Development of a non-radial model for resource reallocation using network data envelopment analysis

Abstract

Public and private sector organizations continually seek to optimize strategies for sustained competitiveness by reallocating resources efficiently among various institutions. This research introduces a non-radial resource reallocation model employing network data envelopment analysis to address this need. The study introduces an approach to redistributing resources in a dynamic network setting over multiple periods. It takes into account indicators of both negative outcomes, aiming to improve the overall effectiveness and efficiency of companies within a holding structure. The research outlines a methodology, including data collection, modeling assumptions, decision variables, and constraints for implementing this reallocation model. By focusing on resource allocation in network systems over periods, this study provides a solid foundation for enhancing resource allocation efficiency in organizations. Additionally, it addresses the complexities associated with resource allocation compared to settings. The proposed dynamic network DEA model considers both temporal aspects in evaluations. Demonstrates its potential for resource allocation in multi-stage processes through applications within the banking industry. One key finding is the importance of recognizing shared constraints among Decision Making Units (DMUs). Considering the impact of restrictions, like government regulations, on decision-making processes and overall efficiency. The created dynamic network DEA model introduces an inventive method to redistribute resources in intricate organizational setups. It offers perspectives for decision-making procedures. Moreover, it sets the stage for further exploration into different indicators and the impact of diverse government interventions on resource allocation effectiveness.