Optimal Energy Procurement in Spot and Forward Markets

Storage capacity for energy, such as electricity, natural gas, and oil, is limited. Thus, spot and forward purchases for delivery on the usage date play an important role in matching the supply and the uncertain demand of energy. Transaction costs tend to be larger in spot than forward energy, and more generally commodity, markets. Hence, partially procuring supply in the forward market, rather than entirely in the spot market, is a potentially valuable real option. We call this option the forward procurement option. The study of this option from the perspective of differential transaction costs has received little attention in the literature. We thus formulate and analyze a parsimonious procurement model with differential spot and forward transaction costs and correlated spot demand and nominal price random variables. Our analysis, in part based on natural gas data, sheds novel light on the value of the forward procurement option and its optimal exercise, as well as their sensitivities to parameters of interest. Our main insight is that procuring the demand forecast in the forward market is nearly optimal on the instances that we consider. This greatly simplifies the management of this option. We obtain analogous results with a richer model in which the supply procured in the forward market is delivered at multiple dates. Beyond energy, our research has potential relevance for the procurement of other commodities, such as metals and agricultural products.</p

Commodity Procurement with Demand Forecast and Forward Price Updates

Commodities, ranging from natural gas to memory chips, can be procured both by trading on the date in spot markets and in advance in forward markets. Transaction costs, such as brokerage fees, are typically higher in spot markets than in forward markets. Moreover, the forecast of a ¯rm's commodity requirement (demand) for a given future date typically changes in an uncertain fashion over time. Thus, although the dynamics of forward and spot prices are notoriously uncertain, firms that procure commodities face the dilemma of choosing between early and possibly less expensive commitments with residual demand uncertainty and late and possibly more expensive sourcing of the exact amount needed. We investigate this issue by developing and analyzing a model of commodity procurement for a single future date. Our model generalizes models available in the real options and operations management literature, by simultaneously considering correlated demand forecast and forward price updates in a setting characterized by multiple forward transactions and a single spot transaction. We derive the structure of the optimal procurement policy and discuss its computation in cases of practical interest. In a numerical study, based on applying our model to natural gas data, we offer managerial insights on the effects that demand forecast and forward price updates, both in isolation and combined, have on the value of a firm's procurement policy. We also assess the sensitivities of these effects to parameters of interest and the potential managerial relevance of the combined effect. Our model and results have significance beyond the specific application

Managing NPD: Cost and Schedule Performance in Design and Manufacturing

Previous work in the area of new product development (NPD) has focused mainly on the role of design in downstream value chain activities. In this field study, conducted at a leading avionics guidance systems manufacturer, we gathered primary data on time and cost performance of both the design and manufacturing phases of customized systems. We modeled the impact of the management levers relating to oversight, the intensity of specialization in design and the level of interaction with the customer. Our model recommends appropriate managerial strategies based on the relative resources required in the design and manufacturing phases. The study highlights the necessity of leveraging the interdependency between the design and manufacturing phases to achieve superior performance in both financial and time metrics

Component-based Technology Transfer: Balancing Cost Saving and Imitation Risk

Technology transfer offers global firms an opportunity to reduce the costs involved in serving emerging markets as well as to source from low-cost locations for their home markets. However, it also poses a potential risk of imitation by local competitors who may enter the market(s). We introduce a component-based technology transfer instrument for the global firm to either deter or accommodate the imitator's entry, by recognizing that components can differ in two dimensions: cost-saving potential and imitation risk. By choosing the range of components to transfer, the global firm's decision has an impact not only on the imitator's fixed entry costs, but also on the post-entry com- petition based on variable costs. Hence, the proposed instrument leads to two different types of deterrence strategies: "barrier-erecting strategy" and "market-grabbing strategy" by transferring a lower or higher amount, respectively, of component technology than in the case of no imitator. Which deterrence strategy the global firm should employ, depends on the level of imitation risk of transferring the components. Some other interesting and counter-intuitive results arise. For example, transferring less technology when the emerging market potential increases can be optimal. Considering a sourcing opportunity for a home market, a larger home market potential makes the deterrence strategy more attractive when the imitation risk is low, but less attractive when the risk is high

Ushering Buyers into Electronic Channels: An Empirical Analysis

Many firms introduce electronic channels in addition to their traditional sales channels and observe increasing buyer adoption rates immediately after the introduction but subsequent declines. Firms must understand the factors that drive channel adoption decisions and how these factors change over time and across buyers. Using panel data pertaining to the purchase histories of 683 buyers over a 43-month period, we estimate a buyer response model that incorporates buyer heterogeneity, channel inertia, and dynamic pricing. We find that channel adoption behavior is both heterogeneous and dynamic, and the firm’s allocation decisions, if not aligned with buyer behavior, can alienate buyers. Based on the parameter estimates from the buyer response model, we propose an alternative channel allocation would enable firms to attract more buyers to the e-channel and improve revenues. Channel adoption increases when firms understand and account for individual buyers’ channel adoption behavior

An Integrated Framework for the Analysis of New Technology Selection for an Application to the LNG Industry

