Modeling and Analysis of Post-Purchase Intentions Using Partial Least Squares

採用偏最小平方法對購後意向建模並分析

10.29977/JCIIE.200401.0007

張新安(Xin-An Zhang)；田澎(Peng Tian)

購後意向 ； 偏最小平方 ； 重複購買 ； 關聯購買 ； 正面推薦 ； customer ； post-purchase intentions ； partial least squares

工業工程學刊

21卷1期（2004 / 01 / 01）

68 - 74

英文

對於企業來說，隨著市場的不斷成熟以及競爭的加劇，挽留老顧客比爭取新顧客具有更爲重要的意義。傳統的觀點認爲，通過讓顧客滿意即能獲得顧客的忠誠，然而，一些調查結論並不支援這一觀點。有賴於此，本研究直接對顧客購後的三種意向進行研究，通過採用偏最小平方法，從10個可能影響顧客購後意向的因素中選擇出7個作爲引數，建立了購後意向的偏最小平方模型，並以一個實際的電視機品牌爲例，說明了該模型的有效性，並通過分析得到了相應的結論。

The partial least squares (PLS) method is introduced, by which seven causal variables are filtered out from ten contigent ones to predict three kinds of customers' post-purchase intentions. Then, a PLS model is built and its validity and prediction capacity are tested. Some conclusions about loyalty marketing are inferred.

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