ChatGPT与说服技术在酒店餐饮业个性化推荐管理与交付中的应用
ChatGPT and Persuasive Technologies for the Management and Delivery of Personalized Recommendations in Hotel Hospitality
AI总结：
本文探讨了将ChatGPT与说服技术集成以自动化改进酒店推荐系统，通过案例研究验证其在提升用户参与度、满意度、转化率及酒店收入方面的潜力。
摘要：
推荐系统已成为酒店餐饮业不可或缺的工具，能够为客人提供个性化和定制化的体验。大型语言模型（LLMs）的最新进展，如ChatGPT，以及说服技术，为提升这些系统的有效性开辟了新途径。本文探讨了将ChatGPT与说服技术相结合以自动化和改进酒店餐饮推荐系统的潜力。首先，我们深入研究了ChatGPT的能力，它能够理解和生成类人文本，从而实现更准确和上下文感知的推荐。我们讨论了将ChatGPT集成到推荐系统中，强调了其分析用户偏好、从在线评论中提取有价值的见解以及基于客人档案生成个性化推荐的能力。其次，我们调查了说服技术在影响用户行为和增强酒店推荐说服力方面的作用。通过结合社会证明、稀缺性和个性化等说服技术，推荐系统能够有效影响用户决策并鼓励期望的行动，例如预订特定酒店或升级房间。为研究ChatGPT与说服技术的有效性，我们通过一个涉及酒店推荐系统的案例研究进行了初步实验。我们旨在研究集成ChatGPT与说服技术对用户参与度、满意度和转化率的影响。初步结果展示了这些技术在提升整体客人体验和业务绩效方面的潜力。总体而言，本文通过探索推荐系统中LLMs与说服技术之间的协同关系，为酒店餐饮业领域做出了贡献，最终影响客人满意度和酒店收入。
英文摘要：
Recommender systems have become indispensable tools in the hotel hospitality industry, enabling personalized and tailored experiences for guests. Recent advancements in large language models (LLMs), such as ChatGPT, and persuasive technologies, have opened new avenues for enhancing the effectiveness of those systems. This paper explores the potential of integrating ChatGPT and persuasive technologies for automating and improving hotel hospitality recommender systems. First, we delve into the capabilities of ChatGPT, which can understand and generate human-like text, enabling more accurate and context-aware recommendations. We discuss the integration of ChatGPT into recommender systems, highlighting the ability to analyze user preferences, extract valuable insights from online reviews, and generate personalized recommendations based on guest profiles. Second, we investigate the role of persuasive technology in influencing user behavior and enhancing the persuasive impact of hotel recommendations. By incorporating persuasive techniques, such as social proof, scarcity and personalization, recommender systems can effectively influence user decision-making and encourage desired actions, such as booking a specific hotel or upgrading their room. To investigate the efficacy of ChatGPT and persuasive technologies, we present a pilot experi-ment with a case study involving a hotel recommender system. We aim to study the impact of integrating ChatGPT and persua-sive techniques on user engagement, satisfaction, and conversion rates. The preliminary results demonstrate the potential of these technologies in enhancing the overall guest experience and business performance. Overall, this paper contributes to the field of hotel hospitality by exploring the synergistic relationship between LLMs and persuasive technology in recommender systems, ultimately influencing guest satisfaction and hotel revenue.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
