Handbook of e-Tourism

More and more aspects of our life “move” to the Web. The Web and the Internet, as the underlying information infrastructure, cannot only be considered as a mirror of the “real” physical world; it is increasingly hard to distinguish between the physical and the virtual. The Web, however, is not only reflecting and “operating” this world, it is obviously also transforming it. Information technology (IT) acts both as an enabler and as driver of technical, economic, and societal developments. One can even speak of a coevolution of humans and machines. With recent achievements in areas such as computational models, Internet of things, or artificial intelligence, we see the power of informatics. Moreover, from an ontological point of view, informatics influences how we perceive the world, how we think about it.This chapter starts by highlighting the historic importance of technology to growth and development. In the following, it intertwines two lines of thought: as informatics forms the technical and methodological basis of e-tourism, it reviews the nature of informatics as a scientific discipline, its methodological roots, and its importance, both for applications and for science. This is then related to the e-tourism domain, its history, development, and possible future. But most importantly: while informatics offers many positive prospects and possibilities, its development raises at the same time serious issues with respect to society, economy, politics, or the individual. Thus, the chapter concludes with a reference to our responsibility as scientists and to the Vienna Manifesto on Digital Humanism.

This chapter reviews e-tourism development across three areas: suppliers, tourists, and educational needs. Regarding suppliers, the adoption of information and communication technology (ICT) begins with simplifying operational procedures, increasing employee productivity and enhancing information retrieval. Tourism managers rely on ICT and data to carry out management tasks such as promoting products online, making strategic decisions, monitoring customer satisfaction and product customization, and maintaining a sustainable business environment. Application systems within the tourism ecosystem should be interconnected and interoperable to form a smart network. An intelligent environment enables smart networks with high-speed data exchange and autonomy services. From the tourist perspective, ICT significantly changes tourists’ trip decision-making process and behavior. Destination choice and travel product information are available online without time delays or any geographical or language barriers. Multimedia and 3D virtual images expand the information richness and facilitate co-created travel experiences. Social media allow tourists to share their trip experiences with friends and relatives in real time and express their feedback about travel products on easily accessible review sites. To address employers’ and future employees’ needs, the university must revise the tourism education curricula with a significant inclusion of the ICT component to ensure students will be equipped with the necessary ICT skills in areas such as data analysis, scenario interpretation, robot management, and artificial intelligence (AI) applications

e-Tourism takes advantage of ICT innovations to improve internal efficiency, establish efficient communication and distribution links with various intermediaries, and engage in conversation and service cocreation with customers. Technology-empowered tourism experiences have been supporting travellers to cocreate value throughout all stages of travel, before –during–after travel. The first proprietary information systems supported tourism and hospitality organizations to centralize and manage their inventory as well as manage their internal processes. The rapid development of the Internet since 1995 revolutionized technological solutions and information provision. Organizations developed their Web 1.0 presence as a window to the world and their websites as e-commerce shops. The Web 2.0 and the social media revolutionized interactivity between users and also between users and organizations. Smart tourism, Web 3.0, or the semantic web bring a range of opportunities that optimize the entire network and support the tourism ecosystem. The development of smart mobile devices rapidly emerged as a new agile flexible network and challenged desktop computing. Finally, ambient intelligence (AmI) tourism takes advantage of smart systems and brings ambient intelligence across tourism ecosystems. The Internet of Everything supports the development of sensitive, flexible, and adaptive ecosystems. Ambient intelligence connects all stakeholders and supports the constant formation of networks to bring value to all stakeholders.

The growing importance of information and communication technology (ICT) in tourism is widely acknowledged, resulting in a growing body of research on e-Tourism. This chapter presents a comprehensive review of the status of e-Tourism research and its topics based on 752 articles collected from 14 tourism and hospitality journals, which are indexed in the Web of Science (WoS) database. Publication trends regarding e-Tourism, contributing countries/territories, and changes in knowledge basis of scientific disciplines are presented as an overview of e-Tourism research. This is followed by a clustering approach based on bibliographic coupling (BC) similarity between each article to reveal salient topics (and subtopics) as well as their relatedness. Interpretations based on quantitative results and qualitative insights are provided. Complemented with domain knowledge and literature evidence, insights are presented to show possible future research directions, which would benefit both novice and experienced researchers and those who are considering e-Tourism as a research focus.

Disciplines have traditionally been the building blocks of knowledge production, especially in higher education. In recent times though, more flexible approaches to production of knowledge beyond disciplines, in the context of application, and with the subject or topic as the starting point have become more popular and no less impactful. Such post-disciplinary approaches to tourism studies have been advocated and in evidence for over a decade. Set against this backdrop, this chapter argues that e-tourism is a field of study that has emerged from, and is best understood in its own right as, post-disciplinary enquiry. The differences between inter-, multi-, and post-disciplinary approaches are explained in the chapter which also examines three ways in which post-disciplinary approaches may be recognized in, and contribute to, the e-tourism body of knowledge. Far from just another esoteric concept, viewing e-tourism in this manner suggests that its emergence is a story of synthesis and eschewing disciplines, it cannot and will not advance as far and as quickly if more restrictive approaches are taken, and that e-tourism is one of the few fields in tourism studies to turn towards the physical sciences for new knowledge production.

Tourism scholars have extensively investigated tourists’ behavior; from motivations to actual choices and consumption patterns, the way tourists behave has relevant implications for theory and practice. In e-Tourism, consumer behavior encompasses the wide range of tourists’ behaviors supported by technologies and happens at different stages: prior undertaking a vacation, during the experience itself, and after it, when tourists are engaged in post-vacation assessments. Research on these aspects is vast, encompassing both the supply and demand side, but it remains scattered. This chapter provides an informed overview of consumer behavior in the e-Tourism era. The core of the chapter focuses on three phases of consumer behavior that have significantly been reshaped by e-Tourism: pre-trip stage, on-site experience, and post-trip evaluation. These three relevant areas are herein analyzed, and considering the tourists and providers’ perspective, the most relevant changes enabled by the e-Tourism era are presented. The conclusion section discusses the relevance of behavioral changes induced by digitally mediated experiences, outlines advances, and presents future perspectives for tourism and hospitality.

The tourism industry is driven by data. Digitization means efficiency and thus cost savings. The tourism industry, as a highly fragmented and complex worldwide industry, has a strong need for data coordination in order to produce and distribute bundles of travel services to customers. Due to their cost structures and the complex process of organizing worldwide transportation in real time, airlines were the first main drivers of digitalization in the travel industry. In Germany, the leisure market was initiated and first driven by state-dominated companies, but subsequently, a significant change in actors and global dependencies can be seen over the course of time. Until today, the recurring themes in the different stages of digitalization are communication formats and the power of various market actors. This has led to a standardization of data exchange formats between various data systems that allows data to be distributed efficiently worldwide and business processes to be completed in real time. This article includes the perspectives of three interview partners who helped shape the development of the German leisure market. It will be shown how the players and drivers of digitization have changed over time but that the key drivers have stayed the same: cost efficiency, data quality, and technical development.

In the current technological paradigm, the functioning of the tourism sector cannot be explained without the process of digitalization. This process takes on special relevance in tourism economics due to two issues: on the one hand, tourism is a highly dependent and sensitive sector to innovation, especially on the demand side; and on the other, it is a sector with little innovative capacity due to its business structure. This changing reality requires the reconsideration and even the reinterpretation of some principles of tourism economics. In this chapter, starting from a comprehensive literature review, five of these principles are analyzed: the development of a new demand, changes in the value chain of tourist supply, pricing with almost perfect information, the labor market in the tourism sector and the challenge of automation, and finally the evolution of destinations in terms of intelligence, sustainability, and accessibility. This is intended to shed light on the transformation that the tourism sector is currently experiencing in digital terms and to anticipate the change that new disruptive technologies, especially artificial intelligence, will continue to create.

E-Tourism started with the first automated airline computer reservation systems (CRS) implemented on mainframes. With the global spread of data transmission networks, they evolved to global distribution systems (GDS), which serve as B2B touristic distribution backbones until today. The seamless integration of heterogeneous data networks into the Internet and the invention of the World Wide Web as a distributed multimedia application platform led to the development of comfortable Internet/web booking engines. They enabled easy-to-use browser-based online booking as a self-service for customers and new forms of B2C travel distribution. Because the Internet and the WWW became the base technologies of all E-Tourism applications, their architecture and components are explained in detail as key enablers for online booking and CRS-Web-Front ends.

Since its invention in 1989, the World Wide Web was extended with many advanced web technologies like XML, Web services, AJAX, JSON, HTML5, etc. They are enablers for innovations like mash-ups, responsive web design, web-enabled mobile apps, or augmented reality apps, which are building blocks for complex E-Tourism applications with many special use cases: Dynamic packaging engines are platforms for virtual/online tour operators. Content management systems evolved as core technology for travel communities, blogs, online advertising, and social media. Travel portals with Internet booking engines serve direct sales of travel suppliers and online travel agents. Online booking engines introduced self-service even for corporate/business travel management. Travel search engines offer direct price and product comparisons and search engine marketing. Destination management systems support service bundling, while mobile web apps innovated tourist guidance.

