INTRODUCTION
Nowadays, the tourism industry is a consumer of a diverse range of information (Buhalis & O’Connor, 2005). Information communication technologies (ICTs) play a critical role for the competitiveness of tourism organizations and destinations. According to Staab and Werthner (2002), ICTs are having the effect of changing:
• The ways in which tourism companies contact their business; reservations and information management systems;
• The ways tourism companies communicate; how customers look for information on, and purchase travel goods and services.
In the tourism industry, the supply and demand sides form a worldwide network in which tourism product’s generation and distribution are closely worked together. Most tourism products (e.g., hotel rooms or flight tickets) are time constrained and nonstockable. Generally, the tourism product is both “perishable” and “complex,” and itself is a bundle of basic products aggregated by intermediaries. Consequently, basic products must have well-defined interfaces with respect to consumer needs, prices, or distribution channels. In addition, a tourism product cannot be tested and controlled in advance. During decision-making, only an abstract model of the product (e.g., its description) is available. Besides, the tourism industry has a heterogeneous nature, and a strong small and medium-sized enterprises (SMEs) base. Undoubtedly, intelligent technologies are increasingly changing the nature of, and processes in, the tourism industry. This chapter reviews, in brief, such technologies applied to the e-tourism domain.
BACKGROUND
E-tourism is defined as the use of ICTs in the tourism industry.
It involves the buying and selling of tourism products and services via electronic channels, such as the Internet, cable TV, and so forth. E-tourism includes all intranet, extranet, and Internet applications, as well as all the strategic management and marketing issues related to the use of technology. ICTs include the entire range of electronic tools that facilitate the operational and strategic management of organizations by enabling them to manage their information, functions, and processes, as well as to communicate interactively with their stakeholders for achieving their mission and objectives. Currently, e-tourism makes use of (syntactic) Web technology for tours, infrastructure, related interesting information, such as public transport, timetables, weather, online reservation, and so forth. However, the major barriers using the syntactic Web are:
• Creating complex queries involving background knowledge on tourism issues.
• Solving ambiguities and synonyms.
• Finding and using Web services for tourism
From another perspective, the characteristics of the tourism product require information on the consumers’ and suppliers’ sides, involving high information search costs and causing informational market imperfections. These outcomes sequentially lead to the establishment of specific product distribution information and value-adding chains. Given such a framework, Staab and Werthner (2002) state that intelligent Information Systems (ISs) should:
• Be heterogeneous, distributed, and cooperative.
• Enable full autonomy of the respective participants.
• Support the entire consumer life cycle and all business phases.
• Allow dynamic network configurations.
• Provide intelligence for customers (tourists) and suppliers as well as in the network.
• Be scalable and open.
• Focus on mobile communication enabling multichannel distribution.
Hereafter, we present intelligent technologies for tourism.
INTELLIGENT TECHNOLOGIES FOR TOURISM
Web intelligence combines two topics: (1) Web analytics, which examines how Web site visitors view and interact with a Web site’s pages and features; and (2) business intelligence, which allows a corporation’s management to use data on customer purchasing patterns, demographics, and demand trends to make effective strategic decisions (Zhong, 2003). In tourism, the developments of artificial intelligence
(AI) are at the cutting edge. Many applications are provided to the users, such as individualized pricing (http://www.priceline.com), reversed multiattribute auctioning (http://www.mytraveldream.com), recommendations in bundling products, and semantic Web, as well as mobile applications (Kanellopoulos, 2006; Kanellopoulos & Kotsiantis, 2006). Using the Web, travelers can get information on routes, timetables, seat availabilities, accommodations, rental cars, and restaurants to help them plan their travels. Remarkable progress has been made in the automation of travel planning with the help of the easily accessible information. There are also many semiautomated commercial service Web sites like travelocity.com, expedia.com, and orbitz.com (Paprzychi, Gilbert, & Gordon, 2002).
web services
The Web services technology is a set of standards that could allow Web applications for the tourism domain to “talk” to each other over the Internet. These standards are:
• XML (eXtensible Markup Language: http://www.w3.org/XML/) for driving applications services.
• SOAP (Simple Object Access Protocol: http://www.w3.org/TR/soap) for communication.
• WSDL (Web Services Description Language: http:// www.w3.org/TR/wsdl/) as the service description language.
• UDDI (Universal Description, Discovery and Integration: http://www.uddi.org/) as the service discovery protocol.
