Keywords

1 Introduction

A considerable share of the scholarly discourse in the entrepreneurship education (EE) field is centered around the questions of whether entrepreneurship can be taught and what its effects are. Finding answers to these questions is important as it determines considerably if downstream research in EE is worth the effort. Today, substantial empirical evidence exists; e.g., the large-scale GUESS (Global University Entrepreneurial Spirit Students’ Survey) study (Bergmann, 2014) shows that EE in higher education has positive impacts, especially in fostering an institution-wide entrepreneurial culture. But some skepticism about the teachability of EE remains (Rideout & Gray, 2013), which might predominantly stem from unreasonably high expectations about the direct effect of EE on start-up activity (Schultz, 2020). To presume that the majority or even a considerable proportion of participants will become entrepreneurs just overcharges the influence of EE. To put it bluntly, not everybody who learns to read will write a book and not everybody who writes a book will publish a bestseller or win a Nobel prize.

To measure success and quality in EE is even more difficult when we consider that the entrepreneurial process is unpredictable and entrepreneurial success depends on many external factors and the “right” mixture of resources. As a result, it remains impossible to provide narrow blueprints for entrepreneurial success through EE (Fayolle, 2008). Consequently, there are elements of entrepreneurship that are rather teachable, such as the functional skills for managing a business or the formal evaluation of opportunities, and there are unteachable parts as the ability to create opportunities (Saks & Gaglio, 2002).

Critics shall also have in mind that the mission of university-based EE is not solely to foster regional start-up activity. First, EE shall develop functional management skills and abilities among students to help them start and manage businesses (Gibb & Nelson, 1996). Second, EE shall encourage students to start businesses (Hills, 1988) and finally EE shall raise the number of start-ups in the region (Liñán, 2004). This study gives recommendations to practitioners to improve the performance of its students in a business plan teaching format to serve the first mission of EE properly. Although scholars regularly call for more innovative ways of teaching entrepreneurship, the rather classical business plan course (“How to write a business plan?”) is still a popular element of EE curricula worldwide. When active teaching elements, e.g., group work, play an integral part in the course’s pedagogical approach, the student team’s composition might impact performance. This study analyzes the effect of gender team composition on different performance measurements. The research guiding question of this study is, what impact does gender team diversity have in EE? Practitioners profit from the results by gaining insights into how a student team performs characteristically and how to optimize team composition for better performance. Students get clues on how they can improve their performance in team settings in EE.

2 Theoretical Background

In this section, we categorize the business plan teaching format in EE from a pedagogical perspective and outline results on the role of gender team diversity in EE. The section concludes with three hypotheses.

2.1 The Business Plan Course Format in Entrepreneurship Education

A state-of-the-art integrated teaching model framework to categorize teaching formats in EE (Nabi et al., 2017) consists of three primary or archetypical teaching models:

  • Supply model: focus is on reproduction methods (lectures, reading, watching/listening).

  • Demand model: focus is on personalized participative methods (interactive searches, simulations).

  • Competence model: focus is on communication, discussion, and production.

It also consists of two hybrid models:

  • Supply–demand model: mixture of supply and demand model formats.

  • Demand–competence model: mixture of demand and competence model formats.

Some researchers use a simpler typology when they differentiate between reflective (rather passive consumption of knowledge) and active (active production of knowledge) pedagogical methods in EE as dichotomous categories (Walter & Dohse, 2012).

In practice, depending on the pedagogical elements, a business plan teaching format can either represent a supply model (passive course), when the focus is on lectures, or a supply–demand model course (active course), when many active teaching elements are integrated. The business plan as a didactic approach in EE has been criticized for various reasons. Exemplary is this quote: “(the) business planning process is an attractive and powerful learning process,” where “a disproportionate amount of time is spent honing secondary research skills than actually taking smart action in the real world.” (Neck & Greene, 2011). The authors contrast this approach with their own entrepreneurship as a method teaching framework, where educators shall focus on providing methodological approaches that enable students to cope with dynamic environments. Besides the potential waste of limited teaching and learning time that could be spent on more important areas of the entrepreneurial process, there are additional arguments for not using business planning in EE. Experienced venture capitalists and business angels oftentimes don’t care for lofty planning documents in their investment decision but rather focus on the entrepreneurial team or the venture’s business potential (Kirsch et al., 2009). Consequently, teaching formats shall focus on the more relevant investment criteria.

