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This article attempts to find out the factors which are significantly related and influence the FDI inflow into China, India and Malaysia during the study period ranging between 1991 and 2010. The objective of FDI is almost the same, but the factors that influence foreign investors when deciding the location of investment are receiving importance and attention. Correlation has been used to study the factors influencing FDI inflow. The study revealed that India and China are very similar, whereas in Malaysia the same factors do not influence inflow of foreign investment to the country. GDP of the country, gross capital formation, capital infrastructure, external debt, export and import volume are the major factors that significantly influence foreign capital inflow into the two highly populated, fast growing Asian countries, that is, China and India. In the case of Malaysia, only domestic investment or gross domestic capital formation is significantly related to its FDI inflow.

In this study, the key areas and current trends in the field of big data applications in the insurance industry are identified, along with suggestions for future research initiatives. We identified the most prominent authors, journals, organizations, and countries based on their total publications and citations, showing their significance within the network, using bibliometric analysis on a sample of 191 articles retrieved from Scopus from 1976 to 2021. VOSviewer and R-Biblioshiny tools were used to generate the bibliometric output on these retrieved papers. The findings showed that although while a good number of writers from other parts of the world contributed to the literature on big data applications in the insurance industry, during this time, most research papers have listed the United States, India, and China as their affiliated countries. The yearly publication was either one or two, with some discontinuity, from 1976 to 2011, but since 2012, it has increased, exhibiting an exponential growth tendency. The three journals “Risks,” “Applied Stochastic Models in Business and Industry,” and “Expert Systems with Applications” are the most popular for including a sizable number of papers in the field of big data technologies in the insurance sector. Each of the top 10 authors in this field published two research papers during these 46 years. Seven areas, including fraud detection and prevention, risk assessment, pricing & rate making, technology utilization, risk management, claim processing & prediction, and finally digitalization, were the major focus of research papers on bigdata applications in the insurance business. The human-centered AI system development, adoption of wearable technology, personalization, and other topics were found to have received very little attention in this study. As a result, the researchers may now direct future research in this area. This study is completely new of its kind in the domain of insurance though few documents are available on the broad concept of finance.

Extreme rainfall events are a significant cause of loss of life and livelihoods in Odisha. Objectives of the present study are to determine the trend of the extreme rainfall events during 1991-2014 and to compare the events between two periods before and after 1991. Block level daily rainfall data were used in identifying the extreme rainfall events, while district level aggregation was used in analysing the trend   in three categories, viz., heavy, very heavy and extremely heavy rainfall as per criteria given by India Meteorological Department (IMD). The state as a whole received one extremely heavy, nine very heavy, and forty heavy rainfall events in a year. When percentage of occurrence of each category out of the total extreme events over different districts was considered, maximum % of extremely heavy rainfall occurred in Kalahandi (5.8%), very heavy rainfall in Bolangir (23.8%) and heavy rainfall in Keonjhargarh (85.4%). Trend analysis showed that number of extreme rainfall events increased in a few districts, namely, Bolangir, Nuapada, Keonjhargarh, Koraput, Malkangiri, and Nawarangapur and did not change in other districts. In Puri district, extremely heavy rainfall frequency decreased. New all-time record high one-day rainfall events were observed in twenty districts during 1992 to 2014, surpassing the earlier records, which could be attributed to  climate change induced by  global warming. Interior south Odisha was found as the hot spot for extreme rainfalls.

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