IDEAS home Printed from https://ideas.repec.org/a/spr/jmgtco/v31y2020i1d10.1007_s00187-020-00294-0.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00187-020-00294-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00187-020-00294-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. Iris Vessey & Dennis Galletta, 1991. "Cognitive Fit: An Empirical Study of Information Acquisition," Information Systems Research, INFORMS, vol. 2(1), pages 63-84, March.
    7. 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.
    8. 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.
    9. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maël Schnegg & Klaus Möller, 2022. "Strategies for data analytics projects in business performance forecasting: a field study," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 33(2), pages 241-271, June.
    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rikhardsson, Pall & Yigitbasioglu, Ogan, 2018. "Business intelligence & analytics in management accounting research: Status and future focus," International Journal of Accounting Information Systems, Elsevier, vol. 29(C), pages 37-58.
    2. 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.
    3. Ágnes Szukits, 2022. "The illusion of data-driven decision making – The mediating effect of digital orientation and controllers’ added value in explaining organizational implications of advanced analytics," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 33(3), pages 403-446, September.
    4. Karin Eberhard, 2023. "The effects of visualization on judgment and decision-making: a systematic literature review," Management Review Quarterly, Springer, vol. 73(1), pages 167-214, February.
    5. Klein, Thomas Michael & Drobnik, Thomas & Grêt-Regamey, Adrienne, 2016. "Shedding light on the usability of ecosystem services–based decision support systems: An eye-tracking study linked to the cognitive probing approach," Ecosystem Services, Elsevier, vol. 19(C), pages 65-86.
    6. Francis Aboagye‐Otchere & Cletus Agyenim‐Boateng & Abdulai Enusah & Theodora Ekua Aryee, 2021. "A Review of Big Data Research in Accounting," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(4), pages 268-283, October.
    7. Fábio Albuquerque & Paula Gomes Dos Santos, 2023. "Recent Trends in Accounting and Information System Research: A Literature Review Using Textual Analysis Tools," FinTech, MDPI, vol. 2(2), pages 1-27, April.
    8. Sulin Ba & Jan Stallaert & Andrew B. Whinston, 2001. "Research Commentary: Introducing a Third Dimension in Information Systems Design—The Case for Incentive Alignment," Information Systems Research, INFORMS, vol. 12(3), pages 225-239, September.
    9. van Capelleveen, Guido & Poel, Mannes & Mueller, Roland M. & Thornton, Dallas & van Hillegersberg, Jos, 2016. "Outlier detection in healthcare fraud: A case study in the Medicaid dental domain," International Journal of Accounting Information Systems, Elsevier, vol. 21(C), pages 18-31.
    10. Babajide Oyewo & Venancio Tauringana & Babajide Moses Omikunle & Olusola Owoyele, 2022. "The global management accounting principles (GMAP) and the relationship between organizational design elements," Accounting Research Journal, Emerald Group Publishing Limited, vol. 35(5), pages 637-659, March.
    11. Peters, Matt D. & Wieder, Bernhard & Sutton, Steve G. & Wakefield, James, 2016. "Business intelligence systems use in performance measurement capabilities: Implications for enhanced competitive advantage," International Journal of Accounting Information Systems, Elsevier, vol. 21(C), pages 1-17.
    12. Markus Jung & Mischa Seiter, 2021. "Towards a better understanding on mitigating algorithm aversion in forecasting: an experimental study," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 32(4), pages 495-516, December.
    13. Kocsis, David, 2019. "A conceptual foundation of design and implementation research in accounting information systems," International Journal of Accounting Information Systems, Elsevier, vol. 34(C), pages 1-1.
    14. Hutchison, Paul D. & Daigle, Ronald J. & George, Benjamin, 2018. "Application of latent semantic analysis in AIS academic research," International Journal of Accounting Information Systems, Elsevier, vol. 31(C), pages 83-96.
    15. Marimo, Pricilla & Kaplan, Todd R & Mylne, Ken & Sharpe, Martin, 2012. "Communication of uncertainty in weather forecasts," MPRA Paper 38287, University Library of Munich, Germany.
    16. Parsons, Linda M. & Tinkelman, Daniel, 2013. "Testing the feasibility of small multiples of sparklines to display semimonthly income statement data," International Journal of Accounting Information Systems, Elsevier, vol. 14(1), pages 58-76.
    17. Monica Ramos Montesdeoca & Agustín J. Sánchez Medina & Felix Blázquez Santana, 2019. "Research Topics in Accounting Fraud in the 21st Century: A State of the Art," Sustainability, MDPI, vol. 11(6), pages 1-31, March.
    18. Ahmad H. Juma’h & Yazan Alnsour, 2018. "Using Social Media Analytics: The Effect of President Trump’s Tweets On Companies’ Performance," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 17(1), pages 100-121, March.
    19. Bergeron, François & Raymond, Louis & Rivard, Suzanne, 2001. "Fit in strategic information technology management research: an empirical comparison of perspectives," Omega, Elsevier, vol. 29(2), pages 125-142, April.
    20. Mark E. Lokanan & Prerna Sharma, 2023. "Two Decades of Accounting Fraud Research: The Missing Meso-Level Analysis," SAGE Open, , vol. 13(3), pages 21582440231, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jmgtco:v:31:y:2020:i:1:d:10.1007_s00187-020-00294-0. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.