But does that mean that business plan courses are useless first from a pedagogical and second from a practical standpoint? It is important to note that critics normally don’t argue that the business plan format is missing positive pedagogic effects. They rather claim that other teaching formats are more effective. As the EE field evolved, practitioners do not only have a larger choice of impactful teaching formats, but they also know a lot more about their potential effects. Therefore, practitioners are able to enrich the classical business plan format with elements of active teaching elements, e.g., design thinking or small group work. From a pedagogical point of view, a reflective oriented business plan has some shortcomings but active teaching elements may at least partially offset pedagogical shortcomings to develop a course of “How to write a business plan?” toward an active or supply–demand (hybrid) course. Another argument in favor of the business plan in an EE curriculum is that a hybrid business model course attracts mainly students with a low intention to start a business, the so-called “magnet effect.” The “pedagogy effect” of a business plan course is that the intention to start a company increases for the lion’s share of students. So, the outcome of a business plan course can be substantial and fulfills the goal of EE to raise entrepreneurial intention rather efficiently as those courses can address a higher volume of students than comparably smaller active courses, e.g., lean start-up camps that require a vast amount of staff resources (Schultz, 2021).

2.2 Gender Diversity in Teams

In a first step, practitioners need to be aware of the different performance characteristics of course formats in order to strategically plan an EE curriculum that meets all targets of EE sufficiently. In a second step, they can take operative measures to further enhance the performance of each course regarding the students’ learning success and overall learning experience. From a practitioner’s point of view, an area of potential improvement is the team’s composition, which leads to the question, what are the best-performing teams? A team is a “set of two or more people who interact dynamically, interdependently, and adaptively toward a common and valued goal/objective/mission, who have each been assigned specific roles or functions to perform, and who have a limited life-span of membership.” (Salas et al., 1992).

Team diversity has been investigated in different contexts from management teams (Ensley & Hmieleski, 2005), entrepreneurial teams (Chowdhury, 2005), or student teams in EE (Hoogendoorn et al., 2013). The literature differentiates between two areas of diversity, first task-related (skills, work experience, academic background) and second biodemographic diversity (gender, age, ethnicity). Same-gender teams are an expression of homophily, which is the individual tendency to associate with other individuals that resemble yourself in different aspects. Homophily can circumvent areas from ethnicity, age, and gender to education or religion. The probability of forming a homophile entrepreneurial team regarding gender is higher than in random matching (Ruef et al., 2004). But the results on the relationship of team diversity and performance are far from homogeneous and need to be discussed in its empirical context. In a meta-analysis of 35 articles, the authors find indicators of a positive relationship of task-related diversity and no significant relationship between biodemographic diversity and team performance (Horwitz & Horwitz, 2007). In a meta-analysis of 92 sources, gender team diversity has small negative effects on team performance, while age differences are not significant (Bell et al., 2011). Diversity affects different conflict categories and increases the potential for conflict (Pelled et al., 1999). In some cases, dissimilar belief systems of team members that surface in different team processes might lead to conflict and negative performance effects (De Wit et al., 2012).

In a study in the entrepreneurship field based on 79 interviews, demographic (gender, age) or background diversity aspects are not important for the entrepreneurial team’s effectiveness (Chowdhury, 2005). Other researchers even state that the approach to take demographic factors such as gender, age, or ethnic groups as predictors of entrepreneurial behavior is conceptually unsound (Liñán & Santos, 2007; Der Foo et al., 2005).

2.3 Hypotheses

While there are strong arguments and some empirical evidence that homophile teams perform inferior to diverse teams, the empirical results in the EE context are heterogeneous. In a group of Harvard students, homogeneity in ethnicity increases team performance (Gompers et al., 2017). But it only raises low-performance teams to a median performance level. Other factors, e.g., gender, education, or past work experience, are not significant determining factors. Gender diversity of student teams in an entrepreneurship program in the Netherlands has positive effects on their performance (Hoogendoorn et al., 2013). The teams are randomly assigned to avoid self-selection bias. The specific teaching context is not business planning but managing a micro company as a team that is supposed to be economically active for at least 1 year. The main result is that teams with an equal gender mix perform better than male-dominated teams in terms of sales and profits. Although the authors analyze multifaceted data, e.g., the team’s characteristics (age, atmosphere), individual personality traits (big five inventory; agreeableness, conscientiousness, extroversion, neuroticism, openness to experience), and team processes (group potency, decision-making, mutual monitoring, coordination, credibility, specialization), they don’t find any explanation for their findings. The resulting hypotheses are the following:

  • Hypothesis 1: A student team’s gender composition influences the performance in writing a business plan in an active EE course.

  • Hypothesis 2: Mixed-gender teams perform comparatively better in developing a business plan than homophile gender teams in an active EE course.

