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  • 學位論文

以資料探勘方法探討服務業之顧客區隔及滿意度指標-以大台北地區餐廳為例

Using Data Mining Approach to Analyze Customer Segmentation and Satisfaction Factors in Service Industry- A Case of Taipei Restaurants

指導教授 : 翁頌舜

摘要


餐廳的經營型態和產品易被模仿、替代性高,為有效維持顧客忠誠度,勢必將顧客以不同需求及相異的消費特性、偏好做區隔,並針對不同的顧客群以不同的方式給予服務,才可使顧客達到較高的滿意度,進而鞏固業者的利基市場。 本研究將餐廳視為服務業分析,參考SERVQUAL服務量表,同時參考入口網站針對餐廳的評比項目建構問卷,分析大台北地區餐廳顧客的特性與影響消費滿意度之服務構面。本研究利用Clmentine 12.0軟體,將資料探勘方法運用於問卷資料分析:利用K-means群集分析、Apriori關聯分析、C5.0決策樹分類法分析資料。 本研究發現,當消費者認為該間餐廳性價比高且食材新鮮,願意推薦給他人的意願也會明顯提高;環境方面,最顯著影響滿意度之構面為環境衛生、餐點品質、裝潢用心;人員服務方面,若能迅速回應顧客問題、態度禮貌友善且溝通能力良好,則可讓消費者有較高滿意度。 本研究利用K-means群集分析,區隔出三群消費者特性:女性較男性缺乏對餐廳的忠誠度,大多會選擇新餐廳嘗鮮,且對網路宣傳較有反應;男性消費者對於餐廳在意的面向是容易獲得且偏向價格考量,也就是不須預約且交通方便就能用餐。月收入較高的消費者通常會選擇價格偏高的餐廳,獲得訊息的方式是口耳相傳,並且忠誠度較高。

並列摘要


While restaurant industry offers service through waiters, we consider it as service industry. To segment different customers’ needs, a questionnaire to collect customers’ responses to meals the target restaurants serve is developed. SERVQUAL is referenced for developing the questionnaire. K-means clustering, Apriori association rule and C5.0 decision tree functions of DM software Clementine 12.0 are used to analyze our data and find out the characteristics of each class. This study concludes that the quality of meals, hygiene and decorations of the restaurant influence customers’ satisfaction most toward the environment of the restaurant. On the other hand, service personnel helps raise customers’ overall satisfaction, including attitude (polite or not) and immediate response. Strong satisfaction will lead customers to recommend the restaurant to their friends. Three clusters of customers are also found out. Female customers usually have less loyalty toward experienced restaurant than male do. They always react to recommendations on the internet and are willing to become early adopters. Male customers choose restaurants by the convenient transportation and price. When people have higher income, they usually choose restaurants with higher price. They have highest loyalty among three clusters.

參考文獻


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被引用紀錄


許珉豪(2014)。運用資料探勘技術於航安風險因素分析〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846%2fTKU.2014.01029

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