DETERMINING HOTEL X AVERAGE ROOM RATE USING DYNAMIC PRICING METHOD WITH CONSIDERATION OF COMPETITION IN MARKET SEGMENT
Hotel X is a four-star hotel in Bandung that faced 40.7% decrease in profits from 2014 until 2017. During that period, both revenue and expenditure were also declining so it can be concluded that the decrease in profit was caused by the decrease in revenue. On the other hand, the biggest source of r...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/36732 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Hotel X is a four-star hotel in Bandung that faced 40.7% decrease in profits from 2014 until 2017. During that period, both revenue and expenditure were also declining so it can be concluded that the decrease in profit was caused by the decrease in revenue. On the other hand, the biggest source of revenue during that period came from room sales and the biggest source of room sales in 2017 came from online travel agent (OTA) segment. Considering that the front office manager as the problem stakeholder can control room price for the OTA segment, this research focuses on determining hotel X average room rate (ARR) nominal on daily basis to maximize hotel X revenue from room sales.
This research problem can be solved using revenue management (RM) concept, especially dynamic pricing (DP) that has been developed by previous researchers with some modifications to fit the problem situation of hotel X – total room over a hundred, incomplete database, and fixed online room selling method. In accordance with the necessary modifications, this research developed a new methodology using hotel profile data from Traveloka website and price-demand structure data in 2017 from hotel X database. The methodology consists of three main phases including competitor segmentation using hierarchical clustering with median linkage method; estimating the effects of ARR to market share using an adapted aggregate market share model with latent class regression; and determining optimal ARR using an adapted dynamic room pricing model by Aziz, Saleh, Rasmy & ElShishiny (2011) with nonlinear programming.
The results show that there are three competitors in the same market segment as hotel X based on ARR. In addition, the elasticity of hotel X’s ARR to its market share has a value of -0.0728 with a 95% confidence interval between -0.1293 and -0.0162. The optimal ARR nominal has the potential of increasing the revenue by 14.87%. Based on the results, hotel X’s management is recommended to integrate this research’s methodology with the hotel’s existing RM, improve the existing RM process, and use the optimal price recommended by the research model output. |
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