Brand, Identity and Reputation: Exploring, Creating New Realities ...

Is this Sponsor a Good Exemplar? Investigating Sport Sponsorship as a Goal-Derived Category
Peter Dickenson, Loughborough University, United Kingdom
Chanaka Jayawardhena, Loughborough University, United Kingdom
Introduction
It is unclear why certain brands are assumed to be sponsors of sporting events even though they are not sponsors, while
other brands, which are actually sponsors, are not associated at all. Previous studies examining this question have
manipulated sponsor-sponsee relationships in such a way that it has limited one‘s understanding of sponsorship effects.
Consequently, understanding how to capitalise or counteract these effects is inadequate, especially when marketing to
specific consumers. The objective of this paper is to address this research question. In so doing we suggest a new
approach.
Purpose
Due to the different suggested heuristics that are assumed to play a part in constructing sponsorship evaluations, it is
proposed that sponsorship should in fact be investigated in terms of a goal-derived category, which consists of members
(brands) that subjects think of when forming their consideration set. Goal-derived categories are defined as those
categories created simply to achieve a particular goal where category members are taken from several taxonomic
(product/service) categories and only become salient when relevant to the necessary goal (Barsalou, 1985). A
consideration set is defined as ―the set of brands that are brought to mind and scrutinized carefully at a particular choice
occasion‖ (Suh, 2009). The graded structure of members distinguishes them from unordered sets (Rosch, Simpson and
Miller, 1976). Graded structure refers to the ―continuum of category representativeness, beginning with the most
representative members of a category and continuing through its atypical members to those nonmembers least similar to
category members‖ (Barsalou, 1985).
To the best of the authors‘ knowledge, ‗sponsorship‘ per se has not been considered as a goal-derived category before.
If such a category of ‗sponsorship‘ can be found then it would suggest that particular factors would share unique
correlations with member typicality. This is important because previous consumer-behaviour research has
predominantly found a linear relationship between member typicality and brand evaluation measures (Loken, Barsalou
and Joiner, 2008). It has also been suggested that the schema congruity effect, where moderate (in)congruity leads to
greater evaluations compared to congruity conditions, may not occur in goal-derived categories (Noseworthy et al.,
2010).
Methodology
Barsalou‘s (1985) methodology (study one) was closely followed, except only brand names were generated during the
main part of the procedure. Unless otherwise stated, subjects were randomly chosen students from a large UK
university, assigned to different conditions, where the research instrument had the appearance of a survey. Subjects in
the first manipulation were asked to generate brands ‗associated with the category: sponsorship‘ and were given a time
period of 30 seconds for each category label. The brands which were mentioned by at least two separate subjects were
included in the ‗sponsorship‘ category. Output dominance scores were calculated by the number of times a brand was
mentioned.
Subsequent subjects were either asked to rate ‗exemplar goodness‘, ‗ideals‘, ‗frequency of instantiation‘ (‗FoI‘) or
‗central tendency‘ (a convenience sample was used for subjects completing the central tendency measures because of
the considerable time needed to complete measures for this variable). If ‗exemplar goodness‘ was being rated, subjects
were told to circle a number on the 9-point scale, anchored by ‗poor example‘ and ‗excellent example‘. If ‗frequency of
instantiation‘ was being rated, subjects were told to circle a number on the 9-point scale, anchored by ‗not frequently at
all‘ and ‗very frequently‘. If ‗central tendency‘ was being investigated, subjects were asked to rate how similar they
perceived each brand to be with the brand it was paired with when considering them together under the category of
sponsorship. In total, there were 190 pairs of brands with anchors on the 9-point scale labelled ‗not similar at all‘ and
‗very similar‘. If ‗ideals‘ was being rated, subjects were told to circle a number on the 9-point scale, anchored by ‗very
low amount‘ and ‗very high amount‘. Unlike Barsalou (1985), they were not given a specific ‗ideal‘ dimension. This is
because subjects could perceive a number of ‗ideals‘ that would make a brand a good sponsor. Brand ratings in each of
these variables were averaged according to the procedure used by Barsalou (1985). Expertise was determined using a
median split on an adapted version of Dickerson and Gentry‘s (1983) sports enthusiasm scale.
Results
Initially, correlation scores were calculated for all groups, before expert- and novice- groups were produced. Without an
‗expertise split‘, all variables (‗ideals‘, ‗FoI‘, ‗CT‘, ‗exemplar goodness‘ and ‗output dominance‘) appear to be
significantly correlated with each other (correlations significant at at least the .05 level) apart from two – ‗central
tendency‘ and ‗output dominance‘ and ‗ideals‘ and ‗output dominance‘. Also, ‗ideals‘ and ‗exemplar goodness‘ and
‗frequency of instantiation‘ and ‗exemplar goodness‘ show the highest correlations, matching Barsalou‘s (1985) initial
work, as well as suggesting ‗FoI‘ and ‗Ideals‘ could predict typicality of the ‗sponsorship‘ category.
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