Business Simulation Performance: Who Performs Better?

AN0182506428;jeb01jan.25;2025Jan30.04:07;v2.2.500

Business simulation performance: Who performs better? 

Anecdotal evidence suggests that students with quantitative business majors (e.g., finance, accounting, data analytics, economics) outperform students from less quantitatively rigorous majors (e.g., management, human resource management, marketing) on a business simulation game at a mid-sized, southeastern, public, AACSB accredited university. We tested the veracity of this anecdotal evidence and found a surprising outcome. Major was not the key driver of performance but rather gender drove most of the differentiation in business simulation performance, such that men outperformed women. We discuss the impact of our findings on pedagogy, consider the greater implications for practice, and make recommendations for future research.

Keywords: Gender; simulation; strategic management; simulation performance

Introduction

There has been some interest and research in understanding student performance in business simulations in undergraduate and graduate strategic management capstone classes (e.g., Alstete & Beutell, [1]; Xu & Yang, [31]). The use of business simulations has been shown to aid students in the development of complex mental models (Xu & Yang, [31]). Additionally, the use of business simulations in capstone courses has been demonstrated to be an effective learning tool that aligns with the assurance of learning expectations (Alstete & Beutell, [1]). It was also determined that courses such as financial management and introduction to accounting impacted student learning and success in the simulation (Gresch & Rawls, [12]). Despite these findings, the research has been sparse and faces other limitations. For example, we did not come across many studies focused directly on determining the factors that lead to individual student performance differences in business strategy simulations, as most simulation research studies teams of students and the interplay of the team member characteristics. Casile et al. ([5]) call for research about the performance by gender in simulations to determine if there was a correlation between self-efficacy and performance in a business simulation work; research that we were uniquely positioned to complete since we do not use team-based performance. Simulations are important learning tools due to their ability to push students from consuming class content to actively using it in a low-risk, active learning, experiential activity. Our capstone class is certified as experiential learning by our university which requires the incorporation of Kolb's ([15]) model of abstract conceptualization, active experimentation, concrete experience, and reflective observations based on the simulation. Therefore, studying individual performance differences helps inform our teaching. Understanding student differences allows us to tailor our feedback and instruction better to improve student simulation-related skills such as their decision-making, benchmarking, and analysis of the competitive environment.

The purpose of this study is to examine what factors drive differences in student performance in a business simulation while also expanding the limited research examining these factors to another university to determine if differences among the students do exist. Anecdotally, faculty members who teach the undergraduate final semester senior strategic management capstone course at a mid-size, southeastern, public, AACSB-accredited university suggest that students with more quantitatively oriented business majors perform better than those in less quantitative majors. One study did find quantitative (finance and accounting) majors performed better on a simulation compared to management and marketing majors (Alstete & Beutell, [1]), but there has been scant research in this domain. To add to the limited research in this area, this study examines the role that a student's major plays in success in a business simulation.

To explore the research question of business majors and simulation performance, we conceptualize and develop a hypothesis regarding why quantitative majors lead to greater business simulation performance. We then discuss the methods and results of our findings. The findings of our study provide a surprising outcome: major is not a key factor explaining student performance. Gender plays a far greater role in business simulation performance than does major. Given our surprising findings, we discuss the implications for practice. We also discuss the potential impact of our findings on pedagogy while making recommendations for future research.

Hypothesis development

Employers look for new university graduates who have demonstrated problem-solving, analytic, quantitative, and technical skills, as well as the ability to work in teams and communicate (written and verbal) effectively (DeBevoise, [6]; Koncz & Gray, [16]). As a critical skill for success in the workplace, business school graduates need to be able to scan internal and external organizational environments and discern essential information necessary to make decisions or provide recommendations. Since discernment requires a base knowledge of business disciplines, including accounting, analytics, economics, finance, international business, human resources, management, marketing, and operations, most undergraduate business schools and MBA programs use strategic management as the degree capstone course (Bell et al., [3]). Students need knowledge and experience across the business curriculum in preparation for the interdisciplinary work of strategic decision-making and management. The multi-faceted decision-making process required for strategic management in the real world includes the ability to assess organizational resources, core competencies, and capacities, as well as the external environment.

