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Information Sharing for the Bullwhip Effect

Information sharing for the bullwhip effect: over- or underestimated? Bachelor thesis: Thesis Circle: Organization studies, 2nd semester, academic year 2011-2012 Time will tell…. A processes perspective on inter-organizational collaboration Name: ANR: E-mail: PC Jansen 770926 P. C.

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[email protected] nl Information sharing for the bullwhip effect: over- or underestimated? Abstract This literature review investigates the effect of information sharing from a buyer to a supplier in a supply chain on the performance of that supplier, with taking in mind that the supplier has to combat the bullwhip effect.

With the existence of the bullwhip effect, a supplier cannot make right forecasts and therefore has difficulties in planning its production and/or inventory control. This research shows that information sharing is the key solution to reduce or avoid the bullwhip effect and, by that, is positively influences the performance of the supplier in the chain. Keywords: Bullwhip, supply chain, information sharing, supplier performance, inventory control Thesis Circle: Time will tell…. A processes perspective on inter-organizational collaboration

Supervisor: Remco Mannak Supervisor 2: Annemieke Stoppelenburg Name: ANR: E-mail: PC Jansen 770926 P. C. [email protected] nl 2 Table of contents Table of contents 1. Introduction 2. Theoretical Framework 2. 1 Performance of a supplier 2. 2 Information sharing 2. 3 Bullwhip effect 3. Methodology 3. 1 Data collection 3. 2 Quality Indicators 4. Results 4. 1 Information sharing is the key solution 4. 2 Information sharing is not the key solution 5. Conclusion and recommendations 5. 1 Conclusion 5. 2 Recommendations for future research 6.

Discussion and reflection 6. 1 Discussion 6. 2 Reflection 7. References 3 4 7 7 7 9 11 11 12 13 13 21 24 24 26 28 28 29 30 3 1. Introduction Collaboration is something which has occurred over all times and is a way for people as well as for organizations to accomplish any goal or wanted result. Min and Zhou (2002) stated that in today’s global marketplace, individual firms no longer compete as independent entities with unique brand names, but rather as integral part of supply chain links.

According to Christopher (1992), a supply chain is the network of organizations that are involved, through upstream and downstream linkages, in the different processes and activities that produce value in the form of products and services delivered to the ultimate consumer. When looking at the downstream linkages, a supplier delivers his products or services to a buyer. The buyer has a recursive demand, and orders this demand to the supplier every period. The supplier, on his turn, has to deal with production scheduling and/or inventory control every period.

However, dealing with those issues can be quite difficult for the supplier, when the demand of the buyer is variable and hard to predict. This problem, or phenomenon, is called the Bullwhip effect. Yu et al. (2001) described this phenomenon as that the variability of an upstream member’s demand is greater than that of the downstream member, and that the effect therefore largely is caused by the variability of ordering. The supplier’s uncertainty about the upcoming buyer’s demand can lead to inefficient productions and inefficient inventory control, which on their turn will lead to increases of costs or decreased in revenues.

According to Chen (2003), information sharing is often suggested to combat the undesirable bullwhip effect. The importance of combating the bullwhip effect was elucidated by Yu et al. (2001), who stated that uncertainties will propagate through the supply chain in the form of amplification of ordering variability, which leads to excess in safety stock, increased logistics costs and inefficient use of resources (Yu et al, 2001). So, in order to reduce the chances for these negative consequences of uncertainties for the supplier, information sharing seems the key solution.

According to Mohr and Spekman (1994), information sharing refers to the extent to which critical and proprietary information is communicated to one’s supply chain partner. Yu et al. 4 (2001) stated that while every single member has perfect information about itself, uncertainties arise due to lack of perfect information about other members. This seems logical, since a supplier can’t make the right decisions for his production schedule and his inventory control when he doesn’t know what the demand of the buyer will be. As Yu et al. 2001) stated, the supplier in the supply chain needs to make a forecast of its downstream site’s product demand for its own production planning, inventory control and material requirement planning. But, this forecast seems hard to make when uncertainties, by the lack of information, exist. However, there are some authors who don’t agree with this. Raghunathan (2001) for example stated that suppliers can do much better in the case without information sharing, because the supplier can use its information about the retailer’s order history to greatly sharpen its demand forecast.

This leads to a remarkable point, because on first sight it seems that the uncertainties, due to the bullwhip effect, can be solved by information sharing between the supplier and the buyer, but some authors have different thoughts on this point. This literature review will asses both views on the importance of information sharing in the supply chain to get a clear overview of its importance for the bullwhip effect and, by that, on the supplier’s performance. This leads to the following research goal and question:

Research Question: What is the effect, according to the literature, of information sharing in a supply chain on the performance of the supplier? Conceptual model The following conceptual model will illustrate the goal of this research: Level of information sharing + Performance of the supplier Research goal: The aim of this literature review is to understand the effect of the level of information sharing in a supply chain on the performance of the supplier, where performance can be measured in terms of reductions in total costs and inventories.

This paper investigates whether the performance of the supplier is positively influenced by the level of information sharing or not. 5 The unit of analysis: The unit of analysis in this research is on the level of the supplier. It could be expected that the level of information sharing has a positive effect on combating the bullwhip effect, and by that, on the supplier’s performance in the chain, since information can make the uncertainty about the buyer’s demand disappear. Yu et al. 2001) stated that while every single member has perfect information about itself, uncertainties arise due to lack of perfect information about other members. According to this theory, information sharing seems the key solution for reducing or eliminating the bullwhip effect. Scientific relevance: The scientific relevance of this literature review lies within the contribution it brings to the field of research of the importance of downstream information for the supplier within a supply chain, in order to reduce or avoid the bullwhip effect. It gives insight in the importance of information sharing.

