use and gratification in e‐consumers

Use and gratification ine-consumers

Echo HuangNational Kaohsiung First University of Science and Technology,

Kaohsiung, Taiwan

Abstract

Purpose – The purpose of this paper is to present a conceptual model based on technologyacceptance with extended antecedent variables (entertainment and irritation) to examine the impact ofuse and gratification on e-consumers’ acceptance of B2C Websites.

Design/methodology/approach – Data were collected from a total of 238 EMBA andundergraduate students from three different Taiwan universities. Structural equation modeling(SEM) was used to evaluate the conceptual model in terms of overall fit, explanatory powers andcausal links.

Findings – The analytical results showed that entertainment gratification, irritation surfingexperience (mass medium), perceived usefulness and ease of Web use (information systems) areimportant predictors of e-consumers’ use intention. The integrated model was then assessed forvariance in explanatory power regarding consumer attitude and intention toward B2C Websites.

Practical implications – Intention to use the Web is the predictor of actual use, purchase andinformation-seeking behaviors in e-consumers. Creating entertaining content and reducing distractingprocesses can enhance acceptance of B2C Websites.

Originality/value – A theoretical model incorporating U&G constructs into a technology acceptancemodel was used to investigate e-consumer behavior in Taiwan. Although ease of use and usefulnessare perceived as important issues in traditional IS environments, U&G provides managers with adifferent perspective.

Keywords Consumer behaviour, Taiwan

Paper type Research paper

IntroductionOf the many causes of the rapid growth of Internet use in the last decade, mostresearchers confer that the critical contribution has been the growth of Web content.Rapid growth of the Internet has created a new arena for international commerce andprovides new possibilities for marketing products and services. The medium hasbecome more user-friendly, more accessible and less expensive than before. Somescholars suggest that focusing on social impacts maybe premature until Web use isbetter understood (Schepers and Wetzels, 2007; King and He, 2006). Accurateknowledge of customer behavior when accessing the Internet allows Internetbusinesses to better serve their customers (Gallaugher, 1999; Lohse et al., 2000; Chenget al., 2006; Yiu et al., 2007). Therefore, understanding the psychological factorsaffecting Web use is essential. Recent studies (Chu and Lu, 2007; Kamis and Stohr,2006; Lee and Lin, 2005) examining the motivations of e-consumers indicate that

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The author is grateful for the constructive feedback received from the two reviewers and Editorhandling this manuscript for the journal.

Use andgratification in

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Received 12 April 2007Revised 20 May 2008

Accepted 23 May 2008

Internet ResearchVol. 18 No. 4, 2008

pp. 405-426q Emerald Group Publishing Limited

1066-2243DOI 10.1108/10662240810897817

common incentives for shopping online include convenience, broader selection(Javenpaa and Todd, 1997; Kamis and Stohr, 200), competitive pricing, and easy accessto information (Liu and Ma, 2005). In fact, many online shoppers use a specific Websiteor content merely by chance (Bogart, 1995). For example, they may visit a particularWebsite after receiving an email about the site or follow an unexpected link after asearch engine result. However, the conditions associated with continuing use of amedium are still unknown. Rayburn (1996) argued that the Internet is intentionallyconsumed, as audiences must make purposive choices about which site to visit.

Exploratory “browsing” or “surfing” is a common mass media behavior (Bogart,1995) and is explained by two major theories. The Uses and Gratifications Theory(U&G) examines broad motivational dimensions to explain the psychologicalgratification associated with a multitude of mediated communication modes. TheU&G research has been fruitful in rationalizing consumer behavior and concerns in thecontext of traditional media. Many researchers (Chen and Wells, 1999; Korgaonkar andWolin, 1999; Ruggiero, 2000; Kaye and Johnson, 2001; Luo, 2002; Ko et al., 2005) haveapplied U&G in the context of the Internet. A second theory is Technology AcceptanceModel (TAM), a well-referenced theory in IS literature. The TAM is among the mostinfluential and widely applied theories for predicting and explaining end-user behaviorand system use. Many recent studies have applied TAM when studying acceptance ofInternet-related technologies, such as email (Gefen and Straub, 1997), Web (Chen et al.,2002; Fenech, 1998, Lederer et al., 2000, Lin and Hsipeng, 2000), virtual store (Chen et al.,2002; Gefen et al., 2003; O’Cass and Fenech, 2003), and electronic commerce (Selim,2003; Kamis and Stohr, 2006; Cheng et al., 2006; Yiu et al., 2007; Chu and Lu, 2007).Other researchers have extended TAM by incorporating external variables to improvethe applicability of TAM in the context of traditional IS and Web environments (Aakerand Stayman, 1990; Chu and Lu, 2007; Lin, 2007). Previous studies (Gefen and Straub,1997; Schepers and Wetzels, 2007; King and He, 2006) suggested that TAM shouldencompass other important theoretical constructs, such as media use theory, whichintegrates normative and utilitarian determinants.