Although the notion that entrepreneurial intention is, on average, higher among men than women (Scherer et al., 1990; Zhao et al., 2005) is debated (Maes et al., 2014), a more recent study (Do Paço et al., 2015) shows that, even in the absence of access to EE, men possess a higher entrepreneurial intention than women. When men are more interested in entrepreneurial activity, it is logically consistent to expect that men will make a greater effort to outline their business ideas, which could result in a comparable higher performance. Against this logical conclusion stands the empirical finding that male-dominated teams underperform in sales and profits in an EE management game (Hoogendoorn et al., 2013). But in the context of a business plan course, men might perform differently. The derived hypothesis is the following:

  • Hypothesis 3: Men’s teams perform better than women’s teams in writing a business plan in an active EE course.

3 Methodology

This section depicts the empirical approach to test the proposed three hypotheses (see Table 1). Many studies in EE do not sufficiently describe the pedagogical approach of the research setting. But a comprehensive description is essential for other researchers to appraise the results adequately. Therefore, this study describes the sample and its context extensively.

Table 1 Description of variables
Full size table

3.1 Sample

The data stem from an “Entrepreneurship and Business Planning” course in a bachelor’s degree program in business administration at a medium-sized university in Germany, specifically from two winter terms in the years 2014 and 2015. The participants are bachelor students in their fifth semester. During the semester, student teams work on a business plan for a start-up idea they develop on their own under the guidance of the teaching personnel. Because more than two students work toward the common goal of developing a business plan during one semester, this organizational mode qualifies as a team. Students receive a grade on their business plan and a written exam at the end of the semester on basic topics of entrepreneurship. Students attend lectures by faculty members and guest speakers on different business plan components. To enhance the inclusion of the market perspective, it is obligatory that every team participates in a state-wide external business plan competition. As a result, students receive not only feedback from faculty members but also from external jurors on the different stages of their business plans. The course starts with an introduction to entrepreneurship and business idea generation followed by a “Market of Ideas,” where every team presents its idea poster of a potential business to fellow students and faculty members. One week in advance, all teams upload and share their digital idea posters on the “Idea Generator.” Through this platform, every course participant and the teaching staff can comment and give feedback publicly to enhance the business idea. The idea posters were accessible until the end of the semester to all participants to gather feedback and comments throughout the semester. Normally, students revise their business ideas based on early feedback before they enter the writing process of their business plans. In addition, every team needs to attend three peer review sessions with an exclusive focus on the proper development of their business plan. Faculty members supervise these sessions and provide every team with the possibility to present their development stage to their peers and experts in the field.

The sample stems from this course which fulfills the criteria of a supply–demand (hybrid) course (Nabi et al., 2017) or active course (Walter & Dohse, 2012), where traditional teaching components (e.g., lectures) are enriched with active teaching elements. In this business plan course, those active teaching elements included small group work, creativity exercises, the introduction of role models, student-oriented teaching, and feedback processes within the business planning process. As the active teaching elements were a substantial and integral part of the overall pedagogy, this course qualifies clearly as a supply–demand (hybrid) or active course.

3.2 Variables

In this study, team performance in developing a business plan is first measured by the received grade on the business plan and second by the views the idea posters generated on the digital idea platform (see Table 1). To define the grade as a performance indicator is straightforward in a course of higher education. Professional teaching staff scored every business plan on ten categories to determine the final business plan grade. Views are a valid performance indicator as comparable; more views show that the business idea is assessed as more interesting. Although skeptics can make the case that very bad as well as good business ideas attract attention, the practical experience is that the above average business ideas receive more attention as participants don’t put effort into looking at low-quality ideas. This study uses team size as a control variable as larger (or smaller) teams might have a significant advantage (disadvantage). Additionally, the specific semester is a control variable as different teaching styles by lecturers and faculty in general might affect the teams’ effectiveness.

3.3 Results

A total of 345 students (women: 180, men: 165) participated in two courses. The distributions of gender and teams per semester show no obvious distortions (see Table 2). 31 single female and male students are excluded from the study as the focus is on team performance.

Table 2 Teams in the sample
Full size table

The lion’s share of team size is three students, but there are some teams who are larger or smaller due to personnel preference.

Table 3 presents the grade performances of the different team categories in developing a business plan and in the written exam on entrepreneurship topics at the end of each semester and views of the business idea poster on the dedicated digital platform. On average, students perform better in business planning than in the written exam. The platform’s backend counted a total volume of 3.673 views in semester A and 3.837 in semester B. As semester B had fewer participants and teams, a higher view count suggests that the platform gained in user acceptance. Furthermore, 90% of the business idea posters in the sample received 134 or less views. Above this threshold, mixed teams are dominant. This study uses a simple linear regression to analyze the effect of team composition on the performance indicators team grade for a business plan and views of the business idea posters on the digital idea generator platform. Team categories are entered as dummy variables into the regression model. To avoid multicollinearity between the independent variables, one out of the three categorical variables in each calculated linear regression model is dropped. This procedure results in three models for each of the two dependent variables for a total of six regression models (see Table 4).

