Search results

This paper aims to investigate the impact of corporate governance mechanisms and the environmental, social and governance (ESG) disclosure score on bank performance and financial stability. Further, this paper analyses how this relationship varies over the different ownership structures.

The paper uses a sample of 41 Indian banks (including both public sector and private sector banks) over the period ranging from 2008 to 2020. The data is analyzed in both static and dynamic frameworks using panel regression and system generalized methods of moments.

The results indicate that the frequency of board meetings has a negative influence on the performance of the banks. Gender diversity reveals both linear and non-linear relationships with bank performance. In the sample of public sector banks, the board size and promoters’ ownership have a significant negative effect on the bank's performance. In private sector banks, CEO duality adversely affects performance. Further, the results indicate that ESG disclosure score is positively linked with the profitability of banks.

This paper provides a comprehensive analysis of the impact of corporate governance mechanisms and ESG disclosure scores on bank performance and stability in the context of the Indian economy. To the best of the authors’ knowledge, there has been no empirical investigation or study that has been conducted in this respect.

This chapter of the book aims to introduce multiobjective linear programming (MLP) as an optimum tool to find the best quality engineering techniques (QET) in the main domains of supply chain management (SCM). The importance of finding the best quality techniques in SCM elements in the shortest possible time and at the least cost allows all organizations to increase the power of experts’ analysis in supply chain network (SCN) data under cost-effective conditions. In other words, this chapter aims to introduce an operations research model by presenting MLP for obtaining the best QET in the main domains of SCM. MLP is one of the most determinative tools in this chapter that can provide a competitive advantage. Under goal and system constraints, the most challenging task for decision-makers (DMs) is to decide which components to fund and at what levels. The definition of a comprehensive target value among the required goals and determining system constraints is the strength of this chapter. Therefore, this chapter can guide the readers to extract the best statistical and non-statistical techniques with the application of an operations research model through MLP in supply chain elements and shows a new innovation of the effective application of operations research approach in this field. The analytic hierarchy process (AHP) is a supplemental tool in this chapter to facilitate the relevant decision-making process.