Since many authors claim that information sharing is the key solution to reduce or avoid the bullwhip effect, but some on the other hand do not agree with this, this paper tries to give insight in what is true for this case. Practical relevance: The practical relevance of this literature review is that in our world a lot of companies are active in supply chains, and therefore, by this literature review, a supplier working in a supply chain is able to get insight in the importance of information sharing for their performance in that supply chain. 6 2. Theoretical framework 2. Performance of a supplier For the purpose of this research, only the supplier’s performance is being overviewed, and the buyer’s performance is disregarded. The reason for this is that the supplier and the buyer have different interests in the supply chain. The buyer only tries to get the best, in other words, lowest price, but the supplier on his turn also seeks to achieve good selling prices, reductions in total costs and inventories, and by that, increase his revenues. Because of these different targets, it is too complex to focus on both sides’ performance in this research.

According to Slack et al. (2004), performance should always be measured against benchmarks, which could be historical standards, target performance standards, competitor performance standards, or absolute performance standards. In addition to that, Clifford (2000) stated that performance often is measured using quantitative measurements, in terms of the gains or benefits a company achieves in comparison to the costs invested. For this research, the benchmark ‘absolute performance standards’ of Slack et al. 2004) will be used, since this benchmark takes performance on theoretical limits. This is what will be done in this paper as well. The performance of a supplier will be measured using theoretical quantitative measurements, in other words, at stated by Yu et al. (2001), by the extent to which a supplier achieves its specific objectives and benefits in terms of reductions in total costs and inventories. Since this is a literature review, no exact numbers will be used, but, as stated here above, theoretical quantitative measurements will be used. 2. Information sharing As stated before, the performance of the supplier is influenced by the level of information sharing. The reason for sharing information in the supply chain was stated by Yu et al. (2001), who stated that a supply chain partnership is a relationship formed between two independent members in supply channels through increased levels of information sharing to achieve specific objectives and benefits in terms of reductions in total costs and inventories. Various authors described the concept of information sharing in supply chains.

According to Mohr and Spekman (1994), information sharing refers to the extent to which critical and proprietary information is communicated to one’s supply chain partner. Lalonde (1998) reviewed five building blocks that characterize a solid supply chain relationship and considered sharing of 7 information as one of them. The other four are sharing of benefits and burdens, multiple contacts between economic entities, cross-functional management processes, and futureoriented collaborative processes (Lalonde (1998)). According to Yu et al. 2001), while every single member has perfect information about itself, uncertainties arise due to lack of perfect information about other members. In their paper they argued that the supply chain member should obtain more information about other members in order to reduce uncertainties. Li and Lin (2006) stated that in a highly uncertain environment with changing markets, organizations tend to build strategic partnership with their supply chain members to share information, increase organizational flexibility, and reduce the risk associated with the uncertainty.

One of these risks could be the presence of the bullwhip effect. In their paper, Li and Lin (2006) concluded that generally, organizations with high levels of information sharing and information quality are associated with low level of environmental uncertainty. Furthermore, Li and Lin (2006) argued that, by taking the data available and sharing it with other parties within the supply chain, an organization can speed up the information flow in the supply chain, improve the efficiency and effectiveness of the supply chain, and respond to customer changing needs quicker. More precisely, according to Lehoux et al. 2010), if actors have access to the demand of the final consumer, the number of products kept in stock at each location, the quantity ordered in the past few years, etc. , and are ready to cooperate, they can make planning decision that will have a positive impact on the system. Sahin and Robinson (2002) stated that information sharing can occur at several levels. Under ‘no information sharing’, the only demand data the supplier receives are actual orders from his immediate customer. On the other hand, at the ‘full information sharing’ level, complete information is available to support the specific decision-making environment.

According to Sahin and Robinson (2002), this complete information include one or more of the following: production status and costs, transportation availability and quantity discounts, inventory costs, inventory levels, various capacities, demand data from all channel members, and all planned promotional strategies. Lin et al. (2002) argued that the higher level of information sharing is associated with the lower total cost, the higher order fulfillment rate and the shorter order 8 cycle time. Seidmann and Sundarajan (1997) summed up a number of possible different information sharing arrangements.

They showed four categories, based on the level of impact the shared information has on the buyer and supplier. The categories are as followed: exchanging order information, sharing operational information, sharing strategic marketing information, and sharing strategic and competitive marketing and sales information. In a supply chain, two different streams of information can occur: downstream and upstream. According to Claro and Claro (2010), downstream information refers to the information obtained from a supplier’s marketing channels, be they wholesalers, distributors or retailers.

The wholesalers, distributors, or retailers can all be seen as a buyer in the context of this research, since they all place orders at an upstream member (a supplier). From this it can be derived that upstream information refers to the information a buyer obtains from the supplier. For the purpose of this research, the focus will be on downstream information; the information a supplier receives from the buyer. This information is critical for the supplier’s performance because with this information the buyer will have to make its forecast for production and/or inventory control.

The upstream information will be disregarded, since, as stated before, this research only focuses on the supplier, and therefore the buyer’s performance will be disregarded. 2. 3 Bullwhip effect Forrester (1958) was the first one to describe the bullwhip effect and identified the supply chain’s natural tendency to amplify, delay, and oscillate demand information, and demonstrates its effect in a serial supply chain consisting of a retailer, distributor, warehouse, and factory. So, this phenomenon is known as the bullwhip effect.

