This report provides the global community of hospitality professionals with critical insights into emerging trends and developments, with a particular focus on the future of business travel. Business travellers play a pivotal role within the tourism industry, contributing significantly to international travel, GDP, and business revenues.In light of recent disruptions and evolving challenges, this forward-looking study aims not only to reflect on the past but, more importantly, to anticipate future developments and uncertainties in the realm of business travel. By doing so, it offers strategic insights to help hospitality leaders navigate the ever-evolving landscape of the industry.Key findings from the Yearly Outlook include:• Recovery of International Travel: By 2024, international travel arrivals have surpassed 2019 levels by 2%, signalling a full recovery in the sector. In Amsterdam, there was a 13% decrease in business traveller numbers, offset by an increase in the average length of stay from 2.34 to 2.71 days. Notably, more business travellers opted for 3-star accommodations, marking a shift in preferences.• Future of Business Travel: The report outlines a baseline scenario that predicts a sustainable, personalised, and seamless business travel experience by 2035. This future will likely be driven by AI integration, shifts in travel patterns—such as an increase in short-haul trips, longer stays combining business and leisure—and a growing focus on sustainability.• Potential Disruptors: The study also analyses several potential disruptors to these trends. These include socio-political shifts that could reverse sustainability efforts, risks associated with AI-assisted travel, the decline of less attractive business destinations, and the impact of global geopolitical tensions.The Yearly Outlook provides practical recommendations for hospitality professionals and tourism policymakers. These recommendations focus on building resilience, anticipating changes in business travel preferences, leveraging AI and technological advancements, and promoting sustainable practices within the industry.
this thesis was simply a research done to see how the manor amsterdam can use technologies to enhance its guest eperience. Surveys and intervews were conducted to see what the guest preferences were after which an implementation process was also drawn up.
MULTIFILE
In this work, the concept of an Artificial Intelligence-based (AI) Digital Twin (DT) of an aircraft system is introduced, with the goal to improve the corresponding MRO Operations. More specifically, the current study aims to obtaining knowledge on the optimal placement of sensors in an ideal Power Electronics Cooling System (PECS) of a modern airliner, aiming to improve input data as a basis for an AI-based DT. The three main fluid parameters to be measured directly or indirectly at various physical locations at the PECS are mass flow rate, temperature and static pressure. The physics-based model can then be combined with a Machine Learning (ML) model, such as a Random Forest (RF), with a multitude of decision trees. Following, the AI system determines whether the PECS operations is considered normal, aiming to optimize the performance of the system and to maximize the Useful Remaining Life (URL). The suggested AI-DT approach is based both on data-driven and physics-based models, an approach which results in increased reliability and availability, reducing possible Aircraft on Ground (AOG) events. Subsequently, the enhanced prediction capability results in the optimization of the maintenance processes and in reduced operational costs.
Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.
