Academic literature on the topic 'Travel recommender system'
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Journal articles on the topic "Travel recommender system"
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Jambusariya, Shlok, Pragati Yadav, Mit Virani, and Pranali Wagh. "Intelligent Travel Guide: A Travel Recommender System." Journal of Web Development and Web Designing 7, no. 1 (2022): 15–20. http://dx.doi.org/10.46610/jowdwd.2022.v07i01.003.
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The hassle of deciding on a travel destination is often overlooked by travel websites. Travellers, a lot of times, do not have a clear idea of where they want to travel to. We aim on solving this problem by introducing a chat bot system that can recommend travel destinations based on minimal information from the traveller. Another interesting feature of the project is its itinerary generator. The system aims on providing a human-like user experience through the use of a chatbot interface. The interface interacts with the user to retrieve information about the user’s details like travel date, number of children and adults travelling and the budget of travelling. The user’s budget will be the main focus of this application as we want to give the end-user the best travel experience based on their particular budget. The recommender also takes other external factors such as the season, previous traveller experiences and weather into consideration. Incorporating these factors ensure that the most optimal destination is recommended to the user. As per the recommendation, the user can opt to get several itineraries to choose from. The itinerary generator also takes several external factors into consideration when generating an itinerary. The choice of itineraries vary in the choice of places and in activities according to budget and other external factors.
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Jambusariya, Shlok, Pragati Yadav, Mit Virani, and Pranali Wagh. "Intelligent Travel Guide: A Travel Recommender System." Journal of Web Development and Web Designing 7, no. 1 (2022): 15–20. http://dx.doi.org/10.46610/jowdwd.2022.v07i01.003.
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The hassle of deciding on a travel destination is often overlooked by travel websites. Travellers, a lot of times, do not have a clear idea of where they want to travel to. We aim on solving this problem by introducing a chat bot system that can recommend travel destinations based on minimal information from the traveller. Another interesting feature of the project is its itinerary generator. The system aims on providing a human-like user experience through the use of a chatbot interface. The interface interacts with the user to retrieve information about the user’s details like travel date, number of children and adults travelling and the budget of travelling. The user’s budget will be the main focus of this application as we want to give the end-user the best travel experience based on their particular budget. The recommender also takes other external factors such as the season, previous traveller experiences and weather into consideration. Incorporating these factors ensure that the most optimal destination is recommended to the user. As per the recommendation, the user can opt to get several itineraries to choose from. The itinerary generator also takes several external factors into consideration when generating an itinerary. The choice of itineraries vary in the choice of places and in activities according to budget and other external factors.
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R, oopesh L., and Tulasi B. . "A Survey of Travel Recommender System." International Journal of Computer Sciences and Engineering 7, no. 3 (2019): 356–62. http://dx.doi.org/10.26438/ijcse/v7i3.356362.
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Supriyanto, Supriyanto, and Jefree Fahana. "Possible System Architecture for Travel Recommender." Jurnal Online Informatika 5, no. 1 (2020): 1–8. http://dx.doi.org/10.15575/join.v5i1.573.
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Travel recommender systems have been developed to meet the needs of users in the field of tourism. This system has several versions depending on the characteristics of the country, users and filtering techniques used. The development of recommendation filtering system techniques is very rapid so that the recommendation system has high enough complexity, but it also must have high usability. This paper discusses how the travel recommender system architecture is built by examining data structures, processing procedures and interaction design. The goal is to obtain the best usability in implementing a travel recommendation system. The system is built using the example case of finding the right tourist spot in Yogyakarta, Indonesia. This system applies several filtering techniques such as knowledge-based filtering, content-based filtering, and collaborative filtering. The evaluation results show that the system architecture optimized gets a usability level acceptable.
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B, Tanuja Choudhary, and Tulasi B. "Recommender system for personalised travel itinerary." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 4460. http://dx.doi.org/10.11591/ijece.v9i5.pp4460-4465.
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<p class="Body">A recommender system is an approach to give an appropriate solu-tion to a particular problem. This helps in recognising the pattern or behaviour of a user to suggest future possible likes of the user. Nowa-days people like to travel during their spare time, it has become a rigid task to decide where to go. This paper represents a customised recommender system to help users in destining their itinerary. A model is designed to suggest the best places to visit in Rome. A questionnaire was prepared to get information about users interest during their travel. The model generates the best five places to visit with respect to the choice picked by the user. The top five places for each category will be displayed to the user and the user was asked to pick a starting point for the itinerary. Then the model generates another set off a filtered list of places to enhance their travel experi-ence. It includes displaying the top 5 restaurants to visit during their travel.</p>
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Tanuja, Choudhary B., and B. Tulasi. "Recommender system for personalised travel itinerary." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 4460–65. https://doi.org/10.11591/ijece.v9i5.pp4460-4465.
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A recommender system is an approach to give an appropriate solution to a particular problem. This helps in recognising the pattern or behaviour of a user to suggest future possible likes of the user. Nowadays people like to travel during their spare time, it has become a rigid task to decide where to go. This paper represents a customised recommender system to help users in destining their itinerary. A model is designed to suggest the best places to visit in Rome. A questionnaire was prepared to get information about user’s interest during their travel. The model generates the best five places to visit with respect to the choice picked by the user. The top five places for each category will be displayed to the user and the user was asked to pick a starting point for the itinerary. Then the model generates another set off a filtered list of places to enhance their travel experience. It includes displaying the top 5 restaurants to visit during their travel.
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Chen, Meng-Kuan, Hsin-Wen Wei, and Wei-Tsong Lee. "Intelligent POIs Recommender System Based on Time Series Analysis with Seasonal Adjustment." International Journal for Applied Information Management 2, no. 2 (2021): 66–80. http://dx.doi.org/10.47738/ijaim.v2i2.28.
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Recommender systems have been applied on a variety of applications including movies, music, news, books, research articles, search queries, and travel information. Instead of searching travel information from the extremely huge amount of travel data, a personalized travel recommender system is desired. However, an inappropriate travel recommendation may result from a wrong season, even if it is already a correct location. The current recommender systems from time to time make an inappropriate commendation without considering the seasonal factor. In order to resolve the discrepancy, the seasonal factor should have been taken into consideration when making a good travel recommender system. Therefore, this study has taken the trend analysis, time series, and seasonal factor into considerations to cope with the above mentioned discrepancy and to make the travel recommender system renders a better fit.
