Abstract
Research shows that managerial decision making is directly correlated to both, the swift availability, and subsequently the ease of interpretation of the relevant information. Visualizations are already widely used to transform raw data into a more understandable format and to compress the constantly growing amount of information 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 including top current research on cognition theory. Furthermore an early stage validation of this model by experimental research using structural equation modeling is presented. The authors are able to identify task complexity as one of the most important predicting variables for information perception of visual data, however, other influences are significant as well (data density, domain expertise, working memory capacity and subjective visual complexity).
Translated title of the contribution | Deriving a holistic cognitive fit model for an optimal visualization of data for management decisions |
---|---|
Original language | German |
Title of host publication | Proceedings of the 2nd International Symposium on Partial Least Squares Path Modeling |
Pages | 1-6 |
Publication status | Published - 2015 |
Event | 2nd International Symposium on Partial Least Squares Path Modeling - Sevilla, Spain Duration: 17 Jun 2015 → 18 Jun 2015 |
Conference
Conference | 2nd International Symposium on Partial Least Squares Path Modeling |
---|---|
Country/Territory | Spain |
City | Sevilla |
Period | 17.06.2015 → 18.06.2015 |
Keywords
- Information visualization
- cognitive fit
- decision making
- PLS modelling