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How data science and behavioral economics can work together | Deloitte University Press

See on Scoop.itBounded Rationality and Beyond

What do predictive analytics and behavioral economics have in common? Quite a bit, as it turns out.

Two overdue sciences Near the end of Thinking, Fast and Slow, Daniel Kahneman wrote, “Whatever else it produces, an organization is a factory that produces judgments and decisions.”2 Judgments and decisions are at the core of two of the most significant intellectual trends of our time, and the one-word titles of their most successful popularizations have become their taglines. “Moneyball” is shorthand for applying data analytics to make more economically efficient decisions in business, health care, the public sector, and beyond. “Nudge” connotes the application of findings from psychology and behavioral economics to prompt people to make decisions that are consistent with their long-term goals. Other than the connection with decisions, the two domains might seem to have little in common. After all, analytics is typically discussed in terms of computer technology, machine learning algorithms, and (of course) big data. Behavioral nudges, on the other hand, concern human psychology. What do they have in common? When the ultimate goal is behavior change, predictive analytics and the science of behavioral nudges can serve as two parts of a greater, more effective whole.

Annunci
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Detection and Estimation of Working Memory States and Cognitive Functions Based on Neurophysiological Measures | Frontiers Research Topic

See on Scoop.itBounded Rationality and Beyond

Executive cognitive functions like working memory determine the success or failure of a wide variety of different cognitive tasks. Estimation of constructs like working memory load or memory capacity from neurophysiological or psychophysiological signals would enable adaptive systems to respond to cognitive states experienced by an operator and trigger responses designed to support task performance (e.g. by simplifying the exercises of a tutor system, or by shutting down distractions from the mobile phone). The determination of cognitive states like working memory load is also useful for automated testing/assessment, for usability evaluation and for tutoring applications. While there exists a huge body of research work on neural and physiological correlates of cognitive functions like working memory activity, fewer publications deal with the application of this research with respect to single-trial detection and real-time estimation of cognitive functions in complex, realistic scenarios. Single-trial classifiers based on brain activity measurements such as EEG, fNIRS or physiological signals such as EDA, ECG, BVP or Eyetracking have the potential to classify affective or cognitive states based upon short segments of data. For this purpose, signal processing and machine learning techniques need to be developed and transferred to real-world user interfaces.In this research topic, we are looking for: (1) studies in complex, realistic scenarios that specifically deal wit

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How pictures of kittens can help you manage money (a story by ING eZonomics)

See on Scoop.itBounded Rationality and Beyond

It might sound strange, but unusual cues that actually distract you can make top reminders for that to-do list. When trying to save more money or pay off a debt, a carefully thought-out plan can really improve personal finances. But it all takes time – and it can be so easy to forget the detail, or otherwise not follow through with a strategy. There’s no foolproof way to remember everything, even when it’s to do with money; memories fade and present bias keeps the focus on the here and now. However, research by Todd Rogers at Harvard and Katherine Milkman of the University of Pennsylvania reveals that certain types of reminder work better than others – sometimes improving the ability to remember tasks on schedule by as much as 32%. Matching the right cues Rogers and Milkman found that making up unrelated, striking cues and matching them up with tasks we need to be reminded about can help. In a first small experiment, the team aimed to get people to remember a promise to donate to charity.

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What is the Halloween indicator in financial markets?

See on Scoop.itBounded Rationality and Beyond

Think of Halloween and scares probably are front of mind. Trick or treat. Ghouls and carved pumpkins. In share markets, it appears investor behaviour can also be skewed by scares that accompany dark nights and downbeat emotions associated with the end of summer in the Northern Hemisphere. The phrases “sell in May” (ideally, when prices are high) and “buy on Halloween” (if prices are in a dip) are well known. This “Halloween indicator” will not work every year but research suggests there is some evidence to back it up, on average. It is one of a range of calendar effects that some believe exist in financial markets.

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Frames, Biases, and Rational Decision-Making in the Human Brain

See on Scoop.itBounded Rationality and Beyond

Human choices are remarkably susceptible to the manner in which options are presented. This so-called “framing effect” represents a striking violation of standard economic accounts of human rationality, although its underlying neurobiology is not understood. We found that the framing effect was specifically associated with amygdala activity, suggesting a key role for an emotional system in mediating decision biases. Moreover, across individuals, orbital and medial prefrontal cortex activity predicted a reduced susceptibility to the framing effect. This finding highlights the importance of incorporating emotional processes within models of human choice and suggests how the brain may modulate the effect of these biasing influences to approximate rationality.

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Decision Science News – Decision Science News is a website about Behavioral Economics, Data Science, Statistics, Marketing, Management, Psychology, Computer Science, Health, Policy, & Law

See on Scoop.itBounded Rationality and Beyond

If you read this website, you probably want to elicit probability distributions from people. A Distribution Builder (DB for short) does just that, and elicits them as cognitively-friendly frequency histograms. The Distribution Builder was created by Dan Goldstein, Bill Sharpe and Phil Blythe in the year 2000 and its first major publication was in 2008. The DB is a digital implementation of a method that was first used, as far as we can tell, by Kabus using poker chips in 1976, as cited in this paper by Goldstein and Rothschild (2014), which found that elicitation using a distribution builder beat conventional methods. Now for the news. Quentin André has built a JavaScript distribution builder that anyone can use and adapt. It creates ball-and-bucket style distribution builders, and has a nice Web site full of documentation.Decision Science News is a website about Behavioral Economics, Data Science, Statistics, Marketing, Management, Psychology, Computer Science, Health, Policy, & Law.

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Attenzione Selettiva: Quanti Scimpanzé non hai visto oggi? – TSW

See on Scoop.itBounded Rationality and Beyond

L’attenzione è quel processo mentale che permette di elaborare una parte limitata d’informazioni del nostro mondo, selezionandola dall’enorme quantità di stimoli che ci circondano. Le risorse cognitive di un individuo sono limitate e riuscire ad elaborare solo le informazioni rilevanti è un meccanismo che abbiamo ereditato dai nostri antenati. Evoluzionisticamente parlando, permette di aumentare le probabilità di sopravvivenza. Nel mondo animale, identificare un predatore (o una preda) in tempi ridotti consente la messa in atto del comportamento più efficiente (attacco o fuga). Siamo sottoposti a una quantità enorme di stimoli, e il nostro cervello seleziona automaticamente le informazioni da filtrare. Scopri come. 




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