Understanding Quality in Declarative Process Modeling Through the Mental Models of Experts
Series
Lecture Notes in Computer Science
Type
conference paper
Date Issued
2020
Author(s)
Andaloussi, Amine Abbad
;
Davis, Christopher John
;
Burattin, Andrea
;
Hugo-andrés López
;
Slaats, Tijs
;
Abstract (De)
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.
Language
English
HSG Classification
contribution to scientific community
Publisher
Springer
Volume
12168
Start page
417
End page
434
Event Title
Business Process Management - 18th International Conference, BPM 2020, Seville, Spain, September 13-18, 2020, Proceedings
Official URL
Subject(s)
Eprints ID
261021