“The Role of Peer-to-Peer Communication in Online Sponsorship”

Online communities are widely studied in marketing and information systems literature.

However, research on the sponsorship effects in online communities is scarce. This research fills

part of this gap by providing an analysis of the role of community commitment and social

network communication in predicting the intention to purchase online sponsoring products. In

particular, this study provides evidence of the relationship between peer-to-peer communication

and online sponsorship effectiveness, examining the relationship between intention to purchase,

online sponsorship outcomes (goodwill, attitude, and fit), commitment and activation in peer-to-

peer communication. Through the analysis of a group of web communities (700) in an online

sponsorship context, the authors demonstrate that people active in peer-to-peer communication

show a greater intention to purchase online sponsoring products than passive community

members. However, not all active members of a community are similar: participants who share

information through different social networks are more sensitive to online sponsorship than

members who use emails.

Keywords: online sponsorship, peer-to-peer communication, online community, intention to

purchase, commitment.

Article classification: Research paper.

1

1 Introduction

Among the marketing advertising activities used by firms, sponsorship is one of the most studied

in the literature (Cornwell and Maignan, 1998; Rifon et al., 2004; Cornwell and Coote, 2005;

Simmons and Becker-Olsen, 2006). In general, sponsorship is an investment in an activity, cause,

or event (or a Web community) made in return for access to exploitable commercial potential

(Meenaghan, 1998).

Cause-related sponsorship, in particular, is a donation that makes an event or an organisation

possible. In doing so, firms hope to gain consumer attitude, goodwill and purchases (Cornwell

and Coote, 2005). The principles of cause-related sponsorship are based on cause-related

marketing, a strategy whereby firms make financial contributions and/or support non-profit

organisations in order to engage in a revenue-providing exchange that satisfies both business and

individual objectives (Varadarajan and Menon, 1988).

Many non-professional sport teams in Europe survive because of firms that support these groups

in an instrumental (e.g., t-shirts, games instruments) and/or expressive way (e.g., banners, logo

expositions and advertising). Thus, , sponsoring companies gain the appearance of “good

citizenship” (Rifon et al., 2004); and, they acquire short- and long-term influence on awareness

and identification of sponsors (Gwinner, 1997; Pham and Johar, 2001), attitude toward sponsors

(Speed and Thompson, 2000; Stipp, 1998), purchase intentions (Madrigal, 2001; McDaniel,

1999) or brand loyalty (Cornwell and Maignan, 1998).

In sponsorship, the Internet has become an important tool to establish and/or leverage

sponsorship activities because many sport teams have their own websites and use them to

communicate with fans, players and managers. Thus, the Internet plays an important role for

2

sponsoring companies because it opens a “richness of niches” (Brynjolfsson et al., 2006) in

which sponsors can utilize websites, blogs, and online communities of every sport, specialisation,

and localisation. For example, teams’ websites are a big opportunity for companies because they

can reach a committed target audience with less expense compared to events and meetings

(Drennan and Cornwell, 2004). In addition, because these communities are part of a virtual

ecosystem (Hanna et al., 2011), peer-to-peer communication (virtual communication among the

members of a community) and eWOM (electronic Word-Of-Mouth – the viral communication

among members and non-members of a community) are common tools to communicate among

social networks. In particular, in this paper, we focus on peer-to-peer communication, because in

the sponsorship literature, the effects of peer-to-peer communication and communications among

people attending sponsorship events or activities are insufficiently studied. To the best of our

knowledge, few authors have investigated peer-to-peer communication in online sponsorship, and

furthermore, word-of-mouth is only considered an outcome of sponsorship activities and not an

opportunity for marketers (Tsiotsou and Alexandris, 2009).

To fill this gap in the literature, this research presents evidence of the effect of peer-to-peer

communication and of community commitment on the outcomes of cause-related sponsorship

(from this point called sponsorship) in an online environment.

This research is based on the study of an Italian web portal that assembles more than 700 non-

professional sport teams’ websites. Each website is the online channel of the local community

related to a non-professional sport team. In the online environment, members of the community

can upload pictures, share comments and exchange news about the results and the performances

of their teams.

The effectiveness of online sponsorship in the 700 non-professional sport teams’ websites is

measured by the intention to purchase evaluating two different types of factors: the outcome of

3

online sponsorship (in terms of attitude, goodwill, and congruence), and the characteristics of the

online community members (pertaining, in particular, to their commitment and to peer-to-peer

communication).

After the literature review, the theoretical framework with hypotheses is introduced. Presentation

on methodology is followed by the test of these hypotheses. Paper is concluded with the

discussion of the results, managerial implications and future research avenues.

2 Literature review

The Internet is an interactive tool, allowing companies to leverage sponsored events and activities

in order to increase the effectiveness of traditional sponsorship (see also Becker-Olsen, 2003;

Rodgers, 2003; Drennan and Cornwell, 2004; Weeks et al., 2008). Nevertheless, the Internet is

also a sponsorship context itself in which companies can sponsor communities, blogs, and online

events (Drennan and Cornwell, 2004). Moreover, thanks to the Internet’s interactive nature,

sponsorship becomes an opportunity to create and/or maintain close relations with potential and

actual consumers through website content (Becker-Olsen, 2003) and to activate viral fans’

seeding communications (Ferguson, 2008; Hinz et al., 2011). In particular, the Internet increases

the diffusion of viral communication, eWOM (Zwass, 1996; Chen, Fai and Wang, 2011;

Chevalier and Mayzlin, 2006; Liu 2006), and peer-to-peer communication, thereby offering

advertising instruments more effective than traditional media (Lee and Youn, 2009; Trusov et al.,

2009).

Sponsorship researchers consider eWOM as an outcome of sponsorship activities (Tsiotsou and

Alexandris, 2009; Trusov et al., 2009) but, to our knowledge, no other author considers online

peer-to-peer communication as a tool to leverage sponsorship advertising or activities. Thus, as

4

highlighted by Hogan et al. (2004), the effectiveness of advertising is underestimated if the ripple

effect of virtual environments is not taken into account; the same conclusions can be extended to

sponsorship.

