The increasing use of video streaming services that followed the Covid-19 pandemic has more than ever driven a rising interest among various stakeholders in service provisioning chain to understand factors influencing quality of experience (QoE). Many research activities have so far addressed different influence factors in order to understand and improve QoE when using video streaming service. However, we have recognized the requirement to address QoE as multidimensional concept, and show the relationship between QoE, perceptual dimensions, and influence factors. In this paper, we provide the multidimensional modelling and analysis of QoE for video streaming. Result analysis has shown that QoE for video streaming can be modelled by using perception of quality of video and perception of ease of use of application as predictors. The analysis of influence of individual system (i.e., resolution, coding tree unit (CTU), and constant rate factor (CRF)), context (i.e., location, lighting, and video type), and human (i.e., gender, education level, and prior experience) factors and their interactions on QoE perceptual dimensions (i.e., perception of quality and perception of ease of use) show statistically significant impacts, which means that alternations of these factors can enhance perceptual dimensions and consequently QoE for video streaming which is a final goal.