Evidence of opacity, datafication and nudging at PickMe
| Representative data | Second-order themes | Aggregate dimensions |
|---|---|---|
| “If their proper amounts are charged, and the app works properly’ then yes, we can give a good service too. Now we don’t know until the hire finishes how much we will get. They won’t show it in a meter. And these apps don’t show it” (D14) | Opacity in fare | Opacity |
| “Most people put the location near a road, understood? So, the remaining distance does not count because the location is actually further down. Now even though they say PickMe amount changes according to the distance it doesn’t happen. Then when that happens, even we get mad” (D14) | ||
| “There are some customers who don’t know what PickMe is. When we tell that, ‘Sir, your location is not clear, can you tell me the exact location where you are,’ and they say ‘no, the location is accurate, check and come.’ When we get there, the location is completely wrong” (D7) | Opacity to the location | |
| “From what I understand, success is based on how the customer rates you. Only if they rate us, we become successful” (D1) | Performance reduced to customer feedback rating | Datafication of the workplace |
| “Q: Do you think your rating reflects the service you offer your customers? A: Yes, I do what the customers ask of me” (D18) | ||
| “We work according to what the customer wants. When this happens, especially in PickMe there’s something called a rating and the more these five stars reduce, the less hires we get. Those who have more ratings get more hires…. If someone puts a Bad rating, our rating reduces drastically” (D14) | ||
| “Some customers wrongly enter the location and then argue about the cost. The cost is calculated through the app. And we incur losses. Then they give feedback that we were unruly or were argumentative. Then the company blocks our access to the app” (D22) | Work sanctions based on one data point |
| Representative data | Second-order themes | Aggregate dimensions |
|---|---|---|
| Opacity in fare | Opacity | |
| “Most people put the location near a road, understood? So, the remaining distance does not count because the location is actually further down. Now even though they say PickMe amount changes according to the distance it doesn’t happen. Then when that happens, even we get mad” (D14) | ||
| “There are some customers who don’t know what PickMe is. When we tell that, ‘Sir, your location is not clear, can you tell me the exact location where you are,’ and they say ‘no, the location is accurate, check and come.’ When we get there, the location is completely wrong” (D7) | Opacity to the location | |
| “From what I understand, success is based on how the customer rates you. Only if they rate us, we become successful” (D1) | Performance reduced to customer feedback rating | Datafication of the workplace |
| “ | ||
| “We work according to what the customer wants. When this happens, especially in PickMe there’s something called a rating and the more these five stars reduce, the less hires we get. Those who have more ratings get more hires…. If someone puts a Bad rating, our rating reduces drastically” (D14) | ||
| “Some customers wrongly enter the location and then argue about the cost. The cost is calculated through the app. And we incur losses. Then they give feedback that we were unruly or were argumentative. Then the company blocks our access to the app” (D22) | Work sanctions based on one data point |
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