Game Theory and Supply Chain Networks

Game Theory and Supply Chain Networks

Fei He (University at Buffalo, The State University of New York, USA) and Song He (Tyson Foods Inc., USA)
Copyright: © 2014 |Pages: 10
DOI: 10.4018/978-1-4666-5202-6.ch096
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Background

The body of literature regarding game theory and supply chain is huge, from both research and practical perspectives (Nagurney, 2006; Boone & Ganeshan, 2002; Pegels, 2005, and the references therein). The list we present is far from complete but can provide a flavor of game theoretic research in supply chains.

An ideal supply chain network model captures strategic interactions among decision makers subject to dynamic and stochastic information sharing, capacity, demand, production and policy across all tiers of the network. Early applications of game theory in supply chain include constructing game-theoretic frameworks of the buyer-supplier relationship (Christy & Grout, 1994), and minimizing the bullwhip effect (Lee, Padmanabhan, & Whang, 1997). Most recently, Stackelberg games (Yu, Huang, & Liang, 2009), Bayesian games (Chu & Lee, 2006), bargaining games (Sucky, 2006) and evolutionary games (Xiao & Yu, 2006) are developed to provide “policy insights;” such as to inform the decision maker the push and pull boundary for inventory management, and the make-to-stock or make-to-order production strategy.

Key Terms in this Chapter

Variational Inequality: An inequality involving a functional, which has to be solved for all the value of a given variable, belonging usually to a convex set.

Incomplete Information: A term used in economics and game theory to describe an economic situation or game in which knowledge about other market participants or players is not complete available.

Biform Game: A hybrid non-cooperative and cooperative game, i.e., a game has both competition and cooperation.

Network Equilibrium: In a supply chain, the transactions between decision makers coincide, the price and demand market match.

Computational Complexity: The measurement of amount of resources needed by a particular algorithm to solve a problem.

Cooperative Game: A game in which players cooperate with each other. For example, a competition between groups of players.

Nash Equilibrium: A state in which each player in the game can’t obtain a higher payoff by unilaterally deviating from his own strategy.

Incentive Compatibility: Incentive compatibility conditions force a desired constellation of choices to form a strategic equilibrium under incomplete information. Incentive compatibility conditions serve to induce a strategic equilibrium that reveals the player’s private information by having them choose difference equilibrium actions.

Non-Cooperative Game: A game in which each player acts independently. The usual case is that players have conflict interests.

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