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169l APRIL 2012 l International Journal of Sports Marketing & Sponsorship

Executive summary

As the number of online sports fans increases, sportsorganisations have started to use the internet as amarketing tool for maintaining sports fans’Involvement by providing news, scores, individualblogs, online stores and fan forums. Despite theinterest of sports businesses in developing their web-based interaction with consumers, little is knownabout what attracts sports fans to use certainwebsites. sports fans’ choices to visit particular sport-related websites may be based on different factorsthan those commonly underlying

people’s choices to use other types of websites.Accordingly, the purpose of this study is to examinedeterminants that influence online sports fans’ use ofsports web portals (e.g. www.espn.go.com,www.foxsport.com).

This study analyses the psychometric properties ofHur, Ko & Claussen’s (2007) Sport Web AcceptanceModel (SWAM) and attempts to explain why and howsports fans accept and use sports web portals to seeksport-related information. It proposes a competingmodel that extends the SWAM by incorporating two


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Determinants of using sports web portals: an empirical examination of the Sport WebsiteAcceptance Model

Keywordssports web portalsonline informationconsumption behaviour

Abstract

This study empirically tested the Sport WebsiteAcceptance Model (SWAM), proposed by Hur, Ko andClaussen (2007). The SWAM added PerceivedEnjoyment (Davis et al, 1992) and PerceivedTrustworthiness (Belanger et al, 2002) to the twofactors Perceived Ease of Use and Perceived Usefulnessused in the Technology Acceptance Model (TAM)(Davis, 1989). This study proposes a competing modelto the original SWAM and compares this byincorporating two additional constructs, SportInvolvement (Shank & Beasley, 1998) andPsychological Commitment to a Team (Mahony et al,2000). Structural equation modeling analyses revealedacceptable model fits, both in the original SWAM and inthe competing model. Subsequent analyses led theauthors to conclude that the competing model was thebetter version of the SWAM.

Youngjin HurAssistant Professor, Sport Management ProgramRoom 132, Morrow Building, University of Central Missouri, USATel: +660 543 4172Email: [email protected]

Yong Jae KoAssociate Professor, University of Florida

Cathryn L. Claussen Professor, Washington State University

Peer reviewed

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salient consumer variables: Sport Involvement (Shank& Beasley, 1998) and Psychological Commitment to aTeam (Mahony et al, 2000).

This research employs a convenience samplingmethod and was carried out on students at a largeuniversity in the north-west region of the UnitedStates. The sample consists of 198 (58.8%) malesand 139 (41.2%) females.

A structural equation modeling analysis showed anacceptable model fit with x 2=900.37, df=444;RMSEA=.055; CFI=.94. Of the ten hypotheses putforward in this study, six hypotheses were supportedand four were rejected at p<.05. The results of thehypotheses tests showed relatively small effects ofSport Involvement and Psychological Commitment to aTeam on Intention and Actual Usage. These resultsindicate that potential mediating variables may existbetween the relationships. This research, therefore,modifies the SWAM model by treating the four sportsfans’ beliefs, employed in the original SWAM(Perceived Ease of Use, Perceived Usefulness,Perceived Enjoyment and Perceived Trustworthiness)as mediating variables between the constructs of SportInvolvement and Commitment and the consumers’Behavioural Intention and Actual Usage, in the contextof a sports web portal.

The main findings of this study are that, amongsports fans, Perceived Enjoyment is the most importantdeterminant of Intention to Use and Actual Use ofsports web portals. Although these portals are usefulsources for favourite team information, game scores,player statistics, game schedules etc., sports fans aremore likely to visit when they feel that the portal itselfwill add to their enjoyment. In addition – according tothe results of the competing model analysis – SportInvolvement and Psychological Commitment are morelikely to indirectly influence Behavioural Intention andActual Use through the four identified sports fans’beliefs.

This study is expected to contribute towards fillingthe gap in current literature between sports marketingtheory and management information systems theory.Its conceptual framework may become a fundamental

base for understanding sports fans’ online informationconsumption behaviours. Sports marketers shouldrealise that the four identified sports fans’ beliefs,when applied to the online sport consumption context,link high Involvement levels in sport and high levels ofCommitment to a Team with fans’ Intention to use,and Actual Use, of sports web portals.

Introduction

According to Internet World Stats (2007), more than1.32 billion people (20% of the total worldpopulation) pursue various activities through theinternet. More than 238 million people (71.1% of thetotal population) in North America access the internetfor email activity, for information and to purchaseproducts online. As a result, online business hasbecome an important segment of the economy.

The internet also gives sports consumers easy accessto key information about their favourite organisationsand products (e.g. teams and retail sporting goods). Inthis study, online sports fans are defined as sportsconsumers who have purchased sport-related productsonline, obtained sport-related information online,downloaded game highlights, or shared their opinionsonline about sport-related issues (e.g. trade of players orhiring of a new coach). The number of online sportsfans is increasing. For example, Madden (2003)reported a 73% increase between 2000 and 2002 inthe number of people who went online for sportsinformation, and about 44% of internet users have usedthe internet to look for sport-related information. Forexample, www.espn.go.com alone had 1.2 billion visitsfrom January to November 2006 (Stories of the Year,2006).

As the number of online sports fans increases,sports organisations have started to use the internet asa marketing tool for maintaining sports faninvolvement by providing news, scores, individualblogs, online stores and fan forums. For example,professional sports organisations in the US, such asthe National Football League (NFL) and the National

Using sports web portals

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Basketball Association (NBA), have changed theirofficial websites. The new websites have visualappeal, revamped individual blogs and socialnetworking spaces in which sports fans can sharetheir opinions and make bargains for sports eventtickets (Stories of the Year, 2006). Recently,www.nbc.com provided live game and replay videocontent of the 2008 Beijing Olympics atwww.nbcolympics.com. This trend demonstrates thelarge and growing influence of the internet on thesports industry (Evans & Smith, 2004).

Despite the interest of sports businesses indeveloping their use of web-based interaction withconsumers, little is actually known about what attractssports fans to use certain websites. sports fans’choices of particular sport-related websites may befounded upon different factors than those commonlyunderlying people’s choices to use other types ofwebsites. Accordingly, the purpose of this study is toexamine determinants that influence online sportsfans’ use of sports web portals, such aswww.espn.go.com and www.foxsport.com. This studyanalyses the psychometric properties of Hur, Ko, &Claussen’s (2007) SWAM. It proposes a competingmodel that attempts to explain why/how sports fansaccept sports web portals when they use them to seeksport-related information. The SWAM was developedby incorporating elements of the TRA (Fishbein &Ajzen, 1975); the TAM (Davis, 1989; Davis, Bagozzi& Warshaw, 1989); and a framework of Involvement,commitment, and loyalty (Iwasaki & Havitz, 2004).

