Enhancing hotel profitability: Dynamic pricing with a Sim-Learnheuristic approach
In recent decades, online travel agencies have emerged as the leading channel for hotel bookings, promoting dynamic pricing and real-time data analysis to stay competitive. Accordingly, we propose a dynamic pricing system based on a sim-learnheuristic model, which combines heuristic and machine lear...
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| Veröffentlicht in: | International journal of hospitality management Jg. 133; S. 104472 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Elsevier Ltd
01.02.2026
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| Schlagworte: | |
| ISSN: | 0278-4319 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | In recent decades, online travel agencies have emerged as the leading channel for hotel bookings, promoting dynamic pricing and real-time data analysis to stay competitive. Accordingly, we propose a dynamic pricing system based on a sim-learnheuristic model, which combines heuristic and machine learning to provide the most appropriate daily room prices. Additionally, deterministic and sim-heuristic models were implemented to benchmark our proposal. The models were tested using simulations based on real data. The results indicate that the sim-learnheuristic learns from past data and react to future outcomes, thus supporting effective hotel price management under dynamic conditions.
•Hotel profit maximization under dynamic market conditions.•Dynamic pricing approach combining heuristics and machine learning: a sim-learnheuristic model.•Hotel pricing system capable of handling dynamic market conditions in near real-time.•Adaptive hotel demand simulator based on real hotel data. |
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| ISSN: | 0278-4319 |
| DOI: | 10.1016/j.ijhm.2025.104472 |