PurposeCOVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.Design/methodology/approachWe adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.FindingsAn AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.Research limitations/implicationsAs the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.Practical implicationsSupply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.Originality/valueThe present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.

Purpose The banking industry plays a key role in society because of its role as a financial intermediary. Today’s banks are being asked to endorse environmental objectives, and recent studies have shown that large banks with strong financial performance are more likely to engage in environmental actions. Thus, the purpose of this paper is to investigate the link between corporate financial performance (CFP) and corporate environmental performance (CEP). Design/methodology/approach The authors focused on the French banking sector, using the data from a sample consisting of 191 observations covering 68 banks from 2008 to 2011. The environmental scores from the Vigeo database were the proxy measures for the extent to which banks engage in environmental actions. A panel regression model was employed for this study. Findings The findings show that high CFP was associated with high CEP. The findings also reveal that CFP and CEP may strengthen each other, suggesting a complex bidirectional relationship. Originality/value While many studies have examined whether it pays to be green, thus focusing on the causal relationship from CEP to CFP, few have considered that the causal direction might be reversed, from CFP to CEP. Furthermore, to the best of the authors’ knowledge, this paper is the first to analyze the CFP-CEP relationship using French bank data.

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