Archivio per 1 novembre 2013

01
Nov
13

Stirling Behavioural Science Blog : Lecture Summary: Judgement, Heuristics and Biases

See on Scoop.itBounded Rationality and Beyond

What are heuristics?
This article by Kahneman and Tversky (1974) is still a classic description of the main heuristics that people use to judge probability and frequency. Heuristics can be thought of as mental ‘rules of thumb’ that people employ for all kinds of judgements. For example, if you want to share a cake among 5 people, rather than optimize the size of each slice depending on each person’s unique preferences, level of hunger, etc you might employ a 1/n heuristic and give everyone an equal 1/5th slice. Or if you see dark clouds forming on your way to work, you might decide to bring a raincoat. To paraphrase Kahneman & Tversky, “People rely on heuristic principles to reduce the complex tasks of assessing probabilities to simpler judgmental operations." I’ll briefly discuss some experiments and examples about the three heuristics from this paper.

See on economicspsychologypolicy.blogspot.co.uk

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01
Nov
13

Stirling Behavioural Science Blog : Lecture Summary: Judgement, Heuristics and Biases

See on Scoop.itBounded Rationality and Beyond

What are heuristics?
This article by Kahneman and Tversky (1974) is still a classic description of the main heuristics that people use to judge probability and frequency. Heuristics can be thought of as mental ‘rules of thumb’ that people employ for all kinds of judgements. For example, if you want to share a cake among 5 people, rather than optimize the size of each slice depending on each person’s unique preferences, level of hunger, etc you might employ a 1/n heuristic and give everyone an equal 1/5th slice. Or if you see dark clouds forming on your way to work, you might decide to bring a raincoat. To paraphrase Kahneman & Tversky, “People rely on heuristic principles to reduce the complex tasks of assessing probabilities to simpler judgmental operations.” I’ll briefly discuss some experiments and examples about the three heuristics from this paper.

See on economicspsychologypolicy.blogspot.co.uk

01
Nov
13

Stirling Behavioural Science Blog : Encouraging Innovation in Public Sector Employees: The Role of Financial Incentives on Creative Tasks

See on Scoop.itBounded Rationality and Beyond

The findings outlined above are important because complex and creative tasks are an essential part of modern day-to-day public sector work, and so understanding what drives this behaviour is a crucial tool for managers. A review on bonuses in the public sector commissioned in 2012 by the UK government demonstrates the difficult decisions in how best to motivate employees with financial means. The emerging evidence outlined here suggests that creating an environment where creativity can flourish requires us to reject many of the old assumptions about employee motivation through financial incentives. Therefore, to encourage creativity and greater innovation from the public sector workforce, managers must instead focus greater efforts on the many non-financial levers available to them. In her classic account, Professor Teresa Amabile of Harvard University suggests the most crucial factors are for employees to feel challenged, to have freedom, to have the resources to achieve the task, and supervisory encouragement [10]. A deeper understanding of the motivational forces acting upon employees is crucial to maximise the human capital potential of the public sector and to overcome the extraordinary challenges currently facing governments across the world.  
See on economicspsychologypolicy.blogspot.it

01
Nov
13

Stirling Behavioural Science Blog : Encouraging Innovation in Public Sector Employees: The Role of Financial Incentives on Creative Tasks

See on Scoop.itBounded Rationality and Beyond

The findings outlined above are important because complex and creative tasks are an essential part of modern day-to-day public sector work, and so understanding what drives this behaviour is a crucial tool for managers. A review on bonuses in the public sector commissioned in 2012 by the UK government demonstrates the difficult decisions in how best to motivate employees with financial means. The emerging evidence outlined here suggests that creating an environment where creativity can flourish requires us to reject many of the old assumptions about employee motivation through financial incentives. Therefore, to encourage creativity and greater innovation from the public sector workforce, managers must instead focus greater efforts on the many non-financial levers available to them. In her classic account, Professor Teresa Amabile of Harvard University suggests the most crucial factors are for employees to feel challenged, to have freedom, to have the resources to achieve the task, and supervisory encouragement [10]. A deeper understanding of the motivational forces acting upon employees is crucial to maximise the human capital potential of the public sector and to overcome the extraordinary challenges currently facing governments across the world.  
See on economicspsychologypolicy.blogspot.it

01
Nov
13

Can you persuade people not to buy stolen goods?

See on Scoop.itBounded Rationality and Beyond

What’s the best way to dissuade people from buying stolen goods? Past experience suggests there’s a way to make it socially beyond the pale.

A man comes up to you in the pub. “Nudge, nudge,” he says, conspiratorially. “Can I interest you in a brand new laptop. Perfect nick. £100. Say no more.”

Of course, you assume that the shiny machine is almost certainly stolen. So what does one do?

You know the correct answer is to say you’d make a citizen’s arrest while the landlord telephones the local constable. But the black market in stuff that just might have fallen off the back of a lorry predates lorries and probably the invention of the wheel.

 
See on bbc.co.uk

01
Nov
13

Can you persuade people not to buy stolen goods?

See on Scoop.itBounded Rationality and Beyond

What’s the best way to dissuade people from buying stolen goods? Past experience suggests there’s a way to make it socially beyond the pale.

A man comes up to you in the pub. “Nudge, nudge,” he says, conspiratorially. “Can I interest you in a brand new laptop. Perfect nick. £100. Say no more.”

Of course, you assume that the shiny machine is almost certainly stolen. So what does one do?

You know the correct answer is to say you’d make a citizen’s arrest while the landlord telephones the local constable. But the black market in stuff that just might have fallen off the back of a lorry predates lorries and probably the invention of the wheel.

 
See on www.bbc.co.uk

01
Nov
13

Chaos at fifty

See on Scoop.itBounded Rationality and Beyond

In classical physics, one is taught that given the initial state of a system, all of its future states can be calculated. In the celebrated words of Pierre Simon Laplace, “An intelligence which could comprehend all the forces by which nature is animated and the respective situation of the beings who compose it—an intelligence sufficiently vast to submit these data to analysis … for it, nothing would be uncertain and the future, as the past, would be present to its eyes.” 1 Or, put another way, the clockwork universe holds true.

Herein lies the rub: Exact knowledge of a real-world initial state is never possible—the adviser can always demand a few more digits of experimental precision from the student, but the result will never be exact. Still, until the 19th century, the tacit assumption had always been that approximate knowledge of the initial state implies approximate knowledge of the final state. Given their success describing the motion of the planets, comets, and stars and the dynamics of countless other systems, physicists had little reason to assume otherwise.

Starting in the 19th century, however, and culminating with a 1963 paper by MIT meteorologist Edward Lorenz, pictured in figure 1a, a series of developments revealed that the notion of deterministic predictability, although appealingly intuitive, is in practice false for most systems. Small uncertainties in an initial state can indeed become large errors in a final one. Even simple systems for which all forces are known can behave unpredictably. Determinism, surprisingly enough, does not preclude chaos.

See on scitation.aip.org




Time is real? I think not

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