TY  - JOUR
PY  - 2023//
TI  - Using behavioral economics to optimize safer undergraduate late-night transportation
JO  - Journal of applied behavior analysis
A1  - Gelino, Brett W.
A1  - Graham, Madison E.
A1  - Strickland, Justin C.
A1  - Glatter, Hannah W.
A1  - Hursh, Steven R.
A1  - Reed, Derek D.
SP  - ePub
EP  - ePub
VL  - ePub
IS  - ePub
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 0021-8855
UR  - http://dx.doi.org/10.1002/jaba.1029
ID  - ref1
ER  -