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Purpose The purpose of this paper was to investigate how attention to wine labels related to preference by using quantitative measures of gaze and of the diameter of the eye pupil. We assessed whether eye fixations could predict choices and willingness to pay and whether pupil size could index the aesthetic value of wine labels. More specific goals were to identify which elements of a wine label captured attention the most and to assess whether an authentic label would be preferred by naïve consumers over other alternative labels, also designed by the same studio but excluded from the market. Design/methodology/approach Infrared eye-tracking was used to measure the amount of time spent on a specific label among four that were simultaneously shown on the computer screen. Participants also made explicit decisions about preferred labels and provided price estimates. Pupillometry was used for labels shown in isolation to obtain a physiological index of their arousing effect and aesthetic appeal. Eye fixations provided an index of what was selected by attention, whereas changes in the pupillary diameter indexed how intensively attention was focused on an item. Findings A strong positive relationship was found between the dwelling of gaze over a specific label and the degree in which a wine bottle was preferred and (virtually) chosen. The pictorial elements of the labels were fixated the most, whereas verbal information was looked at the least. Attractiveness scores of each bottle collected with one independent group of observers were able to predict the willingness to pay in another group. Moreover, pupil size changed non-linearly in relation to the hedonic values of the wine labels, indicating greater responses to the most as well as least attractive labels (i.e. for the most arousing labels). Research limitations/implications A limitation of the present experiments was that only choices and behavior of wine “novices” were probed; hence, the present findings might not be generalized to other segments (e.g. wine connoisseurs). Moreover, the present study could not specify which visual properties of a label affect preference, aesthetic value and estimates of price, as the study of these effects would require a large number and variety of label stimuli. Practical implications Eye monitoring methods could assist marketing studies of preferences and decision-making. Both wine label designers and wine producers could benefit from eye-tracking methods to improve label selection and optimize the design process of a wine label. Originality/value Although both eye-tracking and pupillometry have been used to the investigate aesthetic preferences for at least the past 50 years, the measurement of pupil diameter and eye movements to study attributes of (authentic) wine labels and their effectiveness is entirely novel. The present study confirms that measures based on eye-tracking combined to explicit choices or ratings provide complementary types of market-relevant information. Both methods provide objective, quantitative, information of the effect of the labels on consumers that is independent but predictive of actual choices and verbally reported preferences. Moreover, they appear to index different processes, pupillometry being a proxy of aesthetic value and gaze a reliable index of choice. Thus, the present findings can be of value to the academic researcher as well as industry and design practitioners.

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During the execution of a cognitive task, the brain maintains contextual information to guide behavior and achieve desired goals. The AX-Continuous Performance Task is used to study proactive versus reactive cognitive control. Young adults tend to behave proactively in standard testing conditions. However, it remains unclear how interindividual variability (e.g., in cognitive and motivational factors) may drive people into more reactive or proactive control under the same task demands. We investigated the use of control strategies in a large population of healthy young adults. We computed the proactive behavioral index and consequently divided participants into proactive, reactive, and intermediate groups. We found that reactive participants were generally slower, presented lower context sensitivity, and larger response variability. Pupillary changes and blink rate index cognitive effort allocation. We measured, concomitantly to the task, the pupil size and frequency of blinks associated with the cue maintenance and response intervals. During the cue period, nonfrequent, nontarget cues led to increased pupil dilation and number of blinks in all participants. During the response interval, we found more errors and increased pupil dilation to the probe when all participants had to overcome a response bias generated by the frequent cue. Only reactive participants showed larger response-related pupil when they had to overcome a response bias related to the frequent probe. Contrary to expectations, groups did not differ in ocular measures in the cue period. In conclusion, interindividual differences in cognitive control between healthy adults can be mapped onto different patterns of effort allocation indexed by the pupil.