Price Engineering for SMEs in the Hotel Industry
Master''s Thesis proving how hotel online booking and revenue management techniques harmoniously complement each other
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The advent of the Internet era changed the way business is conducted, especially in the hotel industry. The existent literature argues that the online booking revolution diminishes the effectiveness of traditional revenue management systems (Schwartz, 2008). The present paper shows that, on the contrary, online booking and revenue management perfectly complement each other. In particular, light algorithms are used to construct a pricing policy which can and should be used by managers of small size hotels. The price engineering endeavor is based on both simulated demand following a Poisson dist...
The advent of the Internet era changed the way business is conducted, especially in the hotel industry. The existent literature argues that the online booking revolution diminishes the effectiveness of traditional revenue management systems (Schwartz, 2008). The present paper shows that, on the contrary, online booking and revenue management perfectly complement each other. In particular, light algorithms are used to construct a pricing policy which can and should be used by managers of small size hotels. The price engineering endeavor is based on both simulated demand following a Poisson distribution and on the pricing policy of competing 2-star hotels in the vicinity of the Vrijthof Square, Maastricht. Regression analysis is used to determine the relation between the competitors' prices and the quantitative and qualitative independent variables chosen for this model. The light algorithm presented in this paper uses easily accessible software packages such as Microsoft Excel, simulation tools and online booking sites. The chosen approach adds a new dimension to asset management, thus enriching and improving the managerial decision process.
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