In Search of the “Meta-Maven”: An Examination of Market Maven Behavior across Real-Life, Web, and Virtual World Marketing Channels

In Search of the “Meta-Maven”:An Examination of Market MavenBehavior across Real-Life, Web, andVirtual World Marketing ChannelsStuart J. BarnesUniversity of East Anglia

Andrew D. PresseyLancaster University

ABSTRACT

Recently, a new set of channels for consumer and business interaction have emerged—three-dimensional “virtual” worlds. This study attempts to better understand the nature of market mavenbehavior (diffusers of general marketplace and shopping information) across three differentchannels—virtual worlds, the Web, and real-life—and to examine the extent to which market mavenbehavior is transferable across channel context (i.e., “fluid”) or channel dependent. Using data fromtwo surveys (one in the virtual world “Second Life” and a follow-up Web survey for the samerespondents), this paper explores differences and determinants of maven behavior. Employingpartial least squares analysis, the findings indicate that market maven propensity is transferableacross channels (i.e., high-scoring market mavens retain this across channel). However, while theremay be the transferability of market maven behavior across channels, the findings demonstrate thatmaven propensity is influenced by the channel context. Consequently, individuals with high mavenpropensity tend to exhibit channels in which this behavior is more prominent. Therefore, marketmaven behavior might not only span general product categories, but also the channel itself (i.e.,maven behavior remains fairly constant—or fluid—across channel). The findings also point topossible characteristics that may be used in the identification of market mavens: market mavenstypically have greater cognizance of other mavens, are technology-savvy and individualistic, are ofeither gender and tend to be older and more intensive and experienced users of Web platforms andalso intensive users of virtual worlds than those with low maven propensity. The findings of thestudy contribute to understanding market maven behavior, and provide an insight into the practicesof mavens in a multichannel context, particularly in the case of the emerging channels that arevirtual worlds. C© 2012 Wiley Periodicals, Inc.

The market maven concept, first introduced by Feickand Price (1987), has attracted considerable scholarlyinterest. This group of consumers possesses general-ized marketplace information and takes a keen inter-est in disseminating this to others, thus acting as auseful means of distributing product information of-ten with greater credibility than many traditional mar-keting communications sources. The existence of themarket maven has received widespread report in phys-ical channels (i.e., real-world) (Abratt, Nel, & Nezer,1995; Clark & Goldsmith, 2005; Feick & Price, 1987;Goldsmith, Clark, & Goldsmith, 2006; Walsh, Gwinner,& Swanson, 2004; Williams & Slama, 1995) as well asWeb-based channels (Belch, Krentler, & Willis-Flurry,2005). A notable absence from these studies is an under-standing of market maven behavior in alternative com-munication channels. With the recent emergence and

growth of social networking technologies—includingthe likes of MySpace, Facebook, YouTube, LinkedIn,Flickr, Bebo, Hi5, Friendster, 47 Things, and manymore—a new set of channels for market maven behav-ior has emerged. One such channel is that of the virtualworld (e.g., Second Life, developed by Linden Lab).

Virtual worlds have been recognized as potentiallyone of the more important channels for marketing andmarketplace information (Hemp, 2006), as testified bythe large number of diverse key brands that havecreated a presence there, including Toyota, Reuters,Nokia, and Dell. Little is known, however, concern-ing how these emergent channels differ from existingchannels and the factors that might contribute towardmarket maven behavior. For example, how do marketmavens behave across multiple channels—including,for example, physical channels, the Web, and virtual

Psychology & Marketing, Vol. 29(3): 167–185 (March 2012)View this article online at wileyonlinelibrary.com/journal/marC© 2012 Wiley Periodicals, Inc. DOI: 10.1002/mar.20513

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worlds—and to what extent is market maven propen-sity retained by individuals across marketing chan-nels (i.e., the degree to which individuals who havea high market maven propensity transfer this acrosschannel setting)? If it were possible to establish anindividual’s market maven propensity that exists in-dependent of channel, the implications for marketerswould be significant; such “meta-mavens,” if they canbe identified, would provide enormous value to mar-keters across many channels in terms of disseminatingpositive word-of-mouth and the personal influence theyexert on other consumers. Based on the foregoing, theaim of this study is threefold:

1. To identify the extent to which market mavenbehavior is retained across physical, Web, andvirtual world channels (i.e., whether a maven isalways a maven regardless of channel context);

2. To identify the degree to which market mavenbehavior is constant across physical, Web, andvirtual world marketing channels (i.e., whethermavenism is greatest in a particular channel);and

3. To examine the personal characteristics of mar-ket mavens across channel.

This study is timely for a number of reasons. First,market mavens are an important group of consumers asthey are effective at spreading word-of-mouth throughtheir often extensive social networks making thema useful target for companies, particularly concern-ing new goods and services (Slama & Williams, 1990;Sundaram, Mitra, & Webster, 1998; Williams & Slama,1995). Second, understanding the transferability ofmaven behavior across channels affords an understand-ing of the degree to which maven behavior might beuniversal (i.e., not channel dependent). Third, studiesgrounded in virtual worlds provide a context in whichto examine established marketing tenets (Hemp, 2006)and to question assertions concerning consumer behav-ior based on “real-world” actions that may have to bereconsidered within the context of virtual worlds. Assuch, this study represents one of the first attemptsto understand marketing phenomena within the con-text of virtual worlds. Fourth, if enough studies of thissort can be done, perhaps broad generalizations can bederived that can be integrated into the evidence frompsychology to deepen the understanding of consumerbehavior in general. To this end, the authors hope thatthis study encourages others to embark on research inthis area of investigation.

THE MARKET MAVEN CONCEPT

Defined by Feick and Price (1987) as “Individualswho have information about many kinds of products,places to shop, and other facets of markets, and ini-tiate discussions with consumers and respond to re-quests from consumers for market information” (p. 85),the market maven construct has been a catalyst for

numerous confirmatory studies in the United Statesas well as in other country contexts (e.g., Slama &Williams, 1990; Abratt, Nel, & Nezer, 1995; Wiedmann,Walsh & Mitchell, 2001; Chelminski & Coulter, 2002,2007; Steenkamp & Gielens, 2003; Goldsmith, Clark,& Goldsmith, 2006, Clark, Goldsmith, and Goldsmith,2008; Ruvio & Shoham, 2007; Goodey & East, 2008).The involvement or interest demonstrated by the mar-ket maven is not restricted to a particular product cat-egory but rather is linked to general marketplace andshopping interest. As such, market mavens are consid-ered to be distinct to other influencers such as opin-ion leaders, innovators, and early adopters as theiractivities encompass general market knowledge andactivities rather than relating to a particular prod-uct category (Feick & Price, 1987; Goldsmith, 1996).This is an important distinction as innovators and opin-ion leaders have limited function for “broad-based re-tailers” as researchers have generally been unable to“ . . . .generalize their findings away from specific prod-ucts or product categories” (Abratt, Nel, & Nezer, 1995p. 32).

Influencers use their networks and communities tospread word-of-mouth to reach greater numbers of so-cial contacts than a typical consumer. In the case ofmavens, their personal influence is largely based on al-truistic motives—for the pleasure of sharing informa-tion and to reinforce their image in their community(Sundaram, Mitra, & Webster, 1998)—spanning mul-tiple product categories making them a useful targetfor companies (Slama & Williams, 1990). For example,the social integration of the maven affords them theirinfluence, with individuals who know them being morelikely to act on their information as they tend to havegreater confidence in word-of-mouth than commercialsources such as advertising due to perceived credibility(Gelb & Johnson, 1995; Keller & Berry, 2003; Williams& Slama, 1995). Word-of-mouth can also influence prod-uct choice (Price & Feick, 1984; Kiel & Layton, 1981)making it a useful managerial issue to examine. Con-sequently, mavens can be helpful to other consumersin advertising saturated markets by becoming “com-petent information providers and advisors” (Walsh,Gwinner, & Swanson, 2004 p. 100), particularly as theyare generally “smarter” shoppers (Slama, Nataraajan,& Williams, 1992).

