Consumers often learn their preferences as they search. For example, after test driving new cars, a consumer might find she undervalued trunk space and overvalued sunroofs. Preference learning makes search complex because, each time a product is searched, updated preferences affect the value of...

Over 25 years ago Hoch (1988) found that every day consumers performed poorly at predicting the attitudes, interests, and opinions (AIO) of average Americans. We examined whether every day consumers’ predictive accuracy has changed in any substantive way since then, given the massive increase...

We propose a “visual listening in” approach (i.e., mining visual content posted by users) to measure how brands are portrayed on social media. Using a deep-learning framework, we develop BrandImageNet, a multi-label convolutional neural network model, to predict the presence of perceptual...

Despite the growth of online retail, the majority of products are still sold offline, and the “touch-and feel” aspect of physically examining a product before purchase remains important to many consumers. In this paper, we demonstrate that large discrepancies can exist between the way...