Early entrepreneurship support programs come in various forms, however, there are four main types: accelerators, incubators and coworking spaces, events and competitions, and formal degree or educational programs. They exist across multiple sectors (e.g., public, private, social) and vary widely in quality and scope, which contributes to a mix of research findings about how they impact entrepreneur formation and startup outcomes.
Early stage entrepreneurship support programs are increasingly popular, with thousands of programs existing across the U.S and abroad to support entrepreneurs and startups. Many of these programs are relatively new and hail from a range of sectors, including federal, state, and local governments. Universities play an increasing role, with most colleges having some form of entrepreneurial support program, and many larger universities hosting several. Non-profits and for-profit corporations alike also create programs to support startups and their founders. A whole industry now exists around supporting entrepreneurs with varied business models including fee-for-service, rent-for-workspace, equity-for-seed investments, philanthropic donations, and more. Entrepreneurial support programs have become ubiquitous, however they come in several types. Four main categories of early stage entrepreneurship support programs are outlined below.
The accelerator is a new form of financing and early stage entrepreneurship support program that was pioneered by Y Combinator in 2005. While the number of privately-funded accelerators has increased rapidly in the United States and worldwide, university-based and government-sponsored accelerators are growing in numbers as well. The typical accelerator consists of a time-boxed program with a combination of education, mentorship, and funding, often culminating in a demo day, but the exact structure and terms continue to diversify.
Privately-funded accelerators such as Y Combinator, Techstars, and 500 Startups operate primarily as early-stage investors in startups. Similar to venture capitalists and angel investors, accelerators invest in startups in exchange for equity, but the investment amount is much lower. Applications to this type of accelerator are typically open to any founder, and they are followed by a rigorous screening process to narrow down to the final cohort of startups. During the program, founders learn more about building a company through educational workshops, and are connected with various mentors affiliated with the accelerator. The large number of mentors is one of the distinguishing features of accelerators. Oftentimes, these accelerators also offer coworking spaces for the cohort, so founders are also able to learn and receive feedback from their peers. The end of the program is marked by demo day, which is an opportunity for founders to pitch their company in front of an audience with the goal of raising additional funding and awareness. Corporate-sponsored accelerators operate similarly, but usually with a focus on a specific industry sector or technology platform (such as Windows Azure).
The academic literature has largely focused on privately-funded accelerators, specifically, on how participation affects performance and learning outcomes Hallen, Bingham, and Cohen, 2014; Winston and Hannigan, 2015; Yu, 2015. While the findings on fundraising have been mixed, research consistently finds that companies that participate in accelerators go out of business faster—potentially a positive “fail faster” situation.
University-based accelerators such as StartX tend to emphasize education and entrepreneurial experience over financial returns. Moreover, often founders have to be affiliated with the university. The main difference between university and privately-funded accelerators is that founders receive grants rather than having to dilute the company in exchange for seed financing. In the handful of instances that university accelerators do extract equity, they tends to take lower percentages than non-university accelerators (~2-3%). These arrangements are also found more often in biotech and life science university incubators than more open tech incubators. Furthermore, many university accelerators are built around a structured curriculum such as Lean Launchpad and offer students their first exposure to entrepreneurship.
Government-sponsored initiatives such as Start-Up Chile and the Growth Accelerator Fund generally invest in accelerators rather than companies themselves. The primary goal is to encourage economic growth, which in turn attracts accelerators and startups focused on specific aspects of regional impact, such as job growth and education. While government-sponsored accelerators are still growing in numbers, there is some evidence that certain aspects of the accelerator, such as schooling services, can increase the performance of companies Gonzalez-Uribe and Leatherbee, 2016.
In addition to different sponsoring entities, accelerators may also differ by their technology focus. For example Y Combinator is industry-agnostic while QB3 admits only startups in life sciences. Furthermore, several accelerators focused on underrepresented groups, such as MergeLane, have also emerged as a vehicle to increase diversity in the entrepreneurship ecosystem.
Incubators have overlapping functions with accelerators—namely mentorship, technical assistance, and often some form of seed funding—yet they can be differentiated from accelerators in a few key ways as well. Incubators tend to be longer in duration, usually around two or three years, compared to the multi-month accelerator timeframes. The impact of Incubators on their portfolio companies is difficult to untangle, but research has suggested that incubation has mixed results: decreasing survival rates but improving sales growth in companies that "graduate" out of the space (Amezcua 2010) Incubators tend to have a broad range of local companies rather than cohorts of industry-specific companies. And incubators tend to provide physical infrastructure more often than the culminating demo day approach found more commonly in accelerators (Dempwolf, Auer, D’Ippolito, 2014). Coworking spaces share this emphasis on providing physical infrastructure with incubators, often with educational opportunities as well. Coworking spaces differ in that many allow freelancers or branches of small companies to occupy space, in addition to startup ventures.
