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In this paper, we develop a structural model of household behavior in an environment where there is uncertainty about brand attributes and both prices and advertising signal brand quality. Four quality signaling mechanisms are at work: (1) price signals quality, (2) advertising frequency signals...
Persistent link: https://www.econbiz.de/10008787869
We construct two models of the behavior of consumers in an environment where there is uncertainty about brand attributes. In our models, both usage experience and advertising exposure give consumers noisy signals about brand attributes. Consumers use these signals to update their expectations of...
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To measure the extent of incomplete information about brand qualities faced by consumers, recent research in marketing and economics has extended traditional static choice models to explicitly allow for consumer learning. These models tend to be complicated and make stringent assumptions such as...
Persistent link: https://www.econbiz.de/10014044657
Learning models extend the traditional discrete choice framework by postulating that consumers have incomplete information about product attributes and that they learn about these attributes over time. In this survey we describe the literature on learning models that has developed over the past...
Persistent link: https://www.econbiz.de/10013072631
Learning models extend the traditional discrete choice framework by postulating that consumers have incomplete information about product attributes, and that they learn about these attributes over time. In this survey we describe the literature on learning models that has developed over the past...
Persistent link: https://www.econbiz.de/10013092559
Learning models extend the traditional discrete choice framework by postulating that consumers have incomplete information about product attributes, and that they learn about these attributes over time. In this survey we describe the literature on learning models that has developed over the past...
Persistent link: https://www.econbiz.de/10013404063