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Experts versus Novices: Analyzing Behavioral Variability in Complex Process Environments

In: Digital Innovation and Organizational Transformation

Author

Listed:
  • Nico Elbert

    (Julius-Maximilians-Universität Würzburg)

  • Christoph M. Flath

    (Julius-Maximilians-Universität Würzburg)

Abstract

This paper introduces a novel approach to studying user behavior through the User Behavior Mining Framework, analyzing a unique log of 948,251 complex user interaction traces across 78,547 individuals featuring logs of low-level activities in a complex process environment. Employing methods such as directly-follows-graph analysis and trace clustering and next action prediction, the research uncovers the impact of varying experience levels on user interaction patterns and enhances predictive modeling for action forecasting in complex scenarios. This work not only addresses a significant gap in the field by leveraging an underutilized data source but also highlights the importance of rich, detailed datasets for a comprehensive understanding of user behavior and system interaction.

Suggested Citation

  • Nico Elbert & Christoph M. Flath, 2026. "Experts versus Novices: Analyzing Behavioral Variability in Complex Process Environments," Lecture Notes in Information Systems and Organization, in: Christoph M. Flath & Gunther Gust & Frédéric Thiesse & Axel Winkelmann (ed.), Digital Innovation and Organizational Transformation, pages 41-56, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-08483-5_4
    DOI: 10.1007/978-3-032-08483-5_4
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