Incubators themselves have different strategies and practices. In terms of selection strategies, some are idea-focused while others are entrepreneur-focused. Concurrently, some select earlier stage ventures with a “survival-of-the-fittest” approach, while others carefully vet already promising teams for a “picking-the-winners” approach. The range of business support and innovation exist along a continuum from laissez-faire to strong intervention. Some have an emphasis on certain technology or regional innovation area clusters (e.g., life sciences, hardware, social ventures), while others tend to be more open (Bergek and Norrman, 2008).
Different types of incubators tend to have different kinds of outcomes. Private and basic research incubators tend to outperform economic development incubators at achieving their goals, while university incubators appear somewhere in the middle (Barbero et al., 2012).
University incubators are a rapidly growing part of the incubator landscape, claiming about a third of the share of incubators in the U.S. (Torrance, 2013). Like incubators outside of the academy, they also display a wide range of quality and industry foci. More recently, incubators targeting student entrepreneurs have emerged and are spreading at a range of institutions, including lower-ranking universities and community colleges (Mars and Ginter, 2012).
Coworking spaces have many of the elements of incubators, however they are not always exclusively for startup ventures. They often include individual freelancers and small staff teams that may function as a satellite site of a larger company headquartered in another city. Most provide open floor plans with drop-in desks for a few hundred dollars a month, and with more expensive plans for designated desk space or private offices (Spinuzzi, 2012). Their effectiveness in spurring synergy, productivity, and knowledge sharing are still under review, but it does appear that proximity to colleagues has modest benefits (e.g. Parrino, 2015). Coworking spaces are a growing phenomenon in most U.S. cities in part because of rising interest in startups, but also because of the steady increase in alternative work arrangements in the new economy (e.g., freelance, independent contract, contingent, and part-time).
Prize competitions have a long and storied career in the history of innovation and entrepreneurship, including the solution to the calculation of longitude by English clockmaker and entrepreneur John Harrison (Sobel, 2007). Since the Longitude Prize, policy-makers have attempted to facilitate the entry and success of new innovative ideas through the creation of prize competitions for both the ideas themselves and new businesses that incorporate them. Prizes excel at inducing entry (especially heterogeneous) of new participants in an innovation ecosystem, but prize competitions also redirect labor and attention toward competition (potentially at the cost of useful work) so that prize competition design can have surprising consequences. Early theoretical work on the mechanism behind prize competitions has stressed monetary rewards, but the empirical work in prizes has suggested that non-monetary incentives seem to dominate monetary in the actual operation of prizes. The emerging empirical evidence on prize competitions has stressed the non-monetary impacts of competitions such as the signal value obtained by winning a competition (Brunt et al., 2012). Thus, prize competitions are one of the ways in which entrepreneurs can improve their capacity to gain access to critical resources. Another set of institutions that facilitate the process of resource acquisition are networking events which improve an entrepreneur's social capital. Taken together, competitions and prizes are critical institutions in an innovation ecosystem that facilitate the improvement of the capacity of early stage firms to gain resources.
Much of our understanding of prize competitions comes from the innovation literature that has focused on comparisons to other funding mechanisms. In his analysis of patents, prizes, and procurement, Wright shows that each of these mechanisms can be the optimal funding mechanisms in his model under different parameter conditions (Wright, 1983). Gallini and Scotchmer (2002) use patent design to explore the impact of institutions on how information aggregation shapes cumulative innovation, suggesting that critical information and capacity/willingness to pursue a new opportunity are not always housed in the same firm (Gallini and Scotchmer, 2002). A similar theme is echoed in Kremer and Williams (2010) who sketch out the trade-offs of a range of incentive mechanisms for innovation, stressing the importance of demand uncertainty as a main driver in market failures for products like vaccines (Kremer and Williams, 2010).
Other researchers have noted that there is a significant discrepancy between the theoretical motivation for prizes developed in the economics literature, which stresses the incentive effects of monetary reward, and the rationale for competition participation put forward by participants, who stress the importance of additional non-pecuniary receipts including novel information on customers, media attention, and a certification effect of winning (Murray et al., 2012). These non-monetary incentives evoke previous discussions by economists about the signaling rationale for participating in open source software development (Lerner and Tirole, 2002), but otherwise economic theory has remained relatively blind to the importance of non-monetary rewards.
