定義和比較交付服務的利用率


2

我目前正在研究送餐服務的情況,想知道我的"駕駛員利用"概念是否有意義。

我的數據集包含

的每小時概覽
  1. 活動交付驅動程序的數量,
  2. 他們的在線時間,
  3. 有訂單的送貨司機數量,
  4. 等待送貨的送貨司機的數量
  5. 運送食物的駕駛員數量,
  6. 每個活躍的送貨司機的小時數,
  7. 每在線小時的送貨次數
  8. 該小時已完成的遊樂設施總數,
  9. 看不到交付可用性的用戶,並且
  10. 確實看到交付可用性的
  11. 用戶。

請注意::9.和10.可以重疊(重複計數)。

對於這些類型的信息,您將如何描述"利用率不足/利用率過高"?

5

One possibility is to look at idle time (time a driver spends waiting for the next order). If the drivers are on your payroll (as opposed to working on commission, i.e., doing "gig" work), idle time has a direct cost. If the drivers are gig workers, a relatively even distribution of idle time might be perceived as "fairer" and might contribute to driver retention. (A better measure in the gig case might be driver revenue per hour, adjusted for mileage costs, but your data does not suggest any measure of revenue, or of mileage for that matter.)

If we use idle time, then "under-utilization" ("over-utilization") would mean more (less) idle time per shift than some standard. (The standard would likely be time-dependent, since people are more likely to order food at some times than at others.) You could make the standard either absolute (more than 20 minutes idle per hour is under-utilized, less than 5 minutes per hour is over-utilized) or relative (if you idle time is 1.5 standard deviations below the average for a certain time span, you're over-utilized, etc.), where the standard deviation and mean would be sample-based. Note that the sample-based approach does not detect over- or under-staffing as well as the absolute standard approach (assuming you pick your absolute standards wisely).