This study presents an integrated model based on two well-founded theories: theTechnology Acceptance Model (TAM) and Use and Gratification Theory (U&G), bothof which are widely used in IS and mass communication research. The e-consumer isanalyzed as both a shopper and a medium user as constructs from information systemsuse (TAM) and medium use (U&G) are tested in an integrated theoretical framework toelucidate e-consumer behaviors. The integrated model is evaluated in terms of overallfit, explanatory powers and causal links.

This paper is divided into the following five sections: a literature overview oftheoretical models (TAM, U&G); research design and methodology; analysis ofempirical data; model results and model comparisons; and finally, limitations of thestudy and suggestions for future research.

Theoretical backgroundTechnology Acceptance Model (TAM)The TAM (Davis, 1989) with its basis in Theory of Reasoned Action (TRA) (Ajzen,1991; Fishbein and Ajzen, 1975) is the currently the favored theory for explainingadoption of new IT; its relationship to TRA has been discussed extensively in theliterature (Davis, 1989; Keil et al., 1995; Mitchell and Greatorex, 1993; Roger, 1995) and

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need not be elaborated here. Davis applied TRA to show that beliefs influenceattitudes, which lead to intentions, which then generate behaviors. Attitudes aredefined as the positive or negative feelings of an individual towards a specificbehavior, which are influenced by perceived usefulness and ease of use. Perceivedusefulness is defined as the degree to which a person believes using a particular systemenhances job performance; similarly, perceived ease of use is the degree to which aperson believes using a particular system is free of effort. Therefore, Davis assertedthat the belief-attitude-intention-behavior relationship predicts and explains user ITacceptance.

The TAM theory is among the most influential and discussed theories used toelucidate end user behavior and system use. Although the model is mainly applied toexplaining technology adoption within organizations, its constructs are fairly general(Davis, 1989; Doll et al., 1998). Previous research has shown that, where PU and PEOUare antecedents of use-intentions, TAM is applicable to many IT services for bothexperienced and novice users across various expertise levels (Taylor and Todd, 1995).The TAM theory is applied in this study due to its solid theoretical foundation.

The TAM model has been successfully applied elsewhere in studies of acceptance ofInternet-related technologies, such as e-mail (Ahn et al., 2004; Chen et al., 2002;Koufaris, 2002), e-healthcare (Lanseng and Andreassen, 2007), online taxation system(Chen and Huang, 2007), e-government (Phang et al., 2005; Sahu and Gupta, 2007),online shopping (Li et al., 2006), online banking (Lai and Li, 2005; Sundarraj and Wu,2005) and mobile commerce (Wang et al., 2006). Table I summarizes the findings ofseveral TAM studies in Internet-related research. Thus, using TAM (Figure 1) as thebasis for investigating consumer online behavior is well precedented.

Uses and Gratifications theory (U&G)Uses and Gratifications Theory (U&G) was first developed in research in theeffectiveness of radio communication in the 1940s. U&G is largely intended to identifythe psychological needs that motivate the use of a particular medium to gratify thoseneeds (Ko. et al, 2005). The U&G evolved from the communications theory as a meansof identifying and profiling radio and television audiences. Advertising and marketingresearchers later applied U&G to “novel media”, such as cable television, videorecording and TV/VCR remote control devices; further, recent studies have exploredU&G applications in non-traditional media such as e-mail (Dimmick et al., 2000),Internet use (Chen and Wells, 1999; Eighmey and McCord, 1998; Eighmey, 1997;Fenech, 1998; Korgaonkar and Wolin, 1999; Stafford and Stafford, 1998; Stafford andStafford, 2001; Ko et al., 2005), World Wide Web (Lin, 1999) and wireless advertising(Peters et al., 2007). Rubin (1994) found that certain television programs are related tohuman needs, including information acquisition, escape, emotional release,companionship, reality exploration and value reinforcement. Papacharissi and Rubin(2000) proposed five primary motives for using the Internet: interpersonal utility,pastime, information seeking, convenience and entertainment. Lin (2007), however,asserted that surveillance is the most significant motivation for visiting informationand infotainment Websites whereas entertainment and surveillance are the mostsignificant motivation for visiting shopping sites. Luo (2002) investigated howinformativeness, entertainment and irritation affect various online consumerbehaviors. Gratification in online activity is the satisfaction of needs for


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surveillance, personal identity, information learning, socialization, escape,entertainment and interaction (James et al., 1995).

Rapid growth of the Internet is the major cause of increased Internet use in recentyears. Web content has become increasingly more useful and more accessible thanbefore (Stafford and Stafford, 2001). Online shopping has also become more convenient,streamlined and customer-oriented than previously (Stafford and Stafford, 1998; Koet al., 2005). Most literature in Web use classify Web surfing behavior into two styles ofnavigation. Examples are goal-oriented v. experimental, surfing v. searching,hedonistic v. utilitarian, sensory v. functional or play v. work (Chen and Wells,1999). Wolfinbarger and Gilly (2001) found that e-consumers tend to be moregoal-oriented than experience-oriented while shopping.

