This article attempts to examine the effect of non-performing assets (NPA) on behaviour of banks in India. The objectives of this article is to test if lending choices of Indian Banks demonstrate moral hazard and to test whether an increase in NPA ratio of banks raises riskier bank lending. We employ a threshold panel data regression model on a data set retrieved from the Reserve bank of India, which covered 45 commercial banks during the period 2009–2015, to test if lending choices of Indian banks demonstrate moral hazard. The results establish that the moral hazard hypothesis does not hold true for the given sample of India Banks, suggesting that an increase in the NPA ratio does not potentially increase riskier lending in sample banks. We find empirical evidence for the notion that ‘too-big-to-fail’ banks possibly have certain incentives to take higher risks and thus have higher NPA ratios. Graphical approach to NPA threshold explanation reveals presence of threshold; however, it could not be statistically established. Future implications of findings are evaluated. The study seminally adds to the empirical literature on use of fixed effects threshold panel data regression model in the context of Indian banks.

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Green supply chain is the process used for diminishing the exploitation of resources and producing sustainable technological development. The aim of the research work is to build the proficient Industry 4.0 green architectures index for assessing the feasible candidate choice. In the research work, a crisp numbers set-based MOORA-FMF advanced technique is executed for examining the Industry 4.0 green architectures of vendors firms. The managers are assisted with an Industry 4.0 green architectures index with optimization technique to quantify the performances of alternatives. Therefore, a real case study of a steel manufacturing plant is carried to simulate the proposed Industry 4.0 GSC architectures. Eventually, the results are presented in the conclusion.

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