Avishalom Tor’s research while affiliated with University of Notre Dame and other places

The study of competition from a social comparison perspective offers valuable insights into the neuroscience of social judgment and decision making under uncertainty. When engaging in social comparison, individuals seek and assess information about similarities or differences between others and themselves, in large part to improve their self-evaluation. By providing information about one’s relative position, abilities, outcomes, and more, social comparisons can inform competitive judgments and decisions. People reasonably turn to social comparisons to reduce uncertainty before, during, and after competition. However, the extent to which they do so and the behavioral consequences of social comparisons often fail to match the potential benefits of improved self-evaluation. An examination of the developing neuroscience of social comparison and competition in light of the behavioral evidence reveals numerous questions that merit further investigation.

Digital nudges—that is, significantly behavioral interventions that use software and its user-interface design elements—are an increasingly pervasive feature of online environments that shapes behavior both online (e.g., changing online privacy settings) and offline (e.g., taking a flu vaccine due to a text message reminder). Although digital nudges share many characteristics of their offline counterparts, they merit particular attention and analysis for two important reasons: First, the growing ubiquity of digital nudges makes encountering them nearly unavoidable in daily life, thereby bringing into sharper relief the promise and perils of nudges more generally. Second, the potentially greater potency of digital—compared to offline—nudges, the greater opacity of their instruments and behavioral mechanisms, and the typically dominant role of private intermediaries or independent private actors in their implementation all raise unique or qualitatively different challenges from those presented by their better-studied offline predecessors.KeywordsBehavioral regulationBehavioral insightsNudgeCosts and benefitsArtificial intelligenceMachine learningIntermediaries

This handbook is currently in development, with individual articles publishing online in advance of print publication. At this time, we cannot add information about unpublished articles in this handbook, however the table of contents will continue to grow as additional articles pass through the review process and are added to the site. Please note that the online publication date for this handbook is the date that the first article in the title was published online. For more information, please read the site FAQs.

This handbook is currently in development, with individual articles publishing online in advance of print publication. At this time, we cannot add information about unpublished articles in this handbook, however the table of contents will continue to grow as additional articles pass through the review process and are added to the site. Please note that the online publication date for this handbook is the date that the first article in the title was published online. For more information, please read the site FAQs.

Highly influential recent work by Benartzi et al. (2017) argues—using comparisons of effectiveness and costs—that behavioral interventions (or nudges) offer more cost-effective means than traditional regulatory instruments for changing individual behavior to achieve desirable policy goals. Based on this finding, these authors further conclude that governments and other organizations should increase their investments in nudging to supplement traditional interventions. Yet a closer look at Benartzi et al.’s (2017) own data and analysis reveals that they variously exclude and include key cost elements to the benefit of behavioral instruments over traditional ones and overstate the utility of cost-effectiveness analysis for policy selection. Once these methodological shortcomings are corrected, a reassessment of key policies evaluated by the authors reveals that nudges do not consistently outperform traditional interventions, neither under cost-effectiveness analysis nor under the methodologically required cost-benefit analysis. These illustrative findings demonstrate that governments concerned with social welfare cannot simply assume the superiority of behavioral instruments and should strive instead to conduct cost-benefit analyses of competing interventions, including nudges, to identify the most efficient of the available instruments.

This article examines the law and economics of behavioral regulation (“nudging”), which governments and organizations increasingly use to substitute for and complement traditional instruments. To advance its welfare-based assessment, Section 1 examines alternative nudging definitions and Section 2 considers competing nudges taxonomies. Section 3 describes the benefits of nudges and their regulatory appeal, while Section 4 considers their myriad costs—most notably the private costs they generate for their targets and other market participants. Section 5 then illustrates the assessment of public and private welfare nudges using cost-benefit analysis, cost-effectiveness analysis, and rationality-effects analysis.

This handbook is currently in development, with individual articles publishing online in advance of print publication. At this time, we cannot add information about unpublished articles in this handbook, however the table of contents will continue to grow as additional articles pass through the review process and are added to the site. Please note that the online publication date for this handbook is the date that the first article in the title was published online. For more information, please read the site FAQs.