Incentivizing units in centralized systems: A slacks-based approach
本文指出传统基于投入导向的激励方法可能导致不公平，提出一种非导向的基于松弛的超效率方法，用于集中资源分配场景下的激励参数估计，并通过实际数据验证其有效性。
Having based his incentivisation strategy on cost reimbursement, Bogetoft developed an incentive formula. Given that inputs are typically costs, different input-oriented methods were proposed to estimate the parameters of the incentive formula. Recently, several radial-based input-oriented super-efficiency measures have been developed in the centralized resource allocation (CRA) context for estimation of the incentive formula parameters. We show, using examples, that input-oriented incentive methods can lead to unfair incentive mechanisms. It transpires that fair incentive mechanisms can be achieved via non-oriented methods. To this end, we propose an non-oriented slacks-based super-efficiency method in the CRA context using which we estimate the incentive formula parameters. Given that the slacks-based measures can distinguish between weak and strong efficient units, such measures do not suffer from the known deficiencies of the radial CRA-based incentive methods. The validity and applicability of the proposed approach are demonstrated using a real dataset. We consider percentage of relative returns, and use statistical indices and visualization techniques to compare the incentive plans obtained from the proposed method with those resulted from other existing CRA-based incentive methods.