A Piecewise Objective Probabilistic Optimization Approach as Decision Making for Supplier Selection and Inventory Management With Price Discount

A mathematical model in the form of a piecewise objective probabilistic optimization approach was proposed in this study as the new decision-making tool to solve supplier selection and inventory management problems. The focus was on price discount and uncertain parameters such as product demand, product defect rate, and late-delivery product rate, which were approached using random variables with some known probability distribution function. Meanwhile, the decision variables contained in the model include the product volume ordered by each supplier at each time for each product type and those stored in the inventory to minimize the total operational cost in the problem. The corresponding optimization problem was solved using a probabilistic programming algorithm via the LINGO optimization tool. The computational simulation showed the proposed model provided the optimal decision, and this means it can be used as a decision-making tool by industrial practitioners.

A TISM and MICMAC Analysis of Factors During the COVID-19 Pandemic in the Indian Apparel Supply Chain

The objective of this study is to explore the challenges faced by the Indian apparel supply chain in the wake of COVID-19 to identify the factors that are being affected and build a multilevel hierarchy model to prioritize the factors and understand their inter-relationships. An intensive literature review was conducted and many experts from apparel supply chain were consulted. The study was conducted by the help of a survey sent to these experts from different echelons in the apparel industry. The data was then analysed using Total Interpretive Structural Modelling (TISM). The “Difficulty in export order fulfilment” factor is found to be the most sensitive factor which means that it is present in the TISM model hierarchy in a place that it is affected by most of the factors and in-turn impacts factors like operational cost, change in marketing strategy, change in consumer buying pattern, which impact Profitability and Cut-off in employment. “Cut-off in employment” is found to be most impacted by all other factors in TISM model.

Is Collaborative Planning a Determinant of Financial Performance in Supply Chain?

As both the practice and the results of the contemporary studies show, collaborative planning, forecasting and replenishment (CPFR) improves the financial performance of supply chain members. The study investigated how Russian companies - the supply chain members, implement the process of CPFR in practice, and how implementation of the concept of collaborative planning affects the financial performance of the companies. The analysis of the obtained results revealed that collaborative planning drives the revenue of companies participating in the supply chain.

Research on Quality Evaluation of Online Reservation Hotel APP Based on a RBF Neural Network and Support Vector Machine

In order to evaluate the quality of online reservation hotel APP, RBF neural and support vector machine are used to evaluate the quality of online reservation hotel APP. First, the basic theory of the RBF neural network is studied, and the training algorithm of the RBF neural network is designed. Second, the basic model of support vector machine is analyzed, and the training algorithm is designed. Third, the evaluation index system of online reservation hotel APP is designed, and the weight of every index is established based on questionnaires and expert interview, and the evaluation simulation is carried out for 25 online reservation hotel APP, results show that the RBF neural network and support vector machine can obtain consistent evaluation results, and the support vector machine has better evaluation performance.

A Safety Signaling Game for Small and Medium-sized Manufacturing Enterprises in the Supply Chain

Due to information asymmetry and a prevailing focus on production that ignores safety among small and medium-sized manufacturing enterprises (SMMEs), it is difficult for core enterprises in the supply chain (SC) to establish partnerships with SMMEs that have a high safe production level (SPL). We found that SMMEs would conceal their real SPL when being selected as core enterprise suppliers. This is known as adverse selection. According to the principal-agent theory, we built a signaling model to analyze the conditions of the pooling equilibrium and the separate equilibrium of the signaling game between core enterprises and SMMEs. The equilibrium results showed that adjusting the signal cost parameters of the SMMEs can guide the market to separate equilibrium and stop SMMEs from concealing or exaggerating their SPL. We also discuss corresponding suggestions. This research can reduce SC risks and promote the establishment of sustainable cooperative relationships between core enterprises and SMMEs with high SPLs. This study is applicable globally.