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Competing for Amazon's Buy Box: A Machine-Learning Approach

Authors

GÓMEZ LOSADA, ALVARO, Duch-Brown, Nestor

External publication

Si

Means

Lect. Notes Bus. Inf. Process.

Scope

Proceedings Paper

Nature

Científica

JCR Quartile

SJR Quartile

SJR Impact

0.26

Publication date

01/01/2019

ISI

000611408800038

Abstract

A key feature of the Amazon marketplace is that multiple sellers can sell the same product. In such cases, Amazon recommends one of the sellers to customers in the so-called 'buy-box'. In this study, the dynamics among sellers for occupying the buy-box was modelled using a classification approach. Italy's Amazon webpage was crawled during ten months and features from products analyzed to estimate the more relevant ones Amazon could consider for a seller occupy the buy-box. Predictive models showed that the more relevant features are the ratio between consecutive prices in products and their number of assessment received by customers.

Keywords

Buy-box; Amazon; Machine learning; Classification; Data science