The effects of peer-to-peer communication has been studied in different contexts, such as, e-

commerce (Chen, Fay and Wang, 2011; Chen, Wang and Xie, 2011); advertising (Kozinets et al.,

2010); brand communities (Adjei, Noble and Noble, 2010); web forums (O'Sullivan, 2010),

underling the effectiveness of peer-to-peer communication to publicise products, services and

brands which leads to a higher awareness and to a cost-effective adoption by the market

(Krishnamurthy, 2000). The action to “send this message to a friend” or to “share this news on

Facebook” implies an active role for the sender who decides to share the information (Trusov et

al., 2010). This peer-to-peer communication is a powerful viral communication tool because

people can signal news or information contained in websites, providing potential consumers to

the sponsoring products and brands. Moreover, these viral messages are very effective because

they are sent by known persons, so they can be considered, by the readers, of higher value than

advertising messages or messages received directly from companies (Phelps et al., 2004).

Nevertheless these aspects are overlooked in sponsorship contexts.

In order to fill this gap, we analyse the effects of sponsorship on collectors (people who share

news and information to friends through email, social networks, blogs, and online platforms).

3 Research framework

Consumers’ responses to sponsorship can be cognitive (congruence, brand awareness and brand

image), affective (preference, attitude and goodwill) and behavioural (intention to purchase and

purchase). We focused on an online community context, and use a combination of the Theory of

5

Reasoned Action (TRA; for further details, see Ajzen and Fishbein, 1974) and online

communities and sponsorship theories (Meenaghan, 2001a, 2001b; Cornwell et al., 2005) to

study the online antecedents of the intention to purchase sponsoring products. The purchase

intention was chosen as main sponsorship outcome for two main reasons: first, because the final

objective of a company is to get consumers and their loyalty; second because this variable is

closely related to the community and teams dynamics already studied in previous studies. For

instance, Madrigal (2000) argued that individuals with higher levels of psychological attachment

to a team are more likely to support the property also indirectly, through their willingness to

purchase sponsors’ products. Moreover, according to the TRA, the attitude toward companies and

brands predicts the intention to purchase their products and services; our model agrees with this

and supposes that the attitude towards the online sponsors predicts the visitors’ intention to

purchase. We also consider the sponsorship literature (Meenaghan, 2001b; Cornwell et al., 2005)

in order to enrich the model with the affective antecedent (i.e., the goodwill) and the cognitive

antecedent (i.e., the congruence) of the intention to purchase online sponsors’ products/services.

Moreover, because our aim is to study the sponsorship in a community context, we test members’

commitment to the community (a certain sport team) and its members’ peer-to-peer

communication activity as predictors of the effectiveness of online sponsorship (i.e., the intention

to purchase).

In this matter, our theoretical framework explains some of the most effective elements predicting

the intention to purchase in a community context through an online sponsorship (Figure 1).

6

Figure 1: Theoretical framework

3.1 Online sponsorship effectiveness

In sport sponsorship literature, the effectiveness of sponsorship activities is traditionally

identified with the intention to purchase sponsoring products and services (Pope and Voges,

1999; Madrigal, 2001; Speed and Thompson, 2000; Alexandris et al., 2012). Similarly, in cause-

related sponsorship literature, some authors consider intention to purchase sponsoring products as

the main result of a sponsorship campaign, even though the objective is to support non-profit

activities (Madrigal, 2000; Barone et al., 2000; Simmons and Becker-Olsen, 2006).

In evaluating online sponsorship, some researchers depict the effectiveness of sponsorship

through the intention to purchase (Harvey, 2001; Becker-Olsen, 2003; Weeks et al., 2008),

7

Commitment to the community

Attitude to the sponsor online

Goodwill towards the sponsor online

Viral communication by email

Congruence between online community and

sponsor online

Intention to purchase

HP +

HP +

HP +

HP +

HP +

Viral communication by posts in social

networks

HP +

because the Internet is a measurable and interactive advertising tool that has direct effects on

sales and consumer behaviours. In particular, Harvey (2001) asserts that sponsored online content

can increase the intention to purchase among participants using and not using the sponsoring

brands. Becker-Olsen (2003) demonstrates how sponsored content on websites is an effective

advertising tool in terms of both attitudinal and behavioural responses from website users.

Rodgers (2003) studies the differences in the effectiveness of relevant and irrelevant sponsorships

online, in terms of recall, attitude towards the sponsors and intention to purchase. Weeks et al.

(2008) concentrate on leveraging sponsorship when websites become a way to support sponsored

events through virtual channels. In particular, the latter study demonstrates that the Internet is an

effective tool to leverage sponsorship activities.

Therefore, to study the effectiveness of sponsorship in an online community context, we test the

commitment to the community, enriching the model with the connected peer-to-peer

communication.

3.2 Online community effects

3.2.1 Commitment

According to social identity theory, members of communities are motivated to support their

sponsors because of their identification with their groups (Bhattacharya et al., 1995). This

identification leads them to be involved in the successes and failures of their group (Ashforth and

Mael, 1989). In traditional sponsorship, members’ commitment is related to the team’s

identification (spectators’ perceived connectedness to a team and its performance), and

subsequently, to the purchase intention (Gwinner and Swanson, 2003; Lings and Owen, 2007).

Thus, individuals who identify with a community or group are more likely to patronise sponsors

8

who support the group and its continued existence (Cornwell and Coote, 2005; Gwinner and

Swanson, 2003). In particular, Gwinner and Swanson (2003) contend that the more positive the

affiliation is with the group (property), the more likely members will be to recall or recognise the

sponsor. Moreover, commitment is considered a moderating factor between the attitude and the

effectiveness of sponsorship (Gwinner and Swanson, 2003; Lings and Owen, 2007).

Research regarding online communities, however, reveals how commitment to an online

community affects directly the intention to purchase the advertising brands and products

(Bagozzi and Dholakia, 2002; Kim et al., 2008; Park et al., 2007).

The main difference between the two streams of research is that, in sport sponsorship, many

participants are fans or spectators, whereas in online communities participants are people who

actively form and create the communities themselves. In the latter, members are much more

committed because they are not only spectators but also direct players in the community, directly

involved in its organisation/administration, directing or functioning. Therefore, the commitment

of these players can directly affect the effectiveness of online advertising. Additionally, in our

research context (non-professional teams’ websites), participants are deeply involved in the

existence of the community because they are players, managers or players’ relatives who actively

create the teams and participate in their functions. We expect that the commitment of these

members can directly affect the effectiveness of online sponsorship. Therefore, we hypothesize:

H1: The commitment to the team is an antecedent to the intention to purchase the online

sponsoring products and/or services.

