Nurse Education Today 34 (2014) 446–450

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Nurse Education Today

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The roles of social factor and internet self-efficacy in nurses' web-basedcontinuing learning

Yen-Lin Chiu 1, Chin-Chung Tsai ⁎Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, 43, Section 4, Keelung Rd., Taipei 106, Taiwan

⁎ Corresponding author. Tel.: +886 2 27376511; fax:E-mail addresses: erin0825@ms58.hinet.net, yenlin.c

(Y.-L. Chiu), cctsai@mail.ntust.edu.tw (C.-C. Tsai).URL: h1 Tel./fax: +886 2 27303218.

0260-6917/$ – see front matter © 2013 Elsevier Ltd. Allhttp://dx.doi.org/10.1016/j.nedt.2013.04.013

s u m m a r y

a r t i c l e i n f o

Article history:Accepted 16 April 2013

Keywords:Web-based learningContinuing learningSocial factorInternet self-efficacy

This study was conducted to explore the relationships among social factor, Internet self-efficacy and attitudes to-ward web-based continuing learning in a clinical nursing setting. The participants recruited were 244 in-servicenurses from hospitals in Taiwan. Three instruments were used to assess their perceptions of social factor, Internetself-efficacy (including basic and advanced Internet self-efficacy) and attitudes towardweb-based continuing learn-ing (including perceived usefulness, perceived ease of use, affection and behavior). Structural equation modeling(SEM)was utilized to identify the hypothesized structural model. The results of this study support that social factoris a significant factor correlated to Internet self-efficacy and attitudes toward web-based continuing learning (in-cluding perceived usefulness, perceived ease of use and affection). In addition, nurses' basic Internet self-efficacyplays a key role in attitudes including perceived usefulness, perceived ease of use and affection. However, advancedself-efficacy was not correlated to any of the attitudes. The behavior dimension was not linked to social factor or In-ternet self-efficacy, but was linked to perceived ease of use and affection.

© 2013 Elsevier Ltd. All rights reserved.

Introduction

Web and Internet-based learning is recognized as an effective learn-ing approach for improving nursing knowledge and skills (Cobb, 2004;Lu et al., 2009). The inherent nature of web-based learning such asflexibility and resource richness may encourage nurses to take upsuch learning for their continuing education (Wilkinson et al., 2004;Yu et al., 2007). On-line learning has therefore been widely used forprofessional development and nursing skills training in clinical practice(e.g., Chen et al., 2008; Wilkinson et al., 2004; Yu and Yang, 2006).

The attitudes towardweb-based professional development and con-tinuing learning have been considered in several studies (Kao and Tsai,2009; Liang et al., 2011). Nurses' attitudes are regarded as the most im-portant factor which may promote web-based learning for in-serviceeducation (Yu and Yang, 2006). Although most nurses have revealedpositive attitudes toward web-based learning for continuing educationin clinical settings (Atack, 2003; Yu and Yang, 2006), there is still a needto explore the factors that determine their attitudes.

Although the technology acceptance model (TAM) is suggested asa useful model for explaining attitudes and behavior in the use oftechnology, it has been integrated with extended variables including

+886 2 27303218.hiu@mail.ntust.edu.twttp://www.cctsai.net (C.-C. Tsai).

rights reserved.

personal and social factors. For example, there has been researchstudying web-based learning using TAM with additional factors such asself-efficacy (Chatzoglou et al., 2009), Internet self-efficacy (Chen andTseng, 2012), social influence (Lee et al., 2011; Park et al., 2012) as wellas organizational support including technical support (Bhattacherjeeand Hikmet, 2008; Ngai et al., 2007; Sánchez and Hueros, 2010) andmanagement support (Chatzoglou et al., 2009).

The studies related to web-based learning have been extensive.However, little research has analyzed the predicting factor of web-based learning in organizational settings (Karaali et al., 2011), eventhough it has been indicated that organizational environment influ-ences may have effects on employees' motivation to use web-basedlearning in the workplace via the perceived usefulness of such learn-ing systems (Cheng et al., 2012). The organizational learning environ-ment encompassing factors such as policies and group enrollment hasbeen regarded as playing an influential role in web-based learningprocesses (Atack, 2003). Recent research on web-based workplacelearning has emphasized the influence of employees' characteristicsand technological attributes, but with little attention being paid toorganizational environment factors such as social influence (Chenget al., 2012).

