Tourism Knowledge Destination

Tourism Knowledge Destination

Wolfram Höpken (University of Applied Sciences Ravensburg-Weingarten, Germany), Matthias Fuchs (Mid-Sweden University, Sweden) and Maria Lexhagen (Mid-Sweden University, Sweden)
Copyright: © 2014 |Pages: 15
DOI: 10.4018/978-1-4666-5202-6.ch227

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Although information and communication technologies (ICT) were an important issue for Travel & Tourism (T&T) since the 1960s (i.e. computer reservations systems, global distribution systems; Werthner & Klein, 1999), the difference today is that ICT has become a strategic issue for every business (Buhalis, 2006). The special benefit tourism gains from ICT can be put down to the characteristics of the tourism product, being a service bundle ideally portrayed by electronic media and being jointly delivered by (usually) small-sized enterprises. Indeed, T&T is a highly information intensive sector, and not surprisingly, within the e-Commerce sector T&T represents the largest branch. In 2009, 25.7% (€ 65.2 Bn.) of the EU online sales volume has been generated by the T&T sector, whereat in 2001 this figure stood only at € 5 Bn. (Marcussen, 2009). Moreover, in the US already 59% of the total travel revenue is generated online (NewMedia TrendWatch, 2012). However, although tourism shows high penetration rates with respect to Web-based marketing & distribution, shortcomings become evident with respect to e-business networks (supply-chains) and integrated (internal) process automation (e-procurement, enterprise resource planning, etc.). Finally, most significant adoption gaps are ascertained for ICTs in tourism SMEs to support market research, product development and strategic decision making (eBusiness Watch, 2006).

The attractiveness of tourism destinations particularly depends on how communication and information needs of tourism stakeholders can be satisfied through information and communication technology (ICT)-based infrastructures, so that sustainable knowledge sources can emerge (Buhalis, 2006). Although huge amounts of customer-based data are widespread in tourism destinations (e.g. Web-servers store tourists’ Website navigation, data bases save transaction and survey data, respectively), these valuable knowledge sources typically remain unused (Pyo, 2005). However, managerial effectiveness and organisational learning could be significantly enhanced by applying methods of business intelligence (BI; Sambamurthy & Subramani, 2005; Wong et al., 2006; Shaw & Williams, 2009), offering highly reliable, up-to-date and strategically relevant information, such as tourists’ travel motives and service expectations, information needs, channel use and related conversion rates, occupancy trends, quality of service experience and added value per guest segment (Min et al., 2002; Pyo et al., 2002). This makes clear why ICT and methods of BI are playing a crucial role in effectuating a knowledge destination by enhancing large-scale intra and inter-firm knowledge exchange. Indeed, the major challenge of knowledge management for tourism destinations is to make individual knowledge about customers, products, processes, competitors or business partners available and meaningful to others (Back et al., 2007).

Key Terms in this Chapter

Customer-Based Data: Data provided by customers either intentionally, like demographic data, reviews and comments, or data provided unintentionally, like data on Web-navigation, booking or consumption behavior.

Destination Management Information System (DMIS): A management information system specifically designed to enable improved decision support for the destination management organization and other stakeholders of a tourism destination.

Destination Management Organization (DMO): Organization which coordinates the many constituent elements of the tourism product; provides visitor services and the necessary information structure to market the destination in a most democratic way to enhance residents’ well-being.

Adaptive Management Information System: A management information system adapting its user interface and interaction strategy depending on user preferences and past user behavior and satisfaction.

Data Warehouse Bus Matrix: Visualization of business processes, corresponding facts and dimensions for a multi-dimensional data warehouse model.

Computer Reservation Systems (CRS) / Global Distribution Systems (GDS): Computer systems providing information like prices and availabilities for a wide range of tourism products (e.g. hotels, flights, car-rental, etc.) and supporting the full booking, settlement and after-sales processes.

Tourism Destination: Agglomeration of companies and organizations involved in producing and marketing the overall tourism product within a geographical area; strategic unit providing all necessary resources whose integrated activities allow tourists with the kind of experiences they expect.

Tourist Feedback: Feedback on tourism products, suppliers or whole destinations, provided by tourists in structured and unstructured ways, e.g. in the form of customer ratings, comments or product reviews.

Tourism Knowledge Destination: Novel concept of a tourism destination that supports knowledge creation, transfer and enhanced decision making among destination stakeholders by applying techniques from business intelligence and data mining.

Multi-Dimensional Data Modelling (MDM): A modelling paradigm for data warehouse models building on a separation of measurements, called facts, and surrounded context, called dimensions.

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