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Fang, Hui, Chongcheng Chen, Yunfei Long, Ge Xu, and Yongqiang Xiao. "DTCRSKG: A Deep Travel Conversational Recommender System Incorporating Knowledge Graph." Mathematics 10, no. 9 (2022): 1402. http://dx.doi.org/10.3390/math10091402.
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In the era of information explosion, it is difficult for people to obtain their desired information effectively. In tourism, a travel recommender system based on big travel data has been developing rapidly over the last decade. However, most work focuses on click logs, visit history, or ratings, and dynamic prediction is absent. As a result, there are significant gaps in both dataset and recommender models. To address these gaps, in the first step of this study, we constructed two human-annotated datasets for the travel conversational recommender system. We provided two linked data sets, namely, interaction sequence and dialogue data sets. The usage of the former data set was done to fully explore the static preference characteristics of users based on it, while the latter identified the dynamics changes in user preference from it. Then, we proposed and evaluated BERT-based baseline models for the travel conversational recommender system and compared them with several representative non-conversational and conversational recommender system models. Extensive experiments demonstrated the effectiveness and robustness of our approach regarding conversational recommendation tasks. Our work can extend the scope of the travel conversational recommender system and our annotated data can also facilitate related research.
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Mohite, K. T. "Travel and Tourism Management System Using Chatbot Recommender." International Journal for Research in Applied Science and Engineering Technology 12, no. 4 (2024): 2908–17. http://dx.doi.org/10.22214/ijraset.2024.60581.
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Abstract: The importance of chatbots has surged in both research and practical applications, exemplified by widely used platforms such as Amazon’s Alexa and Apple’s Siri. This paper introduces the methodologies and technologies underpinning a chatbot tailored for e-tourism, facilitating textual communication to aid in hotel bookings, trip planning, and recommendations for noteworthy sights. Specifically, we explore the integration of model-based reasoning to elevate user interaction, particularly in scenarios featuring an overwhelming array of choices or where user preferences are excessively restrictive, leading to inconsistencies and unattainable responses. Additionally, we offer a use case within the tourism domain to demonstrate the practical efficacy of such a model-based chatbot.
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Mohite, Prof K. T. "TRAVEL AND TOURISM MANAGEMENT SYSTEM USING CHATBOT RECOMMENDER." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 07, no. 10 (2023): 1–11. http://dx.doi.org/10.55041/ijsrem26416.
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Chatbots have gained increasing importance for research and practice with a lot of applications available today including Amazon’s Alexa or Apple’s Siri. In this paper, we present the underlying methods and technologies behind a Chatbot for e-tourism that allows people textually communicate with the purpose of booking hotels, planning trips, and asking for interesting sights worth being visit. In particular, we show how model- based reasoning can be used for enhancing user experience during a chat, e.g., in cases where too many possible selections are available or where user preferences are too restricted causing inconsistencies and as a consequence not possible answers to be provided. Besides the underlying foundations, we provide a use case from the intended tourism domain to show how such a model-based chatbot effectively can be used in practice. Key Words: travel recommendation, time sensitivity, recency effect, personalization, social media
Dissertations / Theses on the topic "Travel recommender system"
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Li, Siying. "Context-aware recommender system for system of information systems." Thesis, Compiègne, 2021. http://www.theses.fr/2021COMP2602.
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Travailler en collaboration n’est plus une question mais une réalité, la question qui se pose aujourd’hui concerne la mise en œuvre de la collaboration de façon à ce qu’elle soit la plus réussie possible. Cependant, une collaboration réussie n’est pas facile et est conditionnée par différents facteurs qui peuvent l’influencer. Il est donc nécessaire de considérer ces facteurs au sein du contexte de collaboration pour favoriser l’efficacité de collaboration. Parmi ces facteurs, le collaborateur est un facteur principal, qui est étroitement associé à l’efficacité et à la réussite des collaborations. Le choix des collaborateurs et/ou la recommandation de ces derniers en tenant compte du contexte de la collaboration peut grandement influencer la réussite de cette dernière. En même temps, grâce au développement des technologies de l’information, de nombreux outils numériques de collaboration sont mis à la disposition tels que les outils de mail et de chat en temps réel. Ces outils numériques peuvent eux-mêmes être intégrés dans un environnement de travail collaboratif basé sur le web. De tels environnements permettent aux utilisateurs de collaborer au-delà de la limite des distances géographiques. Ces derniers laissent ainsi des traces d’activités qu’il devient possible d’exploiter. Cette exploitation sera d’autant plus précise que le contexte sera décrit et donc les traces enregistrées riches en description. Il devient donc intéressant de développer les environnements de travail collaboratif basé sur le web en tenant d’une modélisation du contexte de la collaboration. L’exploitation des traces enregistrés pourra alors prendre la forme de recommandation contextuelle de collaborateurs pouvant renforcer la collaboration. Afin de générer des recommandations de collaborateurs dans des environnements de travail collaboratifs basés sur le web, cette thèse se concentre sur la génération des recommandations contextuelles de collaborateurs en définissant, modélisant et traitant le contexte de collaboration. Pour cela, nous proposons d’abord une définition du contexte de collaboration et choisissons de créer une ontologie du contexte de collaboration compte tenu des avantages de l’approche de modélisation en l’ontologie. Ensuite, une similarité sémantique basée sur l’ontologie est développée et appliquée dans trois algorithmes différents (i.e., PreF1, PoF1 et PoF2) afin de générer des recommandations contextuelles des collaborateurs. Par ailleurs, nous déployons l’ontologie de contexte de collaboration dans des environnements de travail collaboratif basés sur le web en considérant une architecture de système des systèmes d’informations du point de vue des environnements de travail collaboratif basés sur le web. À partir de cette architecture, un prototype correspondant d’environnement de travail collaboratif basé sur le web est alors construit. Enfin, un ensemble de données de collaborations scientifiques est utilisé pour tester et évaluer les performances des trois algorithmes de recommandation contextuelle des collaborateurs<br>Working collaboratively is no longer an issue but a reality, what matters today is how to implement collaboration so that it is as successful as possible. However, successful collaboration is not easy and is conditioned by different factors that can influence it. It is therefore necessary to take these impacting factors into account within the context of collaboration for promoting the effectiveness of collaboration. Among the impacting factors, collaborator is a main one, which is closely associated with the effectiveness and success of collaborations. The selection and/or recommendation of collaborators, taking into account the context of collaboration, can greatly influence the success of collaboration. Meanwhile, thanks to the development of information technology, many collaborative tools are available, such as e-mail and real-time chat tools. These tools can be integrated into a web-based collaborative work environment. Such environments allow users to collaborate beyond the limit of geographical distances. During collaboration, users can utilize multiple integrated tools, perform various activities, and thus leave traces of activities that can be exploited. This exploitation will be more precise when the context of collaboration is described. It is therefore worth developing web-based collaborative work environments with a model of the collaboration context. Processing the recorded traces can then lead to context-aware collaborator recommendations that can reinforce the collaboration. To generate collaborator recommendations in web-based Collaborative Working Environments, this thesis focuses on producing context-aware collaborator recommendations by defining, modeling, and processing the collaboration context. To achieve this, we first propose a definition of the collaboration context and choose to build a collaboration context ontology given the advantages of the ontology-based modeling approach. Next, an ontologybased semantic similarity is developed and applied in three different algorithms (i.e., PreF1, PoF1, and PoF2) to generate context-aware collaborator recommendations. Furthermore, we deploy the collaboration context ontology into web-based Collaborative Working Environments by considering an architecture of System of Information Systems from the viewpoint of web-based Collaborative Working Environments. Based on this architecture, a corresponding prototype of web-based Collaborative Working Environment is then constructed. Finally, a dataset of scientific collaborations is employed to test and evaluate the performances of the three context-aware collaborator recommendation algorithms
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Wang, Ning. "Towards a competency recommender system from collaborative traces." Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2300/document.
