Models and Tools for Technology Start-Up Companies Success Analysis
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References listed on IDEAS
- James J. Chrisman & Alan Bauerschmidt & Charles W. Hofer, 1998. "The Determinants of New Venture Performance: An Extended Model," Entrepreneurship Theory and Practice, , vol. 23(1), pages 5-29, October.
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Cited by:
- Stanley Ibeku, 2018. "Organisational Learning, Innovation And Performance Of Technology Start-Ups In Lagos, Nigeria," International Journal of Innovation Management (ijim), World Scientific Publishing Co. Pte. Ltd., vol. 22(03), pages 1-15, April.
- Sheetal Malik & Praveen Sahu, 2024. "Significant entrepreneurial factors: a regional perspective," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 14(1), pages 1-10, December.
- Falco J. Bargagli-Stoffi & Jan Niederreiter & Massimo Riccaboni, 2020. "Supervised learning for the prediction of firm dynamics," Papers 2009.06413, arXiv.org.
- Dafei Yin & Jing Li & Gaosheng Wu, 2021. "Solving the Data Sparsity Problem in Predicting the Success of the Startups with Machine Learning Methods," Papers 2112.07985, arXiv.org.
- Macalik Joanna, 2023. "Personal Brand — Instructions of Use. Do Young Professionals Want and Need to be Taught Personal Branding?," Marketing of Scientific and Research Organizations, Sciendo, vol. 48(2), pages 41-60, June.
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More about this item
Keywords
technology start-ups; success prediction; prediction tool; start-ups analysis;All these keywords.
JEL classification:
- M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
- C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
Statistics
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