A slew of participatory and community-demand-driven approaches have emerged in order to address the multi-dimensional nature of poverty in developing nations. The present study identifies critical factors responsible for poverty alleviation in India with the aid of fuzzy cognitive maps (FCMs) deployed for showcasing causal reasoning. It is through FCM-based simulations that the study evaluates the efficacy of existing poverty alleviation approaches, including community organisation based micro-financing, capability and social security, market-based and good governance. Our findings confirm, to some degree, the complementarity of various approaches to poverty alleviation that need to be implemented simultaneously for a comprehensive poverty alleviation drive. FCM-based simulations underscore the need for applying an integrated and multi-dimensional approach incorporating elements of various approaches for eradicating poverty, which happens to be a multi-dimensional phenomenon. Besides, the study offers policy implications for the design, management, and implementation of poverty eradication programmes. On the methodological front, the study enriches FCM literature in the areas of knowledge capture, sample adequacy, and robustness of the dynamic system model. OPEN ACCESSCitation: Singh PK, Chudasama H (2020) Evaluating poverty alleviation strategies in a developing country. PLoS ONE 15(1): e0227176.

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Drought is among the most dreaded threats as far as natural disasters are concerned wielding, as it does, a significant impact on ecosystems, people's livelihoods, and the socioeconomic development of a country. A significantly large geographic area of India happens to be drought prone. In order to understand people's response to the impacts of drought and their coping strategies, it is crucial to understand their perceptions. Studies investigating community perceptions relevant to drought impacts and concomitant adaptive behaviours are rare in India. This paper documents communities' perceptions of impacts of drought on their livelihood assets and adaptation practices. It does this with the help of the fuzzy cognitive mapping approach in the Mahabubnagar district of India's Telangana state. In order to develop pathways for drought resilient livelihoods we ran simulations for future drought scenarios with various bundles of adaptation strategies enabling us to evaluate their effectiveness in providing resilience against drought. The study also tested the suitability of various activation rules and transformation functions, used for running simulations. Incorporating stakeholders' perceptions, knowledge and beliefs about impacts of droughts, and engaging them in the process of developing drought resilient livelihoods is expected to fine-tune the drought related policy-making.

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.