Literature

Social Factor and Attitudes Toward Web-Based Learning

Social environment may support users to possess more positiveattitudes toward Internet usage (Cheung et al., 2000). Social influ-ence, which may affect perceived usefulness and perceived ease of

SF

PU

PE

AF

BH

AISE

BISE

Organizational factor

Personal factor

Behavior Attitudes

Fig. 1. The hypothesizedmodel of structural relations among SF, BISE, AISE, PU, PE, AF andBH. SF: social factor; BISE: basic Internet self-efficacy; AISE: advanced Internet self-efficacy;PU: perceived usefulness; PE: perceived ease of use; AF: affection. BH: behavior.

447Y.-L. Chiu, C.-C. Tsai / Nurse Education Today 34 (2014) 446–450

use, needs to be considered whiling designing and implementinge-learning systems (Lee et al., 2011). Davis et al. (1989), who proposedthe technology acceptance model (TAM), suggested further research tobetter understand the impact of social influences on usage behavior. Itwas claimed that behavior is affected by social norms, and is dependenton others' messages reflecting what individuals should do (Triandis,1971). Triandis (1980) redefined this and called it social factor, throughwhich individuals may internalize subjective culture originated fromreference groups and interpersonal agreements made with others.However, social factor, which was considered as an explaining factorof the Internet usage (Cheung et al., 2000), has not received enoughattention in the web-based learning field.

Internet self-efficacy and attitudes toward web-based learning

Internet self-efficacy is defined asweb users' confidence in using theInternet (Tsai, 2012; Wu and Tsai, 2006), and is regarded as an impor-tant predictor of attitudes towardweb-based professional development(Kao and Tsai, 2009). Learners with higher Internet self-efficacy mayhave more probability of success in web-based learning tasks (Tsaiand Tsai, 2003). It has been reported that nurses reject web-based con-tinuing learning because of their lack of relevant competence (Yu et al.,2007). Nurseswith higher Internet self-efficacy, on the other hand, tendto reveal higher motivation for web-based continuing learning (Liangand Wu, 2010). Also, Liang et al. (2011) indicated that nurses' Internetself-efficacy is positively related to their attitudes toward web-basedcontinuing learning (Liang et al., 2011).

Social factor, Internet self-efficacy, attitudes and behavior towardweb-based learning

Social factor, including managerial support, job support and or-ganizational support, is positively related to perceived usefulness;moreover, perceived usefulness mediates the environmental influ-ences on individuals' intention to use an e-learning system (Chenget al., 2012). Furthermore, the empirical study of Liang et al. (2011)indicated that nurses' Internet self-efficacy (including basic and ad-vanced Internet self-efficacy) can be linked to their attitudes towardweb-based continuing learning (including perceived usefulness,perceived ease of use, affection and behavior). Bandura's (1997)social cognitive theory suggested that social support is vital toself-efficacy, and influences behavior through self-efficacy. Studyresults have indicated that teacher's support is positively related tolearning strategy, and this relationship is mediated by self-efficacy(Yildirim, 2012). In addition, it has been indicated that the organizationalenvironment factor may have influences on Internet self-efficacy; inturn, the adoption of the Internet is influenced by Internet self-efficacy(Lam and Lee, 2006). The mediation role of Internet self-efficacybetween social support and online learning outcomes has also beenfound (Chu, 2010; Chu and Chu, 2010).

Organizational social influence on attitudes and behavior

The propositions of TAM (Davis et al., 1989) specified that externalvariables may have effects on attitudes, and then the behavioral in-tentions are influenced by these attitudes. Founded on the theory ofreasoned action (TRA), an individual's behavioral intention is deter-mined by his/her attitudes (Ajzen and Fishbein, 1980). Based on thetheoretical rationale of TAM, various studies have supported that so-cial factor has an influence on the attitudes and behavioral intentionof e-learning and web-based training; moreover, attitudes are consid-ered as significant determinants of behavior to undertake such learn-ing (Cheng et al., 2012; Lee et al., 2011; Park et al., 2012).

It has also been revealed that social factor is a predictor of inten-tion and behavior regarding the Internet and web usage at work(Cheung et al., 2000). In addition, the empirical study of Karaali

et al. (2011) indicated that social factor may influence employees'attitudes toward web-based learning and behavior intention; fur-thermore, behavioral intentions are determined by attitudes.