Web information retrieval and search deals with the information provisioning and information search on the World Wide Web. It is used by tourists to find information about, e.g., worldwide touristic services. The chapter starts with an introduction into information retrieval (IR) and the specifics of IR in the tourism domain where it is argued that not only information but real touristic services are searched for which requires also higher trust into found services and information. Further, the basics of IR in local information systems such as a generic retrieval model, indexing, retrieval functions, the relevance of found objects, and the evaluation of IR systems are described.For a large distributed information system as the Web with mostly unstructured or semi-structured content, specialized techniques such as crawling, automated indexing, text mining, computation of the relevance of objects, the ranking of results, and an extended architecture are described. Additionally, user profiling to achieve better matches for seekers is addressed. Web user behavior, Web site optimization, and keyword advertisement as technologies for marketing are included, as well as location-based services.Further, approaches to extract and transform semi-structured data into structured data, deep Web, as well as metasearch, i.e., searching over distributed structured information resources and aggregating search results, are described. Finally, crowd-based approaches such as social tagging to evaluate the quality and relevance of Web resources by users are presented and an outlook into trends is given.

More and more people are using smartphones and other mobile devices as their main means for information access. This is especially true for travelers, and mobile applications supporting them have become very popular in the last years. This chapter first introduces basic concepts and technologies that are important for mobile applications for e-Tourism. After a brief historical overview, we then discuss issues regarding the development of mobile applications, such as determining the context of users with sensors. We also explain basic principles of user modeling and personalization and mobile user interfaces. The second main part of the chapter classifies and outlines existing mobile applications for travel and tourism. We introduce a taxonomy that reflects a traveler’s journey from vacation planning until concluding the trip. This includes applications that assist users in finding destinations; searching for and booking hotels, events, and activities; and identifying other travel-related items. A more specific scenario is the search for points of interest (POIs) that a user can visit during a trip. Modern e-Tourism applications allow browsing and filtering relevant POIs and can combine them to interesting and practical itineraries. In addition, we present applications for social networking, entertainment in e-Tourism, and others that are frequently used by tourists.

The introduction of mobile information services to the tourism domain has represented a radical change in the way tourists plan, enjoy, and reflect on their travel experience. The Internet of Things promises to represent the next big advancement. This corresponds to the possibility of distributing small pieces of interconnected technology in the environment and within objects for a more pervasive monitoring and personalization of how the tourism experience is consumed and for the creation of an extended interaction interface that supports a more direct engagement with the destination and its facilities, products, and services. For the tourism sector, these advancements open up novel scenarios of ubiquitous computing, for example, smart shop windows, digitally augmented showcases for handicrafts display, augmented itineraries that engage visitors with other means than smartphones and tablets for a more immersive experience, personalized souvenirs and smart gadgets, stationary information kiosks that automatically identify their users, mobile applications that are aware of which products, and places the tourist has already been in contact with. This chapter provides an overview of the enlarged ubiquitous computing capabilities enabled by the IoT technologies and illustrates possible applications in the tourism domain.

The perception of touristic space is constantly changing, and today physical and virtual spaces are interwoven due to new technological developments. Virtual Reality, Augmented Reality, and Mixed Reality are opening a new paradigm, receiving increasing interest from marketers and consumers alike. These technologies provide huge opportunities by enhancing customer engagement in a highly interactive way, which leads to an enhanced customer experience and new marketing approaches for innovative players in the tourism industry. The terms, definitions, and boundaries between these technologies are however blurred and not well defined. This chapter therefore tries to clarify key concepts by unraveling the subtleties behind the different terms which are often used interchangeably. After reading this chapter, the reader will arrive at a clearer understanding of the different concepts, their technological background and characteristics as well as possible fields of application within the tourism industry. Several best practice scenarios illustrate the potential, opportunities, chances, and risks of these immersive technologies. The chapter ends with discussing further prospects when it comes to technological developments and alternative application fields.

Electronic data interchange (EDI) is the application-to-application exchange of business-related data between different organizations based on a structured machine-readable format. In this chapter, we will outline the concepts of EDI and its relevance for tourism. Thereby, we first introduce the UN/EDIFACT standards which were the first ones to be used for EDI. Since this book targets IT in tourism, we next describe the standards of the Open Travel Alliance (OTA) which are most commonly used to realize EDI exchanges in the tourism domain today. In order to realize an EDI partnership between organizations, it is also critical to define how the messages are delivered from the message sender to the message receiver. Since service providers are commonly involved in EDI message exchanges, we will have a closer look on their services and explain how these services facilitate EDI partnerships. In particular, we discuss WebEDI which specifically targets small and medium enterprises (SMEs). Finally, we provide a list of critical issues that have to be met in any EDI project.

Smart speakers such as Alexa and later Google Home have introduced Artificial Intelligence (AI) into millions, soon to be billions of households, making AI an everyday experience. These new communication channels present a new challenge for successful e-Marketing and e-Commerce providers. Data, content, and services are becoming semantically annotated, allowing software agents, so-called bots, to search through the web and understand its content. Nowadays, users typically consult their bot to find, aggregate, and personalize information and to reserve, book, or buy products and services. As a consequence, it is becoming increasingly important for touristic providers of information, products, and services to be prominently visible in these new online channels to ensure their future economic maturity. In our chapter, we survey the methods and tools helping to achieve these goals. The core aim is the development and application of machine-processable (semantic) annotations of content, data, and services, as well as their aggregation in large Knowledge Graphs. It is only through these methods bots are able to answer a question in a knowledgeable way and organize a useful dialogue (Knowledge Graphs in Use A significantly extended and generalized version of this article will appear as D. Fensel, K. Angele, E. Huaman, E. Kärle, O. Panasiuk, U. Şimşek, I. Toma, J. Umbrich, and A. Wahler: Knowledge Graphs: Methodology, Tools and Selected Use Cases. Springer Nature, 2020.).

Big Data has emerged as a new technological paradigm during the last few years, because of the need to master the occurring exponential growth of data. Big Data technologies offer toolboxes in the form of frameworks that deal with the data explosion created by the ever-growing number of applications, mobile devices, sensors, and the Internet of Things (IoT) in conjunction with the wish to have a better overview, receive answers to questions, and measure behavior and operational complexity of today’s systems.Big Data refers to large datasets and dataflows whose processing lays beyond the capabilities of traditional information systems and databases. Information like log files, images, messages, transaction records from remote or local application databases, composite distributed data structures, sensor data from remote devices, data from public databases, and IoT devices can be used selectively to enrich existing data to provide clear operational insight and support the recognition of trends and tendencies.Very often, data generated in social media applications are used to measure or extend the impact of specific Internet campaigns for products and services. Big Data is the toolkit that targets the infamous “three Vs” of data, which comprise the three basic characteristics: volume, velocity, and variety.This chapter will explain the basic definitions of Big Data components, provide a list of the technologies used and vendors involved, and show how the 3 Vs can be applied on hand of application examples in tourism.

Thanks to more powerful hardware and a new generation of learning algorithms, artificial intelligence is supporting the automation of a number of tasks and activities that are changing the job landscape as much as they have impacted on our everyday life. The first part of the chapter introduces artificial intelligence from its origins: its definition and its main research and application areas. The nature and the importance of machine learning for artificial intelligence applications are presented in the second part of the chapter. Existing approaches to machine learning are also classified and illustrated. The third part describes artificial intelligence tools and solutions by supported functionalities and automated tasks. Cases of applications in tourism are provided, from the best known and widely adopted, e.g., personal assistants, to the most challenging, i.e., semantic systems. Future trends and risks related to the applications of artificial intelligence are considered in the last part of the chapter.

Recommender systems (RSs) are information search and filtering tools that provide suggestions for items to be of use to a user. They are now common in many Internet applications (Google News, Amazon, TripAdvisor), helping users to make better choices while searching for news, books, or vacations. RSs exploit data mining and information retrieval techniques to predict to what extent an item fits the user needs and wants. RSs interact with the user to fine-tune these suggestions while presenting a selection of the items, among those having the largest predicted fit score. RSs have been used in tourism applications for suggesting points of interest to visit, holiday properties, and flights, or even generating complete plans for holidays, that is, bundling different types of more elementary items (e.g., accommodations and events) in one recommendation bundle.In this chapter, we will first introduce basic recommender systems principles and techniques. We will discuss the general functioning of a recommender system and how various techniques are used to implement the model components. We will then present important key dimensions for recommender systems especially considering the travel and tourism application scenario. We will close this chapter by discussing some limitations and open challenges for recommender systems research.

Blockchain technology has the potential to substantially transform the tourism industry. Its salient features such as immutability, transparency, programmability, and decentralization allow for innovative ways to design customer relationships, enable novel organizational structures and processes, and facilitate new forms of interorganizational collaboration. In this chapter, I first elaborate on the basic functioning of the blockchain and highlight those characteristics which are crucial for understanding the rest of the chapter. I not only equip scholars and practitioners with the knowledge needed to better comprehend blockchain technology and how to apply it in the context of the tourism industry but also highlight shortcomings and important research topics. Furthermore, I investigate the disruptive potential of the blockchain on an economic level by discussing various ways in which it can alter existing market structures und potentially lead to the disintermediation of incumbents in the tourism industry and the emergence of new players. Economic theory is referenced to better understand how blockchain characteristics might shape the future of the tourism industry and who the main beneficiaries will be. I end the chapter with several suggestions for future research and expected future developments.