9

3.2.2 Peer-to-peer Communication

The research on online communities reveals how consumers’ offline and online intentions to

purchase are affected by online community activities. A substantial body of literature

demonstrates how online word-of-mouth predicts and affects the offline intention to purchase

(Chevalier and Mayzlin, 2006; Dellarocas et al., 2007).

Research on viral communication primarily focuses on the reasons to pass along messages. Ho

and Dempsey (2010) study the motivations of e-mavens, i.e., people who actively spread

information through online tools such as email, Facebook and others. These activities are

common in online community contexts, where people share useful information and comments;

these behaviours may be interpreted as altruistic, but they are actually a way to express one’s

uniqueness (Griskevicius et al., 2008). Finally, the most important reasons for sending viral

messages are identified by Phelps et al. (2004) as the need for enjoyment and entertainment.

In addition, we can identify two main tools to send viral messages online: signalling web content

by email and/or information through different social networks (e.g., Facebook and Twitter). In

the first case, people use email to communicate news and information to specific receivers,

whereas in the second case, they post messages on their social network web pages to all of their

contacts (Trusov et al., 2009; Trusov et al., 2010; Chen et al., 2011). In both cases, we expect that

people who share information are more focused and involved in community activities; therefore,

we expect that they are also more sensitive to sponsorship activities than passive community

members. Thus, we hypothesize:

10

H2: Community members who share information about the sponsored website through email

messages demonstrate a greater intention to purchase sponsoring products and/or services than

other community members.

H3: Community members who share information about the sponsored website on social networks

demonstrate a greater intention to purchase sponsoring products and/or services than other

community members.

3.3 Antecedents of Sponsorship Effectiveness

3.3.1 Attitude

In traditional sponsorship research, Nicholls et al. (1999) demonstrate that preference is a good

measure of sponsorship effectiveness beyond the positive attitude towards the sponsor

(McDaniel, 1999; Speed and Thompson, 2000; Madrigal, 2001; Becker-Olsen and Simmons,

2002; Eagleman and Krohn, 2012; Macintosh et al., 2012). Thus, in sponsorship literature,

attitude is an effective outcome of sponsorship. Moreover, in TRA, attitude is the focal element

to understand the consumer choices; the TRA model is the nomological core for many research

projects that study sponsorship effectiveness (McDaniel, 1999; Speed and Thompson, 2000;

Harvey, 2001; Irwin et al., 2003; Simmons and Becker-Olsen, 2006). Weeks et al. (2008)

demonstrate that sponsors of websites can positively affect the attitude towards their products

and/or services, and, consequently, the related intention to purchase. These authors differentiate

between “activational” websites, where visitors can interact with sponsors, and “non-

activational” websites, where sponsorship is displayed through static banners. In both cases, the

sponsorship audience develops a positive attitude towards the sponsors, with a higher degree and

11

for a longer period for activational websites. Studying the banners’ effectiveness, Lings and

Owen (2007) demonstrate that sponsorship banners can improve the attitude toward the company,

the customer responsiveness, the perceptions of product quality and, consequently, the related

intention to purchase. Breuer and Brettel (2012) emphasize how online advertising developed

through banners is the second most effective advertising tool – after the search engine marketing.

In here, the online community and its teams’ websites are sponsored through static banners. Thus,

we expect that online sponsorship creates a positive attitude towards the sponsors and,

consequently, that it stimulates the intention to purchase. Therefore, we propose the following

hypothesis:

H4: Members’ attitudes towards online sponsors predict their intention to purchase sponsoring

products and/or services.

3.3.2 Goodwill

Goodwill (i.e., members’ belief that the sponsor is doing the best for the community) is unique to

sponsorship: this form of communication is distinguished from traditional advertising because it

lowers consumers’ defence mechanisms (Meenaghan, 2001a). Goodwill is generated by the

perception of benefit for the team (or for the community) and by the possibility of distinguishing

a commercial intent in the communication. The sponsorship literature indicates that sponsored

activities that emphasise emphasize the commercial motivation reduce the favourability of

consumer perceptions of the sponsor (Becker-Olsen and Simmons, 2002; Rifon et al., 2004; Dees

et al., 2010; Carrillat and d'Astous, 2012). If the sponsor explains its well-intentioned motives,

both affective and behavioural customer’s responses may increase (Becker-Olsen and Simmons,

12

2002). In an online context, Weeks et al. (2008) state that, if the relationship between sponsor

and sponsored is explained by non-commercial statements, it has a greater impact on attitudes

toward the online sponsor than a relationship based on commercial motivations has.

The online sponsorship studied in this research concerns static banners highlighting companies’

brands/products or services that support the non-professional teams’ website. Although these

banners do not include any explanation of the reasons for the sponsorship, we expect that the

goodwill perceived by communities’ members toward the online sponsors positively affects their

intentions to purchase the sponsoring brands and products (Weeks et al., 2008). Therefore, we

seek to prove the following hypothesis:

H5: Members’ goodwill towards online sponsors predicts the intention to purchase sponsoring

products and/or services.

3.3.3 Congruence

When the sponsor and the sponsored event (or community) share a logical relationship, this

congruence facilitates sponsor identification (Johar and Pham, 1999; Wakefield and Bennett,

2010); moreover, it encourages a positive attitude toward the sponsor (Roy and Cornwell, 2004)

and creates favourable ratings of the sponsor’s image (Speed and Thompson, 2000).

In sponsorship literature, authors use the term “congruence” to outline the direct relevance of the

sponsor to the event (i.e., when the sponsors’ products are used during the sponsored events) or

its indirect relevance (i.e., when the sponsors’ brands share a similar image or the same values

with the sponsored events) (see also McDonald, 1991; Gwinner, 1997; Rifon et al., 2004). This

13

all indicates that customers develop a higher cognitive and affective responsiveness when they

can easily encode the association between sponsoring companies and events.

Congruence (or fit) becomes decisive in improving or in determining the effectiveness of

sponsorship, particularly in an online environment. According to Becker-Olsen (2003), the

effectiveness of online sponsored contents is mainly evident with a high fit between sponsored

website and sponsoring brands. Weeks et al. (2008) demonstrate that the Internet is an effective

tool to leverage sponsorship activities but, in order to develop a more favourable and durable

attitude, sponsors must be accurate in their fit (congruence with the website), articulation (the

explanation of motives for the sponsorship) and activation (information provided online about the

sponsored event).

Rodgers (2003) demonstrates that the relevant online sponsorships have a greater impact on the

intention to purchase than irrelevant sponsorships.

