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Forecasting Performance of Business Process Modelling Utilizing Causality Information

In: Information Systems and Neuroscience

Author

Listed:
  • Kshitij Sharma

    (Norwegian University of Science and Technology (NTNU))

  • John Krogstie

    (Norwegian University of Science and Technology (NTNU))

Abstract

To be able to have neuro-adaptive tools, it is useful to be able to forecast performance when doing interventions. In this paper we use results from an experiment collecting biometric data from different sensors, capturing EEG, eye-tracking, physiological state and facial expression (through cameras). Earlier work has shown the possibility of using such data in causality-analysis. In this paper we investigate to what extent we can use these results for forecasting the effect of different interventions. The paper shows that the basic forecasting results and the models utilizing causality information are significantly better for forecasting performance than models not being based on the causality information. This increases the possibility of using forecasting in Neuro-adaptive modeling tools.

Suggested Citation

  • Kshitij Sharma & John Krogstie, 2025. "Forecasting Performance of Business Process Modelling Utilizing Causality Information," Lecture Notes in Information Systems and Organization, in: Fred D. Davis & René Riedl & Jan vom Brocke & Pierre-Majorique Léger & Adriane B. Randolph & Gernot (ed.), Information Systems and Neuroscience, pages 169-182, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-00815-2_16
    DOI: 10.1007/978-3-032-00815-2_16
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