Research examining market mavens is pervasivein the marketing literature. For example, studieshave considered the demographic profiles (Abratt, Nel,& Nezer, 1995), personality characteristics (Clark,Goldsmith, & Goldsmith, 2008; Geissler & Edison,2005; Goldsmith, Flynn, & Goldsmith, 2003; Ruvio& Shoham, 2007), purchasing alternatives and cri-teria (Williams & Slama, 1995), and motivations formavenism (Chelminski & Coulter, 2007; Clark &Goldsmith, 2005; Inman, McAlister, & Hoyer, 1990;Steenkamp & Gielens, 2003; Walsh, Gwinner, &Swanson, 2004) as well as the notion of industrialmavens in a business-to-business context that display“ . . . broad-based information on industrial markets”

168 BARNES AND PRESSEYPsychology & Marketing DOI: 10.1002/mar

(Nataraajan & Angur, 1997 p. 354). A notable absencefrom this list is an understanding of the degree towhich market maven tendencies are constant or dy-namic across setting and context. Market mavenism isthought to be continuous in that it captures marketmaven propensity rather than to identify mavens ver-sus nonmavens (Feick & Price, 1987). In this sense, justas market maven propensity may feasibly be higherfor one individual as compared to another and mayalso increase or decrease over the lifetime of a con-sumer, contextual factors in terms of channel mayequally play a role in determining market maventendencies.

The rise in social networking technologies and vir-tual worlds also potentially facilitates the ease withwhich mavens can disseminate product and marketinformation. For some individuals, the extension ofmaven behavior across channel may be associated withtheir personality characteristics. For example, a mavenwith an affinity for technology and high propensity toadopt new technologies will be likely to extend theirmaven behavior across channel. Further, other demo-graphic, personality, or technology use characteristicsof mavens may impact on the extent to which mavenbehavior in a real-world setting might extend to theWeb and virtual worlds.

Against the foregoing, identifying the transferabilityor fluidity of market maven behavior across channels(i.e., the extent to which market mavenism is constantor changeable across channel) as well as identifyingthe presence of mavens in multiple marketing chan-nels would seem valuable. As Geissler and Edison (2005p. 74) note: “ . . . finding new ways of identifying and pro-filing market mavens and targeting marketing commu-nications to them may be increasingly important in thetwenty-first century.” This takes on particular impor-tance against a background of growing product choice,media saturation, and multiple channels (e.g., physicalchannels, the Web, and virtual worlds) in which con-sumers can interact with one another as well as withorganizations. In the following section, the existenceof markets mavens in three-dimensional (3-D) virtualworlds is considered.

VIRTUAL WORLDS DEFINED

Investment in online and digital technologies by busi-ness is remarkable with billions of dollars being ex-pended in recent years (Arnold, 2004). The rapid riseof these technologies affords consumers new venuesfor interaction with other consumers as well as withbusinesses (Chelminski & Coulter, 2007; Geissler &Edison, 2005). As a consequence, in addition to tradi-tional real-world settings where consumers might dis-seminate information (e.g., via the telephone, in re-tail outlets, or through face-to-face interactions withfriends and family), there are broadly six virtual/onlinemeans by which consumers can interact (cf. Kozinets,2002) including:

1. Chat rooms (often organized around special in-terests such as consumer and lifestyle issues);

2. Web rings (related home pages where individualscan share information based on a single mailinglist);

3. Electronic bulletin boards (allowing participantsto post-group relevant information);

4. Lists (or listservs) (theme-based e-mail mailinglists);

5. Social networking tools (such as MySpace, Face-book, and YouTube); and

6. Virtual worlds, which can be broadly classified aseither massively multiplayer online role-playinggames (such as World of Warcraft and EverQuest)or virtual economies where participants createbusinesses and communities (such as SecondLife, IMVU, and Active Worlds).

These new channels provide the means for con-sumers to exert greater interpersonal influence, thusmaking it important that marketers better understandthe role of influencers in these settings. In comparisonto physical and Web channels, virtual worlds are a rel-atively new concept and hence require explanation.

Three-dimensional “virtual worlds” (sometimes re-ferred to as “experience worlds”) are increasingly be-coming an important channel for companies to com-municate with current and potential customers. These“fast-growing Internet-based simulated environmentswhere users can not only interact with each other,but with products and services provided by businessesand individuals” (Lui, Piccoli, & Ives, 2007 p. 77) pro-vide a platform for interactivity that can positively in-fluence product knowledge, attitudes toward brands,telepresence, and purchase intention (Klein, 2003; Li,Daugherty, & Biocca, 2002; Steuer, 1992; Suh & Lee,2005). While the Web introduced a new highly inter-active medium that altered the parameters of massand personal communication (Hoffman & Novak, 1996;Rogers, 1986), virtual worlds stand to make an equallyimportant impact on individual’s daily lives and shop-ping behavior. As Drew Stein, CEO of Infinite VisionMedia (an interactive marketing agency that workedwith Dell Island in the virtual world Second Life), notes:“as people get more familiar with 3-D experiences, theflat Web page is going to seem like a thing of the past”(reported in Lui, Piccoli, & Ives, 2007).

As the distinction between virtual worlds (such asSecond Life) and social networking sites (such as Face-book) has not been well established in the literature,it is worth delineating the differences between thesetwo computer-mediated environments. Virtual worldscan be thought of as a distinct form of social networkingsite in terms of the extent of the individual’s interactionwith the medium. For example, the “optimal experi-ence” achieved in terms of “playfulness” or “flow” expe-rienced in a particular environment (cf. Csikszentmiha-lyi, 1977) is demonstrably different between both typesof site. It is proposed that there is a heightened senseof “flow” in virtual worlds—the sense of fun attained

IN SEARCH OF THE “META-MAVEN” 169Psychology & Marketing DOI: 10.1002/mar

in structured activities (Hoffman & Novak, 1996). Forflow to occur, two key antecedents are necessary: thelevel of focused attention possible (the extent to whichan individual is subsumed within the activity) and thebalance between the skills and challenges involved inthe interaction (Hoffman & Novak, 1996). In this sense,virtual worlds provide greater scope of focused atten-tion and tasks/challenges than social networking sites.There are numerous tasks in virtual worlds such asSecond Life not necessarily available via social net-working sites that represent challenges ranging fromshopping (at in-world stores), commerce (e.g., realestate), ability to engage in interactive games andleisure pursuits (including museums and art galleries),and networking opportunities (e.g., via special interestgroups including those affiliated to religious groups andeducational institutions). If the challenge presented bya particular activity is perceived as being incongru-ent with the individual’s level of skill then they canswitch tasks or create their own. Focused attention ispredicated on the capacity of the individual to becomeimmersed in the environment. In this sense, virtualworlds provide an ideal context for focused attentionas they are highly detailed, 3-D-rendered, interactiveenvironments, consistent with the optimal conditionsfor focused attention where the individual “ . . . is incontrol of his actions, and in which there is little dis-tinction between self and environment, between stimu-lus and response, or between past, present and future”(Csikszentmihalyi, 1977 p. 36). Virtual worlds also pro-vide greater “telepresence”: “ . . . the extent to which onefeels present in the mediated environment, rather thanin the immediate physical environment,” by creating“ . . . an almost ‘being there’ experience” (Steuer, 1995p. 36). Therefore, virtual worlds constitute a rich visualmedium with a depth of engagement and high levelof interactivity not afforded by most social networkingsites.

