以文字探勘技術分析品牌競爭優勢--以美國餐飲外送平台為例
Using Text Mining Technique to Explore Brand Competitive Advantage of the US Online Food Delivery

張艾喆、李胤綺

COVID-19 疫情加速電子商務成長。在疫情較嚴重的美國，為減少接 觸而大量使用網路平台，特別是餐飲外送服務，其中 DoorDash、Uber Eats、 Grubhub 三大外賣平台在 2021 年佔據美國高達 95%的市場占有率。本研究 目的為透過文字探勘技術探究用戶對於美國前三大外送平台之服務產品偏 好及品牌競爭優勢。採用 Python 語言爬蟲程式，擷取 Google Play 商店 App 的網路使用者評論;透過詞頻統計、TF-IDF 與 K-means 演算法，將使用者 評論分群並分析品牌優劣勢。研究建議 DoorDash 應改良收費機制;Uber Eats 應改善、排除折價券無法使用的狀況，或是擬定替代方式;而 Grubhub 則應立即將軟體進行更新，並找出市場機會點來增加品牌的競爭優勢。

Due to the COVID-19 epidemic, people rely on online food delivery (OFD) provides a safe and convenient service to user demands. After fierce competition, the three major food delivery platforms, DoorDash, Uber Eats, and Grubhub, have dominated up to 95% of the market share in the United States in 2021. The research aims to explore user preferences of the top three OFD platforms and analyze their competitive advantages between brands via text mining techniques. Using the Python language to extract online user reviewers of three APPs from Google Play Store by web crawler and cluster user preferences by TF-IDF and K-means methods. The research provides suggestions for the improvement of three brands. DoorDash should reform its charging mechanism. Uber Eats could optimize the function of voucher redemption or develop alternatives. Grubhub must update the software immediately and identify market opportunities to increase its competitive advantage.

文字探勘、分群分析、品牌競爭優勢、網路爬蟲、 餐飲外送平台

Brand Competitive Advantage, Clustering Analysis, Online Food Delivery, Text Mining, Web Crawler

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以文字探勘技術分析品牌競爭優勢--以美國餐飲外送平台為例