Various approaches are suggested for engaging upper-level undergraduate students in active learning within strategic management courses, including case studies, simulations, and applied industry assignments. Bell et al. ([3]) advocate advancing strategic management education by emphasizing theories and expanding the curriculum for more ethics, corporate social responsibility (CSR), and multicultural learning. These expansions of traditional strategic management theories help students understand the organizations' social, legal, and economic position (Bell et al., [3]). Within some business simulations, students can make decisions specifically targeted at CSR such as environmental improvements, recycling programs, employee health and benefits packages, and so on. As employers seek employees who can succeed in rapidly changing environments with evolving technology, ambiguity, contradictory information, and/or priorities, all while analyzing complex problems, the strategic management classroom is a perfect lab for students to engage in active learning and application of knowledge in a low stake's environment with faculty support.

One popular mechanism for engaging students in active and experiential learning is a business simulation. Simulations offer students enjoyable and practical gamified experiential learning by making decisions, correcting mistakes, managing their time, and professional role-playing identities (Jennings, [13]; Tao et al., [28]). A simulation is an opportunity for undergraduate business students to integrate and apply all aspects of their business school curriculum. While many US students work (43% full-time and 81% part-time in 2018) or have completed professional internships by the end of their degree program, few have had the real-world experience of making strategic decisions or managing large operations with cross-functional responsibilities (NCES, [20]). Business strategy simulations allow the students to receive fast feedback, require analysis of internal business and external industry-level reports, balance the resource uses of the company, and plan for and react to the competitive environment.

The use of business simulations in a capstone course at the undergraduate level has been demonstrated to yield positive outcomes in student learning, such as improved analytic skills, robust business understanding, and interpersonal skills (Alstete & Beutell, [1]; Faisal et al., [11]; Gresch & Rawls, [12]). However, prior research has been limited in demonstrating the drivers behind the characteristics of those who excel in the simulation. This has led to some discussion among the four faculty members who teach the capstone course at the aforementioned university. We agreed that students from more quantitatively oriented business majors seemed to perform better on the simulation. While this line of thought is anecdotal in nature, we determined it was necessary to research this, as anecdotal evidence can be misleading.

There is some justification for this anecdotal evidence. Alstete and Beutell ([1]) found that a student's major did influence simulation grades. Their findings indicated, for example, that finance students performed better than marketing students. Their results also aligned with Gresch and Rawls' ([12]) study and suggested that their findings "support previous studies reporting that undergraduate courses in financial management and accounting are most useful for successful participation in a simulation game" (p. 422). Gresch and Rawls' (2017) study did not examine majors, as their study was focused on identifying what courses helped with success in the simulation. The limited research has identified that more quantitative students performed well on the simulation. Additionally, quantitative courses (e.g., financial management, introduction to financial accounting) have been identified as being most useful to success in a business simulation (Alstete & Beutell, [1]; Gresch & Rawls, [12]). Given these findings, we hypothesize the following:

Hypothesis 1:

Quantitatively oriented business majors (e.g., finance, economics, data analytics, accounting) will outperform less quantitatively oriented business majors (e.g., marketing, entrepreneurship, human resources, management) on a business simulation.

Methods

The setting for the study was an AACSB-accredited College of Business in a medium-sized public university in the Southeastern United States. All undergraduate students in the College of Business take the Strategic Management capstone course in their final semester before graduation. The course uses the same syllabus, book, final exam, writing assignments, case study, grade rubrics, and simulation across all sections taught by four faculty members. While each of the four full-time, tenured/tenure-track faculty members brings a slightly different research and professional industry perspective to the class lectures, all are mid-career with many years of experience in the classroom, specifically in teaching strategy. The business strategy simulation utilized is the "Business Strategy Game" (BSG), which has students making management decisions about a global athletic shoe company (Thompson et al., [29]). The BSG includes manufacturing, marketing, logistics, financial, CSR, HR, and operations decisions. The students act as CEOs of companies competing in four global regions and in the internet, wholesale, and private label segments (Thompson et al., [29]). To discourage social loafing and ensure that all students actively engage in all aspects of the company operations, they do not work in teams. Instead, as CEO, they individually run their companies over the 7 weekly rounds of decisions, making all company decisions. This approach is also helpful for assurance of learning data gathering at the individual level.

