Deriving a holistic cognitive fit model for an optimal visualization of data for management decisions

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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 contributionDeriving a holistic cognitive fit model for an optimal visualization of data for management decisions
Original languageGerman
Title of host publicationProceedings of the 2nd International Symposium on Partial Least Squares Path Modeling
Pages1-6
Publication statusPublished - 2015
Event2nd International Symposium on Partial Least Squares Path Modeling - Sevilla, Spain
Duration: 17 Jun 201518 Jun 2015

Conference

Conference2nd International Symposium on Partial Least Squares Path Modeling
CountrySpain
CitySevilla
Period17.06.201518.06.2015

Keywords

  • Information visualization
  • cognitive fit
  • decision making
  • PLS modelling

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