The emergence of virtual worlds encourages mar-keters to reflect on the body of knowledge amassed oncustomers based on their real-world and Internet-basedshopping behavior and to question some of these tenetsor widely held axioms. As Fortin (2000) notes, “a com-mon question that generally arises when a new tech-nology is introduced is: How does this affect what wealready know about a phenomenon?” (p. 524). Virtualworlds—such as Second Life and World of Warcraft—capitalize on an individual’s desire to inhabit al-ternative personalities and to occupy an anonymous“alternative self” in a virtual environment, thus poten-tially changing one’s identity and even behavior via anavatar—comprising not only “complex beings createdfor use in a shared virtual reality but any visual rep-resentation of a user in an online community” (Hemp,2006 p. 50). Avatars act as proxies for the real-worldself—offering the possibility for their human controllerto explore “ . . . hidden aspects of their identities” that“ . . . differ substantially from one another and from thecreator’s public self” (Hemp, 2006 p. 50). As a con-sequence, consumers may behave differently in such

environments than they would in real-world interac-tions and encounters thus providing a group of poten-tially new, or at least different, consumers and market-ing opportunities.

In the case of Second Life—a 3-D virtual world thatis free to join and is created by its residents (one ofthe channel contexts examined in the present study)—approximately 14 million residents (as of August,2008) engage in leisure pursuits and trade using thein-world unit-of-trade (the Linden Dollar), which canbe converted into U.S. dollars via online currency ex-changes. Consumers can disseminate information invirtual worlds through a variety of means includingdialogue (via text chat, instant messaging, and Voice-over-IP) with other avatars in public and through en-gagement in special interest groups. A number of majorbrands have a presence in Second Life including high-tech firms (Sun Microsystems, Dell), car manufacturers(Nissan, BMW), luxury items (Armani, Hublot), ser-vice providers (IBM, Playboy), consumer goods (Sony-Ericsson, Nokia), as well as diverse others (StanfordUniversity, the Swedish Embassy, Visit Mexico, andthe Weather Channel). On the basis of these attributes,Second Life has been identified as an environment inwhich to examine consumers’ behavior in a virtualworld context and the implications this might have formarketing (Hemp, 2006).

Against the abovementioned, many assertions con-cerning consumer behavior based on “real-world” ac-tions may have to be reconsidered within the contextof virtual worlds, particularly as individuals’ avatarsmay behave differently to their real-world alter egos.The transferability of market mavenism across chan-nels as well as the personal characteristics of mavensis now considered.

HYPOTHESIS DEVELOPMENT

Market Maven Propensity across Channel

The market maven measure and concept was predi-cated on real-life interaction between consumers (Feick& Price, 1987) (i.e., a single channel), at a point in timewhen both the Web and virtual worlds were at an em-bryonic stage in their development. The present studyconsiders maven behavior within channels, hence chan-nel refers to the context or setting in which consumersinteract and disseminate information about productsand services. In a review of the extant literature, nostudy could be identified that considers market mavenbehavior across multiple channel settings. In their in-vestigation of Internet teen-mavens, however, Belch,Krentler, and Willis-Flurry, (2005) assert that teen-mavens (who take particular pleasure in surfing theInternet), relative to others online, can be relied uponto provide useful information and in so doing influ-ence the family decision-making process to a greaterextent than nonmarket mavens. Geissler and Edison(2005 p. 87) also allude to the notion of market maven


transferability when they propose that “Today’s mavensprobably communicate with more consumers than everbefore. Indeed, more and more consumers are going on-line each year and mavens may be quite influential to-wards a growing number of online consumers, alongwith their traditional circle of friends, neighbors andother associates.” Therefore, one might act as a marketmaven across multiple channels.

Although the preceding does not afford an under-standing of the transferability of maven behavior indifferent settings, it does suggest that mavens can dis-play such behavior in situations other than a physi-cal, or “real-world,” context. Further examination of themaven concept and the nature of personality itself canhelp better understand the transferability of marketmavenism.

Market mavenism is “a role individuals can adopt”(Feick & Price, 1987 p. 85), predicated on the assump-tion that by collating and disseminating marketplaceinformation they can increase their perceived power insociety as they become more useful in their interac-tions with others (Sieber, 1974). Feick and Price (1987)suggest that this compels certain individuals to dis-seminate information in the expectation that they willbecome the recipient of “rewards” (i.e., that they willbe the recipient of informed information on topics fromothers in return). Therefore, Web-based channels andvirtual worlds offer platforms ideally suited to theseindividuals through facilitating social interaction viaavatars (in the case of virtual worlds) and the dissemi-nation of marketplace information.

Some individuals feel that it is their duty to be-come well-informed consumers thus acting as informa-tion seekers (Feick & Price, 1987; Kassarjian, 1981).What drives one individual to become better informedthan another is attributed in part to differences in at-titudes and behavior (Feick & Price, 1987)—hence aconstruct of personality. Specifically, this is a questionof the stability of personality insofar as it can be trans-ferred across setting or context.

Personality is thought to include “objective and ob-servable traits” as well as “roles, attitudes, goals, andbehavioral tendencies” (Tickle, Heatherton, & Witten-berg, 2001 p. 243). The extent to which an individual’spersonality can change (other than via neuro-biologicalinjury such as through major brain damage) has rep-resented one of the most significant issues in per-sonality psychology (Heatherton & Weinberger, 1994).Although opinion is to some extent divided on the topic,with some early views proposing that personality mightbe dynamic (Allport, 1937; Gendlin, 1964), most con-temporary views hold that personality is relatively pre-dictable and stable across time, situation, and over theadult lifespan (McCrae & Costa, 1990; Tickle, Heather-ton, & Wittenberg, 2001). In support, Steuer (1995p. 36) suggests that in certain computer-mediated en-vironments, “ . . . people respond to mediated stimuliin ways similar to their real-life counterparts.” Ev-idence also supports the notion that computers canprovoke social responses that are analogous to human

interactions (Nass & Steuer, 1993; Nass, Steuer, Hen-rikson, & Dryer, 1994; Wang, Baker, Wanger, & Wake-field, 2007). Thus, even when presented with new chan-nels such as virtual worlds and the opportunities theyprovide to change appearance as well as to interact withhuman-controlled and possibly computer-controlledavatars, important underlying personality traits maybe expected to stay the same. Therefore, it is assertedthat:

H1: Individuals with high market maven propen-sity retain this characteristic across channel.

A pertinent question arises from the foregoing dis-cussion. If market mavens do retain their maven be-havior across channel then is this behavior equallystrong in all channels? Put another way, might a mar-ket maven have a particular channel in which he orshe exhibits their strongest maven behavior? As thisis an exploratory study, and as no compelling evidenceexists to suggest the contrary, the null hypothesis isoffered:

H2: Market maven behavior remains constant foran individual across physical, Web, and vir-tual world channels.

Market Maven Propensity and PersonalCharacteristics

The second area of investigation relates to the per-sonal characteristics of market mavens. Although un-derstanding the characteristics of market mavens (andparticularly identifying e-mavens) is an area of intu-itive importance surprisingly little guidance is offeredas to what characteristics might be most revelatory(Geissler & Edison, 2005; Walsh & Mitchell, 2001).As demographic factors have not proved particularlyuseful in classifying market mavens (discussed brieflynext), additional variables to explore maven character-istics were sought. Therefore, in addition to key de-mographics (age and gender), variables were selectedrelated to personality characteristics (individualism,affinity for technology, and knowledge of others asmavens) and interaction with the channel (knowledgeof channel and intensity of channel usage). Some of thehypotheses proposed are new whereas others have beentested previously. These variables are employed as theyeither represent demographic indicators or else relateto the study theme of virtual worlds. These are nowbriefly examined.

