  Modern video streaming services require quality assurance of the presented
audiovisual material. Quality assurance mechanisms allow streaming platforms to
provide quality levels that are considered sufficient to yield user
satisfaction, with the least possible amount of data transferred. A variety of
measures and approaches have been developed to control video quality, e.g., by
adapting it to network conditions. These include objective matrices of the
quality and thresholds identified by means of subjective perceptual judgments.
The former group of matrices has recently gained the attention of (multi)media
researchers. They call this area of study ``Quality of Experience'' (QoE). In
this paper, we present a review of QoE's theoretical models together with a
discussion of their properties and implications for the field. We argue that
most of them represent the bottom-up approach to modeling. Such models focus on
describing as many variables as possible, but with a limited ability to
investigate the causal relationship between them; therefore, the applicability
of the findings in practice is limited. To advance the field, we therefore
propose a structural, top-down model of video QoE that describes causal
relationships among variables. We hope that our framework will facilitate
designing comparable experiments in the domain.
