Explaining the stage of product in pre-seed academic startup ventures: An empirical analysis using m
Authors: Christoph E. Mueller
Year: 2023
Methodology
- Sample: Not explicitly stated in snippet (referenced as data from the EXIST Business Startup Grant monitoring)
- Design: cross-sectional
- Data: EXIST – Business Startup Grant (EGS) monitoring data, Baseline survey of program-accompanying monitoring
Factors Extracted (7)
R&D work stage [strong] — Medium-sized effect (Structural Equation Modeling)
Business model development stage [moderate] — Small effect
Degree of networking [moderate] — Small effect
Project feasibility [moderate] — Small effect
Previous freelance experience (connected with the product) [moderate] — Small effect
Financing [moderate] — Statistically significant (direction/size not specified in highlights)
Technology field [moderate] — Statistically significant (direction/size not specified in highlights)
Key Findings
- The R&D work stage is the primary driver of product development maturity in pre-seed academic startups, showing a medium-sized effect.
- Business model development and networking have statistically significant but small direct/indirect effects on the product's stage of development.
- A large proportion of the variance in product development stage can be explained by combining project characteristics, R&D progress, and founder experience.
Limitations
- Focus is restricted to the pre-seed phase of academic spin-offs, which may not generalize to later-stage startups or non-academic ventures.
- The study uses monitoring data from a specific German support program (EXIST), potentially introducing selection bias based on program entry requirements.
- The analysis focuses on the 'stage of product' as a proxy for potential success rather than long-term economic performance (exit or revenue).
Extracted by lib/ingest/literature_review.py via gemini-flash