Demographic Factors. No clear or consistent demo-graphical profile has been proposed of market mavenswith considerable variability of views evident in theliterature; indeed, Geissler and Edison (2005 p. 85)even go as far as to note the “lack of success of de-mographically profiling mavens,” a view largely shared


by the originators of the concept (Feick & Price, 1987).Equivocal (or at least inconsistent) findings have beenoffered in prior studies (e.g., Clark & Goldsmith, 2005;Clark, Goldsmith, & Goldsmith, 2008; Geissler & Edi-son, 2005; Goldsmith, Clark, & Goldsmith, 2006) con-sequently making targeting mavens challenging. As nocompelling argument or evidence has been offered topropose that mavens are of a particular gender or agegroup, the following hypothesis is offered:

H3: There will be no differences in gender andmarket maven propensity, and

H4: There will be no differences in age and marketmaven propensity.

Personality Characteristics. The first area of mar-ket maven personality characteristics concerns the abil-ity of consumers to recognize others as market mavensand their influence—an important means of validatingthe market maven construct (Feick & Price, 1987). Thissaid, however, subsequent market maven enquirieshave rarely employed this measure. Feick and Price(1987) found that a sizeable proportion of respondentshad knowledge of other mavens, were assisted by themin raising awareness of goods and services, and receivedtheir help in evaluating goods. These measures wereadopted for much the same reason as Feick and Price(i.e., as a means of validating the existence of marketmavens and their recognition by others). It is proposedthat individuals with high market maven propensitywill have a greater likelihood of recognizing this char-acteristic in others that they interact with. This is basedon the premise that mavens seek out other mavens inorder to exchange information, as already noted (Feick& Price, 1987; Sieber, 1974). Hence,

H5: Individuals with high market maven propen-sity will be more likely to: (i) have knowledgeof other market mavens; (ii) be assisted bythem in raising awareness of goods and ser-vices; and (iii) use their help in evaluatinggoods and services than individuals with lowmarket maven propensity.

Individualism is a well-established concept that hasits roots in personality traits attributed to the culturaldifferences between societies and refers to the unique-ness of each individual and concerns related to theirown well-being in contrast to collectivistic individuals(Triandis, 1994, 1995). Although individualism is pri-marily a means to examine consumers from differentsocieties (e.g., see Kim, 1994; Maheswaran & Shavitt,2000), it can also serve to understand the psychologicaldifferences between individuals within a society.

Individualists have a need for achievement, are com-petitive (Triandis, 1994; Triandis, Bontempo, & Ville-real, 1988) and tend to maintain largely superficial

relationships, instead placing greater emphasis on dis-seminating and receiving market information (Markus& Kitayama, 1991). Individualists are also more in-clined to be confident in their decision making andproactive in disseminating their opinions and ideas(Chelminski & Coulter, 2007). Therefore, individual-ism would appear to be a trait consistent with highmarket maven propensity. Indeed, as Chelminski andCoulter (2007 p. 87) note: “where people are more in-dividualistic, and thus more confident in their market-place endeavors, market mavenism is likely to be moreprevalent.” In addition, Clark, Goldsmith, and Gold-smith (2008) found a relationship between aspects ofconsumer self-confidence and mavenism; conceptuallynot unrelated to individualism (Bearden, Hardesty, &Rose, 2001). Therefore, it is proposed that individualswith high market maven propensity are also more likelyto exhibit strong individualism traits. Stated in the for-mal manner:

H6: Individuals with high market maven propen-sity will display higher individualism than in-dividuals with low market maven propensity.

Affinity for technology can be defined as “the de-gree to which an individual likes or looks forward tolearning about and being involved with new technol-ogy” (Geissler & Edison, 2005 p. 77). Consumers dif-fer in their attraction to technology with some eagerto adopt new technology and others anxious of suchchanges (Rogers, 2003). Hence, some consumers (basedon their personal innovativeness) are more likely toadopt new technology than others (Agarwal & Kara-hanna, 2000; Agarwal & Prasad, 1998; Wolfradt & Doll,2001). As mavens are considered innovative and withan attraction to new products (Feick & Price, 1987;Slama & Williams, 1990), it seems likely that they willhave a greater affinity to trial and adopt new technologythan individuals with low maven propensity (Geissler& Edison, 2005). Therefore, it is proposed that marketmavenism is related to affinity for technology:

H7: Individuals with high market maven propen-sity will have a greater affinity for technol-ogy than individuals with low market mavenpropensity.

Channel Interaction. Market mavens enjoy learningabout products and services, collecting coupons fromnewspapers and magazines and generally engagingwith shopping behavior to a greater extent than otherindividuals (Feick & Price, 1987). Virtual worlds poten-tially afford mavens a new channel in which to inter-act. Clearly, users of virtual channels can engage witha particular channel as much as he or she wishes fromlight to heavy usage. In addition, an individual willalso vary in the length of time they have been using aparticular channel.


It is proposed that if, as is supposed, mavens havea greater affinity for technology than nonmavens andproclivity for shopping interest then these character-istics will be extended to the Web and virtual worldchannels. Hence, market mavens’ user interaction andinvolvement with both the Web and virtual world chan-nels in terms of user experience (the length of time theindividual has been using each medium) and intensityof usage (measured in terms of the time spent in eachmedium) will be greater, in general, than those withlow market maven propensity as they search for anddisseminate product information. Therefore, it is pro-posed:

H8: Individuals with high market maven propen-sity will have greater: (i) channel experience;and (ii) intensity of usage of both Web and vir-tual worlds than individuals with low mavenpropensity.

METHODOLOGY

Research Design and Measurement

The research design adopted by the study involveda cross-sectional, convenience sample using two self-report surveys across three marketing channels: twoonline channels (Second Life and the Web) and real-life. Second Life is arguably one of the most advancedof virtual worlds and was deemed an ideal context inwhich to collect data.

In order to be consistent with previous research ex-amining market mavens, only minor modifications weremade to Feick and Prices’ (1987) original measure toreflect the different channels under examination (seeAppendices for all measures and items). The marketmaven scale measures an individual’s tendency to dis-seminate useful market information across a variety ofproducts and brands and is a unidimensional, 7-point,six-item, summated scale. The nomological validity ofthe market maven measure has been generally sup-ported in comparison to the broadly conceptually simi-lar measures of opinion leadership and innovators/earlyadopters (Feick & Price, 1987; Ruvio & Shoham, 2007).

Although the market maven measure has not beenwithout its critics (see, e.g., Goodey & East, 2008;Voss, Stem, & Fotopoulos, 2000; Williams & Slama,1995), it has proved broadly robust across differ-ent cultural settings including the United States(e.g., Goldsmith, Clark, & Goldsmith, 2006; Slama& Williams, 1990), Germany (Wiedmann, Walsh, &Mittchell, 2001), South Africa (Abratt, Nel, & Nezer,1995), The Netherlands (Steenkamp & Gielens, 2003),Israel (Ruvio & Shoham, 2007), South Korea (Chelmin-ski & Coulter, 2007), and Poland (Chelminski & Coul-ter, 2002), as well as for studies of Web mavens (Belch,Krentler, & Willis-Flurry, 2005) and industrial mavens

(Nataraajan and Angur, 1997), thus demonstrating therobust nature of the concept and its broad applicability.

In addition to capturing market maven behavior,data were captured for level of user interaction andinvolvement with both virtual world and Web in termsof user experience (i.e., the length of time using eachmedium) and intensity of usage (measured in timespent in each medium) as well as respondent demo-graphics (age and gender).

