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カワイ ユキコ
KAWAI YUKIKO
河合 由起子 所属 京都産業大学 情報理工学部 情報理工学科 職種 教授 |
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| 発行・発表の年月 | 2023 |
| 形態種別 | 研究論文（国際会議プロシーディングス） |
| 査読 | 査読あり |
| 標題 | A User-POI-Guide Cost Optimization Method for Tourism Planning Considering Social Distance and User Preferences |
| 執筆形態 | その他 |
| 掲載誌名 | Proceedings of the Annual Hawaii International Conference on System Sciences |
| 出版社・発行元 | ScholarSpace |
| 巻・号・頁 | 2023-January,4988-4997頁 |
| 著者・共著者 | Da Li,Panote Siriaraya,Yuanyuan Wang,Yukiko Kawai |
| 概要 | MaaS (Mobility as a Service) itself has come into common use, and these developments have attracted keen interest from the industry in recent years. MaaS can be applied as a solution to deal with the current situation by considering the social distance. However, due to the time-share mechanism, personal assets are monopolized by specific users for a long time that cannot be shared with other users at the same time. Thus, the sharing economy companies in the tourism industry (e.g., Airbnb Experience and Huber) are in a dilemma of low productivity and high cost. In this research, we propose a new travel guide sharing service that considers the concept of social distance and user preferences. The user side only needs to select simple conditions such as travel time and the number of POIs (Point of Interest) that she/he plans to visit, meanwhile, the guide side simply inputs the POIs that she/he can guide. Furthermore, by analyzing these basic information, our proposed system can recommend the tour guides, scenic spots, and route planning to provide a real-time tour guide plan, which addressed the user's preferences and reduced the face-to-face communication to users in advance. To verify the effectiveness of our proposed method, we also ask 68 users to evaluate our system and analyze the results of questionnaires. |
| ISSN | 1530-1605 |
| PermalinkURL | https://hdl.handle.net/10125/103245 |
| researchmap用URL | https://dblp.uni-trier.de/rec/conf/hicss/2023 |