Because online sponsorship can be more actionable due to the Internet’s hyperlink characteristics,

we assert the following hypothesis:

H6: Congruence between online sponsors and the non-professional sport team is an antecedent of

the intention to purchase the sponsoring brands or products.

4 Research design

We studied an Italian web portal that collects more than 700 non-professional sport teams’

websites. Each website is visited by players, managers and fans. It contains photos, results of

14

competitions, news and information about the team. Members of the community can upload

pictures, share comments and exchange news about the results and the performances of their

teams.

To answer to the research questions, we administered a survey to a sample of community

members. The websites of all 700 non-professional sport teams belonging to the Gioca

community (www.gioca.cc) and a link was posted to an online questionnaire. To ensure

consistency with previous studies, the questionnaire was drawn from the available literature

(Churchill, 1979). In particular, this study adapted and increased the measures proposed by

Meenaghan (2001b) and Dees et al. (2008), as explained in the proceedings.

The research model studied includes five constructs and two dichotomous variables used to

analyse the online sponsorship. The dependent variable is the “intention to purchase sponsoring

products”. As independent variables, we consider the following constructs: “attitude toward the

online sponsor”, “goodwill toward the online sponsor”, “sponsor congruence”, and “commitment

to the team”.

Each of these four constructs and the dependent variable were measured by four statements; the

respondent was asked to express how much he/she agrees with each statement using a 4 points

Likert scale. To consider both the agreement and the disagreement with a certain statement, the

original observed values on the Likert scale were recoded as follows. Negative scores were

assigned to the respondents who disagree with a certain statement: “completely disagree (1)” was

recoded into “-2”, “disagree (2)” was recoded into “-1”. On the contrary, positive scores were

assigned to respondents whose “agree (3)” (recoded into “+1”) or “strongly agree (4)” (recoded

into “+2”) with a certain statement. These scores provided us with a more detailed and accurate

measure of the respondent’s positioning concerning a certain construct. Moreover, they allowed

us to balance the agreement and the disagreement within the statements of the same construct.

15

Finally, we acquired more accurate estimates of the models. The results obtained using the

recoded variables (rather than the original values of the variables) actually show a fairly high

level of significance.

In addition to the listed independent variables (the four constructs), in the model we also

considered the item “peer-to-peer communication” by introducing two dichotomous variables to

measure the level of active use of viral communication’s instruments (“Viral communication

through Email” and “Viral communication through Social Networks”). The introduction of these

two variables in the model aims at verifying whether community members who were active in

sharing information online had a higher level of intention to purchase than passive community

members.

The validity and reliability of the constructs and their measurement were tested through a

preliminary questionnaire submitted to 50 university students who play on sport teams

(Churchill, 1979). This test allowed us to refine some questions, in order to make them more

comprehensible, and allowed us to delete two inconsistent item..

In the pre-test phase of the survey, we identified four items that related to the dependent variable

“intention to purchase the online sponsoring brands and products”. This construct shows internal

consistency (Cronbach’s α = 0.876; item-to-total correlations, r, higher than 0.676).

Four items representing members’ positive predispositions towards the sponsoring companies

originally measured the attitude toward the online sponsors (Dees et al., 2008). The factor

analysis suggested that one item should be deleted (factor loading ≤ 0.45). The reliability analysis

supported the internal consistency of this measurement scale (α = 0.783; r = 0.619).

Drawing on Meenaghan’s definitions (2001b), we measured goodwill towards the online

sponsors using three 4-point Likert-type items (one item was deleted after the pre-test phase).

Such items represent the community members’ perceptions that the online sponsors support the

16

team especially for their interest in non-professional sport activities. Cronbach’s alpha shows that

the goodwill measurement scale was internally consistent (α = 0.763 and r = 0.54).

To evaluate sponsor congruence (Meenaghan, 2001b), three items were used (one item was

eliminated after the pre-test). They describe the perceptions of community members that sponsors

and non-professional teams share a logical connection, their values and their image. Cronbach’s

alpha showed the internal consistency (α = 0.781, r = 0.622).

Finally, commitment to the team (or to the community) was originally measured by four items

representing members’ attachment and involvement with the teams and with their sport

association (Meenaghan, 2001b). The factor analysis suggested deleting two items with a factor

loading ≤ 0.45. The reliability analysis supported the internal consistency of this measurement

scale (α = 0.73; item-to-total correlations > 0.58).

After the test phase, the definitive version of the questionnaire was published, and links to the

questionnaire were inserted both on the web portal’s home page and on each team’s website.

5 Results

The online questionnaire was available to visitors to the portal and/or websites between June and

September 2009. During this period, 139 questionnaires were completed. After a preliminary

analysis to check the collected questionnaires’ quality, 130 of them were retained and analysed.

Observing the distribution of the respondents (n = 130) by their role on the team, we noticed that

managers represent the most significant category (43.8%), followed by players (30.8%), coaches

(10%), players’ relatives (7.7%) and fans (6.9%). Unfortunately, a comparison between the

17

distribution of the self-selected sample and that of the target population is not possible; in fact,

only approximately 5% of registered members has indicated their current role in the community

when registering on the web portal. Because we are working with a self-selected sample, we

encounter the risk of collecting biased data; in this case, individuals in some categories could be

more likely to participate in the survey. However, the distribution of respondents by role

indicates that we obtained a well-balanced presence from all of the considered categories. This

finding also dovetails with the sponsors’ primary objective, to reach (and to get a complete

picture of) the community in its entirety.

An evaluation of the respondents’ level of involvement in team activities shows that 91.1% of

them regularly attend their team’s competitions, whereas 11.5% attend competitions with some

frequency, and 2.1% seldom attend. Moreover, 54.6% of the survey participants visit the team’s

website every day, with 26.2% visiting once a week and 17.7% only once a month. Thus, we can

conclude that the sample is generally composed of people who are highly involved in the

community and in both the online and the offline activities of the team.

All of the questionnaire’s variables have been tested for normality, and the exploratory factor

analysis was implemented to select the items most relevant to the intention to purchase

sponsoring products online: “attitude toward the online sponsor”, “goodwill toward the online

sponsor”, “sponsor congruence”, and “commitment to the team”. By applying factor analysis to

the 12 proposed items (using the maximum likelihood extraction and the orthogonal Varimax

rotation) and interpreting the factor loadings, we obtained the four expected independent

variables. Some items from the original list were deleted because they either do not load at the

0.3 level (suggested by Nunnally and Bernstein, 1994) or cross-load on several factors. Criteria

such as the eigenvalues (acceptable if ≥ 1), the level of factor loadings (≥ .45), the KMO (Kaiser-

18

Meyer-Olkin) measure of sampling adequacy and the Bartlett’s test of sphericity were used to

derive the four components. These account for 75.22% of the total variance.

