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From Business Ecosystems to Firm Physiology: The Strategy– Technology– Management Evolutionary Synthesis

Charis Vlados & Dimos Chatzinikolaou

Journal of Entrepreneurship2025https://doi.org/10.1177/09713557251349310article
AJG 1ABDC C
Weight
0.37

What the paper says

This research explores the integration of biological typologies into evolutionary economics, emphasising the ‘physiology’ of firms within business ecosystems. Using the Strategy–Technology–Management (Stra.Tech.Man) framework, firms are categorised as ‘living entities’ with distinct physiological traits in strategy, technology and management—as independent analytical organic spheres. Although the application of evolutionary thinking to socio-economic sciences is not unprecedented, this study offers a novel approach that emphasises evolutionary micro-foundations. The intention is to advance the discourse in evolutionary microeconomic theory concerning firms, veering away from the conventional neoclassical model and placing importance on the inherent dynamism of business operations. These findings provide contemporary organisational science with enriched analytical aspects, highlighting the adaptive nature of firms within the larger ecosystem. This physiological lens also offers a concrete and evolutionary micro-level theoretical mechanism that explains why identical ecosystem-level policies often generate heterogeneous firm-level outcomes.

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https://doi.org/https://doi.org/10.1177/09713557251349310

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@article{charis2025,
  title        = {{From Business Ecosystems to Firm Physiology: The Strategy– Technology– Management Evolutionary Synthesis}},
  author       = {Charis Vlados & Dimos Chatzinikolaou},
  journal      = {Journal of Entrepreneurship},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/09713557251349310},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.