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The power of search engine ranking for tourist destinations

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  • Pan, Bing

Abstract

Most online travelers in the United States use search engines to seek out travel information. Thus, Destination Marketing Organizations (DMOs) need to attract clicks through returned results on search engines. We modeled clickthrough rates (CTRs) of several published clickthrough reports and investigate the CTRs of a DMO's webpages on different ranks of different properties (web, image, and mobile searches) on a search engine. The results validated the power-law distribution of CTRs on different ranks: the top results attract high CTRs but the rates decrease precipitously when the ranks go down. However, top ranks are a necessary condition but not a sufficient one: many top ranked results have low CTRs. Image search and mobile search have different CTR curves, providing different opportunities for tourism destinations and businesses.

Suggested Citation

  • Pan, Bing, 2015. "The power of search engine ranking for tourist destinations," Tourism Management, Elsevier, vol. 47(C), pages 79-87.
  • Handle: RePEc:eee:touman:v:47:y:2015:i:c:p:79-87
    DOI: 10.1016/j.tourman.2014.08.015
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    References listed on IDEAS

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    Cited by:

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    2. Fengzhi Sun & Zihan Li & Mingzhi Xu & Mingcan Han, 2024. "New Changes in Chinese Urban Tourism Pattern under the Impact of COVID-19 Pandemic: Based on Internet Attention," Sustainability, MDPI, vol. 16(14), pages 1-22, July.
    3. Gerard Loosschilder & Jean-Pierre I. Rest & Zvi Schwartz & Paolo Cordella & Dirk Sierag, 2017. "From OTA interface design to hotels’ revenues: the impact of sorting and filtering functionalities on consumer choices," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(2), pages 125-138, April.
    4. Theodoros Lappas & Gaurav Sabnis & Georgios Valkanas, 2016. "The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry," Information Systems Research, INFORMS, vol. 27(4), pages 940-961, December.
    5. Marios Kokkodis & Theodoros Lappas, 2020. "Your Hometown Matters: Popularity-Difference Bias in Online Reputation Platforms," Information Systems Research, INFORMS, vol. 31(2), pages 412-430, June.
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    7. Hulya Bakirtas & Vildan Gulpinar Demirci, 2022. "Can Google Trends data provide information on consumer’s perception regarding hotel brands?," Information Technology & Tourism, Springer, vol. 24(1), pages 57-83, March.
    8. Francisco E. Cabrera & Manuel Amaya & Gustavo Fabián Vaccaro Witt & José Ignacio Peláez, 2019. "Pairwise Voting to Rank Touristic Destinations Based on Preference Valuation," Sustainability, MDPI, vol. 11(21), pages 1-13, October.
    9. Shenzhen Tian & Xueming Li & Jun Yang & Hui Wang & Jianke Guo, 2023. "Spatiotemporal evolution of pseudo human settlements: case study of 36 cities in the three provinces of Northeast China from 2011 to 2018," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(2), pages 1742-1772, February.

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