Approximately 95–100% of our students report working while completing their final senior semester concurrent with the class. While we acknowledge that when employed, few students will have full responsibility across all functional areas, during the simulation, we ask them to make these decisions to better understand the balance and tradeoffs that organizations make when implementing strategy. The simulation, making and selling athletic shoes, allows students to engage in areas of business that their major has well prepared them for and in other areas outside of their specialty focus in alignment with the best practices recommended by Salas et al. ([25]) and with experiential pedagogy practices. Students are offered faculty and peer advice each round to assist them in refining their decision inputs based on the competitive and comparative reports in the simulation. Students write three individual papers about the simulation, reflecting on their intended strategy, successes/failures of their strategic implementation/marketing approach, evaluating their financial performance, and reflecting on the overall experience. The industry group of students (normally 5–6 with different majors) also complete an industry overview report and presentation reflecting on the full competitive environment and simulations. In the BSG, an industry grouping indicates the students competing against one another; therefore, 5 or 6 companies/students constitute the entire global market. The simulation is the basis of the overall applied integration and summation of their business college experiences into an applied practice before graduation; the simulation performance score is 10% of the overall semester score, but related coursework including reflections, strategic analysis, financial analysis, and industry analysis represents an additional 45% of the overall grade.

The Institutional Review Board (IRB) approved the study before data collection. Through the university's central Office of Planning, Evaluation, and Institution Research (OPEIR), student information such as grades, gender, age, and transfer status was collected. Data on student performance and time spent in the simulation were collected directly from BSG. To ensure confidentiality, the data set matchings and subsequent de-identification of the combined dataset were performed by the OPEIR office. The data was collected for all Strategic Management classes in the fall 2018 and spring 2019 semesters. This period was chosen due to student and faculty stability. The academic years 2020–2023 were not included to remove the uncertainty related to the COVID-19 period and frequent variations in class modalities. Additionally, the geographic area of the institution was disrupted in the spring of 2020 when the area experienced tornados, which extended the semester unexpectedly. This also coincided with the College of Business being temporarily rehoused due to renovations disrupting faculty and students. There have been no significant changes to the BSG since the time of this study (graphically or functionally); updates have included fiscal rates, such as more current tariff and exchange rate data, which do not fundamentally change the game. There were 286 total students in the sample.

Measures

Dependent variable

The dependent variable for the sample is Performance. The performance for the simulation used was the Overall Game-to-Date score in the final year of the simulation based on the company's Earnings Per Share, Return on Equity, Stock Price, Credit Rating, and Image rating, each weighted at 20%. Each scoring variable was also measured for 'Best in Industry' and 'Meeting Investor Expectations.'

Independent variable

The independent variable for the study is Quant Major. This measure is a dichotomous measure (0, 1), with 1 representing quantitative majors (finance, financial investments, economics, data analytics, and accounting) and 0 for non-quantitative majors (marketing, entrepreneurship, human resources, and management) (Loo, [17]; Pritchard et al., [23]). We recognize that the majors identified as "non-quantitative" utilize quantitative coursework paired with qualitative data. We use these definitions to delimit which students gravitate to the numeric data tables, similar to the BSG data presentations. There were 112 students considered quantitative majors and 174 categorized as non-quantitative majors. None of the students were double majors, and only 3 were minoring in quantitative minors (STEM).

Control variables

The first control variable used is the Core Finance Class Grade. This course is required of all College of Business students and is focused on basic managerial financial skills, including budgeting, break-even analysis, capital management, and financial statement analysis. Since this course covers many of the key elements necessary for understanding the effects of strategic implementation and market results in the simulation, this course was expected to correlate with the game and individual's perception of their math aptitude. Letter grades were converted to numbers, with an A being coded as a 4, a B coded as a 3, a C coded as a 2, a D coded as a 1, and an F as a 0. Students earning below a C in these pre-requisite classes must retake the course, therefore the final, acceptable grade is coded. The next control used was the grade earned in the capstone course (Management Capstone Grade). It was coded similarly to the Core Finance Class Grade. The simulation performance score only accounted for 10% of the course grade. The total time spent in the simulation was coded as Total Time. This captured all time spent within the simulation by the student. Transfer Student is a dichotomous variable that captures whether the student transferred from another institution, with 1 representing that they did transfer and 0 representing that they had not transferred. Years Enrolled captures the length of time the student was enrolled at the university. Gender is a dichotomous measure, with 0 representing male and 1 female. Age is the student's age at the time they were enrolled in the course. Cumulative GPA captures the student's cumulative grade point average (GPA). We also controlled for whether the student had a minor in Presence of Minor.

