Master Thesis
MSc Entrepreneurship
BUSINESS INCUBATORS AND THEIR
EFFECT ON ENTREPRENEURIAL
COMPETENCES
MSc Entrepreneurship
Master Thesis
Author
Alexander Sprey
UvA: 11664762
VU: 2628296
Supervisor
Prof. Dr. Enno Masurel
Application Date
April 1st, 2018
Submission Date
June 23rd, 2018
Word count
13.569
r Thesis
MSc Entrepreneurship
Table of contents
List of figures ... II
List of tables ... III
Preface ... IV
Abstract ... V
1 Introduction ... 1
2 Incubators ... 4
2.1 Incubator Elements ... 4
2.2 Distinction Between Incubators and Accelerators ... 6
2.3 Incubator Heterogeneity ... 7
2.4 Incubator Performance Measures ... 9
3 Entrepreneurial Competences ... 13 3.1 Proactiveness ... 15 3.2 Perseverance ... 15 3.3 Networking ... 16 3.4 Flexibility ... 17 3.5 Self-efficacy ... 17 3.6 Risk-taking ... 18 4 Hypotheses ... 20 5 Methodology ... 24 6 Results ... 29 7 Discussion ... 33 8 Conclusion ... 38 References ... 40 Appendices ... 45
List of figures
Figure 1:
List of tables
Table 1:
Differences Between Incubators and Accelerators ... 7
Table 2:
Incubator Classification by Author ... 8
Table 3:
Incubator Performance Measurements Used in the Academic Literature ... 10
Table 4:
The Entrepreneurs – Descriptive Statistics ... 26
Table 5:
The Startups – Descriptive Statistics ... 26
Table 6:
The Incubators – Descriptive Statistics ... 27
Table 7:
Development of the Entrepreneurial Competences of the Incubatees ... 29
Table 8:
SPSS Output for Paired Sample t-Test ... 30
Table 9:
SPSS Output for One Sample t-Test ... 30
Table 10:
Preface
This thesis is made as a completion of my Master degree in Entrepreneurship at the Universiteit van Amsterdam and the Vrije Universiteit Amsterdam. Over the past few months, I was lucky to join Refugees Forward, a non-profit initiative from Amsterdam, as a student consultant for their incubation program which started in 2018. Within a short time, I discovered and built a strong passion for incubators. The time at Refugees Forward has shown me how incubators work and what effect such programs can have on nascent entrepreneurs. This led me to the decision to devote more attention to incubators in my Master thesis.
I would like to acknowledge those who provided support in writing this paper. A special note of thanks goes to Prof. Dr. Enno Masurel for his guidance and input into the research. Furthermore, I want to thank my five interview partners, who were willing to share their expertise and knowledge on business incubators. Finally, thanks must go to the numerous entrepreneurs that were willing to take their time to complete our online survey and share their incubator experience with us.
The copyright rests with the author. The author is solely responsible for the content of the thesis, including mistakes. The university cannot be held liable for the content of the author’s thesis.
Abstract
This research intends to provide an insightful view of business incubation and their impact on the development of entrepreneurial competences of the ‘incubatees’. Business incubators are considered as economic development tools designed to accelerate the growth and success of entrepreneurial companies. However, there is disagreement surrounding the performance measurement of business incubators. This paper contributes to the existing state of the literature, as it views and measures incubator performance on an individual level, instead of looking at traditional data such as the number of jobs created or firm survival rates. Based on our literature review and a series of expert interviews, we selected six entrepreneurial competences for this study: proactiveness, perseverance, networking, flexibility, risk-taking, and self-efficacy. Data collection was conducted through an online questionnaire distributed through a web-based survey tool. In total, survey requests were sent out to entrepreneurs from 195 startups, located in 22 incubators in 8 different European countries, and a total of 68 complete questionnaires were returned. Our findings show that incubators have significantly positive effects on all six entrepreneurial competences. The most substantial effect was observed in networking, followed by flexibility and perseverance. To our surprise, we also found significant positive effects on the three remaining competences. This research explores an area of academic research that has received only a little attention so far. It offers opportunities to extend traditional incubator performance theory and its findings could assist business incubation practitioners to identify specific areas that require intervention.
1 Introduction
The value of small and medium enterprises to economic growth and job creation is widely acknowledged. Consequently, the identification of the factors fostering startup creation and success have been of particular interest in academic research (Grimaldi & Grandi, 2005). One possible instrument to promote entrepreneurship is the so-called business incubator. These organizations aim to stimulate and support the creation and development of new ventures. Business incubators offer a favorable environment, created to ‘hatch’ young start-up companies (Bergek & Norrman, 2008). They provide their incubatees with various services, which range from office space and education programs to management support and financial capital. This support allows the tenant companies to concentrate on the implementation of their business plan (Aerts, Matthyssens, & Vandenbempt, 2007).
The first business incubator was established in New York in 1959 by Charles Mancuso. From 1970 on, business incubators have become a worldwide phenomenon (Aerts, Matthyssens, & Vandenbempt, 2007). Estimates in 2007 indicate around five thousand incubators worldwide (Moraru & Rusei, 2012). Nearly 30 percent of them are located in North America, 30 percent in South-East-Asia, another 25 percent in Western Europe, and the rest is dispersed over South America, Eastern Europe, the Middle East and Africa (Moraru & Rusei, 2012). Within the European Union, most incubators are in Germany (400), Great Britain (300) and France (250). Over the past decade, there has been a remarkable rise in the number of incubators, particularly in Europe. According to Salido, Sabás, & Freixas (2013), the number of European accelerators and incubators has increased by nearly 400 percent between 2007 and 2013. Partly thanks to the increased European government support, the per capita number of incubators in Europe is now as high in the United States today (Andonova, 2015).
One of the primary goals of incubators is to increase the survival rates of their tenants. Statistics show that most of the incubators seem to reach this target: survival rates vary from 80 percent in Brazil to even 90 percent Germany (Moraru & Rusei, 2012). According to benchmark studies by the European Commission (2002), business incubators are strikingly successful in Europe. Consequently, public policymakers see them as an essential mechanism for achieving economic growth, innovation, and diversity (Hannon & Chaplin, 2003).
Despite their common goal to provide their clients with business assistance, incubators differ not only in size but also regarding their purpose and types of services offered. Grimaldi and Grandi (2005) have identified four main types of incubators: Business Innovation Centres,
University Business Incubators, Independent Private Incubators and Corporate Private Incubators. Considering the massive investments in incubation programs by governments, universities, corporations and private individuals, the question has been raised about what return society gets back from these investments (Bergek & Norrman, 2008). As a result, the evaluation of incubator performance has attracted some attention in the academic literature (Grimaldi & Grandi, 2005; Hackett & Dilts, 2004; Mian, 1997). Evaluation efforts are crucial to provide necessary information on the effectiveness of such programs (Göthner & Schwartz, 2009).
