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Natural calamities like earthquakes, floods and epidemics/pandemics like COVID-19 significantly disrupt almost all the supply networks, ranging from medicines to numerous daily/emergency use items. Supply Chain Resilience is one such option to overcome the impact of the disruption, which is achieved by developing supply chain factors with Artificial Intelligence (AI) and Big Data Analytics (BDA).

This research examines how organizations using AI and BDA can bring resilience to supply chains. To achieve the objective, the authors developed the methodology to gather useful information from the literature studied and developed the Total Interpretive Structural Modeling (TISM) by consulting 44 supply chain professionals. The authors developed a quantitative questionnaire to collect 229 responses and further test the model. With the analysis, a conceptual and comprehensive framework is developed.

A major finding, this research advocates that supply chain resilience is contingent upon utilizing supply chain analytics. An empirical study provides further evidence that the utilization of supply chain analytics has a positive and favorable effect on the flexibility of demand forecasting to inventory management, resulting in increased efficiency.

Few studies demonstrate the impact of advanced technology in building resilient supply chains by enhancing their factors. To the best of the authors' knowledge, no earlier researcher has attempted to infuse AI and BDA into supply chain factors to make them resilient.

Using bibliometric, this work aims to evaluate the current status of the body of research on the subject of supply chain resilience (SCR) in developing nations and to provide recommendations for potential lines of inquiry for additional research.

Three hundred and thirty-six articles published between 2011 and 2021 were retrieved in Scopus for this bibliometric analysis. This analysis focuses on SCR research conducted in developing countries, highlighting its key authors, countries, institutions, journals, articles and themes.

This bibliometric review seeks to enrich the discourse on SCR in developing nations through a comprehensive and detailed review of 336 articles covering 138 Journals, 73 countries, 877 authors, 743 organizations and 1,145 author keywords. The United Kingdom, India, and the United States provided a substantial share of the publications. Publication-wise, Hong Kong Polytechnic University and The University of Hong Kong play key roles. The author found that supply chain risk management, sustainability, agile management, artificial intelligence and blockchain are trending topics. Additionally, the author identified eight themes by page rank analysis.

This study's importance lies primarily in its examination of the current information about SCR in developing countries and significant cluster areas (themes). In the paths, it recommends for further study, which academics may take, and industry professionals should apply in their businesses to create a more resilient and sustainable supply chain.

Based on published studies, this study gives exploratory data on SCR in developing countries context. This is first of its kind bibliometric study that focuses on developing countries.