Purpose The issue of mounting non-performing assets (NPAs) in Indian banking industry is serious and attracting attention of academia and policy planners. Thus, the purpose of this paper is to test the hypothesis whether NPAs in Indian commercial banking have reached at alarming state where they start affecting the technical efficiency levels adversely or not. Design/methodology/approach The efficiency score have been computed using case model (model with NPAs as bad/undesirable output) vs control model (model without NPAs as bad/undesirable output) methodology under meta-frontier data envelopment analysis framework. Findings It has been noticed that the effect of NPAs on overall technical efficiency and its various components is insignificant. The comparison of the case models (i.e. model with NPAs as bad output) with the control models (i.e. model without NPAs) reveals insignificant difference in average efficiency scores and rank distribution of commercial banks. The major source of inefficiency is technology gap (i.e. structure, setup and objectives of banking) among public, domestic private and foreign private categories of banks. Practical implications Though NPAs are increasing in Indian banking industry and specifically in Indian public sector banks because of their compulsory lending to priority sector yet the banks have huge scope to extend credit to priority sector as the NPAs have not reached at alarming stage where they start affecting adversely the efficiency performance. Originality/value Given the fact that the banking penetrations, structure and objectives differ significantly across ownership, separate frontiers for each ownership (public, private and foreign banks) category has been used to evaluate the technical efficiency levels of 81 commercial banks operating in India over the period 2005 to 2013.
PurposeThis paper seeks to measure the relationship between organizational climate (OCL) with organizational commitment meta‐analytically and the moderators influencing them.Design/methodology/approachA meta‐analytic research method was used in this research to determine the strength of relationship, fail safe n and presence of heterogeneity in study.FindingsThe unfavourable OCL (Case 2) (k=40, n=66,318) is correlated negatively with organizational commitment with confidence interval range varying from −0.552 to −0.562. The favourable OCL (Case 1) (k=89, n=53.865) is correlated positively with confidence interval range varying from 0.509 to 0.521. This research reviewed 106 valid studies after screening from 256 studies. Ten moderators were utilized to see the degree of change in relationship. Case 1 had four moderators namely gender, tenure, age, educational background, while for Case 2, there were two major moderators namely tenure and age.Research limitations/implicationsThe conclusions of this research are limited to employees based in organizations located in the USA and as such cannot be generalized for very dissimilar countries/cultures.Practical implicationsTo minimize the unfavourable OCL, role conflicts, supervisor employee relations, leadership styles, decision making needs to be minimized and focus should be more on favourable climate enhancing variables in order to have substantial employee organization commitment or employee retention.Originality/valueThis study combines the previous available research on relationship between OCL and organization commitment and strives to find the study‐based moderators for comprehension of meta‐analysis results.
Purpose Foreign firms have certain advantages which may spillover to domestic firms in the form of improvements in total factor productivity (TFP) growth. The purpose of this paper is to empirically observe the presence of TFP spillovers of foreign direct investment (FDI) to domestic firms through analyzing source of TFP growth in Indian drugs and pharmaceutical industry. Design/methodology/approach This paper examines the sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry over the period 1999 to 2014. The data of 304 firms has been used for estimation of the growth rates of TFP and its sources under stochastic frontier analyses based Malmquist productivity index framework. For frontier estimation, the Wang and Ho (2010) model has been executed using translog form of production function. Findings The results show that there exists significant TFP spillover effect from the presence of foreign equity in drugs and pharmaceutical industry of India. The results also show that the major source of TFP fluctuations in the said industry is managerial efficiency that has been significantly affected by FDI spillover variables. In sum, the phenomenon of significant Intra-industry (horizontal) efficiency led productivity spillovers of FDI found valid in case of Indian drugs and pharmaceutical industry. Research limitations/implications The number of foreign firms is very less to imitate the significant impact of foreign investment on TFP growth of Indian pharmaceutical industry at aggregated level; and the Wang and Ho (2010) model is failing to capture direct impact of FDI on technological change under Malmquist framework. Practical implications Since, there exists dominance of domestic firms in Indian drugs and pharmaceutical industry, the planners should follow the policy which not only attract FDI but also benefit domestic firms; for example, developing modern infrastructure and institution which will further help domestic firms to absorb spillovers provided by the Multinational Corporations and also accelerate the growth and development of the economy. Social implications In no case, the foreign firms should dominate the market share otherwise the efficiency spillover effect will be negative and the domestic firms will be destroyed under the self-centric approach of foreign firms protected by the recent patent laws. Originality/value The study is a unique attempt to discuss the production structure and sources of TFP spillovers of FDI in Indian drugs and pharmaceutical industry with such a wide coverage of 304 firms over a period of 16 years under Wang and Ho (2010) model’s framework. The existing studies on TFP spillovers are using either a small sample size of firms or based upon traditional techniques of measuring spillover effects.
Abstract. We consider the problem of analyzing influences in financial networks by studying correlations in stock price movements of companies in the S&P 500 index and measures of influence that can be attributed to each company. We demonstrate that under a novel and natural measure of influence involving cross-correlations of stock market returns and market capitalization, the resulting network of financial influences is Scale Free. This is further corroborated by the existence of an intuitive set of highly influential hub nodes in the network. Finally, it is also shown that companies that have been deleted from the S&P 500 index had low values of influence.
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