Adapting Growth Models for Digital Startups: Empirical Evidence and Directions for Digital Entrepreneurship Research
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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ICIS 2024 Proceedings: Digital Innovation, Transformation, and Entrepreneurship. Atlanta: The Association for Information Systems (AIS), 2024. 37.
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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RIS
TY - CHAP
T1 - Adapting Growth Models for Digital Startups
T2 - International Conference on Information Systems - ICIS 2024
AU - Tschoppe, Nils Johann
AU - Drews, Paul
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Business informatics
KW - digital entrepreneurship
KW - growth model
KW - digital startup
KW - Digital technology
M3 - Article in conference proceedings
BT - ICIS 2024 Proceedings
PB - The Association for Information Systems (AIS)
CY - Atlanta
Y2 - 15 December 2024 through 18 December 2024
ER -