors of tourist websites and discovered that perceived usefulness has significant impact on intention to use. Consumers’ perceived usefulness of tourist websites has positive impact on their intention to use the websites, and their perceived ease of use of the websites also affects their intention to use the websites through perceived usefulness. H11: Users’ “intention to use” Web 2.0 websites has

positive influence on their “usage behavior”.

User attitude is affected by perceived usefulness and perceived ease of use and intention to use is directly affected by user attitude and perceived usefulness. Perceived ease of use also influences perceived usefulness. Finally, intention to use will influence usage behavior [14].

The above hypotheses can be organized into a framework as shown in Figure 2. 4. Data analysis and results

The survey was performed in two methods, Internet questionnaire and paper-and-pencil questionnaire.

The questionnaires were mainly distributed to users of Web 2.0 websites. A total of 400 valid responses were obtained.

4.1 Basic sample analysis The sample comprised of 48.5% male and 51.5%

female, mostly aged between 21-25 years old (31%). Most of the subjects have received college education, and 75.8% of them are currently students. 34.5% reported to have used the Internet for 8-10 years, and 61% reported to use the Internet 7 days a week on average. 4.2 Structural equation modeling

Structural Equation Modeling (SEM) was adopted to analyze the collected data. The main findings are as follows:

4.2.1 Model-fit evaluation

In terms of preliminary fit criteria, all the question items had a factor loading between 0.27~0.91 and all the error variances were non-negative and reached the significant level.

In terms of fit of internal structure of model, the composite reliability (CR) values of the four constructs ranged between 0.79~0.89, indicating high reliability.

The average variance extracted (AVE) of latent variables also ranged between 0.52~0.73, revealing a certain level of reliability and convergent validity of this research. Table 1 shows the results of the overall model fit.

Bagozzi and Yi [2] pointed out that AGFI above 0.8 can be accepted. The AGFI results in this study were not above 0.9 but already close to this threshold. Thus, the obtained results were in the acceptable range.

S u b j e c t i v e n o r m

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H 1

H 3

H 8 H 1 1

H 2

H 4

H 5

H 6

H 7

H 9

H 1 0

Figure 2. The research framework

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4.2.2 Discriminant validity

In this research, nine latent variables were involved, and all these latent variables could form 36 pairs of variables. The research results showed that the differences between nonrestrictive model and restrictive model ( χ2) △

all complied with P-value<0.001 (degree of freedom=1 and when P-value=0.001, χ2 =10.827). Besides, the nonrestrictive model had better fit for data and could support discriminant validity. Therefore, it could be inferred that the variables in this study featured good discriminant validity.

4.3 SEM analysis

The 11 proposed hypotheses were tested on LISREL. The path coefficient and t-value of each hypothesis are shown in Figure 3.

5. Conclusion This study mainly explored the relationships among the

constructs of TAM 2. From the research findings, the following conclusions were obtained.

Among the factors affecting user acceptance of Web 2.0 websites, belief of people important to users is an important factor. Besides, users’ perceived usefulness of Web 2.0 websites can also induce users’ willingness to use the websites. Thus, when building Web 2.0 websites, the need for interactions between and within user groups should be considered. For website users, suggestions of people important to them can also help enhance their status in the group. An innovative Web 2.0 website may use RSS to transmit webpage content, video or files and allow users to develop and create content on their own. These functions are ultimately intended to facilitate users’ exchange of information with one another.

The Web 2.0 services are provided by websites, so output service can be utilized to induce clustering of users. Thus, if both user interface and back-end operations are considered when providing web services, more users will be attracted, and the spirit of Web 2.0 “interaction” can also be realized.

Besides, the analysis result revealed that if users can easily communicate with others on Web 2.0 websites, they will perceive that Web 2.0 websites can facilitate interaction and sharing and are likely to carry on using the websites in the future.

Thus, in order to build good user experiences, no matter the interface's ease of use, obtainability of web contents or

0 .1 4(3 .4 2 ** * )

0 .2 5(5 .6 4 ** * )

0 .7 3(1 3 .2 1 *** )

0 .1 1(2 .2 9 * )

-0 .2 2(-4 .6 3 )

0 .2 1(4 .5 3 * * * )

0 .1 8(3 .6 6 * * * )

0 .4 1(6 .4 3 * * * )

0 .3 3(6 .2 4 * * * )

S u b je c tiv e n o rm

Im a g e

J o b re le v a n c e

O u tp u t q u a lity

R e s u lt d e m o n s tra b ility

U s a g e b e h a v io rIn te n tio n to u s e

P e rc e iv e d e a se o f u se

P e rc e iv e d u s e fu ln e s s

0 .6 2 (1 0 .5 7 ** * )

0 .5 1(8 .4 9 ** * )

Test statistics Ideal results Results

χ2(Chi-square) Smaller the

better 886.60

χ2/d.f.( normed Chi-square) (.d.f.=626)

<3 1.42

GFI(Goodness of fit index, GFI) >0.9 0.90 AGFI(Adjusted goodness of fit index, AGFI)

>0.9 0.87

NFI( Normed fit index, NNFI) >0.9 0.98 NNFI( Non-normed fit index, NNFI) >0.9 0.99 CFI(Comparative fit index, CFI) >0.9 0.99 RMSEA(Root mean square error of approximation, RMSEA)

<0.08 0.032

Notes: The numerical figure is path coefficient, and the parenthesized value is t-value. * denotes t –value>1.96, p < 0.05; ** denotes t –value>2.58, p < 0.01; *** denotes t –value>3.29, p < 0.001.

Figure 3. Path coefficients and relationships of the variables

Table 1. The items tested for overall model fit.

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interaction in the community, technical functions and user management should make users perceive the benefits of Web 2.0, so that user participation can be increased.

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