The Influence of Various Factors in a Startup’s Success: A Comprehensive Study

This study explores the many factors that contribute to the success of startups, examining a wide range of elements that can influence their outcomes. By analyzing over 4,000 cases, the research uses advanced statistical and machine learning techniques like Decision Trees, Random Forests, and Gradient Boosting to assess how well different startup traits can predict success. These traits include the industry, location, how long the company has been around, the number of previous ventures the founders have launched, and their educational backgrounds. The results reveal important predictors of success, shedding light on how these factors shape outcomes. With highly accurate predictive models, the study provides valuable insights for those involved in the startup world, offering a solid foundation for making informed decisions. Beyond contributing to the academic conversation on startup success, this research gives entrepreneurs and stakeholders practical, data-driven strategies to navigate the competitive startup environment.

Authors

Institutions

Publication Details

Journal
Journal of Student Research
Published
2025-02-28
DOI
https://doi.org/10.47611/jsrhs.v14i1.8516
Primary Topic
Entrepreneurship Studies and Influences
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Influence of Various Factors in a Startup’s Success: A Comprehensive Study

Akshaj Nadimpalli, Aliya Babul
Journal of Student Research
Entrepreneurship Studies and Influences
article

The Influence of Various Factors in a Startup’s Success: A Comprehensive Study

Akshaj Nadimpalli, Aliya Babul
article en

Abstract

This study explores the many factors that contribute to the success of startups, examining a wide range of elements that can influence their outcomes. By analyzing over 4,000 cases, the research uses advanced statistical and machine learning techniques like Decision Trees, Random Forests, and Gradient Boosting to assess how well different startup traits can predict success. These traits include the industry, location, how long the company has been around, the number of previous ventures the founders have launched, and their educational backgrounds. The results reveal important predictors of success, shedding light on how these factors shape outcomes. With highly accurate predictive models, the study provides valuable insights for those involved in the startup world, offering a solid foundation for making informed decisions. Beyond contributing to the academic conversation on startup success, this research gives entrepreneurs and stakeholders practical, data-driven strategies to navigate the competitive startup environment.

Journal of Student ResearchVol. 14(1)
Windsor Dermatology (US)
Openalex Percentile: Top 70%
Entrepreneurship Studies and Influences
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.