Simulation methods in entrepreneurship research: a systematic review and text mining analysis

Seyed Mohammadreza Ayazi; Seyed Mojtaba Sajadi; Maryam Ghazisaeedi; Danial Esmaeilnezhad; Mohammadreza Taghizadeh-Yazdi

doi:10.1080/17477778.2025.2503869

Simulation methods in entrepreneurship research: a systematic review and text mining analysis

Seyed Mohammadreza Ayazi, Seyed Mojtaba Sajadi^*, Maryam Ghazisaeedi, Danial Esmaeilnezhad, Mohammadreza Taghizadeh-Yazdi

^*Corresponding author for this work

Operations and Service Management

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Abstract

Entrepreneurship, a prolific field of research, is vital for nurturing new ventures, yet comprehending its diverse impacts on enterprises poses a challenge. In this context, the use of simulation methods is innovative to unravel the complex organizational processes affected by entrepreneurship. Therefore, this study aims to investigate simulation approaches in entrepreneurship domains. To achieve this, we combined a systematic literature review (SLR) and a text mining analysis based on Natural Language Processing (NLP). In total, 3527 articles published between 1995 and Jan 2024 in the Clarivate Analytics Web of Science database have been collected; 219 articles were selected for the systematic literature review. A machine learning classification method using Latent Dirichlet Allocation (LDA) determines the optimal number of topics. Thereafter, research methods, fields, themes are extracted and categorized. In addition, this paper highlights the major gaps in this field which shed light on the future research directions. Results indicate that the business field is the most prevalent, and Agent-Based Modeling stands out as the most commonly applied technique.

Original language	English
Number of pages	28
Journal	Journal of Simulation
Early online date	19 May 2025
DOIs	https://doi.org/10.1080/17477778.2025.2503869
Publication status	E-pub ahead of print - 19 May 2025

Bibliographical note

Copyright © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

Keywords

Entrepreneurship
natural language processing (NLP)
simulation methods
systematic literature review (SLR)
text mining
unsupervised learning

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10.1080/17477778.2025.2503869Licence: CC BY 4.0

Simulation methods in entrepreneurship research a systematic review and text mining analysis
Copyright © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
Final published version, 6.39 MBLicence: CC BY 4.0

Cite this

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Simulation methods in entrepreneurship research: a systematic review and text mining analysis

Abstract

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Keywords

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