I run a SaaS that allows for court bookings. A tennis club has exactly this scenario: club offers 1h, 1.5h and 2h bookings, but 30m start. Since it is a private club and requires a membership, gaming the system is not a real issue. However, they can never be fully booked because of the 30m holes.
They open at 7am so in the mornings bookings are on the hour. Competitive junior athletes start at 2:30pm shifting to half-hour starts in the afternoon. So they mess up their schedule to accomodate them.
The non-optimal solution is to avoid proposing slots that would create 30m holes. For example do not offer 5pm if a booking ends at 4:30pm. We implemented that but it does not solve the fundamental issue. And they don't want to change. Such is life!
Isn't it well-known that Nash equilibria of games are highly sensitive to the modelling? And that seemingly benign modifications can lead to much worse outcomes?
I don't agree with the conclusion here. The issue in the sports court example could just as easily be addressed by adding granularity. If the system allowed users more granularity in the length of their sessions, the undesirable strategies in the post would no longer work.
Agreed. I don't think this is a granularity problem, it's a fragmentation problem.
Users are selecting two data points: start time and duration. The fact that those two points have different granularity is what leads to fragmentation, not the fact that start time is more granular than duration.
It is true, however, that more coarse grained allocation sizes will help minimize fragmentation.
I hate the use of "granular" in a relative context. If water is not granular, and ice cubes are granular, what does it mean for some ice cubes to be more granular than other ice cubes? Are the cubes in question larger or smaller?
I run a SaaS that allows for court bookings. A tennis club has exactly this scenario: club offers 1h, 1.5h and 2h bookings, but 30m start. Since it is a private club and requires a membership, gaming the system is not a real issue. However, they can never be fully booked because of the 30m holes.
They open at 7am so in the mornings bookings are on the hour. Competitive junior athletes start at 2:30pm shifting to half-hour starts in the afternoon. So they mess up their schedule to accomodate them.
The non-optimal solution is to avoid proposing slots that would create 30m holes. For example do not offer 5pm if a booking ends at 4:30pm. We implemented that but it does not solve the fundamental issue. And they don't want to change. Such is life!
Isn't it well-known that Nash equilibria of games are highly sensitive to the modelling? And that seemingly benign modifications can lead to much worse outcomes?
Eg Braess' paradox, Induced traffic/demand, strategic voting, etc.?
I don't agree with the conclusion here. The issue in the sports court example could just as easily be addressed by adding granularity. If the system allowed users more granularity in the length of their sessions, the undesirable strategies in the post would no longer work.
Agreed. I don't think this is a granularity problem, it's a fragmentation problem.
Users are selecting two data points: start time and duration. The fact that those two points have different granularity is what leads to fragmentation, not the fact that start time is more granular than duration.
It is true, however, that more coarse grained allocation sizes will help minimize fragmentation.
I hate the use of "granular" in a relative context. If water is not granular, and ice cubes are granular, what does it mean for some ice cubes to be more granular than other ice cubes? Are the cubes in question larger or smaller?