Research in sports websites

sports websites can serve as strategic tools for sportsorganisations and can provide convenient linksbetween sports fans and organisations. Accordingly,sports organisations increasingly rely on websites toaccomplish their marketing goals and to improvecustomer satisfaction. For this reason, scholars in thesports management field have paid increasingattention to marketing opportunities through sports

websites and sports fans’ behaviour on websites.Kahle & Meeske (1999) identified characteristics andpotential roles of the internet in sports business;Caskey & Delpy (1999) proposed revenue models ofsports websites; Delpy & Bosetti (1999) identifieddemographic profiles of internet users; Smith, Pent &Pitts (1999) conducted content analysis of stadiumwebsites; and Turner (1999) introduced integration ofTV broadcasts and the internet. While these studieshighlighted the importance and function of the internetand sports websites, more recent studies haveattempted to understand the users of sports websitesor specific functions of sports websites, such as virtualadvertising. Recent studies have, for example,explored sports fans’ motivation to use sports websites(Hur, Ko & Valacich, 2007; Seo & Green, 2008) andexamined marketers’ perceptions of virtual advertising(Yu, 2007) and brand awareness of virtual advertising(Tsuji, Bennett & Leigh, 2009). In addition, somescholars have examined how professional teams’websites can maximise their marketing opportunities(Carlson, Rosenberger & Muthaly, 2003; Ciletti,Lanasa, Ramos, Luchs & Lou, 2010; Evans & Smith,2004; Filo & Funk, 2005) and how more sports fanscan be attracted to newspaper websites (Butler &Sagas, 2007) or entertainment-games websites(Kitchin, 2006). Despite this research trend, fewstudies have applied and examined theoretical modelsthat explain sports fans’ use of sports websites. Thisstudy, therefore, focuses on sports fans’ behaviourwhen visiting sports web portals.

Theoretical background and hypothesisdevelopment

Theory of Reasoned Action (TRA)The TRA is a conceptual framework of distinctions andrelations among beliefs, attitudes, intentions andbehaviours (Fishbein & Ajzen, 1975). According to theTRA, an individual’s behaviour is determined byhis/her volitional intention to perform the behaviour(Fishbein & Ajzen, 1975). For example, a sports fan’s



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behaviour (e.g. visiting sports web portals) is predictedby his/her volitional intention. The intention, in turn, isinfluenced by his/her attitudes toward the behaviour.In other words, a sports fan may have beliefs about asports website, such as ‘The website is organised well’or ‘The website is easy to navigate’. Such beliefs maylead the fan to have a favourable attitude toward thewebsite. This attitude influences a set of favourableintentions to revisit the website.

Technology Acceptance Model (TAM)Davis (1989) developed the TAM based on the TRA(Fishbein & Ajzen, 1975). Originally focused onpredicting user acceptance of information technologysystems, the TAM includes two main beliefs aspredictors for Intention to Use technology systems:Perceived Usefulness and Perceived Ease of Use.Previous studies of the TAM have found it useful inthe offline context. In addition, several scholars havefound support for the usefulness of the TAM forunderstanding user behaviour in the online context(Moon & Kim, 2001; Porter & Donthu, 2006).Researchers have found support for the positive effectsof Perceived Usefulness and Perceived Ease of Use onIntention to Use technology (Davis, 1989; Davis et al,1989; Shih, 2004).

Several studies have incorporated PerceivedEnjoyment and Perceived Trustworthiness constructsinto the TAM and found that Perceived Enjoyment(Davis, Bagozzi & Warshaw, 1992; Eighmey &McCord, 1998; Jarvenpaa & Todd, 1997; Moon &Kim, 2001) and Perceived Trustworthiness (Bart,Shankar, Sultan & Urban, 2005; Reichheld &Schefter, 2000) are important antecedents of onlineconsumption behaviour. The SWAM proposed by Hur,Ko & Claussen (2007) added Perceived Enjoyment(Davis et al, 1992) and Perceived Trustworthiness(Belanger et al, 2002) to the two factors – PerceivedEase of Use and Perceived Usefulness used in theTAM (Davis, 1989). This study uses this expandedversion of the TAM, as a foundation to develop acompeting model to the SWAM. It develops fourhypotheses to examine the relationships between

sports fans’ beliefs about sports web portals and theirIntention to Use these portals.H1: Perceived ease of use of a sports web portal will

positively influence Intention to Use the portal.

H2: Perception of the Usefulness of a sports webportal will positively influence Intention to Usethe portal.

H3: Perceived Enjoyment of a sports web portal willpositively influence Intention to Use the portal.

H4: Perception of the Trustworthiness of a sportsweb portal will positively influence Intention toUse the portal.

This study then develops a further six hypotheses toexamine the effects of Sport Involvement andPsychological Commitment to a Team.

Sport InvolvementAccording to Laurent & Kapferer (1985), Involvementcauses, or motivates, a certain consequence or abehaviour, such as a consumer’s buying behaviour ora communication behaviour. Sport Involvement in thisstudy is defined, therefore, as “an unobservable stateof motivation, arousal, or interest” in watching a sportsgame or participating in a sport-related activity thatresults in “searching, information-processing anddecision-making” (Laurent & Kapferer, p.49). Anotherwidely used definition of Involvement is “a person’sperceived relevance of the object based on inherentneeds, values and interests” (Zaichkowsky. 1985,p.342). Perceived personal relevance is considered anessential element of Involvement (Celsi & Olson,1988), which means that the level of a consumer’sinvolvement with a product is largely determined bythe degree to which the product is personally relevantto him/her.

Many scholars have applied the Involvementconcept to the context of leisure and sportsconsumption (e.g. Funk, Ridinger & Moorman, 2004;Iwasaki & Havitz, 1998, 2004; Shank & Beasley,




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1998). Shank & Beasley (1998) found thatInvolvement is one of the important factors thatinfluence leisure and sport-related behaviours such asgame attendance, television viewing and commitment.Additionally, several studies have found that aconsumer who is highly involved with a website ismore likely to linger or to show the intention ofpurchasing a product at the website (e.g. Kim & Jin,2001; Richard, 2005). Therefore, the fifth hypothesisof this study was generated.

