Guoming Lai

An Approximate Dynamic Programming Approach to Benchmark Practice-Based Heuristics for Natural Gas Storage Valuation

The valuation of the real option to store natural gas is a practically important problem that entails dynamic optimization of inventory trading decisions with capacity constraints in the face of uncertain natural gas price dynamics. Stochastic dynamic programming is a natural approach to this valuation problem, but it does not seem to be widely used in practice because it is at odds with the high-dimensional natural gas price evolution models that are widespread among traders. According to the practice-based literature, practitioners typically value natural gas storage heuristically. The effectiveness of the heuristics discussed in this literature is currently unknown because good upper bounds on the value of storage are not available. We develop a novel and tractable approximate dynamic programming method that, coupled with Monte Carlo simulation, computes lower and upper bounds on the value of storage, which we use to benchmark these heuristics on a set of realistic instances. We find that these heuristics are extremely fast to execute but significantly suboptimal compared to our upper bound, which appears to be fairly tight and much tighter than a simpler perfect information upper bound; computing our lower bound takes more time than using these heuristics, but our lower bound substantially outperforms them in terms of valuation. Moreover, with periodic reoptimizations embedded in Monte Carlo simulation, the practice-based heuristics become nearly optimal, with one exception, at the expense of higher computational effort. Our lower bound with reoptimization is also nearly optimal, but exhibits a higher computational requirement than these heuristics. Besides natural gas storage, our results are potentially relevant for the valuation of the real option to store other commodities, such as metals, oil, and petroleum products.

Supplier Encroachment Under Asymmetric Information

Prior literature has shown that, for a symmetric information setting, supplier encroachment into a resellers market can mitigate double marginalization and benefit both the supplier and the reseller. This paper extends the investigation of supplier encroachment to the environment where the reseller might be better informed than the supplier. We find that the launch of the suppliers direct channel can result in costly signaling behavior on the part of the reseller, in which he reduces his order quantity when the market size is small. Such a downward order distortion can amplify double marginalization. As a result, in addition to the “win--win” and “win--lose” outcomes for the supplier and the reseller, supplier encroachment can also lead to “lose--lose” and “lose--win” outcomes, particularly when the reseller has a significant efficiency advantage in the selling process and the prior probability of a large market is low. We further explore the implications of those findings for information management in supply chains. Complementing the conventional understanding, we show that with the ability to encroach, the supplier may prefer to sell to either a better informed or an uninformed reseller in different scenarios. On the other hand, as a result of a supplier developing encroachment capability, a reseller either may choose not to develop an advanced informational capability or may become more willing to find a means of credibly sharing his information. This paper was accepted by Yossi Aviv, operations management.

Valuation of Storage at a Liquefied Natural Gas Terminal

The valuation of the real option to store liquefied natural gas (LNG) at the downstream terminal of an LNG value chain is an important problem in practice. Because the exact valuation of this real option is computationally intractable, we develop a novel and tractable heuristic model for its strategic valuation that integrates models of LNG shipping, natural gas price evolution, and inventory control and sale into the wholesale natural gas market. We incorporate real and estimated data to quantify the value of this real option and its dependence on the throughput of an LNG chain, the type of price variability, the type of inventory control policy employed, and the level of stochastic variability in both the shipping model and the natural gas price model used. In addition, we develop an imperfect information dual upper bound to assess the effectiveness of our heuristic and find that our method is near optimal. Our approach also has potential relevance to value the real option to store other commodities in facilities located downstream from a commodity production or transportation stage, such as petroleum and agricultural products, chemicals, and metals, or the real option to store the input used in the production of a commodity such as electricity.

Supply Chain Performance Under Market Valuation: An Operational Approach to Restore Efficiency

Based on a supply chain framework, we study the stocking decision of a downstream buyer who receives private demand information and has the incentive to influence her capital market valuation. We first characterize a market equilibrium under a general, single buyback contract. We show that the buyers stocking decision can be distorted in equilibrium. Such a downstream stocking distortion hurts the buyer firms own performance, and it also influences the performances of the supplier and the supply chain. We further reveal scenarios where full supply chain efficiency cannot be reached under any single buyback contract. Then, focusing on contract design, we characterize conditions under which a menu of buyback contracts can prevent downstream stocking distortion and restore full efficiency in the supply chain. Our study demonstrates that in a supply chain context, a firms incentive to undertake real economic activities to influence capital market valuation can potentially be resolved through operational means. This paper was accepted by Yossi Aviv, operations management.

Salesforce Contracting Under Demand Censorship

We study salesforce contracting in an environment where excess demand results in lost sales and the demand information is censored by the inventory level. In our model, a firm contracts with a risk-neutral sales agent with limited liability whose effort increases the demand stochastically. The firm designs the incentive contract and invests in inventory; the agent decides the sales effort. We find that the sales-quota-based bonus contract is optimal in such an environment, and the quota should be set equal to the inventory level when the first-best solution is not attainable. We further reveal that demand censorship can introduce peculiar effects on the optimal sales effort and service level that the firm implements. From our analysis of the additive and multiplicative effort cases, we find that in the additive effort case, it can be optimal, under demand censorship, for the firm to induce an effort and maintain a service level both greater than those under the first-best solution. Scenarios also exist where the firm should induce zero effort. For the multiplicative effort case, the optimal sales effort under demand censorship is lower than the first-best effort, whereas the optimal service level is higher than the first-best service level. The agent earns zero rent in the additive effort case but may earn a positive rent in the multiplicative effort case. Finally, our numerical analysis shows that demand censorship can have a significant negative impact on the value of contracting with the sales agent, especially when the sales margin is low and the market uncertainty is high.

