Modeling effects of driver safety attitudes on traffic violations in China using the theory of planned behavior
Traffic violations are recognized as one of the main causes of traffic accidents and have been found to be closely associated with driver attitudes toward traffic safety. In this study, a modified theory of planned behavior (TPB) was used to model the effects of driver safety attitudes on traffic vi...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-04-01
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| Series: | IATSS Research |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S038611122200005X |
| _version_ | 1818315489570455552 |
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| author | Chaopeng Tan Yujia Shi Lin Bai Keshuang Tang Kazufumi Suzuki Hideki Nakamura |
| author_facet | Chaopeng Tan Yujia Shi Lin Bai Keshuang Tang Kazufumi Suzuki Hideki Nakamura |
| author_sort | Chaopeng Tan |
| collection | DOAJ |
| description | Traffic violations are recognized as one of the main causes of traffic accidents and have been found to be closely associated with driver attitudes toward traffic safety. In this study, a modified theory of planned behavior (TPB) was used to model the effects of driver safety attitudes on traffic violations, based on a questionnaire survey of 1505 drivers in China. In light of the strong correlations between the observed items, the items of the TPB components were grouped into several parcels, using an item-parceling method. Parcel-based structural equation modeling was then used to operationalize the modified TPB. The results indicate that the proposed model can accurately predict the occurrence of traffic violations based on the observed items related to driver traffic safety attitudes. It was found that driver attitudes, subjective norm, and perceived behavior control significantly affect traffic violations. For predicting traffic violations, driver attitudes toward traffic safety policies had the greatest influence, followed by driver attitudes toward risky driving behaviors and the attitudes of others toward risky driving behaviors. Finally, suggestions on traffic enforcement and education to reduce traffic violations are proposed based on the results. |
| first_indexed | 2024-12-13T09:06:21Z |
| format | Article |
| id | doaj.art-e3cec7fb2e7d4f11a9507f19343e3809 |
| institution | Directory Open Access Journal |
| issn | 0386-1112 |
| language | English |
| last_indexed | 2024-12-13T09:06:21Z |
| publishDate | 2022-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | IATSS Research |
| spelling | doaj.art-e3cec7fb2e7d4f11a9507f19343e38092022-12-21T23:53:03ZengElsevierIATSS Research0386-11122022-04-014616372Modeling effects of driver safety attitudes on traffic violations in China using the theory of planned behaviorChaopeng Tan0Yujia Shi1Lin Bai2Keshuang Tang3Kazufumi Suzuki4Hideki Nakamura5College of Transportation Engineering, Tongji University, Shanghai 201804, ChinaCollege of Transportation Engineering, Tongji University, Shanghai 201804, ChinaCollege of Transportation Engineering, Tongji University, Shanghai 201804, ChinaCollege of Transportation Engineering, Tongji University, Shanghai 201804, China; Corresponding author.Department of Civil Engineering, National Institute of Technology, Gunma College, Maebashi 371-8530, JapanGraduate School of Environmental Studies, Nagoya University, Nagoya 464-8603, JapanTraffic violations are recognized as one of the main causes of traffic accidents and have been found to be closely associated with driver attitudes toward traffic safety. In this study, a modified theory of planned behavior (TPB) was used to model the effects of driver safety attitudes on traffic violations, based on a questionnaire survey of 1505 drivers in China. In light of the strong correlations between the observed items, the items of the TPB components were grouped into several parcels, using an item-parceling method. Parcel-based structural equation modeling was then used to operationalize the modified TPB. The results indicate that the proposed model can accurately predict the occurrence of traffic violations based on the observed items related to driver traffic safety attitudes. It was found that driver attitudes, subjective norm, and perceived behavior control significantly affect traffic violations. For predicting traffic violations, driver attitudes toward traffic safety policies had the greatest influence, followed by driver attitudes toward risky driving behaviors and the attitudes of others toward risky driving behaviors. Finally, suggestions on traffic enforcement and education to reduce traffic violations are proposed based on the results.http://www.sciencedirect.com/science/article/pii/S038611122200005XRoad safetyTraffic violationsDriver attitudesTheory of planned behaviorStructural equation modeling |
| spellingShingle | Chaopeng Tan Yujia Shi Lin Bai Keshuang Tang Kazufumi Suzuki Hideki Nakamura Modeling effects of driver safety attitudes on traffic violations in China using the theory of planned behavior IATSS Research Road safety Traffic violations Driver attitudes Theory of planned behavior Structural equation modeling |
| title | Modeling effects of driver safety attitudes on traffic violations in China using the theory of planned behavior |
| title_full | Modeling effects of driver safety attitudes on traffic violations in China using the theory of planned behavior |
| title_fullStr | Modeling effects of driver safety attitudes on traffic violations in China using the theory of planned behavior |
| title_full_unstemmed | Modeling effects of driver safety attitudes on traffic violations in China using the theory of planned behavior |
| title_short | Modeling effects of driver safety attitudes on traffic violations in China using the theory of planned behavior |
| title_sort | modeling effects of driver safety attitudes on traffic violations in china using the theory of planned behavior |
| topic | Road safety Traffic violations Driver attitudes Theory of planned behavior Structural equation modeling |
| url | http://www.sciencedirect.com/science/article/pii/S038611122200005X |
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