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Supply chain is a network of different business units which focuses on integration among all units in order to produce and distribute end products to the customer. Nowadays, due to increased uncertainty in customer demand, it is necessary to be sure that the supply chain networks operate as efficient as possible in order to satisfy the customer demand at the lowest cost. Enhancing the efficiency of the supply chain necessitates the interaction between different members of the supply chain which can be achieved through supply chain management. Hence, the development of modeling approach in order to understand and analyze the dynamic behavior of supply chains is brought into consideration. This paper proposes a system dynamic simulation model for manufacturing supply chain. System dynamic is used as suitable method to understand and analyze the interactions of various components via feedback structure. The objective of this paper is to simulate the manufacturing supply chain of an electronic manufacturing company in Malaysia. The simulation model is used to study the system’s behavior (in terms of production rate, inventory levels, and backlog orders) under two different operational conditions (named as fixed and varied capacity policies) and compare their efficiency in terms of total cost. The analysis shows that the proposed operational condition, which is varied capacity policy, improves the system efficiency in terms of cost.

Supply chain is a complex system with many challenges to accomplish an important goal. Since the dynamical essence of supply chain is stemmed from the customer demands so decision making will be a major issue in this particular topic. However the decisions wont be usually in an optimum level because of the higher complexity of the system. In addition, the various supervisions of lots of groups with variety of managerial issues on different echelons have made some dilemmas to achieve the overall goal of the system. The aim of this study is developing a system dynamic model for better understanding of the blood supply chain behavioral pattern. Also the reflection of the current model is obtained and some comparisons among the current model and four different scenarios are investigated. The analysis at the end shows the system performance under four various investigated scenarios.

The blood supply chain is a complex system with a multi-echelon structure. Hence, the integration of various interconnected elements, which should be synchronized appropriately, is a necessity to meet the patients’ requirements. The performance of the blood supply chain is a function of different variables that are dependent of each other. Therefore, the main aim of the chain is the optimization of the overall supply chain by considering the dynamic behavior of the system. The purpose of this study is to develop a system dynamic simulation model for a complex blood supply chain in order to improve the average level of inventories. The developed model is based on three echelons with a centrality on a regional blood center. The performance of the supply chain network in the current condition is investigated and based on the objectives, 17 scenarios were experimented for improving the average level of inventories to avoid outdates while there are not any backlogged orders. In addition, the best values of the investigated parameters (safety stock, supplier preparing lead time, in transit time and separation time) were determined.

Crowd-shipping platforms have the potential to serve as flexible and low-cost logistics solutions for small and medium-sized enterprises (SMEs), which tend to have proportionally higher logistics costs than large companies. By increasing visibility and access to underutilized vehicle capacity, crowd-shipping platforms can offer lower rates than traditional delivery services. Leveraging excess capacity on premeditated delivery trips can also improve logistics efficiency and reduce emissions. However, high platform fees, insufficient carriers, and difficulty finding suitable platforms are common barriers to widespread adoption. This research evaluates the degree to which existing commercial crowd-shipping platforms can provide suitable transportation solutions for SMEs. A systematic search yielded 400 platforms, which were evaluated for SME suitability by requesting quotes for delivery service from each platform, based on typical shipping requirements of two agriculture-based SMEs in Texas. The responses and quotes that were received, as well as feedback from the case study SMEs, indicate that most existing platforms are unlikely to meet the needs of SME shippers. The results suggest ways in which crowd-shipping platform managers could take advantage of this market opportunity by tailoring the services and features of their platforms to better meet the expectations of SMEs.

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