To elucidate these important new Internet communication processes and userinteractions (Kannan et al., 1998), U&G provides a user-level perspective rather than amass-exposure perspective (Rayburn, 1996). A basic assumption of U&G is that usersare actively involved in media usage and interact extensively with communicationmedia. Given the inherent interactive and user-directed nature of Internet, U&G isparticularly appropriate for investigating consumer Internet use.

Research model and hypothesesIn the recent decade, motive has also been studied in the context of the Internet, and is arecommended metric for the e-consumer experience (Chen and Wells, 1999; Eighmeyand McCord, 1998; Korgaonkar and Wolin, 1999; Stafford and Stafford, 2001). Motivesreflect needs and are observable and measurable. The underlying constructs of U&Gare multiple; according to the literature, the most important and robust dimensionsinclude entertainment gratification, informativeness gratification and advertisementirritation (Chen and Wells, 1999; Eighmey and McCord, 1998; Fenech, 1998;Korgaonkar and Wolin, 1999; Rubin, 1994; Luo, 2002; Ko et al., 2005). Consumerattitude towards the Internet is a major indicator of Web effectiveness and consumertrust in Internet technology (Chen and Wells, 1999), just as attitude towardsadvertising is considered predictive of advertising effectiveness (Haley and Baldinger,1991; Ko et al., 2005; Peters, al., 2007). Figure 2 shows that the research model thereforeintegrated the original TAM and U&G based on individual motivation. Entertainment,irritation and satisfaction, the extended part of the model, were the constructs ofresearch foci.

Relevant investigations confer that attitudinal reasons such as the need forcommunication, escape, entertainment, interaction and surveillance gratificationexplain why users go online (Eighmey, 1997; Lin and Hsipeng, 2000; Wolfinbarger andGilly, 2001). Enjoyment, entertainment and humor are important reasons for revisiting

Figure 1.Technology acceptancemodel of attitude towardthe use Websites

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certain sites (Stafford and Stafford, 1998; Stafford and Stafford, 2001; Wolfinbargerand Gilly, 2001); in this study, such factors are referred to as “entertainmentgratification”. Hence, the following hypotheses are proposed:

H1. Entertainment gratification will have a positive effect on perceivedusefulness.

H2. Entertainment gratification will have a positive effect on perceived ease ofuse.

H3. Entertainment gratification will have a positive effect on attitudes toward theWeb.

Although numerous studies have investigated the relationship between playfulnessand continued Internet use (Stafford and Stafford, 1998; Stafford and Stafford, 2001;Wolfinbarger and Gilly, 2001), such studies often overlook negative factors such asprocess irritation (Lederer et al., 2000; Stafford, 2003). Criticisms of advertising andmarketing schemes tend to focus on the annoyance or irritation they cause (Peters et al.,2007). Irritation may even reduce the effectiveness of an ad and the perceived value ofan advertised product (Luo, 2002). Some researchers believe that consumers tend to beinfluenced by advertising on the Web more than by advertising on other media such astelevision. Whether they are goal-oriented or experiential shoppers, consumers areusually highly focused when they shop online. According to market studies, the Web isa trading platform that nurtures the e-shopping processes – from searching andrequesting target products/services, to evaluating and selecting purchase options, tofinal ordering, delivery and payment. Therefore, online shopping is viewed as avoluntary behavior in which consumers become more active and autonomous during atransaction (Hoffman and Novak, 1997; Chu and Lu, 2007). Therefore, understandingthe impact of the irritation in the e-shopping process is essential. This leads to thefollowing hypotheses:

H4. Web irritation will have a negative effect on perceived ease of use.

H5. Web irritation will have a negative effect on attitude towards the Web.

Figure 2.The research model


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Understanding new communication processes and user interactions in the blogs isimportant (Sangwan, 2005; Lin, 2007), and U&G provides a user-level view as opposedto a mass-exposure perspective of media use. From the earliest to the most recentapplications, U&G has proven reliable for constructing profiles of intended use andresulting user satisfaction. The U&G approach is a “how and why” approach tounderstand media use motivation, as gratification is defined by users as thesatisfaction of actively using the medium in question (Liang et al., 2006). The followinghypothesis is therefore proposed:

H6. Web satisfaction will have a positive effect on behavioral intention.

MethodologyInstrument developmentThe measures used to operationalize the constructs included in the investigated modelswere mainly adapted from previous studies with minor modifications to tailor them tothe targeted context. Items for perceived usefulness, perceived ease of use, intention touse, and actual use were adapted from Chen et al. (2002) and Davis (1989); items fromattitude towards the Web were adapted from Chen and Wells (1999) and Ajzen (1991);items from entertainment gratification and Web irritation were adapted from Chen andWells (1999), Ducoffe (1996) and Korgaonkar and Wolin (1999). The attributes werethen summarized to create a survey instrument, which asks respondents to indicate theextent to which they agree/disagree with each statement about shopping on B2CWebsites. Each item was rated on a scale from 1 (strongly disagree) to 7 (stronglyagree). This approach was used earlier in Venkatesh and Davis (2000) and Chau andHu (2001) to focus model comparisons on substantive rather than measurementconcerns.