The main results of the factor analyses on the cited independent variables are summarised in

Table 1.

Table 1. Composition of measures and items descriptive statisticsFactors and items

(α = Conbrach’s alpha; EV = Eigenvalue; VAR = % of explained variance)

Std. Loading

Mean(min: -2;max: + 2)

S.D.

Goodwill toward the online sponsors( = 0.845; EV = 4.38; VAR = 39.87%)Online sponsors support our sport activities 0.84 .146 1.550Our team benefits from the online sponsors 0.75 .238 1.493Online sponsors are involved with their community 0.66 .315 1.525Attitude toward the online sponsors( = 0.783; EV = 1.59; VAR = 14.50%)Companies that sponsor my team online are professional 0.80 1.030 1.193Companies that sponsor my team online provide quality products/services 0.78 1.207 .764

Companies that sponsor my team online are leader in their industry 0.60 .476 1.376

Sponsor’s congruence( = 0.763; EV = 1.253; VAR = 11.40%)Online sponsors and our team have the same values 0.78 .169 1.463There is a logical connection between our team and the online sponsors 0.63 -.0615 1.503

The image of the online sponsors and that of my team are similar 0.54 -.453 1.409Commitment to the team( = 0.73; EV = 1.040; VAR = 9.45%)My friends view me as a strong fan of our team 0.84 .853 1.300I see myself as a strong fan of our team 0.71 1.284 1.087Intention to purchase online sponsoring products( = 0.88; EV = 2.92; VAR = 72.88%)I would definitely buy products/services from our online sponsors 0.85 .153 1.433

It is likely that I will buy the products/services of our team’s online sponsors 0.83 .430 1.441

I would try one of the products/services of our team’s online sponsors if they were available before or after a game 0.77 .538 1.370

My overall attitude toward purchasing products/services from our team’s online sponsors is positive 0.74 .853 1.335

19

Moreover, a single factor analysis was conducted on the dependent variable to obtain a single

factor score used to estimate the proposed model, in terms of intention or likelihood to purchase

the sponsoring online brands or products.

Finally, we inserted in our model two more independent dummy variables: the independent

components “peer-to-peer communication by email” and “peer-to-peer communication in social

networks”. The first variable identifies people who use email to share information, whereas the

second one identifies people who use posts on social networks to share the information from the

sponsored web page.

To test our hypothesis, we estimated a regression model in order to assess the determinants for

the intention to purchase online sponsoring brands and products. In our analysis, we considered,

in particular, the attitude and the goodwill towards the online sponsors, the congruence between

online sponsors and the community (or the team), the commitment to the community and the

viral communication. Three control variables were also introduced in the regression analysis, in

order to test the robustness of the model. The first one reflects the respondent’s role: it divides the

sample in people who are directly part of the community (e.g., players, coaches and managers)

and people who are outside the community (fans and players’ relatives). The second control

variable refers to the frequency of respondents’ attendance at the team’s matches. Based on this

frequency, a score between 1 and 10 was given to the respondents as follows: “every time the

team plays” = 10; “once a week” = 9; “once a month” = 4; “when I can” = 2; “never” = 0. The

third control variable reflects the frequency of the respondent’s website visits. The responses

were recoded as follows: “everyday” = 10; “once a week” = 7; “once a month” = 3. Even if the

recoding of these control variables is made on an arbitrary basis, we presume that, in this case,

the recoded variables give us the chance to consider the different levels of distance between the

20

response options. This means that the “distance” between “once a week” and “once a month” in

the frequency of match attendance should not be equal to the same distance in the frequency of

website visiting (considering that the frequency of matches is usually once a week). A

preliminary analysis of data confirmed the pertinence of the recoding. The comparison with the

analysis developed using dummies obtained from the original variables (rather than with recoded

ones) supports the hypothesis that the recoded variables are more effective in highlighting the

relationships studied by the model.

Before the analysis, all of the factors were tested for multicollinearity, but the results did not

reveal problems (VIF < 1.479). The correlations between the tested variables are shown in Table

2.

Table 2: Correlations (between perceived co-brand value, perceived brand image, perceived responsiveness and brand loyalty)

Correlations

Intention to purchase online sponsoring products

Goodwill towards online sponsors

Attitude towards online sponsors

Congruence between sponsors and communities

Commitment to the community

Viral Communication (SN)

Viral Communication (Email)

Intention to purchase online sponsoring products

1

Goodwill towards online sponsors

.333** 1

Attitude towards online sponsors

.370** .069 1

Congruence between sponsors and communities

.392** .101 .077 1

Commitment to the community

.267** -.024 .013 .024 1

Viral Communication (SN)

.227** .083 .001 -.063 .160 1

Viral Communicati

.115 .073 .044 .109 .136 .472** 1

21

on (Email)** p < 0.01

Table 3 illustrates the results of the regression analysis (standardised regression coefficients (B),

standard errors, and VIFs). Both the R2 (.679) and the adjusted R2 (.469) are significantly

different from zero (p < .000). To validate the regression analysis, the underlying assumptions

were tested: the analysis of the normal probability plot of residuals and the plot of the residuals

against the predicted values confirm the hypotheses of normal distribution and of

homoscedasticity.

The results of the regression analysis show that all the six considered variables (attitude towards

online sponsors, goodwill towards online sponsors, correspondence between sponsors and

communities, commitment to the community, peer-to-peer communication by email and peer-to-

peer communication by posts on social networks) are significant, except one (viral

communication by email). The model accounts for approximately 46% of the variance in the

intention to purchase of online sponsoring products.

These findings support the following five of the six suggested hypotheses: commitment to the

community (hp. 1), peer-to-peer communication in social networks (hp. 3), attitude towards

online sponsors (hp. 4), goodwill towards online sponsors (hp. 5), and correspondence between

sponsors and communities (hp. 6).

These results are interesting for three reasons. First, in an online community sponsorship predicts

the intention to purchase the sponsoring products and brands, as expected. In addition, the

characteristics of online community members (commitment and peer-to-peer communication) can

directly affect their intention to purchase sponsoring products. The third interesting element

pertains to the role of viral communication: our analysis indicates that not all collectors

demonstrate a greater intention to purchase sponsoring products than passive members. People

22

active in social networks are more sensitive to sponsorship, but people who use personalised tools

(such as email) do not show a significantly higher level of intention to purchase online.