H5: Involvement level in sport will positivelyinfluence Intention to Use a sports web portal.

In the online context, a consumer who has a highlevel of Involvement with a website tends to search forproduct information there (Balabanis and Reynolds,2001). Therefore, the seventh hypothesis is asfollows:

H6: Involvement level in sport will positivelyinfluence Actual Usage of a sports web portal.

Involvement has been found to be a predictor ofPsychological Commitment (Crosby & Taylor, 1983;Iwasaki & Havitz, 1998, 2004). Therefore, therelationship between Involvement & PsychologicalCommitment to a Team is hypothesised as:

H7: Involvement level in sport will positivelyinfluence Psychological Commitment to a Team.

Psychological commitmentIn organisational behaviour theory, Commitment hasbeen found to be an important factor in determiningemployee turnover (Farrell & Rusbult, 1981). Mowday,Porter & Steers (1982) defined OrganisationalCommitment as “the relative strength of an individual’sidentification with and involvement in a particularorganisation” (p. 27). According to Pritchard, Havitz &Howard (1999), Commitment is comprised of a set of

an employee’s cognitive beliefs, which includeBehavioural Intention.

The concept of Commitment has been applied to thecontext of sports consumer behaviour. Mahony,Madrigal & Howard (2000) describe PsychologicalCommitment to a Team as a sports fan’s persistence insupporting a certain team, even when the team hasperformed poorly or changed players or coaches.Iwasaki & Havitz (2004) examined the causalrelationship between leisure Involvement,Psychological Commitment and behavioural loyalty toa recreation agency finding that PsychologicalCommitment mediates the relationship between theInvolvement and the loyalty. Eastlick, Lotz &Warrington (2006) found that Commitment to anonline retailer is one of the core components of apositive relationship between retailer and consumer, aswell as of purchase Intention. Shore & Wayne (1993)also found that an employee’s affective Commitmenthad a positive effect on organisational behaviour.Therefore, the eighth and ninth hypotheses of thisstudy were generated.

H8: Psychological Commitment to a Team willpositively influence Intention to Use a sportsweb portal.

H9: Psychological Commitment to a Team willpositively influence Actual Use of a sports webportal.

Finally, a positive effect of Intention on actualbehaviour has been supported by scholars (e.g. Davis,1989; Fishbein & Ajzen, 1975; Gefen & Straub,1997; Moon & Kim, 2001; Venkatesh & Davis,2000). Therefore, this study’s tenth hypothesis is:

H10: Intention to Use a sports web portal willpositively influence Actual Use of the portal.

These hypothetical relationships were arranged in a



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model form to comprise a competing model to theoriginal SWAM (Hur et al, 2007; see Figure 1).

Methodology

Field test and pilot studyTo refine purify the survey instrument a panel ofexperts was asked to examine the definitions of eachconstruct to be measured in order to ensure that eachitem represented the content that it was supposed tomeasure. In addition to the items themselves,

judgments about the response format, the number ofscale points and the clarity of the instructions were also made (Netemeyer, Bearden & Sharma, 2003).

Based on the recommendations from this panel,revisions were made to the scale used in the survey.

After revisions were made based on the field test, apilot study was conducted prior to the main study, this was held at a large university in the north-westernUnited States [the same university as the main study].The researchers administered the survey on 23-26 April 2007 to 127 students who were enrolledin sports management classes. The data analysis of


* (a significant path coefficient at p<.05)

x2/df=900.37/444=2.03

RMSEA=.055 (.050-.060)CFI=.94NFI=.88NNFI =.93

FIGURE 1 The results of hypothesis tests based on the original SWAM

INTENTIONSPORTS WEB PORTAL USE

PERCEIVED TRUSTWORTHINESS

.48*

.64*.11*

.05 -.03

.10*.68*-.13.17*

BELIEFS ABOUT A SPORTS WEB PORTAL

INTENTION AND BEHAVIOUR

INVOLVEMENT AND COMMITMENT

PERCEIVED ENJOYMENT

PERCEIVED USEFULNESS

PERCEIVED EASE OF USE

PSYCHOLOGICAL COMMITMENT

SPORT INVOLVEMENT

.07



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the pilot study included Cronbach’s alpha; compositereliability; Average Variance Extracted (AVE); item-to-total correlations; and factor loadings and structureusing SPSS 13.0 version and EQS 6.1 version.Cronbach’s alpha ranged between .82 (SportInvolvement) and .97 (Perceived Enjoyment);composite reliability between .85 (PsychologicalCommitment to a Team) and .96 (Perceived Ease of

Use, Usefulness, Enjoyment and Intention); and AVEbetween .38 (Psychological Commitment to a Team)and .82 (Perceived Enjoyment). Most item-to-totalcorrelations of question items of constructs met thesuggested range (e.g. between .50 to .80; Netemeyer,Boles & McMurrian, 1996).

The initial instrument for the pilot study consisted of52 items and each construct had multiple items. After


VARIABLES DESCRIPTION FREQUENCY PERCENT

GENDER MEN 198 58.8

WOMEN 139 41.2

AGE 19-20 57 17.0

21-22 203 60.2

23-25 51 15.2

> 25 24 7.2

MISSING 2 0.6

ETHNICITY CAUCASIAN (WHITE) 240 71.2

AFRICAN-AMERICAN 5 1.5

HISPANIC 9 2.7

ASIAN-AMERICAN 68 20.2

NATIVE AMERICAN 6 1.8

OTHERS 6 1.8

MISSING 3 0.9

SPORTS WEB PORTAL USAGE (FREQUENCY) LESS THAN ONCE A MONTH 64 19.0

ABOUT ONCE A MONTH 40 11.9

2 OR 3 TIMES A MONTH 78 23.1

SEVERAL TIMES A MONTH 33 9.8

ABOUT ONCE A WEEK 31 9.2

SEVERAL TIMES A WEEK 42 12.5

MORE THAN ONCE A DAY 49 14.5

SPORTS WEB PORTAL USAGE (DURATION) LESS THAN 15 MINUTES A MONTH 94 28.2

15-30 MINUTES A MONTH 108 32.0





MORE THAN 90 MINUTES A MONTH 36 10.7

TABLE 1 Description of participants (N=337)



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the analysis of the pilot study, 36 of 52 items wereincluded in the final survey instrument for the mainstudy: Involvement (10 items); PsychologicalCommitment to a Team (14Û4); Perceived Ease ofUse (6Û4); Perceived Usefulness (6Û4); PerceivedEnjoyment (6Û4); Perceived Trustworthiness (4);Intention (4); and Actual Use (2) (see Table 3).

