Application of technology acceptance model in predicting behavioral intention to use safety helmet reminder system.

Author(s)
Ambak, K. Ismail, R. Abdullah, R.A. Latiff, A.A. & Sanik, M.E.
Year
Abstract

Motorcycle is a common and popular mode of transportation in many developing countries. However, statistic of road accidents by the Royal Malaysian Police reveals that motorcyclists are found to be the most vulnerable road users as compared to users of other vehicles. This is due to the lack of safety protection and instability of motorcycles themselves. Despite the usefulness and effectiveness of safety helmet to prevent head injuries, majority of motorcycle users do not wear and fasten their helmet properly. This study presents a new approach in enhancing the safety of motorcycle riders through proper usage of safety helmet. The Technology Acceptance Model (TAM) was adopted in predicting the behavioural intention to use Safety Helmet Reminder (SHR) system towards a more proper helmet usage among motorcyclists. A multivariate analysis technique, known as Structural Equation Modelling (SEM) was used in modelling exercise. Results showed that the construct variables in TAM were found to be reliable and statistically significant. The evaluation of full structural model (TAM) showed the goodness-of-fit indices such as Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), Comparative of Fit Index (CFI) and Tucker Lewis Index (TLI) were greater 0.9 and Root Means Square Error Approximation (RMSEA) was less than 0.08. Perceived ease of use was found as strong predictors than perceived usefulness regarding behavioural intention to use SHR. In addition, this study postulates that behavioural intention to use SHR has direct effect on the proper usage of safety helmet significantly. (Author/publisher)

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Publication

Library number
20130614 ST [electronic version only]
Source

Research Journal of Applied Sciences, Engineering and Technology, Vol. 5 (2013), No. 3, p. 881-888, 43 ref.

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This publication is one of our other publications, and part of our extensive collection of road safety literature, that also includes the SWOV publications.