Hypothesized model

According to the aforementioned propositions (Bandura, 1997), inthis study it is supposed that social factor in the organizational envi-ronment may enhance nurses' personal Internet self-efficacy includ-ing both basic and advanced Internet self-efficacy. In turn, Internetself-efficacy may improve nurses' attitudes toward web-based con-tinuing learning including perceived usefulness, perceived ease ofuse, affection and behavior (Liang et al., 2011). Finally, attitudes in-cluding perceived usefulness, perceived ease of use and affectionmay reinforce nurses' behavioral intention to use web-based continu-ing learning (Ajzen and Fishbein, 1980).

In addition, social factor may be positively correlated to attitudestoward web-based learning (Cheng et al., 2012; Lee et al., 2011). Also,behavioral intention may be determined by social factor (Karaali et al.,2011). The hypothesizedmodelwhich consists of four aspects includingorganizational factor, personal factor, attitudes and behavior is presentedin Fig. 1.

Methods

Participants

A total of 244 in-service nurses from private hospitals (66%) andthe public sector (34%) in Taiwan were enrolled in the study survey.All of the nurses were female, with an average nursing work experi-ence of 10.26 (SD = 8.67) years. Among them, 99 (40.6%) workedin medical centers, while 145 (59.4%) worked in regional hospitals.

The education levels of the participants were bachelor's degree(66.4%), junior college (29.1%), and master's degree (4.5%), while119 (48.8%) were aged from 21 to 30, 76 (31.1%) were aged between31 and 40, and 40 (16.4%) were from 41 to 50.

Ethical considerations

All the nurses enrolled in this study responded to the question-naire voluntarily. Prior to answering the questionnaire, they were in-formed that they had the right to withdraw from the survey at theirown free will, and were guaranteed that their responses would be

Table 1Means, standard deviations and correlations of research variables.

Mean S.D. 1 2 3 4 5 6

1. SF 4.36 0.872. BISE 5.12 0.81 0.29⁎⁎⁎

3. AISE 4.47 1.37 0.37⁎⁎⁎ 0.66⁎⁎⁎

4. PU 4.34 0.92 0.52⁎⁎⁎ 0.31⁎⁎⁎ 0.32⁎⁎⁎

5. PE 4.52 0.93 0.42⁎⁎⁎ 0.37⁎⁎⁎ 0.32⁎⁎⁎ 0.79⁎⁎⁎

6. AF 4.34 0.99 0.39⁎⁎⁎ 0.34⁎⁎⁎ 0.36⁎⁎⁎ 0.80⁎⁎⁎ 0.77⁎⁎⁎

7. BH 3.80 0.94 0.51⁎⁎⁎ 0.27⁎⁎⁎ 0.35⁎⁎⁎ 0.53⁎⁎⁎ 0.51⁎⁎⁎ 0.56⁎⁎⁎

Note: SF: social factor; BISE: basic Internet self-efficacy; AISE: advanced Internet self-efficacy;PU: perceived usefulness; PE: perceived ease of use; AF: affection; BH: behavior.⁎⁎⁎ p b 0.001

448 Y.-L. Chiu, C.-C. Tsai / Nurse Education Today 34 (2014) 446–450

treated confidentially. Turning in a questionnaire with an agreementsignature was regarded as consent to participate.

Instruments

Three questionnaires were adopted as the survey instruments.Thompson et al.'s (1991) Social Factor Scale was adapted to measurethe organizational environment factor. The Internet Self-efficacy Survey(ISS) adopted from Liang et al. (2011) was used to investigate thenurses' confidence in using the Internet. Finally, the Attitudes to-ward Web-based Continuing Learning Survey (AWCL) developedand validated by Liang et al. (2011) was employed to explore thenurses' perceptions of continuing learning on the web. All of theseinstruments were measured with a six-point Likert scale rangingfrom 1 (strongly disagree) to 6 (strongly agree).

