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Abstract:
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Hotel industry is a data rich industry that captures, in real-time, huge volumes of unstructured and semi-structured text-heavy data such as property search and amenity information. However, such rich data remains under-analyzed and poorly understood due to its sheer volume. We present some statistical challenges in the analysis of such big data and in understanding consumer preferences. By analytical exploitation of reservation, cancellation, length of stay, and other price related data, we demonstrate how effective use of statistical tools can deepen our knowledge of customer behavior and discuss what new statistical techniques are required to improve forecasting and decision-making in hotel revenue management.
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