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This document provides an overview of key concepts related to the digital tourism landscape. It discusses drivers of innovation and technological change, and explains the digital tourism ecosystem perspective. This includes entities, connections, devices, communities, and touchpoints within the ecosystem. It also examines models for the diffusion and adoption of innovations, as well as conceptual frameworks for understanding digital tourist behavior. Traditional and electronic tourism distribution systems are compared.
chapter-2.pptx
- 1. C A B I T O U R I S M T E X T S 2nd Edition Tourism Information Technology PIERRE J. BENCKENDORFF PAULINE J. SHELDON DANIEL R. FESENMAIER COMPLIMENTARY TEACHING MATERIALS
- 2. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Chapter 2 The Digital Tourism Landscape
- 3. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Chapter 2 Learning Objectives After studying this chapter you should be able to: 1. analyze the drivers of innovation and technological change in the digital landscape; 2. explain and evaluate the components of IT in tourism using a digital tourism ecosystem perspective; 3. apply concepts of tourist behavior to explain how digital travelers use and respond to information technologies in tourism settings; 4. evaluate the factors that determine whether travelers will use a particular technology; 5. explain the role of IT in tourists’ decision-making processes; and 6. compare and contrast traditional and electronic tourism distribution systems.
- 4. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Key Concepts Computer anxiety, computer phobia and technophobia Diffusion of Innovations Theory Digital tourism ecosystem Hype Cycle Multi-level perspective (MLP) Technological Innovation Theory Technology Acceptance Model (TAM) Unified Theory of Acceptance and Use of Technology (UTAUT) 4
- 5. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Inspiration Transaction Experience Reflection FIGURE 2.1 The digital tourism ecosystem Entities Suppliers, Travelers, Intermediaries, Governments, DMOs Connections Broadband, Mobile, WiFi, NFC, BLE, GPS, Broadcasting, Protocols, Standards Devices Desktops, Smart devices, Mobile devices, Digital kiosks Communities Social networks, Blogs, Reviews, Forums, Wikis, Local experts, Media sharing Touch Points Websites, Search engines, Mobile apps, Email, Telephone, Face-to-face Content Rich media, Maps & navigation, Transactions, Dynamic content, User-generated content
- 6. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Digital Tourism Ecosystem Ecosystem functions Inspiration Transaction Experience Reflection Ecosystem health Productivity Resilience Diversity 6
- 7. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Digital Tourism Ecosystem Roles of entities and communities Catalyzers Dictators Milkers Niche players Digital technological environment Devices Connections Content Touch points 7
- 8. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Socio-technical regime Landscape developments Small networks of actors support novelties on the basis of expectations and visions. Learning processes take place on multiple dimensions (co-construction). Efforts to link different elements in a seamless web. Elements become aligned and stabilize in a dominant design. Internal momentum increases. New configuration breaks through, taking advantage of “windows of opportunity”. Adjustments occur in socio-technical regime. Socio-technical regime is “dynamically stable” Market preferences External influences on niches Industry Policy Science Culture Technology New regime influences landscape Landscape developments put pressure on existing regime, which opens up, creating windows of opportunity for novelties Niche innovations Increasing structuration of activities in local practices Time Source: Geels (2002)
- 9. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S MARKET SHARE (%) TIME 100 75 50 25 Innovators 2.5% Early adopters 13.5% Early majority 34% Late majority 34% Laggards 16% FIGURE 2.3 Diffusion of innovations Source: Rogers (1962)
- 10. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S THIRD Electricity SECOND Steam power FOURTH Electronics FIFTH Digital networks SIXTH Ubiquitous computing nanotechnology FIRST Mechanization INDUSTRIAL REVOLUTION INFORMATION REVOLUTION FIGURE 2.4 Waves of IT innovation Source: Schumpeter (1934), Perez (2002) 1780 1840 1900 1950 1990 2020 PERFORMANCE TIME
- 11. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Startup firms EXPECTATIONS/VISIBILITY TIME Peak of inflated expectations Trough of disillusionment Slope of enlightenment Plateau of productivity R&D 1st generation products (expensive) “Innovators” adopt products Mass-media hype “Early adopters” adopt products Negative publicity Supplier failure/consolidation New rounds of venture capital 2nd generation products “Early majority” start to adopt product triggering high growth phase New paradigms and practices become accepted Technology trigger Supplier proliferation 3rd generation products FIGURE 2.5 Gartner Hype Cycle. Adapted from Tarkovskiy (2013)
- 12. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Matching with economic opportunities (EO) Choosing enabling/emerging technologies (ET) Executing business innovation for growth (BI) Assessing external customer & internal client value (CV) Value Potential Low High Value Realization High Low COMMUNICATING ET ET ET Taking value propositions to market Communicating e-business initiatives Conveying new IT insights Organizational learning External market Internal organization Time FIGURE 2.6 Net-based Business Innovation Cycle. Adapted from Wheeler (2002)
- 13. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Understanding the Digital Tourist Aspects of IT and behavior: Technology use and acceptance demographics trip characteristics psychographics UTAUT Decision-making information search trip planning purchase Information sharing Co-creation of experiences 13
- 14. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S High tech and high touch travelers 14 Everyday life High tech High touch Travel High tech Spillovers Opportunity seekers High touch Compensators Luddites
- 15. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Performance expectancy Effort expectancy Social influence Mediating factors • Gender • Age • Experience Facilitating factors • Resources • Knowledge • Compatibility • Support Behavioral intention Use behavior Hedonic motivation Price value Habit Adapted from Venkatesh, et al. (2012) FIGURE 2.7 Unified Theory of Acceptance and Use of Technology II (UTAUT II).
