TY - JOUR
T1 - Measuring the sustainability and resilience of blood supply chains
AU - Kazemi Matin, Reza
AU - Azadi, Majid
AU - Saen, Reza Farzipoor
PY - 2022/10
Y1 - 2022/10
N2 - 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.
AB - 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.
KW - Blood supply chains (BSCs)
KW - Integer data
KW - Negative data
KW - Network data envelopment analysis (NDEA)
KW - The Covid-19 pandemic
KW - Undesirable outputs
KW - Zero data
UR - http://www.scopus.com/inward/record.url?scp=85108812469&partnerID=8YFLogxK
UR - https://www.sciencedirect.com/science/article/pii/S0167923621001391?via%3Dihub
U2 - 10.1016/j.dss.2021.113629
DO - 10.1016/j.dss.2021.113629
M3 - Article
AN - SCOPUS:85108812469
SN - 0167-9236
VL - 161
JO - Decision Support Systems
JF - Decision Support Systems
M1 - 113629
ER -