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Les systèmes de recommandation sont conçus dans une variété d'applications pour aider à la prise de décision. Dans un environnement collaboratif, le système de recommandation peut guider la collaboration. Les utilisateurs laissent des traces d’interaction lorsqu'ils collaborent sur une plateforme numérique. Ces traces peuvent être analysées pour détecter les signaux forts et les signaux faibles d’une collaboration. Cette thèse porte sur la mise en œuvre d'un système de recommandation exploitant les traces de collaboration dans un environnement informatique. Les travaux réalisés ont été testés au sein de la plateforme web collaborative E-MEMORAe<br>With the development of information and Internet technology, human society has stepped into an era of information overload. Owing to the overwhelming quantity of information, both information providers and information consumers are facing challenges: information providers want the information to be transferred to the target audience while information consumers need to find the information most relevant to their need. To bridge the gap, recommender systems have been designed and applied in a variety of applications to help making decisions on movies, music, news and even services and persons. In a Collaborative Working Environment, recommender systems are also needed to guide collaboration and allocate task efficiently. When people exchange information and resources, they leave traces in some way or other. For a typical Web-based Collaborative Working Environment, traces can be recorded which are mainly produced by collaborative activities or interactions. The modelled traces represent knowledge as well as experience concerning the interactive actions among users and resources. Such traces can be defined, modelled and exploited in return to offer a clue on a variety of deductions. Firstly they can indicate whether a user is active or not concerning interactions on a certain subject. Combining with users’ evaluation of the information and resources during interaction, we can further evaluate a user’s competency on each subject. This aids the decision for further collaboration because knowing the specialization of users helps to distribute tasks reasonably.This thesis focuses on implementing a recommender system by exploiting various collaborative traces in the group shared/collaborative workspace. To achieve this goal, firstly we collect traces and get them filtered by system filters. For evaluating shared resources we propose a system of vote and combine the result with collaborative traces. Furthermore, we present two mathematical approaches (TF-IDF and Bayes Classifier) with semantic meanings of traced resources and a machine learning method (Logistic Regression) with user profile to exploit traces, and then discuss comprehensive examples. As a practical experience we tested our prototype in the context of the E-MEMORAe collaborative platform. By comparing the results of experiments we assess the strengths and weaknesses of each of the three methods and in which scenario they perform better. Cases show that our exploitation framework and various methods can facilitate both personal and collaborative work and help decision-making
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Bied, Guillaume. "Designing Recommender Systems for the Labor Market." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASG035.
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En apprenant des appariements passés, les systèmes de recommandation ont le potentiel de réduire les frictions informationnelles sur le marché du travail. Cette thèse pose la question de la conception et de l'évaluation d'algorithmes de recommandation d'offres d'emploi, en s'appuyant sur des données détaillées fournies par le service public de l'emploi français. Premièrement, nous proposons une nouvelle architecture neuronale pour la recommandation d'offres d'emploi. Cette architecture présente l'avantage de répondre au problème du démarrage à froid tout en passant à l'échelle. L'approche proposée est comparée à l'état de l'art en termes de performance hors-ligne. Elle est également évaluée sur le terrain en termes de satisfaction des utilisateurs au moyen d'expériences randomisées à grande échelle. Deuxièmement, nous examinons les objectifs possibles qu'un concepteur pourrait assigner à un algorithme de recommandation d'offres d'emploi. Cette analyse est réalisée dans le cadre d'un modèle économique, qui nous permet de discuter les mérites et limites de différentes approches plausibles (satisfaire les critères de recherche exacts des demandeurs, apprendre des candidatures ou des embauches), et de les confronter aux besoins des demandeurs d'emploi. Troisièmement, nous étudions le problème de la congestion qui peut survenir si les recommandations se concentrent sur un ensemble excessivement restreint d'offres, créant des conséquences nuisibles au niveau agrégé. Nous proposons une approche algorithmique utilisant des outils du transport optimal computationnel pour limiter ce phénomène, et étudions ses performances sur des données publiques et propriétaires. Enfin, comme les algorithmes de recommandations sont entraînés sur des données issues du monde réel, ils peuvent reproduire ou aggraver certains comportements indésirables (discriminations, anticipations erronées) existants sur le marché du travail.Afin de répondre à ces inquiétudes, nous réalisons un audit fin de l'algorithme de recommandation (entraîné à partir des embauches) en se focalisant sur les inégalités de genre. En s'inspirant de la littérature en économie du travail, nous proposons des mesures des écarts genrés en termes de caractéristiques des recommandations (salaire, type de contrat...), en moyenne ou conditionnellement aux qualifications et préférences des demandeurs d'emploi. Selon nos résultats, l'algorithme reproduit, sans aggraver,les biais de genre présents dans les données d'entraînement. Nous proposons également une approche dite de ``post-traitement" dont l'objectif est de réduire les écarts femmes-hommes en termes de caractéristiques des offres recommandées. Nous décrivons les arbitrages entre performance et équité que cette intervention implique<br>Recommender systems have the potential to reduce information frictions on the labor market by leveraging past interactions between job seekers and recruiters. This thesis presents several contributions to the design and evaluation of job recommender systems, leveraging detailed real-world data provided by the French Public Employment Service. First, we propose a novel neural architecture for job recommendation, aimed at providing relevant recommendations in the cold-start setting while maintaining scalability. The proposed approach is compared to the state of the art in terms of off-line performance. It is also evaluated in the field in terms of user satisfaction, measured in the context of large-scale randomized experiments. Second, we discuss the possible objectives that a designer could assign to a job recommender system. Based on a formal economic model, we discuss the merits and limits of different plausible approaches (satisfying job seekers' exact search parameters, optimizing for application or hiring probability), and confront them to job seekers' needs. Third, we study the issue of the congestion that may arise if recommendations focus on an excessively small set of job ads, creating negative aggregate consequences. Leveraging tools from the computational transport literature, we propose a post-processing approach to congestion-avoiding recommendation, and assess its performance on proprietary and public datasets. Finally, as recommender systems are trained on real-world data, they may replicate or worsen undesirable behaviors (discrimination, inaccurate beliefs) that may exist on the labor market. We provide a detailed audit of the proposed recommender system (trained on hiring data) in terms of gender inequalities. Drawing inspiration from the labor economics literature on the gender wage gap, we propose measures for gender gaps in recommendation characteristics, on average or conditionally on job seekers' qualifications and preferences. We find that the algorithm reproduces, but does not increase, gender gaps that exist in its training data. We propose a post-processing approach to reduce unconditional or conditional gender gaps, and describe the trade-offs it entails
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Chiu, Chun Yen, and 邱俊彥. "Travel Recommender System in Wireless Environment." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/16760914057670377139.
