(Non-)terrestrial and (Non-)local pathways of behavioral policy diffusion in European cities’ climate action plans: Contextual, cultural, and leadership framing
Jessica Page,
Hong Zhou,
Haozhi Pan,
Chang Zhou,
Pei Pei and
Zahra Kalantari
Land Use Policy, 2024, vol. 147, issue C
Abstract:
This study investigates the spread of innovative behavioral (green nudging) policies within city-level Climate Action Plans (CAPs) across the European Union, focusing on how these innovations diffuse and the factors influencing their adoption. Using textual analysis with a dataset consisting of CAPs from 40 cities across Europe, we categorized various green nudging innovations and then tracked their origins and uptake. Then, we employed fsQCA (Fuzzy set qualitative comparative analysis) to identify the key factors driving diffusion. The findings reveal that while certain innovations, particularly in the building and transportation sectors, have achieved widespread adoption, other initiatives like community co-creation and urban parks have seen lower diffusion. Local terrestrial factors, especially sectoral carbon emissions, are significant drivers, with cities facing higher emissions more likely to adopt these policies. Interestingly, local emissions levels and strong climate leadership emerge as more critical determinants than economic status or climate similarities. The study identifies two primary diffusion pathways—Cultural Leadership for Emission Reduction and Local Adaptive Synergy—demonstrating the diverse strategies cities employ based on their unique contexts. This research highlights the importance of expanding green nudging measures in CAPs beyond technological and infrastructure domains to promote low-carbon behaviors comprehensively.
Keywords: Climate Action Planning; Green Nudging; Behavioral Public Policy; Policy Innovations; Policy Diffusion (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:lauspo:v:147:y:2024:i:c:s0264837724003260
DOI: 10.1016/j.landusepol.2024.107373
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