資訊管理學報
林金賢;周世玉;楊良基;謝宇宣;
頁: 395-418
日期: 2021/10
摘要: 近年來我國旅遊市場不斷成長，而自助旅行人次也屢創新高，加上資通訊科技的進步對旅遊市場造成的衝擊，如何針對自由行旅客提出同時符合旅遊動機以及消費者個人特性的旅遊行程，已成為一個重要的議題。本研究嘗試結合決策樹、羅吉斯、及類神經網路等資料探勘技術提出令旅客滿意的行程推薦。實證結果顯示旅遊動機的確可以提高對旅遊行程滿意度的預測能力，而本研究所提出之方法可以排除個人的主觀意識，從過去的旅遊行為中找出特定的旅遊行程，建構旅客旅遊動機、個人特性、與旅遊行程間的函數關係，進一步精準的預測自由行旅客對不同行程的滿意程度。此方法可以讓目的地行銷公司更有效地提供令旅客滿意的行程推薦。
關鍵字: 旅遊動機;旅遊行程;決策樹;羅吉斯葉;類神經葉;
Abstract: With the continuing growth of Taiwan's tourism market in recent years, especially the number of self-guided travelers has repeatedly hit new heights, and the huge impact caused by the advancement of Information and Communication Technology, how to propose a travel itinerary which can both consider the traveler's motives and demographic characteristics is an essential issue. This study is trying to construct a model by combining Decision Trees, Logit, and Neural Network to provide a trip recommendation that could satisfy the self-guided travelers. The empirical results show that travel motives can indeed help increase the prediction accuracy of travel satisfaction. The method proposed in this study can get rid of the individual subjectivity, finding out specific tourism types from travelers' past tourism behaviors. It constructs a relationship among the travelers' motives, personal characteristics, and the tourist attractions to precisely predict the satisfaction of different tourism itineraries for each self-guided traveler. This proposed method can be applied by the destination marketing organization to effectively provide the customers satisfying travel itinerary.
Keywords: Travel motive;travel itinerary;decision trees;logit leaf;neural network leaf;
瀏覽次數: 12845 下載次數: 310
引用 導入Endnote
頁: 395-418
日期: 2021/10
摘要: 近年來我國旅遊市場不斷成長，而自助旅行人次也屢創新高，加上資通訊科技的進步對旅遊市場造成的衝擊，如何針對自由行旅客提出同時符合旅遊動機以及消費者個人特性的旅遊行程，已成為一個重要的議題。本研究嘗試結合決策樹、羅吉斯、及類神經網路等資料探勘技術提出令旅客滿意的行程推薦。實證結果顯示旅遊動機的確可以提高對旅遊行程滿意度的預測能力，而本研究所提出之方法可以排除個人的主觀意識，從過去的旅遊行為中找出特定的旅遊行程，建構旅客旅遊動機、個人特性、與旅遊行程間的函數關係，進一步精準的預測自由行旅客對不同行程的滿意程度。此方法可以讓目的地行銷公司更有效地提供令旅客滿意的行程推薦。
關鍵字: 旅遊動機;旅遊行程;決策樹;羅吉斯葉;類神經葉;
That's How We Play-Using Data Mining Techniques to Design Your Favorite Tour
Abstract: With the continuing growth of Taiwan's tourism market in recent years, especially the number of self-guided travelers has repeatedly hit new heights, and the huge impact caused by the advancement of Information and Communication Technology, how to propose a travel itinerary which can both consider the traveler's motives and demographic characteristics is an essential issue. This study is trying to construct a model by combining Decision Trees, Logit, and Neural Network to provide a trip recommendation that could satisfy the self-guided travelers. The empirical results show that travel motives can indeed help increase the prediction accuracy of travel satisfaction. The method proposed in this study can get rid of the individual subjectivity, finding out specific tourism types from travelers' past tourism behaviors. It constructs a relationship among the travelers' motives, personal characteristics, and the tourist attractions to precisely predict the satisfaction of different tourism itineraries for each self-guided traveler. This proposed method can be applied by the destination marketing organization to effectively provide the customers satisfying travel itinerary.
Keywords: Travel motive;travel itinerary;decision trees;logit leaf;neural network leaf;
瀏覽次數: 12845 下載次數: 310
引用 導入Endnote