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Determination of essential features for predicting start-up success: an empirical approach using machine learning
16 references·0 citing·56 second hop
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References

  • 2012The Startup Owner's Manual: The Step-By-Step Guide for Building a Great Company1,016 cited
  • 2009Entrepreneurs' Optimism And New Venture Performance: A Social Cognitive Perspective988 cited
  • 2007Success Factors in New Ventures: A Meta‐analysis*507 cited
  • 2013Rank Ordering Criteria Weighting Methods – a Comparative Overview361 cited
  • 2014Does innovativeness reduce startup survival rates?359 cited
  • 2018Toward a Theory of International New Ventures359 cited
  • 2018Do business incubators really enhance entrepreneurial growth? Evidence from a large sample of innovative Italian start-ups203 cited
  • 2016Why businesses succeed or fail: a study on small businesses in Pakistan186 cited
  • 2021A machine learning, bias-free approach for predicting business success using Crunchbase data118 cited
  • 2020Forecasting technological positioning through technology knowledge redundancy: Patent citation analysis of IoT, cybersecurity, and Blockchain117 cited
  • 2020Internationalization and Digitalization: Applying digital technologies to the internationalization process of small and medium-sized enterprises108 cited
  • 2019Assessment of Machine Learning Performance for Decision Support in Venture Capital Investments99 cited
  • 2021Cross-country differences in the size of venture capital financing rounds: a machine learning approach77 cited
  • 2018

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From Uncertainties to Successful Start Ups: A Data Analytic Approach to Predict Success in Technological Entrepreneurship
73 cited
  • 2017Finding the Unicorn: Predicting Early Stage Startup Success Through a Hybrid Intelligence Method72 cited
  • 2020A structural analysis approach to identify technology innovation and evolution path: a case of m-payment technology ecosystem68 cited
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