According to Metters (1997), it is so called because a small variance or seasonality in actual consumer demand can ‘crack the whip’ for upstream suppliers, causing upstream suppliers to alternately produce at capacity then experience downtime. Yu et al. (2001) described this phenomenon as that the variability of an upstream member’s demand is greater than that of the downstream member. Basically, they say, the bullwhip effect is largely caused by the variability of ordering. Lee et al. (1997) identified the five major causes of the bullwhip effect as (1) the use of ‘demand signal processing’, (2) nonzero 9 ead times, (3) order batching, (4) supply shortages, and (5) price fluctuations. According to Sucky (2008), the bullwhip effect has a number of negative effects in real supply chains, which can cause significant inefficiencies. Huang et al. (2007) stated that the devastating consequences caused by the bullwhip effect are clear indeed, like a redundant inventory, excessive production and resultant costs, ineffective transportation and laggardly logistics, inefficient operations, and low economic benefits of supply chain system.

Sucky (2008) agreed with this and stated that the bullwhip effect typically leads to excessive inventory investments throughout the supply chain as the parties involved need to protect themselves against demand variations. So, for the supplier, this means that the uncertainty about demand can lead to more costs, derived from those excessive inventory investments, since suppliers have to forecast their production and/or inventory control, without knowing for sure if this forecast is correct. According to Lee et al. 1997), to reduce uncertainties, and by that the costly bullwhip effect, suppliers and buyers should share demand forecast information as well as information on inventory levels, sales data, order status, and production schedules. The bullwhip effect was illustrated by Sterman (1989) by the ‘beer game’. This game is a role-playing simulation of an industrial production and distribution system. The game is designed in a way that each participant has a lack of information and they cannot communicate with each other. Therefore, according to Lee et al. 1997), each player has to make his decisions relying on orders from the neighboring player as the sole source of communications. The results of this test confirmed the existence of the bullwhip effect, because they revealed that the variances of orders amplify as one moves up in the supply chain (Lee et al. , 1997). 10 3. Methodology The design of this research was an integrative literature review. No empirical data has been gathered, only existing scientific literature was used in order to do this research. Therefore, this research was pure theoretical.

The level of information sharing was used as the independent variable and the supplier’s performance, which is based on the bullwhip effect, was used as the dependent variable. 3. 1 Data collection Since this research is a literature review, only scientific academic literature was used. Therefore, the reliability of this research was guaranteed. The literature was found by using ISI (Web of Sciences) and Google Scholar. Web of Sciences was used as primary database, and Google Scholar was used when Web of Sciences could not provide the articles it showed in the search results.

If this was the case, mostly the articles were indeed found by Google Scholar. When searching literature on Web of Sciences, the citation database was only using the Social Sciences Citation Index (SSCI). Literature was partly searched and selected by some applicable search terms in ‘Web of Sciences’. Table 1 shows the most important search terms which were used. Those terms were used solely as well as in a combination together in order to find relevant articles. The search results were sorted by the times the articles were cited, in order to find the most important paper for my topic.

The only problem which came up when using this strategy was that the newest articles, which could be important for this research, were very low in those search results, since they haven’t been cited that much yet. Therefore, after finishing this first sorting strategy, a second sorting was done as well, based on newest to oldest, to see if the last couple of years important papers regarding my topic have been written. The other part of data collection was done by looking at articles which were cited by the papers I viewed as important for my research.

Search terms Supply chain Information sharing Supplier Supplier’s performance Table 1. Search terms 11 Bullwhip effect Downstream information Inventory control Demand process 3. 2 Quality indicators The reliability of this research was guaranteed, since only scientific academic literature was be used. All the literature that was used in this paper is high quality literature, because the used literature is published in well-known journals, and is peer-reviewed.

The confirmability is high for this research. The results will be able to be confirmed by others, since all statements, definitions and assumptions in this research were derived from previous literature. In this literature review, there has been consistent and correct referring to the authors. Next to that, the validity was also ensured, since more than just one database was used, so that all the relevant literature for this research was assured. The construct validity is enhanced as well.

What had to be measured has actually been measured, since the concepts of this research were clearly defined and the used articles for doing this research were all using the same definitions and concepts. 12 4. Results Two different views on the importance of information sharing in order to reduce or avoid the bullwhip effect can be distinguished in the literature: a positive effect on one side, and on the other hand there are authors who do not agree that information sharing is the key solution to reduce or avoid the bullwhip effect. . 1 ‘Information sharing is the key solution’ The importance of information sharing for combating the bullwhip effect was clearly shown by the simulation study of Chatfield et al. (2004), who used a simulation model to examine the effects in supply chains of stochastic lead times and of information sharing and quality of that information in a periodic order-up-to level inventory system. One of their main findings was that information sharing reduces total variance amplification and stage (node to node) variance amplification.

This, is what is needed to reduce or avoid the bullwhip effect. Chatfield et al. (2004) therefore indeed conclude that information sharing decelerates the bullwhip effect as we go up the supply chain, which could be the result of planning ahead, since the upper supply chain echelons would be responding to customer demand information before the demands actually show up in the form of an order from the downstream partner. The findings of Moyaux et al. (2007), also by a simulation study, are in line with this.

They concluded that, with information centralization (buyer’s demand information available), the supplier knows in real time and instantaneously the market consumption. By this, the supplier will be able to manage his production schedule and inventory control in the best way. Sterman’s (1989) results from his ‘beer game’-experiment are in line with this, since they showed that the bullwhip effect appears when actors in a chain haven’t got all the information they need to make the right decisions about production and inventory control.