Therefore, online long-tail communities can be a source of committed people who also

participate actively in other social networks. Collectors in these virtual contexts can leverage

sponsoring products, thereby becoming viral communication diffusers.

Finally, peer-to-peer communication by email is not significant; nevertheless, the sign of the beta

parameter leads us to presume a negative relation. Although more analysis is needed, this initial

counterintuitive signal suggests that not all active community members are equal. Some members

create value and are more receptive to sponsorship messages, whereas other active members may

not contribute to the effectiveness of sponsorship.

Table 3: Regression model (dependent variable: intention to purchase online sponsor’s products)

Standardized coefficients

(beta)

Standard error VIF Hypothesis check

Commitment to the community .228* .068 1.146 H1 supported

Peer-to-peer communication by email -.126 .168 1.479 H2 not supported

Peer-to-peer communication by posts on social networks .244* .163 1.348 H3 supported

Attitude towards online sponsors .312* .072 1.051 H4 supported

Goodwill towards online sponsors .267* .071 1.045 H5 supported

Congruence between sponsors and communities .361* .075 1.047 H6 supported

Role on the team 0.34 .025 1.171 -

Frequency of match attendance -0.35 .029 1.101 -

Frequency of website visits 0.53 .027 1.117 -

R2 = 0.679*; adjusted-R2 = 0.461*

* p < .05

23

6 Conclusions

Sport sponsorship has become an increasingly important element of a firm’s communication mix,

with many corporations actively pursuing sponsorship in an attempt to avoid the clutter

associated with more traditional marketing communications (Meenaghan, 1996).

With sport sponsorship, sports spectators are exposed to corporate messages under favourable

conditions such as enthusiasm, excitement and enjoyment, which make them more relaxed and

receptive to the promotional message (Dolphin, 2003). In the same way, in online communities

pertaining to personal hobbies, members are exposed to sponsorship in a favourable condition of

participation and concentration.

Thus, our results demonstrate that, in online contexts, sponsorship affects the attitude, goodwill

and perceived congruence towards sponsoring brands and product, factors which together also

predict behavioural outcomes (the intention to purchase).

In addition, we also identify two important characteristics of online communities that can

leverage the sponsorship effectiveness: members’ commitment and peer-to-peer communication.

The results of our analysis support the assertion that in niche communities, members’

commitment is a direct antecedent to their intention to purchase online sponsoring products and

services. Because the members of these communities are directly involved in the existence and

development of the community itself, they likely understand very well the benefits that sponsors

can provide to their activities; for these reasons, they demonstrate a higher responsiveness to

sponsoring brands and products.

24

These findings are particularly useful for brand managers because, on the whole, contemporary

consumers are less committed to brands (Firat and Venkatesh, 1993), and people are also losing

interest in advertising. Meanwhile, the time they are spending online is increasing each year, and

the cost of online contact is very low. For these reasons, online long-tail groups can become a

lucrative market for sponsorships. In these contexts, companies and members can share value in a

more cooperative way, transferring the feelings and the messages that buying sponsors’ products

also means supporting the team.

Furthermore, the results demonstrate not only the strength of commitment to a group in these

communities, but also the potential for peer-to-peer communication to trigger online viral

communication among members participating in different social networks. The Internet is an

open ecosystem (Hanna et al., 2011) where peer communication is easy and costless. Thus,

people engaged in collecting and sharing information (collectors) can also be bearers of

sponsored content and sponsoring brands. Sport community members are also more sensitive to

sponsorship, showing a higher level of intention to purchase of online sponsoring products than

more passive members. This means that they also carry positive messages in the virtual

ecosystem.

These results are very valuable for brand managers because, according to Bernoff and Li (2008),

collectors are different from creators (members who publish, maintain and upload), critics

(members who comment and rate information and news), joiners (members who connect and

unite) and spectators (passive members). Collectors mostly use online functions like “share this

news on Facebook” or “tweet this information”, and marketing managers can monitor them

simply using some web metrics.

Therefore, this research confirms the general applicability of the model suggested by Meenaghan

(2001b) in an online community context. Moreover, a further contribution to the literature is the

25

demonstration that online communities can become a more receptive field for sponsorship due to

the members’ commitment and their activities in peer communication.

This study has limitations as well. Because it is exploratory research, further analyses with

different samples are needed before generalising the results. In addition, this empirical study

focuses on a particular community of interests related to sport activities, and thus, future analysis

could extend to different communities of interests (e.g., several kinds of hobbies). Finally, the

number of participants surveyed should be increased.

Despite these limitations, this study generates several research opportunities regarding online

communities, their members’ behaviour and their efficacy from the perspective of sponsoring

companies.

26

REFERENCES

Adjei, M., Noble, S., & Noble, C. (2010) ‘The influence of C2C communications in online brand communities on customer purchase behavior’, Journal of the Academy of Marketing Science, 38(5), pp. 634-653.

Ajzen, I. & Fishbein, M. (1974) ‘Factors Influencing Intentions and the Intention-Behavior Relation’, Human Relations, 27(1), pp. 1-15.

Alexandris, K., Tsiotsou, R. H., James, J., Alexandris, K., Tsiotsou, R., & James, J. (2012) ‘Testing a Hierarchy of Effects Model of Sponsorship Effectiveness’, Journal of Sport anagement, 26(5), pp. 363-378.

Ashforth, B. E. & Mael, F. (1989) ‘Social Identity Theory and the Organization’, Academy of Management Review, 14(1), pp. 20-39.

Bagozzi, R. P. & Dholakia, U. M. (2002) ‘Intentional Social Action in Virtual Communities’, Journal of Interactive Marketing (John Wiley & Sons), 16(2), pp. 2-21.

Barone, M. J., Miyazaki, A. D. & Taylor, K. A. (2000) ‘The Influence of Cause-Related Marketing on Consumer Choice: Does One Good Turn Deserve Another?’, Journal of the Academy of Marketing Science, 28(2), pp. 248-262.

Becker-Olsen, K. & Simmons, C. J. (2002) ‘When Do Social Sponsorships Enhance or Dilute Equity? Fit, Message Source, and the Persistence of Effects’, Advances in Consumer Research, 29(1), pp. 287-289.