However, according to Zmud and Boynton (1991), refining the instrument throughpre-testing and pilot testing of typical respondents satisfied face validity criteria. Theinstrument was first evaluated for content validity by two IS scholars then furthertested for reliability, item consistency, ease of understanding and question sequenceappropriateness. Hence, a pretest was also given to increase the face validity. Thepretest subjects were part-time graduate students in a masters program tailored toworking students in a Taiwan public university in which candidates received collegecredit. The pretest subjects were full-time employees in various profit and non-profitorganizations, and each had at least three years of working experiences when theyenrolled the graduate program. They were generally full-time employees with familiesand were considered representative of general consumers in Taiwan. Additionally, allpretest members had Internet experience, including email, Weblogging, instantmessaging, online shopping and online content reading. The widely varying modes ofInternet use make the e-consumer population difficult to characterize. Therefore, noappropriate framework for random samples was available.

In total, 52 EMBA students were asked to complete the questionnaire. Comments onquestion sequence, word choice and measures were solicited for use for furtherrefinement of the questionnaire. Based on the pretest feedback, several items wereremoved from the instrument. Table II lists the final questionnaire items used tomeasure each construct together with their source of reference. Pretest subjects wereexcluded from further participation.

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Items Sources

Entertainment Adapted from Chen et al. (2002),Surfing on the Web is entertaining to me Ducoffe (1996),I think the Web is fun to use and Korgaonkar and Wolin (1999)I feel excited when surfing on the WebI enjoy surfing the WebI think the Web is cool

IrritationI think the Web is irritatingThe Web is annoying to meI feel that the Web is confusingI think the Web is messyThe Web is deceptive to me

Satisfaction Adapted from Chen and Wells (1999)I feel satisfied with the ease of use of the WebI am satisfied with information on the WebI am satisfied with online product and servicesI feel satisfied with the prices on the WebOverall, I am satisfied with the Web

Perceived usefulness Adapted from Chen and Wells (1999)Using the Web would enable me to accomplish shopping orinformation seeking more quickly than using traditionalstores

and Davis (1989)

Using the Web would improve my performance in shoppingor information seeking (e.g. save time or money)Using the Web would increase my productivity in shoppingor information seeking (e.g. make purchase decisions or findproduct information within the shortest time frame)Using the Web would enhance my effectiveness in shoppingor information seeking (e.g. get the best deal or find the mostinformation about a product)Using the Web would make it easier for me to shop or findinformationI find the Web very useful in my shopping or informationseeking

Perceived ease of use Adapted from Chen and Wells (1999)Learning to use the Web is easy for me and Davis (1989)I find it easy to use the Web to find what I wantMy interaction with the Web is clear and understandableI find the Web to be flexible to interact withIt is easy for me to become skillful at using the WebI find the Web easy to use

Attitude toward the Web Adapted from Chen and Wells (1999)Using the Web is convenient and Ajzen (1991)Using the Web saves me timeThe fact that I cannot see the actual products makes methink twice about using the Web

(continued )Table II.

Instrument


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Sample and data collectionWeb surveys indicate that the characteristics of the Web user population began toreflect partial parts of the general population in the late 1990s (Korgaonkar and Wolin,1999). Web users are generally college-educated, young and have median orhigher-level income. According to Lin and Hsipeng (2000) suggestion, about 80 percentof Internet users in Taiwan are college students who are expected to become the mostactive Internet users and consumers in the near future. This survey therefore surveyedundergraduate and graduate students in three different universities in Taiwan.

The EMBA sample members were students in universities throughout Taiwan.Most were working students with full-time day jobs. All EMBA students had at leastthree years of working experience before enrolling in the graduate program. TheseEMBA sample members tended to be diverse. Undergraduate sample members werestudents in universities widely dispersed throughout the country and were generallyyounger than the EMBA sample members. Thus, 300 questionnaires were distributedto marketing and e-commerce classes. Of the 290 surveys returned, 238 validquestionnaires were analyzed in this study.

Table III summarized the demographic profile of the respondents. The respondentswere a diverse sample: 63 percent of the respondents were female; 37 percent weremale. Age range was from 18 to 42 years old with 61 percent 20 years old or younger,35 percent between 21 and 30, and 4 percent over 31. More than 80 percent had used theInternet for more than four years. Moreover, 55.9 percent of the respondents reportedthey had purchased a product over the Internet at least once.

