Abstract
Research shows that the quality of managerial decision making is dependent on both the availability and the interpretation of information. Visualizations are widely used to transform raw data into a more understandable format and to compress the constantly growing amount of information being produced. However, research in this area is highly fragmented and results are contradicting. A possible explanation for inconsistent results is the neglect of individual characteristics such as experience, working memory capacity, or cultural background. We propose a preliminary model based on an extensive literature review on cognition theory that sheds light on potential individual antecedents of information processing efficiency. Our preliminary results based on eye tracking, automated span tasks, as well as survey data show that domain expertise, spatial ability and long term orientation exert a significant influence on this cognitive construct.
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Dilla, W., Janvrin, D.J., Raschke, R.: Interactive data visualization: new directions for accounting information systems research. J. Inf. Syst. 24(2), 1–37 (2010)
Edmunds, A., Morris, A.: The problem of information overload in business organizations: a review of the literature. Int. J. Inf. Manage. 20(1), 17–28 (2000)
Eppler, M.J., Mengis, J.: The concept of information overload: a review of literature from organization science, accounting, marketing, MIS, and related disciplines. Inf. Soc. 20, 35–344 (2004)
Lurie, N.H., Mason, C.H.: Visual representation: implications for decision making. J. Mark. 71(1), 160–177 (2007)
Tortosa-Edo, V., López-Navarro, M.A., Llorens-Monzonís, J., Rodríguez-Artola, R.M.: The antecendent role of personal environment values in the relationships among trust in companies, information processing and risk perception. J. Risk Res. 17(8), 1019–1035 (2014)
Al-Kassab, J., Ouertani, Z.M., Schiuma, G., Neely, A.: Information visualization to support management decisions. Int. J. Inf. Technol. Decis. Making 13(2), 407–428 (2014)
Parsons, P., Sedig, K.: Adjustable properties of visual representations: improving the quality of human-information interaction. J. Assoc. Inf. Sci. Technol. 65(3), 455–482 (2014)
Conati, C., Maclaren, H.: Exploring the role of individual differences in information visualization. In: Proceedings of AVI 2008, pp. 199–206. ACM (2008)
Barat, A.H.: Human perception and knowledge organization: visual imagery. Libr. Hi Tech. 25(3), 338–351 (2007)
Galletta, D., Vessey, I.: Cognitive fit: an empirical study of information acquisition. Inf. Syst. Res. 2(1), 63–84 (1991)
Porat, T., Oron-Gilad, T., Meyer, J.: Task-dependent processing of tables and graphs. Behav. Inf. Technol. 28(3), 293–307 (2009)
So, S., Smith, M.: Multivariate decision accuracy and the presentation of accounting information. Acc. Forum 28(3), 283–305 (2004)
Dilla, W.N., Janvrin, D.J.: Voluntary disclosure in annual reports: the association between magnitude and direction of change in corporate financial performance and graph use. Acc. Horiz. 24(2), 257–278 (2010)
Parush, A., Hod, A., Shtub, A.: Impact of visualization type and contextual factors on performance with enterprise resource planning systems. Comput. Ind. Eng. 52(1), 133–142 (2007)
Peck, E.M., Yuksel, B.R., Harrison, L., Ottley, A., Remco, C.: Position paper: towards a 3-dimensional model of individual cognitive differences. In: Proceedings of BELIV 2012, pp. 1–6. ACM (2012)
Yigitbasioglu, O.M., Valcu, O.: A review of dashboards in performance management: implications for design and research. Int. J. Acc. Inf. Syst. 13(1), 41–59 (2012)
Ziemkiewicz, C., Kosara, R.: Beyond bertin: seeing the forest despite the trees. IEEE Comput. Graph. Appl. 30(5), 7–11 (2010)
Miller, G.A.: The magical number seven, plus or minus two: some limits on our capacity for processing information. Psychol. Rev. 63, 81–97 (1956)
Lord, R.G., Maher, K.J.: Alternative information-processing models and their implications for theory, research, and practice. Acad. Manage. Rev. 15(1), 9–28 (1990)
Anderson, E.W., Potter, K.C., Matzen, L.E., Shepherd, J.F., Preston, G.A., Silva, C.T.: A user study of visualization effectiveness using EEG and cognitive load. In: Eurographics/IEEE Symposium on Visualization 2011 vol. 30, issue 3, pp. 791–800 (2011)
Mostyn, G.R.: Cognitive load theory: what it is, why it’s important for accounting construction and research. Issues Acc. Educ. 27(1), 227–245 (2012)
Vessey, I.: Cognitive fit: a theory-based analysis of the graphs versus tables literature. Decis. Sci. 22(2), 219–240 (1991)
Hill, W.Y., Milner, M.M.: Guidelines for graphical displays in financial reporting. Acc. Educ. 12(2), 135–157 (2003)
Kuang, X., Zhang, H., Zhao, S., McGuffin, M.J.: Tracing tuples across dimensions: a ccomparison of scatterplots and parallel coordinate plots. Comput. Graph. Forum 31(3), 1365–1374 (2012)
Speier, C., Vessey, I., Valacich, J.S.: The effects of interruptions, task complexity, and computer-supported decision-making performance. Decis. Sci. 34(4), 771–797 (2003)
Hard, N.J., Vanecek, M.T.: The implications of task and format on the use of financial information. J. Inf. Syst. 5(2), 35–49 (1991)
Wood, R.E.: Task complexity: definition of the construct. Organ. Behav. Hum. Decis. Process. 37, 60–82 (1986)
Speier, C.: The influence of information presentation formats on complex task decision-making performance. Int. J. Hum. Comput. Stud. 64(11), 1115–1131 (2006)
Gelman, A., Unwin, A.: InfoVis and statistical graphics: different goals, different looks. J. Comput. Graph. Stat. 22(1), 2–28 (2013)
Hahn, U.: Experiential limitation in judgment and decision. Top. Cogn. Sci. 6(2), 229–244 (2014)
Kook, N., Parente, R., Verville, J.: Can hofstede’s model explain national differences in perceived information overload? a look at data from the US and New Zealand. IEEE Trans. Prof. Commun. 51(1), 33–49 (2008)
Goldberg, J., Helfman, J.: Eye tracking on visualizations: progressive extraction of scanning strategies. In: Huang, W. (ed.) Handbook of Human Centric Visualization, pp. 337–372. Springer (2014)
Renshaw, J.A., Finlay, J.E., Tyfa, D., Ward, R.D.: Designing for visual influence: an eye tracking study of the usability of graphical management information. In: Proceedings of Interact 2003, pp. 144–151. ACM (2003)
Redick, T.S., Broadway, J.M., Meier, M.E., Kuriakose, N.U., Kane, M.J., Engle, R.W.: Measuring working memory capacity with automated complex span tasks. Eur. J. Psychol. Assess. 28(3), 164–171 (2012)
Hofstede, G.: Culture’s Consequences: Comparing Values, Behaviors, Institutions and Organizations Across Nations, 2nd edn. Sage Publications (2001)
Hair, J.F., Hult, G.T.M., Ringle, C.M., Sarstedt, M.: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publishing (2014)
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Falschlunger, L., Treiblmaier, H., Lehner, O., Grabmann, E. (2015). Cognitive Differences and Their Impact on Information Perception: An Empirical Study Combining Survey and Eye Tracking Data. In: Davis, F., Riedl, R., vom Brocke, J., Léger, PM., Randolph, A. (eds) Information Systems and Neuroscience. Lecture Notes in Information Systems and Organisation, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-18702-0_18
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DOI: https://doi.org/10.1007/978-3-319-18702-0_18
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