IT business model for tourism product placement
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Uticaj savremenih tehnologija na plasman turističkog proizvoda u cilju kastimizacije poslovnog modela prema percepciji digitalnog klijenta
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IT business model for tourism product placement
- 1. IT biznis model za plasman turističkog prozvoda Prof. dr Angelina Njeguš Vanredni profesor Univerziteta Singidunum
- 2. Pregled top 10 tehnologija u 2014. • Mobilne tehnologije • Big Data tehnologije • Inteligentna rešenja • Cloud Computing • Društveno umrežavanje • Bezbednost • Green tehnologije • ... Izvor: news.dice.com/2013/12/23/research-firms-top-10-technology-trends-2014
- 3. Evolucija turizma 1980s 1990s 2000s Client-Server Computing Mainframe Computing Internet Computing E-Business Cloud Computing Service-Oriented Computing 2010s Centralizovani Deljeni SamouslužniServisi: Softver: Centralizovan Decentralizovan Distribuiran e-Turizam Cloud turizam
- 4. Cloud Computing servisi u turizmu Hotels & Resorts Restaurants and Foodservice Cruise Airline Destination Service Providers Travel Agencies SaaS Software as a Service PaaS Platform as a Service IaaS Infrastructure as a Service Micros Cloud POS Fidelio WebSuite Sabre Airline Solution Amadeus e-Ticket Database Development tools Middleware Storage Servers Network
- 5. Big Data • Rast cloud, mobilnog i društvenog (Social) računarstva i drugih pametnih uređaja dovodi do toga da su organizacije danas preplavljene: – ogromnim obimom podataka – velikom brzinom podataka – Raznolikim podacima Izvor: scoop.intel.com/what- happens-in-an-internet-minute/ Naziv Ozn byte B kilobyte KB megabyte MB gigabyte GB terabyte TB petabyte PB exabyte EB zettabyte ZB yottabyte YB brontobyte BB geopbyte GeB
- 7. Uticaj Web generacija na turizam Izvor: lifeboat.com/ex/web.3.0
- 8. Digitalni klijent • Google analitičari ukazuju da putnici pre bookinga posete 22 veb sajta • Digitalni putnici imaju kontrolu i žele više – Više od milijardu korisnika ima facebook nalog – Više od 200 miliona tweet-ova dnevno se postavi na Twitter – Apple je prodao više od 2 miliona iPhone 5 pamentih telefona – Putnici više vremena provode na internetu nego gledajući TV ili druge medije – Putnici sve više koriste mobilne uređaje za planiranje i rezervisanje putovanja ...
- 9. IT tehnologije prema životnom ciklusu putovanja klijenta • Šta klijent želi? – Različiti profili klijenta • Leisure (adventure, eco, heritage, wine, packaged beach vacation ...) • Business (MICE) • Health (spas, fintess, medical intervention ...) • Educational/study • Visiting firends or relatives (VFR) • Religion • Sport – Digitalni klijent • Data mining i intelignente aplikacije • Profil prema putanji pretrage informacija • Mobilne aplikacije • CRM • Deljenje informacija na društvenim mrežama i drugim e-medijima
- 10. Kastimizacija poslovnog modela prema percepciji klijenta Izvor: WTO (2007) A Practical Guide to Tourism Destination Management
- 11. Faktori koji utiču na imidž destinacije Izvor: Ndlovu, J. (2009) Branding as a Strategic Tool to Reposition a Destination. Faculty of Economic and Management Sciences. University of Pretoria. Available at: http://upetd.up.ac.za/thesis/available/etd-09242009-225847/ (accessed: 7.05.2014)
- 12. e-Marketing aktivnosti Izvor: WTO (2007) A Practical Guide to Tourism Destination Management
- 13. Uticaj distribucionih sistema Izvor: European Commission (2013) Business Model TourismLink. Available at: http://www.tourismlink.eu/wp- content/uploads/2013/01/business-model-pres-to-AB-6th-Nov-final.pdf (accessed: 7.05.2014.) • Trenutno stanje distributivnog lanca putovanja
- 14. Postojeći distributivni sistemi Izvor: European Commission (2013) Business Model TourismLink. Available at: http://www.tourismlink.eu/wp- content/uploads/2013/01/business-model-pres-to-AB-6th-Nov-final.pdf (accessed: 7.05.2014.)
