The Values of Safety Factor Optimization and Coordination under Random Supply and Demand
Jian, Liu, Weiming, Yi, International Journal of Entrepreneurship
The classic inventory management dominantly pays attention to the internal inventory control of business, and is neglectful of supply chain coordination and partnering. The local optimization approach results in impeded logistics, cost increase, lack of business and supply chain competitiveness. Supply chain coordination and partnering become significant means to improvement of supply chain performance, enhancement of business competitiveness. The paper introduces concept of effective inventory level, which is used to evaluate upstream shortage's impact on downstream inventory, models the inventory at warehouse and retailer under random lead time and demand, and makes the global optimization of safety factor to minimize channel inventory cost. It is shown that optimization and coordination of safety factor lead to inventory cost savings at two sites, especially under large lead time variability and stock value-adding rate. Meanwhile, authors present the coordination mechanism of global optimization of safety factor, i.e., cost-sharing contract, which makes both supplier and buyer benefiting from global optimization. Finally, this paper makes sensitivity analyses on value of global optimization.
Inventories exist throughout the supply chain in various forms for various reasons. At any manufacturing point, distribution warehouses and retailers, they may exist as raw materials, work in progress, or finished goods. Ballou (1992) estimates that carrying these inventories can cost anywhere between 20 and 40% of their value per year. Inventory cost is a key factor that influences supply chain performance. Lee and Billington (1992) site several opportunities that exist in managing supply chain inventories. Among them are making coordinated decisions between the various echelons, incorporating sources of uncertainty, and designing proper supply chain performance measures. The central premise here is that the lowest inventories result when the entire supply chain is considered as a single system. Such coordinated decisions have produced spectacular results at Xerox (Stenross and Sweet, 1991), and at Hewlett Packard (Lee and Billington, 1995), which were able to reduce their respective inventory levels by over 25%.
Inventory systems are often subject to randomly changing environmental conditions that may affect the demand for the product, the supply, and the cost structure. The environment represents various important factors such as the randomly changing economic conditions, market conditions for new products or products that may be obsolete or any exogenous condition that may affect the demand as well as the supply and the cost parameters. Supply chain models in the literature that are related to uncertain environment mostly concentrate on the demand process, which may vary stochastically in a random environment. In most of the inventory models that involve uncertainties in the environment, the attention has been focused on the probabilistic modeling of the customer demand side. For example, large amount of literature have made qualitative and quantitative research on Bullwhip Effect of demand variability (Lee et al., 1997a, 1997b; Chen, 2000) and inventory collaboration under non-deterministic demand [Kefeng Xu and Yan Dong, 2000]. However, with economic globalization and intensification of competition, supply uncertainty increases apparently, which causes more and more important effect on supply chain performance. In previous literature, the uncertainty in the supply side has not received the amount of treatment it deserved. Up until the recent years supply uncertainty has received greater attention. In the literature, there is growing interest in models where an order that is placed may not be received due to uncertainty involved in the supply process. Parlar and Berkin (1991) propose an EOQ-type formulation where the supply is available or disrupted for random durations in the planning horizon. …