Business intelligence encompasses all activities dealing with collecting, storing/managing, and analyzing business-relevant data with the objective of generating knowledge as input to decision support. Business intelligence is often used as an umbrella term for data warehousing, reporting and OLAP (online analytical processing), MIS/DSS, and data mining, respectively.If we count all topics listed above, it is obvious that business intelligence has quite a long history also in the tourism domain. As early examples in tourism, we can identify the DINAMO system introduced by American Airlines already in 1988 or TourMIS in 1998.The widespread use of ICT, especially the uptake of the Internet and social media, led to an increase of available data on customers, competitors, and the whole market in all major business domains, including tourism. More powerful hardware and sophisticated methods to store and analyze such data turned business intelligence into one of the fastest-growing technologies and most challenging areas in the last decade.This chapter gives an overview on the topic of business intelligence and all technical components of a BI architecture (i.e., information extraction and transformation, data warehousing, and different mechanisms and tools to access and analyze data, like reporting or OLAP tools, dashboards, or data mining toolsets). Moreover, the chapter looks at the history of BI in tourism and presents and discusses typical application scenarios in tourism. Finally, we look at current trends and latest developments in the area of business intelligence and their expected implications for the tourism domain.

Computers and devices, today ubiquitous in our daily life, foster the generation of vast amounts of data. Turning data into information and knowledge is the core of data mining and predictive analytics. Data mining uses machine learning, statistics, data visualization, databases, and other computer science methods to find patterns in data and extract knowledge from information. While data mining is usually associated with causal-explanatory statistical modeling, predictive analytics is associated with empirical prediction modeling, including the assessment of the quality of the prediction. This chapter intends to offer the readers, even those unfamiliar with this topic, a general overview of the key concepts and potential applications of data mining and predictive analytics and to help them to successfully apply e-tourism concepts in their research projects. As such, the chapter presents the fundamentals and common definitions of/in data mining and predictive analytics, including the types of problems to which it can be applied and the most common methods and techniques employed. The chapter also explains what is known as the life cycle of data mining and predictive analytics projects, describing the tasks that compose the most widely employed process model, both for industry and academia: the Cross-Industry Standard Process for Data Mining, CRISP-DM.

In the past decade, the rise of social media, the proliferation of user-generated content (UGC), and, consequently, the effect of electronic word-of-mouth (eWoM) have revolutionized marketing. In tourism, and hospitality, traveler-generated content (TGC), including travel blogs and especially online travel reviews (OTRs), has become a prominent source of information. OTRs hosted on travel-related websites collect information about visitors’ experiences, opinions, and appraisals of places, attractions, activities, products, and services that allows measuring visitors’ perceived image, satisfaction and loyalty. The aim of this chapter is to describe a computerized content analysis of OTRs, from data collection and content analysis. To illustrate the most basic procedures, this study examined a sample of English-language OTRs from TripAdvisor about attractions and activities in Barcelona, Catalonia, between August 17 and December 31, 2017, a period characterized by a terrorist attack and an unrelated independence movement. The results show that serious events had a minimal impact on the city’s image as perceived and shared by reviewers, despite the enormous amount of media coverage of both events.

This chapter provides an introduction to network science and its applications within e-tourism research. In the first part, an overview of network science as a continuously growing scientific field is given. Network science provides various concepts and methods for the analysis of the structure and dynamics of all kinds of networks such as social networks, information networks, and economic networks. Afterward, popular software and tools to model, analyze, and visualize network data are briefly discussed. In the third part, an overview of research in e-tourism that utilized network science methods is provided. In existing studies, different types of networks were constructed and analyzed, in particular networks of travelers, networks of tourism websites, networks capturing behavioral patterns of travelers, or text networks of travel-related posts. Furthermore, it is briefly discussed, which data sources are typically used in the literature. Finally, the main points are summarized and conclusions are drawn.

Along with the growing availability of geospatial data generated with information and communications technologies, spatial analytics and data visualization have prevailed in e-tourism research. This chapter systematically reviews the application of spatial analytics and data visualization in tourism. Specifically, the chapter discusses various exploratory analytics, such as spatial network analysis, spatial clustering, point pattern analysis, ESDA, and sequence analysis, and explanatory analytics, such as spatial interaction model, spatial econometrics, and geographically weighted regression. Some popular geovisualization methods are discussed with examples of their e-tourism applications. Lastly, the chapter discusses several major challenges of spatial analytics and geovisualization, including tourist identification, temporal angle in addition to the spatial analysis, computation burden, and web-based GIS applications.

Tourism scholars are increasingly turning to web-based platforms to conduct e-tourism research. The availability of crowdsourcing websites (e.g., Amazon Mechanical Turk or “MTurk”) has made a range of research approaches, including survey and experimental investigations, more efficient. When used to analyze social media data, human intelligence – an essential component of crowdsourcing research – can also help researchers tackle issues unsolvable through automation or machine learning, such as text and image annotation. However, compared to other domains (e.g., social science, computer science), within e-tourism, crowdsourcing research has not yet been fully leveraged as a scientific method. It is argued herein that, in order to move the field forward, e-tourism scholars must better grasp the unique and dynamic structure and principles of crowdsourcing research. This chapter reviews and synthesizes the relevant literature, proposing a set of building blocks upon which crowdsourcing research may be structured, that is, a crowd of participants, crowdsourcing platforms, and research types. Further, it offers seven guidelines to inform e-tourism crowdsourcing research practice: determining research types, choosing crowdsourcing platforms, defining crowdsourced populations, recruiting participants, managing crowds, handling ethical issues, and reporting.

Design has received increasing attention in the field of tourism research and practice. A number of researchers have pointed out how design as an approach to innovation might benefit the development of digitally enhanced tourism products and services. The central and prevailing view of design in tourism relies on an understanding of design as a rational problem-solving activity, fundamentally devoid of creative judgment and largely decoupled from the situated and embodied context of organizations, creative design practice, and the enactment and use of products in the lifeworld of people. I thus argue that design in tourism research has tended to be aligned with the modernist legacy of Herbert Simon’s account of design as a largely cognitivist and rationalizing practice and tends to maintain a view on design grounded in scientific and managerial discourses. In this chapter, I suggest how such approaches to design in tourism research are potentially limiting the development of innovative practices. The conceptual underpinnings of design in tourism make it challenging to reflect on alternative accounts or conceptualizations of design based within the humanities and anthropology and could impede the construction of a more pluralist engagement with design. The paper reflects on accounts and activities in tourism research that involve designerly work, particularly focusing on the design of digital experience products and services in tourism. It problematizes the modernist decision science legacy of design thinking and design science approaches and suggests how tourism as a research field might usefully extend its vocabulary and conceptual grasp on design. Design is more than a science, and this chapter ultimately suggests some directions that go beyond the currently dominant rationalizing and science-based positions. Based on emerging understandings of speculative design and as a material and highly situated practice, the chapter outlines alternative conceptualizations of design. The chapter suggests positions and approaches that can work to facilitate a broader view and a more reflective practice of design in tourism. The chapter proceeds as a “think piece,” reflecting on two distinct legacies of and approaches to design. One is broadly rationalistic and solution-oriented, borne out of a desire to practice design as a science, and the other is a speculative approach that treats design as a critical, situated, and reflective practice of “studying” the future and the intricate consequences of innovation.

Log files record invaluable information about the operational details of applications, database management systems, operating systems, and devices. They are autogenerated “diaries” that keep timelines of all data reflecting every event that took place during the operation of the system. Every web site visitor request and the corresponding responses is registered in an access log file, generated by the web server. Access log files keep the entire operational history. Publicly accessible web applications and e-commerce sites that operate 24 h a day, 7 days a week are exposed to the global Internet community. Analyzing the log file is not only crucial for security reasons but also for assessing the community of visitors, gaining insight into their operational habits, knowing their requests, measuring response times, spotting implementation errors, and locating problems of all levels.This chapter starts with a description that shows how to configure and customize a web server, in order to produce a useful access log file, and describes conceptually various software compositions that will constitute contemporary web analytics applications that deal with log files, inventory and customer data, a hybrid application combining log files and tagging system data, near real-time extensions, and social media aware applications that support data streams and provide a more global image of the way a web application is approached by visitors. The impact and the implications of the technology paradigm shift toward rich Internet applications (RIAs) on web analytics applications in Web 3.0 are taken into consideration, and remedies that solve the reduced log file problem are proposed.

In this chapter, we focus on the case of e-tourism websites (also known as Travel 2.0 tools or T2T, such as travel blogs, profiles on social networks, and online travel communities) and measure the effectiveness of advertising banners on these sites. To do this, we propose a methodological approach known as VIROG, video-based infrared oculography, or infrared eye-tracking technology. This technique is applied here in a practical application to track subjects’ visual attention when exposed to three different e-tourism websites. To date, marketing scholars have paid very little attention to analyzing the moderating effect of customer engagement (CE) or ad type when measuring visual attention and recall for a certain banner.To achieve objectives of the practical application, a within-subject and between-group experimental design was applied on a sample of participants, using their eye-tracking data in addition to a self-administered questionnaire. Based on variables of visual attention and cognitive processing, results of this study reveal the following: (i) no banner blindness was identified for any of e-tourism websites under analysis, and the greatest advertising efficacy of all sites tested was achieved by Facebook; (ii) post hoc measurements of recall were explained by other gaze metrics related to advertising effectiveness (such as number of fixation or duration of the visit); and (iii) the level of CE and the degree of animation of the particular banner exerted a moderating effect on the relationship between attention and recall or memory.