Finally, three personality indicators were employed,which included “maven knowledge and importance”(consumers’ identification of others as market mavens,their usefulness in assisting awareness and in aidingthe evaluation of goods and services) (Feick & Price,1987), “individualism” (Chelminski & Coulter, 2007,based on Singelis, 1994 and Triandis & Gelfand, 1998),and affinity for technology (using “personal innovative-ness in information technology” or PIIT) (Agarwal &Prasad, 1998).

Data Collection and Sample

Of the two surveys employed in the study, the firstsurvey was administered by means of two avatar “sur-vey bots” operating in Second Life for 10 days (n =240). Each bot is essentially an avatar automated todeliver the survey items in text form and to collect re-sponses in a database. Each bot had an advertisementfor the survey in its group name, above the avatar. De-tails of the survey were also provided in the profile ofthe avatar and respondents were requested to instantmessage (IM) the bot. Respondents initiate contact andare given details of the survey and how to begin thequestionnaire by sending an IM (with the word “SUR-VEY”). The survey then begins, with the respondentprompted to answer the questions in numerical format(e.g., “What is your gender? 1 = Male, 2 = Female”).One bot was male, another was female; both had for-mal attire. To collect sufficient responses, each bot wasplaced at a high-traffic location selected from SecondLife’s “popular locations” list. The two locations werechosen to be as generic as possible (to appeal to bothgenders, different ages, and nationalities) and each fo-cused on providing both free and paid-for digital con-tent and on generating traffic through paid “camping”activities (where individuals are paid small amounts ofmoney for time spent “sitting” at a particular location).

Respondents to the Second Life survey were theninvited to complete an online survey (via Question-Pro.com) measuring market maven behavior on theWeb and in real-life (n = 102). The second survey wassent only to individuals who had completed the Sec-ond Life survey to ensure a matched sample of respon-dents. This was sent four weeks after the first surveywas closed in order to clean the initial response list.A small monetary incentive (in Linden Dollars) of justunder US$2 was provided to respondents for each com-pleted survey (approximately 1 US$ = 265 Linden$, asof May, 2008). Two reminder messages were sent to


Table 1. Respondents’ Age and Gender Profiles.

Virtual World Real-Life/(n = 240) Web (n = 102)

GenderMale 125 (52.1%) 47 (46.1%)Female 115 (47.9%) 55 (53.9%)

Age18–24 98 (40.8%) 28 (27.5%)25–34 66 (27.5%) 36 (35.3%)35–44 43 (17.9%) 20 (19.6%)45–54 23 (9.6%) 13 (12.7%)55–64 6 (2.5%) 2 (2%)65+ 4 (1.7%) 3 (2.9%)

Second Life participants who had completed the firstsurvey to encourage them to complete the second sur-vey. All responses were collected within 10 days (seeAppendices A and B for all items and measures for bothsurveys).

The demographic profile of respondents to each sur-vey (see Table 1) suggests gender profiles were splitbroadly equally between males and females, althoughslightly more females replied to the second survey. Interms of age, data on respondents for all age cate-gories (18–65+) were captured. Respondents’ age pro-files were skewed toward the 18–34 group; the age pro-file of the second survey, however, was spread slightlymore evenly. As no comparative demographic profile(e.g., age and gender) for Second Life or virtual worldusage could be identified it is not possible to be cer-tain as to how the study sample aligns with the actualdemographic profile of virtual world users.

Data Analysis

In order to model and test the assumptions made andto assess the dimensionality of the scales, partial leastsquares path modeling (PLS-PM) was used with reflec-tive indicators (Centroid Weighting Scheme) in Smart-PLS where appropriate (Ringle, Wende, & Will, 2005).PLS has the advantage of being effective on small sam-ples, and does not require distributional assumptionsof the sample. Further, PLS is a useful statistical toolfor building and testing more inclusive models that ex-amine more complex sets of relationships for each ofthe various channels under study.

In order to gauge the adequacy of the sample forPLS, a post hoc power analysis using G∗Power 3 wasconducted (Faul, Erdfelder, Lang, & Buchner, 2007).The analysis (α = 0.05, 1 − β = 0.8) revealed that thesample sizes were adequate for the four separate PLSmodels generated for small-to-moderate population ef-fects (f ≥ 0.10, Models I and II; f ≥ 0.13, Model III; f ≥0.23, Model IV) (Faul et al., 2007).

The associated reliability and validity statistics forthe surveys and models are provided in the relevant ta-bles associated with the PLS analysis (see Appendix Cfor factor loadings and associated statistics). All items

load significantly on their factors with one exception—the third PIIT item did not load significantly in PLSModels III and IV and was omitted from further anal-ysis. The factors display acceptable levels of reliabil-ity (Cronbach’s α > 0.7 and composite reliability, ρc> 0.7, cf. Nunnally, 1978) and validity (AVE > 0.5,cf. Fornell & Larcker, 1981). Discriminant validity isalso demonstrated; the square root of AVE (averagevariance extracted) is larger than the intercorrela-tions. Furthermore, the intercorrelation between anypair of constructs does not exceed 0.9 (Model I, 0.393–0.746; Model II, 0.056–0.512; Model III, 0.063–0.659;and Model IV, 0.055–0.663), suggesting that the mul-ticollinearity problem can be ignored (Hair, Anderson,Tatham, & Black, 1998).

RESULTS

Market Maven Propensity across Channel

Initially, the relationship between the three contextsof maven behavior measured was examined (namely,real-life, Web, and virtual world mavenism). Theresults indicated a strong association between thechannels examined for market maven behavior (seeFigure 1), particularly from real-life to the Web (p <

0.001) and from the Web to virtual worlds (p < 0.01).Hence, market mavenism would appear to be a gener-ally constant phenomenon across channels. As such, amaven in real-life is more likely to display maven ten-dencies in other channels than a nonmaven, thus sup-porting the findings received for Hypothesis 1. Notably

Figure 1. PLS Model I—Maven behavior across all channels.Note: Significance levels denoted by †(10%), ∗(5%), ∗∗(1%), and∗∗∗(0.1%).Virtual world mavenism, n = 240; Web mavenism/real-lifemavenism, n = 102.


though, the R2 for virtual world market mavenism isonly 0.2, indicating that there are other factors that,in the context of a richer nomological net, are likely tobetter explain mavenism in the virtual world context.It is also interesting to note the weak direct maven re-lationship from real-life to virtual worlds (p = 0.10); itis posited that this is likely to be due to the quite dif-ferent perceptions, attitudes, and behaviors betweenthese channels (cf. Hemp, 2006). There is a stronger in-tuitive relationship between the Web channel and vir-tual worlds than between virtual worlds and real-life.Both of the former channels are information technol-ogy based and share some common characteristics, in-cluding the importance of human–computer interactionin behavioral outcomes and the use of electronic com-munications and social networking technologies. Thesefindings also offer support for Hypothesis 2 concerningthe variability of market mavenism between channels.

Market Maven Propensity and PersonalCharacteristics

This section considers market maven propensity andpersonal characteristics. All models tested (see Fig-ures 2–4) employed gender and age as moderating vari-ables but did not identify any significant results. There-fore, these findings offer no support to reject both nullHypotheses 3 and 4 (which posited that there would beno difference between age, gender, and market mavenpropensity).

The next series of tests examined the relationshipsbetween market mavenism and (i) individualism andknowledge of others as mavens for real-life settings,and also (ii) individualism, knowledge of others asmavens, personal innovativeness in information tech-nology, and channel interaction (experience and in-tensity) for both Web and virtual world channels (see

Figure 2. PLS Model II—Maven behavior in real-life.Note: Significance levels denoted by †(10%), ∗(5%), ∗∗(1%), and ∗∗∗(0.1%);n = 102.

