Resilience is a fundamental component of healthcare supply chains, as the quality and endurance of human life are dependent on them. However, there are numerous resilience-building measures, and there is a need for prioritization of those strategies. This research study aims to prioritize resilience strategies for healthcare supply chains while considering the risks that most severe, probable to occur and have the lengthiest periods of recovery.
This research study has used multi-criteria decision-making (MCDM) techniques for analysis. Initially, the criteria for prioritization of risks, i.e. severity, probability of occurrence and recovery time were assigned with importance weights through the fuzzy analytical hierarchy process (AHP). Then, these weights were used in the fuzzy technique for order preference by similarity to ideal solution (TOPIS) analysis for prioritization of risks. Subsequently, the identified risks were used for highlighting the appropriate resilience strategies through the fuzzy quality function deployment (QFD) technique.
Results indicate that Industry 4.0, multiple sourcing, risk awareness, agility and global diversification of suppliers, markets and operations are the most significant resilience strategies.
This study's limitation is that it is conducted in a general perspective, rather than reducing the context to a developing or developed country. Different areas have variable market factors, due to which potential risks occur in a different form. Moreover, resilience strategies work differently in different environments. Therefore, for future endeavors, the studies should be carried out in a limited context.
This research study proposes a novel MCDM-based approach for ranking resilience strategies, in light of the most probable, severe and long-lasting risks. In addition, this approach has been employed for the enhancement of resilience in healthcare supply chains.
