Helmet feature preferences and willingness to pay among iranian motorcyclists: A discrete choice experiment

To boost helmet use among motorcyclists, policymakers must use market fragmentation techniques and subsidize helmets in different subgroups. This intervention can work with health campaigns and fines for not wearing proper helmets.

Authors

Institutions

Publication Details

Journal
Traffic Injury Prevention
Published
2025-10-15
DOI
https://doi.org/10.1080/15389588.2025.2554855
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Helmet feature preferences and willingness to pay among iranian motorcyclists: A discrete choice experiment

Marziye Najafi, Morteza Rahbar Taramsari, Enayatollah Homaie Rad, Ali Davoudi Kiakalayeh et al.
Traffic Injury Prevention
Traffic and Road Safety
article

Helmet feature preferences and willingness to pay among iranian motorcyclists: A discrete choice experiment

Marziye Najafi, Morteza Rahbar Taramsari, Enayatollah Homaie Rad, Ali Davoudi Kiakalayeh, Mostafa Golshekan, Mahsa Eshik Aghasi, Hoorieh Hallajian
article en

Abstract

To boost helmet use among motorcyclists, policymakers must use market fragmentation techniques and subsidize helmets in different subgroups. This intervention can work with health campaigns and fines for not wearing proper helmets.

Traffic Injury Prevention
IIHMR University (IN), Guilan University of Medical Sciences (IR), University of Granma (CU)
Openalex Percentile: Top 64%
Traffic and Road Safety
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.