There are a number of factors that cause motor vehicles to rollover. However, the impacts of roadway characteristics on rollover crashes have rarely been addressed in the literature. This study aims to apply a set of crash prediction models in order to estimate the number of rollovers as a function of road geometry, the environment, and traffic conditions. To this end, seven count-data models, including Poisson (PM), negative binomial (NB), heterogeneous negative binomial (HTNB), zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), hurdle Poisson (HP), and hurdle negative binomial (HNB) models, were developed and compared using crash data collected on 448 segments of Malaysian federal roads. The results showed that the HTNB was the best-fit model among the others to model the frequency of rollovers. The variables Light-Vehicle Traffic (LVT), horizontal curvature, access points, speed limit, and centreline median were positively associated with the crash frequency, while UnPaved Shoulder Width (UPSW) and Heavy-Vehicle Traffic (HVT) were found to have the opposite effect. The findings of this study suggest that rollovers could potentially be reduced by developing road safety countermeasures, such as access management of driveways, straightening sharp horizontal curves, widening shoulder width, better design of centreline medians, and posting lower speed limits and warning signs in areas with higher rollover tendency.

Purpose The purpose of this paper is to investigate the effects of consumers’ perceptions towards volume discount (VD) benefits on their intention to purchase grocery products under this scheme using deal proneness as a moderator. Design/methodology/approach Data were gathered through a survey of 583 Malaysian consumers, and were analysed using the partial least squares technique. Findings The results showed that perceived savings, self-expression value, and convenience positively affected consumers’ intention to purchase grocery products under VDs. Deal proneness negatively moderated the relationship between perceived quality, innovation, and consumers’ intention to purchase under VDs. Practical implications The findings of the study will help retailers to understand the effects of consumers’ perceptions of VD benefits on their intention to purchase products under VDs, thereby allowing retailers to promote products under VDs more effectively. Originality/value Although the VD is a common type of sales promotion, this topic is rarely explored. This study thus contributes to the advancement of knowledge by determining the effects of the potential benefits of VDs on consumers’ intention to purchase.

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The results indicated the presence of overdispersion in the pedestrian crashes (PCs) and showed that it is due to excess zero rather than variability in the crash data. To handle the issue, the hurdle Poisson model was found to be the best model among the considered models in terms of comparative measures. Moreover, the variables average daily traffic, heavy vehicle traffic, speed limit, land use, and area type were significantly associated with PCs.

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