Development of a Data Visualization Model based on Information Processing Theory

Information has emerged as being the fourth production factor and is becoming increasingly important in global competition. Research shows that managerial decision making is directly correlated to both, the swift availability, and subsequently the ease of interpretation of the relevant information. A holistic picture, including the relevant key performance indicators of the company, zooming between the micro and the macro environments, as well as the ability of the involved managers to interpret this information is therefore crucial for the performance of a company. The availability of so called ‘big data’ and the ever shorter cycle time between the identification of an important piece of information and the possible need of the management to react force traditional business concepts to change. Visualizations are already widely used to transform raw data into a more understandable format and to compress the huge amounts of data produced. However, research in this area is highly fragmented and results are contradicting. This paper proposes a preliminary model based on an extensive literature review incl. top current research on cognition theory. Furthermore an early stage validation of this model by exper-imental research using structural equation modeling is presented. The authors are able to identify predicting and moderating variables for information perception of visual data.