For the TAM Davis (1989) initially developed 14items for Perceived Ease of Use and 14 items forPerceived Usefulness and then refined the scale intosix items per factor. For the TAM-related items in thepilot, we used the six item-scale for the main survey.Davis, Bagozzi & Warshaw (1989) further purified thescale into four items per construct. The four-item scalehas been validated in several studies (e.g. Davis &Venkatesh, 1996; Shih, 2004). Therefore, theresearchers were confident that the four-item scaleused in the final instrument, did measure what it wasintended to measure.

Sample characteristicsThe researchers employed a convenience samplingmethod and directly administered the surveyinstrument to students who were enrolled during thesummer of 2007 at a large university located in thenorth-west region of the United States. Therefore, thesample may not be representative of the entirepopulation of sports fans who use sports web portals.

Of a sample of 368, a total of 337 subjects completedthe survey instrument. The summary of characteristicsof subjects is presented in Table 1. The sampleconsists of 198 (58.8%) males and 139 (41.2%)females. The majority of the participants were 19-25years old (80.4%), and Caucasian (White: 71.2%).The participants’ favourite sports were football(26.5%), basketball (18.6%) and baseball (13.0%).Their favourite sports websites visited to obtaininformation about their favourite sport included theCBS website www.sportline.com (32.8%),www.espn.go.com (28.4%), andwww.sport.yahoo.com (10.1%). The participantsvisited sports web portals several times a month andspent around 15-45 minutes a month on average onthis activity.

Measures

For the purpose of this study, multiple measures foreach construct were developed and modified fromitems in existing scales. These comprised: SportInvolvement (Shank & Beasley, 1998; Zaichkowsky,1985, 1994); the TRA (Fishbein & Ajzen, 1975); theTAM (Davis, 1989; Davis et al, 1989; Davis et al,1992; Gefen, Karahanna & Straub, 2003; Moon &Kim, 2001); Perceived Enjoyment (Davis et al, 1992;


CONSTRUCT CRONBACH’S α COMPOSITE AVERAGE VARIANCE NUMBER RELIABILITY EXTRACTED OF ITEMS

SPORT INVOLVEMENT .91 .91 .50 10

PERCEIVED EASE OF USE .93 .94 .78 4

PERCEIVED USEFULNESS .93 .93 .76 4

PERCEIVED ENJOYMENT .96 .96 .84 4

PERCEIVED TRUSTWORTHINESS .92 .92 .75 4

PSYCHOLOGICAL COMMITMENT TO A TEAM .91 .90 .71 4

INTENTION .96 .96 .84 4

ACTUAL USE .75 .76 .62 2

TABLE 2 Reliability of the scale



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ITEMS MEA STANDARD LOADINGS CRITICAL DEVIATION RATIO

(P <.05)

