Transit Mode Report Summary

Mode report provides a mode-level overview of transit spending, service delivery and cost-effectiveness using NTD data. Rather than comparing individual agencies, the analysis summarizes patterns across transit modes and broader mode groups. Related modes are grouped to facilitate interpretation for some analysis - for example Bus includes modes such as Bus, BRT, Commuter Bus and Trolley Bus, while Rail includes modes such as Commuter Rail, Heavy Rail, Light Rail and StreetCar. The remaining modes are grouped into Others. The analysis considers expenditure trends, spending composition, service intensity, operating costs, farebox recovery, fare revenue, and fleet utilization to describe differences in how transit services are funded and delivered.

1. Trend and Composition¶

1.1 Ridership, OPEX, CAPEX, VRH and VRM Trend¶

This chart shows trends in transit ridership, operating expenditures, capital expenditures, and service levels across California transit agencies, disaggregated by mode group (Bus, Rail, and Other). It provides a high-level overview of how passenger demand, transit spending, and service delivery have changed over time.

The measures represent aggregate totals across reporting agencies within each mode group, rather than average agency-level values. Expenditure measures are adjusted for inflation and expressed in 2024 dollars.

How to read the chart

• X-axis: Reporting Years.

• Y-axis: Represents the value of the selected measure: Unlinked Passenger Trips, Operating Expenditures, Capital Expenditures, Vehicle Revenue Hours, or Vehicle Revenue Miles.

• Trend: Changes over time indicate whether total ridership, spending, or service delivery within each mode group is increasing or declining.

• Comparison: Differences in the movement of these measures highlight periods when passenger demand, financial investment, and service delivery have diverged or moved together.

1.2 Capital and Operating Expenditures by Mode Group Over Time¶

This chart shows how operating expenditures and capital expenditures are distributed across transit mode groups from 2019 to 2024. Each bar represents the total expenditure for a mode group in a given year, with the stacked segments showing the share attributable to OPEX and CAPEX.

How to read the chart

• X-axis: Shows year, with bars grouped by mode group.

• Y-axis: Shows each expenditure type as a share of total expenditure (%), ranging from 0% to 100%.

• Composition: The relative size of each colored segment shows the share of CAPEX or OPEX within the mode group’s total expenditure for that year.

• Trend: Changes in the composition over time show whether a mode group’s spending has shifted toward operating or capital expenditures.

• Comparison: Differences in the OPEX and CAPEX shares across mode groups highlight differences in how transit spending is allocated.

1.3 Expenses Breakdown by Mode for Latest NTD Year¶

These two stacked bar charts show the composition of operating and capital expenditures across transit mode groups in 2024. The charts show how each mode group allocates its total expenditures across different spending components. Because the bars are normalized, the focus is on the relative share of each component rather than the absolute amount spent.

How to read the chart

• X-axis: Shows mode group.

• Y-axis: Shows each expenditure component as a share of total expenditures (%), with each bar totaling 100%.

• OPEX: Components include Vehicle Operations, Vehicle Maintenance, Non-Vehicle Maintenance, and General Administration.

• CAPEX: Components include Rolling Stock, Facilities, and Other Expenditures.

• Composition: The relative size of each segment shows the share of total OPEX or CAPEX allocated to that component within a mode group.

• Comparison: Differences in segment sizes across mode groups highlight how spending composition varies across transit modes.

2. Efficiency/ Performance¶

Efficiency and performance evaluate how transit modes use their operating and capital resources. The analysis looks at spending concentration, spending per capita, and year-to-year spending volatility, while also comparing operating costs per vehicle revenue hour, vehicle revenue mile, and passenger trip. Together, these measures show how much agencies spend, how consistently they spend, and how efficiently spending is translated into transit service and passenger trips.

2.1 Mode Performance (Herfindahl-Hirschman Index, Spending Per Capita and Volatility)¶

The OPEX and CAPEX scorecards compare transit mode groups across three measures: expense concentration, spending per capita, and spending volatility. Together, they show how spending is distributed, the level of spending relative to population, and how much spending changed from the previous year.

How to read the chart

• Measures: Each scorecard shows Expense Concentration, Spending per Capita, and Spending Volatility.

• Expense Concentration: Measured using the Herfindahl-Hirschman Index (HHI). Higher values indicate that spending is concentrated in fewer expenditure components, while lower values indicate a more evenly distributed spending composition.