One of the few empirical attempts to characterize the impact of prize competitions on innovation is Brunt et al. (2012) on the agricultural prizes in England where they find that the value of monetary rewards was not as important as the medals that were given out (Brunt et al., 2012). The participants in the agricultural prizes benefitted more from the credentialing effects of prizes as a signal of the quality of their innovation than from the direct resources provided. The importance of non-monetary rewards in prize competitions has also been found in modern prizes such as the X-Prize and Northrop Grumman’s Lunar Lander prize (Kay, 2011). Similarly, the benefit of SBIR grants by entrepreneurial firms is more in the signal value to other external funders than the dollar value of the grant (Lerner, 1999; Howell 2015). In that sense, prize competitions operate in much the same way as other status mechanisms that operate to enable entrepreneurs to acquire resources more easily (Stuart, Hoang, and Hybels, 1999; Waguespack and Fleming, 2009). Relatedly, participating in prestigious accelerators and incubators can have a similar status signaling effect on startups, providing nonmaterial value that goes beyond the seed money or physical space these programs offer. This effect contributes to the mixed results in the literature on the effectiveness of such programs.
Formal networking events also increase the capacity of entrepreneurs to acquire critical resources to build their new ventures. A plethora of studies have noted the importance of entrepreneurs’ initial social capital in determining the survival chances of a new company (Shane and Stuart, 2002; Shane and Cable, 2002; Hallen, 2008). At a more macro-level, regional studies have found that geographies with higher levels of social capital produce more successful startups (Laursen, Masciarelli, and Prencipe, 2012; Samila and Sorenson, 2013; Kwon, Heflin, and Ruef, 2013). Fewer studies have explored the mechanisms whereby startup founders can improve their social capital. The likelihood that entrepreneurs seek outside advice is moderated by the provision of networking events and the level of entrepreneurship in their area (Davidsson and Honig, 2003), but their ability to capitalize on these networking events is highly influenced by their status characteristics (e.g., race and gender) (Abraham, 2014).
Entrepreneurship education programs have become widespread in U.S. colleges and universities, numbering more than 5,000 thousand courses on entrepreneurism nationwide as of 2008, with continued growth since (Torrance, 2013). Nearly every accredited school of business in the country hosts at least one class if not several, and hundreds offer formal certificates and degrees in entrepreneurship. Nor are entrepreneurship programs limited to business schools, with programs springing up in engineering and computer science schools, medical schools, law schools, and more. Beyond post-secondary programs, entrepreneurship education programs are offered in a variety of contexts from secondary and vocational schools to students enrolled as part of an unemployment relief program (Valerio, Parton, and Robb, 2014). Indeed, internationally, entrepreneurship education has been deployed as part of an effort at poverty reduction in a large number of contexts (McKenzie and Woodruff, 2013). Yet despite the huge number of programs, the literature on entrepreneurial education programs offers less than straightforward answers on how effective they are at increasing entrepreneurial intention, rates of startups, and long-term venture success.
Part of the lack of clarity comes from conflicting research reports. Some of the contradictory findings, however, can be explained due to entrepreneurship education research that suffers from: (1) a lack of theoretical grounding; (2) lack of methodological rigor; (3) lack of examination of moderators—or confounding variables, like family exposure to entrepreneurism, race, class, gender, immigration status, nationality, etc.; and (4) and lack of longitudinal tracking (Honing and Martin, 2014).
A meta-analysis shows that despite some of these contradictory outcomes, overall a modest net positive influence exists between entrepreneurial education and entrepreneurial knowledge and skill, positive perceptions of entrepreneurship, intentions to become an entrepreneur, and to a lesser degree on startup creation and performance outcomes. Academic entrepreneurship education environments appear to be slightly more effective than training or non-academic environments (Martin et al., 2013).
Another review of the literature on entrepreneurial education outcomes—this one exclusively in higher education settings—similarly finds modest positive relationships between entrepreneurship education and various entrepreneurial outcomes, especially the subjective outcomes (e.g., intention to startup, inspiration, knowledge) over the objective outcomes (e.g., actually starting up, long-term venture survival, financial outcomes). Notably, the relationships were stronger where the education included an emphasis on experiential learning rather than primarily classroom-based pedagogies (Nabi et al., forthcoming).
