Many studies highlight the significance of agglomeration and spatial competition as factors influencing dynamic pricing strategies in hospitality. Our research advances the literature by examining the interaction between agglomeration benefits and competition drawback along the booking curve. To this aim, we propose a two step Structural Vector Autoregressive (SVAR) approach that accounts for time-variant factors such as daily seasonality, room quality, and rate fences. Our findings reveal a non-linear “U-shaped” pattern of negative competition effects along the booking window, with stronger impacts observed in last-minute and very early bookings. The positive externalities associated with agglomeration increased as the advance booking period shortened. Even in times of crisis, such as during COVID-19, clustering continues to exert a slightly positive effect on rates, particularly for last-minute bookings. Overall, our research contributes to the literature on hotel revenue management and underscores the importance of integrating spatial factors into dynamic pricing models to support decision-making.
Angelini, G., Costa, M., Guizzardi, A. (2025). Agglomeration and competition dynamic effects on hotels pricing strategies in Venice. INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT, 131(October), 1-12 [10.1016/j.ijhm.2025.104298].
Agglomeration and competition dynamic effects on hotels pricing strategies in Venice
Giovanni Angelini;Michele Costa;Andrea Guizzardi
2025
Abstract
Many studies highlight the significance of agglomeration and spatial competition as factors influencing dynamic pricing strategies in hospitality. Our research advances the literature by examining the interaction between agglomeration benefits and competition drawback along the booking curve. To this aim, we propose a two step Structural Vector Autoregressive (SVAR) approach that accounts for time-variant factors such as daily seasonality, room quality, and rate fences. Our findings reveal a non-linear “U-shaped” pattern of negative competition effects along the booking window, with stronger impacts observed in last-minute and very early bookings. The positive externalities associated with agglomeration increased as the advance booking period shortened. Even in times of crisis, such as during COVID-19, clustering continues to exert a slightly positive effect on rates, particularly for last-minute bookings. Overall, our research contributes to the literature on hotel revenue management and underscores the importance of integrating spatial factors into dynamic pricing models to support decision-making.| File | Dimensione | Formato | |
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