In this chapter, we will present the iterative user-centered design process as an adaptive and agile life cycle for open innovation and successful development of socio-technical systems. The user acceptance and usability of the technical system are central to the design process, which determines how to proceed at several stages of designing and evaluating. Besides an overview of the most accepted and well-established methods of design thinking, which are based on user-centered design principles and presented also in tables for easy accessibility, we will describe cultural probes, provocative requisites, design games, design workshops, sketches, wireframes, mockups, low- and high-fidelity prototypes, as well as technology probes in detail. This will enable, on the one hand, an understanding of the methods by different stakeholders in multidisciplinary project teams and, on the other hand, a base for deciding which methods and approaches are suitable for a specific phase or type of a project.

For well over a decade, e-tourism researchers have been using netnography. Yet despite this use, netnography has thus far been under-utilized. Big data methods still predominate as a way to understand social media content, obscuring the potential for a more humanistic and meaning-rich understanding. This chapter is about netnography, a way to research social media that is flexible, contextualized, and enthusiastically agnostic about the type of data. Netnography has been developed as a way to study social media that maintains the cultural complexities of people’s experiences. This chapter introduces the reader to the rigorous practice of netnography as it exists today. Then, it contrasts netnographic methods and insights with those provided by big data analysis approaches. Finally, it uses examples and illustration to explore key territories and implications of netnographic research to the understanding sought by e-tourism researchers, including electronic word of mouth, online reviews, online communities, selfies, and other travel and tourism-related phenomena.

Digital consumers rely on smartphones and the mobile Internet for different tasks in their daily lives. Travel activities as an essential part of life for many people are greatly supported by a variety of connected mobile devices. In turn, these mobile devices and applications capture the digital footprint of tourists, which reflects their behaviors, preferences, and intentions. As a result, mobile ethnography has emerged as a valid and insightful method for researching tourist behavior. Mobile ethnography is distinct from classical ethnography in terms of data collection tools and procedures. Researchers collect data captured by mobile devices to understand the behavior of targeted groups, and participants can share insightful information such as their locations, photos, videos, and data points that indicate their emotions with the researchers. Mobile ethnography provides researchers with a variety of new tools and instruments to capture tourists’ behaviors and opinions from multiple perspectives. This chapter introduces the concept of mobile ethnography, the tools and instruments for data collection and analysis, and the applications of mobile ethnography in tourism and hospitality research. This chapter also discusses the opportunities and challenges such as ethical and privacy concerns in mobile ethnography research.

Tourism researchers have been using experimental design for many years. Although e-tourism studies are well documented in the literature, their trend and rigor remain unknown. Therefore, this review critically analyzed corresponding publications by focusing on five major aspects, namely, article characteristics, research design, sample characteristics, data analysis, and advanced technology used to assist experiments. A total of 50 articles consisting of 60 studies were analyzed after a thorough literature review. Findings revealed that experimental design has been recently gaining popularity in e-tourism research, featuring the use of advanced technology to assist manipulation in experiments. Future e-tourism experimental research should have diversified disciplinary foci, conduct multidisciplinary studies in various contexts, avoid excessive independent variables in a study, perform manipulation checks, report effect sizes, and increase the examination of psychological mechanisms using mediation analysis.

This chapter provides a collection, review, and summary of 20 years of website evaluation studies in hospitality and tourism by adapting a scientometrics approach and content analysis. Seventy-four research articles related to travel website evaluation from 1996 to 2019 were collected from Web of Science, and the collected studies were categorized into four groups based on the methods that the articles employed for website evaluation: analysis of consumer and practitioner views; mathematical evaluation; software automated evaluation; and manual computation. The chapter shows that over the last two decades, website evaluation methods and research priorities have changed: early website evaluation studies focused more on features, functions, and the content of the traditional provider website, and recent studies have focused more on the richness of website content and interaction with users or compare the content of different types of websites. The chapter provides a comprehensive overview and summary of existing methods for evaluating tourism-related websites, serving as an important reference for the future development of tourism websites and related research topics.

The topic of user modelling (UM) in the context of e-tourism needs to be approached from a human-computer interaction perspective. E-tourism as a continuously booming domain is heavily dependent on ICT, from the early eras when online booking became available to the full-fledged mobile tourism applications of today. User modelling is a means to overcome the “one-size-fits-all” strategies which were not appropriate or satisfactory neither for the provider nor for the customer. This chapter enumerates different dimensions of UM approaches, such as emulating vs. complementing the user, implicit vs. explicit data collection, as well as stages of technical maturity, and also provides a retrospective view on the different evolutionary developments of UM from static to highly adaptive and hybrid models. The history of user modelling is characterized by an excessive focus on basic algorithms and business logic (adaptiveness), and a lack of attention to the customer’s front-end user experience (adaptability). To address this issue, the chapter emphasizes the relevance of human-computer interaction (HCI) in the context of user modelling and e-tourism, by describing key concepts such as user experience and exemplary methods like personas. The chapter concludes with a discussion and an outlook on future developments. Specifically, the potentials of segmented personal user models are mentioned, which are owned by the user (instead of the provider) and allow for exchanging only those parts of the user model in a customer-specific way that are needed in an actual interaction.

Market segmentation is a well-established and commonly used concept in tourism. Businesses and destinations benefit from a segmentation strategy because it allows them to focus on a clearly defined subset of consumers which they are best suited to serve, thus developing a long-term competitive advantage. Traditionally, segmentation strategies were built on results from the analysis of on-off cross-sectional survey data sets. Such data sets have a number of disadvantages, including being quickly outdated and biased due to consumer self-reporting. The availability of different kinds of data and the close-to-continuous stream of such data offer new powerful opportunities for market segmentation to be further refined and improved. This chapter discusses the process of market segmentation analysis, highlights the weaknesses of the traditional approach, and points to the future of market segmentation which will leverage new data sources to create knowledge and derive better industry market insights.

The tourism experience has always been closely linked to visual communication and photography. Travelers like to bring home visual proofs of their journey or keep visual memories of what they have experienced. The convergence of digital cameras with mobile and networked communication has had a profound impact on visual practices in the tourism domain. This has increased, for instance, the number, relevance, and uses of user-generated visuals. Today’s travelers, the “unsung armies of semiotics,” represent and co-construct tourism experiences by capturing and sharing photographs online. Consequently, visual representations play an instrumental role in the creation of the image of a destination, attraction, or experience – sometimes providing a different view than the one suggested by official channels.Acknowledging the crucial role that visuals play as means or ends, and their importance for researchers as well as practitioners, this chapter is concerned with how to examine the increasing number of visuals and of visual data that is produced by both official sources, like destination marketing/management organization (DMO) websites, and nonofficial sources, such as user-generated content (UGCs) on social media. The first part of the chapter gives a brief overview of methods of visual analysis for the examination (1) of small sets of images (iconographic and semiotic analysis), (2) of larger sets of visual data (quantitative visual analysis), and (3) mixed approaches. The second part of the chapter focuses on the use of visuals for research processes, with emphasis on the potentials of using (1) visuals in interviews (visual elicitation), (2) visitor-employed photography (VEP), and (3) visual-sorting tasks. Future directions in visual tourism research are discussed at the end.

Compositional Data (CoDa) contain information about the relative importance of parts of a whole, which the researcher deems more interesting than overall size or volume. In web mining, for instance, the relative frequency of a term is normally given more importance than absolute frequency, which mostly tells about web size, in other words, the sheer volume of online content. Many research questions in e-tourism are either related to the distribution of a whole or relative importance: How do the most salient contents in hotel Facebook accounts relate to hotel characteristics? What are the dominant topics on TripAdvisorTripAdvisor comments about fish freshness in seafood restaurants? How does the relative popularity of search terms in Google relate to destination market share?In CoDa, most of the basic statistical notions, such as center, variation, association, and distance, are flawed unless they are re-expressed by means of logarithms of ratios. The appeal of log-ratios is that once they are computed, standard statistical methods can be used. On the other hand, since one part can only increase in relative terms if some other(s) decrease, statistics need to be multivariate.This chapter uses an example based on TripAdvisor hotel reviews from one of the most visited cities worldwide, Barcelona, focusing on what users complain about, to illustrate the main multivariate exploratory and descriptive tools in CoDa, including imputation of zeros prior to computing the log-ratios, multivariate outlier detection, principal component analysis, cluster analysis, and multivariate data visualization tools. The use of CoDaPack, a popular CoDa freeware, is described in a step-by-step fashion.

Information search has long been considered one of the most important aspects of the travel decision-making process. This is because the tourism product (i.e., the travel experience) is intangible, complex, and generally evokes a range of emotional responses; additionally, information search for available opportunities of different experiences may occur at all stages of the trip; finally, comparison of one’s experiences one might have while visiting various destinations is extremely difficult. Therefore, research on travel information search is important for tourism marketing and management which requires providing the right information about the right place at the right time. Today’s information technology has the capabilities not only to connect travelers to the right products but also to make the search process personally relevant, inspirational, fun, and enjoyable. This chapter reviews the foundational tourism literature including several widely cited models on travel information search. Then, it discusses the nature and characteristics of online information search and examines the emerging conditions that may have significant impact on this behavior. Finally, it discusses the directions for future research and implications for tourism marketing.