The Web services technology offers distributed tourism services capability over a network (Ouzzani & Bouguettaya, 2004). The platform- and language-independent interfaces of Web services allow the easy integration of heterogeneous tourism ISs. Web services offer mechanisms for describing tourism-related Web documents, methods for accessing them, and discovery methods that enable the identification of relevant Web service providers. Recently, the OTA (Open Travel Alliance) has developed open data transmission specifications for the electronic exchange of business information for the travel industry, including but not limited to the use of XML.
semantic web
The Semantic Web is an extension of the current Web in which information is given well-defined meaning. It enables computers and users to work in cooperation, and allows the tourism content to become semantic annotated (Kanellopoulos, 2006). This characteristic allows users and software agents to query and infer knowledge from Web tourism information quickly and automatically. The semantic Web is based on formal domain models (ontologies) that define domain specific conceptualization and impose description on the domain knowledge structure and content. An ontology comprises the classes of entities, relations between entities, and the axioms that apply to the entities of the domain. Ontologies can provide a shared understanding of the tourism domain to sustain communication among users and software agents typically being represented in a machine-processable representation language like OWL (Web Ontology Language, http://www.w3.org/2004/OWL/). Through the use of metadata organized in several interrelated ontologies, information concerning tourism objects (e.g., hotels, attractions) can be tagged with descriptors that facilitate its retrieval, analysis, processing, and reconfiguration. Introducing semantics to Web services for tourism brings the following advantages:
• Ontologies offer a promising infrastructure to cope with heterogeneous representations of Web documents (Chandrasekaran, Josephson, & Benjamins, 1999). Semantically enriched Web services can handle the interoperability at the technical level, that is, they make Web applications “talk” to each other independent of their hardware and software platforms (Dell’ Erba, 2004).
• Semantics can be used for the discovery and composition of Web services.
• The main mechanism for service discovery is service registries, and semantics can be used for the discovery of registries of Web services.
ontologies for tourism
Tourism ontologies allow machine-supported tourism data interpretation and integration. The e-tourism ontology (http://e-tourism.deri.at/ont/) was deployed in the OnTour project, and describes the domain of tourism using OWL. It focuses on accommodation and activities, and it is based on an international standard: the “Thesaurus on Tourism & Leisure Activities” of the World Tourism Organization (WTO). This thesaurus is an extensive collection of terms related to tourism. The ISO 18513 standard (“tourism services-hotel and other types of tourism accommodation-terminology”) defines terms used in tourism in relation to the various types of tourism accommodation and other related services. MONDECA’s tourism ontology (http://www.mondeca.com) defines tourism concepts based on the WTO thesaurus. These concepts include terms for tourism object profiling, tourism and cultural objects, tourism packages, and tourism multimedia content. A reference ontology, named
COTRIN (Comprehensive Ontology for the Travel Industry) is presented in Cardoso and Lang (2007). The objective of COTRIN ontology is the implementation of the semantic XML-based OTA specifications. Major airlines, hoteliers, car rental companies, leisure suppliers, travel agencies, and others may use COTRIN to bring together autonomous and heterogeneous tourism Web services, Web processes, applications, data, and components residing in distributed environments.
From another perspective, a destination management system (DMS) provides complete and up-to-date information on a particular tourist destination. DMSs is a perfect application area for semantic Web and P2P (peer-to-peer) technologies. Kanellopoulos and Panagopoulos (2008) developed an ontology for tourist destinations in the LA_DMS (layered adaptive semantic-based DMS based on P2P technologies) project. The aim of LA_DMS project was to enable DMSs adaptive to tourists’ needs concerning destination information. The LA_DMS system incorporates a metadata model to encode semantic tourist destination information in an RDF-based P2P network architecture. This metadata model combines ontological structures with information for tourist destinations and peers. Kanellopoulos and Kotsiantis (2007) proposed a semantic-based architecture in which semantic Web ontology is used to model tourist destinations, user profiles, and contexts. The semantic Web service ontology (OWL-S) is extended for matching user requirements with tourist destination specifications at the semantic level, with context information taken into account. Semantic Web rule language (SWRL) is used for inferencing with context and user profile descriptions. Their architecture enables DMSs to become fully adaptable to user’s requirements concerning tourist destinations.
In the group package tour domain, an intelligent Web portal was proposed that helps people living in Europe to find package tours that match their personal traveling preferences (Kanellopoulos, 2008). For this purpose, the knowledge of the package tour domain has been represented by means of ontology.