The instrument was examined to establish the construct factor structures andreliabilities of scales. Factors (i.e. constructs) specified in each investigated model wereevaluated in terms of reliability, convergent validity and discriminant validity.Instrument reliability is often estimated by Chronbach’s alpha (a). Hair et al. (1998)suggested that a should be at least 0.70. As Table IV shows, Cronbach a in thisresearch ranged from 0.6925 to 0.8987 indicating acceptable reliability.

Items Sources

Using the Web puts my privacy at riskUsing the Web makes me lose social contact (can be apositive belief or a negative belief)Using the Web saves me moneyThe Web has a larger product selection than traditionalstores

Behavioral intention to use Adapted from Davis (1989)I intend to use the Web to purchase a productI intend to use the Web to seek product informationI intend to use the Web for fun

Actual use Adapted from Davis (1989)How often do you use the Web for purchase or informationseeking?How many times have you used the Web for purchase orinformation seeking in the last six months?Table II.

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Entertainment gratification, Web irritation, perceived usefulness, perceived ease ofuse, satisfaction, attitude and behavioral intention were estimated using confirmatoryfactor analyses. Most items exhibited a loading greater than 0.5 on their respectivefactors, signifying a positive convergent validity. The only exception was the fourthitem, entertainment, which had a loading slightly below 0.5. After deleting this item,the CFA results of both models exhibited adequate convergent validity. Table V showsthe correlations between constructs.

Data analysis and resultsThe hypothesized paths for each model were tested using EQS, which is arecommended technique for comparing alternative theoretical models (Joreskog andSorbom, 1993); it is also particularly appropriate for testing well-developed theories(Barclay et al., 1995). Except for behavior, each construct was analyzed as a singleindicator using the mean of summated scale adjusted to form a 7-point measure.

The overall fit, predictive power and significance of paths were all considered. TheR 2 for each dependent construct was examined to assess explanatory power andsignificance of individual paths. Seven common goodness-of-fit models were tested:chi-square/d.f., goodness-of-fit index (GFI), adjusted goodness-of-fit index (AGFI), rootmean square residual (RMR), norm fit index (NFI), non-norm fit index (NNFI) andcomparative fit index (CFI). If a model is inconsistent with empirical data, the commonprocedures for modification are Lagrange Multiplier Index (LM) and the Wald Test.The LM tests whether adding free parameters improves model fitness; conversely, theWald test checks whether removing free parameters improves model fitness.

Assessing model fitness and evaluation of hypothesesPrevious studies (Legris et al., 2003) suggest that TAM should be modified to includeadditional components required to explain more than 40 percent of technology

Category Item Number %

Gender Male 87 37Female 152 63

Age Under 20 146 61.121-30 84 35.1Over 31 9 3.8

Websites experience Less than 3 years 22 9.23-4 years 19 7.94-5 years 30 12.55-6 years 52 21.8Over 6 years 116 48.4

Weekly usage Less than 5 hrs 28 11.76-10 hrs 34 14.211-15 hrs 21 8.816-20 hrs 27 11.321-25 hrs 19 7.926-30 hrs 27 11.3Over 30 hrs 83 34.7

Table III.The profile of sample


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Item Corrected item – total correlation Alpha if item deleted Cronbach a

Enter1 0.8621 0.8506 0.8987Enter2 0.7166 0.8837Enter3 0.7923 0.8667Enter4 0.7460 0.8771Enter5 0.6321 0.9004Irr1 0.7789 0.7845 0.8521Irr2 0.8209 0.7730Irr3 0.7871 0.7834Irr4 0.6777 0.8136Irr5 0.2994 0.9110PU1 0.3622 0.8394 0.8179PU2 0.3696 0.8331PU3 0.7405 0.7549PU4 0.6795 0.7668PU5 0.6768 0.7686PU6 0.7348 0.7588EOU1 0.5938 0.7800 0.8128EOU2 0.6886 0.7561EOU3 0.7435 0.7453EOU4 0.3097 0.8364EOU5 0.3558 0.8333EOU6 0.8172 0.7272ATT1 0.5381 0.6593 0.6925ATT2 0.4582 0.0.6541ATT3 0.4109 0.6640ATT4 0.4931 0.6545ATT5 0.4045 0.6616ATT6 0.5945 0.6432ATT7 0.6056 0.6453SAT1 0.6801 0.7569 0.8040SAT2 0.6567 0.7618SAT3 0.6967 0.7484SAT4 0.4100 0.8478SAT5 0.6468 0.7714Int1 0.7424 0.7261 0.8074Int2 0.6340 0.7593Int3 0.6438 0.7546

Table IV.Item-total correlation

1 2 3 4 5 6 7 8

1 Entertainment 12 Irritation 22.41 * * 13 Perceived usefulness 0.458 * * 0.240 * * 14 Perceived ease of use 0.306 * * 0.238 * * 0.572 * * 15 Attitude 0.489 * * 0.361 * * 0.618 * * 0.583 * * 16 Satisfaction 0.423 * * 0.329 * * 0.641 * * 0.662 * * 0.754 * * 17 Intention to use 0.353 * * 0.191 * * 0.508 * * 0.562 * * 0.540 * * 0.711 * * 18 Usage 0.16 * 20.84 0.076 * * 0.149 * 0.122 0.132 0.121 1

