关键词：
brand advertising
visual attention
brand memory
hierarchical Bayes
摘要：
The number of brands in the marketplace has vastly increased in the 1980s and 1990s, and the amount of money spent on advertising has run parallel. Print advertising is a major communication instrument for advertisers, but print media have become cluttered with advertisements for brands. Therefore, it has become difficult to attract and keep consumers' attention. Advertisements that fail to gain and retain consumers' attention cannot be effective, but attention is not sufficient: Advertising needs to leave durable traces of brands in memory. Eye movements are eminent indicators of visual attention. However, what is currently missing in eye movement research is a serious account of the processing that takes place to store information in long-term memory. We attempt to provide such an account through the development of a formal model. We model the process by which eye fixations on print advertisements lead to memory for the advertised brands, using a hierarchical Bayesian model, but, rather than postulating such a model as a mere data-analysis tool, we derive it from substantive theory on attention and memory. The model is calibrated to eye-movement data that are collected during exposure of subjects to ads in magazines, and subsequent recognition of the brand in a perceptual memory task. During exposure to the ads we record the frequencies of fixations on three ad elements;brand, pictorial and text and, during the memory task, the accuracy and latency of memory. Thus, the available data for each subject consist of the frequency of fixations on the ad elements and the accuracy and the latency of memory. The model that we develop is grounded in attention and memory theory and describes information extraction and accumulation during ad exposure and their effect on the accuracy and latency of brand memory. In formulating it, we assume that subjects have different eye-fixation rates for the different ad elements, because of which a negative binomial model of fixation freq
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