It is widely acknowledged that the success of an incubator depends on the performance of the incubatees (Aerts, Matthyssens, & Vandenbempt, 2007). Prior performance studies have tried to measure incubator success from different perspectives. Specifically, most research has focused on looking at how many jobs are being generated or how many firms have successfully graduated from the incubator (Lalkaka, 1996). However, these are very broad indicators that often fail to provide a detailed picture of the impact of incubators on young ventures and entrepreneurs. Consequently, the incubator industry still lacks a complete evaluation framework (Bergek & Norrman, 2008). Assessing the success of incubation programs solely on the survival of the tenant ventures might lead to misleading interpretations.
This paper aims to contribute to the prior incubator literature by measuring the development of the entrepreneurial competences of the tenants. In other words, we introduce an alternative way of measuring the performance of business incubators. Instead of focusing on the firm level and measuring factors such as venture growth, job creation or survival rates, this research paper intends to measure the success of incubation programs on the individual level. Business ideas and ventures may fail for various reasons, but incubators should ideally still have enabled entrepreneurs to become more competent, which in turn might be helpful for their future entrepreneurial career. To the best of our knowledge, this is the first time that the measure of entrepreneurial competences has been applied to the specific context of incubator performance evaluation. In summary, the literature gap we address is the analysis of how incubators perform based on the development of the tenant’s competences. This raises the following question: To what extent do incubators contribute to the development of the entrepreneurial competences of their incubatees?
This paper is outlined as follows. In section 2, we define the concept of ‘‘incubator’’ and discuss the various elements and types of incubators described in the academic literature. In a next step, we review the notion of “entrepreneurial competences” and discuss the most
a total of five interviews with industry experts, we will formulate a set of hypotheses. The research design, as well as the constitution of the samples, will be elucidated in section 5. Further, we will evaluate the results of this empirical research study. Finally, Sections 7 and 8 present the conclusions and some suggestions for further research.
2 Business Incubators
In this section, we describe the academic background of business incubators. The notion of incubator has been used for various forms of new business facilitation (Schwartz, 2013). The Oxford dictionary describes an incubator as an “enclosed apparatus in which premature or unusually small babies are placed and which provides a controlled and protective environment for their care.” Translating this description into a business setting, we can define business incubators as organizations facilitating the growth of small businesses. Consequently, we will, in this paper, follow the definition of Phan, Siegel, & Wright (2005), who define business incubators as “economic development tools designed to accelerate the growth and success of entrepreneurial companies through an array of business support resources and services.”
In their review of business incubation, Phan, Siegel, & Wright (2005) define four main streams of incubator literature. The first kind of study deals with the incubatees located in the incubator facilities; the second type focuses on the level of the university, region or country. While the third kind of incubator literature stream intends to provide an assessment of incubators, the fourth type examines the individual entrepreneur. Similar to Hackett & Dilts, 2004, the authors identify a lack of academic research on the individual entrepreneurs participating in incubation programs. This is somewhat surprising since the importance of the entrepreneur in the startup process has been widely discussed and acknowledged. Instead of analyzing the incubatee on a firm-level, this paper will observe effects of incubation programs on the entrepreneur, and thus the individual level.
2.1 Incubator Elements
The first generation of business incubators mainly emphasized job creation and real estate appreciation (Aerts, Matthyssens, & Vandenbempt, 2007). The incubators usually offered shared office space and additional facilities to their tenants. From the early 1990’s on, new services were included, such as business consultancy, coaching and mentoring sessions as well as access to network and capital (Peters, Sundararajan, & Rice, 2004).
The main elements of business incubation are summarized in figure 1. Incubators typically offer all or most of these services. These elements have been discussed in various academic studies (e.g., Schwartz, 2013; von Zedtwitz, 2003; Grimaldi & Grandi, 2005; Hackett & Dilts, 2004). In the following, we will briefly describe each of these six elements of incubator support. Incubators usually provide cheap and furnished office spaces. Such subsidized rental spaces help young start-ups to reduce their fixed costs (Aerts, Matthyssens, & Vandenbempt, 2007). Moreover, flexible renting terms often provide the possibility for the tenants to extend the rented space, depending on their growth and needs (Schwartz, 2013). Shared facilities and services typically include secretarial support, the existence of communication infrastructure (e.g., meeting rooms), laboratory equipment, and many more. This is particularly useful for small firms who would otherwise not have access to such essential but often hardly affordable facilities (Schwartz, 2013).
Nascent entrepreneurs are often strong in technology or vision but do not have the necessary organizational or managerial skills to set up and run a business. Incubators help their tenants by guiding them through the essential steps (Allen & McCluskey, 1991; Peters, Sundararajan, & Rice, 2004). This may include accounting, legal, or financial support. Moreover, coaching and mentoring have become increasingly important elements of business incubation, and the access to workshops and individual mentors help to foster the managerial and social skills of the incubatees. Some authors even believe that without these support activities, the term ‘hotel’ would be a better description than incubator (Bergek & Norrman, 2008).
Besides, entrepreneurs do often not have access to an extensive social network. Incubators, however, have mostly taken years to create such a network (von Zedtwitz, 2003). This may include potential customers, suppliers, lawyers, research institutions, programmers, advisors, business angels and venture capitalists. Incubators can connect their tenants to these individuals. Peters, Sundararajan & Rice (2004) underline the importance of networks for
business incubators, as their empirical data show that the services distinguishing the success of incubators relate to the presence or absence of networking activities.
Furthermore, small and young ventures usually face legitimacy issues, which can cause problems when it comes to negotiating contracts or conditions with suppliers, customers or financing institutions. Being part of an incubation program increases the credibility and image of these ventures, which can help to overcome these hurdles (Schwartz, 2013). Some incubators also provide access to financial capital, such as private funds or capital invested by business angels and venture capitalists. Usually, incubators host start-ups in their seed stage, thus looking for pre-seed money, which aims to help the tenants to survive until the next financing round (von Zedtwitz, 2003).
Altogether, these support mechanisms provided by business incubators aim to resolve issues that young ventures generally face and to foster the stability and economic sustainability of the incubatees.
2.2 Distinction Between Incubators and Accelerators
Whereas incubators tend to “hatch” nascent startups by giving them room to grow, accelerators instead aim to speed up market interactions to help the young companies to adapt and learn quickly. Compared to incubators, who help the entrepreneurs in developing their initial idea, accelerators focus more on growing the business. Therefore, the two programs have different missions and are designed for a different stage of the startup lifecycle (Isabelle, 2013).
Cohen (2013) defines the business accelerator as “a fixed-term, cohort-based program, including mentorship and educational components, that culminates in a public pitch event or demo day.” Accelerator programs are usually of limited duration, lasting about three to six months. Most accelerators provide working space in addition to small amounts of seed investment. Moreover, they also offer access to a broad network, such as mentors, program graduates, venture capitalists, angel investors, or corporate executives. Finally, many accelerator programs end with a “demo day”, an event where the entrepreneurs can pitch their business idea to a broad audience of investors (Cohen, 2013).
incubators, where startups generally stay between one to five years (Cohen, 2013). Another crucial distinction between accelerators and incubators is their legal status. While most incubators are typically not profit-oriented, accelerators are for-profit-organizations designed to generate a high return on investment (Isabelle, 2013). Finally, incubators are more willing to support slow growth than accelerators, since they usually don’t put a time stamp on their support programs.
