Charla de Suresh Sethi, Universidad de Texas, Dallas

12:00 horas, Beauchef 851, Sala Consejo (Torre Oriente, 4to piso).

Invitado: Suresh Sethi, director del Centro de Redes de Suministro Inteligentes de la Universidad de Texas, Dallas, Estados Unidos.

Título de la conferencia: “Hierarchical and Mixed Leadership Games for Dynamic Supply Chains: Applications to Cost Learning and Co-op Advertising”.

Abstract

We consider two applications dynamic stochastic supply chains. The first application is a decentralized two-period supply chain in which a manufacturer produces a product with benefits of cost learning, and sells it through a retailer facing a price-dependent demand. The manufacturer’s second-period production cost declines linearly in the first-period production, but with a random learning rate. The manufacturer may or may not have the inventory carryover option. We formulate the problem as a two-period Stackelberg games and obtain their feedback equilibrium solutions explicitly. We then examine the impact of mean learning rate and learning rate variability on the pricing strategies of the channel members, on the manufacturer’s production decisions, and on the retailer’s procurement decisions. We show that as the mean learning rate or the learning rate variability increases, the traditional double marginalization problem becomes more severe, leading to greater efficiency loss in the channel. We obtain revenue sharing contracts that can coordinate the dynamic supply chain. The second application studies a novel manufacturer-retailer cooperative advertising game where, in addition to the traditional setup into which the manufacturer subsidizes the retailer’s advertising effort, we also allow the reverse support from the retailer to the manufacturer. This is modeled as a mixed leadership game in which one player is a leader on some decisions and a follower on other decisions. We find an equilibrium that can be expressed by a solution of a set of algebraic equations. We then conduct an extensive numerical study to assess the impact of model parameters on the equilibrium.

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