Mapping the Landscape of Independent Food Delivery Platforms in the United States
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913280913571840 |
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| author | Liu, Yuhan Liaqat, Amna Zhang, Owen Xingjian Espinosa, Mariana Consuelo Fernández Manjunatha, Ankhitha Yang, Alexander Papakyriakopoulos, Orestis Monroy-Hernández, Andrés |
| author_facet | Liu, Yuhan Liaqat, Amna Zhang, Owen Xingjian Espinosa, Mariana Consuelo Fernández Manjunatha, Ankhitha Yang, Alexander Papakyriakopoulos, Orestis Monroy-Hernández, Andrés |
| contents | Beyond the well-known giants like Uber Eats and DoorDash, there are hundreds of independent food delivery platforms in the United States. However, little is known about the sociotechnical landscape of these ``indie'' platforms. In this paper, we analyzed these platforms to understand why they were created, how they operate, and what technologies they use. We collected data on 495 indie platforms and detailed survey responses from 29 platforms. We found that personalized, timely service is a central value of indie platforms, as is a sense of responsibility to the local community they serve. Indie platforms are motivated to provide fair rates for restaurants and couriers. These alternative business practices differentiate them from mainstream platforms. Though indie platforms have plans to expand, a lack of customizability in off-the-shelf software prevents independent platforms from personalizing services for their local communities. We show that these platforms are a widespread and longstanding fixture of the food delivery market. We illustrate the diversity of motivations and values to explain why a one-size-fits-all support is insufficient, and we discuss the siloing of technology that inhibits platforms' growth. Through these insights, we aim to promote future HCI research into the potential development of public-interest technologies for local food delivery. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_14159 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Mapping the Landscape of Independent Food Delivery Platforms in the United States Liu, Yuhan Liaqat, Amna Zhang, Owen Xingjian Espinosa, Mariana Consuelo Fernández Manjunatha, Ankhitha Yang, Alexander Papakyriakopoulos, Orestis Monroy-Hernández, Andrés Human-Computer Interaction Beyond the well-known giants like Uber Eats and DoorDash, there are hundreds of independent food delivery platforms in the United States. However, little is known about the sociotechnical landscape of these ``indie'' platforms. In this paper, we analyzed these platforms to understand why they were created, how they operate, and what technologies they use. We collected data on 495 indie platforms and detailed survey responses from 29 platforms. We found that personalized, timely service is a central value of indie platforms, as is a sense of responsibility to the local community they serve. Indie platforms are motivated to provide fair rates for restaurants and couriers. These alternative business practices differentiate them from mainstream platforms. Though indie platforms have plans to expand, a lack of customizability in off-the-shelf software prevents independent platforms from personalizing services for their local communities. We show that these platforms are a widespread and longstanding fixture of the food delivery market. We illustrate the diversity of motivations and values to explain why a one-size-fits-all support is insufficient, and we discuss the siloing of technology that inhibits platforms' growth. Through these insights, we aim to promote future HCI research into the potential development of public-interest technologies for local food delivery. |
| title | Mapping the Landscape of Independent Food Delivery Platforms in the United States |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2402.14159 |