Simulation and process mining: review and outlook

Abstract Modeling and simulation of business processes have consistently played a pivotal role in science and industry, increasingly benefiting from process mining algorithms that enable the generation of models and parameter extractions. This paper presents a systematic literature review that explores the integration of simulation with process mining techniques, offering a comprehensive overview of contemporary methodologies, applications, and challenges within this interdisciplinary field. Special emphasis is placed on how simulation approaches are employed and enhanced through process mining, revealing opportunities for improved accuracy, scalability, and applicability in complex process environments. First, network analysis enables the identification of underlying patterns and relationships within the research landscape, revealing insights that may not be captured by conventional review methods. Second, a structured literature analysis provides a comprehensive framework that delineates key modeling tasks, categorizes application domains, tools, and validation strategies, and identifies gaps and opportunities at the intersection of simulation and process mining, discussing future advancements in the field.

Authors

Publication Details

Journal
International Journal of Data Science and Analytics
Published
2026-06-16
DOI
https://doi.org/10.1007/s41060-026-01166-x
Primary Topic
Business Process Modeling and Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Simulation and process mining: review and outlook

Emilio Sulis, Laura Genga, Niels Martin
International Journal of Data Science and Analytics
Business Process Modeling and Analysis
article

Simulation and process mining: review and outlook

Emilio Sulis, Laura Genga, Niels Martin
article en

Abstract

Abstract Modeling and simulation of business processes have consistently played a pivotal role in science and industry, increasingly benefiting from process mining algorithms that enable the generation of models and parameter extractions. This paper presents a systematic literature review that explores the integration of simulation with process mining techniques, offering a comprehensive overview of contemporary methodologies, applications, and challenges within this interdisciplinary field. Special emphasis is placed on how simulation approaches are employed and enhanced through process mining, revealing opportunities for improved accuracy, scalability, and applicability in complex process environments. First, network analysis enables the identification of underlying patterns and relationships within the research landscape, revealing insights that may not be captured by conventional review methods. Second, a structured literature analysis provides a comprehensive framework that delineates key modeling tasks, categorizes application domains, tools, and validation strategies, and identifies gaps and opportunities at the intersection of simulation and process mining, discussing future advancements in the field.

International Journal of Data Science and AnalyticsVol. 22(1)
Università degli Studi di Torino
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Business Process Modeling and Analysis
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