1.79-Approximation Algorithms for Continuous Review Single-Sourcing Lost-Sales and Dual-Sourcing Inventory Models

Stochastic inventory systems with lead times are often challenging to optimize, including single-sourcing lost-sales and dual-sourcing systems. Recent numerical results suggest that capped policies demonstrate superior performance over existing heuristics. However, the superior performance lacks a theoretical foundation. In “1.79-Approximation Algorithms for Continuous Review Single-Sourcing Lost-Sales and Dual-Sourcing Inventory Models,” the author provides a theoretical foundation for this phenomenon in two classical inventory models. First, in a continuous review lost-sales model with lead times and Poisson demand, he proves that a capped base-stock policy has a worst-case performance guarantee of 1.79 by conducting an asymptotic analysis under a large penalty cost and lead time. Second, in a more complex continuous review dual-sourcing model with general lead times and Poisson demand, he proves that a similar capped dual-index policy has a worst-case performance guarantee of 1.79 under large lead time and ordering cost differences. The results provide a deeper understanding of the superior numerical performance of capped policies and present a new approach to proving worst-case performance guarantees of simple policies in hard inventory problems.

On Co-opetitive Supply Partnerships with End-Product Rivals: Information Asymmetry, Dual Sourcing and Supply Market Efficiency

Problem definition: We consider opportunities for cooperation at the supply level between two firms that are rivals in the end-product market. One of our firms is vertically integrated (VI), has in-house production capabilities, and may also supply its rival. The other is a downstream outsourcing (DO) firm that has better market information. The DO is willing to consider a supply partnership with the VI, but it also has the option to use the outside supply market. Academic/practical relevance: Such co-opetitive practices are common in industrial supply chains, but firms’ co-opetitive strategic sourcing with the potential of information leakage has not been examined in the literature. Methodology: We build a game-theoretic model to capture the firms’ strategic interactions under the co-opetitive supply partnership with the potential information leakage. Results: The DO exploits its information advantage to obtain a better wholesale price from the VI and may use dual sourcing to protect its private information. Anticipating that, the VI may offer wholesale price concessions as an information rent to obtain the DO’s information. Our work identifies demand uncertainty and efficiency of outside supply market as the factors affecting the VI’s pricing decision and the resulting equilibrium. Pooling equilibrium arises often, but in a few cases, the equilibrium is separating. At the separating equilibrium, the DO always single sources, either from the VI or the independent supplier depending on the demand state. The VI benefits from ancillary revenue-generating opportunity, and from information acquisition in a separating equilibrium. On the other hand, the DO’s benefit is a cheaper price in exchange for market information in a separating equilibrium. In the pooling case, the DO uses dual sourcing to hide demand information, especially in the high demand case, and to better supply the end-market through his accurate demand information. Managerial implications: Our work provides useful insights into firms’ strategic sourcing behaviors to efficiently deal with the potential of information leakage in the co-opetitive supply environment and for the rationale behind such relationships often observed in industries.