nep-tur New Economics Papers
on Tourism Economics
Issue of 2024‒10‒14
two papers chosen by
Laura Vici, Università di Bologna
  1. Measuring Resilience of the Tourism Sector: Entropy as a Surrogate Indicator of Resilience (EASIOR) Approach By Lee, Seonjin; Pennington-Gray, Lori
  2. The Role of Artificial Intelligence in Improving Hotels Property Management Systems By Nasser Bouchareb
  1. By: Lee, Seonjin; Pennington-Gray, Lori
    Abstract: Resilience has emerged as a critical focus in tourism studies, but the literature on tourism resilience is still embryonic and largely conceptual. This study presents a novel approach that is designed for pre-event assessment of tourism sector resilience. We tested the index by predicting the impact of the COVID-19 pandemic on South Korean and US domestic tourism. Tourism sectors with diversified and balanced demand experienced a greater disruption. Nonetheless, these destinations were able to recover quickly and attract more tourists after recovery. The findings demonstrate that the index captures the responsiveness of the tourism sector. With high versatility and low data requirements, our resilience assessment tool offers opportunity to advance our understanding of tourism resilience and inform policy decisions.
    Date: 2024–09–05
    URL: https://d.repec.org/n?u=RePEc:osf:osfxxx:984nr
  2. By: Nasser Bouchareb (UFAS1 - Université Ferhat-Abbas Sétif 1 [Sétif])
    Abstract: This paper investigates how Artificial Intelligence (AI) can improve Hotel PropertyManagement Systems (PMS) in the hospitality industry. It traces the evolution of PMS from manual to modern AI-infused counterparts, demonstrating how AI improves effectiveness and guest satisfaction. AI-driven PMS significantly improve efficiency in operations, making hotels more competitive in a dynamic landscape, by focusing on dynamic pricing strategies, real-time brand monitoring, and streamlined customer experiences. The paper highlights the practical significance of AI in the hospitality industry, promoting to a better understanding of technology's role in providing customized services and operational excellence, ultimately improving the quality of travel experiences.
    Keywords: Artificial Intelligence (AI) Channel manager Hospitality industry Property Management Systems (PMS) Revenue Management JEL Classification Codes: C88 L83 O32, Artificial Intelligence (AI), Channel manager, Hospitality industry, Property Management Systems (PMS), Revenue Management JEL Classification Codes: C88, L83, O32
    Date: 2023–12–30
    URL: https://d.repec.org/n?u=RePEc:hal:journl:hal-04680595
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