Researchers and practitioners devote substantial effort to targeting banner advertisements to consumers, but focus less effort on how to communicate with consumers once targeted. Morphing enables a website to learn, automatically and near optimally, which banner advertisements to serve to consumers in order to maximize click-through rates, brand consideration, and purchase likelihood. Banners are matched to consumers based on posterior probabilities of latent segment membership, which are identified from consumers' clickstreams. This paper describes the first large-sample random-assignment field test of banner morphing-over 100,000 consumers viewing over 450,000 banners on CNET.com. On relevant webpages, CNET's click-through rates almost doubled relative to control banners. We supplement the CNET field test with an experiment on an automotive information-andrecommendation website. The automotive experiment replaces automated learning with a longitudinal design that implements morph-to-segment matching. Banners matched to cognitive styles, as well as the stage of the consumer's buying process and body-type preference, significantly increase click-through rates, brand consideration, and purchase likelihood relative to a control. The CNET field test and automotive experiment demonstrate that matching banners to cognitive-style segments is feasible and provides significant benefits above and beyond traditional targeting. Improved banner effectiveness has strategic implications for allocations of budgets among media.

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When researchers ask customers to judge product form during the design process, they often manipulate simplified product representations, such as silhouettes and sketches, to gather information on which designs customers prefer. Using simplified forms, as opposed to detailed realistic models, make the analysis of gathered information tractable and also allows the researcher to guide customer focus. The theory of constructed preferences from psychology suggests that the product form presented will influence customer judgments. This paper presents a study in which subjects were shown computer sketches, front/side view silhouettes, simplified renderings, and realistic renderings to test the extent to which a variety of judgments including opinions, objective evaluations, and inferences are affected by form presentation. Results show a variety of phenomena including preference inconsistencies and ordering effects that differed across type of judgment. For example, while inferences were consistent across form, opinions were not. An eye tracker identified differences in viewing strategies while making decisions. Associated data, such as fixation times and fixation counts, provide additional insight into findings.

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Current wind farm layout optimization research assumes a continuous piece of land is readily available and focuses on advancing optimization methods. In reality, projects rely on landowners’ permission for success. When a viable site is identified, local residents are approached for permission to build turbines on their land, typically in exchange for monetary compensation. Landowners play a crucial role in the development process, and some land parcels are more important to the success of project than others. This paper relaxes the assumption that a continuous piece of land is available, developing a novel approach that includes a model of landowner participation rates. A genetic algorithm (GA) is adopted to solve the nonlinear constrained optimization problem, minimizing cost and maximizing power output. The optimization results show that, given a projected participation rate, we can identify the most crucial plots prior to the negotiation process with landowners. This will ultimately increase the efficiency of wind farm development.