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Bridging complexity theory and hierarchies, markets, networks, communities: a ‘population genetics’ framework for understanding institutional change from within

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  • Tim Tenbensel

Abstract

Complexity theory is highly compatible with institutionalist approaches to analysing governance. This article develops a ‘population genetics’ account of governance dynamics using complexity concepts. This framework joins ‘hierarchy, markets, networks and communities’ (HMNC) with concepts of endogenous change, genetic recombination, and fitness landscapes. Institutional environments comprise ‘populations’ that contain a range of genetic profiles. Change and stability are shaped by nesting and abrasion of alternative combinations within a governance field. This framework can help researchers understand how agents attempt to transform meso-level institutions from within, using the field of primary medical care governance in Auckland as an example.

Suggested Citation

  • Tim Tenbensel, 2018. "Bridging complexity theory and hierarchies, markets, networks, communities: a ‘population genetics’ framework for understanding institutional change from within," Public Management Review, Taylor & Francis Journals, vol. 20(7), pages 1032-1051, July.
    • Handle: RePEc:taf:rpxmxx:v:20:y:2018:i:7:p:1032-1051
    DOI: 10.1080/14719037.2017.1364409
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    Cited by:

    1. Astrid Molenveld & Arwin Buuren & Gerald-Jan Ellen, 2020. "Governance of climate adaptation, which mode? An exploration of stakeholder viewpoints on how to organize adaptation," Climatic Change, Springer, vol. 162(2), pages 233-254, September.
    2. Ryan Wong, 2019. "Balancing Institutions for Implementing the Sustainable Development Goals Through ‘Network Within Hierarchy’," Sustainability, MDPI, vol. 11(16), pages 1-15, August.

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