Despite these differences, the terms incubator and accelerator are often used interchangeably, since they have much in common. First of all, they both help nascent startup companies by providing shared office space and access to mentors and workshops (Cohen, 2013). Furthermore, business incubators increasingly perform the role of business accelerators and vice versa, leading to a hybrid phenomenon. These hybrids are a combination of incubators and accelerators. For instance, various incubation programs provide direct equity investment or seed funding to their tenants, which has previously been an accelerator feature (Isabelle, 2013). Besides, several incubators nowadays offer short-term accelerator programs, such as ACE Venture Lab Amsterdam or the Impact Hub Incubator with various locations all over Europe.
Table 1: Differences Between Incubators and Accelerators
Incubators Accelerators Hybrid Forms
Duration One to five years Three to six months Three months to two years
Revenue Model Mostly non-profit Mostly for-profit Mostly for-profit
Mission Economic development Growth and ROI Growth and ROI
Sector Focus Sectors with longer
time to market
Sectors with shorter
time to market Various sectors
Source: Based on Cohen (2013) and Isabelle (2013)
2.3 Incubator Heterogeneity
Most incubators are specialized in one or a limited number of industries since the focus on a specific sector generally increases the expertise of the staff and mentors and therefore also the value of the program to the tenants (Aerts, Matthyssens, & Vandenbempt, 2007). The results of Schwartz & Hornych (2008) support this argument: while the study of incubatees in specific sectors offers on average good performance results, more diversified incubators perform lower.
Table 2: Incubator Classification by Author
Authors Types of incubator classification
Smilor (1987) Private; University; Government; Non-Profit Allen & McCluskey
(1990)
For-profit property development; Academic; Not-for-profit property development; For-profit seed capital; Hybrid; Corporate
Arneoudt (2004) Mixed; Regional Development; Technology; Social; Basic Research Carayannis & von
Zedtwitz (2005)
Regional business; University; Virtual; Independent commercial; Company internal
Grimaldi & Grandi (2005)
Business innovation center; University business; Corporate business; Independent business
Barbero et al. (2012) Basic research; University; Economic development; Private
Source: Based on Barbero et al. (2012)
Incubator classifications depend on geography. Differences do not only exist between, but also within continents and even countries (Barbero, Casillas, Ramos, & Guitar, 2012). Table 2 summarizes the different types of incubators discussed in the academic literature. Allen & McCluskey (1991) were one of the first researchers to indicate the heterogeneity of incubators and to point out the importance of incubator types. The authors suggest that the characteristics of incubator categories should be considered and further analyzed, to lead to more efficient public policy decisions. The authors distinguish six types of incubators: for-profit property development, not-for-profit development corporation, academic, for-profit seed capital, hybrid and corporate.
Aernoudt (2004) distinguishes five types of incubators, based on their philosophy, sectors, and goals. Mixed incubators aim to foster entrepreneurship and employment creation. These incubators usually operate diversified through all sectors. Regional development incubators have the primary goal to foster regional economic growth and competitiveness, whereas, technology incubators help to support start-ups whose business models are based on new technologies. Besides these three “mainstream” types of incubators, Aernoudt (2004) also mentions two emerging incubator types. First, social incubators intend to support people with low employment capacities by increasing employment possibilities for them. Second, basic research incubators focus on entrepreneurs involved in basic research.
In their analysis of business incubation, Grimaldi & Grandi (2005) distinguish four main types of incubators: Business innovation centers, university, corporate business and independent business incubators. Innovation centers are public-private initiatives with the goal of stimulating local economies (Noltes, Masurel, & Buddingh, 2013). Corporate incubators are
university incubators have been founded by universities who wish to apply scientific research and create technology transfer through spin-off ventures (Grimaldi & Grandi, 2005). Independent business incubators are commercial and thus profit-oriented incubators, who are often set up by a group of individuals (Grimaldi & Grandi, 2005). In addition to these four types, Noltes, Masurel, & Buddingh (2013) added another classification: The green business incubator, that is focused on start-ups aiming to tackle social challenges (e.g., clean technologies, renewable energies).
McAdam & Marlow (2008) distinguish five types of incubators. First, the for-profit property development incubators, who aim to maximize occupancy and sell their services to the tenants; second, non-profit development corporation incubators, who want to encourage job creation and entrepreneurship in general; third, university incubators trying to foster the collaboration between faculties and the industry and further to commercialize university research; fourth, for-profit investment incubators trying to make profitable capital gains as quick as possible; and finally corporate venture incubators, aiming to penetrate into related markets quickly and to have a window on related technologies.
In addition to that, new types of incubators are emerging, such as the networked incubator, characterized by a bottom–up approach in which the start-ups develop and manage the incubator (Bøllingtoft & Ulhøi, 2005), or the virtual incubator (Nowak & Grantham, 2000), which is characterized by the distribution of resources through the internet (Barbero, Casillas, Ramos, & Guitar, 2012). As the analysis of the various incubator studies shows, there is not one uniform business incubator classification. Depending on the geographical background, different classifications have emerged over time. However, a general pattern can be identified: First, researchers often distinguish between for-profit and non-profit incubators, and second, also use the primary stakeholders (e.g., universities, corporates, local governments) as a way of classifying business incubators.
2.4 Incubator Performance Measures
Incubator performance has been widely and controversially discussed in the academic literature. The diversity of used measures indicates that no clear consensus exists on how to measure the performance of business incubators (Phan, Siegel, & Wright, 2005). Barbero, Casillas, Ramos, & Guitar (2012) distinguish four different types of performance model categories: complex
models with many measures, complex models based on assessments of input and output R&D measures, simple models with several measures and one measure models. In this section, we review the different performance measures used in the literature, which are also summarized in table 3.
Table 3: Incubator Performance Measurements Used in the Academic Literature
Performance
model category Authors Performance indicators used
Complex models with a large number of measures
Mian (1997) Goal approach (4 measures); System resource approach (7); Stakeholder approach (4); Internal process approach (5) Bigliardi et al.
(2006)
Patrimonial structure; Internal development; Repercussion in the territory; Economic and financial aspects; Human resources and productivity; International relationships Complex models
based on input & output R&D measures
Westhead (1997)
Input R&D (Proportion of qualified engineers, radical new research, R&D spending, gross R&D investment) and Output R&D (Number of patents, introduction of new products or services) Simple models with several measures Allen & McCluskey (1991)
Occupancy; Job creation; Firm graduation
Sherman & Chappell (1998)
Sales growth; Survival rate; Number of new technologies; Patents or trademarks; Jobs created
Siegel et al. (2003)
Survival rate; Employment growth; R&D activity
Voisey et al. (2006)
Hard measures (sales turnover, profitability, growth,
graduation) and Soft measures: client professionalism, client business skills, client confidence, productive networking, client knowledge, etc.)
