Analysis of the Relation Between Price Range, Location and Reputation in Japanese Hotels
Recently, in response to the spread of the CGM, reputation such as numerical online rating and textual online review has begun to exert a big influence on hotel conversion rate and room rate. Therefore, hotel manager must consider not only factors such as the facilities, brand, competitors, and sales channels but also its reputation when formulating hotel’s sales strategy. However, it is not clear how reputation affects hotel management practices in Japanese hotels. In this research, we analyzed the relation between price range, location, and reputation to clarify the impact on reputation. We collected the hotel information from “Travelko”, the typical Japanese travel comparison site. Additionally, we use statistical data on tourism resources possessed by each prefecture for analysis. First, we tried to categorize prefectures using statistical data. Moreover, we conducted the multiple regression analysis to clarify the impact on the reputation for the four clusters. Based on our analysis, we clarified the relation between price range, location and reputation in Japanese hotels.
KeywordsHotel management Reputation Multi-dimensional scaling Multiple regression analysis
- 1.Uetake, T., Sasaki, I., Aoki, A.: Impact of reputation on revenue management at Hotels. In: 3rd International Tourism and Hospitality Management Conference (ITHMC), International Tourism and Hospitality Management Conference (2017). https://www.ithmc.com/sites/default/files/ithmc_2017_abstract_book_v2.pdf
- 3.Wang, M., Liu, Q., Robert, C., Shi, W.: How word of mouth moderates room price and hotel stars for online hotel booking, an empirical investigation with expedia data. J. Electron. Commer. Res. 16(1), 72–80 (2015)Google Scholar
- 4.Travelko. https://www.tour.ne.jp/. Accessed 27 Mar 2019
- 5.Statistical data on tourist spots and number of visitors. http://www.mlit.go.jp/kankocho/siryou/toukei/irikomi.html. Accessed 27 Mar 2019
- 7.MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297 (1967)Google Scholar