| Author: | Liao, Peng |
| Title: | Revenue management : bundling, competing in size and channel |
| Advisors: | Ye, Heng-qing (LMS) Jiang, Li (LMS) |
| Degree: | Ph.D. |
| Year: | 2016 |
| Subject: | Revenue management. Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Logistics and Maritime Studies |
| Pages: | viii, 178 pages : color illustrations |
| Language: | English |
| Abstract: | The thesis consists of four projects under the umbrella of revenue maximization with limited capacity. The topics are motivated from real practices of revenue management and competition in the airline industry, hotel industry, and property market, etc. The first two projects are motivated by the increasing popularity of the travel package and emerging impact of the new third-party channel on the hotel's traditional dynamic pricing. They consider a monopolistic framework in which the supplier owns limited inventory of perishable resource, and dynamically controls the selling process in a finite planning horizon. The first project considers a revenue-maximizing supplier who holds two resources and sells a line of products made up of individual components and a package comprising these two resources. In every period, three streams of consumers arrive: one stream for each component and one for the package. We adopt both quantity-based and price-based controls to maximize the expected revenue. The results show that the optimal solutions behave monotonically with respect to time and inventory level. Finally, we numerically compare the performances between quantity-based and price-based controls. The second project studies a dynamic dual-channel pricing problem. In the travel industry, suppliers usually use both their own direct channel and Online Travel Agency (OTA) channel to distribute services. In particular, we consider the OTA-supplier contract's rate stipulation which prohibits the price of the direct channel be lower than that of OTA channel. We formulate a dynamic pricing model, where a monopolistic supplier with limited capacity faces consumer arrivals from direct and OTA channels in every period. We show that the rate stipulation leads the direct channel's consumers to unilateral switch to the OTA channel. We also obtain the structural properties of optimal prices and the supplier's optimal channel policy with respect to time and inventory level. The last two projects are motivated respectively by the firms' products-size design problems such as the TV stations' advertisement duration decision in the prime time, and the use of Commission Override Model to mitigate the capacity competition between the Online Travel Agency and the hotels. They consider the revenue maximization with limited inventory in a competitive framework. The third project studies whether capacitated suppliers should introduce a small-size product or large-size product in a competitive environment. We study a model where symmetric duopoly capacitated suppliers can either choose to sell the small or large product. We demonstrate that the equilibrium product strategy depends on the decision sequence between the suppliers, and the relative capacity compared to the extent of increasing marginal utility experienced by the consumer when consuming an additional unit of the inventory. The fourth project considers a commonly used allocation scheme in the hotel industry: Commission Override Model (COM), which uses both wholesale contract and consignment contract to sell hotel rooms, allowing the hotel to more flexibly allocate rooms among channels. We study two firms, a hotel that has a direct channel and an OTA that owns the OTA channel. We formulate a two-period stochastic model and obtain the game equilibrium. Our results show that COM is able to benefit the two firms more than the traditional wholesale or consignment contract in a more uncertain scenario. |
| Rights: | All rights reserved |
| Access: | open access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b29499100.pdf | For All Users | 2.54 MB | Adobe PDF | View/Open |
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