Using behavioral economics to optimize safer undergraduate late‐night transportation

Many universities sponsor student‐oriented transit services that could reduce alcohol‐induced risks but only if services adequately anticipate and adapt to student needs. Human choice data offer an optimal foundation for planning and executing late‐night transit services. In this simulated choice ex...

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Published in:Journal of applied behavior analysis 2024, Vol.57 (1), p.117-130
Main Authors: Gelino, Brett W., Graham, Madison E., Strickland, Justin C., Glatter, Hannah W., Hursh, Steven R., Reed, Derek D.
Format: Article
Language:English
Subjects:
alcohol
alternative transportation
behavioral economics
Economics, Behavioral
Humans
operant demand
Students
undergraduate
Universities
university policy
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container_start_page 117
container_title Journal of applied behavior analysis
container_volume 57
creator Gelino, Brett W.
Graham, Madison E.
Strickland, Justin C.
Glatter, Hannah W.
Hursh, Steven R.
Reed, Derek D.
description Many universities sponsor student‐oriented transit services that could reduce alcohol‐induced risks but only if services adequately anticipate and adapt to student needs. Human choice data offer an optimal foundation for planning and executing late‐night transit services. In this simulated choice experiment, respondents opted to either (a) wait an escalating delay for a free university‐sponsored “safe” option, (b) pay an escalating fee for an on‐demand rideshare service, or (c) pick a free, immediately available “unsafe” option (e.g., ride with an alcohol‐impaired driver). Behavioral‐economic nonlinear models of averaged‐choice data describe preference across arrangements. Best‐fit metrics indicate adequate sensitivity to contextual factors (i.e., wait time, preceding late‐night activity). At short delays, students preferred the free transit option. As delays extend beyond 30 min, most students preferred competing alternatives. These data depict a policy‐relevant delay threshold to better safeguard undergraduate student safety.
doi_str_mv 10.1002/jaba.1029
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subjects alcohol
alternative transportation
behavioral economics
Economics, Behavioral
Humans
operant demand
Students
undergraduate
Universities
university policy
title Using behavioral economics to optimize safer undergraduate late‐night transportation
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