Developing a Newsvendor Model based on the Relative Competence of Suppliers and Probable Group Decision-making

The problem of selecting the suppliers along with their Economic Order Quantity (EOQ) has always been an important issue in the Newsvendor model. Multiple qualitative and quantitative criteria are needed to be regarded for making a better supplier selection while performing trade-offs among them. An approach that can take all criteria into account in the selection of suppliers has not been developed yet in the Newsvendor model. Multiple criteria decision-making (MCDM) can be leveraged to make trade-offs among multiple criteria.

This study sought to develop a solution to the Newsvendor problem, accounting for the most significant criteria in supplier selection and product reliability so that the total cost of the chain would be minimized in a multi-product and multi-period model with multiple suppliers. This approach adopted the Bayesian Best Worst Method (BWM), which is one of the MCDM methods, to rank the criteria and also implemented the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritize the suppliers. Then, the suppliers' weights were used as the proposed model inputs. The results obtained from Bayesian BWM validated the effectiveness of the presented approach. The objective function was set in a way that a retailer's profit and weight value of products considering the ranking of suppliers were maximized. The goal was to find optimal order quantity allocating to suppliers. To convert the multi-objective model to a single-objective, the Lp-metric method was used.

To evaluate the derived model, a case study with real data in the electronic supply chain was investigated. The developed model for the Newsvendor problem could find the best suppliers by considering a combination of qualitative and quantitative criteria in selecting them. In this research, the real-world case study was considered in the electronics industry, which allowed the researchers to make a better evaluation of the model.

The obtained results indicated that the retailer uses a combination of suppliers in each period for optimal order allocation to profit-maximizing considering product's reliability and the weight value of products.