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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM56345
Volume:
10 |
2 |
Feb 2026
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The rapid expansion of the startup ecosystem has increased the need for accurate and data-driven methods to evaluate new ventures. Startups often face high failure rates due to poor market fit, financial uncertainty, and subjective decision-making during early evaluation stages. Traditional startup assessment approaches rely on manual analysis, expert opinions, and fragmented tools, which are time-consuming and prone to bias. As a result, investors and founders may struggle to identify viable opportunities and manage risks effectively.
KEYWORDS
Publication Date
3/1/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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