The current literature reviews were mostly applied as systematic literature reviews (SLRs), using standard formats such as Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), which is time-consuming, causing their narrow focus. Automated literature reviews (ALRs) using natural language processing, such as word extraction, phrase extraction, and topic mining, overcome the barriers of SLRs [10]. Using ALRs allows the unstructured analysis of research papers, allowing the broad macrolevel analysis, which leads to the extraction of a broad range of topics, thus overcoming the narrow focus of SLRs.The paper uses a systematic and automated literature review to identify key business simulation games research trends, focusing on learning and domain-driven motivations. It reveals that while research in this field has stagnated since the 2000s, there is a balance between learning and domain-driven research, suggesting the technology for these games is mature. The study also analyses the research timeline, main publication venues, citation trends, and frequently used words and phrases. Through the results of this work, higher education institutions can become aware of the areas in which they could use simulation games to make the learning process more interesting and effective for students of Generation Z, who require a different approach to educational methods. In the same way, the results of this research can guide practitioners from the business world to consider their business perspectives in which they could incorporate and apply simulation games to establish higher quality and more efficient firm performance. The paper contains several contributions. Firstly, by combining SLR and ALR, the current study analyses the research on business simulation games to solve the gaps mentioned above and provide a broader perspective on the research trends and perspectives. This paper combines computational and qualitative methodologies to identify significant study themes, examine the temporal trends of these concerns over the past several decades, and suggest possible future pathways for business simulation games research. Secondly, the suggested data analysis framework is flexible and adaptable to various study areas. In addition to combining the SLR and ALR methods, we introduce the concept of the primary motivation in business simulation research, including learningdriven, domain-driven, and technology-driven research. Such an approach can be easily transferred to other educational, business, and management approaches. Thirdly, this paper sheds insight into past and future research on business simulation games by analysing the most significant research trends and themes from 1973 to 2023. The limitations of this work are as follows. First, only papers from the Scopus database were included in the investigation, and other databases should be included in further investigations. Second, text mining has been conducted based on the paper titles, abstracts, and keywords, while the full text of the papers could be included in future work. Future research should explore new technologies like virtual reality, augmented reality, and artificial intelligence to enhance user communication and decision-making complexity in business simulation games.

[1] Ruohomäki, V. Viewpoints on learning and education with simulation games. In Simulation Games and Learning in Production
Management; Springer: Boston, MA, USA, 1994; pp. 13–25.

[2] Léger, P.-M. Using a Simulation Game Approach to Teach ERP Concepts. In HEC Montréal Groupe de Recherche en Systèmes
D’Information; HEC Montréal: Montréal, QC, Canada, 2006; pp. 1–15.