Knowledge that Transforms

Three studies examine the influence of brand-elicited affect on consumers' evaluations of brand extensions. When a brand spontaneously elicits affective reactions, consumers appear to form an initial impression of the brand's new extension based on these reactions. The affect that they experience for other reasons and attribute to the brand can influence this impression as well. Their later evaluations of the extension are then based on this impression. This is true regardless of the similarity between the extension and the core brand. These results contrast with evidence that affect influences brand extension evaluations through its mediating impact on perceptions of core-extension similarity. This latter influence occurs only when consumers are explicitly asked to estimate the extension's similarity to the core before they evaluate it.

The authors propose a new approach to obtaining stockkeeping-unit (SKU)-level preferences and response sensitivities. The authors distinguish an attribute-level model, in which the unit of analysis is the market share for an alternative created by aggregation (e.g., Colgate toothpaste), from a truly disaggregate SKU-level model, and they establish an analytical relationship between parameters that they obtain from the two models. The authors show that SKU-level parameters can be recovered by calculation from estimated attribute-level parameters, circumventing the need for direct estimation of the more complex SKU-level model. They calibrate the store data market share model using 98 weeks of data for ten brands and 168 SKUs of toothpaste. Rather than estimate 168 preference parameters (when there is an “outside” alternative in addition to the 168 “inside” ones), it is only necessary to estimate ten brand-preference parameters from which the 168 parameters can be computed, as long as share and marketing-mix data are available at the SKU level. Covariate effects, such as marketing-mix response parameters, can be recovered in a similar fashion. Holdout tests demonstrate superior predictive performance, and the authors discuss implications for the derivation of elasticities for new SKU introductions.

In electronic shopping, screening tools are used to sort through many options, assess their fit with a consumer's utility function, and recommend options in a list ordered from predicted best to worst. When the most promising options are at the beginning of the list, even seemingly advantageous factors (e.g., lower search cost, greater selection) that prompt consideration of more options degrade choice quality by (1) lowering the average quality of considered options and (2) lowering customers' selectivity in focusing attention on the more mediocre rather than the better options from the actively considered set. Study 1 shows that lowering search costs diminishes choice quality in an ordered environment. Study 2 shows that presenting consumers with the top 50 rather than the top 15 recommendations has the same effect. Study 3 shows that greater accuracy motivation in combination with lower search cost diminishes choice quality because consumers are encouraged to consider a wider range of options (lower-quality consideration sets), which ultimately leads to worse choices.

The Lucas critique has been largely ignored in the marketing literature. We present a number of conditions under which the critique is most likely to (also) apply in marketing settings. Next, we provide some perspectives on how to diagnose and accommodate the Lucas critique, and identify various avenues for future research.