Using confidence interval-based estimation of relevance to determine women’s emotions and perceptions of the Malaysian road environment during COVID-19

Abstract

The road environment is one of the factors that contribute to road accidents. Extensive research has been conducted on the diversity of road users, conditions, and environments; however, it tends to be general in focus. In Malaysia, the road environment is an important element of the Critical National Information Infrastructure (CNII) agenda. As women play a greater role in a country’s population growth, they are considered to hold greater responsibility for the nation’s sustainability. This paper examines the road environment in Malaysia, centering on women’s perceptions and using emotions as a predictor. The study data were collected via an online Google form that was specifically targeted at female drivers. A total of 93 respondents participated in the survey. The results include an R2 value equal to 0.27 with a 99% confidence interval. The results indicate that emotions played a moderate role in determining women’s perceptions of the on-road environment. Meanwhile, respondents with negative emotions were able to separate their cognitive processes without affecting their perception. Current research indicates that the confidence interval-based estimation of relevance (CIBER) technique is efficient at predicting behavior and is useful for behavior modification in the future, which has significant implications for policy revision and recommendations. Limitations of this research include its focus on women and reliance on data collected during the pandemic, which may be different from other events or situations. Finally, this research suggests that it would be appropriate to establish future behavior interventions among road users at the national level.