Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/147645
Title: Economic profitability of last-mile food delivery services: Lessons from Barcelona
Author: Alvarez-Palau, Eduard J.  
Calvet Liñán, Laura  
Viu-Roig, Marta  
Gandouz, Mariem
Juan, Angel A.  
Others: Universitat Oberta de Catalunya. Estudis d'Economia i Empresa
Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Universidad Internacional de Valencia
Citation: Alvarez-Palau, E. [Eduard], Calvet-Liñan, L. [Laura], Viu Roig, M. [Marta], Gandouz, M. [Mariem] & Juan Perez, A.A. [Angel A.] (2022). Economic profitability of last-mile food delivery services: Lessons from Barcelona. Research in Transportation Business & Management, 45(Part A). doi: 10.1016/j.rtbm.2021.1006
Abstract: During the last years, the number of digital platforms offering allegedly environmental sustainable last-mile logistics services has been increasing fast all over the world. Their size and geographical spread are growing leaps and bounds. Some studies suggest that they are still operating at losses and relying on venture capital to carry on growing. In this paper we employ real-life data gathered from the largest food delivery platforms (Just Eat, Glovo, and Deliveroo) operating in the city of Barcelona (Spain) to analyse the profitability of these business models. We develop a Monte Carlo simulation model with several scenarios to estimate how many orders are needed to reach economic profitability. Using this simulation model, a second model based on multiple linear regression is built to investigate the relationship between ‘the minimum number of orders required to reach profitability’ and several independent variables, such as the share of the total purchase order or the delivery time-distance. The potential use of this tool for managers is discussed, and several lines of future research on the economical profitability of food delivery operations are highlighted.
Keywords: food delivery operations
last-mile logistics
digital platforms
Monte Carlo simulation
multiple regression models
DOI: http://doi.org/10.1016/j.rtbm.2021.100659
Document type: info:eu-repo/semantics/article
Version: info:eu-repo/semantics/acceptedVersion
Issue Date: 29-Apr-2021
Publication license: https://creativecommons.org/licenses/by-nc-nd/4.0/  
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