Accelerators: While academic research related to accelerators has increased in recent years, there are still open questions surrounding the role of accelerators in the entrepreneurial process and their impact on the ecosystem as a whole. For example, do accelerator cohorts encourage founders or create competition? Do accelerators enable more entrepreneurship in a region? Furthermore, collecting data on nascent firms and having good counterfactuals for comparison remains a challenge. Quasi-experimental techniques and randomized controlled trials would be beneficial for establishing causal linkages between accelerators and performance outcomes.
Coworking Spaces: Future research on coworking spaces should look at the differences between spaces made up mostly or exclusively of entrepreneurs compared to those with varying proportions of freelancers and independent contractors. Do these groups share enough similarity in culture to benefit each other, or not? More work also needs done on the impact of spatial layout on synergy, information sharing, and productivity.
Incubators: Future research on incubators will benefit from attention given to the rapidly growing share of incubators found in universities. How do university-sponsored incubators compare with non-university sponsored incubators? Further, some evidence exists that startups may move between incubators, sometimes moving from less to more prestigious programs as the startup develops. Does this “fish-ladder” approach to moving between incubators enhance startup outcomes (by nurturing startups in evolving stages of development), or potentially hinder them (by putting unviable startups on “life support” for longer than they perhaps should be)?
Prize Competitions and Events: Future research on the impact of prize competitions and events should attempt to dissect the impact of the design of these institutions. In terms of prize competitions, researchers should focus on how the structure of judging impacts the startup firms that are selected and how the changes to prize terms vary the startups that apply to the competition. In terms of events, researchers can use the institution itself to understand better the mechanism whereby startup founders accrue and mobilize social capital in order to acquire the resources necessary to build their firms.
Educational Programs: Future research on the effectiveness of entrepreneurial education should improve by comparing several institutions (avoiding single institution studies), gaining a longitudinal over cross-sectional emphasis, drilling into the actual differences of course content and pedagogical styles (not all education is equal), as well as taking seriously variables related to the students (e.g., race, class, gender, previous entrepreneurial exposure). In addition, some evidence suggests that certain types of entrepreneurial education (e.g., a single course in business plan writing) actually can decrease the likelihood of the student attempting entrepreneurship. How do one or two courses, compared to a certificate, compared to a formal major or minor, and/or master’s degrees in entrepreneurship impact outcomes? Is it possible that undergraduates at the traditional age (18-22 years old) are not served well by an emphasis on the rigors of entrepreneurism, which detracts from their academics as well as more traditional internship experiences (nor appears to lead to high rates of sustainable venture creation)?
Abraham, M.L. 2014. “Explaining Unequal Returns to Social Capital among Entrepreneurs.” Abraham, 2014
Barbero, J. L., Casillas, J. C., Ramos, A., and Guitar, S. 2012. Revisiting incubation performance: How incubator typology affects results. Technological Forecasting and Social Change, 79: 888-902,
Bergek, A., and Norrman, C. 2008. Incubator best practice: A framework. Technovation, 28: 20-28.
Brunt, L., Lerner, J., and Nicholas, T. 2012. “Inducement Prizes and Innovation.” The Journal of Industrial Economics 60 (4): 657–96.
Davidsson, Per, and Benson Honig. 2003. “The Role of Social and Human Capital among Nascent Entrepreneurs.” Journal of Business Venturing 18 (3): 301–31. doi:10.1016/S0883-9026(02)00097-6.
Dempwolf, C. S., Auer, J., and D’Ippolito, M. 2014. Innovation accelerators: Defining characteristics among startup assistance organizations. Report for: U.S. Small BusinessAdministration. Downloaded Jan. 5, 2016.
Gallini, N., and S. Scotchmer. 2002. “Intellectual Property: When Is It the Best Incentive System?” Innovation Policy and the Economy 2: 51.
Hallen, Benjamin L. 2008. “The Causes and Consequences of the Initial Network Positions of New Organizations: From Whom Do Entrepreneurs Receive Investments?” Administrative Science Quarterly 53 (4): 685–718.
Hallen, B., C. Bingham, S. Cohen. 2014. Do accelerators accelerate? A study of Venture Accelerators as a Path to Success. Academy of Management Proceedings, 2014.
Honing, Benson and Bruce Martin. 2014. “Entrepreneurship Education.” In Alain Fayolle’s (ed), Handbook of Research on Entrepreneurship: What We Know and What We Need to Know. Northampton, MA: Edward Elgar.
Howell, Sabrina T. 2015. “Financing Constraints as Barriers to Innovation: Evidence from R&D Grants to Energy Startups.” Available at SSRN 2687457.
