The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Business Process Modeling- A Comparative Analysis
Abstract
Many business process modeling techniques have been proposed over the last decades, creating a demand for theory to assist in the comparison and evaluation of these techniques. A widely established way of determining the effectiveness and efficiency of modeling techniques is by way of representational analysis. This paper comparatively assesses representational analyses of 12 popular process modeling techniques in order to provide insights into the extent to which they differ from each other. We discuss several implications of our findings. Our analysis uncovers and explores representational root causes for a number of shortcomings that remain in process modeling practice, such as lack of process decomposition and integration of business rule specification. Our findings also serve as motivation and input to future research in areas such as context-aware business process design and conventions management.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Moore, G. C., & Benbasat, I. (1991) · Information Systems Research · doi:10.1287/isre.2.3.192 · Cited by 9,150
Design science in information systems research
(2004) · Journal of the Association for Information Systems · doi:10.5555/2017212.2017217 · Cited by 8,254
Cited by
Globocnik, D., Faullant, R., & Parastuty, Z. (2020) · European Management Journal · doi:10.1016/j.emj.2019.08.005 · Cited by 79
Metadata
- Authors
- Queensland University of Technology, Recker, J., Rosemann, M., Queensland University of Technology, Indulska, M., The University of Queensland, Green, P., & The University of Queensland
- Venue
- Journal of the Association for Information Systems
- Publisher
- Association for Information Systems
- Published
- 2009-04
- Volume
- 10
- Issue
- 04
- Pages
- 333-363
- ISSN
- 1536-9323 (ISSN-L)
- OpenAlex
- W1487002026
- Cited by
- 361
- References
- 2
- FWCI
- 71.50
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Business Process Modeling- A Comparative Analysis. https://app.cochat.ai/papers/10.17705/1jais.00193
- The paper
- Queensland University of Technology, Recker, J., Rosemann, M., Queensland University of Technology, Indulska, M., The University of Queensland, Green, P., & The University of Queensland. (2009). Business Process Modeling- A Comparative Analysis. Journal of the Association for Information Systems. https://doi.org/10.17705/1jais.00193
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
