線上團購模式預測成團之研究

An Effective Method for Predicting the Success of Group Buying Auctions

鍾孟潔(Meng-Chieh Chung)

指導教授 ： 陳建錦

國立臺灣大學/管理學院/資訊管理學研究所/碩士(2013年)

https://doi.org/10.6342/NTU.2013.02241

摘要

在線上團購中，對買家來說，團購隱含著風險與不確定性。由於買家無法從失敗的團購(流團)得利，因此在決定要加入團購之前，他們會考慮很多因素。過去的文獻裡，許多學者針對這些影響買家決策的因素進行量化研究。學者們探討出各種影響團購決策的因素，儘管如此，只有少部分的研究企圖去量化它們，或者使用它們為團購進行成功(成團)或失敗(流團)的預測。本論文研究此問題，並提出一個能有效預測團購結果(是否成團)的方法。本研究將團購成功與否的預測看作是分類問題，並將前人量化研究得出的相關因素，彙整成五個維度與十二項因子，進一步使用這些因子去預測團購結果。同時使用現實世界團購網的真實資料進行實驗，以證明本方法是有效可行的。而實驗結果顯示，本論文提出的方法在預測的準確率(precision)、召回率(recall)和F值(F1 score)方面皆優於社交傳播模型(social propagation model)。

關鍵字

商業智慧 ； 風險分析 ； 分類

並列摘要

Online group buying involves risks and uncertainties for buyers. Because buyers would not benefit from a failed group buying auction, they usually consider several factors before deciding to join an auction. The factors that affect buyers’ decisions have been qualitatively investigated in the literature. However, few studies have attempted to quantitate the factors, or utilize them to predict an auction’s success. In this paper, we propose an effective method for predicting the success of a group buying auction. We model success prediction as a classification problem, and utilize five dimensions and twelve features derived from previous qualitative research to predict the success of group buying auctions. Experiments based on a real world group buying system demonstrate the efficacy of the proposed method. Moreover, the method outperforms a social propagation model in terms of the prediction precision rate, recall rate, and F1 score.

並列關鍵字

Business Intelligence ； Risk Analysis ； Classification

參考文獻

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