- 16. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Understanding the Digital Tourist Quantitative Traditional surveys Online surveys Polls Web analytics Big data Visitor tracking Experiments 16 Qualitative Interviews Focus groups Content analysis Sentiment analysis Netnography Observation Prototyping
- 17. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S SUPPLIERS CONNECTIONS BOOKINGS Traditional travel agent Global distribution system (GDS) Airlines Hotels Activities and events Cruise Car rental Rail Supplier reservation systems (CRS, ARS, PMS) Call center Point of sale (POS) Switch Tour operator / wholesaler FIGURE 2.8 The traditional travel distribution system. 17
- 18. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S SUPPLIERS Airlines Hotels Activities and events Cruise Car rental Rail CONNECTIONS BOOKINGS Switch Supplier website Affiliate Online travel agent (OTA) Traditional travel agent Channel manager Travel management company (TMC) Global distribution system (GDS) Supplier reservation systems (CRS, ARS, PMS) GDS new entrants (GNE) Social media Mobile app Destination management system (DMS) Tour operator wholesaler Call center Point of sale (POS) Internet booking engine (IBE) DMO website Meta- search FIGURE 2.9 The digital travel distribution system. 18
- 19. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Types of Information in Travel Distribution Descriptive information User information Analytical information Transactional information 19
- 20. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Discussion Questions 1. In 2007 the World Economic Forum released three scenarios of digital ecosystems, which are summarized in the following YouTube video: http://youtu.be/jnrAtXt3uu4. Considering IT developments since 2007, which one has been the most accurate? Justify your answer and discuss the implications for IT and tourism. 2. Which of the innovation models presented in this chapter are most relevant to the tourism industry? Explain why. 3. Conduct your own research about the major generational cohorts alive today (Baby Boomers, Gen X, Gen Y and Gen Z). Do they differ in how they use technologies? Are older consumers as likely to use IT for travel purposes as younger consumers?
- 21. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Discussion Questions 4. Provide examples of how the use of technology can deliver both high-tech and high-touch outcomes. 5. What are the key elements of the Unified Theory of Acceptance and Use of Technology II (UTAUT II). Provide your own tourism and technology example to illustrate the various components of this model. 6. What challenges do small and medium tourism enterprises (SMTEs) face in travel distribution? How might SMTEs respond to the increasingly complex structure of the digital tourism distribution system?
- 22. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Useful Websites 22 American Society of Travel Agents (ASTA) http://www.asta.org/ Mygola http://www.mygola.com/ World Economic Forum Digital Ecosystems http://www.weforum.org/reports/digital-ecosystem-convergence- between-it-telecoms-media-and-entertainment-scenarios-2015
- 23. C A B I T O U R I S M T E X T S C A B I T O U R I S M T E X T S Case Study Mygola Online trip planning tool that aims to answer the following questions: What should I see? How do I get there? What should I look out for? Over 5000 curated itineraries. Use of text-mining software to parse travel articles and extract the structure of a trip. Algorithms also mine other information such as opening hours and travel distances between sites. Visually stunning images and videos are sourced to match itinerary. Users can customize itineraries by selecting interests, which are fed back to create a rich ‘big data’ source for refining the predictive power of the platform.