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碩士<br>國立彰化師範大學<br>資訊管理學系所<br>96<br>Exploring new applications and services for mobile environments has generated considerable excitement among both commercial companies and academics. In this thesis we propose a travel recommender system that accommodates a traveler’s interest with location-dependent sightseeing destinations. Specifically, we investigate the dynamic mobile peer-to-peer architecture and propose a recommender system which includes data model, data dissimilarities model and recommendation model for recommending sightseeing destinations by taking into account the preferences of heterogeneous travelers. We present the developed system and the constructed approaches in this thesis. The results of experiments using synthetic data are also reported and discussed.
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Yoo, Kyung Hyan. "Creating More Credible and Likable Travel Recommender Systems: The Influence of Virtual Agents on Travel Recommender System Evaluation." Thesis, 2010. http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7984.
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To help online trip planners, some online travel agencies and travel service providers have adopted travel recommender systems. Although these systems are expected to support travelers in complex decision-making processes, they are not used efficiently by travelers due to a lack of confidence in the recommendations they provide. It is important to examine factors that can influence the likelihood of recommendations to be accepted and integrated into decision-making processes. The persuasion literature suggests that people are more likely to accept recommendations from credible and likable sources. It has also been found that technologies can be more credible and likable when they give a variety of social cues that elicit social responses from their human users. Thus, it is argued that enhancing the social aspects of travel recommender systems is important to create more persuasive systems.
One approach to enhancing the social presence of recommender systems is to use a virtual agent. Current travel recommender systems use various types of virtual agents. However, it is still not clear how those virtual agents are perceived by travel recommender system users and influence users' system evaluations and interactions with these systems. Consequently, this dissertation aimed to investigate the influence of virtual agents presented in travel recommender systems on system users' perceptions. Specifically, the virtual agents' anthropomorphism as well as similarity and authority cues on system users' perceptions of system credibility and liking were examined.
For this purpose, two experiments were conducted. For Study 1, the impacts of anthropomorphism of the virtual agents on users' perceptions of virtual agents as well as recommender systems in terms of credibility and attractiveness/liking were examined. Anthropomorphism was manipulated with visual human appearance and voice output. Study 2 tested the influence of virtual agents? similarity and authority on travel recommender system users' perceptions of virtual agents and system credibility and attractiveness/liking. Similarity and authority of the virtual agent were tested by manipulating nonverbal cues (age and outfit) of the agent.
The results showed that the characteristics of virtual agents have some influences on system users' perceptions of virtual agents as well as recommender systems. Specifically, a human-like appearance of the virtual agent is found to positively influence users' perceived attractiveness of the virtual agent while voice outputs were found to enhance users' liking of the system (Study 1). Findings also indicate that RS users' perceptions of virtual agent expertise are increased when virtual agents wear a uniform rather than a casual outfit (Study 2). In addition, system users' perceptions of the virtual agent's credibility are found to have a significant influence on users' perceived credibility and liking of the overall system, which implies an important role of virtual agents in recommender system evaluations. Further, perceived credibility and liking of recommender systems lead to favorable evaluations of the recommendations, which, in turn, increase users' intentions to travel to the recommended destination.
Past travel recommender system studies have largely neglected the social role of recommender systems as advice givers. Also, it is not clear whether the specific characteristics of virtual agents presented as a part of the system interface influence system users' perceptions. This dissertation sought to close this knowledge gap. By applying classic interpersonal communication theories to human and system relationships, this dissertation expands the scope of traditional theories used in the context of studying recommender systems. Further, the results of the research presented in this dissertation provide insights for tourism marketing as well as practical implications for travel recommender system design.
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Kung, Yu-Wei, and 龔昱瑋. "An Incentive Model Based Travel Recommender System." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/60840991455243878756.
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碩士<br>國立彰化師範大學<br>資訊管理學系所<br>100<br>Tourists are often confused about where to go when reaching new and unfamiliar places because there could be a large number of selections for consideration. Therefore, in this research, we develop a travel recommender system, which exploits other tourists’ ratings on their visited attractions for making attraction recommendations. We propose to use mobile peer-to-peer communications to provide tourists with convenient and inexpensive means for exchanging ratings stored in their mobile devices. We also develop an inventive model and propose an inventive-based data exchange method that allows users to effectively exchange their ratings toward visited attractions. Simulated experiments are performed in this research to evaluate the proposed model and data exchange method.
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Lu, Chi-An, and 盧濟安. "A Travel Recommender System With Given Accommodations and Interest Spots." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/11004588472349737163.
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碩士<br>淡江大學<br>資訊管理學系碩士班<br>97<br>This work presents a travel recommender system based on solution of the traveling salesman problem. The system is intended for driving travelers with accommodation in mind. It can provide a suitable tour itinerary given the required spots, hotels, and paths; optional spots of varying interest levels; the per day upper and lower bounds for touring time and distance; and the fixed number of total visited spots.
