ANALYZING HOTEL DATA-DRIVEN SYSTEM BY USING DATA SCIENCE TECHNIQUES
DOI:
https://doi.org/10.54613/ku.v11i11.971Keywords:
Data science, data analysis, Hotel, reservation, cancellation, application, hotelAbstract
In the past few years, both the City Hotel and Resort Hotel have experienced significant increases in their cancellation rates. As a result, both hotels are currently facing a range of challenges, such as reduced revenue and underutilized hotel rooms. Therefore, the top priority for both hotels is to reduce their cancellation rates, which will enhance their efficiency in generating revenue. This report focuses on the analysis of hotel booking cancellations and other factors that do not directly impact their business and annual revenue generation.
Foydalanilgan adabiyotlar:
Meliboev, A., Alikhanov, J., & Kim, W. (2022). Performance evaluation of deep learning based network intrusion detection system across multiple balanced and imbalanced datasets. Electronics, 11(4), 515.
Azizjon, M., Jumabek, A., & Kim, W. (2020, February). 1D CNN based network intrusion detection with normalization on imbalanced data. In 2020 international conference on artificial intelligence in information and communication (ICAIIC) (pp. 218-224). IEEE.
Hayotjon o‘g‘li, T. X., & Ikromjon o‘g‘li, M. A. (2023). BIG DATE TIZIMI HAQIDA UMUMIY TASNIF VA TUSHUNCHA. QO ‘QON UNIVERSITETI XABARNOMASI, 1281-1284.
Talluri, K.T., & van Ryzin, G.J. (2004). The Theory and Practice of Revenue Management. Springer Science+Business Media.
Bodea, T., & Ferguson, M. (2014). Segmentation, Revenue Management and Pricing Analytics. Routledge.
Dolnicar, S., & Otter, T. (2003). Which hotel attributes matter? A review of previous and a framework for future research. In CAUTHE 2003: Riding the Wave of Tourism and Hospitality Research.
Xia, L., Wang, T., & Zhang, M. (2014). Examining the influence of recommendation agents on online consumer choice: A personalization-privacy paradox. Decision Support Systems, 57, 93-103.
Ham, S., Kim, W.G., & Jeong, S. (2005). Effect of information technology on performance in upscale hotels. International Journal of Hospitality Management, 24(2), 281-294.
Sigala, M. (2015). The application and impact of gamification funware on trip planning and experiences: The case of TripAdvisor’s funware. Electronic Markets, 25(3), 189-209.
Chen, H., Chiang, R.H.L., & Storey, V.C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165-1188.
Moreno, A., García-Alonso, L., & Fernández-Castro, I. (2016). Applying predictive analytics in the hospitality industry: A case study of a multinational hotel chain. Journal of Hospitality and Tourism Technology, 7(4), 364-375.
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