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Researcher Joda Thongnopnua presents at the UMM Conference, 2019.

Collaboration in action: Researchers share Uncommon Methods and Metrics

As communities across the nation continue to adopt a new economic model that infuses entrepreneurship into their economies, a group of researchers is collaborating to develop new ways to measure these efforts.

The Kauffman Foundation-funded Uncommon Methods and Metrics portfolio of researchers met recently to share progress on their innovative approaches to measuring entrepreneurship.

Because traditional datasets and methods for measuring the impact of entrepreneurial ecosystems are neither timely nor granular enough to provide mayors and other local officials the insights needed to make decisions, the UMM researchers are exploring new methods to produce just-in-time data about ecosystems measurements on behalf of communities. The primary goal is to build open-source data and metrics that researchers, entrepreneurs, and policy staff can adapt to their own locales.

The UMM researchers are building customizable data infrastructures that will help communities build and evaluate their entrepreneurial ecosystems in real time.

Evan Absher
Senior program officer in Entrepreneurship, Kauffman Foundation

“Mayors and other local leaders understand better than anyone how vital entrepreneurs are to their communities as job and wealth generators,” said Evan Absher, senior program officer in Entrepreneurship at the Kauffman Foundation. “The UMM researchers are building customizable data infrastructures that will help communities build and evaluate their entrepreneurial ecosystems in real time. This level of detail has never been available before, so it’s imperative the researchers share findings and solutions with each other.”

Nearly a year into their UMM initiatives, 16 teams comprised of independent and institutional researchers presented the status of their projects, what’s working and what isn’t, what they need help with, and what they’ve learned from collaborating with each other.

“This meeting provided different perspectives on our work from other experts investigating entrepreneurship to help us maximize the value of our research,” said Daniel Basco, president of Vertex Evaluation and Research, LLC. “We couldn’t do this from just sharing in an email or presenting at a conference.”

Basco and research partner Troy Smith, associate economist at the RAND Corporation, are applying a machine-learning algorithm used in defense to identify local and state laws that influence entrepreneurial behavior. Once complete, local leaders will be able to identify policies to adopt or modify to help spur greater entrepreneurship.

Other innovative ways UMM researchers are seeking granular but scalable data in their quests to build new data infrastructure include using coding and hacker methods, creating a variety of ecosystem mapping strategies, and moving beyond scraping text to scraping images to expand findings.

Another UMM team is combining complementary strengths to take a novel approach to identifying biases in venture capital practices. With Paolo Gaudiano’s entrepreneurial and analytical experiences as founder of Aleria and Banu Özkazanç-Pan’s social science perspective as associate professor of Management at University of Massachusetts Boston, the team is collecting survey data and running simulations of how venture capitalists (VCs) and entrepreneurs interact, to identify biases and test how different behavioral changes can influence outcomes.

“This new methodology is a powerful way to understand inclusion and diversity and how both VCs and entrepreneurs can adjust behavior to improve access to each other and opportunities,” said Gaudiano.

Creating diversity and inclusion metrics are priorities in the UMM portfolio, so the researchers discussed more ways to incorporate different views into their research. Ideas included reassessing hiring practices to ensure a diverse pool of researcher applicants, including rural populations in surveys to capture different political opinions, including diversity variables in datasets, and creating an advisory board from different segments of the population to ensure broader input.

Researchers will continue working on their respective projects for the next two years, collaborating with the Kauffman Foundation and each other as their work progresses.


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