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In the supply chain performance measurement (SCPM) there seems to be no consensus about measures for performance evaluation and suitable criteria from resilience and sustainability paradigms. In this way, this research aims to identify the attributes that a supply chain (SC) should follow to be resilient and sustainable, and then to evaluate their importance according to industry experts.

This study suggests a hybrid approach. The authors identified the most commonly used criteria using literature review, and then applied fuzzy Delphi technique (FDT) with the objective of surveying experts to find the attributes used in practice and asked to assess their relevance.

The resilient-sustainable supply chain (RSSC) is formed by four dimensions: resiliency, economic, environmental and social. A total of 15 criteria are identified, and the most important are visibility, flexibility, supply chain risk management (SCRM) culture, work conditions and communication.

This study used a literature review, so it is subject to a time frame, and the criteria could no longer be relevant as the time and business conditions change. Also, the findings may not be completely applicable throughout different industries, and therefore the finding cannot be replicated to other businesses.

This study will assist decision-makers among other interested parties to construct and/or strengthen an integrated SC that mixes resiliency and sustainability.

This study contributes to the state-of-art by producing a characterization of the resilient and sustainable supply chain for the automotive industry. Also, this research produces a new and holistic framework for resilient and sustainable SCPM supporting the decision-making process.

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.