Provision of Incentives for Information Acquisition: Forecast-Based Contracts vs. Menus of Linear Contracts

In the producer–seller relationship, the seller, besides his role of selling, is often in an ideal position to gather useful market information for the producer’s operations planning. Incentive alignment is critical to motivate both information-acquisition and sales efforts. Two popular contract forms are investigated. One is the forecast-based contract (FC) that requires the seller to submit a demand forecast: the seller obtains commissions from the realized sales but is also obliged to pay a penalty for any deviation of the sales from the forecast. The other is the classical menu of linear contracts (MLC), from which the seller can choose a contract that specifies a unique commission rate and a fixed payment. The conventional understanding suggests that the MLC is superior, but it is often assumed that information is exogenously endowed. In contrast, we find that, with an endogenous information-acquisition effort, the MLC may suffer from a conflicted moral hazard effect that creates friction between motivations for the two efforts. The FC can, however, decouple these two tasks and thus dominate the MLC. We further find that when ensuring interim participation is necessary (e.g., renegotiation cannot be prevented after information acquisition), the performance of the FC might be affected by the adverse selection effect because it is unable to effectively separate different types, at which the MLC excels. We show that when the demand and supply mismatch cost is substantial, the conflicted moral hazard effect dominates the adverse selection effect, and the FC is more efficient, and it is the converse otherwise. These findings can enrich the understanding of these two contract forms and are useful for sales and operations planning. This paper was accepted by Yossi Aviv, operations management .

Merchant Commodity Storage and Term-Structure Model Error

Merchant operations involves valuing and hedging the cash flows of commodity-and energy-conversion assets as real options based on stochastic models that inevitably embed model error. In this paper we quantify how empirically calibrated model errors concerning the futures term structure affect the valuation and hedging of natural gas storage. We find that even small model errors-on the order of 1%-2% of the empirical futures price variance-can have a disproportionate impact on storage valuation and hedging. In particular, theoretically equivalent hedging strategies have very different sensitivities to model error, with one natural strategy exhibiting potentially catastrophic performance in the presence of small model errors. We propose effective approaches to mitigate the negative effect of futures term-structure model error on hedging, also taking into account futures contract illiquidity, and provide theoretical justification for some of these approaches. Beyond commodity storage, our analysis has relevance for other real and financial options that depend on futures term-structure dynamics, as well as for inventory, production, and capacity investment policies that rely on demand-forecast term structures.

A pareto optimal model for automated multi-attribute negotiations

This paper presents an applicable model for complex multi-attribute negotiations between autonomous agents. The model adopts a novel protocol which decomposes the original n-dimensional negotiation space into a series of negotiation base lines and in each period agents negotiate locally based on a given base line. A belief based negotiation strategy and an offer enhancement process are proposed for agents to make base offer on the negotiation base line and search for Pareto optimal enhancements of the base offer. The model achieves asymptotic Pareto optimality.

Trade Credit in Competition: A Horizontal Benefit

Trade credit is a widely adopted industry practice. Prior research has focused on how trade credit benefits firms by improving vertical supply chain relationships. This paper offers a novel perspective by examining whether trade credit benefits suppliers through a horizontal channel. Under the classic Bertrand competition framework, we analyze two competing firms’ price decisions with and without trade credit. We find that when the firms are financially constrained, trade credit softens horizontal price competition. Specifically, with trade credit, the firms will behave less aggressively in setting their prices for fear of incurring additional financing costs, resulting in equilibrium prices above the marginal cost, even if the products are perfect substitutes. Equilibrium profits under trade credit may thus be strictly higher than those under cash contracts. Furthermore, we find that with trade credit, a financially stronger firm may be able to exclude its weaker competitor from the market. We also inves...

Leader-Based Collective Bargaining: Cooperation Mechanism and Incentive Analysis

We study leader-based collective bargaining LCB, under which a leading buyer leader and a following buyer follower form an alliance to jointly purchase a common component from a supplier. Although the leader and the follower cooperate in their component purchase, they compete in selling their end products. We first analyze the most common and simple form of LCB, equal price LCB, under which the follower pays to the leader the same wholesale price that the leader obtains from his negotiation with the supplier. We compare each buyers profit under the equal price LCB with the benchmark where each buyer purchases separately from the supplier. We find that although the alliance might obtain a lower wholesale price and although the leader is always better off under equal price LCB, the follower can be worse off if the competition intensity of the leaders and followers products is within an intermediate region. We identify a competition effect resulting from equal price LCB that can place the follower at a disadvantage in the competition. This finding implies that the equal price LCB might not be sustainable in practice. In view of this limitation, we investigate an alternative form of LCB, fixed price LCB, under which the follower pays a fixed price to the leader regardless of the wholesale price the leader obtains from the supplier. We show that fixed price LCB benefits not only the leader but also the follower, compared with separate purchases, which implies that fixed price LCB always achieves a win-win outcome for the buyers. Our analysis further shows that even the supplier might benefit from this form of LCB.