Sterman (1989) stated that misconceptions about inventory and demand information (Lee et al. , 1997) causes the bullwhip effect. So, Sterman (1989) also states that the effect of information sharing on the supplier’s performance is positive since it helps to reduce or avoid the bullwhip effect. Croson and Donohue (2005) do not doubt about whether or not information sharing is the key solution; they see particularly sharing information on inventory levels as countermeasure to the bullwhip effect. According to them, from an operational perspective, inventory 13 nformation can be used to update demand forecasts and lessen the impact of demandsignaling errors and delays. In their paper, they stated that ‘analytical research on inventory management in two-echelon supply chains with a single supplier and one or more retailers (e. g. , Bourland et al. 1996; Lee et al. 1997; Cachon and Fisher 2000; Gavirneni et al. 1999) concludes that sharing inventory information can improve supply chain performance, with the upstream member (i. e. , the supplier) enjoying most of the benefits’ (Croson and Donohue (2005)).

According to Croson and Donohue (2005), in these analytical models, inventory information provides the supplier with more timely and less distorted demand signals, and these signals are then factored into the supplier’s order decisions, and these factors result in lower safety stock and/or higher service levels in comparison with cases where no inventory information is shared. Lee et al. (1997) totally agreed with those findings. In their paper, as stated earlier, they analyzed four sources of the bullwhip effect (demand signal processing, rationing game, order batching, and price variations).

With their demand model, they considered a retailer’s singleitem multiperiod inventory problem, where the retailer (buyer) orders a single item from a supplier every period. In this setting, the supplier relies totally on the order data from the buyer. According to Lee et al. (1997), their result shows that such an arrangement will cause the supplier to lose track of the true demand pattern at the retail end, and, besides that, the supplier’s inventory control based on this distorted information will inevitably suffer. Lee et al. 1997) concluded, based on these findings, that when sales and inventory data are shared among chain members, the supply chain as a whole can implement echelon-based inventory control which can yield superior performance to installation-based inventory control. Moreover, Huang et al. (2007), based on three simulation experiments according to the empirical practice of the three most representative Chinese companies in the steel industry, found that the bullwhip effect existed in this supply chain, and that the effect can be reduced by a control method they developed.

Based on classical control theories and methods, combined with the empirical practices, Huang et al. (2007) concluded that the best way for firms to dampen and control the bullwhip effect is to take effective measures for information sharing, especially in this information society. More specifically, Huang et al. (2007) stated that managers should choose an appropriate method of controlling the bullwhip effect, which 14 as to be the usage of some advanced information management system and management solutions, for example Advanced Planning System (APS), Enterprise Resource Planning (ERP), E-business, Vendor Managed Inventory (VMI), short-term inventory, and distribution optimization, is an effective way to control the bullwhip effect. Since those management systems are advanced information management systems, they are all based on shared information in the supply chain. The conclusions of Huang et al. (2007) therefore indicated the importance of information sharing to reduce or avoid the bullwhip effect.

Ozer and Wei (2004) also showed how important the effect of information sharing can be for the supplier. According to Ozer and Wei (2004), both the cost and the base stock level decrease as customers place more of their demand in advance. Advance demand information, according to Ozer and Wei (2004), refers to the situation when customers place orders in advance for a future delivery. If this is the case, the supplier knows what the order will be for the upcoming period, and therefore, the uncertainty seems low or even eliminated.

As a consequence of that, it is clear that the cost and base stock level decrease. However, Ozer and Wei (2004) even go further on this important role of information. Based on a numerical study, where they studied 350 problem instances, they stated that advance demand information can be a substitute for capacity and inventory. In other words, when a supplier receives full demand information from the buyer’s side, the supplier doesn’t even have to hold any stock, and by that, the supplier’s performance is influenced positively, since the supplier doesn’t have the risk of extra costs and inventories.

One other way to show the value of information sharing in a supply chain was brought up by Cannella and Ciancimino (2011). Cannella and Ciancimino (2011) performed a supply chain stress test via a sudden and intense change in demand, and they distinguished different supply chain configurations: traditional and information exchange. In the traditional supply chain, each level in the supply chain issues production orders and replenishes stock without considering the situation at either up- or downstream tiers of the supply chain (Cannella and Ciancimino (2011)).

On the other hand, in the information exchange supply chain, the retailer and supplier order independently, yet exchange demand information and action plans in order to align their forecasts for capacity and long-term planning (Cannella and Ciancimino (2011)). Their main conclusion regarding the difference in these configurations is that the 15 bullwhip effect, inventory instability and intermittent orders are not completely eliminated, but are reduced with respect to the traditional supply chain, and that information exchange supply chains generally outperform the traditional configuration.

This means that, ceteris paribus, all performance measures are superior to the traditional case (Cannella and Ciancimino (2011)). This conclusion is an important one for the research question of this paper, since it makes clear that the supplier’s performance is really dependent on whether information is shared or not. One other remarkable thing in their conclusion is that the bullwhip effect is not totally eliminated when information is shared in the supply chain. Dejonckheere et al. 2004) concluded this as well in their paper, when they showed that for the class of order-up-to policies, information sharing helps to reduce the bullwhip effect significantly, especially at higher levels in the chain, however, the bullwhip problem is not completely eliminated and it still increases as one moves up the chain. A new question one can come up with here is if it is possible to totally eliminate the bullwhip effect by information sharing. An answer to this new question is given by Chen et al. (2000).