A fundamental issue in the management of technology innovation, both in manufacturing and service industries, is the comparative evaluation of emerging and incumbent technologies. This evaluation entails the juxtaposition of multiple aspects including process configuration and operational and financial performance. In this paper we present an integrated analytic framework for technology selection that models the relation between these three critical dimensions. We apply our framework in the context of the liqueed natural gas industry, in which new o shore vessel-based regasification technology has recently been developed as an alternative to conventional onshore terminal-based regasification. We analyze the impact of process configuration and operational and financial performance on technology selection, and identify the conditions under which a specific regasification technology and its configuration is appropriate for adoption. We also investigate how the insights we derive may depend on how one models stochastic variability in the relevant processing times

Strategic Analysis of Technology and Capacity Investments in the Liquefied Natural Gas Industry

Energy plays a fundamental role in both manufacturing and services, and natural gas is rapidly becoming a key energy source worldwide. Facilitating this emergence is an expanding network of ocean-going vessels that enable the matching of natural gas supply and demand on a global scale. This is achieved through the transportation of liquefied natural gas (LNG) for eventual regasification at its destination. Until very recently, only one type of technology had been available for transporting and regasifying LNG: Conventional LNG vessels coupled with land based LNG regasification. But it is now possible to transport and regasify LNG onboard special LNG vessels. Companies such as Excelerate Energy and Hoegh LNG are currently developing LNG supply chains based on this new technology. Motivated by these developments, we engaged executives at Excelerate Energy to facilitate an investigation of issues related to strategic technology selection, as well as choices around technology configuration and capacity for the incumbent and emerging technologies. The resulting analysis brings to light managerial principles delineating the impact of alternative LNG throughput models on decisions regarding how to deploy each technology option and how to configure and size their capacity. Our findings have additional potential relevance beyond our industry specific analysis.</p

Customization: Impact on Product and Process Performance

Manufacturing capability has often been viewed to be a major obstacle in achieving higher levels of customization. Companies follow various strategies ranging from equipment selection to order management to cope with the challenges of customization. We examine how the customization process affects product performance and conformance in the context of a design-to-order manufacturer of industrial components. Our competing risk hazard function model incorporates two thresholds, which we refer to as mismatch and manufacturing thresholds. Product performance was adversely affected when the degree of customization exceeded the mismatch threshold. Likewise, product conformance eroded when the degree of customization exceeded the manufacturing threshold. Relative sizes of the two thresholds have implications for the investments by firms to improve their customization capabilities. Our research presents a rigorous framework to address two key questions relevant to the implementation of product customization: (1) what degrees of customization to offer, (2) how to customize the design process

Valuation of the Real Option to Store Liquefied Natural Gas at a Regasification Terminal

A global liquefied natural gas (LNG) market is quickly emerging, with several significant development projects very recently completed or underway; these projects consist of extraction, liquefaction, shipping, regasification, and storage facilities. Exact valuation of the real option to store LNG at the downstream terminal of an LNG value chain is computationally intractable. Thus, we develop a novel and tractable model for the heuristic valuation of this real option. This model uses a shipping model to represent upstream LNG production and shipping to the downstream regasification facility; a reduced form model of the evolution of the spot price in the wholesale natural gas market where regasified LNG is sold; a stochastic dynamic programming model to determine a policy for inventory control at the storage facility and sale into this market; and a final Monte Carlo simulation step to estimate the value of this policy. The basestock type structure that we prove for our model's LNG inventory release policy is central to make the final simulation step computationally efficient; this makes our model practical. We incorporate real and estimated data to quantify the value of the real option to store LNG at a regasification terminal, the dependence of this value on the level of stochastic variability in the shipping model and the type of natural gas price model used, and the relative value of this option for different parties involved in an LNG value chain. We also develop an upper bound, based on sample path optimization, to assess the effectiveness of our heuristic and find that our method is highly accurate. Our model has the potential to be used to value the real option to store other commodities in storage facilities located downstream of a commodity production or transportation stage, or the real option to store the input used in the production of a commodity

A Large US Retailer Selects Transportation Carriers Under Diesel Price Uncertainty

A large US retailer that procures transportation services from third-party carriers experienced an unexpected jump in fuel surcharges as the price of diesel fuel skyrocketed in the summer of 2008. As a result, it sought to limit its future exposure to diesel price risk. We collaborated with this retailer to create a lane assignment optimizer (LAO) that incorporates diesel price risk when selecting carriers for its transportation lanes. The LAO tool has significantly improved the retailer's capability to evaluate the trade-off between the two crucial components of a lane's per-shipment cost: base price and risk-adjusted fuel surcharge. The retailer can now take diesel price risk into account when selecting cost-effective carriers for its lanes, negotiating fuel surcharge limits to share diesel price risk with its carriers, and better aligning the fuel surcharges it pays with the true cost of diesel. We estimate that the more favorable contract terms the retailer negotiated for 2009–2011 translate to nearly $5 million in potential savings during years with unexpected diesel price hikes, such as 2008.</p