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Learning and Fatigue in Real Discrete Choice Experiments

Qi Jiang et al.

Land Economics2025https://doi.org/10.3368/le.101.4.052823-0046r1article
AJG 3ABDC A
Weight
0.37

Abstract

We conduct a randomized controlled trial to evaluate the impact of training university students in Bogotá to use a smartphone app that displays real-time location-specific air quality data. The training increased participants’ acquisition of information about air quality, their knowledge about avoidance behavior, and most important, their reported avoidance behavior. Back-of-the-envelope calculations suggest that if scaled to the entire city of Bogotá, the training could reduce premature cardiovascular, cerebrovascular, and respiratory deaths among the additional 3–8 percent of the city’s population incentivized to undertake avoidance behavior by 51–61 percent per year, a benefit valued at US$11–13 million.

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https://doi.org/https://doi.org/10.3368/le.101.4.052823-0046r1

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@article{qi2025,
  title        = {{Learning and Fatigue in Real Discrete Choice Experiments}},
  author       = {Qi Jiang et al.},
  journal      = {Land Economics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.3368/le.101.4.052823-0046r1},
}

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Learning and Fatigue in Real Discrete Choice Experiments

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.