An integrated model for rice supplier selection strategies and a comparative analysis of fuzzy multicriteria decision-making approaches based on the fuzzy entropy weight method for evaluating rice suppliers.

Rice, being a staple food in many countries, necessitates the identification of reliable suppliers to ensure a steady supply. Consequently, it is vital to establish trustworthy vendors for various types of this essential grain who can meet stringent product quality standards. This study aims to identify, analyze, rank, and select primary rice suppliers. The study emphasizes the importance of selecting and managing suitable providers to meet customer demands, proposes a ranking model for rice suppliers, and introduces developed fuzzy MCDM techniques. It proposes an integrated model for selecting rice suppliers, considering factors related to the processes before, during, and after selecting providers within a defined framework. The outcomes shows that rice supplier selection strategy can efficiently identify reliable rice suppliers, improve buyer value, reduce procurement risk, enhance efficiency, and establish strong supply chain relationships in complex decision-making processes. To assess suppliers, the study introduces two advanced integrated approaches and compares them. The fuzzy entropy weight method (EWM) was used to determine the criteria weights. The ranking of rice suppliers was achieved using a fuzzy multi-objective optimization based on ratio analysis (MOORA), fuzzy complex proportional assessment (COPRAS), and combinations of these two methods in different approaches. The methodology supports decision-makers in a rapidly evolving global environment by assisting importers, traders, suppliers, procurement, and logistics management, particularly for non-rice-cultivating countries in rice importation and supplier selection. The numerical analysis is grounded in a real-world case study of selecting rice suppliers in Jordan. The findings reveal that the various strategies yield both similar and different results. Furthermore, the integrated method is considered the most accurate for evaluating rice imports and suppliers, aligning closely with the reality of the current situation.

Applications of MCDM approach (ANP-TOPSIS) to evaluate supply chain solutions in the context of COVID-19.

COVID-19 has impacted various aspects of life and business. The economic panic and effects caused by the pandemic have led to disruptions in most supply chains (SCs) worldwide. Our research aims to analyse the impact of COVID-19 on SCs and enable organisations to prioritise solutions based on their relative importance. The research consists of two main phases. Phase I analyses the impact of the pandemic on SCs in terms of challenges, concerns, steps, and solutions with the goal of SC resilience. The second phase proposes a merged Analytic Network Process-Technique for Order Preference by Similarity to Ideal Solution framework (ANP-TOPSIS) to prioritise the solutions that considers the complicated interrelationships between the factors involved in decision-making. The proposed model increases the efficiency of the decision-making process and helps decision makers effectively select solutions based on their importance and impact on business. The results indicate that SCs should continuously utilise technology to withstand future competition and crises.