Using fuzzy cognitive maps to develop policy strategies for the development of green rural housing: A case study in China

Xiaolong Gan, Kangkang Yan and Tao Wen

Technological Forecasting and Social Change, 2023, vol. 192, issue C

Abstract: Under the strategy of rural revitalization, China has a considerable demand for building green rural housing. Thus, it is urgent to develop related policy strategies for green rural housing development. However, the issue of green rural housing development has been overlooked in recent studies. This research fills this gap by increasing our understanding of factors that hinder green rural housing development and identifying effective policy strategies via fuzzy cognitive maps (FCM). Firstly, 23 system variables were identified including 8 policy drivers, 12 system structure variables and 3 system outcome variables. Then, the causal-effect relationships among these variables were visualized. Secondly, a fuzzy inference simulation was conducted to explore the most effective policy strategies for green rural housing development. The results show that these factors inhibiting green rural housing development are interrelated, which form solid vicious cycles not only between economic factors, social factors and technological factors but also within these sub-aspect factors. Three policy mixes were identified as the most effective policy strategies: financial support and price support, infrastructure development and technology support, guiding information and certification and labelling. The results offer a valuable reference to policy-making on facilitating rural green housing development.

Keywords: Green building; Rural housing; Fuzzy cognitive map; Policy mixes (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:192:y:2023:i:c:s0040162523002755

DOI: 10.1016/j.techfore.2023.122590

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