One measure models Aernoudt (2004); Aerts et al (2007) Survival rate Pena (2004) Growth
Source: Based on Barbero et al. (2012)
Some researchers have developed complex models to evaluate incubator performance. For instance, Mian (1997) bases his performance framework of university incubators on four approaches: goal approach, system resource approach, stakeholder approach and internal process approach. Bigliardi, Dormio, Nosella, & Petroni (2006) offer an assessment depending on six criteria: patrimonial structure, internal development, repercussion in the territory, economic and financial aspects, human resources and technical-scientific productivity and international and interregional relationships. Each of these six elements is analyzed through several indicators.
Other studies have a stronger focus on technology-based start-ups and thus use some research indicators to assess incubator performance. Westhead (1997) differs between input and output R&D indicators. For input R&D measures, he uses the proportion of qualified scientists employed, fundamental new research and some financial indicators such as R&D spending. Output R&D indicators are operationalized by looking at the number of patents or the introduction of new products or services.
However, most of the academic studies use simpler or even one measure models. Allen & Mccluskey (1991) suggest the use of three key indicators, namely incubator occupancy, job and firm creation. Siegel, Westhead, & Wright (2003) use three different measures: tenant survival rate, employment growth, and R&D activity. Voisey, Gornall, Jones, & Thomas (2006) differentiate between hard measures such as sales growth, profitability or graduation and soft measures (e.g., client professionalism, client skills, client confidence and networking).
Despite the various indicators used, it is noticeable that various incubator studies use venture survival as an indicator for incubator performance (e.g., Aernoudt, 2004; Aerts, Matthyssens, & Vandenbempt, 2007; Lalkaka, 1996; Sherman & Chappell, 1998). While some studies provided evidence that new firms associated with incubators have a higher survival rate than non-incubated firms (Hackett & Dilts, 2004), other papers found little or no effect on firm survival (Scillitoe & Chakrabarti, 2010). In contrast to this, other authors criticize the use of firm survival as a performance indicator for incubators. Since incubators are designed to maintain and increase the lifespan of their incubatees, this measure has only little validity (Phan, Siegel, & Wright, 2005). Other authors have used growth in sales or employment as an indicator of incubator performance (Mian, 1997). A few authors even use profit growth (Peña, 2004), which can also be criticized, since young ventures mostly don’t generate profits in their first years. (Barbero, Casillas, Ramos, & Guitar, 2012).
Overall, we reckon that there is a wide range of possible indicators available for the evaluation of business incubators. However, the choice of the right criteria is far from being clear-cut (Göthner & Schwartz, 2009)., which might be because there does not seem to be much consensus on the definition of performance (Bergek & Norrman, 2008). Moreover, issues in measuring incubator success are undoubtedly due to different selection criteria, a general lack of access to data, and the diversity of incubators (Hackett & Dilts, 2004).
Hackett & Dilts (2004) differentiate six different units for incubator performance management: the entrepreneurial (individual) level, the incubator manager (individual) level,
the incubatee (firm) level, the incubator (firm) level, the community (local) level and the incubation industry (industry) level. While most of the academic literature has focused on the firm and community level, there is still a need for further analysis of the individual entrepreneur (Phan, Siegel, & Wright, 2005). This gap in the literature will be filled in this paper, by analyzing the effect of incubation programs on the individual level, and precisely by looking at the development of the entrepreneurial competences of the incubatees.
3 Entrepreneurial Competences
The concept of entrepreneurial competence has its foundation not only in the competence but also in the entrepreneurship literature (Mitchelmore & Rowley, 2010). Before an in-depth analysis of the competence concept, the question “Who is an entrepreneur?” should be answered, since a lack of basic agreement seems to exist in the academic literature (Gartner, 1988). In this paper, we will adopt the definition of Masurel & Grunberg (2012) and define entrepreneurship as the discovery, creation, and exploitation of profitable opportunities. This aligns with Schumpeter (1965), who defines entrepreneurs as “individuals who exploit market opportunities through technical or organizational innovation.”
The concept of entrepreneurial competences crosses different disciplines such as psychology, educational sciences, and organizational behavior. Therefore, it is often referred to as a fuzzy concept (Kyndt & Baert, 2015). Some authors even believe that the confusion and debate around the concept make it impossible to arrive at a definition capable of reconciling all the different ways that the term is used (Delamare Le Deist & Winterton, 2005). On the one hand, the traditional American term competency has usually been perceived as an underlying characteristic of a person which results in a superior job (Boyatzis, 1982). The concept of competence, however, can be described as “an action, behavior or outcome which a person should be able to demonstrate” (Mitchelmore & Rowley, 2010).
In this paper, we define entrepreneurial competences as a set of personal components such as knowledge, skills, motivation, traits, self-images and social roles which eventually help to perform well as an entrepreneur. This definition is increasingly supported by other researchers, who recognize that the use of competences is of added value if it is perceived as more than only knowledge, behavior or skills, but instead as an integration of several elements (Bird, 1995; Lans, Hulsink, Baert, & Mulder, 2008; Ismail, Zain, & Zulihar, 2015).
Driessen & Zwart (2006) indicate that four different components jointly form an individual’s competence: Wanting, Being, Capability, and Knowledge. Wanting relates to motivation and depends on ambition, values, and motives of the person (Driessen & Zwart, 2006). Being refers to the traits or characteristics that make a person able to start a career as an entrepreneur (Ismail, Zain, & Zulihar, 2015). A capability indicates that an individual can do something. This component differs from traits, as capabilities refer to skills that are learnable through experience and coaching (Driessen & Zwart, 2006). Knowledge is the fourth and last component of competence, and refers to the rational part of entrepreneurship. This may include
a specific knowledge about administration, law or regulations, but also experience in general (Ismail, Zain, & Zulihar, 2015). Based on this competence model, Driessen & Zwart (2006) developed the Entrepreneur Scan, an online tool for self-reflection for aspiring, nascent and experienced entrepreneurs. This scan mainly measures two of the four components, namely characteristics and capabilities.
Another essential characteristic of entrepreneurial competences is that they are changeable, learnable and attainable through experience, training or coaching (Kyndt & Baert, 2015). Despite the traditional approach or belief that entrepreneurship is preferably a result of nature than nurture, there is a growing volume of academic research indicating the effect of entrepreneurship education and training as a source for new venture creation, development, growth, and survival (Lans, Hulsink, Baert, & Mulder, 2008).
Interest in entrepreneurial competences results from the positive link between competences and new venture creation and development (e.g., Bird, 1995; Man, Lau, & Chan, 2002; Sánchez, 2011). Thus, it is essential to identify the main competences so that both organizations and educational institutions can work on developing them (Robles & Zárraga-Rodriguez, 2015). Other authors have used the concept to evaluate the effectiveness of entrepreneurship programs (e.g., Sánchez, 2011; Rodrigues, Dinis, do Paço, Ferreira, & Raposo, 2012; Sánchez, 2013; Ismail, Zain, & Zulihar, 2015): They believe that entrepreneurial competences can serve as a useful construct for the development of learning environments, courses and coaching programs that aim to learn for entrepreneurship (Lans, Hulsink, Baert, & Mulder, 2008).
