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Drivers’ Speeding Behavior in Residential Streets: A Structural Equation Modeling Approach

Autor(en):

ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Infrastructures, , n. 1, v. 8
Seite(n): 11
DOI: 10.3390/infrastructures8010011
Abstrakt:

Speeding in residential areas is a rampant high-risk driving behavior that occurs worldwide. This study investigated the intention and behavior of speeding in residential streets (with a speed limit of 30 km/h) in Iran based on the Theory of extended Planned Behavior (TPB). A total of 480 participants filled out the TPB-based questionnaire online. Nine different factors were identified by exploratory factor analysis. The interrelationship of these factors, as well as their connection with speeding intention and behavior, was analyzed using the Structural Equation Modeling (SEM) method. The results suggested that the adoption of the extended TPB framework to identify factors related to speeding in residential areas was effective in predicting speeding intention and behavior. Affective attitude, descriptive and personal norms, perceived behavioral control, habits, and specification of residential streets were direct predictors of speeding intention. The intention was also strongly associated with speeding behavior in residential areas, serving as the only factor that directly predicts speeding behavior. The two factors of specification and facilities were also significantly related to speeding behavior on residential streets. The results of this study can have positive implications for preventing and reducing crashes on residential streets.

Copyright: © 2023 the Authors. Licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10722760
  • Veröffentlicht am:
    22.04.2023
  • Geändert am:
    10.05.2023
 
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