Extended DEA Models for scale Economies and Eco-efficiency

Most of the real-life production processes are multi-stage in nature. Characterizations of such processes via concepts like `returns to scale`, `economies of scope` and `capacity utilization` are common for the analysis of business decisions and public policy formation. Most of the relevant literature hitherto fails to recognize the links between these three concepts and the underlying sources of scale and scope economies. The contribution of this proposed project will provide: (1) an analysis of the economic linkage of the measures of scale and scope with that of capacity utilization in multi-stage production models and the empirical verification of this linkage, (2) the development of new variants of DEA model to reveal scale and scope economies arising from `process indivisibilities`, (3) the demonstration of the empirical distinction between returns to scale and economies of scale through two variants of DEA models, (4) a comparison of two methods: DEA and econometric method, for estimating scale economies in two scenarios: when the cost-based technology set is convex and when it is not, to assess the relative strengths of these two methods, (5) the development of an intertemporal DEA model for analyzing eco-efficiency, and then integrating the impact of regulation to examine and contrast the change in eco- efficiency over time. To achieve the aforementioned goals, the following objectives are set as follows: Developing non-convex data envelopment analysis (DEA) models to measure scale and scope economies arising from process indivisibilities in multi-stage production models, and analytically verifying the economic linkage of the measure of `scale` and `scope` with that of `capacity utilization`. Developing two distinct sets of basic DEA models to estimate returns to scale and economies of scale as it has often recently been argued that in the case of imperfect competition these two concepts have distinctive causative factors that do not permit them to be used interchangeably. The Indian commercial banking sector is taken as an illustration highlighting the empirical distinction between these two concepts. Compare and contrast the results concerning scale economies behavior obtained from DEA and stochastic translog cost frontier models in two scenarios: when cost-based technology set is convex, and when it is not, to highlight the relative strengths of these two methods. Developing an intertemporal DEA model for analyzing the change of eco-efficiency behavior, and then integrating the impact of regulation to examine and contrast the change in eco-efficiency over time.