In lieu of an abstract, here is a brief excerpt of the content:

  • Relatedness, prominence, and constructive sponsor identification
  • Gita Venkataramani Johar and Michel Tuan Pham (bio)

Proper identification of event sponsors is a key concern in sponsorship communication. Although practitioners have assumed that event sponsors are identified primarily through pure recollection, a study shows that sponsor identification involves a substantial degree of construction. Results from 3 experiments indicate that sponsor identification is biased toward brands that are prominent in the marketplace and semantically related to the event. These biases appears to emanate from constructive processes whereby, during identification, respondents use the prominence and relatedness of available brands as heuristics to verify their recollection of event-sponsor associations, The effects of relatedness on sponsor identification seem stronger and more robust than those of prominence, which appears to be invoked only for large events.

A recent survey about the 1998 Winter Olympics sponsors yielded alarming results (The Wall Street Journal 1998). Eleven of the 20 brands most often identified as worldwide sponsors of the event were not in fact sponsors. For example, whereas 50% of the respondents correctly identified United Parcel Service (UPS) as an Olympic sponsor, 40% mistakenly credited Federal Express. These results are far from unusual (e.g., Crimmins and Hom 1996). Event sponsors have expressed concern about public confusion regarding event sponsorship. This concern is evident in the increasing number of commercial studies that track sponsor identification (e.g., Millman 1995), published recommendations on how to increase the chances of proper identification (e.g., Meenaghan 1994), and advertisements warning consumers against “ambush marketing” tactics by which consumers are led to believe incorrectly that some brands are actual sponsors. Proper identification usually is perceived as a necessary condition for achieving the image objectives that most sponsors assign to sponsorship activities (e.g., Stipp and Schiavone 1996).

The processes underlying sponsor identification, surprisingly, are poorly understood. It is assumed widely by practitioners that sponsors are identified through pure recollection, that is, access to a memory record of the event-sponsor association (e.g., Crimmins and Horn 1996). However, extant theorizing on constructive memory processes suggests that there may be more to sponsor identification than sheer retrieval of the original event-sponsor association (e.g., Loftus, Feldman, and Dashiell 1995; Schacter, Norman, and Koustaal 1998). As with other types of marketing communications (Pham and Johar 1997), sponsor identification may involve a substantial degree of construction. In this article, we examine, across three experiments, how two major heuristics - brand-event relatedness and market prominence - operate in constructive sponsor identification.


Retrieval, Relatedness, and Prominence

On the surface, sponsor identification resembles cued retrieval. For example, respondents may be asked, “Which delivery company sponsored the 1998 Winter Olympics in Nagano?” to which they are expected to answer “UPS.” Whether the actual sponsor of an event will be identified correctly depends on the respondents’ ability to retrieve the original event-sponsor association, which is dictated largely by how well the association was encoded. What is perhaps less obvious is that the sponsor’s identification or misidentification also depends on constructive processes the respondents might invoke in attempting to infer the sponsor of an event. We suggest that these constructive processes are likely to include two major heuristics: brand-event relatedness and market prominence.

Consumers who are asked to identify the sponsor of an event may assess the likely association between the event and alternative sponsors. Various streams of research indicate that such associative judgments tend to be based on a heuristic of relatedness. Categorization research suggests that instances are assigned to categories on the basis of the overlap between the attributes of the instance and those of the category (e.g., Rosch and Mervis 1975). Research on the representativeness heuristic (e.g., Kahneman and Tversky 1973) indicates that judgments about the probability that an object (e.g., a movie) belongs to a certain population (e.g., movies that a person likes) often are based on the similarity between the attributes of the object (e.g., features of a given actor) and salient characteristics or exemplars (well-liked movies previously viewed) of the population (e.g., Glass and Waterman 1988). Likewise, research on clinical decision making suggests that diagnoses may be misled by the semantic...

Additional Information

Launched on MUSE
Open Access
Back To Top

This website uses cookies to ensure you get the best experience on our website. Without cookies your experience may not be seamless.