Dynamic Experiments for Estimating Preferences: Time (DEEP)

Toubia, O., Johnson, E., Evgeniou, T., & Delquie, P. (2012). Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters. Management Science.

For setup please contact a Center for Decision Sciences Research Coordinator at deep@decisionsciences.columbia.edu


Table of Contents


Description


References


Description:

Purpose

 DEEP Time is an adaptive test -- allowing for a precise, robust, and fast elicitation of time preferences.
Questions

  • 20 Binary choice time items

Sub-scales

 DEEP Time estimates a quasi-hyperbolic time discounting model and estimates present bias and discount factor.
Domain

 Personality Constructs: Time Orientation
Sample items
  • Please consider the two options below. Which of these two options do you find more attractive?
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References:

Scale:
Toubia, O., Johnson, E., Evgeniou, T., & Delquie, P. (2012). Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters. Management Science.

Uses:
Huang, D., & Luo, L. (2013). Consumer Preference Elicitation of Complex Products using Fuzzy Support-Vector-Machine (SVM) Active Learning.

Ray, D., Golovin, D., Krause, A., & Camerer, C. (2012). Bayesian Rapid Optimal Adaptive Design (BROAD): Method and application distinguishing models of risky choice.

Chesney, T. (2013). Networked individuals predict a community wide outcome from their local information. Decision Support Systems.
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