Results

Table 1 provides information regarding the breakdown of majors in the College of Business for the sample. Table 2 provides the means, standard deviations, and correlations for the variables included in the study.

Table 1. Distribution of majors.

Major	Frequency	Percent
Data analytics	5	1.75
Management	38	13.29
Accounting	52	18.18
Economics	5	1.75
Entrepreneurship	16	5.59
Finance	42	14.69
Financial investments	10	3.50
General management	24	8.39
Human resource management	20	6.99
Marketing	74	25.87
Total	286	100

Table 2. Correlation table.

	Variable	Mean	SD	1	2	3	4	5	6	7	8	9	10	11
1	Performance	75.06	25.52	1
2	Quant major	0.37	0.49	0.06	1
3	Core finance class grade	3.18	0.81	.26**	.25**	1
4	Management capstone grade	3.19	0.79	.38**	0.05	.46**	1
5	Total time	17.23	9.73	.39**	−0.08	.17**	.20**	1
6	Transfer student	0.38	0.49	0.01	−0.03	−.14*	−.12*	−0.03	1
7	Years enrolled	2.65	1.00	−0.07	0.00	0.03	0.04	0.02	−.41**	1
8	Gender	0.49	0.50	−.17**	−.16**	.17**	.14*	0	−0.03	0.03	1
9	Age	22.84	4.28	0.09	0.02	−0.10	−0.07	.17**	.17**	−.20**	−0.06	1
10	Cumulative GPA	3.18	0.49	.23**	.16**	.60**	.60**	.15**	−.14*	−0.04	.26**	−0.10	1
11	Presence of minor	0.09	0.29	−0.05	−.14*	−0.04	0.02	0.02	−0.02	0.11	0.03	−0.06	0.02	1

1 n = 286. **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

To test the main hypothesis, linear regression was used. Multicollinearity was not a concern as no variance inflation factor (VIF) exceeded 2.108, which is far below 10 and would indicate multicollinearity (Tabachnick et al., [27]). Table 3 provides the results of the findings of the linear regression model. Model 1 covers just the control variables, while model 2 contains the independent variable. For model 1, Management Capstone Grade (β = 9.905, p = 0.000), Core Finance Class Grade (β = 3.993, p = 0.048), Total Time (β = 0.794, p = 0.000), and Gender (β = −10.449, p = 0.000) were all significant. When adding the independent variable, those controls remained significant, while Quant Major (β = −0.496, p = 0.861) was not significant, indicating that the hypothesis did not hold up.

Table 3. Regression results.

Variable	β	Sig.	β	Sig.
Constant	25.093	0.058	24.895	0.061
	(13.184)		(13.256)
Management capstone grade	9.905	0.000	9.887	0.000
	(2.067)		(2.073)
Core finance class grade	3.993	0.048	4.074	0.049
	(2.006)		(2.063)
Total time	0.794	0.000	0.791	0.000
	(0.138)		(0.140)
Cumulative GPA	−1.208	0.750	−1.141	0.765
	(3.789)		(3.815)
Presence of minor	−3.666	0.415	−3.757	0.407
	(4.488)		(4.526)
Age	0.230	0.466	0.234	0.460
	(0.315)		(0.316)
Gender	−10.449	0.000	−10.554	0.000
	(2.658)		(2.730)
Transfer student	1.318	0.655	1.328	0.653
	(2.946)		(2.952)
Years enrolled	−1.678	0.245	−1.675	0.247
	(1.441)		(1.443)
Quant major			−0.496	0.861
			(2.840)
F	13.567	< 0.001	12.171	< 0.001
R2	0.307		0.307
N	286		286

Robustness

All the majors were included in the analysis to test the robustness of the results. While multicollinearity is a concern, the highest VIF was 9.227, which is still under the 10 indicating multicollinearity (Tabachnick et al., [27]). In this analysis, the results for the control variables were approximately the same as in models 1 and 2. The only major that indicated any significance was the Economics major (β = 29.189, p = 0.033). As Economic majors represent less than 2% of the total sample (5 students out of 286 total), this finding would not be enough to skew the results.

