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Modeling Sustainable City Trips: Integrating CO2 Emissions, Popularity, and Seasonality into Tourism Recommender Systems
arXiv - CS - Information Retrieval Pub Date : 2024-03-27 , DOI: arxiv-2403.18604
Ashmi Banerjee, Tunar Mahmudov, Emil Adler, Fitri Nur Aisyah, Wolfgang Wörndl

In an era of information overload and complex decision-making processes, Recommender Systems (RS) have emerged as indispensable tools across diverse domains, particularly travel and tourism. These systems simplify trip planning by offering personalized recommendations that consider individual preferences and address broader challenges like seasonality, travel regulations, and capacity constraints. The intricacies of the tourism domain, characterized by multiple stakeholders, including consumers, item providers, platforms, and society, underscore the complexity of achieving balance among diverse interests. Although previous research has focused on fairness in Tourism Recommender Systems (TRS) from a multistakeholder perspective, limited work has focused on generating sustainable recommendations. Our paper introduces a novel approach for assigning a sustainability indicator (SF index) for city trips accessible from the users' starting point, integrating Co2e analysis, destination popularity, and seasonal demand. Our methodology involves comprehensive data gathering on transportation modes and emissions, complemented by analyses of destination popularity and seasonal demand. A user study validates our index, showcasing its practicality and efficacy in providing well-rounded and sustainable city trip recommendations. Our findings contribute significantly to the evolution of responsible tourism strategies, harmonizing the interests of tourists, local communities, and the environment while paving the way for future research in responsible and equitable tourism practices.

中文翻译:

可持续城市旅行建模:将二氧化碳排放、受欢迎程度和季节性纳入旅游推荐系统

在信息过载和复杂决策过程的时代,推荐系统(RS)已成为不同领域(尤其是旅行和旅游业)不可或缺的工具。这些系统通过提供考虑个人喜好的个性化建议来简化旅行计划,并解决季节性、旅行法规和容量限制等更广泛的挑战。旅游领域的复杂性,包括消费者、项目提供者、平台和社会等多个利益相关者的特点,凸显了在不同利益之间实现平衡的复杂性。尽管之前的研究主要从多利益相关者的角度关注旅游推荐系统(TRS)的公平性,但有限的工作集中在生成可持续的建议上。我们的论文介绍了一种新颖的方法,为从用户起点出发的城市旅行分配可持续性指标(SF 指数),整合 Co2e 分析、目的地受欢迎程度和季节性需求。我们的方法包括收集有关交通方式和排放的全面数据,并辅以对目的地受欢迎程度和季节性需求的分析。用户研究验证了我们的指数,展示了其在提供全面且可持续的城市旅行建议方面的实用性和有效性。我们的研究结果对负责任的旅游战略的发展做出了重大贡献,协调了游客、当地社区和环境的利益,同时为未来负责任和公平的旅游实践的研究铺平了道路。
更新日期:2024-03-28
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