Becker-Olsen, K. L. (2003) ‘And Now, a Word from Our Sponsor ‘, Journal of Advertising, 32 (2), pp. 17-32.

Bernoff, J. & Li, C. (2008) ‘Marketing - Harnessing the power of the oh-so-social web’, MIT Sloan Management Review, 49(3), pp. 36-42.

Bhattacharya, C. B., Rao, H. & Glynn, M. A. (1995) ‘Understanding the bond of identification: An investigation of its correlates among art museum’, Journal of Marketing, 59(4), pp. 46-57.

Breuer, R., & Brettel, M. (2012) ‘Short- and Long-term Effects of Online Advertising: Differences between New and Existing Customers’, Journal of Interactive Marketing, 26(3), pp. 155-166.

Brynjolfsson, E., Hu, Y.J., Smith, M.D (2006) ‘From Niches to Riches: Anatomy of the Long Tail’, MIT Sloan Management Review, 47(4), pp. 67-71.

Carrillat, F. A., & d'Astous, A. (2012) ‘The sponsorship-advertising interface: is less better for sponsors?’, European Journal of Marketing, 46(3/4), pp. 562-574.

Chen, Y., Fay, S., & Wang, Q. (2011) ‘The role of marketing in social media: How online consumer reviews evolve’, Journal of Interactive Marketing, 25(2), pp. 85-94.

Chen, Y., Wang, Q., & Xie, J. (2011) ‘Online social interactions: A natural experiment on word of mouth

27

versus observational learning’, Journal of Marketing Research, 48(2), pp. 238-254.

Chevalier, J. A. & Mayzlin, D. (2006) ‘The Effect of Word of Mouth on Sales: Online Book Reviews’, Journal of Marketing Research’, 43(3), pp. 345-354.

Churchill, G. A., (1979) ‘A Paradigm for Developing Better Measures of Marketing Constructs’, Journal of Marketing Research, 16(1), pp. 64–73.

Cornwell, T. B. & Coote, L. V. (2005) ‘Corporate sponsorship of a cause: the role of identification in purchase intent’, Journal of Business Research, 58(3), pp. 268-276.

Cornwell, T. B. & Maignan, I. (1998) ‘An International Review of Sponsorship Research’, Journal of Advertising, 27(1), pp. 1-21.

Cornwell, T. B., Weeks, C. S. & Roy, D. P. (2005) ‘Sponsorship-Linked Marketing: Opening the Black Box’, Journal of Advertising, 34(2), pp. 21-42.

Dees, W., Bennett, G. & Villegas, J. (2008) ‘Measuring the Effectiveness of Sponsorship of an Elite Intercollegiate Football Program’, Sport Marketing Quarterly, 17(2), pp. 79-89.

Dees, W., Hall, T., Tsuji, Y., & Bennett, G. (2010) ‘Examining the effects of fan loyalty and goodwill on consumer perceptions of brands at an action sports event’, Journal of Sponsorship, 4(1), pp. 38-50.

Dellarocas, C., Zhang, X. M. & Awad, N. F. (2007) ‘Exploring the value of online product reviews in forecasting sales: The case of motion pictures’, Journal of Interactive Marketing (John Wiley & Sons), 21(4), pp. 23-45.

Dolphin, R., R. (2003) ‘Sponsorship: perspectives on its strategic role’, Corporate Communications: An International Journal, 8(3), pp. 173-186.

Drennan, J. C. & Cornwell, T. B. (2004) ‘Emerging Strategies for Sponsorship on the Internet’, Journal of Marketing Management, 20(9/10), pp. 1123-1146.

Eagleman, A. N., & Krohn, B. D. (2012) ‘Sponsorship Awareness, Attitudes, and Purchase Intentions of Road Race Series Participants’, Sport Marketing Quarterly, 21(4), pp. 210-220.

Ferguson, R. (2008) ‘Word of mouth and viral marketing: taking the temperature of the hottest trends in marketing’, Journal of Consumer Marketing, 25(3), pp. 179-182.

Firat, A. F. & Venkatesh, A. (1993) ‘Postmodernity: The age of marketing’, International Journal of Research in Marketing, 10(3), pp. 227-249.

Griskevicius, V., Cialdini, R. B. & Goldstein, N. J. (2008) ‘Applying (and resisting) peer influence’, MIT Sloan Management Review, 49(2), pp. 84-88.

Gwinner, K. (1997) ‘A Model of Image Creation and Image Transfer in Event Sponsorship’, International Marketing Review, 14(2/3), pp. 145-158.

Gwinner, K.P. & Swanson, S.R. (2003) ‘A Model of Fan Identification: Antecedents and sponsorship outcomes’, The Journal of Services Marketing, 17(2/3), pp. 275- 294.

28

Hanna, R., Rohm, A. & Crittenden, V. L. (2011) ‘We're all Connected: The Power of the Social Media Ecosystem’, Business Horizons, 54(3), pp. 265-273.

Harvey, B. (2001) ‘Measuring the Effects of Sponsorships’, Journal of Advertising Research, 41(1), pp. 59-65.

Hinz, O., Skiera, B., Barrot, C., & Becker, J. U. (2011) ‘Seeding strategies for viral marketing: An empirical comparison’, Journal of Marketing, 75(6), pp. 55-71.

Ho, J. Y. C. & Dempsey, M. (2010) ‘Viral marketing: Motivations to forward online content’, Journal of Business Research, 63(9/10), pp. 1000-1006.

Hogan, J. E., Lemon, K. N. & Libai, B. (2004) ‘Quantifying the Ripple: Word-of-Mouth and Advertising Effectiveness’, Journal of Advertising Research, 44(3), pp. 271-280.

Irwin, R. L,. Clark, J. & Lachowetz, T. (2003) ‘Cause-related sport marketing: Can this marketing strategy affect company decision-makers?’, Journal of Management & Organization, 16(4), pp. 550-556.

Johar, G. V. & Pham, M. T. (1999) ‘Relatedness, Prominence, and Constructive Sponsor Identification’, Journal of Marketing Research, 36(3), pp. 299-312.

Kim, J. W., Jiho, C., Qualls, W. & Kyesook, H. (2008) ‘It takes a marketplace community to raise brand commitment: the role of online communities’, Journal of Marketing Management, 24(3/4), pp. 409-431.

Kozinets, R., de Valck, K., Wojnicki, A., & Wilner, S. (2010) ‘Networked Narratives: Understanding Word-of-Mouth Marketing in Online Communities’, Journal Of Marketing, 74(2), pp. 71-89.

