Citation

Gelino BW, Graham ME, Strickland JC, Glatter HW, Hursh SR, Reed DD. J. Appl. Behav. Anal. 2023; ePub(ePub): ePub.

Copyright

(Copyright © 2023, Wiley-Blackwell)

DOI

10.1002/jaba.1029

PMID

37932923

Abstract

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.

Language: en

Keywords

alcohol; alternative transportation; behavioral economics; operant demand; undergraduate; university policy