To validate the constructs of social factor, ISS and AWCL, confir-matory factor analysis was conducted. The modification index valuesof the initial model indicated that several items with double-crossloadings needed to be eliminated. Finally, 26 items (including socialfactor with 4 items, basic Internet self-efficacy with 5 items, ad-vanced Internet self-efficacy with 5 items, perceived usefulnesswith 3 items, perceived ease of use with 3 items, affection with 3items, and behavior with 3 items) were retained for further analysis.Although the goodness of fit index (GFI) and the adjusted goodness offit index (AGFI) were somewhat low, these values were still acceptable(GFI = 0.87, AGFI = 0.83). The other fit indices including the normedfit index (NFI = 0.94), the comparative fit index (CFI = 0.97), theroot mean square of approximation (RMSEA = 0.058) and χ2 to thedegrees of freedom ratio (χ2/df = 1.82) showed that the constructmodel provided a satisfactory fit to the data.

Social factor was surveyed by asking the nurses: the proportion ofcoworkers who regularly undertook web-based continuing learning;the extent to which the senior management of their unit supportedthe use of web-based continuing learning; the extent to which the su-pervisor supported the use of web-based continuing learning; and theextent to which the organization supported the use of web-basedcontinuing learning. The alpha coefficient of social factor in this studywas 0.93, representing a good reliability.

The Internet Self-efficacy Survey (ISS) included two components:the basic self-efficacy scale investigated the nurses' self-efficacy ofbasic abilities to use the Internet (e.g., using web browsers or searchingfor online information), while the advanced self-efficacy scale evaluatedthe nurses' confidence in Internet-based interaction andusing advancedfunctions of the Internet (e.g., having online conversations or makingpayments). The alpha coefficients of basic Internet self-efficacy and ad-vanced Internet self-efficacy in Liang et al. (2011) were 0.95 and 0.94,whereas the alpha coefficients in this studywere 0.94 and 0.96, indicat-ing ISS as an adequate questionnaire for assessing nurses' Internetself-efficacy.

The Attitudes toward Web-based Continuing Learning (AWCL)consisted of four scales. The perceived usefulness scale assessed thenurses' perceptions of the extent to which they perceive that the in-fluence of web-based continuing learning is useful (e.g., I get betterlearning outcomes from web-based continuing learning). The per-ceived ease of use scale evaluated the nurses' perceptions of the ex-tent to which web-based continuing learning is easy to use (e.g., It isconvenient for me to receive training by using web-based continuinglearning). The affection scale assessed the nurses' perceptions regardingpositive feelings about web-based continuing learning (e.g., It isinteresting to use web-based continuing learning). The behaviorscale measured the nurses' willingness to take up web-based con-tinuing learning (e.g., I hope to use web-based continuing learningmore often). Compared with the alpha coefficients of the perceivedusefulness (0.96), perceived ease of use (0.95), affection (0.95)and behavior (0.85) scales in Liang et al. (2011), the alpha coeffi-cients in this study were 0.97, 0.95, 0.97 and 0.83, respectively,

demonstrating AWCL as an appropriate questionnaire for evaluatingnurses' attitudes toward web-based continuing learning.

Data analysis

Data screening, descriptive analyses and correlation analyses wereconducted using the Statistical Package for Social Sciences (SPSS)version 17.0. The AMOS 18.0 software was utilized to implementthe confirmatory factor analysis. For testing the structural relation-ships among social factor, Internet self-efficacy and nurses' attitudestoward web-based continuing learning, the AMOS 18.0 software wasalso employed to administer the path analysis of structural equationmodeling.

Results

The results of the correlation analysis are revealed in Table 1.It shows that social factor is significantly positively correlated tobasic Internet self-efficacy, advanced Internet self-efficacy and eachscale of the AWCL. In addition, both basic Internet self-efficacy andadvanced Internet self-efficacy have positive relationships with theAWCL scales.

To explore the path correlations among social factor, Internetself-efficacy and scales of attitudes toward web-based continuinglearning, the path analysis was conducted using structural equationmodeling (SEM) analysis. Fig. 2 reveals the path coefficients of thestructural model that specified the relationships among the latentconstructs. The fit indices of the structural model include an RMSEAof 0.058, a χ2/df of 1.82, a GFI of 0.87, an NFI of 0.94, and a CFI of0.97, showing that the structural model has an acceptable model fit.To simplify the structural relations, the paths with insignificant coef-ficients were omitted in Fig. 2.