INV1. IMPORTANT ------- UNIMPORTANT** 5.83 1.43 .74 -

INV2. BORING ------- INTERESTING 6.34 1.08 .59 8.45*

INV3. RELEVANT ------- IRRELEVANT** 5.47 1.53 .74 14.76*

INV4. EXCITING ------- UNEXCITING** 6.15 1.45 .57 8.44*

INV5. MEANS NOTHING ------- MEANS A LOT TO ME 5.85 1.33 .84 14.39*

INV6. APPEALING ------- UNAPPEALING** 5.96 1.48 .66 11.31*

INV7. FASCINATING ------- MUNDANE** 5.86 1.38 .73 12.96*

INV8. WORTHLESS ------- VALUABLE 5.95 1.24 .75 10.19*

INV9. INVOLVING ------- UNINVOLVING** 6.00 1.32 .73 11.54*

INV10. NOT NEEDED ------- NEEDED 5.88 1.33 .67 10.14*

PEU1. MY FAVOURITE SPORTS WEBSITE IS EASY TO USE. 5.23 1.40 .90 -

PEU2. LEARNING TO OPERATE MY FAVOURITE SPORTS WEBSITE IS EASY. 5.24 1.34 .93 30.51*

PEU3. MY INTERACTION WITH THE WEBSITE IS CLEAR AND UNDERSTANDABLE. 5.26 1.33 .92 24.04*

PEU4. IT IS EASY TO INTERACT WITH MY FAVOURITE SPORTS WEBSITE. 5.20 1.28 .79 15.06*

PU1. THE WEBSITE IS USEFUL FOR SEARCHING FOR SPORT-RELATED INFORMATION. 5.65 1.31 .85 -

PU2. THE WEBSITE IMPROVES MY KNOWLEDGE ABOUT SPORT. 5.56 1.31 .89 23.11*

PU3. THE WEBSITE ENABLES MY EFFECTIVENESS IN SPORT INFORMATION SEARCHING. 5.38 1.24 .91 22.34*

PU4. MY FAVOURITE SPORTS WEBSITE INCREASES MY PRODUCTIVITY IN SEARCHING FOR SPORT INFORMATION. 5.29 1.27 .84 16.92*

PE1. USING MY FAVOURITE SPORTS WEBSITE GIVES ENJOYMENT TO ME. 5.09 1.33 .92 -

PE2. USING MY FAVOURITE SPORTS WEBSITE ENTERTAINS ME. 5.16 1.41 .94 40.52*

PE3. IT IS FUN TO USE MY FAVOURITE SPORTS WEBSITE. 4.99 1.41 .92 33.04*

PE4. IT IS INTERESTING TO USE MY FAVOURITE SPORTS WEBSITE. 5.06 1.39 .89 23.76*

PT1. I BELIEVE IN THE INFORMATION THAT THE SPORTS WEBSITE PROVIDES ME. 5.47 1.31 .76 -

PT2. MY FAVOURITE SPORTS WEBSITE WOULD BE HONEST AND TRUTHFUL. 5.64 1.29 .90 16.03*

PT3. I WOULD BE ABLE TO TRUST MY FAVOURITE SPORTS WEBSITE COMPLETELY. 5.39 1.38 .91 14.40*

PT4. MY FAVOURITE SPORTS WEBSITE WILL BE SINCERE IN ITS PROMISES. 5.18 1.39 .90 13.75*

PCT1. BEING A FAN OF MY FAVOURITE SPORT TEAM IS IMPORTANT TO ME. 5.59 1.50 .88 -

PCT2. I AM A COMMITTED FAN OF MY FAVOURITE SPORT TEAM. 5.47 1.50 .92 25.69*

PCT3. IT WOULD BE UNLIKELY FOR ME TO CHANGE MY ALLEGIANCE FROM MY FAVOURITE SPORT TEAM TO ANOTHER. 5.61 1.43 .74 14.73*

PCT4. IT WOULD BE DIFFICULT TO CHANGE MY BELIEF ABOUT MY FAVOURITE SPORT TEAMS. 5.45 1.46 .80 15.39*

INT1. I WILL USE MY FAVOURITE SPORTS WEBSITE ON A REGULAR BASIS IN THE FUTURE. 4.80 1.75 .91 -

INT2. I WILL FREQUENTLY USE MY FAVOURITE SPORTS WEBSITE IN THE FUTURE. 4.72 1.73 .91 36.78*

INT3. ASSUMING I HAVE ACCESS TO THE INTERNET, I INTEND TO USE MY FAVOURITE SPORTS WEBSITE. 4.99 1.67 .93 30.21*

INT4. GIVEN THAT I HAVE ACCESS TO THE INTERNET, I PREDICT THAT I WOULD USE MY FAVOURITE SPORTS WEBSITE. 5.14 1.64 .92 25.72*

USE1. HOW FREQUENTLY DO YOU USE YOUR FAVOURITE SPORTS WEBSITE THAT YOU CHECKED ABOVE? 3.74 2.06 .88 -

USE2. HOW MUCH TIME YOU SPEND IN USING YOUR FAVOURITE SPORTS WEBSITE THAT YOU CHECKED ABOVE DURING A MONTH? 2.75 1.88 .69 11.46*

TABLE 3 Means, standard deviations, factor loadings and critical ratios of the measure items

Note: INV (sport involvement); PEU (perceived ease of use); * (significant at p < .05), ** (a reversed item).PU (perceived usefulness); PE (perceived enjoyment); PT (perceived trustworthiness): * (significant at p < .05).PCT (psychological commitment to a team); INT (intention to use); USE (actual usage); * (significant at p<.05).



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Moon & Kim, 2001); Perceived Trustworthiness(Eastlick et al, 2006; Koufaris & Hampton-Sosa,2004); Psychological Commitment to a Team(Mahony et al, 2000). The Sport Involvementmeasure included a seven-point semantic differentialscale and the format for the other measures was aseven-point Likert scale format ranging from (1)“Strongly Disagree” to (7) “Strongly Agree” (see Table3). For the measure of Actual Use, frequency andduration of using a sports web portal were utilised(see Table 1). In addition to the measures of eightconstructs, other questions (e.g. favourite sport,favourite sports web portals, age and gender) wereadded to the main survey. For example, we asked“What is your most favourite sport?” and “Which isyour most favourite sports website to obtain theinformation about your favourite sport?”

Data analysis proceduresTo test the efficacy of the proposed competing model,the researchers employed Structural EquationModeling (SEM) with EQS 6.1. The first step was totest a full measurement model including all constructsof the original SWAM model and to test the reliability(i.e. Cronbach’s alpha, composite reliability and AVEand the validity of the measures. The second step wasto test the structural model.

Results

Measurement model, reliability and validity testsA Confirmatory Factor Analysis (CFA) was conductedto examine the psychometric properties of themeasures. The measurement model yielded anacceptable model fit (x 2=785.05, df=436;RMSEA=.049; CFI=.95).

Cronbach’s alpha estimates for constructs in thisstudy ranged between .75 (Actual Usage) and .96(Perceived Enjoyment and Intention). Compositereliability scores of latent constructs ranged between .76(Actual Usage) and .96 (Perceived Enjoyment andIntention), all exceeding .70, which is the rule-of-thumbminimum level (Fornell & Larcker, 1981). The AVEvalues ranged between .50 (Sport Involvement) and .84(Perceived Enjoyment and Intention; see Table 2).

Evidence of convergent validity is established byhigh factor loadings in this study (DeVellis, 1991;Netemeyer et al, 2003). Each measurement scaleitem’s loading on each factor was greater than thesuggested value of .70 (Hair, Anderson, Tatham &Black, 1998; see Table 3). Additionally, critical ratiosof indicators of constructs ranged between 8.44 and40.52, which are greater than the significant value,1.96 at p<.05 (Hair et al). The results are consistentwith those of previous TAM-related studies (e.g. Davis,


INV PEU PU PE PT PCT INTENTION USAGE

SPORT INVOLVEMENT .50 .08 .15 .13 .11 .18 .20 .10

PERCEIVED EASE OF USE .28 .78 .55 .53 .32 .27 .46 .28

PERCEIVED USEFULNESS .39 .74 .76 .58 .44 .36 .42 .17

PERCEIVED ENJOYMENT .36 .73 .76 .84 .34 .35 .67 .34

PERCEIVED TRUSTWORTHINESS .33 .57 .66 .58 .75 .37 .32 .10

PSYCHOLOGICAL COMMITMENT .42 .52 .60 .59 .61 .71 .31 .13

INTENTION .40 .68 .65 .82 .57 .56 .84 .44

ACTUAL USE .31 .53 .41 .58 .31 .36 .66 .62

TABLE 4 Correlations and squared correlations between constructs

Note: The figures underlined represent AVE; Figures below the AVE line are the correlations between the constructs;Figures above the AVE line represent squared correlations between the constructs.



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1989; Moon & Kim, 2001; Porter & Donthu, 2006).To examine discriminant validity, an analysis of

correlation between constructs measured wasconducted. Correlations between constructs rangedbetween .28 (Sport Involvement and Perceived Ease ofUse) and .82 (Perceived Enjoyment and Intention toUse a sports web portal) and were not excessivelyhigh (e.g.<.85; Kline, 2005, p.73). In addition, eachsquared correlation should be smaller than theAverage Variance Extracted (Fornell & Larcker, 1981).All AVE estimates were found to be greater than thesquared correlations. Therefore, it is concluded thatthe research constructs are sufficiently distinct fromeach other (see Table 4).

Structural model and hypothesis testsStructural regression analysis showed an acceptablemodel fit with x 2=900.37, df=444; RMSEA=.055;CFI=.94. The research hypotheses were examined byconducting a structural equation model analysis thatallows for statistical significances of the pathcoefficients between constructs. Of the ten hypotheses,six hypotheses were supported and four were rejectedat p<.05 (see Table 5 and Figure 1).

