Dalia Silberstein
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Dalia Silberstein has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Benjamin Gidron
Ben Gurion University of the Negev
1 shared publication - Daniela Kandel
Innovation Bridges Department, Start-Up Nation Central (SNC), Tel Aviv 6513307, Israel
1 shared publication - Kfir Bar
School of Computer Science, College of Management Academic Studies, Rishon LeZion, Israel Basis Technology, MA, USA
1 shared publication - Michael Lustig
Center for Impact Investing & Entrepreneurship, The College of Management Academic Studies, Rishon LeTsiyon 7579806, Israel
1 shared publication - Yael Israel-Cohen
School of Behavioral Sciences & Psychology, The College of Management Academic Studies, Rishon LeTsiyon 7579806, Israel
1 shared publication
Latest Publications
- Open Access
- 8 September 2021
- Published by MDPI AG in Sustainability
- Vol. 13 (18) , 10048
Impact Tech Startups: A Conceptual Framework, Machine-Learning-Based Methodology and Future Research Directions
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.
- 8 September 2021
- Published by MDPI AG in Sustainability
- Vol. 13 (18) , 10048
Open AccessImpact Tech Startups: A Conceptual Framework, Machine-Learning-Based Methodology and Future Research Directions
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.