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This research investigated how a consumer's cognitive structure for a brand in a given product category affects the possible transfer of associations to other product categories. One key factor in evaluating such possible brand extensions is dominance, which can be defined as the strength of the directional association between the parent category and the branded product. Likewise, another important factor is the relatedness of the brand's parent category and the target category of the proposed extension. The 1st experiment measured dominance and relatedness via response latencies to recognize brand extensions. The 2nd experiment demonstrated that consumers’ affect for strongly category‐dominant brands (a) transfers better to an extension when the proposed extension is closely rather than distantly related to the parent category and (b) transfers better than a weakly category‐dominant brand's affect. Together, the research demonstrated that consumers’ response times to disconfirm the existence of product‐brand pairs is related to their transfer of affect from the brand to the proposed product category. This disconfirmation method could be used as an unobtrusive measure for determining brand boundaries. The attractiveness of potential brand extensions may thus be determined without consumers making any judgments about a proposed extension other than answering whether or not it exists.

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There are numerous situations in management and elsewhere in which an individual decision maker chooses subsets of multiattributed items. The specification of a measure of goodness for selecting subsets may differ from one situation to the next. In this paper, a model is developed for evaluating subsets where the choice criterion is one of balance among the attributes of items in the subset chosen. A method for determining the parameters of the model from a small number of judgments on subsets using linear programming is discussed. The model is applied to the problem of evaluating subsets of television shows and of choosing the most balanced subset of shows. Several extensions of the model and potential applications are also given.

A phantom alternative is an illusory choice option---it looks real but for some reason is unavailable at the time a decision is made. Phantoms can both help and hinder successful decision making. On the one hand, phantoms can provide useful information on the boundaries of a decision problem and thus help generate new options through a restructuring of the problem. But phantoms can also produce biases, deception, and suboptimal decisions. We argue that phantoms should be considered explicitly in decision structuring rather than being allowed to work their effects surreptitiously. We offer guidelines on recognizing unavailable alternatives, utilizing the information provided by phantoms, counteracting phantom biases, avoiding deception in decision structuring, and guarding against suboptimal decisions.decision analysis, problem structuring, unavailability