Understanding quality in declarative process modeling through the mental models of experts

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    Accepted author manuscript, 916 KB, PDF document

  • Amine Abbad Andaloussi
  • Christopher J. Davis
  • Andrea Burattin
  • Hugo A. López
  • Slaats, Tijs
  • Barbara Weber

Imperative process models have become immensely popular. However, their use is usually limited to rigid and repetitive processes. Considering the inherent flexibility in most processes in the real-world and the increased need for managing knowledge-intensive processes, the adoption of declarative languages becomes more pertinent than ever. While the quality of imperative models has been extensively investigated in the literature, little is known about the dimensions affecting the quality of declarative models. This work takes an advanced stride to investigate the quality of declarative models. Following the theory of Personal Construct Psychology (PCT), our research introduces a novel method within the Business Process Management (BPM) field to explore quality in the eyes of expert modelers. The findings of this work summarize the dimensions defining the quality of declarative models. The outcome shows the potential of PCT as a basis to discover quality dimensions and advances our understanding of quality in declarative process models.

Original languageEnglish
Title of host publicationBusiness Process Management : 18th International Conference, BPM 2020, Seville, Spain, September 13–18, 2020, Proceedings
Number of pages18
PublisherSpringer
Publication date2020
Pages417-434
ISBN (Print)978-3-030-58665-2
ISBN (Electronic)978-3-030-58666-9
DOIs
Publication statusPublished - 2020
Event18th International Conference on Business Process Management, BPM 2020 - Seville, Spain
Duration: 13 Sep 202018 Sep 2020

Conference

Conference18th International Conference on Business Process Management, BPM 2020
LandSpain
BySeville
Periode13/09/202018/09/2020
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12168
ISSN0302-9743

    Research areas

  • Declarative process models, Model quality, Personal construct psychology, Process model understandability, Repertory Grid

ID: 250812501