Figure 3. PLS Model III—Maven behavior on the Web.Note: Significance levels denoted by †(10%), ∗(5%), ∗∗(1%), and ∗∗∗(0.1%);n = 102.


Figure 4. PLS Model IV—Maven behavior in virtual worlds.Note: Significance levels denoted by †(10%), ∗(5%), ∗∗(1%), and ∗∗∗(0.1%);n = 240.

Figures 2–4). Each of these constructs is now consid-ered in turn.

Across the three channels examined, the direct re-lationship between market mavenism and knowledgeof others as mavens (a composite of having knowledgeof others as mavens, receiving assistance from them,and using their help in the evaluation of goods and ser-vices) was modeled. The findings suggest that marketmavenism leads individuals to seek and receive assis-tance from other mavens across all three channels andthat mavens rely strongly on their network of othermavens for market information, thus providing supportfor Hypothesis 5. Interestingly, however, this behavioris strongest in real-life (p < 0.001), followed by the Web(p < 0.001), and finally, virtual worlds (p < 0.01), sug-gesting that mavens are less likely to be aware of othermavens and draw on their assistance on the Web andin virtual worlds compared to real-life, which may beattributed to mavens being more easily identifiable inreal-life than in electronic channels.

Next, the relationship between individualism andmarket mavenism was considered for the three chan-nels. The results obtained from the three PLS mod-els indicate that individualism is a determinant ofmavenism for all channels, and these effects arestronger in real-life (p < 0.001) than on the Web orin virtual worlds (p < 0.01). This implies that marketmavens are highly individualistic and provides supportfor Hypotheses 6. Further, these results suggest that

individuals may be marginally less individualisticwhen online, which might be attributed to the natureof social networking technologies such as aspects of theWeb and virtual worlds.

Another further personality construct included inthe assessment of the two technology channels, per-sonal innovativeness in information technology (PIIT),proved significant in both contexts (i.e., Web and virtualworld channels). In particular, PIIT was more signifi-cant for determining maven behavior on the Web (p <

0.01) than in virtual worlds (p < 0.05). Thus, innova-tive users who are more likely to adopt a technology,such as the Web or virtual worlds, are more likely touse it for market maven purposes, thus offering furthersupport for Hypothesis 7.

Finally, the impact of the individual’s interactionwith the channel (in terms of experience and intensityof use) on maven behavior was examined. For this, theimpact of Web experience (WEBEX) and Web use inten-sity (WEBINT) on Web maven behavior was modeledas was the relationship between virtual world expe-rience (VWEX) and use intensity (VWINT) on virtualworld maven behavior. The results for interaction vari-ables on Web mavens were not significant, suggestingthat use experience and use intensity did not signifi-cantly encourage users to become mavens in the Webchannel. The results for virtual world mavens, how-ever, suggest a significant relationship between virtualworld use intensity and virtual world maven behavior


(p < 0.001). This appears to imply that those frequentlyengaged in virtual world activities are more likely toengage in maven behavior. However, another interest-ing finding is the significant negative relationship be-tween Web use intensity (WEBINT) and virtual worldmaven behavior (p < 0.001). Thus, it appears that ahigher intensity of Web use detracts from virtual worlduse and thus the ability to develop maven characteris-tics, suggesting that there is a degree of trade-off be-tween the use of these different electronic channels.Therefore, only partial support can be offered for Hy-pothesis 8, which stipulated that individuals with highmarket maven propensity will have greater (i) chan-nel experience and (ii) intensity of usage of both Weband virtual worlds than individuals with low mavenpropensity.

Based on the tests conducted, the results of the hy-pothesis tests are summarized below (see Table 2). Ev-idence is offered to support four of the hypotheses andprovide partial support for one, while no evidence wasfound to reject the two null hypotheses. One hypothesiswas rejected.

CONCLUSIONS AND IMPLICATIONS

Virtual worlds are fast becoming recognized as an im-portant channel for companies to communicate andinteract with current and potential customers. They af-ford companies the opportunity to simulate customers’experiences in physical stores as well as enhancingproduct knowledge and influencing customer attitudesand purchase intentions (Lui, Piccoli, & Ives, 2007).This study represents one of the first attempts to bet-ter understand how consumer behavior might differ invirtual world channels, and, by so doing, better informthe understanding of an important group of consumers,namely market mavens. This group of consumers is ofparticular value to marketers as they are importantagents in disseminating positive (and negative) word-of-mouth and exerting personal influence over otherconsumers.

In the title to this study, a question was posed whichsuggested the possible existence of the “meta-maven”—individuals whose market maven behavior transcendschannel context. By providing empirical support formarket mavenism across channel and by exploring theexistence of mavens in virtual worlds, this study con-tributes and extends Feick and Price’s (1987) semi-nal work. Consequently, market maven behavior mightnot only span general product categories and marketinformation, but also the channel itself (i.e., mavenbehavior remains fairly constant—or fluid—acrosschannel).

The second area of inquiry was to understand thedegree to which market maven behavior was seen tobe constant across physical, Web and virtual worldchannels or whether maven behavior varied by chan-nel context. The results suggest that market maven

behavior is influenced by channel. Specifically, individ-uals with strong real-life market maven behavior per-ceive this to be at its strongest in this context, followedby the Web and lastly in virtual worlds. Therefore,while there may be the transferability of market mavenbehavior by channel (i.e., high-scoring market mavensretain this across channel), the findings indicate thatmavenism propensity is influenced by the channelcontext.

The significance of the research for marketers isclear. Given that online communities are useful chan-nels for consumers to engage in discussions, inform,and potentially influence others consumers (Kozinets,1999; Muniz & O’Guinn, 2001) targeting mavens viaonline channels would appear beneficial. This has im-portant implications for online advertising and viralmarketing. Marketing communications and strategiestargeted at market mavens deployed through onlinechannels (including using advertising, viral messag-ing, and cybercoupons) not only provides significantvalue in a single channel through word-of-mouth andother viral behavior, but should also prove useful acrossmultiple channels (e.g., real-life, the Web, and virtualworlds) through transferable maven behavior. There-fore, the comprehension that a market maven mightdisplay such behavior across channel context reinforcesthe view that mavens are fairly universal in their be-havior. Indeed, the relative anonymity afforded to indi-viduals in channels such as the Web and virtual worldsmay even encourage maven behavior and its transfer-ability across channel. As such, disseminating infor-mation in such relatively anonymous channels maybe perceived by mavens to be relatively low risk incomparison to interactions with individuals in real-lifesettings.

In the multichannel environment, market mavenstake on greater importance as useful agents to dissem-inate marketplace information across channel context.The findings also point to possible characteristics thatmay be used in the identification of market mavens bymarketers: market mavens will typically have greatercognizance of other mavens, be technology-savvy andindividualistic, will be of either gender and tend to beolder, will be more intensive and experienced users ofWeb platforms and intensive users of virtual worlds.Virtual worlds therefore offer a further means of tar-geting mavens.

As the understanding of market mavens—in termsof their demographics and behavior—is growing, it isworthwhile reflecting on the findings of this study incomparison with this earlier body of literature. In termsof gender, while Feick and Price (1987) and Goldsmith,Clark, and Goldsmith (2006) found that mavens weremore likely to be female, this study found no gender-based differences (in line with the findings of Walsh,Gwinner, & Swanson, 2004; Clark & Goldsmith, 2005;Geissler & Edison, 2005, and Clark, Goldsmith, & Gold-smith, 2008). This study also found no evidence thatmavenism is linked to age, which is in keeping with the


Table 2. Summary of Hypothesis Tests.