The work will first introduce the design of various criteria which include the distance criterion, the time criterion, the required path criterion, the interest spots criterion, and the total visited spots criterion. These criteria are merged on a weighted basis to evaluate the goodness of a tour itinerary. A search algorithm based on the simulated annealing is used to search for the best tour itinerary. In current implementation, the shortest time or distance between adjacent spots in an itinerary is computed by the A* with landmark and triangle algorithm (ALT).
For demonstration, several experiments are conducted which include the 3 common modes of travel patterns: the base camp pattern, the regional tour pattern, and the trip-chaining pattern; and other special cases: one with many spots, one with dense spots, and one with a fixed number of total visited spots. The convergence speed for each experiment is also shown. The results show that the sub-optimal solution returned by the simulated annealing is acceptable in terms of execution time and deviation from the optimal solution. Thus the system is fit for personal independent travelers who want to plan a tour with accommodations on their own.
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Ho, Cho-Yin, and 何卓穎. "U-tour：A context-aware and ontology based recommender system for Kyoto Travel." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/y5d63w.
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碩士<br>國立彰化師範大學<br>資訊管理學系所<br>104<br>With the development of Internet, more and more travelers search for travel information on the Internet. The travelers could use those information to help them plan itinerary. Because of the universal mobile internet, we could get a variety of information immediately, and it helps us make decision better. There are many recommendation systems using context-aware and user-user similarity model, but these systems did not have an organizational structure.
In this study, we propose a travel recommendation system, providing recommendation based on travel topic. The system introduces ontology technology to discover the relationship between each tourist attractions, and build a travel topic model. It also aim to find potential travel topic from user’s travel histories. The system is context-aware which can perceive the context around the user. It will provide different recommendation results when the context changes. The season and distance context information is considered during the recommendation process.
The evaluation result shows that our system can provide high satisfaction. The system is sufficient to meet user’s requirement, and it is capable to provide the tourist attraction that user is interested.
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陳聿惠. "A Study on the Evaluation of Travel Recommender System in Mobile Environment." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/06815006544071804272.
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碩士<br>國立彰化師範大學<br>資訊管理學系所<br>99<br>In recent years,a new trend has been to outfit pocket-sized devices with mobile communication capabilities to develop new types of applications. One of the most promising of the various types of emerging applications is recommender systems for the tourism industry. In this study, we therefore designed a user satisfaction instrument to evaluate a travel recommender system that executes on a personal mobile device to provide on-tour recommendations of tourist attractions. We extended the well-known IS success model and developed measurement scales for the four dimensions of satisfaction - the recommendation, travel, mobility, and functionality of a mobile travel recommender system. By studying a mobile travel recommender system- iTravel, the measurement scales were tested for reliability and validity in this thesis.
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Lee, Yu-Min, and 李玉敏. "A Study on Recommender Systems of Travel Web Sites." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/64230928554724285729.
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碩士<br>中原大學<br>資訊管理研究所<br>92<br>Due to rapid development of <a href="http://www.ntsearch.com/search.php?q=Internet&v=56">Internet</a>, it influences traditional tourism industry. In fact, No matter <a href="http://www.ntsearch.com/search.php?q=Internet&v=56">Internet</a> based or traditional <a href="http://www.ntsearch.com/search.php?q=travel&v=56">travel</a> agency, they all try to make use of <a href="http://www.ntsearch.com/search.php?q=Internet&v=56">Internet</a> to attack and occupy <a href="http://www.ntsearch.com/search.php?q=travel&v=56">travel</a> market. However, while they set up <a href="http://www.ntsearch.com/search.php?q=web&v=56">web</a> sites to sell their <a href="http://www.ntsearch.com/search.php?q=travel&v=56">travel</a> service, a new differentiate service strategy is the best way to raise customer satisfaction and remain customer. So, more scholar place importance on the issue of personalization.
When we want to apply the idea of personalization to <a href="http://www.ntsearch.com/search.php?q=travel&v=56">travel</a> <a href="http://www.ntsearch.com/search.php?q=web&v=56">web</a> sites, recommender systems is the suitable tool. In past, if customer wants to <a href="http://www.ntsearch.com/search.php?q=search&v=56">search</a> for <a href="http://www.ntsearch.com/search.php?q=travel&v=56">travel</a> schedule or <a href="http://www.ntsearch.com/search.php?q=commodities&v=56">commodities</a> that meet their needs, they have to spend much <a href="http://www.ntsearch.com/search.php?q=time&v=56">time</a> to compare these differences among diversity of <a href="http://www.ntsearch.com/search.php?q=travel&v=56">travel</a> <a href="http://www.ntsearch.com/search.php?q=web&v=56">web</a> sites. In fact, abundant content and description is a burden to customer, so evaluation and comparison become a difficult task. If we can make use of recommender systems to compare these different <a href="http://www.ntsearch.com/search.php?q=travel&v=56">travel</a> services, we can help our customer get their suitable information in short <a href="http://www.ntsearch.com/search.php?q=time&v=56">time</a>, and we can raise purchase rate of <a href="http://www.ntsearch.com/search.php?q=web&v=56">web</a> sites.
This study proposes a recommender system that is make use of conjoint analysis and association rule is suitable for <a href="http://www.ntsearch.com/search.php?q=travel&v=56">travel</a> <a href="http://www.ntsearch.com/search.php?q=web&v=56">web</a> sites. We are according to user’s fond sequence and browsing record about <a href="http://www.ntsearch.com/search.php?q=travel&v=56">travel</a> products to recommend target commodity. After expert’s evaluation, we have the conclusion that recommender system indeed raises user’s reception on <a href="http://www.ntsearch.com/search.php?q=travel&v=56">travel</a> <a href="http://www.ntsearch.com/search.php?q=web&v=56">web</a> site, and it will also raises user’s loyalty.
Books on the topic "Travel recommender system"
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1952-, Sharda Nalin, ed. Tourism informatics: Visual travel recommender systems, social communities, and user interface design. Information Science Reference, 2010.
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1952-, Sharda Nalin, ed. Tourism informatics: Visual travel recommender systems, social communities, and user interface design. Information Science Reference, 2010.
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1952-, Sharda Nalin, ed. Tourism informatics: Visual travel recommender systems, social communities, and user interface design. Information Science Reference, 2010.
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Kachan, Natal'ya, and Svetlana Novosel'ceva. Features of accounting in trade and public catering. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1048801.
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The textbook deals with the main issues of setting up accounting of commodity transactions in wholesale and retail organizations, public catering enterprises, including the system of consumer cooperation. This takes into account the features of the organization of inventory accounting in the book and magazine form.
 
 Meets the requirements of the Federal state educational standards of secondary vocational education.
