Jinda Kongcharoen, Nutthajit Onmek, S. Karrila, Jariya Seksan
{"title":"Risk Factors Related to Road Traffic Accidents in Phuket Province, Southern Thailand: a Confirmatory Factor Analysis","authors":"Jinda Kongcharoen, Nutthajit Onmek, S. Karrila, Jariya Seksan","doi":"10.5507/tots.2021.020","DOIUrl":null,"url":null,"abstract":"Phuket is an outstanding province in promoting its economy to domestic and international tourism in Thailand. An investigation of relevant factors for understanding the accident process is one approach to reduce traffic accidents and thereby support tourism industry. This study aimed 1) to examine the characteristics of traffic accidents, physical and surface conditions, and driving behavior in Phuket province; 2) to investigate for an in-depth understanding the factors related to road accidents, including human and vehicle factors, and environmental conditions; and 3) to construct and verify a model concordant with the empirical data. The research instruments were a structural questionnaire to drivers and a checklist assessment of the road surface conditions. A stratified random sampling technique was used for selecting the drivers. The data were statistically analyzed using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and second-order confirmatory factor analysis (SCFA). The majority of drivers were males (56.75%), aged between 21 and 40 years (57.00 %), married (62.25%), and working as company employees (73.25%). The study revealed that nearly half (47.15%) of the road traffic accidents in Phuket province involved motorcycles, surpassing other types of vehicles. Traffic accidents were more likely to occur during the daytime (38.11%), followed by night-time at 37.03%. Guided by the EFA and CFA, the three categories of factors, namely human, environmental and vehicle factors, were confirmed as appropriate in fitted models. The results of SCFA revealed that almost all traffic accidents were caused by human factors, followed by environmental, and vehicle factors, in this rank order. The fitted model was concordant with the empirical data (χ/df = 1.847, GFI = 0.972, AGFI = 0.951, CFI = 0.945, NFI = 0.890, and RMSEA = 0.046). Moreover, substandard road surfaces contributed to traffic accidents as an enabling factor. The responsible agency, therefore, should assist in improving the physical road conditions. Safety consciousness must be set as the default behavior for drivers to avoid accidents. Road accident reduction in Phuket province will increase the confidence among tourists for choosing Thailand as their tourist destination.","PeriodicalId":52273,"journal":{"name":"Transactions on Transport Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions on Transport Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5507/tots.2021.020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
Phuket is an outstanding province in promoting its economy to domestic and international tourism in Thailand. An investigation of relevant factors for understanding the accident process is one approach to reduce traffic accidents and thereby support tourism industry. This study aimed 1) to examine the characteristics of traffic accidents, physical and surface conditions, and driving behavior in Phuket province; 2) to investigate for an in-depth understanding the factors related to road accidents, including human and vehicle factors, and environmental conditions; and 3) to construct and verify a model concordant with the empirical data. The research instruments were a structural questionnaire to drivers and a checklist assessment of the road surface conditions. A stratified random sampling technique was used for selecting the drivers. The data were statistically analyzed using exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and second-order confirmatory factor analysis (SCFA). The majority of drivers were males (56.75%), aged between 21 and 40 years (57.00 %), married (62.25%), and working as company employees (73.25%). The study revealed that nearly half (47.15%) of the road traffic accidents in Phuket province involved motorcycles, surpassing other types of vehicles. Traffic accidents were more likely to occur during the daytime (38.11%), followed by night-time at 37.03%. Guided by the EFA and CFA, the three categories of factors, namely human, environmental and vehicle factors, were confirmed as appropriate in fitted models. The results of SCFA revealed that almost all traffic accidents were caused by human factors, followed by environmental, and vehicle factors, in this rank order. The fitted model was concordant with the empirical data (χ/df = 1.847, GFI = 0.972, AGFI = 0.951, CFI = 0.945, NFI = 0.890, and RMSEA = 0.046). Moreover, substandard road surfaces contributed to traffic accidents as an enabling factor. The responsible agency, therefore, should assist in improving the physical road conditions. Safety consciousness must be set as the default behavior for drivers to avoid accidents. Road accident reduction in Phuket province will increase the confidence among tourists for choosing Thailand as their tourist destination.