As Fig. 2 shows, the social factor has significant relationswith basic In-ternet self-efficacy (γ = 0.37, p b 0.001), advanced Internet self-efficacy(γ = 0.29, p b 0.001), perceived usefulness (γ = 0.48, p b 0.001), per-ceived ease of use (γ = 0.37, p b 0.001) and affection (γ = 0.29,p b 0.001), but not with behavior. Basic Internet self-efficacy also hassignificant correlations with perceived usefulness (β = 0.20, p b 0.05),perceived ease of use (β = 0.33, p b 0.001) and affection (β = 0.22,p b 0.01). However, advanced Internet self-efficacy does not possessany significant coefficient between perceived usefulness, perceivedease of use, affection or behavior. Furthermore, the path coefficientsshow that both perceived ease of use (β = 0.32, p b 0.001) and affection(β = 0.40, p b 0.001) have significant relations with behavior.

In summary, social factor directly links to perceived usefulness,perceived ease of use and affection. In addition, social factor plays an in-direct role in nurses' intention to use web-based continuing learningthrough basic Internet self-efficacy, perceived ease of use and affection.Finally, basic Internet self-efficacy is indirectly correlated to behaviorvia perceived ease of use and affection.

SF

BISE

AISE

PU

PE

AF

BH

0.37***

0.29***

0.20*

0.33***

0.22**

0.48***

0.37***

0.29***

0.32***

0.40***

Fig. 2. The path coefficients of structural relations among SF, BISE, AISE, PU, PE, AF and BH. SF: social factor; BISE: basic Internet self-efficacy; AISE: advanced Internet self-efficacy;PU: perceived usefulness; PE: perceived ease of use; AF: affection. BH: behavior. ⁎p b 0.05; ⁎⁎p b 0.01; ⁎⁎⁎p b 0.001.

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Discussion

Extending the TAM of Davis et al. (1989), this study confirmed thesignificant roles of social factor and Internet self-efficacy in predictingnurses' attitudes toward web-based continuing learning. The resultsof this study illustrated that social factor is an important determinantof nurses' Internet self-efficacy and attitudes toward web-based con-tinuing learning. This result is consistent with Triandis' (1971) modeland other empirical studies (e.g., Cheng et al., 2012; Park et al., 2012),implying that facilitating the conditions of the workplace such asorganizational support and social influence has positive effects onpersonal characteristics such as self-efficacy and attitudes towardweb-based continuing learning. Definitely, more external supportfrom the workplace is suggested to promote nurses' Internet self-efficacy and attitudes toward web-based continuing learning. Whenthe social environment can encourage nurses to undertake suchlearning, they will possess more confidence and positive attitudes to-ward using it. It has been indicated that role models may positivelyinfluence users' adoption of innovative technology and employees'learning orientation (Gong et al., 2009; Thompson et al., 1991). Thatis, potential users may be encouraged while the early adopters whoare successful in utilizing web-based learning are commended andrewarded. Moreover, nurse supervisors can serve as role models andverbally persuade nurse staff to employ such on-line learning.

On the other hand, the study results revealed that nurses' basicInternet self-efficacy is positively correlated to their perceived use-fulness, perceived ease of use and affection. These findings are con-sistent with previous empirical studies (Chen and Tseng, 2012),indicating that Internet self-efficacy is a predictor of attitudes to-ward web-based learning systems. The results suggest that nursingeducators may try to conduct some training programs to fosternurses' basic Internet self-efficacy since training can significantly im-prove individuals' Internet self-efficacy (Torkzadeh et al., 2006;Torkzadeh and Van Dyke, 2002). Accumulating more experience inusing the Internet is another way to promote Internet self-efficacy(Liang and Wu, 2010; Wu and Tsai, 2006). Both strategies mayimprove nurses' Internet self-efficacy and nurture their positive atti-tudes towards undertaking web-based continuing learning.

However, in this study, the insignificant correlations of advancedInternet self-efficacy to nurses' attitudes toward web-based continu-ing learning should be mentioned. This result is somewhat contradic-tory of Liang et al.'s (2011) findings. Otherwise, the study resultsof Shih (2008) also revealed that no direct effect of self-efficacy onattitudes toward web-based learning was discovered, but that self-efficacy was found to indirectly affect individuals' attitudes and be-havioral intentions through personal outcome expectations. In addi-tion, Liang and Wu's (2010) study revealed that nurses' advanced

Internet self-efficacy had different relationships with various motiva-tions toward web-based continuing learning, for example, advancedInternet self-efficacy was positively correlated to life enrichment andsocial connections, but not to external expectations or practical en-hancement. Therefore, there is a need for further studies to investigatethe influential factors such as expectations and motivations betweenadvanced self-efficacy and attitudes toward web-based learning.Probably, these factors may result in divergent relationships betweenadvanced Internet self-efficacy and attitudes towardweb-based learning.

