The Impact of Modularization on the Understandability of Declarative Process Models: A Research Model

Amine Abbad Andaloussi, Pnina Soffer, Tijs Slaats, Andrea Burattin, Barbara Weber

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Process models provide a blueprint for process execution and an indispensable tool for process management. Bearing in mind their trending use for requirement elicitation, communication and improvement of business processes, the need for understandable process models becomes a must. In this paper, we propose a research model to investigate the impact of modularization on the understandability of declarative process models. We design a controlled experiment supported by eye-tracking, electroencephalography (EEG) and galvanic skin response (GSR) to appraise the understandability of hierarchical process models through measures such as comprehension accuracy, response time, attention, cognitive load and cognitive integration.

Original languageEnglish
Title of host publicationInformation Systems and Neuroscience - NeuroIS Retreat 2020
EditorsFred D. Davis, René Riedl, Jan vom Brocke, Pierre-Majorique Léger, Adriane B. Randolph, Thomas Fischer
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages12
ISBN (Print)9783030600723
StatePublished - 2020
EventVirtual conference NeuroIS Retreat, 2020 - Vienna, Austria
Duration: 2 Jun 20204 Jun 2020

Publication series

NameLecture Notes in Information Systems and Organisation
ISSN (Print)2195-4968
ISSN (Electronic)2195-4976


ConferenceVirtual conference NeuroIS Retreat, 2020

Bibliographical note

Publisher Copyright:
© 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.


  • DCR graphs
  • Declarative process models
  • Modularization
  • Neurophysiological experiment
  • Understandability

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Computer Science Applications
  • Information Systems and Management
  • Management of Technology and Innovation


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