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Information sharing is a major strategy to counteract the bullwhip effect. Previous research suggested that applying different ISS(information sharing strategy) to the supply chain may improve the supply chain performance under a simplified two-level supply chain model.
In this paper, we present a simulation study that investigates the effectiveness of information sharing under different information sharing strategy scenarios within a complex multi-level supply chain model. In our research, a computer model is developed to simulate the complex multi-level supply chain model. The simulation data and results analysis show both distributors and suppliers gain significantly from information sharing no matter under different information sharing strategy except retailers and different information sharing strategy has great influence on supply chain performance.
Keywords – information sharing; information sharing strategy; bullwhip effect; multi-level supply chain model; simulation
Supply chain collaboration has a major impact on an organization’s ability to meet customer needs and reduce costs, especially under demand uncertainty. It has become a research focus.
While a key step in supply chain collaboration is to share information among the supply chain partners. And information sharing is also viewed as a major strategy to counteract the bullwhip effect [1,2,3,4]. So evaluating the effectiveness or the value of information sharing becomes hot issue[5,6].Previous research indicated the effectiveness of information sharing on supply chain. Other research suggested that applying different ISS to the supply chain under different demand patterns may improve the supply chain performance[8,9,13,14]. But the supply chain model of their research was two-level or simplified.
What’s more their research is independent and did not connect the two factors which are information sharing and information sharing strategy. Till now, very little research has been done about the effectiveness of information sharing and whether different ISS improve the supply chain performance in complex multilevel supply chain. Z.Huang and A.Gangopadhyay put forward that the inventory costs and backorder penalties are measured in evaluating the supply chain performance, but it is limited because the function is not an expression. We improve on it and put forward an approximately simplifying expression based on it, which helps us to take a computer simulation approach in investigating the impact of information sharing among trading partners on supply chain performance in different information sharing strategies in the complex multi-level supply chain model. Z. Huang and A. Gangopadhyay use a comprehensive supply chain model. In fact, their model is simplified: 1) Only two different parameters, low and high, are used to present different levels of uncertainty demand fluctuation by random number generator. 2) Their research doesn’t take into account the demand forecasting. 3) In their research different levels of inventory buffer instead of a specific inventory model are used, and they only examine three different ranges of inventory buffer levels: 100%-150%, 150%-200%, and 200%250%. In this paper, we put forward an improved multi-level supply chain model based on these unlimited.
And we compare the impact of different information sharing strategy by building a new supply chain performance function. Especially we use computer program to simulate the different parameters in random number generator which are used to present different levels of uncertainty demand fluctuation under different information sharing strategy scenarios.
Supply chain management (SCM) is a set of approaches utilized to efficiently integrate suppliers, manufacturers, warehouses, distributors and retailers, so that goods are produced, distributed and delivered at the right quantities, to the right places, and at the right time. In this part, we introduce an important problem in SCM-the bullwhip effect and the suggested solution-information sharing strategy (ISS).
The Bullwhip effect is one of the most well-known problems of SCM. It refers to the amplification of demand variability resulted from the information distortion in a supply chain where companies upstream do not have information on the actual consumer demand . The effects of the bullwhip effect are: large safety stock, large inventory costs, poor customer service level and inefficient resource use. Its five main causes include: 1) demand forecast update; 2) lead-time; Authorized licensed use limited to: University Kebangsaan Malaysia. Downloaded on July 23,2010 at 04:55:55 UTC from IEEE Xplore. Restrictions apply.
3) order batching; 4) price fluctuation; and 5) shortage gaming [1, 4]. ISS has long been suggested as a method to reduce the bullwhip effect and to help match supply with demand [1, 3, 4, 8, 9, 10, 19], especially in today’s world where IT enables the information to be shared among supply chain partners. Fisher  discussed the relationship among product nature, demand pattern and ISS. Tan and Wang  suggested that applying different ISS to the supply chain under different demand patterns may improve the supply chain performance.
But the supply chain model of their research was two-level or simplified. Commonly used ISSs include: order information, demand information, shipment information, inventory information and forecast information sharing . Each assumes different information policy and the information can flow upstream or downstream in the supply chain.
HA3: there is positive relationship between the inventory buffer level and the effect of information sharing on the supply chain performance. HA4: there is positive relationship between the demand variability, the inventory buffer level and the effect of information sharing on the supply chain performance. Furthermore, we assume the two following hypotheses involving the impact of information sharing on supply chain performance in different information sharing strategies: HB 1: information sharing strategy influences the supply chain performance significantly.
HB2: HAl, HA2, HA3 and HA4 come into existence under different information sharing strategy including OISS, DISS and SISS. III. THE DESIGN OF MULTI-LEVEL SUPPLY CHAIN MODEL Our aim to design the multi-level supply chain model is to understand the behaviors of the supply chain and to find out the impact on supply chain performance of different ISS according to end consumers’ demand uncertainty. The performance of the system under a number of different scenarios needs to be measured, which falls into the specific field of computer simulation.
In this paper, we will consider three information sharing strategies, which are order information sharing strategy (OISS), demand information strategy (DISS) and sales information sharing strategy (SISS)[ll]. l)Order information sharing strategy(OISS): each tier bases its demand forecast only on the order from the lower tier but does not know other tiers’ inventory, shipment, or delivery. Under OISS, each tiers share their forecasting order information in the planning horizon from downstream to upstream besides the real order. 2)Demand information sharing strategy (DISS): each tier is provided with the real end consumer’s demand. The inventory management system used is the echelon inventory system.
Under DISS, each tiers share to their forecasting net demand information with their higher tiers in the planning horizon besides the real order. 3)Shipment information sharing strategy(SISS): which means that each tiers share the historical information of real shipment information. Under SISS, upper tiers sharing their shipment information to their downstream customers can help them make their production /inventory decision. Hypotheses of Peiformances of IS andISSs The overall objective of this research is to study the value of information sharing by examining the combined effects of information sharing, demand variability, and inventory level on supply chain performance. Let Y be the supply chain performance, a be the degrees of information sharing, b be the demand variability, and c be the inventory buffer level .
For a traditional supply chain, each entity only interacts with its immediate upstream and downstream entities, Fig.l, and makes decision based on the information which it can attain for its own optimal goal. Our selection of the four-level information strengthened supply chain model is more generic than the two-level chain structure that is prevalent in most of the current researches. At each level, we have multiple trading partners. Each node/tier interacts with other according to the acquaintance relationship stipulated as the information and physical material flows in Fig.l. Under normal supply chain operation, each tier of the chain generates a forecast for the next period based on the demand that it faces from the previous chain tier. Using information sharing, the central warehouse of each tier has access to its customer demand data and generates its forecast according to that, bypass the information distortion caused by the stores node. We expect that information sharing can help reducing each tier’s warehouse order oscillation and mean cycle inventory.
Y = f(a,b,c) ( 1)
Then we assume the four following hypotheses involving the degree of information sharing (a): HAl: there is positive relationship between the degrees of information sharing and the supply chain performance. HA2: there is positive relationship between the demand variability and the effect of information sharing on the supply chain performance.
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