Information Technology & Tourism最新文献

Beyond words: unveiling the implications of blank reviews in online rating systems 言外之意：揭示在线评级系统中空白评论的影响

IF 9.3 3区管理学

Information Technology & Tourism Pub Date : 2024-09-18 DOI: 10.1007/s40558-024-00300-4

Juan Pedro Mellinas, Veronica Leoni

引用次数: 0

Travelers’ viewpoints on machine translation using Q methodology: a perspective of consumption value theory 旅行者对使用 Q 方法进行机器翻译的看法：消费价值理论的视角

IF 9.3 3区管理学

Information Technology & Tourism Pub Date : 2024-08-13 DOI: 10.1007/s40558-024-00296-x

Namhee Lee, Kanghee Lee

引用次数: 0

Solving the tourist trip planning problem with attraction patterns using meta-heuristic techniques 利用元启发式技术解决具有吸引力模式的旅游行程规划问题

IF 9.3 3区管理学

Information Technology & Tourism Pub Date : 2024-08-12 DOI: 10.1007/s40558-024-00297-w

Kadri Sylejmani, Vigan Abdurrahmani, Arben Ahmeti, Egzon Gashi

引用次数: 0

Automated photo filtering for tourism domain using deep and active learning: the case of Israeli and worldwide cities on instagram 利用深度学习和主动学习为旅游领域自动过滤照片：Instagram 上的以色列和世界城市案例

IF 9.3 3区管理学

Information Technology & Tourism Pub Date : 2024-07-02 DOI: 10.1007/s40558-024-00295-y

Abigail Paradise-Vit, Aviad Elyashar, Yarden Aronson

{"title":"Automated photo filtering for tourism domain using deep and active learning: the case of Israeli and worldwide cities on instagram","authors":"Abigail Paradise-Vit, Aviad Elyashar, Yarden Aronson","doi":"10.1007/s40558-024-00295-y","DOIUrl":"https://doi.org/10.1007/s40558-024-00295-y","url":null,"abstract":"Social media platforms like Instagram significantly influence tourists’ travel decisions by providing them with valuable insights, recommendations, authentic information, and points of interest. However, photos shared with location-specific hashtags, even those related to tourist attractions, do not always reflect the actual destination, creating challenges for potential visitors seeking accurate information. To assist tourists in finding pertinent tourism information for specific destinations, we propose VISTA: Visual Identification of Significant Travel Attractions. The proposed method employs deep learning and active learning techniques to automatically classify photos into: ‘Tourism-Related’ photos (i.e., photos related to tourism) and ‘Non-Tourism-Related’ photos (i.e., photos unrelated to tourism). To train our machine learning classifier, we created a dataset containing photos of the 10 most popular Israeli cities on Instagram. The classifier obtained an accuracy score of 0.965 and a weighted F1 score of 0.964. Evaluating our classifier’s global generalization on the InstaCities100K dataset, derived from InstaCities1M, yielded an accuracy score of 0.958 and a weighted F1 score of 0.959. The effectiveness of VISTA was demonstrated by comparing tourism-related and non-tourism-related photos in terms of photo proportion, user engagement, and object comparison. We found that most photos published on Instagram associated with cities are irrelevant to tourists and that tourism-related photos received more likes than non-tourism-related photos. Finally, there was a low overlap between objects in the two photo collections. Based on these results, we conclude that VISTA can help tourists tackle the problem of finding relevant tourism-related photos among the high volume of photos available on Instagram.","PeriodicalId":46275,"journal":{"name":"Information Technology & Tourism","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141512307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sequential framework for analyzing mobile click-through decision in online travel agency with user digital footprints 利用用户数字足迹分析在线旅行社移动点击决策的顺序框架

IF 9.3 3区管理学

Information Technology & Tourism Pub Date : 2024-06-26 DOI: 10.1007/s40558-024-00294-z

