Impact Tech Startups: A Conceptual Framework, Machine-Learning-Based Methodology and Future Research Directions

Benjamin Gidron, Yael Israel-Cohen, Kfir Bar, Dalia Silberstein, Michael Lustig and Daniela Kandel
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Benjamin Gidron: Research Authority, The College of Management Academic Studies, Rishon LeTsiyon 7579806, Israel
Yael Israel-Cohen: School of Behavioral Sciences & Psychology, The College of Management Academic Studies, Rishon LeTsiyon 7579806, Israel
Kfir Bar: School of Computer Science, The College of Management Academic Studies, Rishon LeTsiyon 7579806, Israel
Dalia Silberstein: Center for Impact Investing & Entrepreneurship, The College of Management Academic Studies, Rishon LeTsiyon 7579806, Israel
Michael Lustig: Center for Impact Investing & Entrepreneurship, The College of Management Academic Studies, Rishon LeTsiyon 7579806, Israel
Daniela Kandel: Innovation Bridges Department, Start-Up Nation Central (SNC), Tel Aviv 6513307, Israel

Sustainability, 2021, vol. 13, issue 18, 1-15

Abstract: The Impact Tech Startup (ITS) is a new, rapidly developing type of organizational category. Based on an entrepreneurial approach and technological foundations, ITSs adopt innovative strategies to tackle a variety of social and environmental challenges within a for-profit framework and are usually backed by private investment. This new organizational category is thus far not discussed in the academic literature. The paper first provides a conceptual framework for studying this organizational category, as a combination of aspects of social enterprises and startup businesses. It then proposes a machine learning (ML)-based algorithm to identify ITSs within startup databases. The UN’s Sustainable Development Goals (SDGs) are used as a referential framework for characterizing ITSs, with indicators relating to those 17 goals that qualify a startup for inclusion in the impact category. The paper concludes by discussing future research directions in studying ITSs as a distinct organizational category through the usage of the ML methodology.

Keywords: SDG; social enterprises; Impact Tech; startups; hybrid ventures; entrepreneurship; innovation; impact investing; machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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