Hypothesis Accept/Reject

H1: Individuals with high market maven propensity retain this characteristic across channel. AcceptH2: Market maven behavior remains constant across physical, Web, and virtual marketing channels. RejectH3: There will be no difference in gender and market maven propensity. Failed to rejectH4: There will be no differences in age and market maven propensity. Failed to rejectH5: Individuals with high market maven propensity will be more likely to have (i) knowledge of other

market mavens, (ii) be assisted by them in raising awareness of goods and services, and (iii) usetheir help in evaluating goods and services than individuals with low market maven propensity.

Accept

H6: Individuals with high market maven propensity will display higher individualism thanindividuals with low market maven propensity.

Accept

H7: Individuals with high market maven propensity will have a greater affinity for technology thanindividuals with low market maven propensity.

Accept

H8: Individuals with high market maven propensity will have greater (i) channel experience and (ii)intensity of usage of both Web and virtual worlds than individuals with low maven propensity.

Partially accept

general consensus (Clark & Goldsmith, 2005; Clark,Goldsmith, & Goldsmith, 2008; Feick and Price, 1987;Goldsmith, Clark, & Goldsmith, 2006; Walsh, Gwinner,& Swanson, 2004).

The findings suggest that market mavens were morelikely to be individualistic than nonmarket mavens.This is consistent with the findings of Chelmin-ski and Coulter (2007), and also offers similaritieswith Clark, Goldsmith, and Goldsmith (2008)—whofound a relationship between aspects of consumer self-confidence and mavenism—and Clark and Goldsmith(2005), who offered evidence to suggest that mar-ket mavenism is associated with higher self-esteemand a need for uniqueness expressed through brandchoice.

In terms of affinity for new technology, the find-ings support Geissler and Edison (2005), who foundthat mavens were likely to have a greater affinity to-ward new technology than nonmavens, and broadlywith Andrews and Benedicktus (2006) who found thatmavenism was associated with innovativeness and neg-atively related to resistance to change. For channel ex-perience and intensity of usage, the results for Webmavens were not significant, although the data didshow a relationship between virtual world usage in-tensity and market mavenism. Given their affinity fornew technology, however, it is perhaps not surpris-ing that mavens seek further conduits to diffuse theirknowledge.

Often overlooked by researchers of the marketmaven concept is the notion that mavens are cognizantof other mavens. Feick and Price (1987) found that asizeable proportion of respondents had knowledge ofother mavens, were assisted by them in raising aware-ness of goods and services, and received their helpin evaluating goods. The results concur with Feickand Price’s (1987) original findings, and also extendthem as they show that this behavior occurs acrossall three channels examined, suggesting that there issomething pervasive about this aspect of a maven’spersonality.

Finally, and central to the study, it was assertedthat market mavens retain this characteristic acrosschannel—an assertion that has no base of comparisonin previous studies as it has not been the subject of em-pirical attention. While some variability across chan-nel was found, market mavenism would appear to be agenerally constant phenomenon across physical, Web,and virtual world channels. In this regard, this find-ing offers support for the pervasive nature of Feick andPrice’s (1987) market maven concept.

This study, like all others, has several limitationsthat need mention. Initially, a convenience sample wasemployed. More precise sampling techniques may aidgeneralizability. Although Second Life is arguably themost popular virtual world, it is not the only vir-tual world; studies of different virtual worlds maylead to different results. Finally, while this study hasadded to the understanding of the demographic pro-files of market mavens and personal characteristics,other measures could be used and would be valuablein shedding further light on this important group ofconsumers.

Virtual worlds have added new channels to typicalbusiness models. Such channels are unlikely to displaceother more “traditional” channels and shopping modesbut rather to offer greater consumer choice and access(cf. Goldsmith & Flynn, 2005). Greater channel choiceopen to consumers merits additional study chiefly interms of the channel decisions made by consumers aswell as those of marketers. Understanding the transfer-ability of key concepts (such as market mavenism) andthe generalizability of “real-world” findings to virtualworlds will further extend knowledge of this increas-ingly important medium.

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Correspondence regarding this article should be sent to:Stuart J. Barnes, Norwich Business School, University ofEast Anglia, Norwich NR4 7TJ, U.K. ([email protected]).


APPENDIX A

Table A1. Virtual World Maven Survey.

Measure Item

Gender Are you:• Male• Female

Age • 18–24 years• 25–34 years• 35–44 years• 45–54 years• 55–64 years• 65+ years

Virtual world knowledge How long have you been using Second Life?• less than one month• more than one and less than three months• more than three and less than six months• more than six and less than 12 months• more than one year and less than two years• more than two years

Virtual world intensity In an average week, how much time would you say you spend on Second Life?• less than one hour• between one and four hours• between four and 10 hours• between 10 and 30 hours• between 30 and 60 hours• more than 60 hours

Virtual world marketmavenism

Please answer the following statements on a scale from 1 = strongly disagree to 7 = stronglyagree, and where 4 = neutral (neither agree nor disagree). The statements will ask you aboutyour opinions and behavior in Second Life.

• I like using information collected from Second Life to introduce new brands and products to myfriends.

• I like helping people by using Second Life to provide them with information about many kindsof products.

• People ask me for information on Second Life about products, locations to shop, or sales.• If someone wanted to know which Second Life locations had the best bargains on several types

of products, I could tell him or her where to shop.• My friends think of me as a good source of information on Second Life when it comes to new

products or sales.• Think about a person who gets information from Second Life about a variety of products, and

likes to share this information with others. This person knows about how to use Second Life,how to find information on Second Life, what the best locations are, and so on, but does notnecessarily feel he or she is an expert on the products he/she gathers information on. How welldoes this description fit you?


APPENDIX B

Table B1. Web and Real-Life Maven Survey.

Measure Item

Gender Are you:• Male• Female

Age • 18–24 years• 25–34 years• 35–44 years• 45–54 years• 55–64 years• 65+ years

Web knowledge How long have you been using the Web?• less than a year• more than a year and less than two years• more than two years and less than three years• more than three years and less than five years• more than five years and less than 10 years• more than 10 years

Web intensity In an average week, how much time would you say you spend using the Web? · less than one hour• between one and four hours• between four and 10 hours• between 10 and 30 hours• between 30 and 60 hours• more than 60 hours

Web marketmavenism

The following statements will ask you about your opinions and behavior regarding your use of the WorldWide Web (NOT Second Life). Please answer the statements on a scale from 1 = strongly disagree to 7 =strongly agree, and where 4 = neutral (neither agree nor disagree).

• I like helping people by using the Web to provide them with information about many kinds of products.• I like using information collected from the Web to introduce new brands and products to my friends.• People ask me for information on the Web about products, locations to shop, or sales.• If someone wanted to know which Web sites had the best bargains on several types of products, I could

tell him or her where to shop.• My friends think of me as a good source of information on the Web when it comes to new products or sales.• Think about a person who gets information from the Web about a variety of products, and likes to share

this information with others. This person knows about how to use the Web, how to find information onthe Web, what the best locations are, and so on, but does not necessarily feel he or she is an expert on theproducts he/she gathers information on. How well does this description fit you?

Real-life marketmavenism

The following statements will ask you about your opinions and behavior in real-life (i.e., physical channels),including shopping in physical stores. Please answer the statements on a scale from 1 = stronglydisagree to 7 = strongly agree, and where 4 = neutral (neither agree nor disagree).

• I like using information collected from real-life to introduce new brands and products to my friends.• I like helping people by using real-life channels to provide them with information about many kinds of

products.• People ask me for information from real-life channels about products, locations to shop, or sales.• If someone wanted to know which locations in real-life had the best bargains on several types of products,

I could tell him or her where to shop.• My friends think of me as a good source of information in real-life when it comes to new products or sales.• Think about a person who gets information from real-life about a variety of products, and likes to share

this information with others. This person knows about how to use real-life channels, how to findinformation in real-life, what the best locations are, and so on, but does not necessarily feel he or she isan expert on the products he/she gathers information on. How well does this description fit you?

