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Jun 9, 2020 at 21:02 vote accept HubHu
Jun 9, 2020 at 17:08 comment added prubin If the issue is convincing drivers to work during "underserved hours", maybe the thing to look at is the number of available orders per driver, as a function of time. The higher that number is, the more likely a driver is to get an order and the more they are likely to earn per hour, which would be the kind of things that would get my attention if I were a gig driver.
Jun 8, 2020 at 15:52 comment added HubHu @prubin that’s unclear. There’s no info on waiting time for customers. It’s mainly about incentivizing drivers to drive during “underserved” hours. I only know the number of user requests and whether they had delivery slots or not. Users that didn’t have a slot, but got one within the same hour are counted twice.
Jun 8, 2020 at 15:12 comment added prubin Are customers turned away, or is just a question of how long they wait? Do drivers turn down customers, or do they always take assigned deliveries? (There are variables in the gig economy that don't exist with employee-based delivery systems.)
Jun 8, 2020 at 9:11 history edited TheSimpliFire CC BY-SA 4.0
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Jun 8, 2020 at 9:06 comment added HubHu @Richard Multiobjective on driver waiting time being low and number of delivery requests that can't be served being low as well. Or is there a better/easier way?
Jun 7, 2020 at 23:30 comment added Richard Multiobjective on driver idle time and customer wait time? @Hubhu?
Jun 7, 2020 at 22:18 comment added HubHu Thank you for the great response! Is there any approach that would take into account the demand side as well? Since I assume I have to view this from a gig economy business perspective, I wondered whether I could create something that links the customers without delivery slot and the waiting delivery drivers: the higher the difference, the lower the “efficiency” of the service.
Jun 7, 2020 at 21:53 history answered prubin CC BY-SA 4.0