A Graph Analytics Methodology for Analyzing Startup Ecosystems
Ali AlKatheeri (),
Saif Abdulmajeed (),
Abdulla Albedwawi (),
Abdulalrheem AlSheebany (),
Samir Safi () and
Gurdal Ertek ()
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Ali AlKatheeri: United Arab Emirates University
Saif Abdulmajeed: United Arab Emirates University
Abdulla Albedwawi: United Arab Emirates University
Abdulalrheem AlSheebany: United Arab Emirates University
Samir Safi: United Arab Emirates University
Gurdal Ertek: United Arab Emirates University
Chapter Chapter 6 in Business Analytics and Decision Making in Practice, 2024, pp 63-71 from Springer
Abstract:
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.
Keywords: Graph analytics; Unicorn companies; Startup ecosystems; Technology management; Entrepreneurship; Innovation management (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-031-61589-4_6
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DOI: 10.1007/978-3-031-61589-4_6
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