Knowledge Challenge Special Interest Areas
Kauffman Knowledge Challenge
The following four Special Interest Areas indicate topics and questions of interest for the Kauffman Knowledge Challenge. These areas of interest are not mutually exclusive and proposers are not limited to the sample questions identified below.
Special Interest Areas
Successful projects should have a sound scientific approach and should clearly describe how they will advance current knowledge and how these insights will benefit entrepreneurs and those that aim to support them. Successful projects will clearly articulate how the findings will yield tangible and actionable insights for users and beneficiaries of the research. Research projects should aim to balance specific project components with the potential for scalability and generalizability of the expected findings.
The Foundation is interested in research that identifies causal links for effective action to support entrepreneurship. Designing programs and policies without evidence on the effectiveness of specific design features is challenging. For example, entrepreneurship support programs have a variety of support tools they can offer to entrepreneurs, but their effectiveness could vary based on the tool (or combination of tools), timing and the target entrepreneurs. If an intervention will target a specific group of entrepreneurs, how should the program manager identify needs in the ecosystem, identify potential participants, conduct screening and determine what kind and what level of support to provide, and for how long?
Preference will be given to studies that pilot new methods, novel qualitative and quantitative data collection, new analytical approaches to existing data and/or the creation of data and analyses at scale. Projects that consider heterogeneity of different components in the entrepreneurial ecosystem are encouraged. For example, several key factors in an ecosystem can affect women entrepreneurs, but some may dominate in size of the effect. Projects that consider heterogeneity in entrepreneurship outcomes also are encouraged. For example, new firms in the logistics sector and in the informatics sectors may respond very differently to the same condition in a shared ecosystem, e.g., depth of financial networks.
The Foundation also values geospatially referenced data across multiple geographic scales and in analyses that appropriately embed the entrepreneur in multiple levels of action, influence and decision-making. Considering multiple levels also can be useful to disentangle the effects of program interventions, such as outcomes at the entrepreneur level, the neighborhood level, the industry level and so on. An example of gains from multilevel research is the creation of specific information for local policymakers that need to consider how potential policy action could enhance or mitigate the effect of state- or federal-level policies on entrepreneurs or investors.
The Foundation is interested in proposals that validate or leverage validated approaches from a wide range of disciplines and that can result in methodological gains. Multidisciplinary projects and projects that leverage big data in a rigorous manner are encouraged, as are projects rooted in a complex systems perspective. Approaches of interest include, but are not limited to: anthropology, evolutionary biology, cognitive science, computer science, complex systems, criminal justice, decision systems, ecology, economics, engineering, finance, mathematics, medicine, neuroscience, political science, psychiatry, psychology, robotics and sociology.
Overlap and collaboration across the Special Interest Areas is expected, but proposers should focus on the most relevant area for their work.
- Special Interest Area 1: Technology and the new nature of entrepreneurship
- Special Interest Area 2: Gaps and entrepreneurship
- Special Interest Area 3: Culture and entrepreneurship
- Special Interest Area 4: Causal research on entrepreneurship interventions at scale
Special Interest Area 1: Technology and the new nature of entrepreneurshipThe first industrial revolution unlocked economic growth and better lives by augmenting muscles with machines. Now, machines are augmenting minds. The internet, artificial intelligence, machine learning, virtual reality, new work platforms and other major technological advances have reshaped the way people work and interact. Indeed, the nature of work itself has shifted, as have labor markets, industries and local economies affected by these technologies. The new nature of entrepreneurship is characterized by the growth of nontraditional employment arrangements, such as workers who also work in alternative work arrangements, including the “platform” or “gig” economy.
The future is about people and about work. Economic activity can no longer be captured by measuring only firms and jobs. New approaches to understanding, measuring and influencing economic activity are necessary to keep up with the changing nature of technology, labor, work and entrepreneurship.
Sample topics include:
- How do people participate in the new ways work and entrepreneurship are conducted? Who participates and who faces barriers – and why? How do we measure participation in the future of work?
- How do we measure work in the future? What can be explained by established measures, like wages or new firm formation, and what types of new metrics can be validated?
- How does the gig economy intersect with entrepreneurship? Is it a stepping stone to entrepreneurship? Do entrepreneurs benefit from the growth of the gig economy? How does technology shape the relationship between the gig economy and the entrepreneur? Do workers in the gig economy view themselves as entrepreneurs?
- To what degree does technological advancement create or reduce barriers to entrepreneurs and/or industry concentration? How do platforms, like online marketplaces, change an entrepreneurial ecosystem?
