Search

Every development and production process needs to operate within a circular economy to keep the human being within a safe limit of the planetary boundary. Policymakers are in the quest of a powerful and easy-to-use tool for representing the perceived causal structure of a complex system that could help them choose and develop the right strategies. In this context, fuzzy cognitive maps (FCMs) can serve as a soft computing method for modelling human knowledge and developing quantitative dynamic models. FCM-based modelling includes the aggregation of knowledge from a variety of sources involving multiple stakeholders, thus offering a more reliable final model. The average aggregation method for weighted interconnections among concepts is widely used in FCM modelling. In this research, we applied the OWA (ordered weighted averaging) learning operators in aggregating FCM weights, assigned by various participants/ stakeholders. Our case study involves a complex phenomenon of poverty eradication and socio-economic development strategies in rural areas under the DAY-NRLM (Deendayal Antyodaya Yojana-National Rural Livelihoods Mission) in India. Various scenarios examining the economic sustainability and livelihood diversification of poor women in rural areas were performed using the FCM-based simulation process implemented by the "FCMWizard" tool. The objective of this study was three-fold: (i) to perform a brief comparative analysis between the proposed aggregation method called "OWA learning aggregation" and the conventional average aggregation method, (ii) to identify the significant concepts and their impact on the examined FCM model regarding poverty alleviation, and (iii) to advance the knowledge of circular economy in the context of poverty alleviation. Overall, the proposed method can support policymakers in eliciting accurate outcomes of proposed policies that deal with social resilience and sustainable socio-economic development strategies. [ABSTRACT FROM AUTHOR]

The Sundarbans is the world's largest coastal river delta and the largest uninterrupted mangrove ecosystem. A complex socio-ecological setting, coupled with disproportionately high climate-change exposure and severe ecological and social vulnerabilities, has turned it into a climate hotspot requiring well-designed adaptation interventions. We have used the fuzzy cognitive maps (FCM)-based approach to elicit and integrate stakeholders' perceptions regarding current climate forcing, consequent impacts, and efficacy of the existing adaptation measures. We have also undertaken climate modelling to ascertain long-term future trends of climate forcing. FCM-based simulations reveal that while existing adaptation practices provide resilience to an extent, they are grossly inadequate in the context of providing future resilience. Even well-planned adaptations may not be entirely transformative in such a fragile ecosystem. It was through FCM-based simulations that we realised that a coastal river delta in a developing nation merits special attention for climate-resilient adaptation planning and execution. Measures that are likely to enhance adaptive capabilities of the local communities include those involving gender-responsive and adaptive governance, human resource capacity building, commitments of global communities for adaptation financing, education and awareness programmes, and embedding indigenous and local knowledge into decision making. [ABSTRACT FROM AUTHOR]