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- W2770675679 abstract "The E-commerce industry is growing year on year in double digits. But customers today are not only buying more through their computers, they are also returning more. The volume of these returns is such that it just can't be ignored. E-tailers today are following many practices to handle these returns but the ‘predictability' factor is still missing from their approaches. This paper tries to fulfill that void. The framework suggested in this paper will help the E-tailers to predict the probability of a particular item being returned by a particular shopper. The idea is that if the E-tailer will know the probability of return during any transaction he/she would certainly be better equipped to handle the situation." @default.
- W2770675679 created "2017-12-04" @default.
- W2770675679 creator A5036699659 @default.
- W2770675679 date "2018-01-01" @default.
- W2770675679 modified "2023-09-23" @default.
- W2770675679 title "Predicting Online Returns" @default.
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- W2770675679 doi "https://doi.org/10.4018/978-1-5225-3056-5.ch010" @default.
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