Hongming Gao, Di Deng, Hongwei Liu, Zhouyang Liang

{"title":"Sequential framework for analyzing mobile click-through decision in online travel agency with user digital footprints","authors":"Hongming Gao, Di Deng, Hongwei Liu, Zhouyang Liang","doi":"10.1007/s40558-024-00294-z","DOIUrl":"https://doi.org/10.1007/s40558-024-00294-z","url":null,"abstract":"In the hotel booking market, high click-through rates are essential for online travel agencies (OTAs) to earn commissions. Given the dominance of mobile devices in web traffic, analyzing the mobile click-through decision-making process plays a vital role in search engine optimization. This study proposes a sequential framework that leverages Bayesian inference to model individual users’ click-through behaviors using user digital footprints, which encompass sequences of search, browse, compare, and click-through actions. This framework extracts three categories of information based on the degrees of dynamism in the hotel search process, ranging from less dynamic to highly dynamic levels: static hotel attributes, information cues in the search results, and temporal characteristics of user behaviors. Extensive experiments on a global OTA mobile clickstream dataset with over 600,000 observations reveal the substantial superiority of the proposed framework over the baseline models like probit regression and Naive Bayes. Notably, temporal characteristics emerge as the most important category. Drawing on our model, we delve into the interpretability of these three information categories. Additionally, we compare their varying impacts across different devices. Beyond these findings, this study offers valuable managerial implications for mobile OTA search engine marketing and optimization.","PeriodicalId":46275,"journal":{"name":"Information Technology & Tourism","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141529462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The perils of smart technology in museums 博物馆智能技术的危害

IF 9.3 3区管理学

Information Technology & Tourism Pub Date : 2024-06-25 DOI: 10.1007/s40558-024-00292-1

Yulan Fan, Aliana Man Wai Leong, IpKin Anthony Wong, Jingwen (Daisy) Huang

引用次数: 0

Do deep learning models accurately measure visual destination image? A comparison of a fine-tuned model to past work 深度学习模型能准确测量视觉目的地图像吗？微调模型与过去工作的比较

IF 9.3 3区管理学

Information Technology & Tourism Pub Date : 2024-06-04 DOI: 10.1007/s40558-024-00293-0

Lyndon J. B. Nixon

引用次数: 0

Enabling active visitor management: local, short-term occupancy prediction at a touristic point of interest 实现积极的游客管理：旅游景点的本地短期入住率预测

IF 9.3 3区管理学

Information Technology & Tourism Pub Date : 2024-06-04 DOI: 10.1007/s40558-024-00291-2

Jessica Bollenbach, Stefan Neubig, Andreas Hein, Robert Keller, Helmut Krcmar

{"title":"Enabling active visitor management: local, short-term occupancy prediction at a touristic point of interest","authors":"Jessica Bollenbach, Stefan Neubig, Andreas Hein, Robert Keller, Helmut Krcmar","doi":"10.1007/s40558-024-00291-2","DOIUrl":"https://doi.org/10.1007/s40558-024-00291-2","url":null,"abstract":"After the temporary shock of the Covid-19 pandemic, the rapid recovery and resumed growth of the tourism sectors accelerates unsustainable tourism, resulting in local (over-)crowding, environmental damage, increased emissions, and diminished tourism acceptance. Addressing these challenges requires an active visitor management system at points of interest (POI), which requires local and timely POI-specific occupancy predictions to predict and mitigate crowding. Therefore, we present a new approach to measure visitor movement at an open-spaced, and freely accessible POI and evaluate the prediction performance of multiple occupancy and visitor count machine learning prediction models. We analyze multiple case combinations regarding spatial granularity, time granularity, and prediction time horizons. With an analysis of the SHAP values we determine the influence of the most important features on the prediction and extract transferable knowledge for similar regions lacking visitor movement data. The results underline that POI-specific prediction is achievable with a moderate relation for occupancy prediction and a strong relation for visitor count prediction. Across all cases, XGBoost and Random Forest outperform other models, with prediction accuracy increasing as the prediction time horizon shortens. For effective active visitor management, combining multiple models with different spatial aggregations and prediction time horizons provides the best information basis to identify appropriate steering measures. This innovative application of digital technologies facilitates information exchange between destination management organizations and tourists, promoting sustainable destination development and enhancing tourism experience.","PeriodicalId":46275,"journal":{"name":"Information Technology & Tourism","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141257125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Developing 360-degree stimuli for virtual tourism research: a five-step mixed measures procedure 为虚拟旅游研究开发 360 度刺激：五步混合测量程序

