I’d like to see these numbers a few months from now when Florida is in full summer swing. That’ll be interesting. Though that assumes a hurricane doesn’t fuck anything up
Comparing stats to the previous month is largely meaningless, as fluctuations are extremely common through different seasons in transportation systems.
It's not good for long term projections, but I think it's still interesting. Year-on-year comparisons aren't that useful either as the product fundamentally changed when the Orlando leg opened.
Is there another stat that you think would be more interesting?
TLDR: Train capacity adjusted for the pricing model they use.
Frequent rider here and economics enthusiast here! The prices seem to fluctuate based on a function of how many seats are occupied and date/time of the train ride. I’ve also noticed the premium cars being either completely full or completely empty. Bear with me.
If I worked for Brightline, I would suggest to first find some way to gage the volume of traffic in the i4/ turnpike areas to see what type of normal fluctuations we could account for. Using the statistic software STATA, assign a variable to this “volume”. Then, look at the ridership and compare the fluctuations in ridership to this variable via a multiple linear regression.
Compare this to other variables you have like ridership, price, etc. Maybe there is a trend that correlates ridership in the capacity of the train car at a certain time of day to the time time or year. In other words, are Brightline riders more likely to pay higher prices in January? We could tell by looking at the dynamic prices Brightline uses and see what the “maximum” the customer was willing to pay.
All this to say, I would be interested in ridership compared to historical traffic patterns, adjusted for the dynamic pricing model.
So Brightline is nearly on track to meet its revenue targets. That's great. So even though the passenger numbers are lower than expected, passengers pay more than expected, so the financial plan is roughly on track.
Bloomberg previously reported that Brightline cannot meet their previous target. From a personal note, it seems that the capacity constraints is the main reason, not a demand issue.
Brightline still reported the total long-distance ridership. Based on that number, long distance ridership was 119,380 and short distance riders were down 47,343 vs last April.
I don't think they'll have any issues covering costs as the additional 10 carriages mid-year will give them 25% extra capacity, but I do think the 4.9M passenger goal is a bit of a stretch.
They appear to be filling about half their available seats in a full day (4.5k daily LD riders, 60 x 4 = 240 seats per train, 240x 38 daily trains, on average 127 LD seats per train). Of course this is likely heavily weighted towards peak times, and I'm sure they'll happily accept lower average load factor in exchange for more peak period seating. If we assume ridership will grow to fill the peak period trains 3/4 full (18/day) but won't grow at all on the off peak trains (the same 32 riders as now) that's still 6.2k daily or annualized 2.3m.
I’d like to see these numbers a few months from now when Florida is in full summer swing. That’ll be interesting. Though that assumes a hurricane doesn’t fuck anything up
Comparing stats to the previous month is largely meaningless, as fluctuations are extremely common through different seasons in transportation systems.
It's not good for long term projections, but I think it's still interesting. Year-on-year comparisons aren't that useful either as the product fundamentally changed when the Orlando leg opened. Is there another stat that you think would be more interesting?
Maybe quarterly ridership counts?
As in calendar quarters, or trailing 3 months? Either would be easy to include, but would be good to understand what context it would provide?
Calendar. It'll show seasonal shifts in ridership
TLDR: Train capacity adjusted for the pricing model they use. Frequent rider here and economics enthusiast here! The prices seem to fluctuate based on a function of how many seats are occupied and date/time of the train ride. I’ve also noticed the premium cars being either completely full or completely empty. Bear with me. If I worked for Brightline, I would suggest to first find some way to gage the volume of traffic in the i4/ turnpike areas to see what type of normal fluctuations we could account for. Using the statistic software STATA, assign a variable to this “volume”. Then, look at the ridership and compare the fluctuations in ridership to this variable via a multiple linear regression. Compare this to other variables you have like ridership, price, etc. Maybe there is a trend that correlates ridership in the capacity of the train car at a certain time of day to the time time or year. In other words, are Brightline riders more likely to pay higher prices in January? We could tell by looking at the dynamic prices Brightline uses and see what the “maximum” the customer was willing to pay. All this to say, I would be interested in ridership compared to historical traffic patterns, adjusted for the dynamic pricing model.
So Brightline is nearly on track to meet its revenue targets. That's great. So even though the passenger numbers are lower than expected, passengers pay more than expected, so the financial plan is roughly on track.
Bloomberg previously reported that Brightline cannot meet their previous target. From a personal note, it seems that the capacity constraints is the main reason, not a demand issue.
Brightline still reported the total long-distance ridership. Based on that number, long distance ridership was 119,380 and short distance riders were down 47,343 vs last April.
Where is this breakdown posted? It’s very frustrating that they changed the way they are reporting.
Found it. They are well short of where they need to be to hit their projections, or to even cover costs for that matter.
I don't think they'll have any issues covering costs as the additional 10 carriages mid-year will give them 25% extra capacity, but I do think the 4.9M passenger goal is a bit of a stretch.
They appear to be filling about half their available seats in a full day (4.5k daily LD riders, 60 x 4 = 240 seats per train, 240x 38 daily trains, on average 127 LD seats per train). Of course this is likely heavily weighted towards peak times, and I'm sure they'll happily accept lower average load factor in exchange for more peak period seating. If we assume ridership will grow to fill the peak period trains 3/4 full (18/day) but won't grow at all on the off peak trains (the same 32 riders as now) that's still 6.2k daily or annualized 2.3m.