- What does digitalization mean for entrepreneurs and for the organizations that support them? What can be done to achieve inclusion? How can entrepreneurship support organizations leverage digitization for their programs?
- What kind of education and training programs fit a future where people will need entrepreneurial skills to work?
- What are the major implications and potential shifts for regional economies and for labor markets? What does the future of work mean for local economies, like cities and counties? What are the geospatial characteristics of changing work arrangements?
- How do alternative work arrangements affect employer firm starts? How are declining entrepreneurship rates linked to decline in mobility and increased inequality? What interventions are best positioned to improve these conditions? Who – and how – should identify, design and manage these approaches?
- What types of programs and organizational structures can effectively manage the future of work transitions?
Special Interest Area 2: Barriers to entrepreneurshipResearch indicates that a variety of demographic, socioeconomic and geographic barriers stand in the way of potential entrepreneurs, keeping them from founding and growing new businesses. The Foundation is interested in projects that identify barriers that prevent people from becoming entrepreneurs. Much of the current research on entrepreneurs is conducted on individuals who have become, or are in the process of becoming, entrepreneurs. An important knowledge gap is on who is not becoming an entrepreneur and why. Approaching this question from a complex systems perspective can provide insight on the relative role of new or surprising factors.
Minority and female founders are underrepresented in entrepreneurship and among small business owners more broadly. Rural regions face greater challenges in building entrepreneurial ecosystems. Specific ecosystems also may harbor barriers tied to immigration status, including type of immigration status, ethnicity, religion, race, educational status and age.
Access to capital also may be salient from the perspective of barriers to entrepreneurship. There are persistent racial and ethnic gaps in access to credit. Some minorities experience less-favorable loan application outcomes. These barriers disproportionately hurt segments of the population and can result in disproportionate participation in industries with low capital requirements and high failure rates. While much research has been conducted on private equity and on microcredit, the majority of entrepreneurs in the United States do not access these types of financing. There remains a large gap in our knowledge about other types of financing and, more broadly, how entrepreneurs access the capital they need.
There may be intersections of criminal justice and entrepreneurship. Recidivism and successful reintegration are tied to economic participation, and entrepreneurship presents a unique mechanism to accomplish reentry to the labor market. Research from various disciplines has left this topic unexplored, despite a growing number of programs serving this population.
The complexity of gaps can be linked not only to heterogeneity in the ecosystem, but also to characteristics of the entrepreneur, the industry and the type of activities being undertaken. For example, occupational licensing regulations in some industries or in some geographic areas may disproportionately hurt some entrepreneurs more than others. The same conditions that favor some entrepreneurs can create barriers for other entrepreneurs.
The Foundation is interested in studies that identify specific barriers to entrepreneurship and their effects and in research on interventions that effectively reduce gaps in who participates in entrepreneurship. Programs and policies aimed at reducing barriers to entrepreneurship present an opportunity for research to focus on disentangling key causal relationships.
Sample topics include:
- Are certain groups of entrepreneurs differentially impacted by increasing industry and firm concentration?
- Are there specific “decision points” at which specific groups opt out of entrepreneurship? What interventions might help entrepreneurs overcome barriers at these points?
- What action will mitigate or close a specific barrier? What key barriers affect specific demographic groups? For example, if a particular ethnic group faces a key identifiable barrier, e.g., access to capital or logistics networks, what is the most effective way to mitigate the barrier? What level, e.g., city programs or state policy, is effective?
- How do subnational regional economies (e.g., cities, counties, states) close gaps in entrepreneurship? What mechanisms can achieve this, and what methods of implementation are promising? How is an entrepreneur affected by action taken at different levels of government or different types of public and private activities?
- How do policy decisions unintentionally create or reduce barriers to entrepreneurship?
- Are targeted policies (focused on entrepreneurs specifically) versus nontargeted policies (focused on broader economic gains) more effective in creating favorable conditions or inputs for entrepreneurs?
- Do some policies, such as occupational licensing or non-compete agreements, affect some groups disproportionately? What are the implications for program or policy design?
- Beyond private equity and direct lending, what other types of financing (e.g., revenue-share or dividend-based financing, factoring, royalty/licensing) can entrepreneurs access? How do target outcomes compare in these alternative forms of financing?
- What strategies do investors pursue to mitigate bias in investment decisions (alternative selection mechanisms, data/technology)? What outcomes are associated with these?
- What strategies can be used to form capital in particular geospatial units and/or sectors?
- Are declines in entrepreneurship more broadly linked to declines in economic mobility?
