Cargando…

Extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior

Low-speed driving is an underestimated dangerous behavior that may cause safety issues, such as speed dispersion and traffic flow bottlenecks. To investigate the influence mechanism of low-speed driving behavior, this study constructed the low-speed specific model (LSSM) by extending theory of plann...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Jinliang, Liu, Huan, Liu, Xianyong, Gao, Chao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575494/
https://www.ncbi.nlm.nih.gov/pubmed/37831699
http://dx.doi.org/10.1371/journal.pone.0287489
_version_ 1785120934005309440
author Xu, Jinliang
Liu, Huan
Liu, Xianyong
Gao, Chao
author_facet Xu, Jinliang
Liu, Huan
Liu, Xianyong
Gao, Chao
author_sort Xu, Jinliang
collection PubMed
description Low-speed driving is an underestimated dangerous behavior that may cause safety issues, such as speed dispersion and traffic flow bottlenecks. To investigate the influence mechanism of low-speed driving behavior, this study constructed the low-speed specific model (LSSM) by extending theory of planned behavior (TPB). The LSSM incorporated two factors, namely, risk perception and behavior habit, into the standard TPB components (attitude, subjective norm, perceived behavioral control, and behavior intention). Web-based questionnaires were used to collect data from a valid sample of 374, of which males accounted for 50%. The participants were aged from 18 to 65 years (M = 35.40, SD = 0.88). The structural equation model was applied to calculate and validate the interrelationships among the components of LSSM. Results showed that the LSSM could explain the variance in low-speed driving behavior and behavior intention by 46% and 76%, respectively. Meanwhile, attitude (β = 0.52, p < 0.001) and behavior habit (β = 0.48, p < 0.001) had the strongest positive influence and prediction power over low-speed driving behavior, respectively, whereas subjective norm (β = 0.05, p > 0.01) and perceived behavioral control (β = -0.12, p > 0.01) showed few significant in influencing the intention. LSSM also showed that people who were sensitive to driving risk perception would avoid low-speed driving behaviors and attitudes. Our findings may provide theoretical support for interventions on low-speed driving behavior.
format Online
Article
Text
id pubmed-10575494
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-105754942023-10-14 Extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior Xu, Jinliang Liu, Huan Liu, Xianyong Gao, Chao PLoS One Research Article Low-speed driving is an underestimated dangerous behavior that may cause safety issues, such as speed dispersion and traffic flow bottlenecks. To investigate the influence mechanism of low-speed driving behavior, this study constructed the low-speed specific model (LSSM) by extending theory of planned behavior (TPB). The LSSM incorporated two factors, namely, risk perception and behavior habit, into the standard TPB components (attitude, subjective norm, perceived behavioral control, and behavior intention). Web-based questionnaires were used to collect data from a valid sample of 374, of which males accounted for 50%. The participants were aged from 18 to 65 years (M = 35.40, SD = 0.88). The structural equation model was applied to calculate and validate the interrelationships among the components of LSSM. Results showed that the LSSM could explain the variance in low-speed driving behavior and behavior intention by 46% and 76%, respectively. Meanwhile, attitude (β = 0.52, p < 0.001) and behavior habit (β = 0.48, p < 0.001) had the strongest positive influence and prediction power over low-speed driving behavior, respectively, whereas subjective norm (β = 0.05, p > 0.01) and perceived behavioral control (β = -0.12, p > 0.01) showed few significant in influencing the intention. LSSM also showed that people who were sensitive to driving risk perception would avoid low-speed driving behaviors and attitudes. Our findings may provide theoretical support for interventions on low-speed driving behavior. Public Library of Science 2023-10-13 /pmc/articles/PMC10575494/ /pubmed/37831699 http://dx.doi.org/10.1371/journal.pone.0287489 Text en © 2023 Xu et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Xu, Jinliang
Liu, Huan
Liu, Xianyong
Gao, Chao
Extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior
title Extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior
title_full Extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior
title_fullStr Extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior
title_full_unstemmed Extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior
title_short Extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior
title_sort extended theory of planned behavior to explain the influence mechanism of low-speed driving behavior
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10575494/
https://www.ncbi.nlm.nih.gov/pubmed/37831699
http://dx.doi.org/10.1371/journal.pone.0287489
work_keys_str_mv AT xujinliang extendedtheoryofplannedbehaviortoexplaintheinfluencemechanismoflowspeeddrivingbehavior
AT liuhuan extendedtheoryofplannedbehaviortoexplaintheinfluencemechanismoflowspeeddrivingbehavior
AT liuxianyong extendedtheoryofplannedbehaviortoexplaintheinfluencemechanismoflowspeeddrivingbehavior
AT gaochao extendedtheoryofplannedbehaviortoexplaintheinfluencemechanismoflowspeeddrivingbehavior