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A Graph Analytics Methodology for Analyzing Startup Ecosystems

In: Business Analytics and Decision Making in Practice

Author

Listed:
  • 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)

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.

Suggested Citation

  • Ali AlKatheeri & Saif Abdulmajeed & Abdulla Albedwawi & Abdulalrheem AlSheebany & Samir Safi & Gurdal Ertek, 2024. "A Graph Analytics Methodology for Analyzing Startup Ecosystems," Lecture Notes in Operations Research, in: Ali Emrouznejad & Panagiotis D. Zervopoulos & Ilhan Ozturk & Dima Jamali & John Rice (ed.), Business Analytics and Decision Making in Practice, chapter 0, pages 63-71, Springer.
  • Handle: RePEc:spr:lnopch:978-3-031-61589-4_6
    DOI: 10.1007/978-3-031-61589-4_6
    as

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