Influence of others as mavensKnowledge Do you know someone, other than yourself, who has information about a variety of products, stores, sales,

etc. and likes to share this general information with others?Yes/No

Assistance How important is this person in helping you to find out about new brands and products?Evaluation How important is this person in helping you to evaluate different brands and products?

• Extremely important• Important• Somewhat important• Neutral• Somewhat unimportant


Table B1. Continued

Measure Item

• Unimportant• Extremely unimportant• Not applicable

Individualism Please answer the following statements on a scale from 1 = strongly disagree to 7 = strongly agree, andwhere 4 = neutral (neither agree nor disagree).

• I’d rather depend on myself than others.• I rely on myself most of the time.• My personal identity, independent of others, is very important to me.• Being able to take care of myself is a primary concern for me.• I enjoy being unique and different from others.• It is important to me that I do my job better than others.

PIIT Please answer the following statements on a scale from 1 = strongly disagree to 7 = strongly agree, andwhere 4 = neutral (neither agree nor disagree).

• If I heard about a new information technology, I would look for ways to experiment with it.• Among my peers, I am usually the first to try out new information technologies.• I like to experiment with new information technologies.• In general, I am hesitant to try out new information technologies.

APPENDIX C

Factor Loadings and Associated Statisticsfor PLS Models

Table C1. Model I—Results of PLS Analysis.

Real-Life VirtualWeb Maven Maven World Maven

Items (Loadings) (Loadings) (Loadings)

Web maven1 0.890∗∗∗Web maven2 0.874∗∗∗Web maven3 0.788∗∗∗Web maven4 0.857∗∗∗Web maven5 0.875∗∗∗Web maven6 0.784∗∗∗Real-life maven1 0.789∗∗∗Real-life maven2 0.889∗∗∗Real-life maven3 0.879∗∗∗Real-life maven4 0.895∗∗∗Real-life maven5 0.906∗∗∗Real-life maven6 0.828∗∗∗VW maven1 0.752∗∗∗VW maven2 0.771∗∗∗VW maven3 0.595∗∗∗VW maven4 0.712∗∗∗VW maven5 0.762∗∗∗VW maven6 0.713∗∗∗Reliability and average variance extractedAVE 0.716 0.749 0.518Cronbach’s α 0.920 0.933 0.812CR 0.938 0.947 0.865

Note: Significance level denoted by ∗∗∗(0.1%).AVE = average variance extracted; CR = composite reliability.

Table C2. Model II—Results of PLS Analysis.

Influence ofOthers as Real-Life

Individualism Mavens Maven(Loadings) (Loadings) (Loadings)

Individualism1 0.881∗∗∗Individualism2 0.863∗∗∗Individualism3 0.839∗∗∗Individualism4 0.868∗∗∗Individualism5 0.893∗∗∗Individuailism6 0.831∗∗∗Influence of others 0.946∗∗∗

as mavens1Influence of others 0.955∗∗∗

as mavens2Influence of others 0.931∗∗∗

as mavens3Real-life maven1 0.779∗∗∗Real-life maven2 0.885∗∗∗Real-life maven3 0.876∗∗∗Real-life maven4 0.898∗∗∗Real-life maven5 0.908∗∗∗Real-life maven6 0.842∗∗∗Individualism → 0.512∗∗∗

real-life mavenReal-life maven → 0.297∗∗∗

influence of othersas mavens

Reliability and average variance extractedAVE 0.744 0.891 0.750Cronbach’s α 0.931 0.941 0.933CR 0.946 0.961 0.947R2 0.088 0.262Discriminant validityIndividualism 0.863Influence of others 0.056 0.944

as mavensReal-life maven 0.512 0.297 0.886

Note: Significance level denoted by ∗∗∗(0.1%); intercorrelations fordiscriminant validity are shown in italics on diagonal; n = 102.

AVE = average variance extracted; CR = composite reliability.


Table C3. Model III—Results of PLS Analysis.

Individualism Influence of Others Affinity for Web Maven(Loadings) as Mavens (Loadings) Technology (Loadings) (Loadings)

Individualism1 0.882∗∗∗Individualism2 0.854∗∗∗Individualism3 0.841∗∗∗Individualism4 0.872∗∗∗Individualism5 0.899∗∗∗Individualism6 0.826∗∗∗Influence of others as mavens1 0.941∗∗∗Influence of others as mavens2 0.947∗∗∗Influence of others as mavens3 0.938∗∗∗PIIT1 0.899∗∗∗PIIT2 0.822∗∗∗PIIT3 0.050a

PIIT4 0.901∗∗∗Web maven1 0.886∗∗∗Web maven2 0.875∗∗∗Web maven3 0.775∗∗∗Web maven4 0.856∗∗∗Web maven5 0.882∗∗∗Web maven6 0.795∗∗∗Individualism → Web maven 0.246∗∗PIIT → Web maven 0.356∗∗∗WEBEX → Web maven 0.066WEBINT → Web maven 0.089Web maven → influence of others as mavens 0.261∗∗∗Reliability and average variance extractedAVE 0.744 0.888 0.765 0.716Cronbach’s α 0.931 0.941 0.846 0.920CR 0.946 0.959 0.907 0.938R2 0.068 0.398Discriminant validityIndividualism 0.863Influence of others as mavens 0.063 0.942PIIT 0.658 0.143 0.875Web maven 0.543 0.261 0.583 0.846

Note: Significance levels denoted by ∗∗(1%), and ∗∗∗(0.1%); intercorrelations for discriminant validity are shown in italics on diagonal; n = 102.aItem omitted from structural model.AVE = average variance extracted; CR = composite reliability.


Table C4. Model IV—Results of PLS Analysis.

Influence of Affinity forIndividualism Others as Mavens Technology Virtual World

(Loadings) (Loadings) (Loadings) Maven (Loadings)

Individualism1 0.880∗∗∗Individualism2 0.843∗∗∗Individualism3 0.841∗∗∗Individualism4 0.876∗∗∗Individualism5 0.896∗∗∗Individualism6 0.838∗∗∗Influence of others as mavens1 0.942∗∗∗Influence of others as mavens2 0.951∗∗∗Influence of others as mavens3 0.935∗∗∗PIIT1 0.923∗∗∗PIIT2 0.756∗∗∗PIIT3 0.082a

PIIT4 0.914∗∗∗Virtual world maven1 0.720∗∗∗Virtual world maven2 0.749∗∗∗Virtual world maven3 0.618∗∗∗Virtual world maven4 0.697∗∗∗Virtual world maven5 0.715∗∗∗Virtual world maven6 0.776∗∗∗Individualism → virtual world maven 0.288∗∗∗PIIT → virtual world maven 0.199∗∗∗WEBEX → virtual world maven 0.055WEBINT → virtual world maven −0.339∗∗∗VWEX → virtual world maven 0.057VWINT → virtual world maven 0.428∗∗∗Virtual world maven → influence of others as mavens 0.183∗∗Reliability and average variance extractedAVE 0.744 0.889 0.753 0.510Cronbach’s α 0.931 0.941 0.846 0.812CR 0.946 0.960 0.901 0.861R2 0.034 0.359Discriminant validityIndividualism 0.863Influence of others as mavens 0.055 0.943PIIT 0.663 0.134 0.868Virtual world maven 0.447 0.183 0.386 0.714

Note: Significance level denoted by ∗∗(1%), and ∗∗∗(0.1%); intercorrelations for discriminant validity are shown in italics on diagonal; n = 240.aItem omitted from structural model.AVE = average variance extracted; CR = composite reliability.


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