In their research, they provided a model based on the assumption that demand information is centralized, and all stages use the same inventory policy and forecasting technique. Centralized demand information means that customer demand information is available to every stage of the supply chain (Chen et al. , 2000). The findings of Chen et al. (2000) showed that providing each stage of the supply chain with complete access to customer demand information can significantly reduce bullwhip effect. However, according to Chen et al. 2000), the results also demonstrated that even when (i) all demand information is centralized, (ii) every stage of the supply chain uses the same forecasting technique, and (iii) every stage uses the same inventory policy, there will still be an small increase in variability at every stage of the supply chain. Reason for this, given by Chen et al. (2000), is that the supplier can never know the mean and the variance of buyer’s demand. This means that the bullwhip effect can never totally be eliminated from the supply chain, even if full information sharing is done by the buyer.

Croson and Donohue (2006), who conducted the beer game-experiment of Sterman (1989), also concluded that the bullwhip cannot totally be eliminated. Croson and Donohue (2006) conducted the game under business students at the University of Minnesota and found that the bullwhip effect still exists when retail demand is stationary (not fluctuating) and commonly known. Reason for this was 16 given by Sterman (1989) itself, who noted that dynamic settings render decision making difficult, even when only one decision maker is involved, due to reduced saliency of feedback.

For the purpose of this study this means that a supplier is missing the feedback or forewarning of when the buyer is running short on inventory. Therefore, uncertainty still exist since the forecast is hard to make, and the bullwhip effect will not be eliminated. However, Yu et al. (2001) stated that this is possible. Based on their case study of L&TT, a Hong Kong based multinational company which had to deal with a large number of new manufacturers and component suppliers in their industry, Yu et al. (2001) concluded that with access to the customer rdering information, the supplier can eliminate the amplified buyer’s demand variance in its replenishment process. Besides that, Yu et al. (2001), according to their quantitative analysis, stated that the supply chain partnership can not only help the members of a decentralized supply chain to eliminate the bullwhip effect, but also improve the overall performance of the supply chain. So, based on the findings of Yu et al. (2001), the overall performance of the supply chain can be improved. This means that the supplier and buyer should make information sharing arrangements, since it can be advantageous for them both.

Seidmann and Sundarajan (1997) summed up possible different information sharing arrangements, showing the impact of information sharing on the operations, sales, marketing, and production strategies of the parties that contract to share the information. The four arrangements they summed up are exchanging order information, sharing operations information, sharing strategic marketing information, and an agreement where the information adds both strategic and competitive value to the party that receives it. The sharing strategic marketing information agreement seems the optimal agreement for the research question in this paper.

According to Seidmann and Sundarajan (1997), arrangements like these occur when one organization owns information that it can derive little independent value from, but which another can use to generate operational benefits for the company it receives the information from, besides garnering strategic value for its own sales and marketing departments. This level can be very beneficial for the supplier. As Seidmann and Sundarajan (1997) stated, the information in this level can be used by the supplier’s sales and product development groups for improved demand forecasting, promotion scheduling, and segment-specific forecasts and therefore, in 17 hat situation, it is possible for a buyer to allow a supplier to access broad market information that provides the supplier with strategic and competitive benefits. A new point of discussion can come up here, because, according to Lee et al. (1997), sales data and inventory status data are proprietary for buyers, and they are not obligated to share this data with others, in this case, the supplier. Lee et al. (1997) in their paper do not state that sharing information can be advantageous for the buyer as well as the supplier as Yu et al. (2001) do, but they take in mind why the buyer would exchange information to the supplier.

According to Li (2002), in line with this, buyers would not voluntarily share their information. He identified conditions under which the manufacturer would be able to buy retailer information. Claro and Claro (2010) concluded as well that sharing information can be good for both sides in the supply chain. They found their results by doing a survey research under 174 suppliers and 67 buyers, with which they tested their hypothesis, which was: ‘the more downstream information a supplier obtains, the higher the degree of collaboration in a buyer-supplier relationship’ (Claro and Claro, 2010).

The results supported the hypothesis. Claro and Claro (2010) showed that when downstream information is shared, so, from buyer to supplier, the degree of collaboration, in terms of joint planning, joint problem solving and flexibility in the supply chain is very high. These findings show that sharing the proprietary information can bring advantages for the buyer as well. An interesting point in the studies who showed that information sharing is the key solution for reducing or avoiding the bullwhip effect was brought up by Croson and Donohue (2006).

As stated before, they conducted the beer game under business students, but for the purpose of the study of this interesting finding the participants also had access to dynamic inventory information. According to Croson and Donohue (2006), the results suggest that members near the beginning of the chain exhibit a different impact from inventory information than those near the end. This means that having access to dynamic information will lead to a greater reduction of the bullwhip effect for suppliers like a manufacturer and a distributor, than for suppliers who are closer to the end consumer, like a distributor.

So, from their findings, information sharing is very important for reducing or avoiding the bullwhip effect, but much more important for suppliers who are at the beginning of the chain than for suppliers who are closer to the end buyer. 18 ‘Information sharing is the key solution’ Chatfield et al. (2004) simulation model to examine different effects in a supply chain ? periodic order-up-to level inventory system Moyaux et al. (2007) ? simulation study ? Findings: Information sharing reduces total variance amplification and stage (node to node) variance amplification.

Sterman (1989) ? Beer-game experiment ? This experiment is used and conducted a lot in the literature Croson and Donohue (2005) ? Analytical research on inventory management in two-echelon supply chains with a single supplier and one or more retailers Lee et al. (1997) ? Analyzed four sources of the bullwhip effect ? With their demand model, they considered a retailer’s single-item multiperiod inventory problem Huang et al. (2007) ? Three simulation experiments in the Chinese steel industry ?