• Spending per Capita: Shows operating or capital expenditure relative to the population of the service area.

• Spending Volatility: Shows the average absolute year-over-year change in spending. The 2024 scorecards compare spending in 2024 with 2023; higher values indicate larger changes in spending.

• Bars: Each bar represents a transit mode group. The highlighted bar represents the mode group with the highest value for that metric.

• Comparison: Values should be compared within each metric because the three measures use different units and scales.

2.2 Cost-Efficiency by Mode¶

This heatmap compares operating cost efficiency across transit modes in 2024 using operating expenditure per Vehicle Revenue Hour (VRH), Vehicle Revenue Mile (VRM), and Unlinked Passenger Trip (UPT). Each metric is standardized separately using a z-score and reverse-scaled so that lower relative costs indicate greater cost efficiency.

How to read the chart

• Rows: Each row represents a transit mode.

• Columns: Each column represents a cost-efficiency measure: OPEX per VRH, OPEX per VRM, or OPEX per Trip.

• Color: Blue indicates relatively lower cost and greater cost efficiency, while red indicates relatively higher cost. Values near the midpoint represent costs closer to the mode average.

• Standardization: Each column is standardized separately using a z-score, so the colors show how each mode compares with other modes for that metric.

• Interpretation: Because each column is standardized independently, colors should be compared within each column, not across columns.

• Cost per VRH: Operating expenditure associated with each hour of revenue service.

• Cost per VRM: Operating expenditure associated with each revenue-generating vehicle mile.

• Cost per Trip: Operating expenditure associated with each unlinked passenger trip.

2.3 Cost per VRH: Variation Within Each Mode¶

This box plot shows the distribution of operating expense per Vehicle Revenue Hour (VRH) across California agencies within each transit mode in 2024. Unlike the mode-level averages shown in the previous chart, this view shows how much costs vary between individual agencies operating the same mode. Multiple service records belonging to the same agency and mode are aggregated before calculating cost per VRH, so each agency contributes one observation per mode. Modes are ordered by their median cost, and the number of agencies included in each mode is shown as (n=...).

How to read the chart

• X-axis: Shows operating expense per Vehicle Revenue Hour (VRH). Values farther to the right indicate higher operating costs per hour of revenue service.

• Y-axis: Shows transit mode. Modes are ordered from higher to lower median cost.

• Box: Represents the middle 50% of agencies in a mode, from the 25th percentile to the 75th percentile. A wider box indicates greater variation in costs among the agencies in that mode.

• Median: The dark line inside the box represents the median cost. Half of the agencies have costs below this value and half have costs above it. The median is used to represent the typical agency because it is less affected by unusually high or low costs than an average.

• Whiskers: Extend beyond the box to the lowest and highest observations that fall within 1.5 × IQR of the lower and upper quartiles. They represent the typical range of agency costs within the mode.

• Dots: Represent outliers beyond the whiskers. These agencies have unusually high or low costs compared with other agencies in the same mode.

• Overall spread: The position of the box shows the typical cost level for a mode, while the width of the box and length of the whiskers show how much costs vary across agencies.

3. Cost-effectiveness¶

Cost-effectiveness examines how effectively transit modes generate fare revenue relative to their operating costs. It uses farebox recovery, fare revenue per passenger trip, and net subsidy per trip to show how much of the cost is supported by fares and how much subsidy is required. The indexed comparison of operating costs and fare revenue from 2019 onward also shows whether expenses and fare revenue have grown at similar or different rates over time.

3.1 Farebox Recovery Ratio by Mode¶

This ridge plot shows the distribution of Farebox Recovery Ratio across transit modes in California in 2024. Farebox Recovery Ratio represents the share of operating expenses covered by fare revenue. The chart shows both the typical level of farebox recovery and the variation across agencies within each mode.

How to read the chart

• X-axis: Shows Farebox Recovery Ratio. Higher values indicate a greater share of operating expenses covered by fare revenue.

• Ridges: Each ridge represents the distribution of farebox recovery ratios across agencies within a transit mode.

• Peak: Indicates where observations are most concentrated within a mode.

• Spread: A wider ridge indicates greater variation in farebox recovery ratios across agencies, while a narrower ridge indicates more similar values.

• Density: The height of a ridge represents the relative concentration of observations at a given recovery ratio. Because density is normalized within each mode, ridge height should not be used to compare the number of agencies across modes.