Based on a thorough literature review, we found a total number of 24 entrepreneurial competences to be the most relevant ones in having a positive impact on entrepreneurship. In the following, we conducted some interviews with incubation experts to determine the most critical entrepreneurial competences for this specific study. Based on these interviews and our own opinion, we finally chose the six following competences to be particularly relevant: proactiveness, perseverance, networking, flexibility, self-efficacy, and risk-taking. This competence selection process and the results from our qualitative interviews will be explained in more detail in chapter four. We are aware that the selected competences are not mutually exclusive and that they might partly overlap. The next subsections explore each of these entrepreneurial competences in detail.
3.1 Proactiveness
According to the Oxford English Dictionary, a proactive person creates or controls a situation instead of just responding to it after it has happened. Proactiveness implicates anticipating potential issues before they occur (Sánchez, 2011). It also includes the general willingness to take action, to create opportunities and improve outcomes without the need for any external requirement (Robles & Zárraga-Rodriguez, 2015). In contrast, non-proactive individuals often fail to identify and work on opportunities (Sánchez, 2011).
Crant (1996) proves that proactive personality can be a predictor of entrepreneurial intentions, because more proactive people tend to envisage creating situations, such as seeing opportunities or building a new venture. Covin & Slevin (1989) indicate that proactiveness is one of the crucial dimensions for entrepreneurial orientation, i.e., for what is needed to put entrepreneurship into practice. Other academic studies have confirmed the relationship between proactiveness and entrepreneurial behavior (Rauch & Frese, 2007). Finally, there is also empirical evidence of a positive relationship between proactive behavior and a successful career (Seibert, Kraimer, & Crant, 2001).
In his longitudinal research, Sánchez (2011) analyzed the effect of university training on entrepreneurial competencies and its impact on the intention of venture creation. The results indicate that students in the program group significantly developed their proactive behavior, whereas students in the control group did not. Such findings contribute to the literature of entrepreneurship education and suggest that proactivity can be learned or trained through entrepreneurship programs.
3.2 Perseverance
The second identified competence for entrepreneurs is perseverance, also sometimes referred to as endurance. This competence describes the persistence in doing something despite difficulty or delay in achieving success (Oxford English Dictionary). Throughout the foundation process, most entrepreneurs face setbacks, objections or rejection conditions. Successful entrepreneurs have a high level of durability and can continue despite these difficulties and finish assignments even when they are tired of it (McClelland, 1987). Their endurance enables them to hold on until the preset goals are reached (Kyndt & Baert, 2015).
Van Gelderen (2012) has offered a descriptive model of perseverance, consisting of four main categories: The continued attempts to solve the problem, coping with the entrepreneurial situation, adapting the goals, and regaining the ability to deal with the problem. Kyndt & Baert (2015) found that perseverance contributes positively to being and remaining active as an entrepreneur, whereas the majority of the other competences used in their research did not significantly predict the entrepreneurship status of the research participants. Moreover, Ismail, Zain, & Zulihar (2015) found perseverance to be amongst the two highest characteristics being developed in an entrepreneurship education program for college students. However, even though perseverance seems to be a crucial success factor in new venture creation, only a limited number of studies have explored the phenomenon of endurance in the entrepreneurial context (Lamine, Mian, & Fayolle, 2014).
3.3 Networking
For any entrepreneur, it is crucial to build relevant networks and maintain them over time (Man, Lau, & Chan, 2002).It is widely acknowledged that networking is one of the key competences that entrepreneurs should have. This network of contacts is crucial to achieve preset goals, such as recruiting potential suppliers, investors or customers (Kyndt & Baert, 2015).
Uzzi (1997) differentiates between arms-length relationship and embedded relationships. Embedded relationships have three main components that regulate the behaviors of exchange partners: Trust, fine-grained information transfer, and joint problem-solving arrangements. Such embeddedness promotes economies of time and allocative efficiency, which positively affects organizational performance (Uzzi, 1997). The research suggests that entrepreneurs should put an effort in developing and maintaining a diverse social network that integrates arm's-length and embedded ties to optimize their venture’s performance potential.
In their case study of high-technology firms, Elfring & Hulsink (2003) improve the understanding of the causal mechanisms between network structure and performance in different situations of the entrepreneurial process. The authors identify three entrepreneurial processes that link the network ties (mix of weak and strong ties) with the performance for emerging ventures in each of the three stages: discovering opportunities, acquiring resources and obtaining legitimacy. They find that networks influence each of these three entrepreneurial processes in new venture development by providing access to power, information, knowledge,
3.4 Flexibility
Flexibility reflects the willingness to change, adapt or compromise (Oxford English Dictionary). Successful entrepreneurs react to changes observed in their environment, such as the emergence of new competitors in the market or the change of customer needs and legal regulations (Ismail, Zain, & Zulihar, 2015).
Smith (1967) differs between two basic types of entrepreneurs: the craftsman-entrepreneur and the opportunistic-craftsman-entrepreneur. While the craftsman-craftsman-entrepreneur is rather focused on the present and past and possesses only low levels of flexibility, the opportunistic-entrepreneur has a high degree of flexibility and a strong orientation to the future. The results of the study support the hypothesis that ventures run by opportunistic-entrepreneurs achieve higher sales growth rate, since they are more effective in making decisions that encourage innovation, thanks to their flexibility and orientation to the future.
Colton & Udell (1976) studied alumni at the University of Oregon. Their results also underlined the importance of flexibility for entrepreneurs. To cope with the hectic and rapidly changing nature of modern life, flexibility should be considered as one of the primary skills that each individual, and in particular entrepreneurs need to possess (Halal, 1996).
Both studies by Oosterbeek, van Praag, & Ijssel (2010) and Ismail, Zain, & Zulihar (2015) measure the effect of entrepreneurial education programs on the development of entrepreneurial competences such as flexibility. While Oosterbeek, van Praag, & Ijssel (2010) did not find any significant change, Ismail, Zain, & Zulihar (2015) found a significantly positive effect, indicating that flexibility is learnable through experience and training.
3.5 Self-efficacy
Self-efficacy reflects the personal belief in one’s own ability to meet preset goals (Bandura, 1997). In some academic studies, self-efficacy is also referred to as self-confidence (Ismail, Zain, & Zulihar, 2015). Rauch & Frese (2007) distinguish between generalized and task-specific self-efficacy. According to them, generalized self-efficacy is crucial for entrepreneurs because they must be confident in their capabilities to perform in different and unexpected situations. People with high generalized self-efficacy are likely to persevere when problems arise and are continually searching for challenging opportunities (Bandura, 1997). Therefore,
generalized self-efficacy is positively related to business creation and success (Rauch & Frese, 2007).