Based on classical control theories and methods, combined with the empirical practices Ozer and Wei (2004) ? Numerical study with 350 instances Findings: With information centralization, the supplier knows in real time and instantaneously the market consumption Findings: The bullwhip effect appears when actors in a chain haven’t got all the information they need to make the right decisions about production and inventory control Findings: Sharing inventory information can improve supply chain performance, with the upstream member (i. e. the supplier) enjoying most of the benefits Findings: When sales and inventory data are shared among chain members, the supply chain as a whole can implement echelon-based inventory control which can yield superior performance Findings: The best way for firms to dampen and control the bullwhip effect is to take effective measures for information sharing, especially in this information society. Managers should choose an appropriate method of controlling the bullwhip effect Findings: Both the cost and the base stock level decrease as customers place more of their emand in advance. Advance demand information can be a substitute for capacity and inventory Findings: The bullwhip effect, inventory instability and intermittent orders are not completely eliminated, but are reduced with respect to the traditional supply chain, and that information exchange Cannella and Ciancimino (2011) ? Supply chain stress test via a sudden and intense change in demand 19 supply chains generally outperform the traditional configuration. Dejonckheere et al. (2004) ? The class of order-up-to policies Findings: ?

Information sharing helps to reduce the bullwhip effect significantly, especially at higher levels in the chain ? Hhowever, the bullwhip problem is not completely eliminated and it still increases as one moves up the chain Chen et al. (2000) Findings: ? A model based on the assumption that ? Providing each stage of the supply chain demand information is centralized, with complete access to customer demand and all stages use the same inventory information can significantly reduce policy and forecasting technique bullwhip effect ?

The supplier can never know the mean and the variance of buyer’s demand, so the bullwhip effect is never completely eliminated Yu et al. (2001) Findings: ? Case study of L ? With access to the customer ordering ? Quantitative analysis information, the supplier can eliminate the amplified buyer’s demand variance in its replenishment process ? The supply chain partnership can not only help the members of a decentralized supply chain to eliminate the bullwhip effect, but also improve the overall performance of the supply chain Claro and Claro (2010) Findings: ?

Survey research under 174 suppliers ? When downstream information is shared, and 67 buyers so, from buyer to supplier, the degree of collaboration, in terms of joint planning, joint problem solving and flexibility in the supply chain is very high. Croson and Donohue (2006) Findings: ? Sterman’s (1989) beer-game under ? Members near the beginning of the chain business students exhibit a different impact from inventory information than those near the end ? Having access to dynamic information ill lead to a greater reduction of the bullwhip effect for suppliers at the beginning of the chain, than for suppliers who are closer to the end consumer 20 4. 2 ‘Information sharing is not the key solution’ Eventhough a lot of authors, as shown here above, state that information sharing is the key solution for reducing or avoiding the bullwhip effect and by that improving the supplier’s performance, there are also authors who do not agree with this. For example Raghunathan (2001), based on analysis of the earlier study of Lee et al. (2000) and through simulation. Lee et al. 2000), studied the value of sharing demand information in a supply chain model with a nonstationary demand process. Their key findings are that the suppliers costs can be reduced as a result of information sharing. Raghunathan does not agree with this. According to Raghunathan (2001), a supplier can reduce the variance of its forecast further by using the entire order history to which it has access. Thus, Raghunathan (2001) stated, when intelligent use of already available internal information (order history) suffices, there is no need to invest in interorganizational systems for information sharing.

Next to Raghunathan are Cachon and Fisher (2000), who studied the value of sharing data in a model with one supplier, N identical retailers, and stationary stochastic consumer demand. They concluded that, for the setting they studied, implementing information technology to accelerate and smooth the physical flow of goods through a supply chain is significantly more valuable than using information technology to expand the flow of information. The reason they give is that when a retailer is flush with inventory, its demand information provides little value to the supplier because the retailer has no short-term need for an additional batch.

According to Cachon and Fisher (2000), a retailer’s demand information is most valuable when the retailer’s inventory approaches a level that should trigger the supplier to order additional inventory, but this is also precisely when the retailer is likely to submit an order. Graves (1999) goes beyond this and gives an even lower value to information sharing in a specific, namely, zero. Graves (1999) developed a model assuming assume that each site in the system orders at preset times according to an order-up-to policy, that delivery times are deterministic, and that the demand processes are stochastic with independent increments.

Graves (1999) concludes that information sharing provides no benefits to the supply chain, when there is no outside inventory source and an order-up-to-policy. 21 Gavirneni et al. (1999) furthermore studied different patterns of information flow between a retailer and a supplier. With their study they found that information sharing is does not always have a big value, in other words, is not always the key solution for reducing or avoiding the bullwhip effect.

The objective in their paper is to determine a production strategy to minimize the supplier’s costs, under various scenarios that differ in terms of the supplier’s information about the downstream part of the supply chain. Their key observations, according to Chen (2003), are: (1) when the retailer demand variance is high, or the value of (s, S) is either very high or very low, information tends to have low values, and (2) if the retailer demand variance is moderate, and the value of (s, S) is not extreme, information can be very beneficial.

A (s, S)-policy, according to Yu et al. (2001) means that an order will be placed to replenish the stock level to S at each time period if the stock level is less than the recorder point s. So, according to Gavirneni et al. (1999), in some situations information sharing is overestimated and is definitely not the key solution for reducing or avoiding the bullwhip effect. Dejonckheere et al. (2003) found some other solution for reducing the bullwhip effect and neither did say that information sharing is the key solution.

