Data of collaborative consumption in online food delivery services

Miguel A. Segura; Juan C. Correa

doi:10.1016/j.dib.2019.104007

Data of collaborative consumption in online food delivery services

Miguel A. Segura, Juan C. Correa^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

This data article contains data regarding the collaborative consumption that takes place in an Online Food Delivery Platform that connects restaurants owners, and customers who wish to order meals and receive them at home or office. These data are associated with the article “Evaluation of Collaborative consumption of food delivery services through web mining techniques” [1]. These data are stored in a comma separated value format; that can be easily downloaded from a Mendeley data repository (https://data.mendeley.com/datasets/m9z9hw4nsc/1).

Original language	English
Article number	104007
Pages (from-to)	104007
Journal	Data in Brief
Volume	25
DOIs	https://doi.org/10.1016/j.dib.2019.104007
Publication status	Published - Aug 2019
Externally published	Yes

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Publisher Copyright:
© 2019 The Author(s)

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abstract = "This data article contains data regarding the collaborative consumption that takes place in an Online Food Delivery Platform that connects restaurants owners, and customers who wish to order meals and receive them at home or office. These data are associated with the article “Evaluation of Collaborative consumption of food delivery services through web mining techniques” [1]. These data are stored in a comma separated value format; that can be easily downloaded from a Mendeley data repository (https://data.mendeley.com/datasets/m9z9hw4nsc/1).",

author = "Segura, {Miguel A.} and Correa, {Juan C.}",

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AB - This data article contains data regarding the collaborative consumption that takes place in an Online Food Delivery Platform that connects restaurants owners, and customers who wish to order meals and receive them at home or office. These data are associated with the article “Evaluation of Collaborative consumption of food delivery services through web mining techniques” [1]. These data are stored in a comma separated value format; that can be easily downloaded from a Mendeley data repository (https://data.mendeley.com/datasets/m9z9hw4nsc/1).

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Data of collaborative consumption in online food delivery services

Abstract

Bibliographical note

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