Importance-Performance Analysis

INTRODUCTION: Supply chains face various disruptions from human-made to natural disasters preventing proper flow of materials and products. This problem is more important in the healthcare supply chains, especially the blood supply chains, in which human lives are at risk. Making the supply chains resilient, recently addressed by managers and researchers, can be a good way to tackle them. This study aimed to identify the most important disruptions and associated resilience strategies in the blood supply chain of Tehran, Iran, and prioritize the identified strategies based on the disruptions. METHODS: In the current study, important disruptions and associated appropriate resilience strategies were determined using previous studies and Delphi method. Then, the most important resilience strategies were identified and prioritized proposing the House of Quality and Importance-Performance Analysis (IPA) as a novel hybrid approach. FINDINGS: A total of 9 disruptions and 16 resilience strategies were determined by reviewing previous studies and asking for expert opinions. The suggested hybrid model also contributed to determining the importance of each strategy in addressing disruptions and prioritizing them in the blood supply chain of Tehran. CONCLUSION: Those strategies with high importance and low performance, such as flexibility or risk management culture, are of great importance and should be considered by managers and improved according to IPA. In addition, other strategies, such as social responsibility or redundancy, should be continued in the current way.

This study aims to analyze and identify critical success factors of Total Quality Management (TQM) for evaluating organizational performance using a framework based on the Knowledge Management (KM) approach. Initially, the study determines the success factors of TQM and KM by reviewing research history, and then assesses the significance and performance of each factor through questionnaires. Data mining algorithms are used to cluster the factors, and a Data Envelopment Analysis (DEA) model is employed to evaluate the organizational performance by considering the success factors of KM as inputs and success factors of TQM as outputs. The Return-to-Scale (RTS) variable model is used to calculate the performance indicator for the organization. The study reveals that, while KM and TQM have some differences rooted in their distinct focus, they also have many similarities that can complement each other if properly planned.