Blood supply chains (BSCs) play a strategic and crucial role in healthcare systems especially in unexpected situations such as earthquakes and pandemic outbreaks. Nevertheless, measuring the sustainability and resilience of BSCs is a major challenge for many decision-makers in healthcare systems. To this end, this paper presents an advanced network data envelopment analysis (NDEA) method to evaluate the sustainability and resilience of BSCs. We deal with BSCs, including blood collection centers (BCCs), blood production centers (BPCs), and blood distribution centers (BDCs). A new directional distance function (DDF) is also developed for evaluating both the overall and stage efficiency scores. Our proposed model can deal with different types of data, including integers, undesirable outputs, negative, zero, and positive. The undesirable outputs are the outputs that adversely impact the performance of DMUs. Moreover, the developed method addresses the sustainability and resilience of BSCs. A case study is provided to demonstrate the usefulness of the proposed model.

血液供应链 (BSC) 在医疗保健系统中发挥着战略性和关键性作用，尤其是在地震和大流行病爆发等意外情况下。然而，衡量 BSC 的可持续性和弹性对于医疗保健系统的许多决策者来说是一项重大挑战。为此，本文提出了一种先进的网络数据包络分析（NDEA）方法来评估 BSC 的可持续性和弹性。我们与 BSC 打交道，包括血液采集中心 (BCC)、血液生产中心 (BPC) 和血液配送中心 (BDC)。还开发了一种新的方向距离函数 (DDF)，用于评估整体和阶段效率得分。我们提出的模型可以处理不同类型的数据，包括整数、不良输出、负数、零和正数。不良输出是对 DMU 性能产生不利影响的输出。此外，所开发的方法解决了 BSC 的可持续性和弹性。提供了一个案例研究来证明所提出模型的有用性。