Finding the Right Fit: A Comparison of Process Assumptions Underlying Popular Drift-Diffusion Models

Recent research makes increasing use of eye-tracking methodologies to generate and test process models. Overall, such research suggests that attention, generally indexed by fixations (gaze duration), plays a critical role in the construction of preference, although the methods employed to support this supposition differ substantially. In two studies we empirically test prototypical versions of prominent processing assumptions against one another and several base models. We find that general evidence accumulation processes provide a good fit to the data. An accumulation process that assumes leakage and temporal variability in evidence weighting (i.e. a primacy effect) fits the aggregate data, both in terms of choices and decision times, and does so across varying types of choices (e.g., charitable giving and hedonic consumption) and numbers of options well. However, when comparing models on the level of the individual, for a majority of participants simpler models capture choice data better. The theoretical and practical implications of these findings are discussed

Understanding the Effect of Information Presentation Order and Orientation on Information Search and Treatment Evaluation

Background. Past research finds that treatment evaluations are more negative when risks are presented after benefits. This study investigates this order effect: manipulating tabular orientation and order of risk–benefit information, and examining information search order and gaze duration via eye-tracking. Design. 108 (Study 1) and 44 (Study 2) participants viewed information about treatment risks and benefits, in either a horizontal (left-right) or vertical (above-below) orientation, with the benefits or risks presented first (left side or at top). For 4 scenarios, participants answered 6 treatment evaluation questions (1–7 scales) that were combined into overall evaluation scores. In addition, Study 2 collected eye-tracking data during the benefit–risk presentation. Results. Participants tended to read one set of information (i.e., all risks or all benefits) before transitioning to the other. Analysis of order of fixations showed this tendency was stronger in the vertical (standardized mean rank difference further from 0, M = ±.88) than horizontal orientation (M = ± 0.71). Approximately 50% of the time was spent reading benefits when benefits were shown first, but this was reduced to ~40% when risks were presented first (regression coefficient: B = −4.52, p <.001). Eye-tracking measures did not strongly predict treatment evaluations, although time percentage reading benefits positively predicted evaluation when holding other variables constant (B = 0.02, p =.023). Conclusion. These results highlight the impact of seemingly arbitrary design choices on inspection order. For instance, presenting risks where they will be seen first leads to relatively less time spent considering treatment benefits. Other research suggests these changes to inspection order can influence multi-option and multi-attribute choices, and represent an area for future research

Choice in experiential learning: True preferences or experimental artifacts?

The rate of selecting different options in the decisions-from-feedback paradigm is commonly used to measure preferences resulting from experiential learning. While convergence to a single option increases with experience, some variance in choice remains even when options are static and offer fixed rewards. Employing a decisions-from-feedback paradigm followed by a policy-setting task, we examined whether the observed variance in choice is driven by factors related to the paradigm itself: Continued exploration (e.g., believing options are non-stationary) or exploitation of perceived outcome patterns (i.e., a belief that sequential choices are not independent). Across two studies, participants showed variance in their choices, which was related (i.e., proportional) to the policies they set. In addition, in Study 2, participants' reported under-confidence was associated with the amount of choice variance in later choices and policies. These results suggest that variance in choice is better explained by participants lacking confidence in knowing which option is better, rather than methodological artifacts (i.e., exploration or failures to recognize outcome independence). As such, the current studies provide evidence for the decisions-from-feedback paradigm's validity as a behavioral research method for assessing learned preferences

Desired and Undesired Effects of Energy Labels—An Eye-Tracking Study

<div><p>Saving energy is an important pillar for the mitigation of climate change. Electric devices (e.g., freezer and television) are an important player in the residential sector in the final demand for energy. Consumers’ purchase decisions are therefore crucial to successfully reach the energy-efficiency goals. Putting energy labels on products is often considered an adequate way of empowering consumers to make informed purchase decisions. Consequently, this approach should contribute to reducing overall energy consumption. The effectiveness of its measurement depends on consumers’ use and interpretation of the information provided. Despite advances in energy efficiency and a mandatory labeling policy, final energy consumption per capita is in many countries still increasing. This paper provides a systematic analysis of consumers’ reactions to one of the most widely used eco-labels, the European Union (EU) energy label, by using eye-tracking methodology as an objective measurement. The study’s results partially support the EU’s mandatory policy, showing that the energy label triggers attention toward energy information in general. However, the energy label’s effect on consumers’ actual product choices seems to be rather low. The study’s results show that the currently used presentation format on the label is insufficient. The findings suggest that it does not facilitate the integration of energy-related information. Furthermore, the current format can attract consumers to focus more on energy-efficiency information, leading them to disregard information about actual energy consumption. As a result, the final energy consumption may increase because excellent ratings on energy efficiency (e.g., A⁺⁺) do not automatically imply little consumption. Finally, implications for policymakers and suggestions for further research are discussed.</p></div