When threatened with catastrophic political or economic fluctuations, a firm might be forced to consider relocating their supply chain to reduce the risk. Such a relocation necessitates a series of changes, so making the right decision is crucial for sustainable development of the company. In the past, various models have been developed to help managers to select the optimal location. However, most of these considered the factors independently but in the real world, these factors have a mutually influential relationship. This study purposes a hybrid multiple criteria decision making (MCDM) model to provide decision makers with a comprehensive framework to evaluate the best strategies to solve relocation problems, which also considers the interdependency between criteria. The model incorporates the DANP (Decision Making Trial and Evaluation Laboratory-based Analytic Network Process) model (subjective weight) and entropy method (objective weight) to determine the weights of the criteria. Then, the modified VIKOR (VIšekriterijumsko Kompromisno Rangiranje) method is applied to select the optimal alternative for relocation. The usefulness of the model is demonstrated by taking an electronics manufacturing company with a global supply chain as an example. The results indicate that the proposed hybrid model can assist companies in choosing the best locations for their supply chains for sustained development.

The global economy has been hit by the unexpected COVID-19 outbreak, and foreign investment has been seen as one of the most important tools to boost the economy. However, in the highly uncertain post-epidemic era, determining how to attract foreign investment is the key to revitalizing the economy. What are the important factors for governments to attract investment, and how to improve them? This will be an important decision in the post-epidemic era. Therefore, this study develops a novel decision-making model to explore the key factors in attracting foreign investment. The model first uses fuzzy Delphi to explore the key factors of attracting foreign investment in the post-epidemic era, and then uses DEMATEL to construct the causal relationships among these factors. To overcome the uncertainty of various information sources and inconsistent messages from decision-makers, this study combined neutrosophic set theory to conduct quantitative analysis. The results of the study show that the model is suitable for analyzing the key factors of investment attraction in the post-epidemic period. Based on the results of the study, we also propose strategies that will help the relevant policy-making departments to understand the root causes of the problem and to formulate appropriate investment strategies in advance. In addition, the model is also used for comparative analysis, which reveals that this novel approach can integrate more incomplete information and present expert opinions in a more objective way.

The effectiveness of the national/regional healthcare system is one of the keys to prevent the spread of COVID-19. In the face of this unknown pandemic, where the healthcare system should continue to be promoted and improved are crucial decision issues. In the past, most studies have used the subjective opinions of experts for analysis and decision-making processes when investigating complicated decision-making problems. However, such decision-making processes are easily influenced by experts’ preferences. Therefore, this research proposes a soft computing technology that integrates CRiteria Importance Through Intercriteria Correlation (CRITIC) with the modified VlseKriterijumska Optimizacija I Kompromisno Resenje in Serbian, meaning multicriteria optimization and compromise solution (modified VIKOR) technique to reduce the impact of expert preference. In order to cope with the fact that COVID-19 has spread globally and to discover problems quickly and effectively, this study uses the global health security (GHS) index as the evaluation framework and conducts overall discussions in 195 countries/regions around the world. It is verified that the technology of soft computing can be used for continuous promotion and improvement of the national/regional healthcare system. This technology facilitates decision makers to know the gap of performance between the current healthcare system and the aspiration level. Finally, based on these gaps, we provide management advice to help improve these systems.