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The purpose of this paper is to examine pro-poor urban asset adaptation to climate variability and change. It constructs a conceptual framework that explores the appropriate asset adaptation strategies for extreme poor households as well as the process of supporting these households and groups in accumulating these assets.

Qualitative data are obtained from life histories, key informant interviews (KIIs) and focus-group discussions (FGDs). These data are collected, coded and themed.

This research identifies that households among the urban extreme poor do their best to adapt to perceived climate changes; however, in the absence of savings, and access to credit and insurance, they are forced to adopt adverse coping strategies. Individual adaptation practices yield minimal results and are short lived and even harmful because the urban extreme poor are excluded from formal policies and institutions as they lack formal rights and entitlements. For the poorest, the process of facilitating and maintaining patron–client relationships is a central coping strategy. Social policy approaches are found to be effective in facilitating asset adaptation for the urban extreme poor because they contribute to greater resilience to climate change.

This study analyses the empirical evidence through the lens of a pro-poor asset-adaptation framework. It shows that the asset-transfer approach is an effective in building household-adaptation strategies. Equally important is the capacity to participate in and influence the institutions from which these people have previously been excluded.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.