Understanding Commodity Price Volatility Mitigationfrom Transaction Cost Economics: Preliminary

Understanding Commodity Price Volatility Mitigationfrom Transaction Cost Economics: Preliminary

Understanding Commodity Price Volatility Mitigationfrom Transaction Cost Economics: Preliminary Results

George A. Zsidisin, Virginia Commonwealth University, School of Business, 301 W. Main Street, Richmond, VA, 23284-4000, phone:804-828-1488, e-mail:

Barbara Gaudenzi, University of Verona, Department of Business Administration, Via dell’Artigliere 19, 37129 Verona, Italy, phone: +390458028623; e-mail:

Janet L. Hartley, Bowling Green State University, Supply Chain Management Institute, 3026 Business Administration,Bowling Green, OH, phone: 419-372-8645, e-mail:

Lutz Kaufmann, WHU – Otto Beisheim School of Management, Burgplatz 2, 56179 Vallendar, Germany, phone:+49 261 6509-320;e-mail:

Understanding Commodity Price Volatility Mitigation from Transaction Cost Economics: Preliminary Results

Summary

Most firms are exposed to price volatility associated with commodities, which can significantly affect the price paid for raw materials, energy and component purchases. The purpose of this paper is to examine how organizations mitigate the risk of commodity price volatility(CPV) in their organizations and supply chains. Initial findings from case studies support prior theory that as uncertainty and risk increase, organizations are more likely to create hierarchical structures to manage the effects of CPV. Likewise, whenCPV does not pose a significant risk, there appears to be a greater use of approaches to offset or pass this risk to markets or other supply chain actors.

Key Words: Price volatility, Risk assessment, Supply risk mitigation, Case studies

Submission category: Working Paper

Introduction

All organizations including those in the private sector, non-profit entities, and governmental agencies, are exposed to commodity price volatility and risk at some level. Risk exposure is either from direct raw materials and energy purchases or from risk upstream in their supply chains from commodities purchased by their suppliers. Commodities are usually categorized into energy, metals, refined petroleum products, food and non-food agricultural products.

The challenge associated with mitigatingCPV is a relatively recent phenomenon in supply chain management(Zsidisin et al., 2014). For many years the prices of most commodities were relatively stable. However, within the last 10 years, many commodities have experienced significant price fluctuations (Dobbs et al., 2013).

The purpose of thisworking paper is to build a framework of commodity price volatility and risk mitigation strategies based on an initial analysis from thirteen case studies. The paper presents insights to firms’ practices for mitigating commodity price risk that emerged utilizing a grounded theory approach.

AbbreviatedLiterature Review

Commodity price volatility (CPV) is the measure for any variation of the price of a commodity and is typically classified as a type of financial risk (ISO Guide 31.000, 2009;AIRMICet al., 2010). This form of risk is influenced by different factors related to purchases markets, demand (Sodhiet al., 2012; Jüttner, 2005),operations (Cigolini and Rossi, 2009), financial systems and government policies (Kalari and Power, 2013). However, the literature in Supply Chain Risk Management (SCRM) is nascent in describingthe relationships between commodity price risk mitigation approachesand supply chain strategies (Choi et al., 2009; Zsidisin et al. 2014).

Transaction costs represent key factors in decision-making processes about when and how to monitor and mitigate CPV and risk. Transaction costs typicallyoccur when decision makerssearch for cost information (about suppliers), take decisions (about purchases) and adopt mitigation strategies (Weveret al.,2012). Initial theoretical and empirical investigations utilizing Transaction Cost Economics (TCE) as a foundation focused on organizational structures and ownership – specifically with regard to determining if vertical integration and ownership provided greater efficiencies than market transactions (Walker and Weber, 1984; Williamson, 1979). More recent applications of TCE utilize relationships, which reduces the threat of opportunism, as a surrogate for hierarchical structures (Ellram et al., 2008; Geyskens et al., 2006; Wever et al, 2012). It is this latter view that we adopt in our study investigating which commodity price volatility mitigation strategies and approaches are appropriate from a TCE perspective. Variables germane for grounding commodity price volatility from a TCE perspective areasset specificity, uncertainty, and transaction frequency.

Commodities are not generally thought to be highly asset specific. However, many different food groups, such as corn and wheat, are considered commodities and are traded as futures contracts in the commodity exchange markets, but can also be differentiated depending on characteristics such as texture or flavor, which subsequently affect the taste of the final product(Klein et al., 1978). Another manifestation of asset specificity in terms of commodities is associated with the processing and operating practices of commodity producers. For example, steel processing plants are capital intensive and have a tendency for continual operations. Depending on the current prices and perceived balance of demand and supply, steel processing centers have the flexibility of shutting down their operations, which can either lead to a stockout for firms that purchase steel from a specific processing center, or significantly increase the total landed costs for acquiring steel from processing centers located longer distances from the focal firm. Asset specificity may also be applicable with regard to special processing or systems (as later discussed with substitution and forward buying, respectively).