 
 Recommended for students of the specialty Economics and accounting (by industry)" to study the discipline "Features of accounting in organizations of various types of activity". It can be useful for practitioners of trade and public catering."
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Institute, American National Standards, American Institute of Aeronautics and As, and American Anstitute of Aeronautics &. Astr. Recommended Practice for Human-Computer Interfaces for Space System Operations. AIAA (American Institute of Aeronautics & Ast, 1995.
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Gluckman, Sir Peter, Mark Hanson, Chong Yap Seng, and Anne Bardsley. Copper in pregnancy and breastfeeding. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780198722700.003.0024.
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Copper is an essential trace mineral with a central role in oxidation#amp;#x2013;reduction reactions. It is involved in connective tissue formation and disulphide bonding of keratin. Clinical deficiency for copper is uncommon but has been increasing in prevalence, resulting from malnutrition or lack of trace metals in the food source, even in Western diets. Secondary copper deficiency can be induced by excess intake of zinc or iron and is sometimes seen in individuals taking supplements of these minerals. Copper requirements are increased in pregnancy, and suboptimal supply may have adverse effects on developing tissues and organ systems including the lung, skin, bones, and immune system. Despite the increased need, supplementation is generally not recommended in pregnancy. An increased intake of foods high in copper, such as nuts, and a proportionate lowering of low-copper foods (e.g. fats/oils) may be advisable in women with potentially marginal copper status.
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Panella, Cristiana, and Walter E. Little, eds. Norms and Illegality. Published by Lexington Books, 2021. https://doi.org/10.5040/9781978721081.
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Norms and Illegality: Intimate Ethnographies and Politics explores liminal and illegal practices in relation to political control and cultural normativity. The contributors draw on years of ethnographic experiences in Greece, Guatemala, Hong Kong, Italy, Madagascar, Mali, Philippines, and Thailand to study the contradictions of what is legal and illegal. They explore the production of illegal subjects by the state, the creation of illegal and normative values by liminal and illegal actors, and the mutual entanglements of legal and illegal in the public domains of markets and trade networks. This volume shows that criminalization policies are not necessarily oriented toward erasing crime. Instead, the contributors maintain that opaque spaces ensure the efficacy of control and outwardly conform to the rhetoric and ethics of global neoliberalism. Within these contexts, the contributors shed light on moral economies and frames of value entailed in systems of representation that have been set up by individuals who are deemed illegal, liminal, or deviant in their confrontations with the state. This book is recommended for students and scholars of anthropology, political science, and urban studies.
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Hooker, Mark T. The History of Holland. Greenwood, 1999. http://dx.doi.org/10.5040/9798400664847.
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Holland was once a superpower upon whose empire the sun never set. Today it is on the leading edge of social change. This history of Holland, from its earliest beginnings to the present day, provides the most up-to-date survey of modern Dutch history, including the current Dutch approach to a number of social issues, such as the welfare state, the environment, socialized medicine, and the role of the military in the post-Cold War world. Containing a wealth of current information and statistics, this work will help the reader to understand the Dutch both within the historical context in which Holland exists and as world leaders in social change as we approach the twenty-first century. This engagingly written history provides a contemporary overview of Holland's geography, economy, political system, and society. Chapters arranged chronologically trace the history and culture of the nation from the Ice Age to the new post-Cold War world. Chapters on recent Dutch history show how Holland has claimed a leading role in social change: the Dutch have authorized euthanasia, socialized medicine, and legalized soft drugs. A selection of brief biographical sketches will introduce the reader to many of the important Dutch personalities throughout Holland's history, and a bibliographical essay will help the researcher to locate recommended books and other materials for further reading.
Book chapters on the topic "Travel recommender system"
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Garcia, Ander, Isabel Torre, and Maria Teresa Linaza. "Mobile Social Travel Recommender System." In Information and Communication Technologies in Tourism 2014. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03973-2_1.
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Muneer, V. K., and K. P. Mohamed Basheer. "Collaborative Travel Recommender System Based on Malayalam Travel Reviews." In Artificial Intelligence and Speech Technology. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95711-7_53.
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Linaza, Maria Teresa, Amaia Agirregoikoa, Ander Garcia, Jose Ignacio Torres, and Kepa Aranburu. "Image-based Travel Recommender System for small tourist destinations." In Information and Communication Technologies in Tourism 2011. Springer Vienna, 2011. http://dx.doi.org/10.1007/978-3-7091-0503-0_1.
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Gretzel, Ulrike. "Dreaming About Travel: A Pinterest Netnography." In Information and Communication Technologies in Tourism 2021. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65785-7_23.
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AbstractOngoing travel information search remains under-examined in general, and specifically in terms of social media use. Understanding how visual social media platforms inspire travel dreams is increasingly pertinent as visual contents gain in importance. This is especially relevant when travel is restricted, such as during the COVID-19 pandemic. Pinterest seems to be ideally suited for supporting ongoing search but has been rarely used as a data source in e-tourism research. This paper uses a netnographic approach to explore travel-related Pinterest data. From a methodological perspective, it finds that the platform is suitable for informing ongoing travel information search research but points to potential methodological challenges. As a theoretical contribution, it highlights the popularity of capturing travel dreams through Pinterest boards and illustrates the affective labor users put into their collections of travel dreams. The paper concludes with implications for tourism marketing and recommender system design.
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He, JinLu, IlYoung Choi, and JaeKyeong Kim. "A Group Travel Recommender System Based on Collaborative Filtering and Group Approximate Constraint Satisfaction." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39512-4_179.
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Kiritbhai, Katira Madhuri, and Ripal Ranpara. "A Comprehensive Comparative Analysis of Artificial Intelligence-Based Recommender System Algorithms for Enhancing Travel Search Experience." In Algorithms for Intelligent Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4533-3_17.
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Braunhofer, Matthias, and Francesco Ricci. "Contextual Information Elicitation in Travel Recommender Systems." In Information and Communication Technologies in Tourism 2016. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28231-2_42.
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Logesh, R., and V. Subramaniyaswamy. "Exploring Hybrid Recommender Systems for Personalized Travel Applications." In Cognitive Informatics and Soft Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0617-4_52.
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Teklemicael, Feben, Yong Zhang, Yongji Wu, Yanshen Yin, and Chunxiao Xing. "Toward Gamified Personality Acquisition in Travel Recommender Systems." In Human Centered Computing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31854-7_34.
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Erbil, Elif, and Wolfgang Wörndl. "Personalization of Multi-day Round Trip Itineraries According to Travelers’ Preferences." In Information and Communication Technologies in Tourism 2022. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94751-4_17.
