Infoscience

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Location choice with longitudinal WiFi data

While moving from diary survey to location-aware technologies, recent data collection techniques provide new insights about location choices. Only few dynamic models of location choice exist in the literature, and none of them to our knowledge correct for serial correlation. In this paper, we apply a method proposed by Wooldridge (2005) to deal with the initial values problem on the choice of catering locations on a campus using WiFi traces. Cross-validation, price elasticity and simulation of a scenario predicting the opening of a new catering location are presented. Predicted market shares of the new catering location correspond to point-of-sale data of the first week of opening.

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