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 language | English |
|---|---|
| Article number | 102427 |
| Journal | Long range planning |
| Volume | 57 |
| Issue number | 2 |
| Early online date | 14 Feb 2024 |
| DOIs | |
| Publication status | Published - Apr 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
Keywords
- UT-Hybrid-D
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