Post-hoc

Given the findings that Gender was significantly and negatively related to performance on the simulation, indicating that women performed worse on the simulation, we decided to explore if there may be a moderated relationship between Gender and Quant Major. Therefore, we created this moderating variable. The results did not change, and the moderator (gender) was not significant (β = −6.150, p = 0.245).

To further explore the role gender had on the results, we first provided the means on each of the variables based on gender (Table 4). To determine whether the differences between groups were significant, we ran a One-Way ANOVA (Table 5). Performance, Management Capstone Grade, Core Finance Class Grade, Cumulative GPA, and Quant Major all displayed significant differences between male and female students. Male students tended to perform better on the simulation; however, female students exhibited stronger grades in both the Management Capstone and core Finance courses. Women also had higher cumulative GPAs when compared to men. Finally, there was a significant difference found between men and women with regard to being a quantitative major. We have a reasonably equal gender distribution of quantitative majors in the sample (only 4 more males than females).

Table 4. Averages between genders.

Variable		N	Mean	Std. Dev.
Performance	Male	145	79.228	25.533
Female	141	70.773	24.881
Total	286	75.059	25.523
Management capstone grade	Male	145	3.083	0.846
Female	141	3.298	0.715
Total	286	3.189	0.790
Core finance class grade	Male	145	3.048	0.844
Female	141	3.319	0.759
Total	286	3.182	0.813
Total time	Male	145	17.621	9.860
Female	141	16.834	9.605
Total	286	17.233	9.726
Cumulative GPA	Male	145	3.052	0.480
Female	141	3.302	0.464
Total	286	3.175	0.488
Presence of minor	Male	145	0.083	0.276
Female	141	0.099	0.300
Total	286	0.091	0.288
Age	Male	145	23.076	4.062
Female	141	22.603	4.489
Total	286	22.843	4.277
Transfer student	Male	145	0.393	0.490
Female	141	0.369	0.484
Total	286	0.381	0.487
Years enrolled	Male	145	2.628	1.080
Female	141	2.681	0.921
Total	286	2.654	1.003
Quant major	Male	145	0.462	0.500
Female	141	0.319	0.468
Total	286	0.392	0.489

Table 5. One-way ANOVA results.

Variable	Sum of squares	df	Mean square	F	Sig.
Performance	Between groups	5109.762	1	5109.762	8.038	0.005
Within groups	180544.227	284	635.719
Total	185653.990	285
Management capstone grade	Between groups	3.308	1	3.308	5.384	0.021
Within groups	174.496	284	0.614
Total	177.804	285
Core finance class grade	Between groups	5.245	1	5.245	8.127	0.005
Within groups	183.300	284	0.645
Total	188.545	285
Total time	Between groups	44.217	1	44.217	0.467	0.495
Within groups	26916.418	284	94.776
Total	26960.635	285
Cumulative GPA	Between groups	4.470	1	4.470	20.056	0.000
Within groups	63.292	284	0.223
Total	67.762	285
Presence of minor	Between groups	0.020	1	0.020	0.235	0.628
Within groups	23.617	284	0.083
Total	23.636	285
Age	Between groups	15.995	1	15.995	0.874	0.351
Within groups	5197.924	284	18.303
Total	5213.920	285
Transfer student	Between groups	0.042	1	0.042	0.178	0.673
Within groups	67.416	284	0.237
Total	67.458	285
Years enrolled	Between groups	0.203	1	0.203	0.201	0.654
Within groups	286.528	284	1.009
Total	286.731	285
Quant major	Between groups	1.460	1	1.460	6.219	0.013
Within groups	66.680	284	0.235
Total	68.140	285

Discussion

We set out on this study to address the anecdotal perceptions that students in quantitative focused business majors outperformed students in less quantitative focused business majors. The limited research conducted in this area did identify that quantitative courses tended to be more helpful in a business simulation (Gresch & Rawls, [12]), and evidence that quantitative majors performed better (Alstete & Beutell, [1]). The findings of our study did not support our hypothesis. We were surprised that the findings indicated that gender played an important role in determining success in the business simulation. We were not surprised to find that the capstone course grade, the finance course grade, or the total time spent in the simulation were positively correlated with the simulation performance scores. As one would expect, students who spend more time in the simulation or have previously attained higher grades would receive better scores and grades since they are likely to continue leveraging successful study habits into their last semester in college. Upon reflecting on the surprising outcome – that gender matters for simulation performance – we asked students in our strategic management courses why they thought there might be a gendered difference in simulation performance. This finding about gender was concerning to us, since three of the four faculty are female and we struggled with how to explain the results, knowing that we could not alter our pedagogical approach to better teach female students utilizing the simulation if we cannot identify why this difference occurs.

