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My interests are multidisciplinary and therefore span a range of different research areas that are described below. I am interested in collaboration or supervision associated with any of the the following research areas:

Information Framing

  • How are people’s preferences influenced by changing the scale upon which information is presented? For example, expressing the cost of fuel over 100,000 miles. Collaborators: Rick Larrick.
  • How are people’s preferences influenced when aggregating potential savings over a large number of people? For example, expressing the potential savings from use of an efficient lightbulb aggregated over an entire city. Collaborators: Rick Larrick.
  • How are people’s preferences influenced when a single product characteristic (e.g., fuel economy) is represented by multiple translated attributes (e.g., fuel consumed, cost of fuel, carbon emissions)? Collaborators: Christoph UngemachRick LarrickElke WeberEric Johnson.


  • Are people more motivated to pursue a goal when the timing of the goal’s achievement is probabilistic? For example, a loyalty card with uncertainty regarding when a free gift will be given. Collaborators: Ying Zhang and Jin Liyin.
  • Loyalty cardAre the factors that encourage people to attain the goal (e.g. velocity) the same as those factors that encourage people to maintain a goal? Collaborators: Jill Lei and Anish Nagpal.
  • What motivates people to over-invest in capacity (e.g., car size, computer specs)? In particular, does it have to do with biased recollection of previous extreme events? Collaborators: Sam Swift and Rick Larrick.
  • What motivates people to invest resources into keeping options open even when they cannot use all available options?
  • What features of the choice environment encourage people to repeat pro-environmental behaviors rather than licensing immoral ones? Collaborators: Christoph UngemachRick LarrickElke WeberEric Johnson.

Choices Under Risk and Uncertainty

  • How can people be nudged towards making more appropriate retirement investment decisions? Collaborators: Rob Hoffmann, and Marie-Anne Cam.
  • Does the number of realizations a single choice will produce – for example, a doctor choosing between a risky treatment and a safer treatment for a single patient or a group of patients – influence choice? Collaborators: Ben Newell.
  • When and how do preferences vary as a function of whether information is learned from a summary description or acquired from the personal experience of observing sampled outcomes over time? Collaborators: Ben Newell.
  • What mathematical model can best capture how decision-makers integrate experiences into mental representations that can subsequently be used to make probability judgments and form preferences?  Collaborators: Guy HawkinsBen Newell, and Scott Brown.

 Pro-social Marketing

Product Review Scores

  • How does the format in which product review scores are presented  influence people’s preferences? For example, are preferences different when focusing on the the summary review score versus focusing on the individual review scores?Screen Shot 2015-04-12 at 9.03.51 pm
  • To what extent do people understand the sampling biases inherent in online product review scores, which make review score distributions look more positive and extreme than would be without sampling biases. How can this (mis-)understanding be addressed?
  • How do people integrate the strength of evidence (e.g., average review score) with the weight of evidence (e.g., the number of reviewers)?