The HARMONISE (http://www.harmonise.org) is an EU tourism harmonisation network (THN) established by the ECommerce and Tourism Research Laboratory, IFITT (International Federation for IT and Travel & Tourism), and others. The HARMONISE project allows participating tourism organizations to keep their proprietary data format and use ontology mediation while exchanging information (Fodor & Werthner, 2005). HARMONISE is an ontology-based mediation and harmonization tool that establishes the bridges between existing and emerging online marketplaces.
In the SATINE project (semantic-based interoperability infrastructure for integrating Web service platforms to P2P networks), a secure semantics-based interoperability framework was developed for exploiting Web service platforms in conjunction with P2P networks in the tourist industry (Dogac, Kabak, Laleci, Sinir, Yildiz, Kirbas, & Gurcan, 2004).
Intelligent software agents
The semantic Web includes intelligent software agents that “understand” semantic relationships between Web resources, and seek relevant information as well as perform transactions for users. Intelligent agents can provide various tourism products and services into an integrated tourism package that can be personalized to a tourist’s needs. A variety of traveler, hotel, museum, and other agents can enhance the tourism marketing and management reservation processes (Kanellopoulos, 2006). There are many research prototypes of intelligent travel support systems based on software agent technology (Camacho, Borrajo, & Molina, 2001). Traveler software agents can assist travelers in finding sources of tourism products and services, and in documenting and archiving them. A set of agents can be deployed for various tasks including tracking visitor schedules, monitoring meeting schedules, and monitoring user’s travel plans. For example, if the user specifies the travel itinerary and his/her required services, then a set of information agents can be spawned to perform the requested monitoring activities (Camacho et al., 2001). An additional capacity of the semantic Web is realized when intelligent agents extract information from one application and subsequently, utilize the data as input for further applications (Kanellopoulos, 2006). Therefore, software agents can create greater capacity for large-scale automated collection, processing, and selective dissemination of tourism data.
dynamic packaging systems
A package tour consists of transport and accommodation advertised and sold together by a vendor known as a tour operator. Tour operators provide various services like a rental car, activities, or outings during the holiday. Consumers can acquire packages from a diversity of Web sites including online agencies and airlines. The objective of dynamic packaging is to pack all the components chosen by a traveler to create one reservation. Regardless of where the inventory originates, the package that is created is handled seamlessly as one transaction, and requires only one payment from the consumer. Cardoso and Lang (2007) proposed a framework and a platform to enable dynamic packaging using semantic Web technologies. A dynamic packaging application allows consumers and/or travel agents to bundle trip components. The range of products and services to be bundled is too large: guider tour, entertainment, event/festival, shopping, activity, accommodation, transportation, food and beverage, and so forth. Figure 1 depicts the operation of a dynamic packaging tour system (DPTS).
Figure 1. The operation of DPTS
Travel recommender systems
Recommender systems can predict what the user needs based on the information provided by the user (Ricci, 2004). A Web-based recommendation system was developed in the intelligent Recommendation for Tourist Destination Decision Making project (DieToRecs) (http://etd.ec3.at). This system helps the tourist destination selection process and accommodates individual traveler’s preferences. Based on the user profiles, personalized recommendations are created to support potential tourists to choose their ideal destination. The Travel Recommender System (Trip@dvice) (http://tripadvise.itc.it) assists travelers in their search for tourism products and services. A prototype called NutKing (http://itr.itc.it) is available. Using the WAP (wireless application protocol), the Mobile Tourism Recommender System (mITR) (http://mobile.itc.it) implements mobile tourism services such as airlines (reservations, check-in, flight status, etc.), hotels and restaurants (reservations), maps, transportation (schedules, connections etc.), traffic, and weather conditions. Context-aware applications, such as mobile tourism guides, utilize contextual information, such as location, display medium, and user profile, in order to provide tailored functionality to the end-user.
mobile tourism guides
A user interacts with a mobile tourism guide using a “map.” Many mobile tourism guides have been deployed. The COMPASS (COntext-aware Mobile Personal ASSistant) guide provides tourists with context-aware recommendations and services (Van Setten, Pokraev, & Koolwaaij, 2004). The GUIDE system (Schmidt-Belz, Polsad, Nick, & Zipf, 2002) provides tourists with context-aware information about a city via a PDA (personal digital assistant). It is based on a client/server architecture and utilizes software agent technology, with a Fujitsu TeamPad 7600 used as a terminal. CRUMPET (CReation of User-friendly Mobile services Personalized for Tourism) is an EU project that developed a guide system that provides mobile services personalized for tourism. In the CRUMPET framework, tourism-related value-added services for nomadic users (across mobile and fixed networks) are provided. In most mobile guides, the characteristics of “context” are categorized into: (1) scope of context, (2) its representation and acquisition, as well as (3) the access mechanism used.
