Abstract
The network data envelopment analysis (NDEA) technique has been recently developed to measure the relative efficiency of complex production systems. NDEA models provide more meaningful and informative results in comparison to the conventional black-box DEA approach that ignores the operations of the component processes. Regarding the centralized decision-making systems, normal management imposes common resource constraints to maximize produced outputs and minimize consumed inputs. The present study seeks to introduce new centralized resource allocation models in two-stage network production systems. This intra-organizational perspective also provides the possibility of closing down some of the existing units to improve system efficiency. To do so, three scenarios of centralized DEA models are introduced to take advantage of this possibility. A simple numerical example is used for illustration purposes. An empirical application of the proposed approach to the twenty branches of a university is also presented to show the applicability of the new approach.
Highlights
The non-parametric frontier analysis was first introduced by Farrell [21] and later developed into Data Envelopment Analysis (DEA) by Charnes et al [9] and Banker et al [6], as a linear programming-based technique for assessing the efficiency of a set of homogenous decision-making units (DMUs)
This paper attempted to introduce a procedure for efficient resource allocation in a centralized decisionmaking setting for a two-stage network system
This study aimed to evaluate the possibility of closing some DMUs in the interest of non-radial efficiency
Summary
The non-parametric frontier analysis was first introduced by Farrell [21] and later developed into Data Envelopment Analysis (DEA) by Charnes et al [9] and Banker et al [6], as a linear programming-based technique for assessing the efficiency of a set of homogenous decision-making units (DMUs). This type of situation occurs whenever all of the units belong to the same organization (public or private), which provides the units with the necessary resources to obtain their outputs In such a decision-making environment, the centralized decision-maker aims to minimize the overall input consumption (or to maximize the overall output production) by all DMUs, instead of considering the consumption of each DMU separately [15, 18]. In a centralized DM environment, a set of units operates under a central unit with the power to control certain decision parameters such as the allocation of resources to these units To cope with such a situation, this research proposes a centralized DEA-based approach by considering the organizational setting.
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