The purpose of this study is to examine the antecedents of behavioural intention to adopt mobile payment among working adults in Malaysia. The variables of the unified theory of acceptance and use of technology 2 (UTAUT2) with perceived security were adopted as a theoretical base. The gathered data through a questionnaire were examined by using multiple linear regression (MLR) analysis. The study revealed that performance expectancy, facilitating conditions, hedonic motivation, and perceived security are significant in mobile payment adoption. However, effort expectancy and social influence are not significant. The findings of this study contributed to a simple UTAUT2 model with perceived security as an additional construct in explaining the adoption intention of mobile payment. The findings of this study are applicable to the mobile payment service providers in Malaysia to improve their mobile payment quality by improving the facilitating conditions.

Abstract. In general, poor road conditions, specifically road cracks constitute a public nuisance, causing troublesome to road users, severe damage to vehicles and accidents. Hence, it is essential to detect the road crack earlier as an early-stage preventive for maintenance, but traditional inspection method used in Malaysia to physically collect the road information is extremely time-consuming, hazardous and labour-intensive. Nowadays, new technologies have improved the measuring performance. This leaves a gap in comparing two modern technologies in road cracks mapping. This study aims to explore the quality assessment between the unmanned aerial vehicle (UAV) and terrestrial laser scanning (TLS) methods in road cracks mapping. Two study areas inside the campus of Universiti Teknologi Malaysia (UTM), Johor, were selected. The ground control points (GCPs) and check points (CPs) at the study areas were georeferenced by global navigation satellite system (GNSS) data with MyRTKNet and ISKnet connections. Low altitude aerial imageries were collected using DJI Phantom 4 UAV, while Topcon GLS-2000 was employed to acquire the dense data of the cracked road. GNSS and manual inspection methods were performed to evaluate the results. In terms of mapping and measurement, both TLS and UAV methods produce almost similar results with average RMSE differences ranging from ±0.003 m to ±0.030 m and ±0.042 m to ±0.224 m respectively. This revealed that TLS is more accurate than UAV in mapping and measuring work. Differences in DTM quality across these approaches is below two (2) cm. Based on this study, TLS is more reliable than UAV. However, UAV offers advantages based on several considerations such as cost, time, safety, and accessibility. In summary, findings from this study shed some light to the authorities on the feasibility of UAV and TLS methods in road cracks mapping.

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