Abstract
Selecting a good site plays a crucial role in the success of a hotel, and as competition intensifies in the lodging industry, it has become increasingly important. The success of a site is based on competitive, demographic, physical, market awareness, and demand generator variables. We built a regression model for La Quinta Motor Inns, a mid-sized hotel chain headquartered in San Antonio, Texas, that predicted profitability for sites under consideration. We validated the regression model on new data and incorporated it into a spreadsheet decision model that management uses for selecting sites. The model minimizes the risk of picking an unprofitable site.
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