- 15. Udeo na tržištu Internet distribucionih sistema (IDS) u regionu D-A-CH Izvor: Schegg, R., Fux, M. (2012). The Power of Internet Distribution Systems (IDS). Institute of Tourism. University of Applied Sciences of Wester Switzerland Valais Sierre.
- 16. Kriterijumi za izbor kanala prodaje Izvor: Schegg, R., Fux, M. (2012). The Power of Internet Distribution Systems (IDS). Institute of Tourism. University of Applied Sciences of Wester Switzerland Valais Sierre.
- 17. Studija slučaja: German National Tourist Board (GNTB) Izvor: www.germany.travel
- 18. Studija slučaja: GNTB Izvor: www.germany.travel
- 19. Studija slučaja: TOB Izvor: http://portal.tob.rs/en/home
- 20. Studija slučaja: TOB Izvor: http://portal.tob.rs/en/home
- 21. Prof. dr Angelina Njeguš anjegus@singidunum.ac.rs
Notas del editor
- Rast cloud, mobilnog i društvenog (Social) računarstva dovodi do toga da su organizacije danas preplavljene: ogromnim obimom podataka (svakodnevno obrađuju čak do petabajt raznih vrsta podataka) Svakodnevno se kreira 12 terabajt tvitova, koji se prate radi analize klijenata, potreba tržišta ili analize proizvoda Godišnje se sa brojila očitava 350 milijardi podataka kako bi se bolje predvidela potrošnja električne energije velikom brzinom podataka (ponekad je i 2 minuta prekasno, npr. potrebno je što pre uočiti računarski kriminal, kao što je krađa osetljivih podataka o gostima hotela) Dnevno se nadgleda 5 miliona transakcija kako bi se identifikovale potencijalne prevare Svakodnevno se analizira u realnom vremenu oko 500 miliona zapisa o pozivima klijenata kako bi se na vreme uočile bilo koje promene kod klijenata Raznolikim podacima (bilo da su struktuirani ili nestruktuirani podaci, kao što su tekst, podaci od različitih senzora, audio, video i klik tokovi podataka, log fajlovi i dr) Uživo se nadgleda oko stotinak video zapisa sa kamera Rast od 80% podataka u slikama, video zapisima ili dokumentima koristi se radi poboljšanja zadovoljstva klijenata
- At a fundamental level, it sounds like a relatively simple recipe: Take one tiny, very powerful microprocessor, connect it wirelessly to the cloud, and add a generous portion of very smart software. According to many experts, these are the primary ingredients of an intelligent system, a place where everyday objects provide information to a centralized computing infrastructure where this data is aggregated, sliced, diced and analyzed. Expand that recipe 50 billion times, add the immense storage capacity and analytics functionality provided by cloud services, and the next big intersection of technology and society begins to emerge. It’s a very real place where smart devices share their experiences wirelessly with large data warehouses, and software then connects that data in logical ways to portray the hidden patterns and trends that allow organizations to see business intelligence faster than ever before — from individual buying habits, to oil consumption by region, to the epidemiology of diseases across continents. As the cost of powerful microprocessors continues to decrease, the economic argument for embedding them into everyday objects becomes more and more practical. Consider how much smarter a soft drink company would operate if every single can of soda in the United States could relay information on where it was purchased and where it was consumed. If it sounds far off, it’s not. The technology is already available, and shipments of microprocessor-enabled devices capable of handling sophisticated software and connecting wirelessly are already outstripping shipments of mobile phones and PCs. By 2015, shipments of embedded devices will surpass those of phones, PCs and servers combined. Developers around the world are building intelligent systems for manufacturers, retailers, healthcare providers and a host of other industries.
- IDS – Internet Distirbution Systems OTA – Online travel agency