Towards understanding the process of process modeling: Theoretical and empirical considerations

Pnina Soffer, Maya Kaner, Yair Wand

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


Empirical studies of business process modeling typically aim at understanding factors that can improve model quality. We identify two limitations of such studies. First, the quality dimensions usually addressed are mainly syntactic and pragmatic, not addressing semantic quality sufficiently. Second, while findings related to model understanding have been anchored in cognitive theories, findings related to model construction have remained mostly unexplained. This paper proposes to study the process of process modeling, based on problem solving theories. Specifically, the work takes the approach that problems are first conceptualized as mental models, to which solution methods are applied. The paper suggests that investigating these two phases can help understand and hence improve semantic and syntactic quality of process models. The paper reports on an empirical study addressing the mental model created during process model development, demonstrating the feasibility of such studies. It then suggests designs for other studies that follow this direction.

Original languageEnglish
Title of host publicationBusiness Process Management Workshops - BPM 2011 International Workshops, Revised Selected Papers
PublisherSpringer Verlag
Number of pages13
EditionPART 1
ISBN (Print)9783642281075
StatePublished - 2012
Event9th International Conference on Business Process Management, BPM 2011P - Clermont-Ferrand, France
Duration: 29 Aug 201129 Aug 2011

Publication series

NameLecture Notes in Business Information Processing
NumberPART 1
Volume99 LNBIP
ISSN (Print)1865-1348


Conference9th International Conference on Business Process Management, BPM 2011P


  • Empirical study
  • Problem solving
  • Process modeling

ASJC Scopus subject areas

  • Management Information Systems
  • Control and Systems Engineering
  • Business and International Management
  • Information Systems
  • Modeling and Simulation
  • Information Systems and Management


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