The level of uncertaintyconcerns unanticipated changes in the environment or marketplaces associated with the transaction. The risk to organizations is their inability to adapt to these changes in the exchange (Gulati and Singh, 1998; Weveret al., 2012). Williamson (1991) distinguishes between responses to uncertainty that require a coordinated response by two or more entities, such as the adoption of new technologies, and issues such as price uncertainty (akin to commodity price volatility, the focus of our study), in which he argues that each of the transaction parties can autonomously adapt to these changes. However, some organizations are not well-equipped to handle or mitigate commodity price volatility, especially when those changes result in the significant increase of the commodity price.

Transaction frequency has traditionally been operationalized as the overall number of transactions, whereas more transactions constitute higher transaction costs for firms (Maltz, 1994; Williamson, 1985; Ellramet al. 2008). However, transaction frequency as a construct has received less attention in empirical studies as compared with asset specificity and uncertainty (Rindflesch and Heide, 1997; Macher and Richman, 2008). In the case of commodity price volatility mitigation, the issue of frequency from a TCE perspective may not necessarily be from how often the transaction is made (Ellram et al.,2008, p. 151). Instead, with regard to commodity price risk mitigation, the frequency of transactions dimension of TCE may be more appropriately viewed in terms of how frequently these tools need to be monitored and implemented to rectify and adjust contracts and processes to mitigate commodity price risk.

Methodology

In order to gain an in-depth understanding of firms’ practices for mitigating commodity price risk, we adopted a grounded theory approach (Glaser and Strauss, 1967; Strauss and Corbin, 1998). The unit of analysis is the buying firms’ commodity price risk management practices. Medium-sized and large companies from the U.S. and Europe that purchase a range of agricultural and industrial raw materials provide a particularly information-rich setting (Flyvbjerg, 2006) for our study.Our sample includes six medium and seven large-sized companies, five of them from the U.S. and four each from Germany and Italy. For each of these case studies we focused the discussion on only one or two key commodity purchases for both direct commodity purchases, and significant value stream commodity purchases (key commodities that suppliers purchase).

Preliminary Results

Froma TCE perspective, and particularlyconsidering the variables of asset specificityand transaction frequency (since price uncertainty is the focus of the study and is assumed in the model), the CPV and risk mitigation strategies can be categorized as indicated in Figure 1.Each of these will be discussed in depth at the conference, and are briefly reviewed below. A more complete description of each of these approaches can be found in Zsidisin et al. (2014).

Financial Hedging consists of acquiring futures, options or other derivatives to offset anticipated future commodity price increases. Firms that engage in this practice utilize financial instruments solely as a risk management approach, and not as a speculative tool. For example, a case study firm in the consumer package goods industry has a highly structured decision-making process to make hedging decisions that determines what level in the organization can make which decisions about using financial hedging. Several firms participating in this study do not utilize this technique because of the nature of their purchases or due to the lack of knowledge and experience with this hedging strategy. This approach is mainly used for high-volume purchases.

One of the primary drivers for financial hedging appears to be associated with established industry practices. For example, the four companies in the food production industry all use financial hedging to a significant extent to offset price increases for agricultural products like coffee, wheat, and corn. These commodities have a rich history of trading in financial markets and are clearly defined with regard to their specifications and market liquidity.

The firms that engage in financial hedging appear to frequently utilize this tool – for some firms even on a daily or weekly basis. Likewise, these contracts are very standardized, thereby having a very low degree of asset specificity, as shown in Figure 1.

Cross Hedging is used to offset price risk with a commodity that has similar price movements in situations in which no commodity exchange exists or the market liquidity for a commodity’s financial derivatives is low. However, the use of cross-hedging has specific legal requirements that must be met in order to implement it as a risk management tool, thereby limiting the extent to which it is deployed. Among our study participants, only two firms in the food industry are notably experienced in utilizing cross-hedging. As shown in Figure 1, the utilization of this commodity price risk approach has a higher degree of asset specificity, since it is usually more difficult to find highly correlated commodities with regard to price movements, and, at least from a U.S. perspective, requires additional legal justification and is limited in its application.

Switching Suppliers is also sometimes done to reduce commodity prices. The companies that engage in supplier switching tend to have long-term agreements in place with suppliers but flexibility within the contract to shift volumes among these suppliers. All three Italian-based companies and one US-based firm use this approach. Although they shifted volumes between suppliers, all four companies emphasized the importance of maintaining long-term relationships with a limited number of suppliers that can meet their quality and other requirements.

