Marketing researchers design exploratory, descriptive, and causal
research projects. Exploratory research, as the name implies, explores
the marketing problem further through primarily informal, qualitative
(rather than quantitative) means, such as personal interviews, observation,
or focus groups. For example, the Memphis Grizzlies selected a
panel of fans to visit other NBA arenas (via observation) to provide
input (via interviews and focus groups) as to what they would like to
see in the Grizzlies’ new arena prior to its construction.
Descriptive research, surprisingly, is most often used to describe a
particular state of affairs in quantitative terms. Every sporting event
or organization conducts (or purchases) research that describes their
typical customer in demographic terms. Other descriptive research
might include describing the average fan’s opinion about service quality
or some other facet of the sporting event.
Causal research seeks to understand factors (cognitive, affective, or
behavioral) that cause, explain, or predict other perceptions, feelings,
or behaviors. In a strict sense, researchers design experiments to
isolate causal factors. For instance, the NBA might want to determine
if using Rovion’s Bluestream technology (see
Showcase/DRJ_demo.htm) is more effective in driving business to
team Web sites for ticket purchases than traditional Web site video
technology. Subjects could be exposed to both Web sites (identical Web
sites, except one employs the Bluestream technology and one does not)
and differences measured. Interestingly, we conducted this experiment
and found that the Rovion technology does make a signifi cant difference
in fans’ feelings about the Web site experience and subsequent
intentions to purchase from the Web site—as long as the subject liked
the celebrity used in the “video-over” technology. The presence of the
celebrity adds a social cue (similar to attractive sales people in a bricksand-mortar
store) that enhances the online shopping experience.
On a practical basis, researchers build predictive models to help
understand factors that theoreti
cally and pragmatically infl uence variables
of concern. Sports marketers are often interested in determining
what factors related to fans and the event lead to attendance. Our
model of identifi cation presented in Chapter 2 is an example of a
causal model. In general, the form of a causal model is patterned after
attitudinal structure:
Perceptions → Affect → Behavior
Think → Feel → Do
What an individual thinks about the Dallas Cowboys (winners or
losers) infl uences what he or she feels (excited or bored), which, in turn,
infl uences what he or she does (attends or avoids Cowboys’ games).
Researchers are sometimes interested in just one or two aspects of
attitude. For example, you might be interested in fi nding out how
individual perceptions of event quality (food and beverage quality,
employee service quality, facility quality) infl uence fans’ overall perceptions
of event quality. Alternately, you might be interested in fi nding
out how fans’ feelings regarding one aspect of the event (e.g., satisfaction
with team performance) infl uence their behaviors (e.g., attendance).
The methods described in this chapter are geared particularly
toward descriptive and causal research projects.