In the field of disaster management, it is imperative to recognize the progress made in the study of natural disasters, particularly in terms of methodology and technology. Artificial intelligence is being utilized in various fields and industries. The field of study includes various disciplines such as geospatial analysis, robotics, technology for drones, machine learning, telecommunications and network services, remote sensing, and environmental impact assessment. The incorporation of technology across various sectors is essential for accelerating societal change. Recent technological advancements have greatly influenced studying societal responses to risks and catastrophes. Researchers in the social sciences have utilized various methodologies and approaches to study natural disasters from the viewpoints of their specific disciplines, as well as transdisciplinary and interdisciplinary domains. The researchers used quantitative and qualitative methodologies for data collection and analysis. This study provides a comprehensive analysis of the various applications of AI currently utilized throughout different stages of disaster management. The statement above highlights the substantial influence of AI in different fields, emphasizing its ability to provide quick and efficient responses characterized by increased speed, precision, and readiness. Utilizing remote sensing and geographic information systems in disaster management improves planning and analysis capabilities, facilitates situational awareness, and accelerates recovery efforts. There is a widely accepted agreement among individuals regarding the significant importance of GIS and RS in managing emergencies. In mitigating the impacts of natural disasters, governmental entities can enhance the efficiency of decision-Making by employing visualization tools, satellite imagery, and AI analyses.

The purpose of this paper is to explore the impact of ESG sustainability practices (i.e., Environmental, Social, Governance/economic) on share performance. Moreover, the objective of the study is to investigate the sustainability practices with mediation of board member experience, which might contribute in maintaining the share performance. The study is unique in such a way that instead of analysing the stated relationship with internal financial performance measures such as return on asset (ROA) or return on equity (ROE), this study will investigate the relationship using external performance measures such as firm share performance. In this research, data were collected from 100 Bursa Malaysia listed companies using purposive sampling during the sampling period from 2017 to 2020. The data were analysed using the Autoregressive Distributed Lag (ARDL) bound testing model instead of a traditional regression model to examine the causal relationship. The results of the study showed the long-run steady relationships through the error correction term (ECT) at the optimum lag. Further, the findings also revealed that there is no short run association between the sustainability practices and the stock performance with mediation of the board experience. The findings also showed that sustainability practices have a significant impact on share performance with mediation of board experience. It is found that sustainability practices, especially environmental and social, are essential to attract investors. The results have also demonstrated that a board of directors of different ages has different knowledge, competencies, and expertise which could prove beneficial in terms of board diversity that decides to adapt the best sustainability practices. These findings provide some inference for future research on the relationship of sustainability practices and share performance with other mediating factors of board attributes.