Self-efficacy has been able to help explain why equally skilled individuals can perform differently (Shane, Locke, & Collins, 2003). A person with a high degree of self-efficacy will invest more time and effort, take criticism more positively, set higher goals, and develop more thorough plans to fulfill these goals (Shane, Locke, & Collins, 2003). Since the entrepreneurial process includes setbacks, risks, and difficulties, entrepreneurs should preferably have a high level of self-efficacy to be successful (Sánchez, 2011).
The concept of self-efficacy has been used in a variety of models analyzing entrepreneurial behavior and intention. In fact, some researchers found out that perceptions of self-efficacy in the forming of entrepreneurial intentions can explain why some individuals engage in entrepreneurship (Sánchez, 2011). It has also been used in several studies measuring the impact of entrepreneurial training (Oosterbeek, van Praag, & Ijssel, 2010; Sánchez, 2011; Ismail, Zain, & Zulihar, 2015) and therefore seems to be an appropriate competence for our study on business incubators.
3.6 Risk-taking
The last competence of interest in this paper is risk-taking, which reflects both the willingness to take risks and the ability to deal with uncertainty and possible adverse outcomes (Oosterbeek, van Praag, & Ijssel, 2010). This is an essential competence for successful entrepreneurs since any entrepreneurial process involves uncertainty (Shane, Locke, & Collins, 2003). As a result, it has been mentioned various times in the academic trait and competence literature (e.g., McClelland, 1961; Brockhaus, 1980; Shane, Locke, & Collins 2003; Oosterbeek, van Praag, & Ijssel, 2010; Sánchez, 2011).
The propensity towards risk has emerged from McClelland (1961) and his claim that individuals with a high degree of need for achievement have a stronger inclination towards risk-taking. Despite these theoretical claims and the consensus on the importance of risk and uncertainty in the entrepreneurial process, previous research has often failed to provide empirical evidence that entrepreneurs differ significantly from the rest of the population (Shane, Locke, & Collins, 2003). Only Brockhaus (1980) and Begley (1995) found that entrepreneurs
Sánchez (2011) analyzed the effect of university training for entrepreneurial competencies and its impact on the intention of venture creation and found that students in the program group significantly increased their propensity towards risk-taking, whereas students in the control group did not. These results stand in contrast to those of Rodrigues, Dinis, do Paço, Ferreira, & Raposo (2012): In their study, the educational program had a significantly negative impact on the student’s propensity to risk. Other studies (Oosterbeek, van Praag, & Ijssel, 2010; Ismail, Zain, & Zulihar, 2015) did not yield any significant results.
4 Hypotheses
Our literature review revealed a total number of 24 entrepreneurial key competences (see appendix 1). Before taking a look at what the incubatees themselves say about the development of their competences, we first conducted a series of five interviews with incubation experts. All five experts were from the field of entrepreneurship and business incubation. Four of the experts currently own or manage an incubator or co-working space in the Netherlands, and one expert is currently conducting academic research on incubators. The expert interviews had a qualitative approach and were transcribed (see appendix 3). These interviews served to investigate which entrepreneurial competences the experts recognize the most in successful entrepreneurs. As we do not have a strong theoretical basis to formulate explicit hypotheses, the incubation experts were also asked to estimate the effect of incubation programs on the development of the tenant’s key competences.
All five experts emphasized that proactiveness is a crucial competence for entrepreneurs. Successful entrepreneurs should be individuals who actively seek opportunities and who are not afraid to go out and deal with problems or issues before or immediately as they arise. However, the estimated effect of incubators on the proactive behavior of the incubatees remained somewhat unclear. While one expert expected a positive impact, the others predicted no or even an adverse effect. This might be due to the reason that the most significant risk of incubation programs is that the entrepreneur gets too comfortable. Since many things are arranged for the entrepreneur during the program, he or she might not learn to be very proactive and believe that some things happen ‘naturally’. Another expert suggested that proactive behavior could not be significantly influenced by incubators, since it is a relatively fixed character trait. Altogether, the first hypothesis is suggested:
Hypothesis 1: The participation in the incubation program has no significant impact on the proactiveness of the entrepreneur.
A crucial second competence named by four out of five experts was perseverance or endurance. Entrepreneurs need to have the strength to continue because entrepreneurship is a very complex and challenging domain; every entrepreneurial process includes problems and setbacks. In incubation programs, entrepreneurs learn that failure is part of entrepreneurship – they
mentors. Recognizing this, they might eventually overcome these hurdles to achieve success. As a result, our experts believe that business incubators can foster the development of this entrepreneurial competence. Only one out of five experts did not expect any influence of incubators on endurance. After all, we posit the second hypothesis for this study:
Hypothesis 2: The participation in the incubation program has a significantly positive impact on the perseverance of the entrepreneur.
The third most crucial stated competence for entrepreneurs was networking. Again, four out of five experts saw networking as a crucial competence for firm founders. No entrepreneur knows everything right from the start, but he or she should know the right people to approach if help is needed. Therefore, it is indispensable for any entrepreneur to build relevant networks and maintain them over time. This depends on the social orientation of the founder, i.e., to what extent he or she understands that connection with other people is needed to realize the intended ideas. All interviewed industry experts believed that incubators could play an important role here. During the incubation program, startups usually receive access to a broad network of customers, suppliers, investors, and advisors who help to bring the business to the next level. As a result, we derive our third hypotheses:
Hypothesis 3: The participation in the incubation program has a significantly positive impact on the networking capabilities of the entrepreneur.
Flexibility is another fundamental competence, since entrepreneurs continously need to adapt to changes and adjust their plans, products or processes during the startup phase. Especially in the seed phase, entrepreneurs constantly face issues and therefore have to adapt their strategy or even completely change their business model. Thorough planning is necessary and essential, but spontaneously adjusting these plans is crucial as well, if needed. All interviewed experts believed that incubation programs should have a positive impact on this key competence. This argument is also supported by Ismail, Zain, & Zulihar (2015), who found a significantly positive effect of entrepreneurship education on this competence, indicating that flexibility is learnable through experience and training. Therefore, the following hypothesis is suggested:
Hypothesis 4: The participation in the incubation program has a significantly positive impact on the flexibility of the entrepreneur.
The fifth most stated competence of the experts was self-efficacy. This competence is also widely used in the academic literature and has proven to be necessary for entrepreneurs, as it enables them to be confident and optimistic enough to reach their goals. The effect of incubation programs on the founder’s self-efficacy remains somewhat unclear though. Only one of our experts suggested a strongly positive effect since entrepreneurs receive a lot of support and positive feedback on their ideas during the incubation period. Also, the expert expected that more knowledge about entrepreneurship, usually acquired in incubator programs, would make the entrepreneurs more confident to achieve the desired results. However, most of the interview experts did not expect significant changes in this crucial competence through business incubators, as it is a quite stable characteristic. Therefore, we derive the following hypothesis:
Hypothesis 5: The participation in the incubation program has no significant impact on the self-efficacy of the entrepreneur.