Table 3 Descriptive statistics on grades (business plan, entrepreneurship exam) and views of the business idea poster on the digital idea platform per team in semester A and semester B
Full size table
Table 4 Parameter estimates of six linear regression models
Full size table

The variance inflation factor (VIF) as an indicator for multicollinearity lies under the critical value of 4 in every model. The Durbin–Watson statistic as a test for autocorrelation in the residuals doesn’t reach worrying values of under 1 or more than 3. There is no indication that multicollinearity and autocorrelation distort the regressions’ results. The corrected r2 shows how well the model fits the linear regression models and indicates the percentage of the variance in the dependent variable that the independent variables explain collectively. As corrected r2 doesn’t exceed 0.086, there are probably variables in the model missing that would raise the models’ fit. The first model shows that affiliation with a mixed or women’s team improves the average grade for a business plan significantly. The beta coefficient is negative as a smaller number indicates a better grade. Models 2 and 3 show that men’s teams perform, on average, significantly worse in business planning. Models 4 and 5 show that affiliation to a mixed team results, on average, in a significantly positive effect on views on the digital idea generator platform. Model 6 shows that affiliation to a women’s or men’s team has, on average, a significant negative effect on the number of views. The dummy variable semester serves as a control variable and is significant in models 4–6. A plausible explanation for this effect is that in semester B the students accepted the idea generator platform as a viable feedback instrument and were more active in giving feedback and viewing their peer’s idea posters. The descriptive statistics on views support this argument.

Table 5 gives an overview of whether the hypotheses are confirmed or rejected.

Table 5 Overview of hypotheses and results
Full size table

4 Conclusion 

This study shows that in the specific context of a business plan course in EE non-task-related team diversity has effects on different performance indicators. Gender-mixed teams write better business plans and generate more interest in their start-up idea.

These results are contrary to research that only finds performance effects for task-related areas (Der Foo et al., 2005). Whether the effects disappear when task-related diversity aspects are considered cannot be determined with the available data. But it is highly questionable to what extent bachelor students of the same semester in the same educational program at the same university can differ considerably regarding typical task-related indicators such as work experience or competencies. Some studies offer different approaches to explain gender-specific diversity performance differences ranging from individual personality traits to team processes and didn’t find any explanation for their findings (Hoogendoorn et al., 2013).

The question that remains is, why are mixed teams more successful in a business plan course? The answer may lie in the distinct task requirements. To develop a business idea from scratch is a creative task, where especially homophile men’s teams are seemingly less effective. This might be due to less creative ability or an unfavorable team dynamic. That the worse performance is due to less motivation is rather unlikely considering that the men’s entrepreneurship exam grades don’t differ significantly from those of women. That diverse teams oftentimes possess advantages in creativity is underscored by a large meta-analysis (Horwitz & Horwitz, 2007). Each gender may contribute characteristic competencies that complete the team’s competence portfolio, e.g., in regard to the quality of creative output and the integration of different perspectives. To find out what these competencies are, how they are characteristically bound to gender and how they interact in an EE context are promising research endeavors. For lecturers, these results are an impulse to pay more attention to gender composition in teamwork assignments and to point out to students that mixed-gender teams perform on average best in the business plan EE context. In particular, male students should take this recommendation to heart, as they profit considerably from teaming up with women.

Critics may argue that this finding is of little relevance as a business plan course is still about planning and doesn’t provoke entrepreneurial action in real life. While this course type has its inherent limitations in enhancing the student’s entrepreneurial intentions and initiating entrepreneurial activity, recent empirical research shows that a supply–demand business plan course can contribute to a rise in the student’s entrepreneurial intention and entrepreneurial activity (Schultz, 2021).

There are two main reasons for the mixed empirical results in the literature on gender diversity in different educational settings: first, inconsistencies in the research design and second, the influence of contextual factors. In regard to the first argument, a potential shortcoming of this study is that students self-selected into teams and that therefore the low and high performers were free to conglomerate. In this study, the results of linear regression models with the dependent variable entrepreneurship exam grade show no significant results that team affiliation has a significant effect on exam performance. When team affiliation is independent of exam performance, there is less indication that high or low performers selected themselves in characteristic teams. Furthermore, to criticize self-selection is valid from a strictly theoretical perspective, but it is out of touch with reality. Normally, entrepreneurial teams as well as student teams don’t form by chance under controlled conditions. They form by choice, which makes self-selection rather a property of real life and in EE a part of the learning experience. In regard to the second point of critique, it seems evident that contextual factors ranging from educational settings (e.g., course type, EE pedagogy) to culture possess influence. As a business plan course is part of the EE curriculum at many higher learning institutions, opportunities exist to replicate this study on a larger scale. Then, it might become possible to explore the effects that lead to team performance differences in detail.