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AbstractTravel planning is a long and tedious process for tourists since it requires processing a vast amount of information. Recommender systems can be used to facilitate the process of scoring points-of-interests (POIs) according to the travelers’ interests and creating feasible itineraries. However, itinerary planning is personal and each itinerary created must reflect the interest of the traveler as well as his/her travel style. In this paper, we extend the creation of multi-day round trip itineraries by adding different personalization options such as the pace of the traveler and diversity level of the route. The information about the travel style of the user is used to personalize the visiting duration of each POI and to create routes for each day that follow the constraints defined by users. We conducted a user study through a mobile application and the results show that the added personalization options improved the recommended multi-day round trip walking tours from a user’s perspective.
Conference papers on the topic "Travel recommender system"
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Narendran, Advik, Anantha Hothri, Manyam Yashaswini, Srinidhi Sundaram, and K. Aiswariya Milan. "Personalized Travel Itinerary Recommender System using Tkinter and SQLite." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725832.
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Pereira, Rickson Simioni, Claudio Di Sipio, Martina De Sanctis, and Ludovico Iovino. "On the Need for Configurable Travel Recommender Systems: A Systematic Mapping Study." In 2024 50th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). IEEE, 2024. https://doi.org/10.1109/seaa64295.2024.00057.
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Clark, Jeffery Caleb, Boyd A. Laurent, Joshua F. Addis, and James Williams. "Development of Application Friendly Products for Wet Gas Corrosion Inhibition." In CORROSION 2017. NACE International, 2017. https://doi.org/10.5006/c2017-09519.
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Abstract An operator in North America discovered an internal corrosion failure in a wet gas system directly below the point of injection of a water-soluble corrosion inhibitor (CI). Upon further investigation, an inconsistency was found between the standard laboratory based carbon steel immersion corrosion rate of the neat water-soluble corrosion inhibitor and the observed corrosion rate based on the field time to failure. For this reason, studies were conducted to uncover the discrepancy between the laboratory compatibility test and the observed field corrosion rate in a wet gas system. Tests using low shear rotating cage autoclaves were performed as a corrosion screening method of the neat CI. Additionally, it was desired to ensure that the product would travel with the gas and provide corrosion inhibition throughout the entire system. As a result, an additional study was conducted using a dual autoclave system to study the ability of the product to travel with a stream of gas, effectively inhibiting the entire gas system. Using these findings from the corrosivity evaluation and the CI transport studies, criteria for CI qualification in gas systems are recommended as best practices.
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Khosravi, Arash, and Ahmad Azarnik. "Optimizing Multi-Criteria Recommender Systems for the Travel and Tourism Sector: A Hybrid Approach Using ANFIS and Particle Swarm Optimization." In 2024 10th International Conference on Signal Processing and Intelligent Systems (ICSPIS). IEEE, 2024. https://doi.org/10.1109/icspis65223.2024.10931075.
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Son, Adelina J. "Pitfalls in Monitoring Sweet Corrosion Inhibition Using Residual Analysis Techniques." In CORROSION 2004. NACE International, 2004. https://doi.org/10.5006/c2004-04373.
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Abstract The use of analytical techniques to monitor the level of corrosion inhibitors is widespread in the industry. Residual chemical analysis, either qualitative or quantitative, yields information that relate to the corrosion protection in the system. The residual methods have the advantage of speed, sensitivity, ease of setup and low cost and can be excellent tools provided that the field and laboratory personnel understand the limitations. The accuracy of a chemical analysis is as good as the sample submitted; hence, samples must be representative of the system being monitored. The use of residual analysis for monitoring of sweet corrosion and recommended guidelines for the analysts to achieve the accuracy and precision of the analysis are discussed in the paper. Field case histories involving equipment leaks in gas/condensate production systems with sweet corrosion problems are presented in the paper. In one case, the cause of the leaks was traced to changes in the field conditions that impacted the performance of the corrosion inhibitor being monitored by residual analysis. In the other system, the leak in the pipeline occurred in an elbow. The mechanical configuration of the pipeline, variable high and turbulent velocity flows, solids carried by the fluids promoted corrosion-erosion processes in some areas. In both situations, the applicability of the chemical inhibitors and the analytical procedures to the changes in the field conditions was reviewed and the appropriate program revision put in place.
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Lorenzi, Fabiana, Stanley Loh, and Mara Abel. "PersonalTour: A Recommender System for Travel Packages." In 2011 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). IEEE, 2011. http://dx.doi.org/10.1109/wi-iat.2011.69.
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Chelcea, Sergiu, George Gallais, and Brigitte Trousse. "A personalized recommender system for travel information." In the 1st French-speaking conference. ACM Press, 2004. http://dx.doi.org/10.1145/1050873.1050905.
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Lan, Jian, Runfeng Shi, Ye Cao, and Jiancheng Lv. "Knowledge Graph-based Conversational Recommender System in Travel." In 2022 International Joint Conference on Neural Networks (IJCNN). IEEE, 2022. http://dx.doi.org/10.1109/ijcnn55064.2022.9892176.
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Renjith, Shini, and C. Anjali. "A personalized mobile travel recommender system using hybrid algorithm." In 2014 First International Conference on Computational Systems and Communications (ICCSC). IEEE, 2014. http://dx.doi.org/10.1109/compsc.2014.7032612.
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Ahmad Sabri, Ily Amalina, Noor Maizura Mohamad Noor, Noraida Haji Ali, and Fathilah Ismail. "A PERSONALIZED TRAVEL RECOMMENDER SYSTEM USING FUZZY ANALYTIC HIERARCHY PROCESS." In GLOBAL TOURISM CONFERENCE 2021. PENERBIT UMT, 2021. http://dx.doi.org/10.46754/gtc.2021.11.011.
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Information and communication technologies have deep implications for the tourism industry. This combination of devices is being used extensively in an excessive variety of functions and numerous applications. On the other hand, tourism has become an extremely dynamic system. The globalisation enabled by technological development and budget travel has greatly increased competition. Decision support systems (DSS) can play an important role within organisations and assist people who manage tourist destinations. The main intention of this research paper is to see how to apply Decision Support Systems (DSS) to the tourism industry. It aims to establish a personalised interactive travel recommender system that can be shared and integrated easily in order to work as a proof of concept for the decision to provide the tourism sector with interactive decision support systems. Specifically, the study aims to achieve the following objectives which are to evaluate and measure criteria and alternatives to performance, to analyse the ranking of criteria and alternatives and to recommend tourist attractions in terms of islands, accommodation, activities and etc. based on the travellers’ budget constraints. The evaluation module enables experts to evaluate and consider alternatives to the small islands to benchmark the islands’ performance. An analysis module will provide reports for performance of criteria and alternatives based on a “Best Non-fuzzy Performance” basis. A risk analysis model for the travel recommender system using a fuzzy set approach has been proposed and incorporated into a Fuzzy Decision Support System (FDSS). This study presents fuzzy-AHP as a proposed method to apply to decision-making with social attributes. A web-based prototype Decision Support System (DSS) has been designed and developed in order to prove the objectives.
