Marketing is about numbers but not necessarily just a number. From a big crowd to a half empty arena, adjectives carry numerical associations. The research within this dissertation builds on that idea while focusing on markedness, a linguistics theory, which has been called the evaluative superstructure of language. For example, asking "How tall is the person?" is not an indication that the person is tall but merely a neutral way to ask about a person's height. Tall, in this case, is considered an unmarked term given its neutral meaning. Asking "How short is the person?" however, implies the person is actually short in addition to asking for their height. Linguistics literature has touched on the power of language in numerical estimations but has not fully explored it, nor has linguistics literature transitioned to the marketing literature.
Study 1 begins to explore markedness in a consumer setting by using Google Trends to show that unmarked terms, such as tall, are searched more frequently than marked terms, such as short. Study 2 shows that using an unmarked term results in significantly higher estimates of crowd size than using a marked term but is not significantly different than using a neutral term. Study 3 incorporates numerical anchors, which reduce the markedness effects. Study 4 illustrates how an unmarked term results in a wider range of crowd size estimates than a marked term. Study 5 shows how markedness effects are largely eliminated based on the source of the message (team) and capacity constraint of the arena. Study 6 incorporates time to show that markedness effects are stronger in a judgment framed as per day than per year. Studies 7, 8 and 10 show how a marked term, such as half empty, results in significantly different numerical estimates over time. This effect is eliminated when reference to a point in time, such as "at halftime", is removed (study 9). These findings highlight the role of markedness in consumer judgment and have important implications for a variety of marketing theories.
| Identifer | oai:union.ndltd.org:uoregon.edu/oai:scholarsbank.uoregon.edu:1794/18352 |
| Date | 29 September 2014 |
| Creators | Lee, Christopher |
| Contributors | Kahle, Lynn |
| Publisher | University of Oregon |
| Source Sets | University of Oregon |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Rights | All Rights Reserved. |
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