Unveiling Venice's hotels competition networks from dynamic pricing digital market

We study the dynamic price competition of hotels in Venice using publicly available data scraped from an online travel agency. This study poses two main challenges. First, the time series of prices recorded for each hotel encompasses a twofold time frame. For every single asking price for an overnight stay on a specific day, there is a corresponding time series of asking prices along the booking window on the online platforms. Second, the competition relations between different hoteliers is clearly unknown and needs to be discovered using a suitable methodology. We address these problems by proposing a novel Network Autoregressive model which is able to handle the peculiar threefold data structure of the data set with time-varying coefficients over the booking window. This approach allows us to uncover the competition network of the market players by employing a quick data-driven algorithm. Independent, mixed, and leader-follower relationships are detected, revealing the competitive dynamics of the destination, useful to managers and stakeholders.