Kay, L. 2011. “The Effect of Inducement Prizes on Innovation: Evidence from the Ansari XPrize and the Northrop Grumman Lunar Lander Challenge.” R&D Management 41 (4): 360–77.
Kremer, M., and H. Williams. 2010. “Incentivizing Innovation: Adding to the Tool Kit.” Innovation Policy and the Economy 1-17..
Kwon, Seok-Woo, Colleen Heflin, and Martin Ruef. 2013. “Community Social Capital and Entrepreneurship.” American Sociological Review, 0003122413506440.
Laursen, Keld, Francesca Masciarelli, and Andrea Prencipe. 2012. “Regions Matter: How Localized Social Capital Affects Innovation and External Knowledge Acquisition.” Organization Science 23 (1): 177–93..
Lerner, J. 1999. “The Government as Venture Capitalist: The Long-Run Impact of the SBIR Program.” Journal of Business 72 (3).
Lerner, J., and J. Tirole. 2004. “The Economics of Technology Sharing: Open Source and Beyond.” National Bureau of Economic Research. Lerner and Tirole, 2002.
Mars, M. M., and Ginter, M. B. 2012. Academic innovation and autonomy: An exploration of entrepreneurship education within American community colleges and the academic capitalist context. Community College Review, 40(1): 75-95.
Martin B., McNally, J., and Kay, M. 2013. Examining the formation of human capital in entrepreneurship: A meta-analysis of entrepreneurship education outcomes. Journal of Business Venturing, 28(2): 211-224.
Murray, Fiona, Scott Stern, Georgina Campbell, and Alan MacCormack. 2012. “Grand Innovation Prizes: A Theoretical, Normative, and Empirical Evaluation.” Research Policy 41 (10): 1779–92.
Nabi, G., Linan, F., Fayolle, A., Kreuger, N., and Walmsley, A. 2016. The impact of entrepreneurship education in higher education: A systematic review and research agenda. Academy of Management Learning and Education, Available online ahead of print at: Academy of Management Learning & Education.
Parrino, Lucia. 2015. Coworking: Assessing the role of proximity in knowledge exchange. Knowledge Management Research & Practice, 13(3): 261-271.
Samila, Sampsa, and Olav Sorenson. 2013. “Community and Capital in Entrepreneurship.” In 35th DRUID Celebration Conference. Barcelona. http://druid8.sit.aau.dk/druid/acc_papers/nnrdn2fh9i12hx7lvugvlh873l2p.pdf.
Shane, Scott, and D. Cable. 2002. “Network Ties, Reputation, and the Financing of New Ventures.” Management Science, 364–81.
Shane, Scott, and Toby Stuart. 2002. “Organizational Endowments and the Performance of University Start-Ups.” Management Science 48 (1): 154–70.
Sobel, D. 2007, Sobel, 2007. Longitude. HarperPerennial.
Spinuzzi, Clay. 2012. Working Alone Together: Coworking as Emergent Collaborative Activity. Journal of Business and Technical Communication, 26(4): 399-441.
Stuart, Toby, Ha Hoang, and Ralph C. Hybels. 1999. “Interorganizational Endorsements and the Performance of Entrepreneurial Ventures.” Administrative Science Quarterly 44 (2): 315–49. doi:10.2307/2666998.
Torrance, Wendy E. F. 2013. “Entrepreneurship Education Comes of Age on Campus: The Challenges and Rewards of Bringing Entrepreneurship to Higher Education.” Ewing Marion Kauffman Research Paper. Available at SSRN.
Gonzalez-Uribe, Juanita and Leatherbee, Michael, The Effects of Business Accelerators on Venture Performance: Evidence from Start-Up Chile (August 11, 2016). Available at SSRN.
Winston, S.W., and TJ Hannigan. 2014. “Home Run, Strike Out, or Base Hit: How Do Accelerators Impact Exit and VC Financing in New Firms?” Academy of Management Proceedings 2014 (1), 13811
Waguespack, D. M, and Lee Fleming. 2009. “Scanning the Commons? Evidence on the Benefits to Startups Participating in Open Standards Development.” Management Science 55 (2): 210–23.
Wright, B.D. 1983. “The Economics of Invention Incentives: Patents, Prizes, and Research Contracts.” The American Economic Review 73 (4): 691–707.
Yu, S. 2015. “How Do Accelerators Impact High-Technology Ventures.” Working paper. Available at SSRN
Daniel Colin Fehder - University of Southern California, Marshall School of Business, Contributor
Sandy Yu -
University of California, Berkeley, Contributor
Daniel Davis -
University of California, San Diego, Contributor