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- W4285606935 abstract "With the increasing popularity of food delivery platforms, it has become pertinent to look into the working conditions of the 'gig' workers in these platforms, especially providing them fair wages, reasonable working hours, and transparency on work availability. However, any solution to these problems must not degrade customer experience and be cost-effective to ensure that platforms are willing to adopt them. We propose WORK4FOOD, which provides income guarantees to delivery agents, while minimizing platform costs and ensuring customer satisfaction. WORK4FOOD ensures that the income guarantees are met in such a way that it does not lead to increased working hours or degrade environmental impact. To incorporate these objectives, WORK4FOOD balances supply and demand by controlling the number of agents in the system and providing dynamic payment guarantees to agents based on factors such as agent location, ratings, etc. We evaluate WORK4FOOD on a real-world dataset from a leading food delivery platform and establish its advantages over the state of the art in terms of the multi-dimensional objectives at hand." @default.
- W4285606935 created "2022-07-16" @default.
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- W4285606935 date "2022-07-01" @default.
- W4285606935 modified "2023-10-10" @default.
- W4285606935 title "AgriBERT: Knowledge-Infused Agricultural Language Models for Matching Food and Nutrition" @default.
- W4285606935 doi "https://doi.org/10.24963/ijcai.2022/711" @default.
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