Development of a competing modelThe results of the hypothesis tests showed relativelysmall effects of Sport Involvement and PsychologicalCommitment to a Team on Intention and ActualUsage. These results indicate that potential mediatingvariables may exist between the relationships. Inaddition, it is important to examine external variables(e.g. individual difference, internet use behaviour,system experience, etc.) as antecedents of beliefconstructs within the TAM (Legris, Ingham &Collerette, 2003). These external variables can directlyor indirectly influence Actual Usage (Burton-Jones &Hubona, 2006). The researchers, therefore, modifiedthe original SWAM by incorporating sports fans’ beliefsabout the attributes of a sports web portal (i.e.Perceived Ease of Use, Perceived Usefulness,Perceived Enjoyment and Perceived Trustworthiness)as mediating variables between the constructs of SportInvolvement and Commitment and the consumers’Behavioural Intention and Actual Usage (Figure 2). Inother words, the indirect effects of Sport Involvementand Commitment on Intention and use of sports webportals through sports fans’ beliefs were examined.Within the competing model, all possible indirect


HYPOTHESIS STANDARDISED CRITICALPATH COEFFICIENT RATIO

H1. PERCEIVED EASE OF USE Û INTENTION .17* 2.42 CONFIRMED

H2. PERCEIVED USEFULNESS Û INTENTION -.13 -1.87 REJECTED

H3. PERCEIVED ENJOYMENT Û INTENTION .68* 10.30 CONFIRMED

H4. PERCEIVED TRUSTWORTHINESS Û INTENTION .10* 2.00 CONFIRMED

H5. SPORT INVOLVEMENT Û INTENTION .11* 2.22 CONFIRMED

H6. SPORT INVOLVEMENT Û USE OF SPORTS WEB PORTALS .07 .13 REJECTED

H7. SPORT INVOLVEMENT Û PCT .48* 7.83 CONFIRMED

H8. PCT Û INTENTION .05 1.18 REJECTED

H9. PCT Û USE OF SPORTS WEB PORTALS -.03 -.47 REJECTED

H10. INTENTION Û USE OF SPORTS WEB PORTALS .64* 9.56 CONFIRMED

TABLE 5 Results of hypothesis tests

Note: * (a significant path coefficient at p<.05)



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effects, except for the indirect effect of PerceivedUsefulness on sports website use, were significant atp<.05 (see Table 6).

The model comparison between the original and theproposed competing model was conducted on thebasis of the following criteria: overall model fit with theCFI; the percentage of the model’s hypothesisedparameters that are statistically significant; parsimony,as measured by the normed chi-square; and theproportion of variance explained in each dependentvariable by measuring the squared multiplecorrelations (James, Mulaik & Brett, 1982; Morgan &Hunt, 1994). The structural model tests of the originaland competing models revealed that the CFI for the

competing model (.91) was smaller than that of theoriginal model (.94), which means the original modelslightly outperformed the competing model. However,the percentage of hypotheses that were found to havestatistically significant support in the original modelwas 60% (6 of 10 hypotheses), whereas thecompeting model identified support for 71.4% (10 of14). In terms of percentages, the competing modelhas more significant path coefficients.

Next, a comparison of the original model with thecompeting model using the normed chi-square (x 2/df)showed that the competing model seems to be slightlymore parsimonious (2.03 vs. 1.91). The final basisfor comparison is the proportion of variance explained


* (a significant path coefficient at p<.05)

x2/df=1058/450=1.91

RMSEA=.063 (.058-.068)CFI=.91NFI=.86NNFI =.91

FIGURE 2 A competing model

INTENTIONSPORTS WEB PORTAL USE

.48*.64*

.05

.05

.60*

.64*

.65*.12*

.05

.12*

.12

BELIEFS ABOUT A SPORTS WEB PORTAL INTENTION AND BEHAVIOURINVOLVEMENT AND COMMITMENT

PERCEIVED ENJOYMENT

PERCEIVED USEFULNESS

PERCEIVED EASE OF USE

PSYCHOLOGICAL COMMITMENT

SPORT INVOLVEMENT

PERCEIVED TRUSTWORTHINESS

.69*

-.05

.18*

.63*



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in each dependent variable. In the original model,there were three dependent variables (PsychologicalCommitment to a Team, Intention and Actual WebUsage). The competing model had seven dependentvariables (with the exception of Sport Involvement; seeFigure 2). The squared multiple correlations for theoriginal model demonstrate that a slightly greaterproportion of the variance is explained by the

constructs of Psychological Commitment to a Team(20%), Intention (71%) and Actual Usage (44%), ascompared to the competing model (18%, 69% and42% respectively; see Table 7). Even though theoriginal model explained a greater proportion of thevariance, more information about the varianceexplained in dependent variables (due to the inclusionof the four sports fans’ beliefs about websites) was

CRITERIA ORIGINAL MODEL COMPETING MODEL

CFI .94 .91

NUMBER OF HYPOTHESES SUPPORTED 6 OF 10 (60%) 10 OF 14 (71.4%)

NORMED CHI-SQUARE 2.03 (900.37/444) 1.91 (1058.52/450)

PROPORTION OF VARIANCE EXPLAINED IN DEPENDENT VARIABLES (THE SQUARED MULTIPLE CORRELATION: SMC) PCT (.20) PCT (.18)

INTENTION (.71) INTENTION (.69)

ACTUAL USAGE (.44) ACTUAL USAGE (.42)

N/A PEU (.39)

N/A PU (.49)

N/A PE (.48)

N/A PT (.46)

TABLE 7 Comparison between the Original Model and the Competing Model

Note: N/A (Four sports fans’ beliefs were independent variables in the original model).

INDIRECT RELATIONSHIPS PARAMETER ESTIMATES CRITICAL RATIOS

SPORT INVOLVEMENT Û PERCEIVED EASE OF USE .29 5.74

SPORT INVOLVEMENT Û PERCEIVED USEFULNESS .27 5.56

SPORT INVOLVEMENT Û PERCEIVED ENJOYMENT .30 6.14

SPORT INVOLVEMENT Û PERCEIVED TRUSTWORTHINESS .25 5.37

SPORT INVOLVEMENT Û INTENTION .49 5.09

PCT Û INTENTION .71 11.45

SPORT INVOLVEMENT Û USE OF SPORTS WEB PORTALS .37 4.84

PCT Û USE OF SPORTS WEB PORTALS .53 8.43

PERCEIVED EASE OF USE Û USE OF SPORTS WEB PORTALS .16 3.90

PERCEIVED USEFULNESS Û USE OF SPORTS WEB PORTALS -.05 INSIGNIFICANT.