Based on a methodology by control systems engineering, which includes transfer functions, frequency response curves and spectral analysis, they introduced a general decision rule that avoids variance amplification (bullwhip effect) and succeeds in generating smooth ordering patterns, even when demand has to be forecasted. Firstly, Dejonckheere et al. (2003) concluded that whatever forecasting method is used, order-up-to policies will always result in a bullwhip effect. Therefore, they tried to find a solution to reduce or avoid this effect. According to Dejonckheere et al. 2003), the crucial difference with the class of order-up-to policies is that in their proposed rule, net stock and on order inventory discrepancies are only fractionally taken into account. Their general decision rule has to expected benefits: (1) it is expected to detect and eject rogue variations in demand (high frequencies) so that excess costs due to unnecessary ramping up and down production or ordering levels are avoided, and (2) it is possible to quantify the amount of variability reduction by means of the same procedure (Dejonckheere et al. (2003)). 22 ‘Information sharing is not the key solution’ Raghunathan (2001) Findings: ?

Analysis of the earlier study of Lee et ? A supplier can reduce the variance of al. (2000) and through simulation its forecast further by using the entire order history to which it has access Cachon and Fisher (2000) Findings: ? Based on a model with one supplier, ? Implementing information technology N identical retailers, and stationary to accelerate and smooth the physical stochastic consumer demand flow of goods through a supply chain is significantly more valuable than using information technology to expand the flow of information Graves (1999) Findings: ?

Based on a model assuming that each ? Information sharing provides no site in the system orders at preset benefits to the supply chain, when times according to an order-up-to there is no outside inventory source policy, that delivery times are and an order-up-to-policy. deterministic, and that the demand processes are stochastic with independent increments Gavirneni et al. (1999) Findings: ? Studied different patterns of ?

When the retailer demand variance is information flow between a retailer high, or the value of (s, S) is either and a supplier. very high or very low, information tends to have low values Dejonckheere et al. (2003) Findings: ? Based on control systems engineering ? Introduced a general decision rule ? Whatever forecasting method is used, order-up-to policies will always result in a bullwhip effect ? Their general decision rule: (1) is expected to detect and eject rogue variations in emand (high frequencies), and (2) it is possible to quantify the amount of variability reduction by means of the same procedure 23 5. Conclusion and recommendations 5. 1 Conclusion The answer to the research question as stated in the beginning of this paper is provided in this section. The research question where this research is based on was: ‘What is the effect, according to the literature, of information sharing in a supply chain on the performance of the supplier? To answer the research question, and to see if information sharing for the bullwhip effect is over- or underestimated, the literature around the topic of the bullwhip effect had to be assorted, and it showed that in two main streams exist in the literature when focusing on the role of information sharing for the bullwhip effect. In the literature, with exceptions (Raghunathan 2001: Cachon and Fisher 2000: Graves 1999: Gavirneni et al. 1999: Dejonckheere et al. 2003), information sharing as the key solution to reduce or avoid the bullwhip effect seems to have the upper hand.

First, shortly the most important findings from the first view will be summarized, which was the view of information sharing as key solution to reduce or avoid the bullwhip effect in order to increase the performance of a supplier. Chatfield et al. (2004) and Moyaux et al. (2007) showed by simulation studies that with information sharing in the supply chain, the supplier is much more well-known about what is going happen, in other words, what the market does and what the buyer’s demand will be, and therefore, according to their findings, the bullwhip effect is reduced.

Also results of some empirical studies showed that information sharing is the key solution. Huang et al. (2007) concluded that managers should stick to advanced information management systems for their company because this will reduce the bullwhip effect. Ozer and Wei (2004), with their numerical study, found that advance demand information will results in decreases of costs and inventory level, and therefore has a positive effect on the supplier’s performance. Yu et al. 2001), with their case study of L, concluded that when a supplier has access to the buyer’s ordering information, the supplier can eliminate the amplified buyer’s demand variance in its replenishment process. Claro and Claro (2010), by their survey research, even showed that not only the supplier can benefit from sharing information but the buyer can do as well, because when downstream information is shared, the degree of collaboration, in terms of joint planning, joint problem solving and flexibility in the supply chain is very high. 24

The main findings of the other view, the view which finds that information sharing is not the key solution, were as followed. Raghunathan (2001) stated that information sharing is not necessarily needed, because a supplier can reduce the variance of its forecast further by using the entire order history to which it has access. Furthermore, Cachon and Fisher (2000) concluded that accelerating and smoothing the physical flow of goods through a supply chain is significantly more valuable than using information technology to expand the flow of information.

Graves (1999) found that, in a specific market model, information sharing provides no benefits to the supply chain, when there is no outside inventory source and an order-up-to-policy. Dejonckheere et al. (2003) had a remarkable result. They introduced a general decision rule, which should detect the bullwhip effect and quantify the amount of the bullwhip effect, so that suppliers can respond to this in time. The arguments for information sharing as key solution seem stronger than the ones who say information sharing is not that important.

The argument of Raghunathan (2001) for example, that a supplier can reduce the variance of its forecast further by using the entire order history to which it has access, seems not very strong. The findings of Raghunathan in fact were rejected by Croson and Donohue (2006) who conducted the beer game of Sterman (1989) under business students and found that the bullwhip effect still exists when retail demand is stationary (not fluctuating) and commonly known.

This means that, even if a supplier has the order history, the demand is known, and the demand is not really fluctuating, a supplier cannot make the right forecast since the bullwhip effect isn’t totally eliminated. The argument of Raghunathan (2001) can call up more discussion. Results from the past do not guarantee anything for the future, and especially these days with the economic crises, you never know what the market with do and how the financial situation of your customers will be.

