A review of simulation studies on supply chain management

ABSTRACT

In a supply chain, a company links to its suppliers upstream and to its distributors downstream in order to serve its customers. Usually, materials flow forward while information and money flow backward in the chain. The goal of supply chain management is to provide maximum customer service at the lowest possible costs. In recent years, simulation is increasingly used to study supply chains. However, at present, simulation studies on supply chains are scattered. There is an urgent need to assess the results of these studies. The purpose of this research is to provide a comprehensive listing of these simulation studies so as to summarize their findings and to identify future research areas. Results of these studies indicate 1. Simulation is a useful tool to study supply chains in various industries. 2. Demand variability amplification in a supply chain is problematic but can be dampened by operating the supply chain more coherently using information sharing and lead time reduction. 3. Other enhancement strategies can be adopted to improve supply chain performance. Practitioners can use these findings to better manage their supply chains and researchers can use them to identify future research areas which are also discussed.

1. INTRODUCTION

The supply chain concept is derived from industrial dynamics which describes the interactions and flows of a production-distribution system (Forrester, 1958, 1961). Specifically, in a supply chain, a company links to its suppliers upstream and to its distributors downstream in order to serve its customers. Usually, materials flow forward while information and money flow backward in the chain. The goal of supply chain management is to provide maximum customer service at the lowest possible costs. Forrester (1958, 1961) also advocated managing the supply chain as an integrated and coordinated system. But in the following decades, operations researchers had mostly used analytical approaches focusing on how to improve the efficiency of the individual entities in a supply chain instead of improving the performance of the entire supply chain. This myopic approach had led to local optimization at the expense of suboptimization of the supply chain. However, several recent developments highlight the need to manage a company's supply chain integratively and cohesively. These developments include the increased demand for better and faster customer service, globalization of business and competition, and availability of information technology to facilitate information exchange. The concurrence of these factors has demanded and has also enabled companies to manage their supply chains holistically to achieve strategic advantages (Arntzen, Brown, Harrison & Trafton, 1995; Lee & Billington, 1995; Camm et al., 1997)

In response to the challenge of investigating the supply chain in its entirety, instead of its individual entities, studies using simulation have become more popular in recent years (Wyland, Buxton & Fuqua, 2000). Riddalls, Bennett and Tipi (2000) conclude that global behavior of a supply chain can only be assessed by using dynamic simulation. However, at present, simulation studies on supply chains are scattered. There is an urgent need to assess the results of these studies. The purpose of this research is to provide a comprehensive listing of these simulation studies so as to summarize their findings and to identify future research areas.

This paper is organized as follows. In the next section, methodology used to locate and to group simulation studies on supply chains is described. Then, findings of studies in each group are discussed in detail. Finally, a summary of all findings is presented before future research areas are identified.

2. METHODOLOGY

The purpose of this research is to review the results of simulation studies on supply chains. To locate these studies, databases provided by ABI Inform/Proquest and EBSCO were searched using keywords "simulation," "supply chain," and "value chain." In addition, academic journals that were not included in these databases but were likely to publish simulation studies on supply chains, for example, International Journal of Production Research, were also searched. Studies identified by the search were then reviewed for relevance to the objective of this research. Due to the fact that using simulation to investigate supply chains is relatively recent, only relevant studies published after 1990 are included in this research.

Currently, there is no established framework to classify the simulation studies on supply chain management. Therefore, to facilitate discussion on the findings of studies included in this research, each study was classified into one of the following groups based on its major focus:

1. Studies on simulation methods

2. Studies on different industries

3. Studies on demand variability amplification

4. Studies on coordination and information sharing

5. Studies on enhancement strategies

Findings of simulation studies in each group are detailed in the next sections.

