Skip to main content

Advertisement

Log in

Learning and open data in sustainability transitions: evolutionary implications of the theory of probabilistic functionalism

  • Perspectives
  • Published:
Environment Systems and Decisions Aims and scope Submit manuscript

Abstract

The Theory of Probabilistic Functionalism, as a general theory of how organisms interact with complex environmental systems, provides a useful framework for describing essential processes of sustainability planning groups. Particularly, the mechanism of producing evolutionary stable representations of and judgment about the environment has important implications for sustainability transitions. In comparison with biological evolution, the environment changes much faster in social phenomena, and the selection dynamics working on heterogeneous groups for successful survival would be incomplete. That makes continuous learning by the members of planning groups as well as collective decision-making among them critically important. The policy of open data for assembling, distributing, and utilizing various kinds of data will facilitate vision creation, strategy development, and consensus building with stakeholders for sustainability transitions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Avelino F, Grin J, Pel B, Jhagroe S (2016) The politics of sustainability transitions. J Environ Plan Policy Manage 18(5):557–567

    Article  Google Scholar 

  • Beinhocker ED (2006) The origin of wealth: evolution, complexity and the radical remaking of economics. Harvard Business School Press, Boston

    Google Scholar 

  • Dosi G, Nelson RR (2010) Chapter 3—technical change and industrial dynamics as evolutionary processes. In: Bronwyn HH, Nathan R (eds) Handbook of the economics of innovation. Elsevier, Amsterdam

    Google Scholar 

  • Elster J (1989) Nuts and bolts for the social sciences. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Marshall A (1890) Principles of economics. Macmillan, London

    Google Scholar 

  • Nelson RR, Winter SG (1982) An evolutionary theory of economic change. Belknap Press of Harvard University Press, Cambridge

    Google Scholar 

  • Scholz RW (2011) Environmental literacy in science and society: from knowledge to decisions. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Scholz RW (2017) Managing complexity: from visual perception to sustainable transitions—contributions of Brunswik’s theory of probabilistic functionalism. Environ Syst Decis 37(4):381–409

    Google Scholar 

  • Veblen TB (1898) Why is economics not an evolutionary science? Q J Econ 12(3):373–397

    Article  Google Scholar 

  • Yarime M (2017) Facilitating data-intensive approaches to innovation for sustainability: opportunities and challenges in building smart cities. Sustain Sci 12(6):881–885

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Masaru Yarime.

Additional information

This Perspectives paper is a comment on Scholz’s “Managing complexity: from visual perception to sustainable transitions—contributions of Brunswik’s Theory of Probabilistic Functionalism”, Environ Syst Decis. https://doi.org/10.1007/s10669-017-9655-4.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yarime, M. Learning and open data in sustainability transitions: evolutionary implications of the theory of probabilistic functionalism. Environ Syst Decis 38, 88–91 (2018). https://doi.org/10.1007/s10669-017-9668-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10669-017-9668-z

Keywords

Navigation