Krishnamurthy, S. (2000) ‘Deciphering the Internet Advertising Puzzle’, Marketing Management, 9(3), pp. 34-39.

Lee, M. & Youn, S. (2009) ‘Electronic word of mouth (eWOM)’, International Journal of Advertising, 28(3), pp. 473-499.

Lings, I. N. & Owen, K. M. (2007) ‘Buying a sponsor’s brand: the role of affective commitment to the sponsored team’, Journal of Marketing Management, 23(5/6), pp. 483-496.

Liu, Yong (2006) ‘Word of Mouth for Movies: Its Dynamics and Impact on Box Office Revenue’, Journal of Marketing, 70, July, pp. 74–89.

Madrigal, R. (2000) ‘The Influence of Social Alliances with Sports Teams on Intentions to Purchase Corporate Sponsors’ Products’, Journal of Advertising, 29(4), pp. 13-24.

Madrigal, R. (2001) ‘Social Identity Effects in a Belief-Attitude-Intentions Hierarchy: Implications for Corporate Sponsorship’, Psychology & Marketing, 18(2), pp. 145-165.

Macintosh, E., Nadeau, J., Seguin, B., O'Reilly, N., Bradish, C. L., & Legg, D. (2012) ‘The Role of Mega-Sports Event Interest in Sponsorship and Ambush Marketing Attitudes’, Sport Marketing Quarterly, 21(1), pp. 43-52.

McDaniel, S. R. (1999) ‘An Investigation of Match-Up Effects in Sport Sponsorship Advertising: The Implications of Consumer Advertising Schemas’, Psychology & Marketing, 16(2), pp. 163-184.

29

McDonald, C. (1991) ‘Sponsorship and the Image of the Sponsor’, European Journal of Marketing, 25(11), pp. 31-38.

Meenaghan, T. (1996) ‘Ambush Marketing: a Threat to Corporate Sponsorship’, Sloan Management Review, 38(1), pp. 103-113.

Meenaghan, T. (1998) ‘Current developments & future directions in sponsorship’, International Journal of Advertising, 17(1), pp. 3-28.

Meenaghan, T. (2001a) ‘Sponsorship and Advertising: A Comparison of Consumer Perceptions’, Psychology & Marketing, 18(2), pp. 191-215.

Meenaghan, T. (2001b) ‘Understanding Sponsorship Effects’, Psychology & Marketing, 18(2), pp. 95-122.

Meenaghan, T. & Shipley, D. (1999) ‘Media Effect in Commercial Sponsorship’, European Journal of Marketing, 33(3/4), pp. 328-347.

Nicholls, J. A. F., Roslow, S. & Dublish, S. (1999) ‘Brand recall and brand preference at sponsored golf and tennis tournaments’, European Journal of Marketing, 33(3/4), pp. 365-386.

Nunnally, J. & Bernstein, I. (1994) Psychometric Theory, 3rd ed., McGraw Hill, New York.

O'Sullivan, T. (2010) ‘Dangling conversations: Web-forum use by a symphony orchestra's audience members’, Journal Of Marketing Management, 26(7/8), pp. 656-670.

Park, D.-H., Lee, J. & Han, I. (2007) ‘The Effect of On-Line Consumer Reviews on Consumer Purchasing Intention: The Moderating Role of Involvement’, International Journal of Electronic Commerce, 11(4), pp. 125-148.

Pham, M. T. & Johar, G. V. (2001) ‘Market Prominence Biases in Sponsor Identification: Processes and Consequentiality’, Psychology & Marketing, 18(2), pp. 123-143.

Phelps, J. E., Lewis, R., Mobilio, L., Perry, D. and Raman, N. (2004) ‘Viral Marketing or Electronic Word-of-Mouth Advertising: Examining Consumer Responses and Motivations to Pass Along Email’, Journal of Advertising Research, 44(4), pp. 333-348.

Pope, N. K. & Voges, K. E. (1999) ‘Sponsorship and Image: A Replication and Extension’, Journal of Marketing Communications, 5(1), pp. 17-28.

Rifon, N. J., Choi, S. M., Trimble, C. S. & Li, H. (2004) ‘Congruence Effects in Sponsorship’, Journal of Advertising, 33(1), pp. 29-42.

Rodgers, S. (2003) ‘The effects of sponsor relevance on consumer reactions to internet sponsorships’, Journal of Advertising, 32(4), pp. 67-76.

Roy, D. P. & Cornwell, T. B. (2004) ‘The Effects of Consumer Knowledge on Responses to Event Sponsorships’, Psychology & Marketing, 21(3), pp. 185-207.

Simmons, C. J. & Becker-Olsen, K. L. (2006) ‘Achieving Marketing Objectives Through Social

30

Sponsorships’, Journal of Marketing, 70(4), pp. 154-169.

Speed, R. & Thompson, P. (2000) ‘Determinants of Sports Sponsorship Response’, Journal of the Academy of Marketing Science, 28(2), pp. 227-238.

Stipp, H. (1998) ‘The impact of Olympic sponsorship on corporate image’, International Journal of Advertising, 17(1), pp. 75-87.

Trusov, M., Bucklin, R. E., & Pauwels, K. (2009) ‘Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site’, Journal of marketing, 73(5), pp. 90-102.

Trusov, M., Bodapati, A., & Bucklin, R. E. (2010) ‘Determining influential users in internet social networks’, Journal of marketing Research, XLVII (August), pp. 643–658. 

Tsiotsou, R. & Alexandris, K. (2009) ‘Delineating the outcomes of sponsorship: Sponsor image, word of

mouth, and purchase intentions’, International Journal of Retail & Distribution Management, 37(4), pp. 358-369.

Varadarajan, P. R. & Menon, A. (1988) ‘Cause-Related Marketing: A Coalignment of Marketing Strategy and Corporate Philanthropy’, Journal of Marketing, 52(3), pp. 58-74.

Wakefield, K. L. & Bennett, G. (2010) ‘Affective Intensity and Sponsor Identification’, Journal of Advertising, 39(3), pp. 99-111.

Weeks, C. S., Cornwell, T. B. & Drennan, J. C. (2008) ‘Leveraging sponsorships on the Internet: Activation, congruence, and articulation’, Psychology & Marketing, 25(7), pp. 637-654.

Zwass, V. (1996) ‘Editorial Introduction’, Journal of Management Information Systems, 13(1), pp. 3-8.

31