Therefore, making forecasts based on history seems not a strong argument. Other arguments saying that information sharing is overestimated all focus on specific situations, but it seems that overall information sharing is not overestimated at all in the literature. Much more authors, based on different (simulations) models and empirical studies, claim that information sharing is the key solution to reduce or avoid the bullwhip effect than authors who do not claim that, and this seems logical. Without enough information, a supplier 25 annot make right judgments about his production schemes and inventory control, since he doesn’t know what the next period will bring for him in terms of the buyer’s demand. The results of this uncertainty for the supplier can be either a low inventory and the chance of not being able to fulfill the buyer’s demand because of that inventory, or the chance of having an inventory which is too large and being stuck with too many unsold products after the buyer’s demand. To avoid this effect, the supplier should have access to the necessary information from the buyer.

However, as also stated by Li (2002), why would a buyer share this information, when it is not in any way beneficial for him? The information sharing arrangements of Seidmann and Sundarajan (1997) can bring the solution. Their third level, sharing strategic marketing information, is the one which suits the best in this case. The supplier and buyer should make this arrangement, so that the buyer shares the needed downstream information to the supplier. This information shared has strategic value to the supplier.

The buyer, on his turn, could, in return for the information, ensure himself for example of better purchase prices. In this way, both parties can gain from the agreement. Claro and Claro (2010) came up with more descriptions of how the performance of the buyer could positively be influenced as well next to the performance of the supplier, by stating that joint planning, joint problem solving and flexibility in the supply chain are all possible consequences of a situation where information is being shared from buyer to supplier. 5. Recommendations for future research For further research it will be very interesting to investigate to what extent the performance of the buyer and supplier can be negatively influenced as well by information sharing within the supply chain. In the literature, as I have seen, a lot is written about the importance of information sharing, and the overall conclusion is that information sharing is the key solution to reduce or avoid the bullwhip effect, and, by that, positively influences the performance of the supplier and also the whole chain’s performance.

However, there hasn’t been done much research about possible negative consequences of information sharing within the chain and therefore this seems a gap in the existing literature. For example, what could happen when information is fully shared between suppliers and buyers, is that the suppliers get totally dependent on those information by controlling their production and/or inventory, and when the information for any reason suddenly is distorted, misinterpreted or wrong, a problem can occur. 26 6. Discussion and reflection 6. Discussion As it is clear from the results section and conclusion, two views on the importance of information sharing for the supplier’s performance exist in the literature. The conclusion shows that it can be stated that information sharing is the key solution to reduce or avoid the bullwhip effect, and, by that, has a positive influence on the performance of the supplier. The practical implication of this research lies within the insight it gives to actors in a supply chain. The insight is especially meant for suppliers, since this research focused on the supplier and not specifically on the buyer.

The bullwhip effect seems a very common problem in supply chains and therefore it seems to be a topic which suppliers will often will encounter. This research gives insight in how the bullwhip effect can be reduced or avoided. As concluded, the first solution on sight seems easy. Suppliers should try to make the buyer share the needed downstream information, so that the supplier can make right forecasts, and wellover thought production and/or inventory control. However, one cannot ignore for example the general decision rule of Dejonckheere et al. (2003).

They believe that their model can detect and quantify the bullwhip effect in time, so this might be a solution as well for reducing or avoiding the effect. However, no sequel study on their paper has been done and so, there hasn’t been any further prove of this model. The setting of this paper gives reason for discussion. In this paper, the focus has only been on the performance of a supplier and did not specifically focus on the buyer’s performance. This research even ignored more or less the buyer’s performance. Therefore, discussion can come up, since the supply chain has two sides: a buyer and a supplier.

As said, this research only looked through the eyes of the supplier, in other words, how the supplier could reduce or avoid the bullwhip effect, by that make better forecasts and decisions about production and/or inventory control, and so improve his performance. The overall conclusion is that information sharing is the key solution. However, this is only in the interest for the supplier, while the other important player in this story, namely, the buyer, hasn’t been spotlighted in this story. In this paper it is assumed and concluded that a buyers should share his information, but the 7 paper did not really put a good focus on the buyer’s performance, and what the possible consequences of information sharing for the buyer could be. Another point of discussion lies within the literature used for this research. The problem is that a lot of authors use models in their paper to conduct, analyze and conclude about whether or not information sharing is important for the bullwhip effect, but those models differ from each other. Some authors use stationary market models, some use non-stationary, some use order-up-to policy models, some use order-point-quantity policies.

In other words, authors use specific supply chain settings to make their conclusions, and therefore, this research includes a very broad scope on the topic, which means that conclusions made in this research are not applicable in every supply chain, since the supply chain settings can differ. 6. 2 Reflection When looking back on writing this literature review, findings literature was not the problem. Many articles have written about the topic ‘supply chain’ in relation to ‘bullwhip effect’, but this didn’t mean that it was easy to find the right literature.

Because of the large quantity papers, a very specific search method was needed in order to find the really important papers to be able to answer the research question of this paper. One difficult point in doing this research was that many of the most important papers included very detailed and extensive statistical models, which sometimes made it very difficult to understand the papers in the right way and derive right conclusions from it. Besides that, it was important to focus only on the supplier’s performance and leave the buyer’s performance outside the focus of this paper.

The reason of that is that the supplier and buyer, as written before, both have their own values and interests, and therefore, if the paper would focus on both of these actors, more than one dimension will exist and the research will get too extensive. When the research goal and question were clear, soon it became clear as well that two views on the importance of information sharing for the bullwhip effect existed. However, I was hoping to find much more results on the second view, namely that information sharing is not the key solution. This was a disappointing thing in the research. 28 7.

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