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Explaining landscape preference heterogeneity using machine learning-based survey analysis

Author

Listed:
  • Xiaozi Liu
  • Endre Tvinnereim
  • Kristine M. Grimsrud
  • Henrik Lindhjem
  • Liv Guri Velle
  • Heidi Iren Saure
  • Hanna Lee

Abstract

We conducted a national survey on a high-quality internet panel to study landscape preferences in Norway, using photos as stimuli. We examined preference heterogeneity with respect to socio-demographic characteristics and latent topics brought up by the respondents, using ordinal logistic regression and structural topic modelling (STM), a machine learning-based analysis. We found that pasture landscapes are the most favoured (55%), while densely planted spruce forests are the least favoured (8%). The contrast was particularly strong between eastern and western Norway, between men and women, and between young and old. STM revealed that the choices were mainly driven by the preference for landscape openness, especially by women. Other important drivers were concerns regarding reforestation of former farmlands, aesthetic properties, forest management, biodiversity issues, and cultural values. Our results suggest that landscape policies may clash with socio-cultural preferences, and failure to account for these may undermine the success of a policy.

Suggested Citation

  • Xiaozi Liu & Endre Tvinnereim & Kristine M. Grimsrud & Henrik Lindhjem & Liv Guri Velle & Heidi Iren Saure & Hanna Lee, 2021. "Explaining landscape preference heterogeneity using machine learning-based survey analysis," Landscape Research, Taylor & Francis Journals, vol. 46(3), pages 417-434, April.
    • Handle: RePEc:taf:clarxx:v:46:y:2021:i:3:p:417-434
    DOI: 10.1080/01426397.2020.1867713
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    Cited by:

    1. Xiaozi Liu & Henrik Lindhjem & Kristine Grimsrud & Einar Leknes & Endre Tvinnereim, 2023. "Is there a generational shift in preferences for forest carbon sequestration vs. preservation of agricultural landscapes?," Climatic Change, Springer, vol. 176(9), pages 1-22, September.
    2. Mohamed M. Mostafa, 2023. "A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3905-3935, August.
    3. Markéta Braun Kohlová & Petra Nepožitková & Jan Melichar, 2021. "How Do Observable Characteristics of Post-Mining Forests Affect Their Attractiveness for Recreation?," Land, MDPI, vol. 10(9), pages 1-19, August.

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