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Hybrid Rough/Fuzzy Modeling of Advertising Effects on Consumer Preferences
Abstract
Advances in computational methods have led, in the marketing domain, to huge databases of consumer and marketing information. In the past decade, various machine intelligence techniques have been applied in mining this data for obtaining knowledge and in-depth information about the consumers and the markets. This paper presents a hybrid rough/fuzzy model to discover knowledge on advertising effectiveness from time series databases on consumer preferences and advertising expenditures. The data set used for application example contains weekly investments in different media categories: TV, radio, cinema, morning press, evening press, popular press, special interest press, and outdoor posters; for seven makes of cars on Swedish market, and consumer awareness and preference indices.
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