Climate change poses a significant challenge to urban areas, particularly given the projected increase in urban populations. Nature-based solutions (NBS), defined as cost-effective, nature-inspired solutions offering environmental, social, and economic benefits, are increasingly recognized as effective approaches to climate change mitigation and adaptation. However, the success of NBS hinges on social acceptance, which has often been overlooked in the planning process. This 'social gap' necessitates a comprehensive understanding of the factors influencing public acceptance to ensure the smooth and effective implementation of NBS. This study addresses this gap by developing a dynamic and adaptive social acceptance framework, incorporating behavioral theories and data-driven science, to guide the integration of NBS into cities while ensuring public support. The researchers acknowledge the complexities involved in implementing NBS within socio-ecological systems and the long timeframes required to observe benefits. They emphasize the need for collaborative, multi-stakeholder approaches that build trust and transparency to achieve lasting public support. The study examines four distinct case studies – METU Forest (Ankara), Tisza River Bank (Szeged), Forest Garden (Alcalá de Henares), and Quarries (Milan) – to demonstrate the applicability and generalizability of the proposed framework across varying socio-spatial contexts, highlighting the unique interaction of NBS with their environments and the importance of tailored solutions reflecting community diversity.

The paper reviews existing literature on social acceptance of technological and policy interventions, noting a lack of consensus on its definition and measurement. Different conceptualizations of social acceptance, encompassing socio-political, community, and market dimensions, are examined. The authors discuss the theory of planned behavior, emphasizing the role of attitudes, subjective norms, and perceived behavioral control in shaping intentions and behaviors. They integrate additional factors, such as affect (positive and negative) and personal norms, to enhance the explanatory power of the model. The literature also underscores the importance of trust in decision-makers, procedural and distributive fairness, and knowledge/experience in shaping attitudes towards NBS. Existing studies on social acceptance are often fragmented and lack common methodological underpinnings, highlighting the need for a generalizable framework for comparison and analysis across diverse contexts. The framework developed in this study aims to address these limitations.

The study employs a quantitative approach using a comprehensive, dynamic, and adaptable framework for developing questionnaires to collect primary data on social acceptance of different NBS. The framework, derived from behavioural theories, integrates factors such as perceived benefits, risks, costs, trust, procedural and distributive fairness, knowledge, experience, positive and negative affect, personal norms, and social norms. The chosen methodology is Partial Least Squares (PLS), a component-based structural equation modelling technique suitable for handling complex models with both single and multiple-item measures, which is particularly advantageous for smaller sample sizes. The PLS method allows for the simultaneous testing of the hypothesized relationships between the various factors. The research involves a multi-stage process: 1) literature review to inform questionnaire development; 2) survey design tailored to each case study, considering implementation stage (pre- or post-implementation); 3) data collection with a target sample size of 200-300 respondents per case; 4) PLS analysis for model fitting, reliability, validity, and hypothesis testing. The study addresses potential methodological issues such as common method bias by applying relevant assessment techniques. Four case studies – METU Forest (Ankara), Tisza River Bank (Szeged), Forest Garden (Alcalá de Henares), and Quarries (Milan) – are used to test the framework, chosen to represent diverse contexts and implementation stages. The four case studies are analysed separately, generating tailored results for each city and specific NBS project, reflecting the heterogeneity of socio-spatial contexts and avoiding pooling data.

The analysis, using PLS, reveals varying patterns of influence across the four case studies. While perceived benefits consistently show a positive relationship with social acceptance, the relative importance of other factors such as trust, fairness, risks, costs, and affect, vary depending on the specific context and implementation stage. In the Tisza River Bank (pre-implementation), trust emerges as a crucial driver, significantly influencing social acceptance via its impact on perceived costs, risks, and benefits. Procedural fairness also demonstrates a significant direct and indirect (through trust) effect on acceptance. Distributive fairness also plays a role, highlighting the importance of fair distribution of costs and benefits. In the Quarries in Milan (ongoing implementation), trust again plays a central role, with procedural fairness indirectly influencing acceptance through trust. In contrast to Szeged, distributive fairness is not significant. The Alcalá de Henares Forest Garden (post-implementation) reveals that both procedural fairness and experience/knowledge significantly contribute to social acceptance, with procedural fairness having both direct and indirect impacts. Personal norms are also a significant predictor of social acceptance in this case. Finally, the METU Forest (post-implementation) emphasizes the importance of perceived benefits and risks in shaping social acceptance, while trust plays an indirect role. Experience/knowledge also influences acceptance through its effect on trust. Across all cases, the study confirms the importance of procedural fairness in establishing trust and enhancing social acceptance, while the relevance of other factors is context-dependent.

The findings confirm the complexity of social acceptance and the lack of a one-size-fits-all solution. The study's framework successfully captures the diverse factors influencing social acceptance across different NBS types and locations. The results highlight the importance of integrating social considerations into all stages of the NBS planning and implementation process. Trust, procedural fairness, and perceived benefits emerge as consistently important factors, while the impact of other factors (distributive fairness, risk perception, affect, personal norms) is context-specific. The variation across cases underscores the need for tailored strategies to enhance social acceptance, adapting to local conditions and community characteristics. The research demonstrates that a data-driven, evidence-based approach can inform the development of effective policy instruments and management strategies that promote lasting public support for NBS.

This research provides a valuable contribution by developing a generalizable framework for assessing social acceptance of NBS. The findings highlight the importance of a multi-faceted approach, considering procedural fairness, trust, perceived benefits, and other context-specific factors. The study successfully demonstrates the applicability of the framework across different NBS and locations. Future research could explore the dynamics of group perception formation and expand the framework to include additional factors, like policy design and governance mechanisms. Moreover, investigating the long-term impacts of NBS on social acceptance and conducting comparative studies across a larger number of cases could further enhance the robustness and generalizability of these findings.

The study’s findings are based on four case studies, limiting the generalizability to other contexts. While the sample sizes aimed for 200-300 per case, potential response bias or limitations in data collection methods could have influenced the results. The cross-sectional nature of the data limits causal inference, although PLS allows exploring interrelationships between variables. Future research with longitudinal data and a broader geographical scope would enhance the reliability and generalizability of the results. Also, the study focuses on community acceptance and might not fully capture the wider dimensions of socio-political and market acceptance of NBS.