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Activity Number: 301
Type: Topic Contributed
Date/Time: Tuesday, August 2, 2016 : 8:30 AM to 10:20 AM
Sponsor: Business and Economic Statistics Section
Abstract #321154 View Presentation
Title: Statistical Challenges in Big Data Analysis of the Hotel Industry
Author(s): Kai-Sheng Song *
Companies: University of North Texas
Keywords: big data in hotel industry ; reservation and cancellation ; length of stay ; forecasting

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.

Authors who are presenting talks have a * after their name.

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