Designing (group) recommender systems in the travel and tourism domain is a difficult task, considering the complexity and intangibility of a tourism product, i.e., (i) it is a bundle of products and services; (ii) it is an emotional experience; (iii) it is difficult to characterize users’ travel-related preferences explicitly (especially in the early phase of the travel decision-making process); and, finally, (iv) traveling is usually a group activity. Therefore, to support travel-related group decision-making process and to suggest appropriate items introduce new challenges into the overall picture. In comparison to individual decision-making and recommendations, when a group of people is faced with a decision task, group dynamics comes to play. In fact, group members’ preferences are usually not so uniform; thus a conflict might arise. In a group discussion, opinion shift might occur due to group members’ influence on each other by exchanging experiences, information, preferences, etc. Moreover, emotional contagion is a phenomenon that explains how satisfaction/dissatisfaction of one member might contaminate the others in the group. All of these group behavioral aspects are greatly affected by group members’ individual personalities and their intragroup relationships. In this chapter, we provide an overview of the research done in the field of group decision-making, group recommender systems, and group personalization in the travel and tourism domain.

The field of eTourism research encompasses a plethora of research on users’ adoption and acceptance of technologies. As a multidimensional phenomenon, an in-depth understanding of eTourism technology acceptance requires crossing the boundaries of tourism and hospitality, information and communication technologies, and marketing. Taking such a multidisciplinary approach enables researchers to integrate knowledge from the broader disciplines of psychology, sociology, and economics to construct a deep understanding of users’ behavior. However, while there have been some recent advances in broadening the horizons of research in this field, the majority of eTourism technology acceptance research relies on a few classical technology acceptance and consumer behavior theories. This chapter presents a summarized overview of the most important determinants of technology acceptance behavior and critically reviews most influential theoretical models that have been used as the foundation of the majority of existing research in this field. Subsequently, some major areas of theoretical and empirical gaps in our understanding of eTourism technology acceptance will be discussed to provide researchers with a pathway towards further expanding the boundaries of research in this field. This chapter assists emerging researchers in this field to gain an overall understanding of the progress of research so far. It also directs emerging researchers towards developing alternative research agendas to diversify the theoretical foundations of eTourism technology acceptance research and expand the boundaries of knowledge in this field beyond the status quo.

Virtual, augmented, and mixed reality are technologies that are slated to significantly transform tourism experiences in the next few years. Although these technologies have been around for quite some time, they have only recently appeared to be ready for mainstream adoption and able to provide a high-quality substitutive experience (in the case of virtual reality) and a good augmentation of the experience (in the case of augmented reality). In this chapter, we first review how these technologies can be used in the different stages of travel, as a complement to and augmentation for a travel process. We then review how they can be used to substitute the tourism experience, allowing tourists to enjoy an experience without travelling. We end with a discussion of the main gaps, their impact on the tourism and travel sector, and expected future developments.

User experience and design are central factors in information and communication technologies, determining the use and success of adoption of any tourism application. These issues are tackled within the so-called “usability” tests, which provide multiple ways of investigating whether an application is usable to visitors within specific contexts of interest. With the aim of providing both tourism scholars and practitioners with an original overview on the topic of usability, this book chapter will take the case of augmented reality (AR) applications from an online communication perspective. First, we provide an overview on usability analysis and web analytics, also illustrating how data from actual uses can provide information on the risks involved with the use of an application. Second, we present a collection of AR studies, positioning them in relationship with usability analysis and related challenges. Lastly, future research trends, including the concept of gamification and replayability, are outlined in the conclusion.

The intangible characteristics of tourism services may cause concern for travel risks and anxiety to trip planners. In order to reduce uncertainty, an increasing number of trip planners are reading experiences shared by other travelers online. Notably, user-generated content (UGC) is considered more trustworthy than information provided by tourism providers. However, a rise in fake and sponsored online content makes travelers question the trustworthiness of UGC. As many factors account for evaluating the credibility of UGC, past E-tourism studies have aimed to identify the drivers, antecedents, and consequences of trust in UGC. This chapter offers a comprehensive literature review of past research on trust in E-tourism, focusing on UGC. We synthesize theories and frameworks used and discuss major concepts of trust as they relate to information and communication technology in tourism. This review of the literature shows that research in this area has made substantial progress but has not reached its level of maturity yet. Finally, the chapter suggests future directions for research in this area.

This chapter offers a conceptual discussion of smart tourists by firstly addressing the complex concept of intelligence. The multiple meanings of this term and the implied links to smart tourists are used to broaden the frame of reference for much of what has been discussed in previous specific ICT work. The work then examines the meaning of intelligence and smartness in a tourism context and suggests the value of key topics and strategies to shape intelligent tourist desires that are congruent with sustainability and local needs. Five broad ranging topics are considered: economic levers for intelligent action, building intelligence through extended destination contact prior to and post-holidays, intelligent and usable technology filters for shaping on-site action, enhanced use of tourist zone design to create specific use of space, and the reconstitution and representation of an intelligent social position for the tourist role. Select case studies from a global research agenda will illustrate key points. The concept “intelligent tourist,” one linked to but beyond the smart tourist, needs to be viewed not as an oxymoron, but as a pleonasm.

Travelers and tourists nowadays rely on a variety of online services or mobile apps for planning their trips, for making travel arrangements, and for making the choice between touristic offers during the trip. Prominent types of applications are hotel search and booking sites, travel planning applications, and in particular recommender systems. Academic research is often concerned with algorithmic aspects of such systems, e.g., by proposing techniques that find optimal routes or making recommendations based on long-term preference models. In the tourism domain, however, such systems must often be highly interactive, e.g., to let users state and revise their preferences in an incremental way. In many cases, the system also has to take the user’s context (e.g., their location) into account to make meaningful recommendations. In this chapter we first briefly review typical interactive e-tourism applications and then focus on the class of interactive and context-aware recommender systems. In that context, we will survey previous approaches to interactive recommendation in the tourism domain and then highlight open questions and outline future directions in the area.

The impact of information and communication technologies (ICTs) on firms’ strategic development and value creation has been a topic of academic debate for decades. Tourism is no exception. This chapter provides a synthesis of the literature on the strategic decision to adopt and use ICTs as well as an analysis of their impact on the value creation of tourism firms. We reflect on theoretical frameworks and analytical concepts developed and validated by tourism scholars, their implications for ICT use, and the factors affecting the realization of ICT-enhanced business value. Problems of measurement, analysis, and organizational adjustments appear as major factors behind volatile ICT productivity in tourism, known as the ICT Productivity Paradox. To ensure the realization of ICT-enhanced business value, various adjustment strategies, including the development of firms’ capabilities, cultures, and organizational structures, are addressed. The discussion section critically assesses the reviewed literature on the strategic use of ICTs in tourism. Finally, the conclusion deduces research needs and sketches an agenda for future research.

Information and communication technologies are major drivers of change. Also in tourism, businesses and entire destinations have to find new business models to stay competitive and relevant. Utilizing the possibilities of digital technologies in developing new business models is called digital transformation. This chapter examines what digital transformation in tourism is and how technology affects leadership and management in tourism organizations. Digital transformation is conceptualized as a creative process activated by knowledge management and knowledge transfer which, in turn, aims at creating new business possibilities and models, respectively. By drawing on extensive literature on topics connected to digital transformation such as tourism management, leadership, knowledge and change management, as well as creativity, the chapter at hand discusses the current state of digital transformation management in tourism. A research outlook for the future of digital transformation management in tourism is finally proposed.

The purpose of this chapter is to reflect on business models employed by online travel service providers since the beginning of online travel until 2019. In lockstep with technological development, this study identified three time periods of development. For each period, we investigate cases that best represent e-business model development. Employing Wirtz’s four business-to-consumer business model subtypes, we found that the commerce-type model (focus on trade transactions) dominated online travel agencies until 2000, while the next period was characterized by the advent of Web 2.0-enabled content-type models (providing online content, specifically user-generated content) and context-type models (aggregation of already existing online content) for information search portals. Finally, the increased complexity of the Internet in the last decade is also captured in multiple online business models, including the connection-type model (establishing real or virtual connections) pursued by platform businesses. The chapter offers avenues for future research that relate to theoretical issues across the three identified periods and an outlook of future tourism business model developments.

This chapter provides an informed review of service management in the E-Tourism Era. The core of the chapter focuses on three aspects of service management that have significantly been reshaped with E-Tourism: customer-provider interaction, customer relationship management, and service recovery process. These three relevant areas are herein analyzed considering the changes, opportunities, and challenges enabled by the E-Tourism Era. The conclusions discuss the transformational and disruptive character of E-Tourism, present future perspectives for service management, and outline advances, shortcomings, and open questions for academia and industry.

This chapter discusses the challenges and opportunities destinations have when transforming their communication and marketing strategies in the social media world. Building on the principles of experience design for destinations, the chapter synergizes destination strategies with the principles of the emotional branding paradigm. Therefore, the chapter first elaborates on the theory of brand personality and its use for communicating destination brands on popular social media platforms. Furthermore, the chapter also elaborates on the concept of user engagementUser engagement in order to understand how destination brands can optimize online engagement with their audience. The combination of the aforementioned concepts leads to a better understanding of strategic opportunities for e-destination management. Through the presentation of common social media marketing practices among European Destination Management Organizations (DMOs), various critical lessons learned are provided. More specifically, DMOs’ Facebook and Twitter engagement are illustrated by analyzing their actual emotional brand communication strategies, user engagement metrics, and their overall activity. In doing so, an overall assessment is provided that includes a set of successful strategies as well as failing strategies that are important for DMOs to consider when opting to stay competitive.