3. STUDIES ON SIMULATION METHODS

Different approaches have been used to simulate supply chains. Hafeez, Griffiths, Griffiths and Naim (1966) demonstrate that system engineering is an effective tool to design and analyze a two-echelon steel industry supply chain that services the construction industry. Baines and Harrison (1999) argue that system dynamics has not been fully utilized to model supply chains. Santa-Clara (1993) describes a simulator to evaluate logistic operations at strategic and tactical levels in a multi-organizational environment. To facilitate supply chain simulation, a generic, modular and reusable modeling framework has been suggested (Swaminathan, Smith & Sadeh, 1998). Recently, fuzzy models are incorporated into a simulator to analyze a serial supply chain behavior and performance in an uncertain environment (Petrovic, Roy & Petrovic, 1988, 1999; Petrovic, 2001).

4. STUDIES ON DIFFERENT INDUSTRIES

Companies in various industries have used simulation to assist in designing and improving their supply chains. Berry, Towill and Wadsley (1994) use simulation to estimate benefits to be expected from the re-engineering of a supply chain in the United Kingdom electronics industry. A similar study describes the development of simulation models that evaluate the relative dynamic implications of different supply chain redesign strategies considered by a major European manufacturer of personal computers (Berry & Naim, 1996). LeBel and Carruth (1997) use a probabilistic spreadsheet model to simulate the variability in processing wood fiber for a papermill to provide information for optimizing logging capacity utilization and wood inventory. Van der Vorst, Beulens and van Beek (2000) apply discrete-event simulation to support decision making when redesigning a supply chain for chilled food products in the Netherlands. Similarly, a simulation model is developed to analyze a multi-compartment distribution system in a catering supply chain (Jansen, van Weert, Beulens & Huirne, 2001). Levy (1995, 1997) simulates an international supply chain of a company in the personal computer industry and concludes that, when compared to its domestic counterpart, an international supply chain has longer lead times, higher inventory levels, less sales-forecasting accuracy and lower demand fulfillment.

5. STUDIES ON DEMAND VARIABILITY AMPLIFICATION

As stated, in a supply chain, a company links to its suppliers upstream and to its distributors downstream in order to serve its customers. Forrester (1961), in case studies of industrial dynamics models, observes that demand variability increases as demand travels upstream in a supply chain. This amplification of demand fluctuations from downstream to upstream is also known as the bullwhip effect (Lee, Padmanabhan & Whang, 1997). Simulation studies have been conducted to investigate causes and effects of the bullwhip effect. Bhaskaran (1998) indicates that dynamics and instability in schedules are constantly amplified from downstream to upstream in a supply chain and controlling or dampening this amplification is essential for good supply chain management. Failure to control schedule instability results in high average inventory levels. A simulation experiment conducted by van Donselaar, van den Nieuwenhof and Visschers (2000) shows that more stable planning is achieved using demand information from the end customer of the entire supply chain instead of using demand information from the immediate downstream customer. Removing one or more immediate echelons by business takeover to improve supply chain dynamics has been suggested (Wikner, Towill & Naim, 1991; Towill, Naim & Wikner, 1992). Wilding (1998) argues that chaos generation contributes to the uncertainty experienced within a supply chain. As a result, small changes made to optimize one echelon of the supply chain can result in massive changes in other parts of the chain. To reduce chaos, customer demand should be communicated as far upstream as possible. Taylor (1999) agrees that the increasingly variable upstream demand is a result of internal supply chain dynamics and, therefore, managers along the supply chain can potentially reduce demand variability amplification. Anderson, Fine and Parker (2000) state that in the machine tool industry, demand volatility amplification hurts productivity. However, companies that use smoother forecasting policies tend to impose less of their own volatility upon their supply base and may consequently enjoy system-wide cost reduction. Towill and McCullen (1999) also report success in dampening demand variability amplification and in reducing inventory by applying four material flow principles, namely, control systems principle, time compression principle, information transparency principle, and echelon elimination principle.

