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Rethinking New Venture Growth: A Time Series Cluster Analysis of Biotech Startups’ Heterogeneous Growth Trajectories

  • Vincent Göttel*
  • , Yasmina Lichtinger
  • , Andreas Engelen
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Startups are crucial job creators and drivers of economic growth. Research on startups has predominantly targeted high-growth startups, while a comprehensive understanding of alternative growth journeys remains limited. Addressing this gap, we employ the theory of early firm growth and the time-calibrated theory of entrepreneurial action to examine 416 biotech startups. We use time series cluster analysis to unveil four heterogeneous new venture growth trajectories. These are characterized by unique timings, paces, and sequences of financial, human, and innovative resource-related activities. This study contributes to new venture growth research, particularly in science-based high-tech startups, with its nuanced understanding of diverse growth pathways, including intriguing notions of early failure, growth reversal, and high and moderate steady growth.
Original languageEnglish
Article number102427
JournalLong range planning
Volume57
Issue number2
Early online date14 Feb 2024
DOIs
Publication statusPublished - Apr 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth

Keywords

  • UT-Hybrid-D

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