Analyzing the intellectual structure of research on simulation-based learning in management education, 1960–2019: A bibliometric review
Introduction
Over the past six decades, management educators have experimented with various approaches to active learning in an effort to find ways of making academic content more meaningful and applicable for students in universities and professional settings (Cohen & Rhenman, 1961; Faria, 1987; Faria & Wellington, 2004; Walker, Bridges, & Chan, 1996). Concurrently, the need to identify and refine active learning methods that engage students and foster the retention and transfer of learning has led to an explosion of empirical research (Ampountolas, Shaw, & James, 2019; Felder & Brent, 2009; Martin, Kolomitro, & Lam, 2014; Steadman et al., 2006). This same trend is evident among scholars who have studied the use of simulations and serious games in management education (Asiri, Greasley, & Bocij, 2017; Salas, Wildman, & Piccolo, 2009). Reviews of this research find that simulations and serious games have become a signature feature of management education and training programs (Faria, Hutchinson, Wellington, & Gold, 2009; Keys & Wolfe, 1990; Salas & Kozlowski, 2010).
This systematic review of research used science mapping to extend findings from prior reviews of research in this domain (e.g., (Anderson & Lawton, 2009; Bell, Kanar, & Kozlowski, 2008; Crookall, 2010, 2012; Faria & Wellington, 2004, 2001; Keys & Wolfe, 1990). More specifically, this review sought to document and analyze trends in knowledge production on simulation-based learning in management education. Three research questions guided the review.
- 1.
What general trends describe the evolution of scholarship published on simulation-based learning in management education between 1960 and 2019?
- 2.
What is the intellectual structure of the knowledge base on simulation-based learning in management education?
- 3.
What research topics have gained the attention of scholars studying simulation-based learning in management education?
The authors analyzed 1200 Scopus-indexed documents on the use of simulations and games in management education using descriptive statistics, co-citation analysis, and keyword analysis (Bragge, Thavikulwat, & Töyli, 2010; Zupic & Čater, 2015). The authors draw on these findings to chart future directions in research in this field. Subsequent sections provide a conceptual overview of this domain, describe the review procedures, present results, and discuss the findings of the review.
Section snippets
Conceptual background
Scholarship on the use of simulations and games in management education has a rich history dating back more than a century (Faria, 1987 ;Faria & Wellington, 2004). There is broad agreement that simulations and serious games provide an engaging mode of learning that enables students to develop a deeper understanding of how to apply management theory, enhanced capacity for performing management tasks, and the kind of action-oriented thinking needed by managers in the workplace (Anderson & Lawton,
Method
This review of research used bibliometric methods to analyze the knowledge base on simulation-based learning in management education (SBL-ManEd). In contrast with traditional literature reviews, bibliometric reviews do not focus explicitly on the ‘findings’ in a body of literature. Instead, they analyze bibliographic data associated with documents stored in document repositories such as the Web of Science, Clarivate, or Scopus. As Bragge et al. (2010) observed, “[B]ibliometric approaches can
Results
The findings are presented in the order of the three research questions outlined at the beginning of the paper.
Discussion
This review of research used science mapping to document the evolution of knowledge production on the use of simulations and serious games in management education over the past six decades. In this section, we highlight limitations of the review and discuss our interpretation of key findings and their implications for research and practice.
Credit author statement
The lead author was responsible for checking the dataset, data analysis, and writing the manuscript. The second author was responsible for conceptualizing the paper, data collection, portions of data analysis and writing selected sections of the paper.
Declaration of competing interest
None.
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