Math anxiety

Female students were more likely to tell us that they were "not very good at math," and thus, they assume that they will do poorly on the simulation. Therefore, math anxiety may be one such topic that could explain this outcome in our study.

Math anxiety in adults is a global issue, with estimates of high math anxiety ranging from 17% of US adults, 18% of UK adolescents, and 30% of adolescents across the 34 OECD countries (Organization for Economic Co-operation and Development) (Luttenberger et al., [18]). Math anxiety has been found to cause not only physiological "fight or flight" reactions but also to impair not only mathematical operations abilities and numerical comprehension but overall cognition, leading to a self-fulfilling prophesy of "I am bad with numbers" that leads to being worse at all numerical comprehension, logic, and learning once they see numbers (Luttenberger et al., [18]). Females report higher math anxiety as young as age 7–8 (Luttenberger et al., [18]). Research has shown that genetic differences explain less than 5% of gendered math anxiety. Instead, the beliefs of parents and elementary teachers, the cultural stereotypes, and educational systems are more significant factors in starting female students to internalize the idea that "girls and women are worse at math," which leads to self-efficacy reduction and ultimately colors what professions and thus educational attainment is possible for these students (Luttenberger et al., [18]).

Competition

Math anxiety alone does not explain this outcome, as the women in the study had better overall GPAs, better grades in the capstone course, and better grades in the introductory finance class, findings consistent with Downey and Vogt Yuan ([7]). In recent research examining simulation performance by teams, Casile et al. ([5]) found that there is a gender difference in self-efficacy with business simulations (females reported less self-efficacy and less enthusiasm). Female students were less enthusiastic about the simulation's competition against others (Casile et al., [5]). This could be an additional explanation for why female students' performance in the simulation was lower than males. Since all our students compete as individuals, female students' dislike of the competition aspects of the simulation may contribute to the gendered differences in performance (Apicella et al., [2]).

Reviewer comments suggested a potential gamer effect explanation for the differences in gender-based competition responses. While it is true that males prefer gamification more than female students, both genders aged 18 to 29 are statistically equally represented in playing video games (53% male; 46% female; 1% other/no response) (Entertainment Software Association, [10]). However, women are far less likely to call themselves "gamers" or to be represented in "e-sports" (Drenten et al., [8]; Rogstad, [24]). Research into e-sports reinforces the idea that these environments are not welcoming to females (or males) who do not match the idealized "masculinity" of the gaming environment and create hostile virtual environments for those who differ from these standards (Rogstad, [24]).

Risk aversion

While the competitive nature of the simulation may contribute to the gender difference in simulation performance, another possible implication is that some level of risk aversion may be at play (Eckel & Grossman, [9]). It has been found that women are more risk averse when facing gambling losses, but not in controlled conditions such as companies, where both men and women make similarly risky decisions (Schubert et al., [26]). This risk aversion may play into the simulation performance such that women are trying to prevent losses, thus making less aggressive changes to their firm that yield fewer performance gains compared to more risky decisions with higher payoffs. Students may equate simulation decisions with gambling, as the game represents fake money and people, where the risks are not real, but students see the grade as a "gamble" if they pursue more risk. If men begin the simulation with more enthusiasm and a greater desire to "win" than women, men may be more likely to try aggressive approaches from the outset of the game (Casile et al., [5]) Further study is needed to understand if this is the case. Also, a greater number of decision rounds may need to be examined to determine whether performance differences disappear over time. Much like the tortoise and the hare, it could be that more years of decision-making in the simulation could erode differences in performance across genders. Studying this outcome could play an important role in helping researchers and practitioners alike understand the gains of having more women in leadership positions. For example, in a meta-analysis examining women on boards of directors, Post and Byron ([22]) found that female representation on boards yielded better accounting returns.

