Resource allocation and target setting based on virtual profit improvement

Abstract

One application of Data Envelopment Analysis (DEA) is the resource allocation and target setting among homogeneous Decision Making Units (DMUs). In this paper, we assume that all units are under the supervision and control of a central decision making unit, for instance chain stores, banks, schools, etc. The aim is to allocate available resources among units in a way that the so-called organisational overall "virtual profit" is maximized. Our method is highly flexible in decision making to achieve the goals of the Decision Maker (DM). The resulting production plans maintain the following characteristics: (1) the virtual profit of each unit is calculated with a common set of weights; (2) the selected weights for calculating the virtual profit prevent the virtual profit of the system from getting worse; (3) the virtual profits of less profitable units are improved as much as possible. The proposed method is illustrated with a simple numerical example and a real life application.

A Scenario-based Model for Resource Allocation with Price Information

“…. This means that the optimal solution of the RA model (15) satisfies the constraint set (10.4) of the RA model (10). Therefore, (𝜆 * , Δ𝑋 * , Δ𝑌 * ) satisfies all constraint of the RA model ( 10)…”

“…[6] incorporated the cross-efficiency measures in the centralized RA problem. [15] considered the target setting line in the RA problem and concentrated on the profit improvement of targeted units. [17] studied the centralized RA models based DEA from an axiomatic perspective.…”

“…The next theorem compares our second RA model with the second RA model proposed by [7], which is as follows Theorem 3. Considering the same managerial assumptions and expecting the same output level of 𝑌 *( + Δ𝑌 *( , the total cost of RA model (10) is not greater than the total cost of model (15).…”

Second order cone programming formulation of the fixed cost allocation in DEA based on Nash bargaining game

“…They seek to find appropriate distribution criteria to get a fair allocation of cost among subsets [28]. In several recent research, data envelopment analysis (DEA) based models are used to do this task [8,19,20,22,27,31,33]. DEA is a non-parametric approach for identifying the best performance of the same decision making units (DMUs) introduced by Charnes, Cooper and Rhodes [7].…”