Staggering Contracts by using contracts for different quantities and time periods is another way to reduce the effects of commodity price volatility. For example, one of the firms in the packaging industry uses fixed price contracts are that staggered throughout the year with more contracts locked-in as the product time frame approached. Another firm in the furniture building industry also staggers its contracts from 30 days to up to almost a year depending upon price forecasts.

Both switching suppliers and staggering contracts are done on a relatively frequent basis in managing commodity price volatility, often on a monthly or quarterly basis, depending on prices. However, this approach does not require a significant degree of asset specificity, since both approaches are done interchangeably with multiple supply sources and are often easily replicated. Overall, these two approaches serve to dampen the effects of wild fluctuations over time due to the timing and quantity of the commodity purchases.

UtilizingEscalator Clauses in contractual agreements with suppliers and customers is the most common approach for managing commodity price volatility found in this study. Key decisions that must be made when developing contract clauses include how often the prices are reviewed and changed, the base cost/price, what the prices will be compared to, if past or future prices will be changed, and if there is a band in which no adjustment is used. The escalation clause might relate to commodity price variations; other variations might be based on energy/oil costs or labor costs. The definitions and weights of the different price components depend on the specific product, its characteristics and suppliers.

For organizations with many customers or suppliers, the price adjustment process can become very complex if different customers and/or suppliers have different contract clauses. For example, some of the case study firms’ customers allow monthly while other use quarterly adjustments, some use published indices and others use actual prices paid, and some use surplus/rebates on previous prices, while others change the next period price. Further, typically changes have to be made manually. Hence, as shown in Figure 1, there appears to be some variation as to how frequently this approach is exercised in sharing price volatility with customers and/or suppliers. In addition, there appears to be different levels of complexity and specificity in creating these contracts, and hence, the range shown in Figure 1.

Forward Buying involves acquiring commodities well in advance of anticipated need during times when prices are considered very favorable but anticipated to increase in the future. In addition, for the six firms studied that utilize this strategy, forward buying is almost always focused on short-term needs, and more often implemented as a method to assure supply continuity, rather than in response to anticipated price increases. The firms that engage in forward buying use it selectively, and only for very specific commodities. For example, one of the firms uses forward buying only when financial hedging or contract agreements cannot be used. Forward buying consumes working capital, increases carrying costs and has a direct effect on the balance sheet. In addition, it is largely impractical for perishable commodities. Therefore, by definition this is a hierarchical approach since the firm takes ownership, and is highly asset specific since capacities must be established to inventory larger commodity purchases. This approach is not as frequently executed due to all the additional transaction costs necessary for implementing a forward buy.

Substituting Commodities concerns the ability of the purchasing firm or supplier to use different materials in the product based upon the price movements of the commodity itself. Ideally, the different commodities should be preapproved so that they can be easily switched. However, easy switching from one commodity to another is often not technically feasible or economically viable. For example, when sourcing tires for its products, a firm in the equipment manufacturing industry allows its tire suppliers to switch the percentage mix of styrene butadiene rubber and natural rubber quantities within strict bounds, based in part on the prices of these commodities. The actual tire formulation is left up to the suppliers’ discretion as long as they stay within the agreed-upon specifications. Additional examples include one firm having flexibility in the ratios of butter and milk powder that are used in its products, and another organization creating the flexibility to switch between sugar and other types of sweeteners.

In most cases, we found that switching from one commodity to another requires engineering design and extensive testing to confirm that the product with the new material meets performance requirements. It is absolutely essential that prior approval is obtained from customers, including the final consumer, in these types of decisions — and that no detrimental technical effects result from the substitution. In addition, new equipment and tooling are often needed. For example, one of the case study firms has been encouraging its customers to switch their products to a resin that has a more stable price. However, this switch is not a painless one; for one thing, there are some technical advantages to the current resin relative to the alternative resins. If the resin is switched on an existing product, new molds are needed. Further, prior to switching, customers have to conduct tests to confirm that the packages perform to their specifications. All of these factors result in substitution being classified as having a high degree of asset specificity. Further, once the formulas or processes have been established for allowing substitution, proactive mitigation of price risk utilizing this tool is only done when prices fluctuate to the extent where switching provides financial incentives.

Directed Sourcingis an approach in which an organization enters into contracts with commodity upstream suppliers for a specific purchase volume and price. With directed sourcing, the organization’s direct suppliers are then required to purchase their commodities off of this contract (also referred to as “piggy-back contracts). There are several benefits to this approach. Volumes can be combined across suppliers so volume discounts can be obtained. In addition, the purchasing organization knows the actual price that is being paid for the commodity by its direct suppliers. However, in our study we only found two firms that were using this approach.