6. STUDIES ON COORDINATION AND INFORMATION SHARING

Forrester (1961) reports time lags in information and material flows in supply chain and advocates the need to reduce these delays to achieve a more coordinated system. Subsequently, researchers have used simulation to determine the effects of information sharing to reduce information delay and production lead time reduction to shorten material delay on supply chain performance. Studies have shown superior performance from the reduction of these lead times (Towill, 1996; Mason-Jones & Towill, 1999). Great benefit is obtained by encouraging collaboration between all players within the chain especially the free exchange of information concerning true market demand (Towill, Naim & Wikner, 1992). Specifically, Evans, Naim and Towill (1993) state that by creating integration via information sharing in a supply chain results in reduced inventory and a better investment in working capital. A simulation study by Closs, Roath, Goldsby, Eckert and Swartz (1998) supports the feasibility of achieving both improved service and lower inventory as a result of information sharing. Furthermore, Mason-Jones and Towill (1997, 1998) indicate that information sharing reduces demand variability amplification and improves capacity utilization. According to de Souza, Song and Liu (2000), reducing information delay, rather than shortening material delay, can obtain much dynamic performance improvement and increase service level. Recently, however, Zhao and Xie (2002) caution that while information sharing can bring tremendous benefits to suppliers and the entire supply chain, it hurts the retailers in most conditions. Demand pattern and forecast error distribution faced by retailers significantly influence the amount of cost savings due to information sharing.

7. STUDIES ON ENHANCEMENT STRATEGIES

The goal of supply chain management is to provide maximum customer service at lowest possible costs. To increase the likelihood of achieving this goal, researchers, in recent years, have used simulation to evaluate the effectiveness of various enhancement strategies. Lehtonen, Holmstrom and Slotte (1999) state that large excess capacity is needed to provide quick service response to customers. Helo (2000) also recommends using idle flexible capacity to hedge against market demand changes. Other enhancement strategies shown to be effective in improving supply chain performance include using product range management by separating packaging from labelling (Holmstrom, 1997), postponing product differentiation (Johnson & Anderson, 2000), initiating vendor-managed inventory partnerships with suppliers (Waller, Johnson & Davis, 1999), pooling risk through internal transshipments (Tagaras, 1999), and deploying controlled partial order shipments to improve customer service (Banerjee, Banerjee, Burton & Bistline, 2001).

8. SUMMARY OF SIMULATION STUDIES RESULTS

Results of simulation studies on supply chains reviewed in this research indicate the following:

1. Simulation is a useful tool to study supply chains. Its use is gaining popularity in industries and companies that are redesigning their supply chains to improve customer service.

2. In a supply chain, demand variability amplification, the so-called bullwhip effect, is problematic. It causes increased inventory, irregular capacity utilization, and reduced service level.

3. Operating a supply chain as an integrated coordinated system is an effective way to counter the bullwhip effect. To accomplish that, information sharing is necessary to minimize information delay and information distortion. Additionally, production lead time reduction is necessary to shorten material delay and, often times, removal of echelons in the supply chain is necessary to facilitate communication.

4. Supply chain performance can be improved by adopting enhancement strategies identified in this review. Generally, these strategies require more collaboration among the echelons in the supply chain so that the chain, as a whole, can function more effectively.

9. CONCLUSION

In recent years, simulation is increasingly used to study supply chains. This research has provided a comprehensive listing of these studies and a summary of their major findings. Practitioners can use the information to better manage their supply chains and researchers can use them to identify areas for further research which include the following:

1. This review indicates that information sharing is important to effective supply chain management. However, its importance may not be the same for all industries or companies. Studies can be conducted to determine which industries' or companies' supply chains require more information sharing to function effectively.

2. Enhancement strategies identified in this review offer fruitful research areas. These strategies have been proposed recently and tested in limited environments. Therefore, more extensive studies need to be conducted to determine their general applicability.

3. These enhancement strategies can also be combined and tested jointly. For example, risk-pooling through internal transshipments can be tested with vendor-managed inventory partnerships for synergic effect to further improve supply chain performance.

4. In addition to information and material flows, many supply chains also have money flows due to financial transactions which often trigger the physical flow. Simulation can be used to better understand the interactions of all these flows.

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Edward Chu, California State University, Dominguez Hills

Author Profile

Dr. Edward Chu earned his Ph.D. at the University of Southern California in 1985. Currently he is a professor of operations management at California State University, Dominguez Hills.

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