Editing Behavioral economics (section)

=== Other areas of research ===
Other branches of behavioral economics enrich the model of the utility function without implying inconsistency in preferences. [[Ernst Fehr]], [[Armin Falk]], and Rabin studied [[distributive justice|fairness]], [[inequity aversion]] and [[reciprocal altruism]], weakening the neoclassical assumption of perfect [[selfishness]]. This work is particularly applicable to wage setting. The work on "intrinsic motivation by [[Uri Gneezy]] and [[Aldo Rustichini]] and "identity" by [[George Akerlof]] and [[Rachel Kranton]] assumes that agents derive utility from adopting personal and social norms in addition to conditional expected utility. According to Aggarwal, in addition to behavioral deviations from rational equilibrium, markets are also likely to suffer from lagged responses, search costs, externalities of the commons, and other frictions making it difficult to disentangle behavioral effects in market behavior.<ref>{{cite journal|last1=Aggarwal|first1=Raj|year=2014|title=Animal Spirits in Financial Economics: A Review of Deviations from Economic Rationality|journal=International Review of Financial Analysis|volume=32|issue=1|pages=179–87|doi=10.1016/j.irfa.2013.07.018}}</ref>

"Conditional expected utility" is a form of reasoning where the individual has an [[illusion of control]], and calculates the probabilities of external events and hence their utility as a function of their own action, even when they have no causal ability to affect those external events.<ref>{{cite journal|author=Grafstein R|year=1995|title=Rationality as Conditional Expected Utility Maximization|journal=Political Psychology|volume=16|issue=1|pages=63–80|doi=10.2307/3791450|jstor=3791450}}</ref><ref>{{cite journal|author=Shafir E, Tversky A|year=1992|title=Thinking through uncertainty: nonconsequential reasoning and choice|journal=Cognitive Psychology|volume=24|issue=4|pages=449–74|doi=10.1016/0010-0285(92)90015-T|pmid=1473331|s2cid=29570235}}</ref>

Behavioral economics caught on among the general public with the success of books such as [[Dan Ariely]]'s ''[[Predictably Irrational]].'' Practitioners of the discipline have studied quasi-public policy topics such as [[Broadband mapping in the United States|broadband mapping]].<ref name="twsA2faa4">{{cite web|date=March 17, 2010|title=US National Broadband Plan: good in theory|url=http://www.telco2.net/blog/2010/03/us_national_broadband_plan_qui.html|archive-url=https://web.archive.org/web/20100420151540/http://www.telco2.net/blog/2010/03/us_national_broadband_plan_qui.html|url-status=usurped|archive-date=April 20, 2010|access-date=2010-09-23|publisher=Telco 2.0|quote=... Sara Wedeman's awful experience with this is instructive....}}</ref><ref name="twsA2xx">{{cite news|last1=Cook|first1=Gordon|last2=Wedeman|first2=Sara|date=July 1, 2009|title=Connectivity, the Five Freedoms, and Prosperity|publisher=Community Broadband Networks|url=http://www.muninetworks.org/reports/cook-report-broadband-mapping-connectivity-five-freedoms-and-prosperity|access-date=2010-09-23}}</ref>

Applications for behavioral economics include the modeling of the consumer decision-making process for applications in [[artificial intelligence]] and [[machine learning]]. The Silicon Valley–based start-up Singularities is using the [[AGM postulates]] proposed by Alchourrón, Gärdenfors, and Makinson—the formalization of the concepts of beliefs and change for rational entities—in a [[symbolic logic]] to create a "machine learning and deduction engine that uses the latest [[data science]] and [[big data]] algorithms in order to generate the content and conditional rules (counterfactuals) that capture customer's behaviors and beliefs."<ref>{{cite web|year=2017|title=Singularities Our Company|url=https://www.singularities.com/our-company|url-status=dead|archive-url=https://web.archive.org/web/20171112074640/https://www.singularities.com/our-company|archive-date=2017-11-12|access-date=2017-07-12|publisher=Singular Me, LLC|quote=... machine learning and deduction engine that uses the latest data science and big data algorithms in order to generate the content and conditional rules (counterfactuals) that capture customer's behaviors and beliefs....}}</ref>

The [[University of Pennsylvania]]'s Center for Health Incentives & Behavioral Economics (CHIBE) looks at how behavioral economics can improve health outcomes. CHIBE researchers have found evidence that many behavioral economics principles (incentives, patient and clinician nudges, gamification, loss aversion, and more) can be helpful to encourage vaccine uptake, smoking cessation, medication adherence, and physical activity, for example.<ref>{{Cite web|title=Impact|url=https://chibe.upenn.edu/about/impact/|access-date=2020-11-23|website=Center for Health Initiatives and Behavioral Economics|language=en-US}}</ref>

Applications of behavioral economics also exist in other disciplines, for example in the area of supply chain management.<ref>{{cite journal|last1=Schorsch|first1=Timm|last2=Marcus Wallenburg|first2=Carl|last3=Wieland|first3=Andreas|year=2017|title=The human factor in SCM: Introducing a meta-theory of behavioral supply chain management|url=https://research-api.cbs.dk/ws/files/46469212/andreas_wieland_the_human_factor_in_scm_postprint.pdf|journal=International Journal of Physical Distribution & Logistics Management|volume=47|pages=238–262|doi=10.1108/IJPDLM-10-2015-0268|hdl=10398/d02a90cf-5378-436e-94f3-7aa7bee3380e|s2cid=54685109 |hdl-access=free}}</ref>