Nudge: An example of the psychological limits of influence (Magda Osman)
The behavioural insights initiative (better known as Nudge) is billed as a way to help the public and private sector support better decision-making in its citizens/clients. The basic idea behind nudge is that people can be guided towards making "better" decisions by cleverly shaping the choice environment (i.e. the way options are presented) in such a way as to make salient a choice that people would have difficulty making, and for which the outcome would be better for them in the long run. The work presented in this talk covers some of the controversies associated with Nudge by looking at issues that concern the public as well as the academic world, none of which have gained significant traction in the world of policy.
Connecting commitment to self-control problems: evidence from a weight loss challenge (Séverine Toussaert)
In the context of a weight loss challenge, I use the menu choice approach of Gul and Pesendorfer (2001) to provide new insights on the link between commitment demand and self-control problems. First, I study commitment demand to eat healthy by eliciting participants’ preferences over a set of lunch reimbursement options, which differed in their food coverage. Using information on the entire ordering, I develop menu preference measures of temptation and validate them with survey data. Finally, I investigate whether temptation revealed through menu choice can predict self-control problems in an other domain: commitment to self-set goals pertaining to exercise and participation in the challenge. I find strong evidence of a demand for commitment driven by temptation. First, close to 50% of participants strictly preferred a coverage that excludes the foods they rated as most tempting and unhealthy. Second, temptation revealed through menu choice not only predicts a higher likelihood of commitment to self-set goals but also a lower likelihood of achieving them. The elicitation of menu preferences therefore offers a promising venue for measuring self-control problems.
A meta-analytical perspective on scientific reproducibility (Anne Scheel)
A recent collaborative project led by Daniël Lakens attempted to reproduce 20 meta-analyses published in three psychological review journals in 2013 and 2014. In many cases, data and methods were not reported transparently enough to identify which results from original studies had been included a given meta-analysis. As a consequence, most attempts failed even before the recalculated outcomes could be compared to the outcomes reported in the meta-analyses. These findings highlight the importance of reporting guidelines and the problems that arise when they are ignored: If meta-analytical results cannot be traced and checked appropriately, and are not readily accessible for re-use or further investigations, the accumulation of knowledge will suffer. To increase the reproducibility of meta-analyses, they should be subject to the same (or similar) practices that have been suggested to increase the reproducibility of original work, for example open data and preregistration of the sampling and analysis plan.
In the second part of my talk I will turn to discuss Registered Reports, a new publication format which incorporates many of these practices and which is designed to prevent publication bias. As Registered Reports become more popular, a new scientific literature with drastically reduced levels of bias is emerging. This new literature will allow us to obtain a picture of scientific results that reflect the studied phenomena much more accurately than previous studies. I will present an ongoing project which examines the outcomes of Registered Reports that have been published so far, and discuss implications and further directions.
Preferential Choices based on Similarity Comparisons (Jana Jarecki)
This paper proposes that humans form preferences based on similarity comparisons. Similarity comparisons constitutes an alternative to most standard theories of preference formation which assume that preferences result from a linear integration of subjective attribute values and attribute weights. We investigate if preferences result from the similarity between an option and previously experienced and evaluated options, resembling ideas of exemplar-based inferential judgment and categorization processes. Using cognitive modeling and computer simulations we contrast the standard linear-weighting and the similarity-based view on preferences. In two choice experiments (N=33 and N=29) with consumer goods (writing pens and food), we find that the out-of-sample predictions made by the individually-fitted exemplar-similarity-based preference model outperformed a linear-weighting model. Moreover, the similarity-based model describes behavior better in a task with direct experience (food choices) compared to a task without experience (pen choices). These results show how individuals’ past experiences in a preferential domain can strongly impact preferential decisions in the future.