Zheng Xiang, Daniel R. Fesenmaier's Analytics in Smart Tourism Design: Concepts and Methods PDF

By Zheng Xiang, Daniel R. Fesenmaier

ISBN-10: 3319442627

ISBN-13: 9783319442624

ISBN-10: 3319442635

ISBN-13: 9783319442631

This ebook provides leading edge learn at the improvement of analytics in commute and tourism. It introduces new conceptual frameworks and size instruments, in addition to purposes and case stories for vacation spot advertising and marketing and administration. it's divided into 5 elements: half one on commute call for analytics specializes in conceptualizing and enforcing go back and forth call for modeling utilizing large facts. It illustrates new how you can determine, generate and make the most of huge amounts of information in tourism call for forecasting and modeling. half makes a speciality of analytics in shuttle and way of life, offering fresh advancements in wearable pcs and physiological size units, and the consequences for our knowing of on-the-go tourists and tourism layout. half 3 embraces tourism geoanalytics, correlating social media and geo-based information with tourism data. half 4 discusses web-based and social media analytics and provides the newest advancements in using user-generated content material on the web to appreciate a couple of managerial difficulties. the ultimate half is a suite of case stories utilizing web-based and social media analytics, with examples from the Sochi Olympics on Twitter, leveraging on-line studies within the inn undefined, and comparing vacation spot communications and marketplace intelligence with on-line resort stories. The chapters during this part jointly describe various diverse ways to realizing industry dynamics in tourism and hospitality.

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Extra info for Analytics in Smart Tourism Design: Concepts and Methods

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The value of this tool for the decision making of tourism organisations is unquestionable, as it allows them to know the responses of a series of people to this improvement. Travel Demand Modeling with Behavioral Data 35 Fig. 1 Linking sample revealed preferences through choices made Fig. 2 Individual revealed preferences through choices made However, note that the estimations of parameters βi and γ i are made at the global sample level (see Fig. 1). What if the estimation of these parameters could be made tourist by tourist?

Hotels and destinations). , 2015).

2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 98–115. , & Silva, E. (2015). Forecasting with big data: A review. Annals of Data Science, 2(1), 5–19. , & Perdana, D. H. F. (2014). Trip guidance: A linked data based mobile tourists guide. Advanced Science Letters, 20(1), 75–79. , & Samaraweera, S. (2013). Big data solution for Sri Lankan development: A case study from travel and tourism. Paper presented at the 2013 International Conference on Advances in ICT for Emerging Regions, ICTer 2, Colombo.

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Analytics in Smart Tourism Design: Concepts and Methods by Zheng Xiang, Daniel R. Fesenmaier

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