Food Delivery Platform in the United Kingdom: The Flexible Matching of Deliveroo
- DOI
- 10.2991/978-2-494069-31-2_137How to use a DOI?
- Keywords
- matching algorithm; online platform; food-delivery workers; Deliveroo; piece wage
- Abstract
With the development of the Internet, online platforms are changing our daily life. Especially, the food delivery platform, like Deliveroo, is leading a new trend of gig economy. There is no denying that Deliveroo provides abundant jobs every year and has mature operating mechanism, but excessive automation leads to some problems, like inefficient matching process since dishonesty by riders, unreasonable work intensification and the irresponsible actions to workers by the platform. Based on the existing matching algorithm between riders and orders and salary system in Deliveroo, this paper mainly focuses on the matching algorithm of Deliveroo, and finds that current situation is not friendly to riders even influence the working performances. This paper discusses the existing problems and puts forward some suggestions to improve this situation, so as to make the work environment be more friendly to riders and improve people’s life to be more convenient.
- Copyright
- © 2022 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Qiushi Yao PY - 2022 DA - 2022/12/29 TI - Food Delivery Platform in the United Kingdom: The Flexible Matching of Deliveroo BT - Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022) PB - Atlantis Press SP - 1176 EP - 1180 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-494069-31-2_137 DO - 10.2991/978-2-494069-31-2_137 ID - Yao2022 ER -