PERCEIVED ENJOYMENT Û USE OF SPORTS WEB PORTALS .66 9.71

PERCEIVED TRUSTWORTHINESS Û USE OF SPORTS WEB PORTALS .15 2.64

TABLE 6 Indirect effects within the competing model (p<.05)

PCT (psychological commitment to a team)



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provided by the competing model. In summary, basedupon four comparison tests, the competing model isslightly more parsimonious, shows more significantcausal relationships between constructs and providesmore information about the dependent variables thanthe original model. Thus, it is concluded that thecompeting model is more powerful for explainingsports fans’ acceptance of a sports web portal thanthe original model.

Discussion

sports fans’ beliefs about sports web portals andBehavioural Intention

Perceived Ease of Use and Intention. The firsthypothesis predicted the effect of Perceived Ease ofUse on Intention. The results showed small butsignificant positive effects (path coefficients=.17; seeFigure 1). This result is consistent with prior studies(Lin & Wu, 2002; Venkatesh & Davis, 2000). Thesmall effect of the Perceived Ease of Use on Intentioncan be explained by the fact that the internet hasbecome easier to use and sports fans have becomemore technologically savvy (Klopping & McKinney,2004). In particular, the subjects in this study wereundergraduate students who have more than threeyears of experience in using the internet. In sum, mostof the participants were already users of sports webportals and their favourite sports web portal is alreadyvery easy to use, resulting in their impression thatPerceived Ease of Use is not a concern.

Perceived Usefulness and Intention. The lack of acausal relationship between Perceived Usefulness andIntention (H2) is inconsistent with the findings of afew previous studies that found a positive causalrelationship between these constructs (e.g. Davis,1989; Davis et al, 1989; Shih, 2004). Those studies,focused on technology use, such as work-related useof word processing or email, found a much strongereffect of Perceived Usefulness on Intention than ofPerceived Ease of Use on Intention. The present study,however, found a non-significant relationship between

Perceived Usefulness and Intention both in the originaland competing models, whereas Perceived Ease ofUse positively influenced Intention in both models.This result is consistent with several studies conductedin the online business environment. For example, Lin& Wu (2002) found that Perceived Ease of Use had amuch stronger effect on Intention than PerceivedUsefulness in the context of internet portal sites,which consumers use voluntarily. Brown, Massey,Montoya-Weiss & Burkman (2002) applied the TAMin a voluntary setting (e.g. a student’s use ofPowerPoint) and found a non-significant effect ofPerceived Usefulness on Behavioural Intention and asignificant effect of Perceived Ease of Use onBehavioural Intention. The voluntary nature of sportsfans’ use of sports web portals may thus explain thelack of support for the second hypothesis.

Perceived Enjoyment and IntentionAmong the four beliefs-about-portals constructs,Perceived Enjoyment was the most significantdeterminant of Intention with a path coefficient of .68.This result supports previous studies which revealedthat Perceived Enjoyment is one of the key factors indetermining end users’ acceptance of systems (Daviset al, 1992; Igbaria, Schiffman & Wieckowski, 1994;Moon & Kim, 2001). Interestingly, Atkinson & Kydd(1997) found that Perceived Usefulness was only apredictor of web usage behaviour for course-relatedpurposes (e.g. library search), whereas PerceivedEnjoyment and ease of use were predictors of usagefor entertainment purposes. The results of this studysupport the findings of prior studies conducted in avoluntary entertainment website environment such asblog usage (Hsu & Lin, 2008). That is, online sportsfans are more likely to have an Intention to Use asports web portal when they perceive they are likely toenjoy it.

Perceived Trustworthiness and IntentionThere was a positive and significant effect of PerceivedTrustworthiness on Intention with a path coefficient of.11. This result supported the findings of prior studies




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on the TAM and Perceived Trustworthiness (Bart et al,2005; Grabner-Kräuter & Kaluscha, 2003; Reichheld& Schefter, 2000). Even though the previous studiesmainly focused on Trustworthiness in the context ofonline retailer and shopping behaviours, the results ofour study suggested that sports fans’ beliefs about thereliability of sports information obtained on sports webportals and the integrity of these portals, is asignificant predictor of their future intentions to visitthem. The relatively small effect found in this study isexpected to increase if the proposed competing modelis applied; not just to sports fans’ information-seekingbehaviours, but also to their purchasing behaviours inthe online context.

Sport Involvement, Commitment, Intention and Useof a sports web portalHypotheses 5-10 pertained to the causal relationshipsbetween Sport Involvement, PsychologicalCommitment, Intention and Actual Use of sports webportals. Among the six hypotheses in the originalmodel (see Figure 1), three hypotheses weresupported:

Sport Involvement Û Intention (pathcoefficient=.11, at p<.05); Sport Involvement Û Psychological Commitment to aTeam (path coefficient=.48); andIntention Û Actual Use (path coefficient=.64).

Because the direct effects of Sport Involvement andCommitment on Actual Use (H6 and H9) were notsignificant, other variables (e.g. beliefs about sportswebsites) may be mediating those relationships.Additionally, it is concluded that, although levels ofSport Involvement and Commitment do not determineActual Use of a sports web portal, Sport Involvementindirectly influences Actual Use through Intention.

As predicted, the effect of Sport Involvement onPsychological Commitment to a Team was strong andpositive (path coefficient=.48). This result isconsistent with prior research in which a highcorrelation between Involvement and Commitmentwas identified (Crosby & Taylor, 1983; Iwasaki &

Havitz, 1998, 2004; Kyle & Mowen, 2005). The effect of Intention on Actual Use of sports web

portals was significant (path coefficient=.64 for bothoriginal and competing models, at p<.05). This resultis consistent with the findings of prior studies thatsuggested a strong causal relationship betweenIntention and Actual Use (Gefen & Straub, 1997;Moon & Kim, 2001; Venkatesh & Davis, 2000).

