Productivity analysis of Indian non-bank financial institutes under uncertainty: A dynamic two-stage DEA approach

The conventional multi-period two-stage Data Envelopment Analysis (DEA) model assesses the overall performance of a production system comprised of two stages across multiple time periods. In situations of uncertainty, this study incorporates fuzzy sets theory to measure efficiency both on an overall and period-specific basis. The major contribution of this research lies in its examination of productivity changes over time within the framework of fuzzy two-stage DEA. Specifically, the study provides valuable insights into Indian non-bank financial institutes (NBFIs) using the proposed two-stage DEA approach. NBFIs are structured in two consecutive stages: premium acquisition and profit operations, with the former stage being linked sequentially to the latter. The central idea of this investigation is to delve into the internal operations of both public and private NBFIs across multiple periods, taking into consideration the presence of negative data. The multi-period two-stage DEA model is presented in Indian NBFIs for the first time in this research by incorporating the handling of negative data framework under uncertainty. The key findings reveal that private NBFIs in India demonstrate lower efficiency compared to their public counterparts. In other words, none of the NBFIs are fully efficient, with public NBFIs consistently outperforming their private counterparts. To deepen the analysis, the second phase employs regression analysis to evaluate the impact of various external factors. The results highlight that factors such as size and return on assets (ROA) have a more substantial influence on efficiency than age and firm type.