This systematic review addresses a significant gap in the existing literature by examining the
intricate relationship between management practices and Industry 4.0 technologies in …

Data envelopment analysis (DEA) is a widely used mathematical programming approach for
assessing the efficiency of decision-making units (DMUs) in various sectors. Inverse DEA is …

In recent years, natural disasters such as sudden changes in climate, earthquakes,
typhoons, storms, and snowstorms have occurred frequently around the world, which have …

As a powerful efficiency evaluation tool, cross-efficiency measurement in data envelopment
analysis (DEA) has been proverbially concerned. However, most of existing studies on cross …

The main objective of this study is to propose a network data envelopment analysis (NDEA)
model and a deep learning approach for forecasting the sustainability of healthcare supply …

Supply chains are getting more and more complex with addition of new sustainability
paradigms in highly fragile and vulnerable environments as the world is transforming faster …

Data Envelopment Analysis (DEA) is one of the fastest growing approaches to solving
management problems for the multi-criteria evaluation of the efficiency of homogeneous …

Blood supply chains (BSCs) play a strategic and crucial role in healthcare systems
especially in unexpected situations such as earthquakes and pandemic outbreaks …

In recent years, globalization has highlighted the vital role of sustainable supply chains
(SSCs) in the development of organizations and production systems to increase profits. The …

The industrial sector is the largest energy consumption sector and major source of
environmental pollution in China. Improving the industrial eco-efficiency is significant for …