During the recent years, value of financial assets has grown exponentially when compared to physical assets indicating that intangibles are growing in importance in their contribution to economic growth. The evidence in support of this phenomenon can be found in the increasing gap between market and book valuation of firms. The present study attempts to measure the intellectual capital (IC) of publicly listed firms in India and empirically examine the relationship among IC, financial performance and market valuation of these firms. Value creation efficiency of the firms listed on CNX Nifty over the period ranging from 2004–2005 to 2013–2014 has been estimated using Pulic’s Value Added Intellectual Coefficient (VAIC). It was observed that firms operating in sectors such as financial services, mining and energy had the highest VAIC scores. Further, there was a positive association between VAIC and all the measures of financial performance—profitability, productivity and market valuations. Efficiency of physical capital employed had a significant positive relation with profitability, market valuation as well as productivity. Human capital efficiency was found to have a strong positive association with profitability, while structural capital efficiency did not have any significant impact on any of the measures of financial performance.
A well-developed and efficient banking sector is the fundamental requirement for smooth functioning of any economy. The present study is an attempt to examine the technical, pure technical and scale efficiencies of the Indian banks across different ownership categories for the period 2009–2012. About 7 out of the 44 banks selected lie on the efficiency frontier and form the reference set for their peers. Further, it is observed that efficiency scores do not vary much across the public sector, private sector and foreign banks. Performance of the public sector and private sector banks is almost at par with respect to technical efficiency whereas in the case of foreign banks, there lays scope for improving scale efficiency. A second stage regression analysis is carried out using Tobit regression to examine the determinants of efficiency. Non-interest income emerges the most important determinant of efficiency of banks in India.
The financial crisis and resulting failure of large banks worldwide has shaken the entire world. Improper management of operational risk has been touted as one of the reasons for this failure. In light of the rising importance of operational risk management (ORM) in banks, the study explores the range of ORM practices followed by a cross section of Indian banks and compares them with the banks worldwide. The study also analyses the impact of size and ownership of banks on these practices. Reliability analysis using Cronbach alpha model, Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy and Bartlett’s test of sphericity was used to test reliability of questionnaire and justifies the use of factor analysis. Factor analysis was performed to extract the most important variables in ORM. The small size of bank was observed to be a deterrent to deep involvement of operational risk functionaries, collection and usage of external loss data and data collection and analysis. Further, the performance/preparedness of public sector and old private sector banks lagged behind peers in usage of key reporting components, such as risk and control self-assessment (RCSA), key risk indicators (KRI), scenarios, collection and usage of external loss data, data collection and analysis and quantification and modelling of operational risk.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.