Practical applications

A recent McKinsey study (Kirckovich et al., [14]) found that women moving into management roles is still limited despite more women entering the workforce. Perhaps one reason they are not moving up is because it takes more time for performance outcomes to come to fruition. This is why it is important to further study why performance differs to better understand what is driving the outcomes, especially since the benefits of heterogeneity (notably gender) at the top have been found to be quite positive in past research (e.g., Byron & Post, [4]; Post & Byron, 2015; Wowak et al., [30]). If more time is necessary to see the favorable outcomes on performance, this understanding could yield faster promotion times before the full outcomes are achieved, thus closing the gender divide in top roles. The lack of risk as a female work quality may compound these issues. If, as suggested by Maxfield et al. ([19]), women are making risky management moves but are not normally discussing or labeling these practices, there may also be a gender-related blindness to these actions in female leaders.

With more women graduating from college than men in the United States (National Center for Education Statistics, [21]), it is important for us to better understand how to bridge the gender divide in management roles, especially related to quantitative decision-making. If girls have been told at an early age that they are not good at math, then it is important for adjustments to be made (Luttenberger et al., [18]). One adjustment would be reinforcing that gender does not impact one's ability to learn or understand mathematics. However, as this is a broad sociocultural challenge, it will take time to see the benefits of such an approach.

Since simulations and experiential learning, such as case studies, are common in higher-level business classes, faculty need to understand the implications of using different tools. Simulations provide an important laboratory for students to engage in active experimentation and concrete experience through feedback loops. Since women and men perform differently in the simulation and have different perspectives of their potential for success with these tools, educators need to understand better how and where these simulations are best utilized. Casile et al. ([5]) suggest that the designers of simulations "expand their thinking beyond competition, winning, and profitability and into areas that focus on a larger body of stakeholders, include a strong sense of purpose, reward ethical decision-making, and place higher value on the strengths of female competitors," (page 9) offers one approach to leveling the performance gap. While simulation redesign is a promising approach, and indeed, within the BSG, students are rewarded for CSR-related choices, the truth is that the simulation is a simplified replication of a specific type of business and the competitive environment. One cannot study strategic management without asking the question of why some companies outperform others, most often from the lens and ranking of key performance indicators (KPIs). Competition is a necessary aspect of strategic management and simulations. A different approach is suggested from Kolb's experiential pedagogy model (1984); abstract conceptualization and reflective observations based on the simulation might offer more promise and quicker changes in gender performance gaps. If students engage in the critical examination of real-world companies, especially the competitive factors that help these companies to succeed, both the KPIs and the environmental, social, and governance (ESG)-related metrics, they may be more enthusiastic about competing and may see the value and performance benefits that their simulated companies experience. Another idea when using a simulation in a capstone course may be to change the approach to how the simulation is introduced and taught. For example, it may be beneficial to reinforce the idea that a complex understanding of math is not necessary for success in the simulation and to demonstrate all the instances in which the simulation automatically handles the calculations. This would likely benefit all students who have struggled mathematically, which in turn hampers cognition and logic. Therefore, future research should explore the impact this may have on the simulation performance.

These findings do have their limitations. We can only hypothesize why female students do better overall in the classes (finance and strategic management) while scoring lower on the simulation. The findings in Table 4 are limited as well since the game does not distinguish time actively making decisions and engaging with the reports from time spent with the windows open but not engaged. We are thus unable to determine if the time in the game is a finding between the genders (males spend more time in the game and thus score better) or simply noise, lending itself to be explored in a future study. Generalizability continues to be challenging as this study was done at a single institution. However, Alstete and Beutell ([1]) did find that gender did not play a role in business simulation performance and examined this relationship at a single private university. Given the difference in our findings that gender has on simulation performance, we suggest further research is needed at other universities across the United States and globally.

Conclusion

We explored whether students in more quantitatively oriented business majors (e.g., Finance, Accounting, Data Analytics, Economics) performed better on the Business Simulation Game in the Strategic Management capstone course than those that tend to be less quantitatively oriented (e.g., Management, Marketing, Human Resources, Entrepreneurship). The results of our study identified that women performed worse in the simulation. Further exploration of the data found that women had better grades in the introductory finance class and the overall grade for the capstone course while also having a higher overall GPA. Given this finding, we recommend that future research explore the effect more decision rounds in the simulation may have on performance and also study some different pedagogical approaches to determine if they change the outcomes of the simulation.

By Frank C. Butler; Deborah M. Mullen and Kathleen K. Wheatley

Reported by Author; Author; Author