“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-topeer 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.
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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 nonprofessional 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, ecommerce (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).
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Figure 1: Theoretical framework
Attitude to the
sponsor online
HP +
Goodwill towards
the sponsor online
HP +
Commitment to the
community
Congruence between
online community and
sponsor online
Intention to purchase
HP +
HP +
HP +
Viral communication
by email
HP +
Viral communication
by posts in social
networks
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 causerelated 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
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.
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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:
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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 “nonactivational” 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,
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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
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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.
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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 statistics
Factors and items
(α = Conbrach’s alpha; EV = Eigenvalue; VAR = % of explained variance)
Goodwill toward the online sponsors
( = 0.845; EV = 4.38; VAR = 39.87%)
Online sponsors support our sport activities
Our team benefits from the online sponsors
Online sponsors are involved with their community
Attitude toward the online sponsors
( = 0.783; EV = 1.59; VAR = 14.50%)
Companies that sponsor my team online are professional
Companies that sponsor my team online provide quality
products/services
Companies that sponsor my team online are leader in their
industry
Sponsor’s congruence
( = 0.763; EV = 1.253; VAR = 11.40%)
Online sponsors and our team have the same values
There is a logical connection between our team and the online
sponsors
The image of the online sponsors and that of my team are similar
Commitment to the team
( = 0.73; EV = 1.040; VAR = 9.45%)
My friends view me as a strong fan of our team
I see myself as a strong fan of our team
Intention to purchase online sponsoring products
( = 0.88; EV = 2.92; VAR = 72.88%)
I would definitely buy products/services from our online
sponsors
It is likely that I will buy the products/services of our team’s
online sponsors
I would try one of the products/services of our team’s online
sponsors if they were available before or after a game
My overall attitude toward purchasing products/services from our
team’s online sponsors is positive
19
Mean
Std.
Loading
(min: -2;
max: + 2)
S.D.
0.84
0.75
0.66
.146
.238
.315
1.550
1.493
1.525
0.80
1.030
1.193
0.78
1.207
.764
0.60
.476
1.376
0.78
.169
1.463
0.63
-.0615
1.503
0.54
-.453
1.409
0.84
0.71
.853
1.284
1.300
1.087
0.85
.153
1.433
0.83
.430
1.441
0.77
.538
1.370
0.74
.853
1.335
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
Communicati
on (SN)
Viral
Communicati
on (Email)
Intention to
purchase
online
sponsoring
products
Congruence
Goodwill
Attitude
between
towards online towards online
sponsors and
sponsors
sponsors
communities
Commitment
to the
community
Viral
Communicati
on (SN)
Viral
Communicati
on (Email)
1
.333**
1
.370**
.069
1
.392**
.101
.077
1
.267**
-.024
.013
.024
1
.227**
.083
.001
-.063
.160
1
.115
.073
.044
.109
.136
.472**
** p < 0.01
21
1
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-topeer 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
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