Caracterización del fenómeno de «cola larga» en los portales de boca a boca electrónico

María Olmedilla Fernández; Sergio Luis Toral Marín; María del Rocío Martínez-Torres

doi:10.51302/tce.2019.335

Authors

María Olmedilla Fernández Assistant professor de la SKEMA Business School (Francia)
Sergio Luis Toral Marín Catedrático de universidad de la Escuela Técnica Superior de Ingeniería de la Universidad de Sevilla (España)
María del Rocío Martínez-Torres Catedrática de universidad en la Facultad de Ciencias Económicas y Empresariales de la Universidad de Sevilla (España)

DOI:

https://doi.org/10.51302/tce.2019.335

Keywords:

electronic word-of-mouth (eWOM), user generated content, long tail, power law fitting, elbow criterion

Abstract

Online commerce and recommender systems influence the demand for different products. The objective of this paper is to prove if the internet promote super-hits products, niche products or both, and to analyse the coexistence of super-hit effect and long tail phenomenon using a quantitative perspective. Through the analysis of the distribution curve of the actions developed by consumers in the internet in 28 different product categories, the power-law distribution of the number of products (supply factor) through the number of online reviews (demand factor), and the elbow criterion over the case of a power law distribution are proposed to mathematically prove the presence of both phenomena. Data were capture with a crawler designed using Python and an open source web crawler framework called Scrapy. Findings reveal that eWOM promotes both the super-hit and the long tail phenomenon depending on the different product categories, and that they can coexist. As a main managerial implication, the study provides new insights about potential markets that can be open as a result of the tail expansion.

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