...Irem Önder Purpose This study aims to investigate the effectiveness and accessibility of GPT-4-turbo, a large language model ( LLM ), compared to traditional machine learning ( ML ) methods for sentiment analysis in restaurant reviews. Beyond predictive performance, the study emphasizes practical...

...Nasim Binesh; Kushi Vardhan Reddy Pasham; Gidon Jakar; Ahmad Mujafar Syah Purpose In this study, the authors used advanced machine learning ( ML ) models combined with game theory concepts to predict the occupancy of Airbnb properties. By leveraging big data and explainable artificial intelligence...

... evidence, nearly half a year of extensive observations at a dim sum restaurant yielded 1,784 transactional data points and corresponding food leftover records. Second, multiple machine learning models were built and compared to identify the most parsimonious model that effectively predicts food leftovers...

... commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence maybe seen at Link to the terms of the CC BY 4.0 licence. Artificial intelligence Congruency Hospitality Machine learning Multi-sensory cues Sensory...

... and machine learning techniques, it aims to bridge the gap between behavioral intentions and actual behavior. Design/methodology/approach This study constructs the TPB components (attitudes, social norms and perceived control) from textual data, and analyzes their impacts on hotel customers’ behavioral...

.... Honggang Guo can be contacted at: ghg970612@163.com 15 05 2023 12 10 2023 10 12 2023 24 01 2024 25 01 2024 © Emerald Publishing Limited 2024 Emerald Publishing Limited Licensed re-use rights only Wine price forecasting Interval forecasting Machine learning...

.... Ampountolas and Legg (2021) combined the segmented boosting method with social media text analysis to enhance demand forecast accuracy at multiple time horizons. The practical value of the study is high, and their machine learning approach outperforms widely used traditional methods. A key limitation...

... proximity in their formation. Design/methodology/approach Data mining and machine learning techniques were applied to data collected from the websites of tourism companies located in northeastern Italy, namely, the Veneto region. Specifically, the authors used Web scraping to extract relevant...

.... Based on review samples of restaurants in a tourist destination Las Vegas, this study used an integrated method combining a machine learning algorithm and econometric modeling. Results indicate that the number of UGPs depicting a restaurant’s food, drink, menu and physical environment has...

... literature has significant implications for industry and practice, given that this, as far as the authors know, is the first systematic review of existing literature in this research area. Hospitality management Tourism research Deep learning Tourism management Machine learning Systematic...

..., hospitality and tourism literature has shown minimal efforts to process and analyze big hospitality data through AI. Thus, this study aims to develop and compare prediction models for review helpfulness using machine learning (ML) algorithms to analyze big restaurant data. Design/methodology/approach...

... and compared data for the same tourism destination from two sources: responses from a visitor intercept survey (n = 1,336) and Flickr social media photos and metadata (n = 11,775). Content analysis, machine learning and text analysis techniques were used to analyze and compare the destination...

...Apostolos Ampountolas; Mark P. Legg Purpose This study aims to predict hotel demand through text analysis by investigating keyword series to increase demand predictions’ precision. To do so, this paper presents a framework for modeling hotel demand that incorporates machine learning techniques...

... from 116,241 reviews scraped from Tripadvisor.com using a stratified sampling technique comprising hotels in major cities in the USA. A sample comprising 1,800 reviews was randomly drawn from this larger pool of reviews and manually annotated. A manual-set rule-based model, supervised machine learning...

... a machine learning algorithm, decision tree, to analyze the influential determinants on hotel booking considering the geographical distance between origin and destination. Findings The results of the findings demonstrate that the choice of package product is the prioritized determinant for longer-stay...

... research. © 2019 Emerald Publishing Limited 2019 Emerald Publishing Limited Licensed re-use rights only Literature review Bibliometrics Machine learning Contemporary hospitality management Structural topic modelling This study also examined changes in the research streams before...

.... This study applies machine learning and natural language processing approaches to combine features derived from the qualitative component of a review with the corresponding quantitative component and, therefore, generate a richer review rating. Experiments were performed over a collection of hotel...

...Eunhye (Olivia) Park; Bongsug Chae; Junehee Kwon Purpose This paper aims to identify the intellectual structure of four leading hospitality journals over 40 years by applying mixed-method approach, using both machine learning and traditional statistical analyses. Design/methodology/approach...