Sequential Malmquist-Luenberger productivity index for interval data envelopment analysis

Data envelopment analysis (DEA) based productivity indexes models are widely applied to evaluate the of decision-making units over a period. This study proposes index for evaluating environmentally sensitive growth while excluding possibility spurious technical regress. innovative has been created by combining directional distance functions, sequential DEA, undesirable data, and concept interval DEA. With this combination, traditional Malmquist-Luenberger (SMLPI) reformulated as an DEA problem present novel named SMLPI. We propose decomposition developed utilizing both constant returns scale variable frontiers benchmark, which allows us quantify efficiency change with data. To exhibit capability proposed extension SMLPI, we model framework Indian commercial banks measure intervals twenty-one from 2011 2018. The empirical findings elucidate that plays essential role in driving change. ICICI Bank had highest average marginal gain 1.5007 between 2018, whereas Karur Vysya bank decline 0.9411.