Finally, the experts emphasized the importance of risk-taking tendencies for entrepreneurs, since every entrepreneurial activity includes risks and uncertainty. According to them, entrepreneurs with a higher propensity towards risk are more likely to be successful. However, most of the experts stated that risk-taking is a somewhat stable characteristic that is not likely to be changed through participation in an incubation program. Only one expert suggested a slightly positive effect. As a result, we suggest the following and last hypothesis for this study:
Hypothesis 6: The participation in the incubation program has no significant impact on the risk-taking propensity of the entrepreneur.
To sum up, we derived a set of six entrepreneurial competences from our literature review and series of expert interviews: proactiveness, perseverance, networking, flexibility, self-efficacy, and risk-taking. The expert interviews revealed that other widely acknowledged
not the most important ones. Nevertheless, we continued our research with the six identified entrepreneurial competences. Based on the interview results, the most substantial impact of incubation programs on these entrepreneurial competences can be expected for networking. We also expect a positive effect on perseverance and flexibility. However, the estimated effect of incubators on the proactiveness, self-efficacy and risk-taking tendency of their tenants are expected to be comparably small and not significantly positive.
5 Methodology
In a next step, each of our six selected competences was translated into four propositions (see appendix 2). The items measuring the proactiveness of the incubatees are based on the study of Seibert, Kraimer, & Crant (2001). These authors set up a ten-item scale to measure the proactive behavior of individuals. We picked four of these ten items, which we believed to be particularly interesting for this study. These propositions serve to assess to what extent the participants have improved to undertake significant actions to influence their environment. Three of our four items related to perseverance were deducted from Kyndt & Baert (2015) and supplemented by one proposition from the E-scan test (Driessen & Zwart, 2006). Altogether, these four items serve to identify whether the entrepreneurs have learned to cling to their work and not give up until their goals have been reached. Networking skills were also measured using items based on the study of Kyndt & Baert (2015) and the E-scan test (Driessen & Zwart, 2006). These propositions help to identify, whether the entrepreneurs have learned that people and networks are necessary to realize their ideas, and whether they have improved to build new business relationships. The items measuring the flexibility of the incubatees are based on three propositions from the E-scan test (Driessen & Zwart, 2006) and supplemented by one own suggestion. Together, these propositions aim to identify whether the entrepreneurs have improved in reacting to changes they observe in their environment, such as new competitors in the market or new wishes of customers. Three of our four items related to the self-efficacy were deducted from Masurel & Grunberg (2012) and supplemented by a proposition from the E-scan test (Driessen & Zwart, 2006). These propositions help to assess whether the participation in the program has increased the entrepreneur’s personal belief that their goals can be reached on their own strengths. The last competence, risk-taking, was operationalized using four items from three different sources: two by Masurel & Grunberg (2012), one by Rodrigues, Dinis, do Paço, Ferreira, & Raposo (2012) and one by a proposition of the E-scan test (Driessen & Zwart, 2006). These propositions serve to assess to what extent the incubation program has pushed the entrepreneurs towards active risk-taking.
In our questionnaire (see appendix 4), the respondents were asked to indicate to what extent the 24 propositions (see appendix 2) fit their situation. The potential answers were displayed on a 5-point Likert scale, ranging from ‘fully disagree’ (score 1), ‘somewhat disagree’ (score 2), ‘neither agree nor disagree’ (score 3), ‘somewhat agree’ (score 4) and ‘fully agree’ (score 5). Besides, the questionnaire also contained questions about the demographics and
To ensure comparability between the analyzed startups, we have set certain sample restrictions. First, we only measured the development of entrepreneurial competences for startups located in Europe. Second, the duration of the incubation program should not be less than one year and not exceed five years; and third, the incubator must offer physical facilities such as office space. This excludes, for instance, virtual incubators, not offering physical workspaces, and acceleration programs, with a typical program duration of three to six months. Fourth, the startups must have been founded in 2015 at the earliest and 2018 at the latest to ensure that the analyzed companies are still in the seed or startup stage. Fifth, the entrepreneur must have joined the incubation program at the earliest in July 2016 and at the latest in January 2018. Using these sample requirements, we want to ensure that the results are well comparable. For our fieldwork among incubators and their participants, the data was gathered in May and June 2018, utilizing an online questionnaire. Incubator participants across Europe were invited to fill in the questionnaire, and two reminders were sent out after one and two weeks. Our primary focus was on incubators in the Netherlands, but also founders in Germany, France, Austria, United Kingdom, Spain, Italy, Finland, and Switzerland were contacted. Desk research generated the contact information. In a first step, we selected incubator programs that meet the criteria described above. In doing so, we restricted ourselves to university incubators and for-profit incubators. In the following step, the participating startups were identified and individually contacted. All entrepreneurs were contacted via the social media platforms LinkedIn (98 percent) or e-mail (two percent). In total, survey requests were sent out to 343 entrepreneurs from 195 startups, located in 22 incubators in eight different European countries. From these 343 founders, 80 replied and requested more information about the survey. Finally, a total of 68 complete questionnaires were returned, leading to an overall response rate of 19,8 percent. The descriptive characteristics of the entrepreneurs, startups, and incubators participating in this study are summarized in the tables 4 to 6.
Table 4: The Entrepreneurs - Descriptive Statistics
Gender Prior Experience
Male 72% Yes 37%
Female 28% No 63%
Age Highest Education
< 24 10% High School 3% 25-29 43% Bachelor 29% 30-34 16% Master 59% 35-39 19% Doctorate 7% > 40 12% Other 2% N = 68
Table 4 summarizes the descriptive statistics of the entrepreneurs participating in this study. The average age of the respondents was 31,2 years. The youngest entrepreneur was 22 years old, while the oldest founder had an age of 47 years. In total, 53 percent of all survey respondents were aged under 30, while 47 percent were equal to or older than 30. Almost half of the respondents were aged between 25 to 29. Furthermore, more than 70 percent of the entrepreneurs were male, and only 28 percent was female. More than half of the respondents (59 percent) have a master degree as their highest educational degree, 29 percent a bachelor degree, and seven percent a doctorate. Moreover, 37 percent state to have prior entrepreneurial experience, while 63 percent indicate that their current venture is their first one.
Table 5: The Startups - Descriptive Statistics
Year of Foundation Founder Team Size
2015 7% 1 4%
2016 31% 2 50%
2017 50% 3 24%
2018 12% 4+ 22%
Industry Number of Employees
Technology/Computers 25% 0 24% Healthcare/Medical 13% 1 10% Aerospace/Automotive 9% 2 19% Education 7% 3 13% Real Estate 6% 4 7% Entertainment 6% 5 4% Others 34% > 5 23%
Table 5 summarizes some of the key statistics about the startups participating in this study. Half of the startups were founded in 2017, 31 percent of the ventures started in 2016, and only seven percent of the companies were founded in 2015. Twelve percent of the entrepreneurs started their venture only in January of 2018. Besides, the participating founders are active in a variety of different industries: most of the startups operate in the technology sector (25 percent), followed by healthcare/medical (13 percent), aerospace/automotive (nine percent) and education (seven percent). Six percent each operate in the real estate and entertainment sector. The remaining 34 percent operate in several other industries, such as Pharmaceutical, Media & Printing, Food & Beverages, Finance & Insurance or Biotechnology. Regarding the founder team size, 74 percent of the startup teams consist of two or three co-founders. 22 percent of the respondents operate in a team of four or more, whereas only five percent of the respondents work as a solo founder. Moreover, most of the startup teams are still small: 24 percent of the respondents reported to have no employees at all, 29 percent have one or two, another twenty percent have three or four employees. Only 27 percent of the founders have employed five or more individuals.
