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Communication Dans Un Congrès Année : 2018

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

Régression statistique et approche open-data pour identifier les indicateurs économiques influençant le commerce électronique

Résumé

— 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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Dates et versions

hal-01790991 , version 1 (14-05-2018)

Identifiants

  • HAL Id : hal-01790991 , version 1

Citer

Apollinaire Barme, Simon Tamayo, Arthur Gaudron. 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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