Purpose 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. Design/methodology/approach 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. Findings 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. Practical implications The findings of this study would facilitate in devising better strategies for entering or expanding online pharmacy business in developing countries such as Bangladesh. Originality/value 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.
Previous research studies investigating the impact of situational variables on project planning effectiveness have not examined how the situational variables work together to influence planning effectiveness. A structural equation model (SEM) has been developed for describing and quantifying the influence of situational factors in project environments and organizational characteristics of performing organizations on project planning effectiveness. The individual effects of directly-observable variables on the project planning process were evaluated using regression analysis. The SEM approach enables the modelling of multiple factors as latent not-directly-measurable variable sets, thus providing a theoretical insight into how individual influence factors work together to determine the effectiveness of project planning efforts. The project environment has a dominant significant influence on the potential effectiveness of project planning efforts. In contrast, the influence of organizational characteristics is relatively insignificant.Project management, project planning, planning effectiveness, structural equation modelling, Australia,
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