Progress in information technology and tourism management: 20 years on and 10 years after the Internet—The state of eTourism research

This paper reviews the published articles on eTourism in the past 20 years. Using a wide variety of sources, mainly in the tourism literature, this paper comprehensively reviews and analyzes prior studies in the context of Internet applications to Tourism. The paper also projects future developments in eTourism and demonstrates critical changes that will influence the tourism industry structure. A major contribution of this paper is its overview of the research and development efforts that have been endeavoured in the field, and the challenges that tourism researchers are, and will be, facing

Referencial para a caracterização de websites de hotéis de acordo com as necessidades dos consumidores

Online presence is essential for tourism organisations, and the quality of websites can influence customers. In the case of hotels, there are many studies to evaluate website performance based on functionality, usability and other factors, much less on the amount of different information available to the consumer. In the near future by using Big Data it is expected that hotel websites will be dynamic, they will adapt themselves on-the-fly, showing personalized information to each consumer. Different consumers will have different websites (information? available) from the same hotel. This paper presents a framework for the characterisation of hotel websites, focusing on the amount of information available to the consumer in each website, which was applied in a case study during the last months of 2013 to the websites of five-star hotels that operate in the tourist region of the Algarve, Portugal. The framework allowed to identify a set of exhaustive indicators for hotel website characterisation, which were then grouped into ten fundamental information dimensions. These dimensions further fell into four dimension groups. Finally, it is presented and discussed quantitative and qualitative evaluations, that illustrates which indicators and dimensions are more often considered on hotel websites to satisfy the consumer?s information needs

A context aware recommender system for tourism with ambient intelligence

Recommender system (RS) holds a significant place in the area of the tourism sector. The major factor of trip planning is selecting relevant Points of Interest (PoI) from tourism domain. The RS system supposed to collect information from user behaviors, personality, preferences and other contextual information. This work is mainly focused on user’s personality, preferences and analyzing user psychological traits. The work is intended to improve the user profile modeling, exposing relationship between user personality and PoI categories and find the solution in constraint satisfaction programming (CSP). It is proposed the architecture according to ambient intelligence perspective to allow the best possible tourist place to the end-user. The key development of this RS is representing the model in CSP and optimizing the problem. We implemented our system in Minizinc solver with domain restrictions represented by user preferences. The CSP allowed user preferences to guide the system toward finding the optimal solutions; RESUMO O sistema de recomendação (RS) detém um lugar significativo na área do sector do turismo. O principal fator do planeamento de viagens é selecionar pontos de interesse relevantes (PoI) do domínio do turismo. O sistema de recomendação (SR) deve recolher informações de comportamentos, personalidade, preferências e outras informações contextuais do utilizador. Este trabalho centra-se principalmente na personalidade, preferências do utilizador e na análise de traços fisiológicos do utilizador. O trabalho tem como objetivo melhorar a modelação do perfil do utilizador, expondo a relação entre a personalidade deste e as categorias dos POI, assim como encontrar uma solução com programação por restrições (CSP). Propõe-se a arquitetura de acordo com a perspetiva do ambiente inteligente para conseguir o melhor lugar turístico possível para o utilizador final. A principal contribuição deste SR é representar o modelo como CSP e tratá-lo como problema de otimização. Implementámos o nosso sistema com o solucionador em Minizinc com restrições de domínio representadas pelas preferências dos utilizadores. O CSP permitiu que as preferências dos utilizadores guiassem o sistema para encontrar as soluções ideais

Context-based Grouping and Recommendation in MANETs

International audienceWe propose in this chapter a context grouping mechanism for context distribution over MANETs. Context distribution is becoming a key aspect for successful context-aware applications in mobile and ubiquitous computing environments. Such applications need, for adaptation purposes, context information that is acquired by multiple context sensors distributed over the environment. Nevertheless, applications are not interested in all available context information. Context distribution mechanisms have to cope with the dynamicity that characterizes MANETs and also prevent context information to be delivered to nodes (and applications) that are not interested in it. Our grouping mechanism organizes the distribution of context information in groups whose definition is context based: each context group is defined based on a criteria set (e.g. the shared location and interest) and has a dissemination set, which controls the information that can be shared in the group. We propose a personalized and dynamic way of defining and joining groups by providing a lattice-based classification and recommendation mechanism that analyzes the interrelations between groups and users, and recommend new groups to users, based on the interests and preferences of the user

Application of Big Data in Tourism Destination Management: A Case Study of Changsha City

In the era of information technology, the utilization of big data technology is rapidly growing, leading to significant changes in the tourism industry. Big data not only creates more business opportunities for the industry but also drives the transformation and enhancement of tourist destinations and the implementation of efficient management. This study employs two research methods: literature review and case analysis. Firstly, by reviewing relevant literature, the latest research findings and trends in big data technology for tourism destination management are summarized. Secondly, through case analysis, a comprehensive understanding of the current situation and challenges in the application of big data technology in tourism destination management in Changsha is obtained. Leveraging the Changsha cultural and tourism data platform, this study retrieves information such as tourist reception data of tourism destinations in Changsha and assesses the impact of Changsha’s big data technology on tourism destination management. The research reveals limitations and challenges in the application of big data technology in Changsha’s tourism destination management, including data privacy protection and technical security, which require further exploration in future practices. The goal of this study is to offer insights for the application of big data in tourism destination management in Changsha and provide guidance for destination managers in similar cities

Markets for Information: An Introduction

We survey a recent and growing literature on markets for information. We offer a comprehensive view of information markets through an integrated model of consumers, information intermediaries, and firms. The model embeds a large set of applications ranging from sponsored search advertising to credit scores to information sharing among competitors. We then review a mechanism design approach to selling information in greater detail. We distinguish between ex ante sales of information (the buyer acquires an information structure) and ex post sales (the buyer pays for specific realizations). We relate this distinction to the different products that brokers, advertisers, and publishers use to trade consumer information online. We discuss the endogenous limits to the trade of information that derive from its potential adverse use for consumers. Finally, we revisit the role of recommender systems and artificial intelligence systems as markets for indirect information

Approaching Future Customer using Technological Advance in Hotel Industry

The purpose of the paper is to draw attention to the technological advance and its impact on marketing strategies in the hospitality industry. It examines the development of the profile of future consumers and their relationship towards technology. In order to approach the new consumer a brand touch-point wheel framework was used as a filter which enabled to analyze the communication between hotels and their guests as a process. The role of the model is to identify and explore all situations where organizations have the opportunity to influence consumer decision-making through technological innovation. Moreover it aims to evaluate effectiveness and potential of each digital channel for hospitability establishments and highlights their impact on consumer behavior. The research results show that attracting today’s consumer requires using a wide range of online media, social networks and mobile applications that work in a relationship involving all brand touch-points. Most importantly, aligning the marketing strategy properly with the corporate brand strategy through an integrated multi-channel campaign creates a sustainable competitive advantage. Each hotel may have different digital marketing strategy, however when a compelling message is sent, engaging the customer throughout the communication process, as a result, customer will identify with the brand, create an emotional connection and become loyal in a long run