Table V.Construct correlations

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acceptance and use. Therefore, the integrated model in Figure 3 was derived from U&Gand TAM. Attitude is determined by perceived usefulness, perceived ease of use,entertainment and irritation. Behavior intention is influenced by attitude towards theWeb and user satisfaction. The overall statistical analyses indicated a satisfactory fitof the modified model to the empirical data (x2 ¼ 2:427, p , 0.01; AGFI ¼ 0:914.RMR ¼ 0:049, NFI ¼ 0:950, CFI ¼ 0:969). Although the x2 value was significant, allother statistics were within an acceptable range, suggesting a good fit. The modelaccounted for 3.7; 56.8 percent; 65.5 percent and 56.8 percent of the variance inbehavior, intention, satisfaction and attitude, respectively. As Figure 3 shows, mostpath coefficients were as hypothesized (see Table VI).

Assessing integrated model using the original TAMThe overall fit indicated that TAM also provided a good fit to the data (x2 ¼ 3:931, p,0.01; AGFI ¼ 0:910. RMR ¼ 0:049, NFI ¼ 0:959, CFI ¼ 0:969). Although thex2 valuewas significant, all other fit statistics were within an acceptable range, suggesting agood fit. The model accounted for 3.7 percent of variance in behavior, 45 percent ofvariance in intention and 52.2 percent in attitude. As indicated in Figure 4, most pathcoefficients were significant. The paths from ease of use to perceived usefulness andattitude were significant as were the paths from perceived usefulness to attitude andintention and the path from intention to behavior. Figure 4 shows that perceivedusefulness and ease of use both significantly affected on attitude, intention and usage.

Overall, the two models exhibited a comparable fit to the data based on themeasures presented in Table VII. Both the integrated model and the original TAMmodels explained a significant proportion of the variance in e-consumer behaviors. Theoriginal TAM model accounted for 52.2 percent of the variance and the integratedmodel explained 56.8 percent of the attitude variance. Moreover, the integrated modelaccounted for 56.8 percent of the variance in behavioral intention toward Websitescompared to 45 percent variance in the original TAM model.

Figure 3.Path coefficients for the

integrated model


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Discussion and conclusionThis study integrated U&G theory with a technology acceptance model by includingtwo U&G behaviors which elucidate e-consumer behaviors toward Web use. Bycombing theoretical paradigms from information systems and mass media, the dualnature of the e-consumer as an online shopper and a new medium user was confirmed.In accordance with current literature in mass media, the original TAM model proposedby Davis (1989) was used to test the hypotheses that perceived usefulness and ease ofuse would be affected by perceived content present on the medium and the browsing

Latent dependentvariable

Latent independentvariable Indirect effect Direct effect Total effect Z value

Attitude Entertainment N/A 0.172 0.172 3.96 * *

Irritation 20.159 20.178 20.337 20.5848 * *

Perceived usefulness N/A 0.285 0.285 6.078 * *

Perceived ease of use N/A 0.496 0.603 12.532 * *

Satisfaction Entertainment 0.138 N/A 0.138 3.890 * *

Irritation 20.271 N/A 20.271 25.631 * *

Perceived usefulness 0.229 N/A 0.009 5.835 * *

Perceived ease of use 0.485 N/A 0.485 10.743 * *

Attitude N/A 0.804 0.804 20.864 * *

Intention to use Entertainment 0.114 N/A 0.114 3.804 * *

Irritation 20.224 N/A 20.224 25.377 * *



Attitude 0.469 0.195 0.664 13.688 * *

Satisfaction N/A 0.583 0.583 8.069 * *

Usage Entertainment 0.022 N/A 0.022 2.349 *

Irritation 20.043 N/A 20.043 22.611 * *



Attitude 0.126 N/A 0.126 2.918 * *

Satisfaction 0.111 N/A 0.111 2.801 * *

Intention to use N/A 0.190 0.190 2.987 * *

Table VI.Direct, indirect and totaleffects

Figure 4.Path coefficients for thetechnology acceptancemodel

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process of B2C Website. The analytical results showed that psychological variablesand perceptional constructs of the Web are important predictors of e-consumerbehavior. Entertainment gratification, irritation surfing experience (mass medium),perceived usefulness and ease of use of the Web (information systems) are importantpredictors of e-consumer intention to use, purchase and seeking information. Severalinteresting findings and implications are discussed in the following sections.

The findings confirmed the TAM assumption that behavioral intention predictse-consumer behavior, which is consistent with previous studies (Davis, 1989; Yiu et al.,2007). As Figure 3 shows, the variance in usage explained (R 2) in this study was only3.7 percent, which was much lower than that for intention (R 2 ¼ 56.8 percent). Toclarify this point, the original TAM model, in Figure 4 was examined, and itsexplanatory power was congruent. However, further studies are needed to clarify thisissue.

