Experts versus Novices: Analyzing Behavioral Variability in Complex Process Environments

Nico Elbert () and Christoph M. Flath ()
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Nico Elbert: Julius-Maximilians-Universität Würzburg
Christoph M. Flath: Julius-Maximilians-Universität Würzburg

A chapter in Digital Innovation and Organizational Transformation, 2026, pp 41-56 from Springer

Abstract: 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.

Keywords: User behavior mining; UI logs; Process mining; Data sourcing (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-032-08483-5_4

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DOI: 10.1007/978-3-032-08483-5_4

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