INVESTIGATING PRICE DISCRIMINATIONS IN DELIVERY FEES ON A FOOD DELIVERY PLATFORM

Abstract

With the rapid advancements in technology, digital platforms are integrating into our everyday lives more seamlessly than one would ever imagine, especially with the presence of enticing promotion and refreshing content. Tremendous amount of data from one’s online activities can be stored, shared or used by the digital platforms, and this can help to refine the platforms’ price discrimination mechanism. With the authorities watching closely, many digital platforms are gradually adopting dynamic algorithmic price discriminations, where consumers are priced dynamically based on a set of characteristics. Using two empirical approaches – randomised controlled experiments and a novel user survey study – this paper elucidates empirically the presence and explicit structure of an algorithmic liked discriminatory pricing mechanism on a specific online food delivery platform. The paper found statistically significant price discriminatory effects of an extensive set of user-related, order-related and digital search/usage data-related characteristics on the delivery fees faced by users.