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Visualization in Operations Management Research

Author

Listed:
  • Rahul Basole

    (Accenture AI, Atlanta, Georgia 30308)

  • Elliot Bendoly

    (Operations and Business Analytics, The Ohio State University, Columbus, Ohio 43210)

  • Aravind Chandrasekaran

    (Operations and Business Analytics, The Ohio State University, Columbus, Ohio 43210)

  • Kevin Linderman

    (Penn State University, State College, Pennsylvania 16801)

Abstract

The unprecedented availability of data, along with the growing variety of software packages to visualize it, presents both opportunities and challenges for operations management (OM) research. OM researchers typically use data to describe conditions, predict phenomena, or make prescriptions depending on whether they are building, testing, or translating theories to practice. Visualization, when used appropriately, can complement, aid, and augment the researcher’s understanding in the different stages of research (theory building, testing, or translating and conveying results). On the other hand, if used incorrectly or without sufficient consideration, visualization can yield misleading and erroneous claims. This article formally examines the benefits of visualization as a complementary method enhancing each stage of a broader OM research strategy by examining frameworks and cases from extant research in different OM contexts. Our discussion offers guidance with regard to researchers’ use of visual data renderings, particularly toward avoiding misrepresentation, which can arise with the incorrect use of visualization. We close with a consideration of emerging trends and their implications for researchers and practitioners as well as recommendations for both authors and reviewers, regardless of domain, in evaluating the effectiveness of visuals at each stage of research.

Suggested Citation

  • Rahul Basole & Elliot Bendoly & Aravind Chandrasekaran & Kevin Linderman, 2022. "Visualization in Operations Management Research," INFORMS Joural on Data Science, INFORMS, vol. 1(2), pages 172-187, October.
    • Handle: RePEc:inm:orijds:v:1:y:2022:i:2:p:172-187
    DOI: 10.1287/ijds.2021.0005
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    References listed on IDEAS

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    1. Kalyan Singhal & Qi Feng & Ram Ganeshan & Nada R. Sanders & J. George Shanthikumar, 2018. "Introduction to the Special Issue on Perspectives on Big Data," Production and Operations Management, Production and Operations Management Society, vol. 27(9), pages 1639-1641, September.
    2. Stefan Kurpjuweit & Dagmar Reinerth & Christoph G. Schmidt & Stephan M. Wagner, 2019. "Implementing visual management for continuous improvement: barriers, success factors and best practices," International Journal of Production Research, Taylor & Francis Journals, vol. 57(17), pages 5574-5588, September.
    3. Stylianos Kavadias & Karl T. Ulrich, 2020. "Innovation and New Product Development: Reflections and Insights from the Research Published in the First 20 Years of Manufacturing & Service Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 84-92, January.
    4. Franco, L. Alberto & Greiffenhagen, Christian, 2018. "Making OR practice visible: Using ethnomethodology to analyse facilitated modelling workshops," European Journal of Operational Research, Elsevier, vol. 265(2), pages 673-684.
    5. Hardcopf, Rick & Gonçalves, Paulo & Linderman, Kevin & Bendoly, Elliot, 2017. "Short-term bias and strategic misalignment in operational solutions: Perceptions, tendencies, and traps," European Journal of Operational Research, Elsevier, vol. 258(3), pages 1004-1021.
    6. Sodhi, ManMohan S. & Tang, Christopher S., 2014. "Guiding the next generation of doctoral students in operations management," International Journal of Production Economics, Elsevier, vol. 150(C), pages 28-36.
    7. Chih-Hung Peng & Nicholas H. Lurie & Sandra A. Slaughter, 2019. "Using Technology to Persuade: Visual Representation Technologies and Consensus Seeking in Virtual Teams," Information Systems Research, INFORMS, vol. 30(3), pages 948-962, September.
    8. Bin Zhu & Stephanie A. Watts, 2010. "Visualization of Network Concepts: The Impact of Working Memory Capacity Differences," Information Systems Research, INFORMS, vol. 21(2), pages 327-344, June.
    9. Zhwan M. Khalid & Subhi R.M Zeebaree, 2021. "Big Data Analysis for Data Visualization: A Review," International Journal of Science and Business, IJSAB International, vol. 5(2), pages 64-75.
    10. Pavlos Delias & Vassilios Zoumpoulidis & Ioannis Kazanidis, 2019. "Visualizing and exploring event databases: a methodology to benefit from process analytics," Operational Research, Springer, vol. 19(4), pages 887-908, December.
    11. Matthias Trier, 2008. "Research Note ---Towards Dynamic Visualization for Understanding Evolution of Digital Communication Networks," Information Systems Research, INFORMS, vol. 19(3), pages 335-350, September.
    12. Pinar Keskinocak & Nicos Savva, 2020. "A Review of the Healthcare-Management (Modeling) Literature Published in Manufacturing & Service Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 59-72, January.
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