Transforming Resource Allocation Strategies: Harnessing Pseudo-Returns To Scale For Optimal Performance

Abstract

In the centralized data envelopment analysis (DEA) model, one unit supervises others, resulting in the concentration of all resources within the organization. Then, resource allocation to all units is performed based on the specific conditions of the organizations. If restrictions are applied on each corresponding indicator for each unit, they are also taken into account. The aim of this paper is to develop resource allocation technology, by introducing the concept of pseudo-returns to scale. So far, in the technologies presented, the development coefficient has been considered the same across the indicators. However, this is not always practical. Therefore, in this article, technologies have been proposed where the indices are categorized into different groups based on the flexibility of their development coefficients. The change coefficient for the sum of certain indicators is assumed as a multiple of the development coefficient for the sum of other indicators. Corresponding models are designed based on the proposed technologies. By interacting with system managers and solving models, resource allocation is accomplished ideally, aligning with the desired target setting. The primary focus of this paper lies in the developed of centralized data envelopment analysis with development of principle returns to scale. The designed models are implemented on a numerical example. Finally, it compares the total resources consumed by each group of input indicators and the total output produced by each group of output indicators from the proposed models with previously presented models. It also examines the percentage of resource savings and the percentage of profit obtained from solving the proposed models.