3.2 Cost Effectiveness Matrix¶

This heatmap compares the cost-effectiveness of different transit modes in 2024 using Farebox Recovery, Fare Revenue per Trip, and Net Subsidy per Trip. Each metric is standardized separately using a z-score, with the scale oriented so that higher fare-related values and lower subsidy requirements indicate greater cost-effectiveness.

How to read the chart

• Rows: Each row represents a transit mode.

• Columns: Each column represents a cost-effectiveness measure: Farebox Recovery, Fare Revenue per Trip, or Net Subsidy per Trip.

• Color: Blue indicates relatively greater cost-effectiveness, while red indicates relatively lower cost-effectiveness. Values near the midpoint represent results closer to the mode average.

• Standardization: Each column is standardized separately using a z-score, so colors show how each mode compares with other modes for that metric.

• Direction: For Farebox Recovery and Fare Revenue per Trip, higher values are more favorable. For Net Subsidy per Trip, the scale is reversed because lower subsidy requirements are more favorable.

• Interpretation: Because each column is standardized independently, colors should be compared within each column, not across columns.

3.3 Operating Costs vs. Fare Revenue, Indexed to 2019¶

This chart compares how operating expenses and fare revenue have changed relative to their 2019 levels across transit mode groups. Both measures are indexed to 2019 = 100, which puts them on a common scale and makes their growth rates directly comparable even though their actual dollar amounts are very different. Each panel represents a transit mode group, with separate lines for operating expenses and fare revenue.

Using a common base year makes it easier to see whether fare revenue has kept pace with changes in operating expenses. For example, if operating expenses rise to 150 while fare revenue rises to 120, operating expenses have grown by 50% since 2019 while fare revenue has grown by 20%.

How to read the chart

• X-axis: Shows year, starting from the 2019 base year.

• Y-axis: Shows the indexed value, where 2019 = 100. A value of 120 means the measure is 20% higher than in 2019, while a value of 80 means it is 20% lower.

• Lines: Blue represents Operating Expenses; orange represents Fare Revenue.

• Index: Each year’s value is divided by that mode group’s value in 2019 and multiplied by 100. This sets both measures to the same starting point, allowing their relative growth to be compared.

• Gap between lines: A widening gap indicates that operating expenses and fare revenue are growing at different rates. If the operating expense line is above the fare revenue line, expenses have grown faster relative to 2019.

• Convergence: Lines moving closer together indicate that the relative growth rates of operating expenses and fare revenue are becoming more similar.

• Important: The indexed values show relative change since 2019, not actual dollar amounts. Two mode groups can have the same index while having very different levels of spending or fare revenue.

4. Service Effectiveness¶

Service effectiveness focuses on how efficiently transit resources are converted into passenger service and how intensively the fleet is used. By comparing operating costs with passenger trips per vehicle mile and hour, the analysis shows the relationship between service costs and passenger utilization. Fleet utilization and operating speed provide additional insight into how intensively vehicles are used and how quickly service is delivered.

4.1 Operating Efficiency: Cost vs. Service Utilization and Service Intensity¶

These scatter plots examine the relationship between operating cost and passenger utilization across transit mode groups. Each observation represents one agency-mode combination, with multiple service records aggregated before calculating efficiency metrics. The VRM-based chart relates costs and passenger trips to the amount of service provided in miles, while the VRH-based chart uses hours of service. Both axes are shown on a log10 scale to make differences across agencies easier to visualize when values vary substantially.

How to read the chart

• X-axis: Shows operating expense per Vehicle Revenue Mile (VRM) in the VRM-based chart and operating expense per Vehicle Revenue Hour (VRH) in the VRH-based chart. Values increase from left to right.

• Y-axis: Shows passenger trips per VRM in the VRM-based chart and passenger trips per VRH in the VRH-based chart. Values increase from bottom to top.

• Colors: Each color represents a mode group.

• Point size: Represents total Unlinked Passenger Trips (UPT). Larger points indicate more passenger trips.

• Log scale: Both axes use log10 scaling. A fixed distance on an axis represents a multiplicative change rather than a fixed numerical change.

• Position: Points toward the upper-right have both higher operating costs per unit of service and higher passenger utilization per unit of service, while points toward the lower-left have lower values for both.

• VRM-based chart: Evaluates cost and passenger utilization relative to the amount of service provided in miles.

• VRH-based chart: Evaluates cost and passenger utilization relative to the amount of service provided in hours.