Special Interest Area 3: Culture and entrepreneurshipThe Foundation is interested in research that can identify the influence of culture for the entrepreneur. Culture, broadly defined, can exist at multiple levels and could influence the entrepreneur in many ways, e.g., through family, schooling, neighborhoods, ethnic group, immigration status, religious identity, geographic location and industry. Dimensions of culture also can be visible or hidden within a broader system.
Disentangling the role of culture could be relevant, for example, to understanding the clustering of some immigrant groups or some ethnic groups by industry. The relative role of culture in driving entrepreneurial decision-making, compared to other influences, could have important implications for program and policy targeting and design. For example, ecosystem builders will benefit from new templates and tools to identify influencers, mentors and assets in a community.
Similarly, an understanding of how culture influences entrepreneurial motivations could assist the design of programs intended to identify, mentor and train potential entrepreneurs. This can lead to more effective targeting and significant cost savings for entrepreneurship support organizations. Further, a better understanding of the role that culture and social interactions play in entrepreneurship could help inform decisions made by local policymakers intent on fostering entrepreneurship in their own communities.
The question of personal, psychological and social-psychological motivators and barriers to entrepreneurship also are closely related to culture. Of particular interest are studies of interventions that help cultivate motivation and/or overcome barriers among potential entrepreneurs.
An important question is the degree to which entrepreneurship is viewed socially as legitimate, not limited just to those with greater risk tolerance and who do not fear failure. This can vary widely across ecosystems, as well as by gaps relevant to Special Interest Area 2. Attitudes toward entrepreneurship may be passed along or modified through social interactions, but the nature of the effect (size and direction) can vary based on the individual.
Sample topics include:
- How do we measure culture as it relates to entrepreneurship and the environment in which the entrepreneur is embedded? How do concepts like lifestyle, social interaction, quality of life, amenities and geographical attractiveness influence the entrepreneur?
- Within an entrepreneurial ecosystem, are some levels of culture more influential than others? For example, among immigrant entrepreneurs, are there cultural legacies through family that dominate or fade in the presence of a city’s culture or schooling?
- What does an entrepreneurial mindset look like, and what kind of cultural influences matter? How do these matter, relative to other influences in the ecosystem? How can program interventions influence mindset, and what design features can be most effective?
- How do the media and popular messaging around entrepreneurship influence the way people think and act in the entrepreneurial process? Are some influences positive and are some negative? For example, some business owners do not self-identify as entrepreneurs – is there a cultural component to this?
- Can interventions to cultivate an entrepreneurial mindset in educational institutions be effective? What kind would be most effective, and at what age and level of schooling?
- How do social/peer effects influence the decision to become an entrepreneur? Are there methods of measuring this using new tools such as social network analysis?
- How can researchers identify the relative importance of key influences in a community or entrepreneurial ecosystem? Do these vary by role and industry (e.g., funders, educators, mentors, etc.), and do these vary in their importance to different types of entrepreneurs (e.g., women, tech) in an ecosystem?
Special Interest Area 4: Causal research on entrepreneurship interventions at scaleThe Foundation is interested in multi-site causal research that tests specific interventions designed to overcome barriers to entrepreneurship. Insight from causal research can be useful for the work of entrepreneurship support organizations and ecosystem builders, including the Foundation, and for policymakers.
Randomized Control Trials (RCTs) and high-quality quasi-experimental studies can be effective in identifying the causal impact of a particular intervention and on a specific group of people. However, they can have limited generalizability, which limits their usefulness in informing program and/or policy design. As such, the Foundation is interested in projects that exploit rigorous causal research across multiple ecosystems which, by nature of being systems, comprise many moving parts.
The Foundation also is interested in methodological advancements that facilitate causal research at scale.
Research conducted in Special Interest Area 4 is likely to be closely tied to the other Special Interest Areas in terms of substance and topic. The focus for this Area is on expanding the scope of causal research and on identifying methodological constraints and opportunities to enhance this research.
Collaborations between entrepreneurship support organizations and researchers are encouraged, particularly with organizations that operate in several ecosystems.
Samples topics include:
- RCTs conducted across multiple sites.
- Are there specific types of programs, or combinations of programs, that yield better outcomes for entrepreneurs? Do these outcomes change based on the entrepreneur?
- The creation of new methods that can be used for causal research on entrepreneurship, and how they compare to existing methods.
- What level of intervention is most influential for determining impact on the entrepreneur?
- What lessons can be provided to program managers in entrepreneurship support organizations who are concerned with implementation of their programs? For example, how should they determine eligibility criteria for participation in a program? How should the selection process be designed, if a program is competitive?
- Comparison of RCT results with results from other statistical methods to test the robustness of traditional quasi-experimental design approaches in the entrepreneurship context.