IF 9.3 3区管理学

Information Technology & Tourism Pub Date : 2024-04-18 DOI: 10.1007/s40558-024-00287-y

Biqiang Liu, Anna Kralj, Brent Moyle, Yaoqi Li

{"title":"Developing 360-degree stimuli for virtual tourism research: a five-step mixed measures procedure","authors":"Biqiang Liu, Anna Kralj, Brent Moyle, Yaoqi Li","doi":"10.1007/s40558-024-00287-y","DOIUrl":"https://doi.org/10.1007/s40558-024-00287-y","url":null,"abstract":"Virtual reality has emerged as a powerful tool for the design of immersive tourism experiences. Prior studies have primarily relied on externally produced 360-degree stimuli, with the potential to undermine causal inference among concepts and increase risk of flattening real-world responses. Consequently, building on design principles embedded in human–computer interaction, this paper draws on an exemplar of an iconic nature-based tourism destination to elucidate the process which underpins the development of 360-degree stimuli, with an emphasis on the manipulation of ‘presence’. Emergent findings demonstrate the efficacy of a five-step procedure: (1) concept manipulation and location selection; (2) preliminary field filming; (3) expert evaluation and preliminary test; (4) re-filming and editing; and (5) confirmatory test. Physiological and self-report measures assessed the internal and external validity of the 360-degree stimuli, confirming the effectiveness of the manipulation. This research contributes to knowledge through the transfer of core principles from information technology and tourism into the design of immersive 360-degree stimuli to facilitate rigorous manipulation and multi-measurement in experimental design in tourism. Future research should focus on enhancing validity and reliability of internally produced immersive stimuli, overcoming methodological challenges with the design and manipulation of stimuli in tourism research.","PeriodicalId":46275,"journal":{"name":"Information Technology & Tourism","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140631045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Attributes influencing guests’ experiences: a comparison of nonprofit and for-profit peer-to-peer accommodation platforms 影响客人体验的因素：非营利性和营利性点对点住宿平台的比较

IF 9.3 3区管理学

Information Technology & Tourism Pub Date : 2024-04-16 DOI: 10.1007/s40558-024-00289-w

Vivian C. Medina-Hernandez, Estela Marine-Roig, Berta Ferrer-Rosell

{"title":"Attributes influencing guests’ experiences: a comparison of nonprofit and for-profit peer-to-peer accommodation platforms","authors":"Vivian C. Medina-Hernandez, Estela Marine-Roig, Berta Ferrer-Rosell","doi":"10.1007/s40558-024-00289-w","DOIUrl":"https://doi.org/10.1007/s40558-024-00289-w","url":null,"abstract":"Peer-to-peer accommodation has generated an ecosystem of platforms with different business models (i.e., for-profit and nonprofit). This study aims to identify and compare attributes that influence guests’ experiences as reviewed on the for-profit platform Airbnb and the nonprofit platforms Couchsurfing.com and HomeExchange.com according to a three-dimensional experience theoretical model and a methodological approach to interpret these attributes. The study used text-mining techniques to analyze 772,768 online travel reviews representing Spain’s four most-visited cities. Findings show that attributes influencing guests’ experiences in the case of nonprofit platforms relate to the authenticity dimension of experience (e.g., existential values and travel philosophy). Furthermore, guests reported that their guest–host interaction was the most representative attribute and that, unlike with Airbnb, such interaction helped to create a more authentic experience. By contrast, attributes of guests’ experiences in the case of for-profit platforms related to the physical amenities and characteristics that guests would expect to find in hotels. Those results can allow destination managers and accommodation practitioners to better understand users of peer-to-peer accommodations and thereby design more suitable strategies and experiences for them.","PeriodicalId":46275,"journal":{"name":"Information Technology & Tourism","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140610183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0