Revenue management (RM) is a management philosophy based on systematic information analysis that aims at maximizing profit through effective price and inventory management. It is mainly applied in service businesses with fixed capacities, such as airlines, hotels, spas, etc. RM implies an analytical vision of management that affects the entire organization and is supported not only by scientific (statistics, mathematics, marketing) and technological advances but also by a radical change in traditional management theory. However, current RM is still based on a narrow inventory/price view without considering a key factor: the customer. In this regard, big data-based methods will provide the opportunity for more sophisticated discrimination and customer-based knowledge leading to a customer-centered vision which allows for lasting customer relationships and personalized pricing. Thus, it is necessary to conduct further research that updates theoretical RM concepts and practices that have evolved over time. The objective of this chapter is to offer a current revision of RM literature from both a strategic and a holistic perspective. This approach refers not only to the application of the flywheel model (marketing, sales, and revenue management) but to RM implementation in all income source departments in the hospitality industry. In addition, RM peculiarities in major tourist industries are outlined. Finally, an agenda of future RM research in tourism is proposed.

Supply chain management (SCM) was originally introduced in the early 1980s with the focus on increasing economic values in the manufacturing sector. The term has gained tremendous attention over the years. The rising focus on competitiveness and sustainability along with the fragmented nature of tourism represented as networked supply chains led to the novel perspective of tourism supply chain management (TSCM). Despite the popularity and benefits of SCM initiatives, enhanced supply chain performance has been hindered by the cost of communication and coordination among individual actors in each supply chain. Recent developments in information systems and technologies, however, have gained expectations that SCM performance will be enhanced. Research shows that information technology can enhance SCM performance by making real-time information available to the coordination process of the various supply chain actors. Therefore, e-SCM, defined as the use of information and communication technology to improve SCM operations, has been acknowledged as an outstanding topic in the supply chain literature. The purpose of this chapter is to analyze the interaction of TSCM and e-SCM. Moreover, the main contribution of this chapter is to show how research in e-SCM has evolved and to identify lines of future SCM research in the e-tourism domain.

Information and communication technologies have contributed significantly to the development and growth of the tourism industry. Tourists use the Internet in all phases of the customer journey. In 2020, the typical user spent on average 6 h and 43 min online each day, which was about 40% of their waking life. Mobile devices account for more than half of all the online time, but most Internet users still use a combination of mobiles and computers to access the Internet. Therefore, digital marketing offers great opportunities for tourism organizations and suppliers to promote and sell their offers and to establish long-lasting relationship with their customers. This chapter discusses the development of digital marketing in tourism and illustrates the evolution over various steps. A brief history of the development of digital marketing for tourism businesses and an outline of its benefits and challenges will be provided. This chapter focuses on website publishing, traffic building, and digital marketing campaign planning. Challenges and future developments of digital marketing conclude this chapter.

A geographic information system (GIS) is a computer-based information system using special tools to manage location-based data and their attributes for decision-making. Geospatial functions cut across many fields and support problem solving through geodata design and analysis. GIS have been used, for example, in environmental conservation and wildlife management. Its use in tourism planning, development and management, and marketing of destination products is only a more recent approach. The adoption of the technology affects both the sustainability of environmental resources and the quality of tourists’ experience. The purpose of this chapter is, first, to explore the functionalities and usage potentials of GIS in the tourism domain. Second, two studies of Maasai Mara Game Reserve and Nairobi National Park portray how GIS and satellite remote sensing imagery is applied to assess the ecosystem’s changes, their causes, and major implications. Examination of Landsat satellite image data for 2000 and 2017 shows that due to conversion of areas to farmlands and settlements, the coverage of Mau Forest Complex, the main catchment area for the Mara ecosystem, had reduced by 30.2% and vegetation by 22.8%. The analysis of Nairobi National Park showed that the Kitengela wildlife migration corridor has been completely encroached by human settlement and mining activities, thus seriously compromising the performance of the ecosystem. Mapping of human development pressure on the ecosystem using GIS technologies can be used to assess and manage the tourism resources potential in conjunction to biodiversity conservation as a critical element in improving wildlife as a tourism destination product.

Social media and mobile devices have changed how tourists’ experiences are created and the ways travelers and companies interact. Increasingly, multichannel and multimedia systems characterize the relationship between customers and companies. Travel companies face a more competitive environment, now influenced by new online actors, and they must improve their communication strategies to satisfy an increasingly demanding traveler who is more oriented to conversations than to simple interactions. Social media has contributed to a paradigm shift: from one-way communication to three-way communication. Companies employ different methods when attempting to optimize social media use and communicate with current and potential consumers. Various approaches could be identified: from simple methods that are disconnected from the corporate strategy to fully integrated approaches. By referring to mainstream literature, the chapter discusses and examines the approaches that travel and tourism companies may adopt with particular emphasis on utilizing fully integrated social media strategies which aim to learn from consumers and create customer engagement.

This chapter outlines the approach of Expedia Group, the world’s travel platform, and the role of technology in revolutionizing travel search, discovery, and booking. It covers innovations developed by online travel agencies (OTAs) and the unique challenges and opportunities provided by the breadth and depth of the data that global OTAs leverage to power travelers’ online experiences. The focus is on accommodation, the largest revenue-generating, and most complex tourism segment. The chapter explores specific use cases where data are brought together with leading and innovative machine learning methodologies to improve traveler and supplier experiences. They include recommender systems, machine learning models that help Expedia Group manage the text and image content for over a million properties and revenue management systems for accommodation providers. The chapter concludes with a comment on the Expedia Group COVID-19 response.

This chapter provides a comprehensive overview of information and communication technologies (ICTs) used by event organizers and attendees. The ways that ICTs are integrated into event administration, design, operations, marketing, and risk management, both back-stage and in plain sight, are considered from an applied perspective and through the lenses of theories applied in the literature. Currently, events and festivals use diverse ICTs to enhance utilitarian aspects, such as ticket purchasing, safety procedures, wayfinding and scheduling, as well as hedonic visitor experiences, like virtual and enhanced reality, gamification, and innovative programming using social media. How ICTs influence attendees’ experiences is discussed in-depth by exploring the contribution of ICTs to “communitas,” “liminality,” sense of place, mindfulness, memorableness, and co-creation. Throughout the chapter, both emerging and established ICTs are described, and real-world examples from festivals are provided to gain insights into the opportunities and drawbacks of ICTs in the event and festival domain. The chapter focuses on ICTs used during the festival experience. However, the importance of the pre- and post-event and festival experience is acknowledged as well.

The practice of meditative mindfulness as a process of bringing a certain quality of attention to moment-by-moment experiences is considered important in achieving subjective wellbeing. In the era of increasing digitization, a new trend in the use of technological devices and smartphone applications has arisen which aims to cultivate mindfulness in everyday lives. This trend holds important repercussions for the development of e-Tourism, especially in the context of managing and (co-)creating tourist experiences, as attention to and awareness of a present moment experience represent the pillars of mindfulness. Although there are several studies that discuss meditative mindfulness in the context of tourism, there are no clear directions on how to employ technology-assisted mindfulness in achieving specific business goals, such as to (co-)create tourist experiences. This chapter provides a comprehensive and critical review of technology-assisted mindfulness in the context of tourist experiences. To this end, it first elaborates upon the definition of meditative mindfulness. It, then, takes stock of research on technology-assisted mindfulness, discusses the scope for the co-creation of technology-assisted mindful tourist experiences, and analyses the antecedents of their integration into organizational practices of tourism and hospitality enterprises. Finally, the chapter outlines directions for future research.

It is often claimed that small- and medium-sized tourism enterprises have a limited innovation capacity. However, framed by innovation policies, public and private organizations assist with various kinds of innovation management. In recent years, a multitude of e-tools have been launched to effectively support businesses in their innovation processes. This chapter undertakes a qualitative analysis of 21 of these e-tools. More precisely, the chapter examines the digital software measures through two lenses. First, a categorization of the approaches shows that e-tools can support innovation in a variety of ways, with idea management tools, brainstorming/idea generation tools, idea sharing tools, networking tools, collaboration/crowdsourcing tools, open innovation tools, idea ranking and assessment tools, trendspotting/trend scouting tools, gamification tools, analysis tools and dashboards, etc. Thus, e-tools seem to accommodate tourism SMEs’ diverse development and creativity challenges well. Second, the chapter scrutinizes the phases of innovation and finds that the majority of the e-tools tend to support the planning, scoping, definition, and exploration phase, while later steps in the innovation processes are not as well covered by e-tools, including concept generation and early prototype iteration, evaluation, and refinement. The chapter concludes that further developments may refine and expand digital tools and that tourism SMEs may be receptive if the e-tools properly address operational conditions, such as financial constraints, seasonal fluctuations, and, most importantly, adaptability to collaborative usage settings.

