An intervention for motorcycle helmet usage based on technology acceptance model
Motorcycle is a major personal transport mode in Malaysia. However, majority of road accidents fatalities involve motorcyclist. Royal Malaysian Police reported that head is the most part of body casualties and fatalities in year 2014. One of the strategies to mitigate this problem is through proper...
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Main Author: | |
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Format: | Thesis |
Language: | English English English |
Published: |
2017
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Online Access: | http://eprints.uthm.edu.my/9972/2/24p%20NAIDA%20ROSLI.pdf http://eprints.uthm.edu.my/9972/1/NAIDA%20ROSLI%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/9972/3/NAIDA%20ROSLI%20WATERMARK.pdf |
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Summary: | Motorcycle is a major personal transport mode in Malaysia. However, majority of road accidents fatalities involve motorcyclist. Royal Malaysian Police reported that head is the most part of body casualties and fatalities in year 2014. One of the strategies to mitigate this problem is through proper usage of safety helmet. Thus, this study was introduce a new approach on motorcyclist safety using Technology Acceptance Model (TAM) with additional variables. TAM is a theory model used by researcher to examine the factor of acceptance of new technologies among users. To test the hypothesized model, 319 of respondents among motorcyclist was chosen as a sample size. The Structural Equation Modelling (SEM) approach was performed to test full structural model. The result shows that the goodness of fit indices are excellent fit and all variables (perceived usefulness, perceived ease of use, descriptive norm, subjective norm and perceived safety) were statistically significant towards behavioral intention to use Safety Helmet Reminder System (SHR). It demonstrates that SHR is significantly improve the helmet use among motorcyclist. R2 value of . 77 shows that 77% change in the criterion variables is caused due to the change taking place by a combination five predictor variables. Perceived Safety was found the most dominant variables towards behavioral intention to use Safety Helmet Reminder system. Therefore, TAM model with extended variables are suitable to predict the behavioral intention to use SHR system among motorcyclist. The conceptual of SHR system is proposed to function effectively and directly will increase safety helmet usage. |
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