A Nested Logit-Based Approach to Measuring Air Shopping Screen Quality and Predicting Market Share

Understanding the relationship between itineraries displayed on an air travel website’s shopping screens and the website’s market share has never been so important nowadays. This paper presents an approach to measure ‘screen quality’, that is, the overall desirability of itineraries displayed by a website. At the centre of this approach is a nested logit model that generates a screen quality metric called ‘selection probability’ by comparing the screens of the host website to those of a reference website. This metric measures the probability an individual would select an itinerary on the host website. Recognising the fact that there are unobserved factors across websites that influence shopping behaviour, we introduce website-specific constants to capture the average of those effects, which directly translates our ‘selection probability’ to market share prediction. We present three models and conduct experiments to evaluate their performance. Results show that the model using shopping, booking and screen data simultaneously in calibration generates satisfactory prediction results