This dissertation analyzes the economic incentives involved in three distinct supply chain and revenue management decision environments. The first study examines the adoption of the percent deviation contract in a supply chain to induce the buyer to share some of the demand risk in an environment in which the buyer would typically place her order when she has full knowledge of the customer demand levels. The subgame-perfect Nash Equilibrium decisions are characterized, and the percent deviation is shown to achieve full supply chain channel coordination in cases where a simpler contract cannot. Pareto-improving examples based on
industry demand data are presented and discussed. The second section considers a revenue management problem for sports and entertainment organizations. Given that the organization starts the selling season by offering ticket packages exclusively, the optimal time during the selling season for the organization to begin selling individual-event tickets is derived. Extensions of the base model are developed to include multiple ticket packages and heterogeneous ticket packages. The model is illustrated using empirical data sets obtained from the Georgia Tech Athletic Department and the Atlanta Symphony Orchestra. The third section develops a model of vendor-controlled category management in which vendors are in charge of the stocking and assortment decisions for a given amount of shelf space at a vendor when the retailer retains control over the retail price. The subgame-perfect Nash Equilibrium strategies for two vendors and a single retailer are analyzed, and a revenue-sharing contract is shown to coordinate the channel when the vendors can produce multiple brands in a given product category and shelf space is sufficiently large or small.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/13965 |
| Date | 24 August 2006 |
| Creators | Drake, Matthew J. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 1311276 bytes, application/pdf |
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