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This paper aims to investigate the marine vehicle accident characteristics in the inland waterways of Bangladesh, with particular emphasis on collision type accidents.

Accident data were collected from different sources such as the daily newspapers, reports of Department of Shipping (DOS) and Bangladesh Inland Water Transport Authority (BIWTA). The accidents are analysed according to different variables such as vehicle type, time distribution, spatial distribution, weather condition, nature of casualties, and others.

The study revealed that the leading causes of accidents were collision between ships, trawlers and country boats and loss of stability due to Nor'wester (a seasonal storm that appears from the north and western directions). Of the accidents, 80 per cent involve cargo vehicles hitting other vehicles. Collisions have increased dramatically over the last decade and the number of fatalities has increased significantly.

Many accidents in Bangladesh often remain under‐reported owing to limited exposure to the media, which is probably because the victims represent the poorer segment of society. This under‐reporting appears to be a major barrier for accident analysis and prevention.

The paper provides an explicit idea on the characteristics of accidents, so that the problem can be easily comprehended and necessary action can be taken by different stakeholders, such as operators, law enforcement agencies, designers, users and others concerned in order to come up with a coordinated action plan to stop these severe incidents.

This study aims to understand the determinants of online pharmacy or epharmacy adoption among young consumers in Bangladesh using an extended unified theory of acceptance and use of technology (UTAUT) model.

A structured Google Docs questionnaire was sent out to 420 respondents using messenger service; 285 useable responses were finally extracted. Data were empirically validated using the two-staged structural equation model (SEM)-neural network analysis approach.

The robustness of the classical UTAUT model remains intact in the context of online pharmacy adoption. Among the integrated variables, while perceived trust and health literacy were found significant, perceived risk and personal innovativeness were found insignificant in determining consumers’ intention to adopt online pharmacy. The neural network analysis provided further verification of these findings derived from the SEM.

The findings of this study would facilitate in devising better strategies for entering or expanding online pharmacy business in developing countries such as Bangladesh.

The originality of the current study relates to the two-fold contributions of this study. First, while this study extended the classical UTAUT model by incorporating perceived risk, perceived trust, personal innovativeness and health literacy, the inclusion of the following two variables is fresh within the extant online pharmacy literature. Second, by using a two-staged SEM-neural network analysis approach, this study advances the past studies on e-commerce adoption in pharmaceutical settings and provides a general understanding of the customers of developing countries.