Table 6: The Incubators - Descriptive Statistics
Location Services offered The Netherlands 54% Shared business facilities 75% Germany 18% Seminars and workshops 82% France 18% Access to mentors 81% United Kingdom 6% Access to network 88% Austria 3% Direct finance/funding 37%
Switzerland 2%
Program Start Program Size
2016 15% < 15 incubatees 56% 2017 60% 15-35 incubatees 21% 2018 25% > 35 incubatees 15% Don’t know 8% N = 68
The descriptive statistics for the incubators of our study are shown in Table 6. Overall, we received responses from 68 entrepreneurs located in 19 different incubators in six European countries. With 54 percent, the majority of our respondents are located in incubation programs
in the Netherlands, in cities such as Amsterdam, Utrecht, Delft, Noordwijk, Herleen, Maastricht and Den Bosch. Furthermore, 18 percent of the entrepreneurs come from four different incubators in Germany (Berlin and Munich), 18 percent from France (Paris), six percent from the United Kingdom (London), three percent from Austria (Graz) and two percent from Switzerland (Bienne). We started our data collection in the Netherlands, but as the number of answers was not sufficient, we also started to gather data in other European countries. We focused mainly on Germany, France and the United Kingdom, and specifically on three cities: Berlin, Paris, and London. These cities are known to be particularly attractive to founders and therefore offer numerous incubator programs.
We note that our sample is very diverse, especially in terms of spread over different countries. Besides, most of the entrepreneurs joined the incubation program in 2017 (60 percent), 15 percent in the second half of 2016, and 25 percent have started the incubation period in January 2018. Not surprisingly, all our respondents state that their incubators provide them with office or co-working space, as this was one of our requirements to be eligible for the study. Moreover, 75 percent of the incubators provide shared business facilities, and 82 percent offer educational seminars and workshops. The majority of the incubators additionally provides access to mentors (81 percent) and a broad network of customers, suppliers or investors (88 percent). Finally, 37 percent of the incubators also offer direct investment to their startups. Regarding the size of the program, the majority can be considered as rather small, with fewer than 14 incubatees (56 percent). Another 21 percent of the incubators have 15 to 35 startups, while the remaining 15 percent of the incubators host more than 35 startups. Eight percent of the respondents were not sure about the exact size of their incubator.
Now that we have described our study sample sufficiently, the next section will focus on the results of our study and the question to what extent business incubators can foster the development of the entrepreneurial competences of their incubatees.
6 Results
Table 7 presents the averages and standard deviations of the six entrepreneurial competences derived from our literature review and expert interviews. First, we can see that all competences have a comparably low standard deviation, which enables us to work with the averages in column four. To understand whether the questions in this questionnaire all reliably measure the same variable (competence), we computed the value for Cronbach's alpha for each competence. Cronbach's alpha is one of the most common measurements of internal consistency and is most commonly used in questionnaires consisting of multiple Likert questions that together form a scale. Cronbach’s alpha reliability coefficient normally ranges between 0 and 1. The closer the coefficient gets to 1, the greater the internal consistency of the items in the scale (Gliem & Gliem, 2003). Moreover, George & Mallery (2003) state the following rules of thumb: > 0.9 – Excellent, > 0.8 – Good, > 0.7 – Acceptable, > 0.6 – Questionable, > 0.5 – Poor, and < 0.5 – Unacceptable. As we can see in column 3, all measurements for Cronbach’s alpha can be considered acceptable or good.
Table 7: Development of the Entrepreneurial Competences of the Incubatees
N Cronbach’s α Mean Std. Deviation Variance
Networking 68 0,72 3,88 0,76 0,58 Flexibility 68 0,82 3,62 0,83 0,69 Proactiveness 68 0,83 3,61 0,86 0,74 Perseverance 68 0,80 3,60 0,87 0,75 Risk-taking 68 0,80 3,53 0,84 0,71 Self-efficacy 68 0,77 3,49 0,85 0,72
Looking at the averages, we conclude that, from the perspective of the incubatees, their networking competence (3,88) is the most positively influenced by incubation programs. Then, we have flexibility with a mean of 3,62, followed by proactiveness (3,61) and perseverance (3,60) on position three and four. Finally, we see that risk-taking (3,53) and self-efficacy (3,49) seem to be positively, but the least influenced by incubators. On the first look, we can already state that part of our initial expectations can be confirmed. As stated above, we expected the most influential impact of incubation programs to be on networking, which can be confirmed by looking at the means in table 7. Furthermore, we also estimated that the effect of incubators on the self-efficacy and risk-taking tendency of their tenants would rather small in comparison, which also seems to be true.
However, we must note that the mean scores of the six entrepreneurial competences hardly differ. Table 8 shows whether the average competence values differ significantly from each other. The results indicate that networking scores significantly higher than the other competences. However, we have found no significant difference between the five remaining competences, since the mean values are between 3,49 and 3,62 and thus quite close to each other.
Table 8: SPSS Output for Paired-Sample t-Test
Competences Mean SD Ne. Fl. Pr. Pe. R-t.. S-e.
Networking 3,88 0,76 - Flexibility 3,62 0,83 0,00* - Proactiveness 3,61 0,86 0,00* 0.89 - Perseverance 3,60 0,87 0,00* 0,77 0,85 - Risk-taking 3,53 0,84 0,00* 0,27 0,18 0,37 - Self-efficacy 3,49 0,85 0,00* 0,15 0,06 0,23 0,58 -
Note. * Significant at 5% level
In a next step, we formally tested our hypotheses of section four. To check these hypotheses, we conducted a one-tailed t-test for each competence, by choosing a test value of 3. In other words, we tested whether each of the six competences is significantly higher than 3. If incubators have a positive impact on a given competence, the mean score should be significantly higher than 3. According to our hypotheses, we expect this to be true for networking, flexibility and perseverance, and not true for proactiveness, self-efficacy and risk-taking.
Table 9: SPSS Output for One-Sample t-Test
Test Value = 3 t df Sig. (2-tailed) Mean Difference 90% Confidence Interval of the Difference Lower Upper Networking 9,551 67 ,000 ,87868 ,7252 1,0321 Flexibility 6,110 67 ,000 ,61765 ,4490 ,7863 Proactiveness 5,817 67 ,000 ,60662 ,4327 ,7805 Perseverance 5,664 67 ,000 ,59559 ,4202 ,7710 Risk-taking 5,174 67 ,000 ,52941 ,3588 ,7001 Self-efficacy 4,781 67 ,000 ,49265 ,3208 ,6645
