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Startup Sustainability Forecasting with Artificial Intelligence.

Authors :
Takas, Nikolaos
Kouloumpris, Eleftherios
Moutsianas, Konstantinos
Liapis, Georgios
Vlahavas, Ioannis
Kousenidis, Dimitrios
Source :
Applied Sciences (2076-3417); Oct2024, Vol. 14 Issue 19, p8925, 13p
Publication Year :
2024

Abstract

In recent years, we have witnessed a massive increase in the number of startups, which are also producing significant amounts of digital data. This poses a new challenge for expert analysts due to their limited attention spans and knowledge, also considering the low success rate of empirical startup evaluation. However, this new era also presents a great opportunity for the application of artificial intelligence (AI) towards intelligent startup investments. There are only a few works that have considered the potential of AI for startup recommendation, and they have not paid attention to the actual requirements of investors, also neglecting to investigate the desirability, feasibility, and value proposition of this venture. In this paper, we answer these questions by conducting a survey in collaboration with three major organizations of the Greek startup ecosystem. Furthermore, this paper also presents the design specifications for an AI-based decision support system for forecasting startup sustainability that is aligned with the requirements of expert analysts. Preliminary experiments with 44 Greek startups demonstrate Random Forest's strong ability to predict sustainability scores. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
14
Issue :
19
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
180273542
Full Text :
https://doi.org/10.3390/app14198925