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The power of search engine ranking for tourist destinations

Pan, Bing - In: Tourism management : research, policies, practice 47 (2015), pp. 79-87

Persistent link: https://www.econbiz.de/10010499495

A framework of search engine use for travel planning

Fesenmaier, Daniel R.; Xiang, Zheng; Pan, Bing; Law, Rob - In: Journal of travel research : a quarterly publication of … 50 (2010/11) 6, pp. 587-601

Persistent link: https://www.econbiz.de/10009388167

Predicting hotel demand using destination marketing organization's web traffic data

Yang, Yang; Pan, Bing; Song, Haiyan - In: Journal of travel research : a quarterly publication of … 53 (2014) 4, pp. 433-447

Persistent link: https://www.econbiz.de/10010379414

Google trends and tourists' arrivals : emerging biases and proposed corrections

Dergiades, Theologos; Mavragani, Eleni; Pan, Bing - In: Tourism management : research, policies, practice 66 (2018), pp. 108-120

Persistent link: https://www.econbiz.de/10011814597

Machine learning in internet search query selection for tourism forecasting

Li, Xin; Li, Hengyun; Pan, Bing; Law, Rob - In: Journal of travel research : a quarterly publication of … 60 (2021) 6, pp. 1213-1231

Persistent link: https://www.econbiz.de/10012593211

Does algorithmic filtering lead to filter bubbles in online tourist information searches?

Gong, Yaqi; Schroeder, Ashley; Pan, Bing; Sundar, S. Shyam - In: Information technology & tourism 26 (2024) 1, pp. 183-217

Persistent link: https://www.econbiz.de/10014452362

Forecasting hotel room demand using search engine data

Pan, Bing; Chenguang Wu, Doris; Song, Haiyan - In: Journal of Hospitality and Tourism Technology 3 (2012) 3, pp. 196-210

Purpose – The purpose of this paper is to investigate the usefulness of search query volume data in forecasting demand for hotel rooms and identify the best econometric forecasting model. Design/methodology/approach – The authors used search volume data on five related queries to predict...

Persistent link: https://www.econbiz.de/10014873977