Statistic regression and open data approach for identifying economic indicators that influence e-commerce

Abstract : — This paper presents a statistical approach to identify explanatory variables linearly related to e-commerce sales. The proposed methodology allows specifying a regression model in order to quantify the relevance between openly available data (economic and demographic) and national e-commerce sales. The proposed methodology consists in collecting data, preselecting input variables, performing regressions for choosing variables and models, testing and validating. The usefulness of the proposed approach is twofold: on the one hand, it allows identifying the variables that influence e-commerce sales with an accessible approach. And on the other hand, it can be used to model future sales from the input variables. Results show that e-commerce is linearly dependent on 11 economic and demographic indicators.
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Communication dans un congrès
20th International Conference on Urban Transportation and City Logistics, May 2018, London, United Kingdom
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Soumis le : lundi 14 mai 2018 - 11:30:09
Dernière modification le : lundi 12 novembre 2018 - 11:02:46
Document(s) archivé(s) le : mardi 25 septembre 2018 - 12:07:47

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Apollinaire Barme, Simon Tamayo, Gaudron Arthur. Statistic regression and open data approach for identifying economic indicators that influence e-commerce. 20th International Conference on Urban Transportation and City Logistics, May 2018, London, United Kingdom. 〈hal-01790991〉

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