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Evaluation of tech ventures' evolving business models: rules for performance-related classification

Author

Listed:
  • Marc König
  • Manon Enjolras
  • Christina Ungerer
  • Mauricio Camargo
  • Guido H. Baltes

Abstract

At the early stage of a successful tech venture's life cycle, it is assumed that the business model will evolve to higher quality over time. However, there are few empirical insights into business model evolution patterns for the performance-related classification of early-stage tech ventures. We created relevant variables evaluating the evolution of the venture-centric network and the technological proposition of both digital and non-digital ventures' business models using the text of submissions to the official business plan award in the German State of Baden-Württemberg between 2006 and 2012. Applying a principal component analysis/rough set theory mixed methodology, we explore performance-related business model classification rules in the heterogeneous sample of business plans. We find that ventures need to demonstrate real interactions with their customers' needs to survive. The distinguishing success rules are related to patent applications, risk capital, and scaling of the organisation. The rules help practitioners to classify business models in a way that allows them to prioritise action for performance.

Suggested Citation

  • Marc König & Manon Enjolras & Christina Ungerer & Mauricio Camargo & Guido H. Baltes, 2022. "Evaluation of tech ventures' evolving business models: rules for performance-related classification," International Journal of Entrepreneurial Venturing, Inderscience Enterprises Ltd, vol. 14(2), pages 145-167.
    • Handle: RePEc:ids:ijeven:v:14:y:2022:i:2:p:145-167
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