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The purpose of this study is to estimate revealed comparative advantage and normalized revealed comparative advantage (NRCA) indices of India’s computer and information services (CIS) export competitiveness with regard to information technology (IT) competing developing nations, such as China, Philippines, Malaysia and Brazil.

Using annual data of total exports for CIS, transportation (TNS), travel (TVL) and insurance (INS) services under service categories of the balance of payment, the present study estimates the pattern of comparative advantage (CA) in India’s CIS exports with respect to IT competing developing nations such as China, Philippines, Malaysia and Brazil from 2000 to 2018. The choice of the study period is determined by the availability of consistent data on IT service exports of these nations. The study also estimates the export position of CIS export in comparison to India’s traditionally strong commercial services export of TNS, TVL and INS during the study period.

Both the indices showed that India had a strong CA in CIS compared to the selected nations, indicating India’s relative export performance to be stronger than that of China, Malaysia, Philippines and Brazil. The cross-service index showed that India’s relative specialization level in CIS with respect to the world’s average specialization level was stronger than its relative specialization level in TNS, TVL and INS services. Furthermore, The NRCA cross-nation index showed that India’s NRCA index score has been declining since 2010 with respect to these nations, which implied a decline in the competitiveness of CIS. On the other hand, NRCA has increased in the case of Philippines, Malaysia and Brazil for most of the period post-2010.

IT is a dynamic area of economic activity, and when the pace of change is so rapid, the relevance of individual factors can change over time. The study period is also limited to the available data.

The paper has implications for attaining sustainability in IT export growth. It is suggested that policies are directed at enhancing the overall performance of IT sector.

The novelty of the present study lies in the estimation of India’s competitiveness in IT exports in relation to the group of reference countries. With its policy recommendations, this research is helping to shape the sustainability of the IT sector.

Traditional statistical methods to study the financial performance of any industry have many barriers and limitations in terms of the statistical distribution of the financial ratios, and, in particular, it considers only its positive values of it. The purpose of this paper is to estimate the financial performance of 24 Indian life insurance companies for the period from 2013 to 2016 using Grey relational analysis (GRA) proposed by Deng (1982) that accommodates the negative values in the analysis.

Financial performance of 24 Indian life insurance companies for the years from 2013–2014 to 2015–2016 is examined using a total of 14 indicators from capital adequacy ratios, liquidity ratios, operating ratios and profitability ratios (PR). The methodology used is GRA to obtain the Grey grades to rank the performance indicators, where higher relational grade shows better financial performance, and a lower score depicts the scope for improving the performance.

The results rank the insurance companies according to their financial performance in which Shriram insurance stands first with higher relational grade score, followed by the companies like IDBI Insurance, Sahara Insurance and Life Insurance Corporation of India. The main finding is that PR which have negative values are playing a crucial role in determining the financial performance of Indian life insurance companies.

This study has far-reaching practical implications in twofold: first, for the Indian life insurance industry, they have to concentrate more on PR for better financial health and, second, for any financial performance analysis, ignoring negative value ratios produce biased inference and GRA can be used for better inference.

This study is the first attempt to evaluate the financial performance of Indian life insurance using the GRA methodology. The advantage of GRA is that there is no restrictions on the statistical distribution of the data and it also accommodates the negative values, whereas all the other traditional methods insist on the statistical distribution of data, and, more importantly, they cannot handle negative values in the performance analysis.