D.G. Goldstein (Daniel G.)
http://repub.eur.nl/ppl/55035/
List of Publicationsenhttp://repub.eur.nl/eur_signature.png
http://repub.eur.nl/
RePub, Erasmus University RepositoryUsing Preferred Outcome Distributions to Estimate Value and Probability Weighting Functions in Decisions under Risk
http://repub.eur.nl/pub/39958/
Wed, 08 May 2013 00:00:01 GMT<div>A.C.D. Donkers</div><div>C.J.S. Lourenço</div><div>B.G.C. Dellaert</div><div>D.G. Goldstein</div>
In this paper we propose the use of preferred outcome distributions as a new method to elicit individuals’ value and probability weighting functions in decisions under risk. Extant approaches for the elicitation of these two key ingredients of individuals’ risk attitude typically rely on a long, chained sequence of lottery choices. In contrast, preferred outcome distributions can be elicited through an intuitive graphical interface, and, as we show, the information contained in two preferred outcome distributions is sufficient to identify non-parametrically both the value function and the probability weighting function in rank-dependent utility models. To illustrate our method and its advantages, we run an incentive-compatible lab study in which participants use a simple graphical interface – the Distribution Builder (Goldstein et al. 2008) – to construct their preferred outcome distributions, subject to a budget constraint. Results show that estimates of the value function are in line with previous research but that probability weighting biases are diminished, thus favoring our proposed approach based on preferred outcome distributions.Using Preferred Outcome Distributions to estimate
Value and Probability Weighting Functions in Decisions
under Risk
http://repub.eur.nl/pub/40405/
Wed, 08 May 2013 00:00:01 GMT<div>A.C.D. Donkers</div><div>T. Lourenco</div><div>B.G.C. Dellaert</div><div>D.G. Goldstein</div>
In this paper we propose the use of preferred outcome distributions as a new method to elicit individuals' value and probability weighting functions in decisions under risk. Extant approaches for the elicitation of these two key ingredients of individuals' risk attitude typically rely on a long, chained sequence of lottery choices. In contrast, preferred outcome distributions can be elicited through an intuitive graphical interface, and, as we show, the information contained in two preferred outcome distributions is sufficient to identify non-parametrically both the value function and the probability weighting function in rank-dependent utility models. To illustrate our method and its advantages, we run an incentive-compatible lab study in which participants use a simple graphical interface - the Distribution Builder (Goldstein et al. 2008) - to construct their preferred outcome distributions, subject to a budget constraint. Results show that estimates of the value function are in line with previous research but that probability weighting biases are diminished, thus favoring our proposed approach based on preferred outcome distributions.
Beyond nudges: Tools of a choice architecture
http://repub.eur.nl/pub/34799/
Fri, 01 Jun 2012 00:00:01 GMT<div>E.J. Johnson</div><div>S.B. Shu</div><div>B.G.C. Dellaert</div><div>C. Fox</div><div>D.G. Goldstein</div><div>G. Häubl</div><div>R.P. Larrick</div><div>J.W. Payne</div><div>E. Peters</div><div>D. Schkade</div><div>B. Wansink</div><div>E.U. Weber</div>
The way a choice is presented influences what a decision-maker chooses. This paper outlines the tools available to choice architects, that is anyone who present people with choices. We divide these tools into two categories: those used in structuring the choice task and those used in describing the choice options. Tools for structuring the choice task address the idea of what to present to decision-makers, and tools for describing the choice options address the idea of how to present it. We discuss implementation issues in using choice architecture tools, including individual differences and errors in evaluation of choice outcomes. Finally, this paper presents a few applications that illustrate the positive effect choice architecture can have on real-world decisions.