The proposed model revealed higher variance in intention explained (R 2 ¼ 56.8percent) then the 45 percent variance observed in the original TAM model. Satisfactionwith the Web use was the strongest predictor of e-consumer intention to use followedby attitude which was a significant but weaker predictor. Higher perceived satisfactionand attitude toward Websites were associated with higher intention to use. Thesefindings confirmed the Premkumar and Bhattacherjee (2008) argument thatsatisfaction with transaction experience may be critical for retaining user loyaltyand continuance of that service.

Increased entertainment gratification, favorable perceived usefulness and ease ofuse as well as lower feelings of irritation were associated with increased perception ofattitude toward B2C Websites. Perceived ease of use was the strongest predictor ofe-consumer attitudes followed by perceived usefulness, irritation and entertainment.Therefore, the data suggests that online merchants should focus on minimizing thecomplexity of online shopping and provide user-friendly features such as the “1-Click”feature available on the Amazon Website, or other aids such as avatars, shopping bots,etc.

TAM Research model Recommended value

Fit indexFIT 0.959 0.950 .¼ 0:9x2/DF 3.931 2.427 ,¼ 3 or ,¼ 5GFI 0.970 0.962 .¼ 0:9AGFI 0.901 0.914 .¼ 0:9RMR 0.049 0.049 ,¼ 0:08NFI 0.959 0.950 .¼ 0:9NNFI 0.938 0.946 .¼ 0:9CFI 0.969 0.969 .¼ 0:9Explanatory powerR2

B 0.037 0.037R2

BI 0.522 0.568R2

ATAM 0.522R2

ANew 0.568

Note: * p , 0.001

Table VII.Fit index and explanatory

power of the models


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The findings also indicate that feelings of irritation negatively impact perceivedease of use, conversely, entertainment gratification positively impact perceived ease ofuse. Consistent with previous U&G research (Luo, 2002; Ko et al., 2005), consumerswith high entertainment gratification and low irritation tend to have favorableperceptions of online shopping. Consumers who have high gratification withentertainment experience are more likely to prefer entertainment-specific Websites;consumers who have experienced high irritation are more likely to prefer non-irritatingWebsites. Consumers tend to prefer entertainment-specific Websites evaluate suchWebsites more positively, which leads to positive perceptions of ease of use andattitude toward the Websites. Again, consumers who prefer non-irritating Websitestend to assess them more positively, which increases perceived ease of use and positiveattitude toward such Websites.

Theoretical implicationsThis study elucidates the dual nature of e-consumers by using a theoretically groundedapproach based on the technology acceptance model. This model addresses theoften-cited need to understand the gap of user acceptance of B2C Websites in thecontext of medium effect (Luo, 2002; Wolfinbarger and Gilly, 2001). The findingsdemonstrate that a TAM-based model can explain a significant amount of variance inuse intention. Most importantly, two major communication and interaction constructswere theoretically and empirically tested. The research model shows that Web use bye-consumers depends on their Web attitude and satisfaction and confirms thate-consumer attitudes depend on individual perceptions (usefulness and ease of use) andWeb functions (e.g. entertainment, irritation, etc.). Thus, this study makes an importanttheoretical contribution to explaining the medium effect phenomenon.

In the field of technology acceptance, the structure of the model was consistent withprevious theory and research on antecedents-beliefs-attitude-behavior. This analysisfocused on those constructs that may affect Web use by e-consumers for any purposes.To understand this, our argument was based on the propositions and findings ofprevious studies (Chen et al., 2002; Koufaris, 2002; O’Cass and Fenech, 2003; Shih, 2004)indicating the appropriateness of extending the TAM analysis. Similar to these studies,we posited that two constructs, perceived usefulness and perceived ease of use, mediateall external variables likely to influence consumer decisions to use the Web. Thesefindings are consistent with the theoretical foundation for understanding Webbehavior established elsewhere. These analytical results indicate that antecedents(entertainment and irritation) differentially affect e-consumer beliefs (perceivedusefulness and perceived ease of use). The beliefs of e-consumers affect attitudestoward the Web; attitudes affect satisfaction with the Web and intention to use;satisfaction and attitudes affect intention to use; and intention affects actual behavior.Also, from an e-consumer perspective, the Web is apparently most enjoyable when itmatches the surfing and media needs of users (Wolfinbarger and Gilly, 2001) andprovides them with a user-friendly processing experience.

Regarding uses and gratifications, although ease of use and usefulness areperceived as important issues in traditional IS environments, U&G provides managerswith a different perspective. Building on recent applications of U&G, this studyprovides perspectives about media uses and gratification which can serve asantecedents affecting perceptual factors and offers operational examples of B2C

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Websites. The findings here indicate that the Web is a unique mass communicationmedium since variables predictive of behavior in other mass media do not alwaysapply. Another possibility may be that entertainment gratification has no effect onperceived usefulness. Arguable, entertainment is related to whether or not ane-consumer finds a Website useful. Finally, entertainment conceivably affects initialperceptions of the Web, but its importance declines with continued use of the Web.Further longitudinal research is needed to clarify the entertainment effect.

