休閒產業行銷推薦機制探勘

Mining of Leisure Industry Marketing Recommendation Mechanism

陳盈如(Yin-Ju Chen)；羅健銘(Jian-Ming Lo)

資料採礦 ； 推薦機制 ； 電子口碑行銷 ； data mining ； recommendation mechanism ； electronic word-of-mouth

Electronic Commerce Studies

14卷3期（2016 / 09 / 30）

389 - 407

繁體中文

隨著時代的變遷，資訊科技的進步及消費習慣的改變，大家對生活品質越來越重視，連帶地消費者的生活型態及休閒的習慣也跟著調整。當消費者選擇考慮的因素為簡單的時候，決策者很容易的靠著經驗法則判斷消費者的決定；但是當消費者選擇的種類以及考慮的因素增多的時候，決策者如何從資料分析以及消費者的經驗法則來判斷消費者的行為，儼然變成一個重要的課題。不同於過去關聯規則的演算過程，本研究針對不同的旅遊天數、旅遊目的以及旅遊動機，利用分群後尋找關聯所產生的順序關聯規則組合，經過演算模式的建立、修正及改進，裨益發展推薦機制，輔以現代科技所賜予的便利，進而從電子口碑部分強化並發展觀光。

With the changing times, thanks to the advancing technologies and the changing consumption characteristics, the life style and recreation habit of consumers are keeping changed due to the request of higher quality of life. Contrast to the old time consumers with their simple factors in choosing product that they purchased, nowadays' consumers have far more factors need to be considered before they make their decisions in choosing products. How the business decision makers predicting the behaviors of consumers by data analytics and the rule of thumb has become an important issue. Unlike conventional association rules' process, this study focuses on tourists for their available dates, purpose and motive of touring. Through the association sequence set, which is generated by clustering method, the association rules are found. The model is then developed, with the following improvement. The recommendation mechanism can be established for enhancing the tourism with the aid of modern technology.

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