Measuring multiple automatic product appraisals simultaneously: introduction and examination of the implicit attribute classification task

Past research has demonstrated that both carefully formed, contemplated attitudes, but also spontaneously elicited, automatic evaluations play a crucial role in motivating behaviour. However, the accurate measurement of automatic appraisals can be challenging because existing measures can assess automatic appraisals on single attribute dimensions only (e.g. "pleasant"/"unpleasant"). This limitation is particularly critical in consumer decision making because (a) products are never unidimensional, and (b) past research has demonstrated that the complex weighting of various product dimensions (e.g. price, taste, healthiness) often plays a crucial role in consumer decision making. Here, we present the Implicit Attribute Classification Task ("IMPACT"), a new measure of automatic product appraisals that, crucially, was designed specifically to reflect the multidimensionality of stimuli by assessing automatic appraisals of multiple facets simultaneously. Across six experiments, we systematically investigate the paradigm in a series of IMPACTS that examine different facets of automaticity. Our findings make a substantial contribution to research on implicit (consumer) cognition by introducing the IMPACT as a sophisticated new tool that, for the first time, facilitates the assessment of automatic appraisals of multiple facets at once.