The implications for practitionersThese findings have several practical implications. Most B2C merchants understandwhat variables affecting e-consumer behavior beyond information system disciplinesare critical to effective managing and assessing their Websites. Fewer visits reducerevenue/profit, which could discourage merchants and investors and eventually forcethem to leave the online market. The integrated findings of this research explain whysome poor B2C Websites often fail.

Practitioners must focus on e-consumers intention to use the Web as a strongmechanism for encouraging e-consumers to revisit the Web. To create positiveintention they should focus on enhancing overall satisfaction and positive attitudestoward the Web. User satisfaction can be increased by retaining who are satisfied.Retention can be achieved by satisfying customer needs by providing user-friendlyfunctions, specific features, quality information, good combinations of products andservices and competitive pricing strategies.

To ensure e-consumers satisfaction with the Web, vendors must create a positiveattitude toward B2C Websites use. Based on the findings of this study, attitudes can beenhanced when online merchants provide a convenient and safe environment,cost-savings and a larger product selection. Again, to create positive attitudes, theyshould focus on creating strong perceptions that the Web is easy to use, enjoyable, andefficient. To satisfy customer needs by providing quick and effective identificationthrough smart user interface designs, online merchant should be mindful of theentertainment and appreciation that consumers derive from customized contentdelivery and display. Understanding important Web uses and gratifications can guidemanagers in fine tuning their e-commerce Websites. Finally, practitioners should focusnot just on providing an interesting and enjoyable interface for obtaining productinformation but also on reducing the negative feelings toward the process of accessingproduct information and minimizing the irritation of irrelevant and obtrusiveadvertisements. Providing entertaining content and a simple, streamlined processwould increase perceived ease of use.

This study has several notable limitations. First, this study posits an extension totheories of e-commerce technology. Several possible issues raised by the Web studyinclude the generalizability of the results to other settings and technologies andoperationalization of the study constructs. Second, the integrated model should beinterpreted cautiously when applied to predict the behavior of light users, or whenextending the results to elder consumers. Only 11.7 percent of the respondents reportedweekly Internet usage of less than five hours, which may have produced inconsistentfindings for cognitive impacts when comparing individual perceptions and Webfunction recognition between light, normal, and heavy users. Further research issuggested to clarify this issue. Finally, the ideal sampling frame for stratified random


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sampling was undetermined, given the diversity of location, age, occupation andincome in this study sample. Additional data for B2C Websites is needed to clarify thisissue.

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Further reading

Castaneda, J.A., Munoz-Leiva, F. and Luque, T. (2007), “Web Acceptance Model (WAM):moderating effects of user experience”, Information & Management, Vol. 44, pp. 384-96.

Karahanna, E. and Straub, D.W. (1999), “The psychological origins of perceived usefulness andease-of-use”, Information & Management, Vol. 35, pp. 237-50.


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Karahanna, E., Straub, D.W. and Chervany, N.L. (1999), “Information technology adoption acrosstime: a cross-sectional comparison of preadoption and post-adoption beliefs”, MISQuarterly, Vol. 23, pp. 183-213.

Kiesler, S. (1997), Culture of the Internet, Erlbaum, Mahwah, NJ.

LaRose, R. and Eastin, M.S. (2004), “A social cognitive theory of internet uses and gratifications:toward a new model of media attendance”, Journal of Broadcasting & Electronic Media,Vol. 48 No. 3, pp. 358-77.

Maignan, I. and Lukas, B.A. (1997), “The nature and social uses of the Internet: a qualitativeinvestigation”, The Journal of Consumer Affairs, Vol. 31 No. 2, pp. 346-71.

Mukherji, J., Mukherji, A. and Nicovich, S. (1998), Understanding Dependency and Use of theInternet: A Uses and Gratifications Perspective, American Marketing Association, Boston,MA.

Perse, E. and Dunn, D. (1998), “The utility of home computers and media use: implications ofmultimedia and connectivity”, Journal of Broadcasting and Electronic Media, Vol. 42 No. 4,pp. 435-56.

Peterson, R.A., Balasubramanian, S. and Bronneberg, B.J. (1997), “Exploring the implication ofthe Internet for consumer marketing”, Journal of the Academy of Marketing Science, Vol. 25No. 4, pp. 329-46.

Rao, H.R., Salam, A. and DosSantos, B.L. (1998), “Marketing and the Internet”, Communicationsof the ACM, Vol. 41 No. 3, pp. 32-4.

Stafford, T.F., Stafford, M.R. and Schkade, L.L. (2004), “Determining uses and gratifications forthe Internet”, Decision Science, Vol. 35 No. 2, pp. 259-88.

Corresponding authorEcho Huang can be contacted at: [email protected]

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