Information and communication technologies (ICT) play an important role in every sector where information is the basis of the business. Tourism is no exception. Since the implementation of computerized reservation/global distribution systems to the advent of the Internet, the adoption of ICT solutions is an important arena to apply technological forecasting through “diffusion methods.” These methods help in the analysis of the temporal dimension of ICT adoptions, independent of whether adopters are persons or firms. Diffusion models are descriptive, as they yield a general understanding of the diffusion process, and predictive as their aim is to forecast diffusion patterns. In tourism, and specifically in e-tourism research, diffusion models have only received low to moderate interest. Thus, one of the aims of this chapter is to encourage research of innovations in ICT using this valuable tool. Innovation diffusion models are useful for the analysis of both the timing of the diffusion of an innovation inside a given population and of the dynamic of the same adoption pattern across different adopters’ populations. The chapter discusses major diffusion models (Rogers, Bass, logistics) and applies them on the adoption of Domain Name Registration (DNR) in the Web 1.0 era by the Swiss accommodation sectorsSwiss accommodation sectors. This chapter finally presents two cases. The first discusses the dynamics of DNR adoption by Swiss hotels controlled by hotels’ size and star categories. The second case analyzes differences in the adoption process across Swiss accommodation sectors, such as hotels affiliated to the Swiss Hotel Association (hotellerie-suisse), non-affiliated hotels, and guesthouses.

The chapter provides an overview of the literature investigating the sharing economy in tourism with the aim to identify what we already know and what we should further investigate about two major issues: (1) the multidimensionality of the sharing economy phenomenon and its impacts on tourism and its stakeholders and (2) the variety of the actors and the major issues pertaining their involvement in the sharing economy. By adopting an ecosystem approach, this chapter aims to contribute to the literature by providing a holistic multi-stakeholder, multidimensional, and multidisciplinary perspective of how we (should) understand and research the sharing economy in tourism. To achieve this, the chapter begins by clarifying the concept of the sharing economy and its overlaps with other related concepts such as gig, platform, collaborative, and peer-to-peer economy. This section concludes by developing a figure visualizing the four major sharing economy stakeholders, namely, platform; provider (i.e., micro-entrepreneurs, company, tourism gig worker) which includes the sub-economies of secondary entrepreneurs; seeker (e.g., tourist, seeker of resources); and environment/destination. The chapter continues by individual sections that each one discusses the research themes and gaps pertaining to each sharing actor and by concluding with ideas for future research.

Tourism has experienced quite relevant changes since when Information and Communication Technologies (ICTs), in all their forms, have started to permeate the society, the industry, and the markets. As an effect, a new concept has gained the attention of both researchers and practitioners, that of Digital Business Ecosystem (DBE). It arises from the deep interaction between the digital world and the ensemble of individuals and organizations that compose the complex domain of tourism and mainly for what concerns tourism destinations. Here we go beyond the known considerations on the important role of ICTs and show how the virtual and the real components are strongly coupled and co-evolve forming a single system. The conceptual framework used is that of complexity science and, in particular, the methods of network science. These allow to well assess both the structural and dynamic characteristics of these complex digital ecosystems. Several examples from the recent literature show how these methods have been applied so far and the validity of the outcomes, as, besides a pure academic interest, they can help in providing a deeper and better knowledge of the issues considered and can, thus, inform policy and governance activities. Moreover, the network approach allows the possibility to simulate structural changes, mainly on the virtual side, that can provide more suitable environments for improving or optimizing certain features of the system (e.g., attractiveness, innovativeness, etc.), crucial to provide a good basis for a sensible and harmonic tourism development.

The rapid development of information communication technologies and the diverse value co-creation processes are affecting and enhancing the interactive processes between actors in dynamic networks and e-tourism. To understand the conceptual development of value co-creation and how technology creates new opportunities to facilitate and enhance experiences within a tourism system, this chapter provides an overview of the literature aiding the understanding of co-creation in a context of dynamic networks and e-tourism. Co-creative processes for value creation are increasingly adopted to create and enhance engaging and meaningful service experiences, and complex tourism networks operate dynamically to facilitate the actor interactions, dialogue, and learning. Recognizing the significance of co-creation, the concluding integrative framework builds on the conceptual shift from service-dominant to customer-dominant logic promoting the central role of the customer in the value creation and tourism experience processes. Future developments are discussed in relation to the increasing and widespread use of ICT constituting e-tourism development, which is transforming the dynamic networks moving them toward digitally augmented smart interconnectivity and deeper value co-creation.

Companies increasingly use technology to track their customers, exploiting the resulting insights to tailor the customer experience and better targeted online marketing. Travel companies in particular collect substantial customer data, both in their booking processes and through loyalty/reward programs. This voluntarily surrendered data is increasingly being supplemented with highly granular data on browsing and physical behavior, collected automatically and surreptitiously by technology-based systems. When consolidated with existing sources, this can be analyzed to reveal insights hitherto considered personal, resulting in increased concerns about privacy. Legislative restrictions are increasingly being introduced to regulate privacy protection. This chapter examines the implication of such developments for travel companies and the industry globally. While alternative approaches are considered, it pays particular attention to Europe’s GDPR, highlighting areas of concern and identifying the steps travel companies need to make to insure compliance.

As the travel and tourism sector is embracing emerging technologies to redefine products, services, and consumer experiences, their cyber ecosystems become increasingly vulnerable to security risks related with these technologies, the huge amount of financial transactions they carry out, and the valuable customer data they store. Over the last few years, several high-profile organizations in the sector made negative headlines because they did not pay appropriate attention to these risks and took an approach to cybersecurity that was fragmented, technology-focused, and compliance-oriented. It is evident that a step change is needed, and this chapter presents a more comprehensive, business-driven, and risk-based approach to building cybersecurity capability in an organization. The chapter starts with the business case for a cybersecurity strategy and then unfolds the components of a risk-based approach to cybersecurity.

The chapter discusses the overlapping area between e-Government and tourism. It addresses the complex transition of governments from being completely offline to integrating information and communication technologies (ICTs). Their efforts range from improving the efficiency of their usual practices to changing their procedures (and approaches) in accordance with new media affordances. To do so, the chapter presents a map of six main e-Government relationships illustrated with examples from the tourism domain. These relationships are government-to-government (G2G); government-to-businesses (G2B); government-to-citizens (G2C); government-to-nonprofits (G2N); government-to-own-employees (G2E); and government-to-visitors (G2V). Furthermore, two cases are presented in depth to provide a better understanding of the complexity of e-Government support for tourism. Case one shows how an e-Government service (provision of public municipal Wi-Fi) can benefit tourism, while case two gives an overview of how governments include e-tourism-related interventions in their tourism management strategies. The chapter highlights the importance of the tourism sector for e-Government-related policies and practices, a relevance that is likely to grow in the future.

The role of ICT for sustainable tourism development is discussed in this chapter. The tourism industry is experiencing a sustainability crisis. Mounting evidence exists on the detrimental impacts created as a result of tourism activities such as overcrowding in destinations and accelerated production of carbon emissions. Research in sustainable tourism is mature, but challenges still exist in its operationalization and addressing the consequences of tourism on the economic, sociocultural, and natural environments. Therefore, it is critical that e-tourism researchers focus their attention on how ICT can be of critical significance in addressing sustainability issues. This chapter first examines the relationship between ICT and sustainable tourism and subsequently focuses on ICT role in sustainable tourism for destination planners, tourists, and local communities. The specific ICTs used by each of these aforementioned groups are expanded upon. Detailed attention is given to how destination planners can position ICT for achieving the sustainable development goals. The chapter concludes by looking at the critical success factors of the effective implementation of ICT for sustainable tourism development.

Information and communication technologies and tourism education have been going hand in hand in the last decades. Currently, it is a rich environment with numerous players, attractive offers, as well as varied training modalities and covered topics. This chapter presents the overlapping areas between tourism, education, and technologies. It will first introduce the context of e-learning and the main issues related to it while discussing the benefits e-learning brings to tourism education. It will also present how e-learning dimensions such as media and technologies, space and time, delivery scenarios, and trends can be leveraged within the tourism and hospitality sector. Numerous players in the domain, mostly belonging to the academic institutions and industry at large, together with their online training offer, will be extensively reviewed. Main academic studies about e-learning in the tourism domain will be discussed along. The chapter is concluded by discussing open challenges, emerging trends, and possible future developments.

The chapter examines the impact and role of technology on tourism curriculum, pedagogy, and assessment. The chapter starts by considering the importance of technology as a content area in the tourism curriculum. The discussion explores contemporary applications of technologies such as simulations, Massive Open Online Courses (MOOCs), and mobile learning and their impact on pedagogy. The discussion of assessment practice considers how technologies have provided learners and educators with new tools for assuring and verifying learning gains. Challenges, benefits, and future directions are highlighted throughout the chapter. Key themes across the chapter are brought together in the form of a future research agenda for educators and researchers. It is hoped that this chapter will help tourism academics and educators to make informed decisions about the adoption and integration of contemporary educational technologies in their own courses and institutions.

Accelerating levels of stress and chronic disease have urged travellers to seek products and experiences that promote a holistic healthy living. However, in the context of increasingly integrated online and offline experiences, where technology does not always work in concert with human nature, tourists are facing the challenge of finding about how to best live a connected life. With travel being one of the most stress-inducing experiences we voluntarily subject ourselves to, tourism players are taking advantage of the latest technology to respond to the travellers’ changing needs and values, by designing innovative experiences that promote overall well-being. This chapter provides a review of the existing research on well-being related to the travel and tourism sector, while focusing on the link with technology advancements, especially the dual perspective of unplugging and intense technology use. As in all great technological revolutions, the digital traveller’s life may potentially unveil a dark side. However, the general consensus is that the positives of using technology within the travel and tourism sector will continue to outweigh the negatives. The chapter focuses on highlighting the different types of technology used to support the traveller’s state of well-being, as well as the role and impact of technology in relation to well-being while travelling.