Consistent with previous studies (Chatzoglou et al., 2009; Chenand Tseng, 2012), this study found that nurses' attitudes towardweb-based continuing learning were linked to their behavioral inten-tion. Among the attitudes toward web-based continuing learning,perceived ease of use and positive affection were indicated as beingsignificant predictors of behavior. These findings comply with theconcepts of TRA and TAM, which have identified attitudes as determi-nants of behavioral intention (Ajzen and Fishbein, 1980; Davis et al.,1989). This implies that the learning system is an important facilitatorwhich may raise nurses' perceived ease of use and positive affectiontoward web-based learning, and then their willingness to use suchlearning systems may be enhanced. In other words, technical supportof on-line learning system such as information seeking help and in-structions for solving problems in undertaking such learning systemmay make users feel more positive toward it.

For future studies, other external variables such as job charac-teristics (e.g., job demand and job control) and task characteristics(e.g., flexibility and difficulty); as well as personal characteristicssuch as age, nursing tenure and job position are recommended tobe included in the theoretical model while exploring nurses' web-based learning.

Conclusions

This study provides more comprehensive insights into social fac-tor and Internet self-efficacy in exploring nurses' attitudes towardsusing web-based continuing learning in the context of the workplace.Social factor has been found to be an important factor which may fa-cilitate nurses' Internet self-efficacy and attitudes toward web-basedcontinuing learning. In other words, the influence of colleagues andsupervisors on the users of web-based continuing learning shouldbe taken into consideration. Their positive opinions may supporteach other to use web-based continuing learning. Encouragementfrom coworkers and supervisors such as verbal persuasion may del-iver efficacy information for forming expectation and confidence inusing on-line learning (Lam and Lee, 2006). In addition, if the wholeorganization promotes and supports nurses to take up their trainingthrough the web, potential users may be inspired to undertake such

450 Y.-L. Chiu, C.-C. Tsai / Nurse Education Today 34 (2014) 446–450

learning. The hospital's reward policy and support from managementand facilities may back up nurses to adopt online continuing learning.A positive organizational climate toward web-based continuing learn-ing is also suggested to be created to foster the nurses' attitudes. To doso, the nursing staff are encouraged to communicate and share success-ful experiences with each other.

The study results also revealed that nurses' personal efficacy inbasic Internet ability plays a determinant role in web-based continu-ing learning. As mentioned above, the facilitating factor of social con-texts in the workplace is an influential way of raising nurses' Internetself-efficacy. In addition, nursing educators and managers are sug-gested to provide nurses with more training and practice in usingthe Internet. It has been recommended that a pre-course of computerand Internet capability may foster nurses' skills in handling web-basedlearning (Atack and Rankin, 2002). Especially, the basic Internet skillsare significantly linked to attitudes. Once the nursing staff obtainsmore expertise and experience of basic Internet utilization, they maydevelopmore positive attitudes towardweb-based continuing learning.

Although social factor and Internet self-efficacy were not linkeddirectly to nurses' behavioral intent to use web-based continuinglearning, they were indicated as having an indirect influence on be-havioral intention through the effects of perceived ease of use andpositive affection for web-based learning. That is to say, setting up afacilitating work environment and raising basic Internet self-efficacymay stimulate nurses' intent to undertake web-based continuinglearning via the effects of positive attitudes.

Several limitations of this study should be mentioned. Since all par-ticipants of this study were female nurses, the generalization of thestudy results to other male employees and other industries should bemadewith care. Further studies may try to compare the differences be-tween different genders and industries. In addition, the conveniencesampling method used in this study may limit the generalization ofthe study results. Finally, the disadvantages of self-reported measuresshould also be considered. Further research may be combined withqualitative methods to obtain more comprehensive interpretations ofthe nurses' attitudes and intent to undertake web-based continuinglearning.

Acknowledgment

This study was supported by the National Science Council, Taiwan,under grant number NSC 99-2511-S-011-005-MY3.

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