Reports on the topic "Travel recommender system"
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Eggleston, Karen N. Evidence-Based Public–Private Collaboration in the Health Sector: The Potential for Collaborative Governance to Contribute to Economic Recovery from COVID-19 in Asia. Asian Development Bank, 2023. http://dx.doi.org/10.22617/wps230027-2.
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This South Asia Working Paper explores the benefits and trade-offs of harnessing private sector health services as governments look to build more resilient, accessible, and affordable health systems and support the post-pandemic recovery. It considers why governments must continuously decide whether to produce or buy-in services, analyzes how public-private collaborations can bolster the social sector, and explores how these helped governments respond to the pandemic and its aftermath. Outlining the role ADB can play, the paper recommends governments adopt an evidence-based approach, encourage private sector involvement in healthcare provision, and bolster collaborative governance to strengthen their health systems.
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Reeb, Tyler D., and Stacey Park. Trade and Transportation Talent Pipeline Blueprints: Building UniversityIndustry Talent Pipelines in Colleges of Continuing and Professional Education. Mineta Transportation Institute, 2023. http://dx.doi.org/10.31979/mti.2023.2144.
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The rapid adoption of transformational technologies along with other economic and cultural shifts, have created a gap between workers and the skills and knowledge necessary for in-demand occupations. Trade and Transportation Talent Pipeline Blueprints: Building University-Industry Talent Pipelines in Colleges of Continuing and Professional Education identifies the steps required to build talent pipelines that target in-demand trade and transportation occupations requiring specific degrees, certificates, and non-credit professional development. This report provides a literature review and labor market data analysis. It also includes documentation of methodology in planning a pilot program for Colleges of Professional and Continuing Education housed within each of the 23 California State University campuses. The recommendations guide the colleges to develop talent pipelines to empower trade and transportation employers to play a more central role in addressing skills gaps and other critical workforce development needs in working partnerships with postsecondary education and training providers. The report concludes with a recommended university-industry Intelligent Transportation Systems (ITS) Talent Pipeline pilot program.
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Hynd, David, Caroline Wallbank, Jonathan Kent, et al. Costs and Benefits of Electronic Stability Control in Selected G20 Countries. TRL, 2020. http://dx.doi.org/10.58446/lsrg3377.
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This report, commissioned by Bloomberg Philanthropies, finds that 42,000 lives could be saved and 150,000 serious injuries prevented by 2030 if all new cars in seven G20 countries were required to be equipped with an inexpensive crash avoidance technology starting in 2020. Thirteen G20 counties currently adhere to United Nations regulations on electronic stability control (ESC). If the seven remaining countries—Argentina, Brazil, China, India, Indonesia, Mexico and South Africa—also mandated ESC in 2020, the report estimates $21.5 billion in economic benefit to those countries from the prevention of deaths and serious injuries. Argentina and Brazil are due to start applying ESC regulations in 2020. The UK-based Transport Research Laboratory (TRL) conducted the independent study of costs and benefits of applying ESC regulation in G20 countries, which are responsible for 98% of the world’s passenger car production. This report comes before the 3rd Ministerial Conference on Road Safety in Stockholm, which is the largest gathering of governments and is a key opportunity for adoption of this UN-recommended standard. According to the World Health Organization’s Global Road Safety Report, the number of road traffic deaths reached 1.35 million in 2016. Of all vehicle safety features, electronic stability control is regarded as the most important one for crash avoidance since it is 38% effective in reducing the number of deaths in loss-of-control collisions. ESC tries to prevent skidding and loss of control in cases of over-steering and under-steering. The technology continuously monitors a vehicle’s direction of travel, steering wheel angle and the speed at which the individual wheels are rotating. If there is a mismatch between the intended direction of travel and the actual direction of travel, as indicated by the steering wheel position, ESC will selectively apply the brakes and modulate the engine power to keep the vehicle traveling along the intended path. The cost of implementing ESC on vehicles that already contain anti-lock braking systems is thought to be as little as $50 per car. And the report finds the benefits are significant: For every dollar spent by consumers in purchasing vehicles with these technologies, there is a US$2.80 return in economic benefit to society because of the deaths and serious injuries avoided. The analysis warns that without regulation of ESC, the seven remaining G20 countries will only reach 44% installation of ESC by 2030. However, if all seven countries implemented ESC regulations this year, 85% of the total car fleet in G20 countries will have ESC by 2030, a figure still below the United Nations target of 100% ESC fleet coverage by 2030.
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Fossong, Derrick, and Ashu Mc Moi Ndi. Digital Tax Policy and Tax Revenue Collection in Cameroon. Institute of Development Studies, 2023. http://dx.doi.org/10.19088/ictd.2023.060.
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Cameroon adopted a digital tax policy some eight years ago. Before full implementation of the digital tax policy in 2016, councils in Cameroon, especially local councils, reported many challenges due to delays and irregularities in central government revenue-sharing (shared taxes). The direct taxes and fees collected by the councils were felt to be low, given the effort needed to collect them. It is important to understand whether adoption of the digital tax policy has increased the much-needed tax revenue for local council projects, and enhanced general tax revenue. General tax revenue refers to compulsory transfers to the central government for public purposes, and is made up of resource rent, direct and indirect taxes, and trade taxes. This study examines the impact of the digital tax policy on tax revenue collection in Cameroon using quarterly data from 2010 to 2021, employing an autoregressive distributed lag (ARDL) estimation technique. The results reveal that the digital tax policy put in place in 2016 had a positive and significant long-term impact on general tax revenue, but a negative and significant short-term impact on general tax revenue. The impact was positive but insignificant on council tax revenue in both the long and short term. Findings indicate that full positive gains from the digital tax policy in Cameroon have not yet been achieved due to local constraints in rural areas. Based on our findings, we recommend that business owners should be trained to use the online declaration and payment system. This will improve ease of use, reduce dependence on agents, and boost collection of general and council tax revenue.