The goal of this chapter is twofold: Recent research work in the domain of e-Tourism curriculum design, development, and adjustment is explored and critically discussed. More importantly, necessary elements constituting the “state of the art” e-Tourism curriculum are presented. The book chapter is structured as follows: First, the often overlooked positions in the philosophy of education are outlined. After a short discussion of major tourism educational frameworks (Tribe 2002, 2015) and tourism curriculum models (Dredge et al. 2012), the Tourism Curriculum Framework proposed by Oktadiana and Chon (2016) is introduced. This framework serves in discussing prior research work on e-Tourism curriculum design and major e-Tourism curriculum initiatives. After emphasizing commonalities and omissions of analyzed studies, major elements constituting the IFITT (International Federation for IT and Travel & Tourism) e-Tourism curriculum are outlined. Finally, after illustrating research gaps, the conclusion section proposes an agenda for future research in the domain of e-Tourism curriculum design.

The nature of the contribution of tourism to local socio-economic development is subject to numerous debates, both by practitioners and academics. UNWTO declared 2017 the Year of Sustainable Tourism for Development, endorsing de facto the travel industry as one of the levers for socio-economic development. However, what is often missing within the general narrative about tourism for development is the crucial and central role of digital technology. Therefore, this chapter highlights the importance of digital technologies and, particularly, the role of e-tourism in emerging markets. It proposes a bottom-up vision of the role of information and communications technologies in travel as one of the key elements for rural community-based innovation and diversification toward active tourism delivery.

The digital revolution and the widespread use of information and communication technologies (ICT) have empowered information management to enhance the social and economic impacts of tourism worldwide. The digital divide is one of the competitiveness issues currently facing tourism organizations and destinations, affecting their capacity to interact effectively in a global tourism environment. Generally understood as a phenomenon of unequal distribution of information, the digital divide can lead to digital and social exclusion, as certain groups of tourists and destinations are unable to participate in the opportunities emerging from the use of the Internet and ICT. In this chapter, we discuss the two most important conceptual models used to interpret the digital divide and the barriers to tourism competitiveness it presents for different territorial areas, from the perspective of both supply and demand. Given that the digital divide has important implications for tourism organizations and destinations, we review the main indicators, tools, and instruments used to measure this phenomenon, as well as the strategies and recommendations employed to minimize it. Finally, we discuss new research approaches to the digital divide, especially those that focus on the link between digital technology, tourism inequalities, and connectivity.

The use of social media in the crisis communications process has grown tremendously in the past decade. Social media is now an integral part of the crisis management process. The evolution of the mobile phone and other mobile technologies, computers, Internet access, and digital video equipment is reshaping communication networks and the ways we connect with each other. This chapter defines crisis and crisis communication, explains the role of crisis communication for the tourism and hospitality industry, and details the challenges and opportunities of social media for crisis communication in tourism and hospitality.In addition, this chapter explores the latest literature on social media related to risk and crisis communication. A thorough review of academic literature, industry white papers, and trade publications was conducted. Using the insights from this literature review, this chapter provides implications of social media and crisis communication for the hospitality and tourism industry for each phase of a crisis (pre, during, post) and discusses recent developments in social media and technology that may affect crisis communication.

In tourism, biometrics have become a major technology application for user authentication in premises such as hotels and airports. The main reasons of utilizing biometrics for access control are convenience, high security, and reliability. Biometrics refer to any human trait, for instance, fingerprint, retina, palm print, and voice, which is used to establish an identity. It is already used extensively in many airports worldwide to facilitate automated identity verification, while the backbone is linked to police criminal databases, which enables identification of possible terrorists, victims of human trafficking, or tourists with past convictions. Additionally, many hotels have substituted traditional door locks or card access with biometrics for its convenience. However, there are some concerns associated with biometric applications, for instance, information privacy, physical privacy, and contamination fears. Tourists worry whether the storage mechanism of biometric data is safe from hacking and leakage to terrorist organizations. If biometric data were compromised, tourists would have to surrender different biometric identifiers because biometric features are irrevocable (permanent). Further, fear of contamination can be much more apparent on touch-based biometric applications such as fingerprint scanners. This concern is aggravated especially during pandemic outbreaks such as COVID-19, Ebola, and SARS. In a nutshell, this chapter aims to provide a holistic perspective on potential issues of biometrics in the tourism industry.

Simulations have long been used in business management generally and in the tourism and hospitality industry in particular. They have been employed in business planning, policy making, decision support, gaming, and, notably, with considerable success T&L. In addition, they have been developed to support planning and operations at the individual, enterprise, tourism destination, state, national, regional, and international levels. In short, there is hardly an area of the tourism and hospitality industry nor any category of involved party left untouched by the rapidly expanding array of simulations currently available. In this chapter, the history and range of tourism and hospitality simulations is reviewed, with an emphasis on those constructed using system dynamics and agent-based modelling approaches. In common with an increasing number of researchers, we believe that there is considerable advantage to be gained from a combined system dynamics and agent-based approach, and we present a detailed example of one such tourism T&L simulation game. The motivation behind the game’s development, the research approach (design science) that informed its development, design, construction, and validation are all discussed.

This chapter provides a comprehensive review of robotics in tourism and hospitality, including the technical foundations of robotics, synthesis of academic literature, and current and potential applications. Robots may be defined as programmable, intelligent devices, with a certain degree of autonomy, mobility, and sensory capabilities, designed to perform a certain task. Distinguishing between industrial and service robots, the chapter focuses on the category of service robots that perform useful tasks for humans in the tourism and hospitality industry. The chapter begins with the review of relevant studies and addresses both engineering and social sciences perspectives. The latter is evaluated deeper by looking at conceptual and empirical research. The chapter presents applications of robots across different segments of the tourism and hospitality industry, including hotels (e.g., front desk agents, concierges, delivery robots, porters, and housekeepers), restaurants (e.g., cook assistants, hosts, wait staff, food runners, bartenders, and robots delivering food), events (e.g., guest entertainment and physical presence for virtual attendees), attractions (e.g., museums), and travel (e.g., airports, autonomous vehicles). This book chapter investigates the issues related to robot adoption by tourism and hospitality companies from two perspectives: the supply- and the demand-side. From the supply-side perspective, the chapter evaluates the economics of robotics in tourism and hospitality, presents analysis of financial and non-financial costs and benefits, discusses employee resistance towards robotic labor, and outlines considerations for designing robot-friendly facilities. From a demand-side perspective, the chapter elaborates on customer attitudes towards the use of robots by tourism and hospitality companies, human-robot interaction, and customer willingness to pay for robot-delivered services. The chapter concludes by looking at future opportunities for robotization and research directions.

This chapter examines the question of whether future virtual reality (VR) experiences will be accepted as substitutes for real tourism experiences. It begins with an overview of the present state of VR technology and a vision of how future VR technology may further enhance the user experience. The chapter then summarizes the various benefits that VR tourism can provide (e.g., minimizing costs and hassles, providing limitless accessibility and opportunity, and eliminating negative environmental and social impacts), in addition to the limitations of VR tourism (e.g., technological restrictions, artificiality, and limited duration). It is argued that VR will not replace tourism entirely, but will be accepted as a substitute by some people for some tourism experiences. A substitution acceptance model is proposed that details the variables that will determine the likelihood of a VR experience being accepted as a substitute for a real-world tourism experience. These variables are divided into three categories – characteristics of the user, characteristics of the experience, and the quality of the VR experience. Lastly, various implications of VR tourism are explored.

This futuristic look at tourism aims to inform a tourism research agenda directed at the health and well-being of the tourism sector and at our earth’s natural and social ecosystems. The nexus between natural ecosystem changes and social ecosystem responses will demand tourism sector responses. This chapter is not designed to create an explicit tourism research agenda. Instead, it is suggestive and provocative, to promote researcher reflection around the forces within IT and forces from the outside, which will impact tourist destinations and attractions. It is time for tourism researchers to look beyond academia for research topics. While there is always scope for incremental advances in knowledge and practice in the traditional areas of IT and Tourism, it is also time for bold research initiatives. The tourism sector is facing a troika of disruptive forces. Climate change is reshaping destinations and attractions. Demographics, in terms of age distributions and a tsunami of climate change refugees, will impact both demand and supply capacity. Lastly, income and wealth concentration and societal responses will impact tourism and the roles played by IT. Applying IT, AI, and VR within the context of these forces will have a huge impact on how tourism develops. The central question for the tourism research agenda is: Given the forces at play, what research avenues are central to the future of tourism, its place within the Internet ecosystem, and the role of tourism in our social and natural ecosystems?

Artificial intelligence (AI) is currently present in almost every area of travel and tourism, appearing in different types of applications such as personalization and recommender systems, robots, conversational systems, smart travel agents, prediction and forecasting systems, language translation applications, and voice recognition and natural language processing systems. Recent improvements in big data, algorithms, and computing power have enabled significant enhancements in AI. In this chapter, we review how AI has changed and is changing the main processes in the tourism industry. We start with the IT foundations of AI that are relevant for travel and tourism and then address the AI systems and applications available in the sector. We then examine hospitality in detail, as a sector in which most of these systems are being implemented. We conclude with the challenges that AI faces in the tourism sector, a research agenda, and draw a scenario of the future of AI in tourism.