Joint Inventory and Pricing Policy for an Online to Offline Closed-Loop Supply Chain Model with Random Defective Rate and Returnable Transport Items

The impact of blockchain on optimal incentive contracts for online supply chain finance

In China, supply chain finance is still in infancy. However, it is the problems of information sharing, trust transfer, and risk management that have been making it difficult to meet the financing needs of small- and medium-sized enterprises (SMEs) in supply chain. The emerging blockchain technology, with its unique decentralization, traceability, and other characteristics, has found a digital solution for traditional supply chain finance. Although blockchain has attracted widespread attention and there are more general descriptions of blockchain application areas, there are few researches on the impact mechanisms of blockchain in-depth. Especially in the field of supply chain finance, there is little research on optimal incentive contract in online supply chain finance empowered by blockchain technology. Therefore, this paper explores the influence of blockchain technology maturity on participants, and thus finds the optimal incentive contract in online supply chain empowered by blockchain technology. Because of the mastery of blockchain technology, platforms believe they are well protected against risk and may behave irrationally. Therefore, this paper considers the overconfident behavior of blockchain supply chain finance platform in actual operation, and then applies the principal-agent model and incentive theory to design the incentive mechanism between platforms, banks, and central banks. Finally, numerical analyses show that overconfident behavior and the maturity of blockchain technology have an impact on the optimal decision for the whole supply chain.

An Automated Smart EPQ-Based Inventory Model for Technology-Dependent Products under Stochastic Failure and Repair Rate

With the ever-growing technology development, high-tech products such as mobile phones, computers, electromagnetic devices and smart devices are facing high design and production modification requirements with relatively shorter life cycles. For instance, every forthcoming smart phone goes out of production in a shorter period after its launch, followed by its next generation. The design of high-tech products requires high investments in smart and automated manufacturing technology to ensure higher production efficiency. For high-tech products with short life spans, the manufacturing performance-quality variable is an important design parameter that affects system reliability, production efficiency and manufacturing costs. Major performance-quality factors of a manufacturing system which affect productivity and reliability of the manufacturing process are discussed in this research. The study investigates an integrated smart production maintenance model under stochastic manufacturing reliability for technology dependent demand and variable production rate. The smart unit production cost is a function of manufacturing reliability and controllable production rate, as a manufacturing system can be operated at different production rates within designed limits μ ϵ [ μ m i n , μ m a x ] . Manufacturing reliability is increased through investment in smart manufacturing technology and resources. The integrated smart production maintenance model is formulated under general failure and repair time distributions and the optimal production maintenance policy is investigated under specific failure and repair time distributions. A mathematical model is developed to optimize the manufacturing quality-performance parameter, variable production rate, per unit technology investment and production lot size. The total cost function is optimized through the Khun–Tucker method. The mathematical model is also validated with numerical analysis, comparative study, and sensitivity analysis for model key parameters.

A Constrained Production System Involving Production Flexibility and Carbon Emissions

The proposed study presents an economic lot size and production rate model for a single vendor and a single buyer setup. This model involves greenhouse gas (GHG) emissions from industrial sources. The carbon emissions in this model are considered as two types: direct emissions and indirect emissions. The production rate affects carbon emissions generation in production, i.e., generally, higher production rates result in more emissions, which is governable in many real-life cases. The production rate also impacts the process reliability and quality. Faster production deteriorates the production system quickly, leading to machine failure and defective items. Such reliability and quality problems increase energy consumptions and supply chain (SC) costs. This paper formulates a vendor-buyer SC model that tackles these issues. It considers two decision-making policies: integrated or centralized as well as decentralized, where the aim is to obtain the optimal values of the decision variables that give the minimum total SC cost. It includes the costs of setup, holding inventory, carbon emissions, order processing, production, reworking, and inspection processes. The decision variables are the production rate, lead time, order quantity, the number of shipments, and the investments for setup cost reduction. In the later sections, this paper compares the numerical outcomes of the two centralized and decentralized policies. It also provides sensitivity analysis and useful insights on the economic and environmental execution of the SC.

Pricing Strategy of Construction and Demolition Waste Considering Retailer Fairness Concerns under a Governmental Regulation Environment

In order to investigate the issues of the recycling and remanufacturing of construction and demolition waste (C&D waste), this paper develops a closed-loop supply chain (CLSC) consisting of a manufacturer, a retailer, and a recycler, considering both the retailer's fairness concern psychology and governmental regulations. Four mathematical models are developed for the calculations, and the models are solved through game theory. In both the decentralized and centralized scenarios, the members' strategies are discussed and the optimal values of decision variables are determined. A numerical study is carried out for sensitivity analyses to verify the accuracy of the theoretical conclusions. The results reveal that retailer fairness concerns lead to a decrease in the wholesale price of building materials and negatively affect manufacturers' profits. Additionally, governmental regulations can effectively increase the recycling amount and improve the utilization rate of C&D waste, and promote a virtuous cycle of the recycling and remanufacturing of C&D waste.

Integrated Vendor–Buyer Lot-Sizing Model with Transportation and Quality Improvement Consideration under Just-in-Time Problem

This paper deals with the problem of transportation and quality within a Just-in-Time (JIT) inventory replenishment system. Formerly, transportation and quality problem are often modelled separately in most integrated inventory lot-sizing models. Hence, this paper develops an integrated vendor-buyer lot-sizing model by considering transportation and quality improvements into a JIT environment. The model is developed for minimising a total vendor–buyer system cost by optimising decisions such as delivery quantity, production batch, number of shipments, and process quality. Numerical examples and sensitivity analysis are provided to illustrate the proposed model. The developed model was also compared with an enumeration method to analyse the effectiveness of the proposed model to find the optimum solution. The results emphasise that the proposed model contributes to a new approach and obtains a near optimum solution for inventory replenishment decisions. The results are also beneficial to JIT practices as the model can improve the transport payload and reduce the chance of defective products and improving quality-related costs.

Optimum Design of a Transportation Scheme for Healthcare Supply Chain Management: The Effect of Energy Consumption

The perishability of blood platelets complicates the management of their supply chain. This paper studies the impact of energy consumption and carbon emissions of transportation activities in a blood platelet supply chain. Energy consumption and carbon emissions vary significantly, and the effective location-allocation of blood facilities is a key strategy for the optimal use of energy. The total cost of the supply chain for perishable products is minimized when energy consumption is optimized. The proposed model is too complex to be solved with existing methodologies; therefore, mathematical tools are used to solve it. A numerical experiment is carried out to validate the proposed model, and graphical representations are presented for better visualization of the study’s outcomes. The results of the numerical studies confirm that the selected locations of blood facilities are optimal for the maximization of energy efficiency and minimization of the total cost.