A competing modelThe results did not support our hypothesisedrelationships between Sport Involvement and ActualUse of sports web portals, or between Commitment,Intention and Use. Thus, we proposed a competingmodel to examine the role of sports fans’ beliefs aboutsports web portals as mediating variables. Althoughwe did not find a significant improvement of model fitin the competing model, the competing model doeshelp to explain the non-significant relationships. Themajor advantage of the competing model over theoriginal model is that the competing model allows forexamination of the indirect effects of Commitment onIntention and Actual Use through the mediatingvariables of Perceived Ease of Use, Usefulness,Enjoyment and Trustworthiness. The path coefficientsfrom Commitment to Perceived Ease of Use (.60),Usefulness (.64), Enjoyment (.63) andTrustworthiness (.65) were all significant at p<.05.These results suggest that Commitment indirectlyinfluences Intention to Use and Actual Use when thefour belief constructs mediate the relationships. Asmediating variables, consumer beliefs about websiteswere thus identified as important predictors ofBehavioural Intention and Actual Use, with oneexception (Perceived Usefulness; see Table 6).

Within the competing model, the influences of SportInvolvement on the four beliefs about sports webportals were not significant except for PerceivedEnjoyment (path coefficient =.12 at p<.05; figure 2).However, Sport Involvement indirectly influenced thefour beliefs (i.e. Perceived Ease of Use, Usefulness,Enjoyment and Trustworthiness) through theCommitment construct. In addition, Sport Involvement




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indirectly influenced Intention with an indirect effect of.49 and Actual Use with an indirect effect of .37through Commitment, Perceived Ease of Use,Usefulness, Enjoyment and Trustworthiness.Commitment also indirectly influenced Intention with apath coefficient of .71 and Actual Use with .53.Based on these results, we concluded that sports fans’beliefs about the portals were important variables thatmediate the relationship between PsychologicalCommitment to a Team/Sport Involvement andIntention.

Interpretation of the resultsCaution should be exercised in interpreting theseresults. First, the researchers utilised a conveniencesampling method. The majority of subjects whoparticipated in the survey were undergraduatestudents at a large university in the north-westernUnited States. Most subjects were computer literate,internet-savvy and highly involved in sport. Eventhough the competing model fits to the data well,further studies are necessary to confirm the factorstructure and the causal relationships betweenconstructs by using a broader sample in order toincrease generalisability of the research findings. Forexample, the effect of Perceived Ease of Use onIntention might be greater if the model is tested withan older group. Additionally, Usefulness andTrustworthiness may be significant factors whenapplied to a different type of online sportsconsumption, such as purchasing sports productsonline.

Second, this study focuses on sports fans’perceptions of general sports web portals such aswww.espn.go.com, www.sportlines.com orwww.foxsport.com which are primarily used forinformation-seeking. Model fits and path coefficientsmight differ across different types of websites.Therefore, future studies should examine sportsconsumers’ behaviour on different types of websites,such as online sport-related shops, sports teams’websites or fantasy sports websites.

Third, in this study, only two sport-related constructs(Sport Involvement and Psychological Commitment toa Team) were incorporated into the SWAM model(Davis, 1989). Future research using other sport-related constructs (e.g. Sport Spectators’ Motivation orFan Satisfaction/Perceptions of Service Quality) mayfurther improve our understanding of online sportsconsumption behaviour. Nonetheless, this studymakes contributions to both theory and practice.

Theoretical implicationsAlthough some scholars have paid attention to onlinesports business, their studies have focused on contentanalysis (e.g. Smith, Pent & Pitts, 1999);demographic profiles of online sports consumers (e.g.Brown, 2003); and motivation research (e.g. Hur, Ko& Valacich, 2007; Seo & Green, 2008). There hasbeen little research applying consumer behaviourtheories to online sports consumer behaviour. Thisstudy is expected to contribute towards filling the gapin current literature between sports marketing theoryand management information systems theory. In orderto accomplish this goal, the Technology AcceptanceModel (TAM) has been supplemented with sport-specific constructs (Sport Involvement andPsychological Commitment to a Team) and applied tothe sports web portal environment. This conceptualframework may become a fundamental base forunderstanding sports fans’ online informationconsumption behaviours. In particular, it providesinformation about how sports fans perceive and acceptsports web portals and how their involvement level insport and commitment to a team influence theirintention to use the portals and are related to theiractual use.

In addition, as the TAM has mainly focused on workor mandatory system use environments, this studyextends TAM-related research by applying the model tothe voluntary leisure use environment common in theentertainment and sports industry.




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Practical implicationsThis study contributes to the understanding of sportsfans’ perceptions about and acceptance of sports webportals and provides a practical marketing tool forevaluating the likelihood of fans’ intention to use theportals and their actual visiting behaviours.

First, among sports fans’ beliefs, PerceivedEnjoyment is the most important determinant ofIntention to Use and Actual Use of sports web portals.Although the portals are useful sources for sports fans’favourite team information with regard to game scores,player statistics, game schedules etc., sports fans aremore likely to visit the portals when they feel that theportal itself will add to their enjoyment. Therefore,sports website managers need to focus more on howto enhance fans’ enjoyment of content by using, forexample, techniques such as weekly prize quizzes,interviews with star players and video highlights.

Second, although Sport Involvement directlyinfluenced Intention to Use a sports web portal, it didnot directly affect Actual Use. Also, PsychologicalCommitment to a Team did not directly influenceeither Intention or Actual Use. According to the resultsof the competing model analysis, these two sports-related constructs (Sport Involvement andPsychological Commitment to a Team) are more likelyto indirectly influence Behavioural Intention and ActualUse through sports fans’ beliefs about sports webportals (Perceived Ease of Use, Perceived Enjoymentand Perceived Trustworthiness). Therefore, attentionshould be paid to sports fans’ beliefs about theseportals in attempts to increase future Intention to Useand Actual Usage behaviours. Sports marketers shouldrealise that, in the online sports consumption context,these beliefs about the attributes of websites link highInvolvement levels in sport and high levels ofCommitment to a Team with fans’ Intentions to useand Actual Use of sports web portals.

Conclusion

This study provides an integrated model of sports fans’sports website acceptance decisions by incorporatingthree fairly well accepted models. Although the originalSWAM model fits the data fairly well, severalhypothesised relationships were not supported.However, our proposed competing model supportsadditional hypothesised relationships and providesmore information about dependent variables. Sincethere has been a lack of research on sports fans’behaviour in the context of online sports business, theSWAM competing model and the empirical testresults, will assist sports marketers to gain a betterunderstanding of how online sports fans develop anintention and decision to use, a sports web portal.

© 2012 International Marketing Reports

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