# ChatGPT and Persuasive Technologies for the Management and Delivery of Personalized Recommendations in Hotel Hospitality

**Authors:** Manolis Remountakis, Konstantinos Kotis, Babis Kourtzis, George E. Tsekouras  
**arXiv:** [2307.14298](https://arxiv.org/abs/2307.14298)  
**Date:** 2023-07-26  
**Summary page:** https://www.summarizepaper.com/en/paper/2307.14298v1/

## Key points

- Recommender systems are essential in the hotel hospitality industry for providing personalized experiences to guests.
- Integration of ChatGPT into recommender systems allows for more precise and context-aware recommendations by analyzing user preferences and extracting insights from online reviews.
- Persuasive technologies, such as social proof and personalization, can enhance the persuasive impact of hotel recommendations and influence user behavior towards desired actions like booking a specific hotel or upgrading their room.
- A pilot experiment involving ChatGPT and persuasive techniques in a hotel recommender system showed promising outcomes in enhancing guest experiences, satisfaction levels, and business performance within the hospitality sector.

## Summary

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Recommender systems have become essential tools in the hotel hospitality industry, providing guests with personalized and tailored experiences. Recent advancements in large language models (LLMs), such as ChatGPT, and persuasive technologies have paved the way for enhancing the effectiveness of these systems. This paper delves into the potential of integrating ChatGPT and persuasive technologies to automate and enhance hotel hospitality recommender systems. Firstly, the capabilities of ChatGPT are explored, showcasing its ability to comprehend and generate human-like text for more precise and context-aware recommendations. By integrating ChatGPT into recommender systems, user preferences can be analyzed, valuable insights from online reviews can be extracted, and personalized recommendations based on guest profiles can be generated. Secondly, the role of persuasive technology in influencing user behavior is investigated to amplify the persuasive impact of hotel recommendations. Through incorporating techniques like social proof, scarcity, and personalization, recommender systems can effectively guide user decision-making processes towards desired actions such as booking a specific hotel or upgrading their room. To assess the efficacy of ChatGPT and persuasive technologies in this context, a pilot experiment involving a case study with a hotel recommender system is presented. The aim is to evaluate how integrating ChatGPT and persuasive techniques impacts user engagement, satisfaction levels, and conversion rates. Preliminary results indicate promising outcomes in enhancing overall guest experiences and improving business performance within the hospitality sector. In conclusion, this paper contributes significantly to the field of hotel hospitality by exploring the synergistic relationship between LLMs like ChatGPT and persuasive technology within recommender systems. Ultimately, these advancements aim to positively influence guest satisfaction levels while also boosting hotel revenue through more effective recommendation strategies.