Virtual Reality Vehicle Inspection Routine (VR-VIR): Evaluation of Technology Acceptance

This paper proposes a Virtual Reality Vehicle Inspection Routine (VR-VIR) simulation application that teaches students how to perform vehicle inspections, also known as “Rutin Pemeriksaan Kenderaan” in Malaysia, which drivers must learn before obtaining a Malaysian driver’s license. The goal of VR-VIR is to provide students with a fresh perspective on learning the vehicle inspection routine module to ensure their vehicle's safety on the road. Users can learn about vehicle inspection routines in a more informative and hands-on manner through the VR-VIR, supplementing existing methods of learning such as books or videos. Users who have never performed vehicle inspections before or are unsure how to do so properly can practice in a safe virtual setting during and post-pandemic. Virtual Reality (VR) is widely used in various fields to aid learning in the virtual world. Many scholars engaged with the Technology Acceptance Model (TAM) to explore user acceptance of new technology. However, there are limited studies on evaluating user acceptance for vehicle inspection routines through VR using TAM. Thus, this research aims to investigate how the VR-VIR affects user acceptance. Davis's TAM final version was used to assess how the VR-VIR was accepted based on elements of perceived ease of use (PEU), perceived usefulness (PU), and behavioral intention (BI). The 28 respondents evaluated the VR-VIR and answered questionnaires through a simple random sampling method. Three experts in IT and VR were involved in VR-VIR construct validation and design evaluation. Data analysis is on descriptive and correlation analysis using SPSS 26.0. The findings showed positive responses from users with medium and high values on PEU (mean = 4.04), PU (mean = 3.72), and BI (mean = 3.30). Experts’ findings also indicated medium and high values in PEU (mean = 3.67), PU (mean = 3.92), and BI (mean = 4.00). The findings on correlation analysis for Hypothesis (H1, H2, and H3) found the correlation coefficient (r) is significant with a value of r > 0.50, indicating PEU (r = 0.63), PU (r = 0.59) and BI (r = 0.63) have a strong correlation. Thus, all hypotheses are accepted. The study proved that VR-VIR is accepted by users and can assist them in learning vehicle inspection routines. This research contributes to the vehicle inspection routine in VR transport field, as a virtual learning tool for experiencing the vehicle inspection process. This study can be enhanced by improvements in interaction and application design