Kun Soo Park

Transferring and sharing exchange-rate risk in a risk-averse supply chain of a multinational firm

This paper analyzes risk management contracts used to handle currency risk in a decentralized supply chain that consists of risk-averse divisions in a multinational firm. Particular contracts of interest involve transferring risk to a third party by using risk-transfer contracts such as currency options and re-arranging risk between supply chain members using risk-sharing contracts. Due to decentralization, operational and risk management decisions are made locally; however, a headquarter who is interested in total supply chain profit has some controllability over those activities. We question if each kind of risk management contract can improve the utility of all supply chain members compared to the utility without any of those, and how the conditions to achieve such improvements are different. Further structural differences are investigated via sensitivity analysis with respect to the transfer price, the variability of exchange rates, and the location of the headquarter. We also find that using the two kinds of contracts jointly does not necessarily result in better outcomes.

Offshoring and outsourcing in a global supply chain: Impact of the arm's length regulation on transfer pricing

We consider the structure of a global supply chain for operational decisions in a multinational firm (MNF) with tax considerations. The MNF consists of two divisions: one for production and the other for retailing. While the retail division of the MNF and the market for its product is located in a domestic country, the production division may be located in either the domestic (high-tax) country or a foreign (low-tax) country. When the two divisions of a MNF are co-located in the domestic country, the firm enjoys the benefit of a centralized operational decision on the order quantity to maximize its total profit although there is no tax saving opportunity. On the other hand, a MNF can enjoy a tax saving benefit when offshoring its production division to a low-tax country although its operational decision on the order quantity is decentralized, which is harmful to the supply chain profit due to double marginalization. The MNF may further pursue the low procurement cost of its retail division by allowing the retail division to search for an outsourcing opportunity from an outside supplier. However, outsourcing can hurt the profit of the MNF from the loss of the production division due to competition with outside suppliers. We analyze the trade-offs in the MNF’s optimal choice of supply chain structure. In addition, we incorporate a regulation on the MNF’s internal transaction by tax authorities, which is commonly called the arm’s length regulation. We study how the MNF’s choice of the operational structure of its supply chain changes in consideration of this regulation. Our results suggest that tax considerations deserve attention from managers when designing the supply chain structure.

A stochastic-difference-equation model for hedge-fund returns

We propose a stochastic difference equation of the form X n = A n X n−1 + B n to model the annual returns X n of a hedge fund relative to other funds in the same strategy group in year n. We fit this model to data from the TASS database over the period 2000 to 2005. We let {A n } and {B n } be independent sequences of independent and identically distributed random variables, allowing general distributions, with A n and B n independent of X n−1, where E[B n ] = 0. This model is appealing because it can involve relatively few parameters, can be analysed, and can be fitted to the limited and somewhat unreliable data reasonably well. The key model parameters are the year-to-year persistence factor γ ≡ E[A n ] and the noise variance . The model was chosen primarily to capture the observed persistence, which ranges from 0.11 to 0.49 across eleven different hedge-fund strategies, according to regression analysis. The constant-persistence normal-noise special case with A n = γ and B n (and thus X n ) normal provides a good fit for some strategies, but not for others, largely because in those other cases the observed relative-return distribution has a heavy tail. We show that the heavy-tail case can also be successfully modelled within the same general framework. The model is evaluated by comparing model predictions with observed values of (i) the relative-return distribution, (ii) the lag-1 auto-correlation and (iii) the hitting probabilities of high and low thresholds within the five-year period.

Joint decisions on product line selection, purchasing, and pricing

When creating a product line, a retailer must make several decisions simultaneously: the selection of the product types to include in the product line as well as the order quantity and price of each selected product type. This study investigates joint product line decisions by considering the dynamic substitutions of products as driven by the valuations that customers place on the products and the availability of each product type, which changes as consumers purchase a product. An integer programming model was developed for joint decisions of product selection, price, and order quantity in the product line problem to maximize the total profit of the retailer. To solve the model, we propose a hybrid genetic algorithm (HGA) that uses special genetic operators and heuristic algorithms to ensure the feasibility and efficiency of solutions. Computational experiments demonstrate the superiority of the proposed HGA over the solution obtained by CPLEX for large scale problems. Useful managerial insights on the joint product line decisions are also derived from the numerical results.

Vertically integrated producer when a rival is also a customer: impact of demand uncertainty

ABSTRACT When a vertically integrated producer (VIP) is also a supplier of a component for its rival firm, it was found that the profit in a decentralized structure is higher for the VIP than the profit in a centralized structure under deterministic demand. In contrast, we found that firms’ ordering decisions under uncertain demand can reverse this findings and it is more likely to happen as demand variability increases.