A competitive-cooperative approach to dynamic pricing for two-sided hospitality platforms

Fair pricing as an essential scope in the two-sided hospitality web platforms, refers to setting room rates that balance affordability for guests with profitability for the hotel, taking into account factors like market demand, seasonality, and competitive pricing. Unfair pricing practices can lead to customer dissatisfaction and disrupt the competitive balance within the industry. This study extends the FairPlay method, a cooperative game-theoretic approach designed to balance service provider and customer interests, by incorporating local competitor analysis at the room and hotel level. While FairPlay effectively addresses competitive dynamics, it lacks the consideration of regional and agglomeration effects, which are critical for capturing spatial market influences and competitive overlap among hotels in nearby areas. To address this gap, we introduce an enhanced method that utilizes graph node embedding techniques to model regional proximity and inter-dependencies between hotels. By leveraging these embeddings, our approach attempts to adapt to market dynamics that traditional models often miss. Our results demonstrate that embedding-based methodology outputs fairer and more competitive pricing, offering real-time adjustments that better align with local market demands and competitor behaviour. This enhancement significantly improves upon the FairPlay model by integrating regional effects, resulting in more equitable and balanced pricing for the hospitality industry.