Ubiquitous computing and Ambient Intelligence For tourism
Ubiquitous computing is a model of human-computer interaction in which information processing has been thoroughly integrated into everyday objects and activities. Recently, several projects have focused on ubiquitous computing. Such projects include Xeroz PARC’s ubiquitous computing, IBM’s pervasive computing, and MIT’s Oxygen initiative. An interesting ubiquitous travel service delivery system is presented in O’Brien and Burmeister (2003).
Ambient intelligence is the convergence of ubiquitous computing and communication, and intelligent user-friendly interfaces. Ambient intelligent systems are embedded, personalized, adaptive, and anticipatory, as well as they provide access for tourists, anywhere, at any time (Manes, 2003). In an ambient intelligent environment, tourists are surrounded by intelligent interfaces supported by computing and networking technologies that are embedded in everyday objects such as clothes, vehicles, and smart materials.
future trends
In the near future, the mode of users’ interaction will become laid-back (relaxed and enjoyable) in e-tourism. Users will enjoy computer interaction for travel planning, and technology will move to the background. In addition, users will become an integral part of tourism product creation. Therefore, personalized services and complex market mechanisms should be deployed and provided to the users. For that reason, researchers must consider nontechnical issues related to markets and users, such as dynamic market and network structures; pricing and market design; design and experimenting business models; user decision modeling; and usage analysis.
conclusion
E-tourism is a decent area for Web and semantic Web technologies by assisting users and agencies with quick information searching, integrating, recommending, and various intelligent services. Semantic Web technology has an enormous potential for e-tourism by providing: (1) integration and interoperability, (2) personalized and context-aware recommendations, (3) semantically enriched information searching, and (4) internationalization. Staab and Werthner (2002) state that the requirements of intelligent tourism ISs will raise a number of important technical research issues such as (1) semantic interoperability and mediated architectures; (2) e-business frameworks supporting processes across organizations; (3) mobility and embedded intelligence; (4) natural multilingual interfaces and novel interface technologies; (5) personalization and context-based tourism services; (6) information-to-knowledge transformations, data mining and knowledge management. To these directions, much work has to be done.
KEY TERMS
CRS (Computerized Reservation System): A CRS enables travel agencies to find what a customer is looking for and makes customer data storage and retrieval relatively simple.
DMO (Destination Management Organization): It is an entity or a company that promotes a tourist destination such as to increase the amount of visitors to this destination. It uses a DMS to distribute its properties and to present the tourist destination as a holistic entity.
DMS (Destination Management System): A DMS provides complete and up-to-date information on a particular tourist destination. It handles both the pre-trip and post- arrival information, as well as integrates availability and booking service too. It is used for the collection, storage, manipulation, and distribution of tourism information, as well as for the transaction of reservations and other commercial activities. Well-known DMSs are TISCover, VisitScotland, and Gulliver.
GDS (Global Distribution System): A GDS provides travel information services, such as real-time availability and price information for flights, hotels, and car rental companies.
Dominant GDSs are Sabre and Galileo.
IFITT (International Federation for IT and Travel & Tourism): The IFITT (http://www.ifitt.org/) is a not-for-profit organization aiming to promote international discussion about ICTs and tourism.
LA_DMS (Layered Adaptive Semantic-Based DMS Based on P2P Technologies): It is a DMS that is adaptive to tourists’ needs for tourist destination information. It uses a metadata model to encode semantic destination information in an RDF-based P2P network architecture. Its metadata model combines ontological structures with information for tourism destinations and peers.
OTA (Open Travel Alliance): The OTA (http://www.opentravel.org/) is an organization that develops open data transmission specifications for the electronic exchange of business information for the travel industry, including, but not limited to the use of XML.
WTO (World Tourism Organization): The WTO (http://www.world-tourism.org/) is a global body concerned with the collection and collation of statistical information on international tourism. It represents public sector tourism bodies from most countries, and the publication of its data makes possible comparisons of the flow and growth of tourism on a global scale.
