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Does design matter when visualizing Big Data? An empirical study to investigate the effect of visualization type and interaction use

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  • Lisa Perkhofer

    (University of Applied Sciences Upper Austria)

  • Conny Walchshofer

    (University of Applied Sciences Upper Austria)

  • Peter Hofer

    (University of Applied Sciences Upper Austria)

Abstract

The need for good visualization is increasing, as data volume and complexity expand. In order to work with high volumes of structured and unstructured data, visualizations, supporting the ability of humans to make perceptual inferences, are of the utmost importance. In this regard, a lot of interactive visualization techniques have been developed in recent years. However, little emphasis has been placed on the evaluation of their usability and, in particular, on design characteristics. This paper contributes to closing this research gap by measuring the effects of appropriate visualization use based on data and task characteristics. Further, we specifically test the feature of interaction as it has been said to be an essential component of Big Data visualizations but scarcely isolated as an independent variable in experimental research. Data collection for the large-scale quantitative experiment was done using crowdsourcing (Amazon Mechanical Turk). The results indicate that both, choosing an appropriate visualization based on task characteristics and using the feature of interaction, increase usability considerably.

Suggested Citation

  • Lisa Perkhofer & Conny Walchshofer & Peter Hofer, 2020. "Does design matter when visualizing Big Data? An empirical study to investigate the effect of visualization type and interaction use," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(1), pages 55-95, April.
    • Handle: RePEc:spr:jmgtco:v:31:y:2020:i:1:d:10.1007_s00187-020-00294-0
    DOI: 10.1007/s00187-020-00294-0
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    References listed on IDEAS

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    1. Lisa Perkhofer & Othmar Lehner, 2019. "Using Gaze Behavior to Measure Cognitive Load," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph (ed.), Information Systems and Neuroscience, pages 73-83, Springer.
    2. Timur Pasch, 2019. "Strategy and innovation: the mediating role of management accountants and management accounting systems’ use," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 30(2), pages 213-246, July.
    3. Dilla, William N. & Raschke, Robyn L., 2015. "Data visualization for fraud detection: Practice implications and a call for future research," International Journal of Accounting Information Systems, Elsevier, vol. 16(C), pages 1-22.
    4. Janvrin, Diane J. & Raschke, Robyn L. & Dilla, William N., 2014. "Making sense of complex data using interactive data visualization," Journal of Accounting Education, Elsevier, vol. 32(4), pages 31-48.
    5. Christine Ohlert & Barbara Weißenberger, 2015. "Beating the base-rate fallacy: an experimental approach on the effectiveness of different information presentation formats," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 26(1), pages 51-80, April.
    6. Appelbaum, Deniz & Kogan, Alexander & Vasarhelyi, Miklos & Yan, Zhaokai, 2017. "Impact of business analytics and enterprise systems on managerial accounting," International Journal of Accounting Information Systems, Elsevier, vol. 25(C), pages 29-44.
    7. Singh, Kishore & Best, Peter, 2019. "Anti-Money Laundering: Using data visualization to identify suspicious activity," International Journal of Accounting Information Systems, Elsevier, vol. 34(C), pages 1-1.
    8. Yigitbasioglu, Ogan M. & Velcu, Oana, 2012. "A review of dashboards in performance management: Implications for design and research," International Journal of Accounting Information Systems, Elsevier, vol. 13(1), pages 41-59.
    9. Iris Vessey & Dennis Galletta, 1991. "Cognitive Fit: An Empirical Study of Information Acquisition," Information Systems Research, INFORMS, vol. 2(1), pages 63-84, March.
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    2. Domino, Madeline A. & Schrag, Daniel & Webinger, Mariah & Troy, Carmelita, 2021. "Linking data analytics to real-world business issues: The power of the pivot table," Journal of Accounting Education, Elsevier, vol. 57(C).

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