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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/85899


    Title: 以商機分析理論應用於iPhone之研究;The application of opportunity algorithm on iPhone
    Authors: 廖品晴;Liao, Pin-Ching
    Contributors: 企業管理學系
    Keywords: 關鍵屬性;商機演算法
    Date: 2021-07-22
    Issue Date: 2021-12-07 11:39:50 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 以前的研究基於問卷和訪談進行客戶調查,然後利用調查數據來分析產品特性。近年來,消費者積極地在網路上發表評論,其中評論內容有大量關於客戶意見和期望的訊息。然而,之前的研究未能解決使用詞級別的分析而難以識別潛在的產品特徵以及對已識別產品的機會潛力分析考慮不足的問題。據此,本研究提出了一種機會挖掘方法,以線上評論數據的關鍵屬性和情感分析找出產品機會。對於多功能產品,這種方法可以識別產品客戶在網路上討論的潛在產品屬性,從而量化每個產品關鍵屬性的重要性。接下來,使用情感分析評估每個產品關鍵屬性的滿意度。最後,透過產品主題的重要性和滿意度以機會算法從客戶為中心的角度識別每個產品關鍵屬性的機會價值和改進方向,在快速發展的產品環境中分析不斷變化的客戶需求。

    關鍵字:關鍵屬性、商機演算法
    ;Previous research conducted customer surveys based on questionnaires and interviews, and then used survey data to analyze product characteristics. In recent years, consumers have actively posted comments on the Internet, and the comments contained a lot of information about customer opinions and expectations. However, previous research failed to solve the problem of using term-level analysis to identify potential product features and insufficient consideration of the opportunity potential analysis of identified products. Based on this, this research proposes an opportunity mining method to find product opportunities based on the key attributes of online review data and sentiment analysis. For multi-functional products, this method can identify potential product attributes discussed by product customers on the Internet, thereby quantifying the importance of each product’s key attributes.
    Next, use sentiment analysis to evaluate the satisfaction of each product′s key attributes. Finally, through the importance and satisfaction of the product theme, the opportunity algorithm identifies the opportunity value and improvement direction of each key attribute of the product from a customer-centric perspective, and analyzes the ever-changing customer needs in the fast-developing product environment.
    Appears in Collections:[Graduate Institute of Business Administration] Electronic Thesis & Dissertation

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