Motivation and satisfaction of Chinese and U.S. tourists in restaurants: A cross-cultural text mining of online reviews |
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| Institution: | 1. School of Hotel and Tourism Management, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region;2. School of Hospitality and Tourism Management, University of Surrey, Guildford, United Kingdom;3. School of Management, Harbin Institute of Technology, 92 West Dazhi Street, Harbin, China;1. Hohai University, Nanjing City, Jiang Su Province 21110, China;2. School of Management and Business, King''s College London, Franklin-Wilkins Building, 150 Stamford Street, London SE1 9NH, United Kingdom;1. Business School of Guilin University of Technology, Guilin, 541004, China;2. School of Business Administration, Nanjing University of Finance and Economics, Nanjing, 210023, China;3. School of Economics and Management, Nanjing University of Information Science and Technology, Nanjing, 210044, China;1. College of Business Administration, Capital University of Economics and Business, Beijing, China;2. School of Business Administration, Southwestern University of Finance and Economics, Chengdu, China |
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| Abstract: | Tourists with dissimilar cultural backgrounds think and behave differently. Precisely capturing and correctly understanding the cultural difference will help tourism managers generate greater customer satisfaction and increased business revenue. To this end, this paper uncovers and compares the motivation and satisfaction of restaurant tourist customers coming from China and U.S. by investigating their online ratings and reviews. From two major online review communities, customer ratings and reviews have been retrieved, quantified, text-mined, compared, and interpreted using statistics, latent Dirichlet allocation, and frequency analysis. Results suggest that Chinese tourists are less inclined to assign lower ratings to restaurants, and are more strongly fascinated by the food offered, whereas U.S. tourists are more apt to be fun-seeking, and are less uncomfortable with crowdedness. |
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| Keywords: | Tourist Restaurant Cross-culture Online review Text mining |
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