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Paper Number
1422
Paper Type
Complete
Abstract
We contribute to digital entrepreneurship research by adapting growth models to better reflect the dynamics of entrepreneurial growth trajectories and increasing digital technology pervasion in digital startups. By grounding our findings in a dataset that includes interviews with founders and executive managers of 24 digital startups from eight countries, we propose three directions for advancing theory that supports a better understanding of the complexity and ambiguity of digital startups when growing. Directions I and II aim at revising and extending established growth models to support research on attributes that better capture the ubiquitous digital technology pervasion in digital startups. In direction III, we explore seminal research on dynamic states that contradict the dominant view of deterministic stages in growth model research and illustrate the need to integrate both approaches when designing new theoretical growth models by presenting four archetypes of digital infrastructure evolution.
Recommended Citation
Tschoppe, Nils Johann and Drews, Paul, "Adapting Growth Models for Digital Startups: Empirical Evidence and Directions for Digital Entrepreneurship Research" (2024). ICIS 2024 Proceedings. 37.
https://aisel.aisnet.org/icis2024/diginnoventren/diginnoventren/37
Adapting Growth Models for Digital Startups: Empirical Evidence and Directions for Digital Entrepreneurship Research
We contribute to digital entrepreneurship research by adapting growth models to better reflect the dynamics of entrepreneurial growth trajectories and increasing digital technology pervasion in digital startups. By grounding our findings in a dataset that includes interviews with founders and executive managers of 24 digital startups from eight countries, we propose three directions for advancing theory that supports a better understanding of the complexity and ambiguity of digital startups when growing. Directions I and II aim at revising and extending established growth models to support research on attributes that better capture the ubiquitous digital technology pervasion in digital startups. In direction III, we explore seminal research on dynamic states that contradict the dominant view of deterministic stages in growth model research and illustrate the need to integrate both approaches when designing new theoretical growth models by presenting four archetypes of digital infrastructure evolution.
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