Adapting Growth Models for Digital Startups: Empirical Evidence and Directions for Digital Entrepreneurship Research

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

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.
Original languageEnglish
Title of host publicationProceedings of ICIS 2024
Number of pages17
PublisherThe Association for Information Systems (AIS)
Publication date2024
Publication statusPublished - 2024