Business process and rule integration approaches—An empirical analysis of model understanding

Item Type Journal paper
Abstract

Business process models are widely used in organizations by information systems analysts to represent complex business requirements. They are also used by business users to understand business operations and constraints. This understanding is extracted from graphical process models as well as business rules. Prior research advocated integrating business rules and business process models to improve the effectiveness of various organizational activities, such as developing a shared understanding of practices, process improvement, and mitigating risks of compliance and policy breaches. However, whether such integrated modeling can improve the understanding of business processes, which is a fundamental benefit of integrated modeling, has not been empirically evaluated. In this paper, first, we report on an experiment investigating whether rule linking, a representative integrated modeling method, can improve understanding performance. We use eye tracking technology to understand the cognitive process by which model readers use models to perform understanding tasks. Our results show that rule linking outperforms separated modeling in terms of understanding effectiveness, efficiency, perceived mental effort, and visual attention. Further, cognitive process analysis reveals that the form of rule representation does not affect the extent of deep processing, but rule linking significantly decreases the occurrence of rule scanning and screening processes. Moreover, our results show that rule linking leads to an increase of visual association suggesting improved information integration, leading to improved task performance.

Authors Wang, Wei; Chen, Tianwa; Indulska, Marta; Sadiq, Shazia & Weber, Barbara
Journal or Publication Title Information Systems
Language English
Keywords Business process modeling, Business rule modeling, Eye-tracking, Cognitive process, Model understanding, Controlled experiment
Subjects computer science
HSG Classification contribution to scientific community
HSG Profile Area None
Refereed Yes
Date 2022
Publisher Elsevier
Volume 104
Page Range 101901
Official URL https://www.sciencedirect.com/science/article/pii/...
Depositing User Prof. Dr. Barbara Weber
Date Deposited 27 Oct 2021 11:40
Last Modified 27 Oct 2021 11:40
URI: https://www.alexandria.unisg.ch/publications/264691

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Citation

Wang, Wei; Chen, Tianwa; Indulska, Marta; Sadiq, Shazia & Weber, Barbara (2022) Business process and rule integration approaches—An empirical analysis of model understanding. Information Systems, 104 101901.

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https://www.alexandria.unisg.ch/id/eprint/264691
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