Machine Learning Insights into the Influence of Business Incubators on Startup Success

The paper emphasises the effect of incubator services on startup success indicators such as revenue growth and survival rates. This paper creates a prediction framework that links crucial incubation services to startup success outcomes using machine learning models. This study qualitative in nature. The results show how important incubator services are for improving startup performance. To forecast startup results based on the availability of particular incubation services, a machine learning-powered recommendation engine was developed. Policymakers and incubator managers might use the findings to customise support services for a bigger impact. By filling in gap or literature in this domain about the direct correlation between incubation services and company success, the study adds to the body of literature on entrepreneurship and provides a data-driven approach to optimizing business incubators.

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Publication Details

Published
2025-02-06
DOI
https://doi.org/10.1109/cictn64563.2025.10932614
Citations
4
Primary Topic
Entrepreneurship Studies and Influences
Type
article
Field-Weighted Citation Impact
11.04
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article

Machine Learning Insights into the Influence of Business Incubators on Startup Success

Shagun Tyagi, Amit Rawat, Akhilesh Sharma, Kapil Ahalawat
4 citations
Entrepreneurship Studies and Influences
11.04
article

Machine Learning Insights into the Influence of Business Incubators on Startup Success

Shagun Tyagi, Amit Rawat, Akhilesh Sharma, Kapil Ahalawat
article en
4 citations

Abstract

The paper emphasises the effect of incubator services on startup success indicators such as revenue growth and survival rates. This paper creates a prediction framework that links crucial incubation services to startup success outcomes using machine learning models. This study qualitative in nature. The results show how important incubator services are for improving startup performance. To forecast startup results based on the availability of particular incubation services, a machine learning-powered recommendation engine was developed. Policymakers and incubator managers might use the findings to customise support services for a bigger impact. By filling in gap or literature in this domain about the direct correlation between incubation services and company success, the study adds to the body of literature on entrepreneurship and provides a data-driven approach to optimizing business incubators.

Graphic Era University (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 2%
Entrepreneurship Studies and Influences
11.04
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