旅遊體驗社群之決策行為與大數據目標行銷策略

The Big Data Analysis of Decision behavior and Target Marketing Strategy from Travel Experience Community

李宛臻(Wan-Chen Lee)

指導教授 ： 林心慧

國立臺中科技大學/資訊與流通學院/流通管理系碩士班/碩士(2020年)

摘要

隨著經濟的發展及觀光旅遊的開放，即開啟了近 30 多年的台灣觀光旅遊史，使得國人對旅遊越來越重視，逐漸成為生活中不可或缺的一部分，其中，旅遊資訊的豐富多元，大幅降低了自助旅行的門檻，使得自由行已成為近年來觀光旅遊的主要選擇，人們對於旅遊平台的接受度也逐漸提升，更願意在旅遊平台上進行消費，並在體驗後給予評價，其中，不同生活型態的族群對於旅遊內容也都有各自的見解及偏好。
首先，本研究將運用python網路爬蟲技術蒐集訂房網站Booking.com及行程網站Klook的評論，並彙整出各評論的平均分數、字詞的重要性，藉由找出評論內容中的意見領袖，進行情感分析，其次，將根據情感分析結果設計相關問卷之問項，分為行為構面、生活型態構面、評論及人口統計構面，最後，運用SPSS Modeler中的決策樹進行顧客分群，本研究共蒐集了305份問卷，以再購意願、向親友推薦及正向口碑傳遞為依變數，生活型態、評論、人口統計為自變數，將消費者依據特性分為高意願、中意願及低意願。
情感分析結果顯示，消費者在正面住房評論中，對房間內部的乾淨度、舒適度、住宿地點交通的方便性及服務人員的態度較為注重，在負面住房評論中，對房間的舒適度、大小、安靜度及設備較為重視，在正面行程評論中，以領隊/導遊的態度、專業度較為重視，在負面行程評論中，則以領隊/導遊專業度、行程的價值、體驗中的感受較為注重。決策樹分析結果顯示，大多數的消費者在使用旅遊平台後有較高的再購意願，向親友推薦則意願較低，其中又以每年旅遊平均花費為20001~30000元的消費者占多數。本研究將根據上述分析結果，對旅遊平台及旅宿業者提出目標行銷策略上的建議。

關鍵字

旅遊體驗社群 ； 分析 ； 決策樹

並列摘要

With the development of economy and the development of sightseeing tourism, Taiwan has opened up the history of sightseeing tourism for more than 30 years, which makes people pay more and more attention to tourism and become an indispensable part of life. Among them, different life-oriented ethnic groups also have their own views and preferences on tourism content. This study first uses python network crawling technology to compile comments on the Booking.com of the booking website and the itinerary website Klook, and to compile the average scores and the importance of words in each comment. By finding out the opinion leaders in the evaluation content, we carry out emotional analysis. Secondly, we divide the questionnaire of emotion analysis into behavior structure, life style structure, evaluation and population statistics.
Finally, we use the decision-making tree in the SPSS Modeler to carry out customer clustering. This study has collected 305 questionnaires to obtain opinions, promote positive word-of-mouth and forward word-of-mouth change, Life style, evaluation, population statistics are independent variables, according to the characteristics of consumers are divided into high willingness, willingness and low will.
The results of emotional analysis show that consumers pay more attention to the cleanliness, comfort, convenience of accommodation and service personnel in the positive housing evaluation. In the negative housing evaluation, the comfort, size, stability and equipment of the room are more important. In the positive travel evaluation, the attitude and professionalism of the tour guide are more important. Decision tree analysis results show that most consumers have a higher desire to repurchase after using the tourism platform, and lower willingness to push friends and relatives, among which the average annual travel cost is 20001~30000 dollar. According to the results of the above analysis, this study puts forward some suggestions on the target marketing strategy for the tourist platform and the tourist industry.

並列關鍵字

Travel Experience Community ； Sentiment Analytics ； dcision tree

參考文獻

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