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

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

9 Citations (Scopus)
14 Downloads (Pure)

Abstract

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
Number of pages12
PublisherSpringer
Publication date2020
Pages133-144
ISBN (Print)9783030600723
DOIs
Publication statusPublished - 2020
EventVirtual conference NeuroIS Retreat, 2020 - Vienna, Austria
Duration: 2 Jun 20204 Jun 2020

Conference

ConferenceVirtual conference NeuroIS Retreat, 2020
Country/TerritoryAustria
CityVienna
Period02/06/202004/06/2020
SeriesLecture Notes in Information Systems and Organisation
Volume43
ISSN2195-4968

Bibliographical note

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

Keywords

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

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