Abstract
Startup companies are engines of economic growth and diversity. A unicorn company is a privately held start-up company that has grown to a valuation of over $1 billion. As of January 2023, there were over 1,200 unicorn companies worldwide. In this study, we present a custom-developed graph analytics methodology for the systematic analysis of unicorn and startup ecosystems. We show the applicability of and insights obtained by the methodology through a case study using a public dataset on unicorn companies. Graph analytics through algorithmically generated visualizations can enable the derivation and understanding of meaningful insights, even by non-technical analysts and decision-makers in entrepreneurship ecosystems and government organizations.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Operations Research |
| Publisher | Springer Nature |
| Pages | 63-71 |
| Number of pages | 9 |
| DOIs | |
| Publication status | Published - 2024 |
Publication series
| Name | Lecture Notes in Operations Research |
|---|---|
| Volume | Part F3798 |
| ISSN (Print) | 2731-040X |
| ISSN (Electronic) | 2731-0418 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
Keywords
- Entrepreneurship
- Graph analytics
- Innovation management
- Startup ecosystems
- Technology management
- Unicorn companies
ASJC Scopus subject areas
- Management Science and Operations Research
- Statistics, Probability and Uncertainty
- Applied Mathematics
- Control and Optimization
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