are less in VMI system, even the unfilled customer orders remains approximately the same for both pull and VMI systems.
2.2 Bullwhip Effect
Various researchers identified bullwhip as a dominant source-causing inefficiencies in supply chain operations. Bullwhip (BW) refers to the phenomenon that order variability increases as orders move upstream along the supply chain (figure 2.1, [44]). This phenomenon is so well known that it is sometimes referred to as, “the first law of supply chain dynamics” [45]. The importance and influence of bullwhip has been well analyzed by researchers both in theory and practice. Forrester [46]
is the pioneer in identifying the oscillations in supply chain due to ineffective coordination between internal entities. Wikner et al [47] showed the performance of three-echelon Forrester production-distribution system is far from optimal due to bullwhip effect. Demand forecasting, lead-times, batch orders, supply shortages, and price variations are identified as the major sources causing bullwhip in supply chain systems [24,48–50]. Lead time (delay in demand/order information transfer and material transportation) has been identified as the primary cause of bullwhip [51, 52]. Secondary causes include inaccurate demand forecast, batch ordering, price fluctuations, rationing and shortage gaming. Disney et al [53] identified and quantified the bullwhip in multi-echelon system. Other than these sources, human behavior can also generate bullwhip effect in supply chain networks [54].
2.2 Bullwhip Effect
Figure 2.1: The Bullwhip Effect
2.2.1 Sources of Bullwhip Effect
(1) Planning and behavioral aspects: Production planning and inventory al-location based on distorted information from succeeding downstream nodes instead of end customer demand causes bullwhip effect.
(2) Batch Order: Batch order is practiced by the supply chain entities mainly to reduce set-up costs and fixed order cost by placing orders in batches periodically to suppliers [55]. Because of this ordering technique, the suppliers receive distorted and delayed information about end customer demand.
(3) Price fluctuations: Depending on the market reasons, the companies vary the product prices to retailers and end customers either by promotional offers or temporary price reductions. This leads buyers to speculate, buying large quantities when prices are low and avoiding buying when prices are higher. This forward buying increases the variation in end customer demand and amplifies the demand variation results in bullwhip [48,49].
(4) Rationing and shortage gaming: Suppliers often ration their products by
2.2 Bullwhip Effect
prioritizing the customers or products during insufficient inventory situation. This causes delivering only a proportion of the quantity that customers order. Buyers anticipating shortages and rationing will often increase the size of their orders in excess of their actual demand to ensure that they get the amount that they really require. As soon as delivery bottlenecks are overcome, they cancel their orders for the unneeded quantity [48, 49]. This phenomenon of gaming leaves the manufacturer with a much distorted picture of consumer demand, and the bullwhip effect sets in.
(5) Role of human behavior: Simulation experiments clearly reveal two human strategies causing the bullwhip effect [54]. In supply chains, some practitioners act aggressively (safe harbour) by ordering more products than necessary and increase their safety stock. Aggressive nature not only costs high capital employed in stock at their tier but also force their suppliers to either increase their orders or to pay for out-of-stock situations. Thus aggressive strategy practiced by only one tier can have a negative impact on the whole supply chain. The second extreme of human behavior is very conservative and aims to prevent inventory built-up and can lead to out-of-stock situations. The conservative strategy depletes the inventory before the end customer’s demand increases. Initially, cautious ordering does not affect other nodes in the network badly. But as soon as end customer’s orders increase, a node following this strategy will order more than the required level causing a negative impact on the entire supply chain. Furthermore, the node following the conservative strategy is not able to deliver for some periods causing out-of-stock situations for its customers.
2.2 Bullwhip Effect
2.2.2 Consequence of Bullwhip
The bullwhip effect leads to overloaded and/or under-loaded production at the manufacturing firms and ineffective inventory allocation at the distribution nodes.
It dramatically increases the operating costs of the supply chain system and often leads to serious supply and demand mismatches and deterioration in customer service levels [45]. Supply chains facing bullwhip effect need high level of inventory to ensure sufficient service level against variation in demand. The proven fact is, by exchanging both the demand and order information would reduce the bullwhip effect (i.e demand distortion). Nevertheless, due to decentralized management, humans act as obstacles for information flow in supply chains.
2.2.3 Bullwhip Quantification and Impact
Various researchers have attempted to quantify the bullwhip and its effects on inventory allocation. Analytical expressions have been derived to quantify the bullwhip and variance in inventory position [51,56]. Linear control theory concepts were utilized to derive analytical expressions for variance of order and inventory time series by Hoberg et al [57]. They studied the stability and performance (order and inventory variances) of inventory on-hand policy and base-stock policy with and without information sharing. Their study confirmed the instability of the inventory on-hand policy for non-zero lead time system. The base-stock policy, installation-stock policy (without information sharing) and echelon-stock policy (with information sharing) were compared using performance criteria such as order amplification and inventory variances.