The Board uses trip data and other data sources to make objective, data-driven, and evidence-based decisions to support a healthy and sustainable passenger transportation industry. The Board is committed to transparency in its data analysis.

The Board has developed 10 indicators that provide insight into factors related to public need and sound economic conditions pertaining to the taxi and TNS sectors in B.C. Each indicator is primarily identified with a public need or sound economic conditions factor, as described in their respective policies in the Board’s Policy Manual.

It is important to understand that each indicator represents only one dimension of the passenger transportation market. To draw larger conclusions about the status of the industry, it will be necessary to consider several indicators in relation to each other.

The Board relies on the advanced economic expertise of its economists and data analysts to ensure quantitative analysis presents an accurate picture of the industry. 

• Learn how the Board makes objective evidence-based decisions.
• Understand more about quantitative analysis.

Service quality factor (PN)

Wait time

Primary Factor: Service Quality as described in the public need policy.

Description: Wait time reflects the duration that passengers wait for vehicles to arrive for pick-up.

Measurement: Wait time for each trip is calculated as the difference between the pick-up arrival time and the hail time. Wait time is measured by the median (i.e., the 50th percentile) of the monthly wait time distribution in an area.

Interpretation: Wait time serves as an indicator of the quality of passenger transportation services. It acts as a market-clearing indication, influenced by factors such as demand, supply, and the efficiency of the technology used to match passengers with vehicles. A longer median wait time indicates reduced service quality, as it suggests longer delays for passengers and higher operating costs for licensees. 

Examples: The Board’s public need policy lists examples of the service quality factor. The relevant examples are set out below alongside their corresponding implications on wait time:

• The proposed service provides more or improved service where there is currently inadequate service.
  • Long wait times suggest an inadequate level of service supplied.
• The proposed service provides more reliable service.
  • Consistently short wait times suggest that the service is reliable.
  • Significant variations in wait times can suggest that the service is not reliable.
  • Consistently long wait times suggest that the service is not reliable.
• The proposed service encourages more efficient service to the public, including trip speed.
  • Wait time is part of the overall time for passengers to complete a trip, so a short wait time contributes to an efficient service.
• The proposed service provides a service that is comfortable and convenient.
  • A short wait time is more likely to contribute to a more comfortable and convenient service.
• The proposed service supports better customer service and customer satisfaction.
  • A short wait time may contribute to better customer service and customer satisfaction.

Limitations: In calculating the median wait time, trips with unreasonably long wait times due to data errors are not included. Trips with wait times above 95th percentile are not reported in the distribution due to data quality concerns.

Sustainability factor (SEC)

Taxi fleet utilization rate

Primary Factor: Sustainability as described in the sound economic conditions policy.

Description: Taxi fleet utilization rate represents the proportion of approved taxi vehicles that are active in an area over a month.

Measurement: The taxi fleet utilization rate is determined by dividing the number of average active vehicles by the total number of approved taxi vehicles in a given area during the reporting period. The number of average active vehicles is determined by data reported to the Trip Database, while the total number of approved taxi vehicles is the maximum fleet size approved by the Board.

Interpretation: A relatively stable taxi fleet utilization rate over time can indicate long-term stability for the taxi sector. On the other hand, a significant decline in fleet utilization rate, other things being equal, may suggest unsustainable economic conditions as licensees choose to operate fewer vehicles in their fleet. 

Examples: The Board’s sound economic conditions policy lists examples of the sustainability factor. The relevant examples are set out below alongside their corresponding implications on taxi fleet utilization rate:

• The proposed service promotes long-term stability for the passenger transportation industry.
  • Significant changes in the fleet utilization rate can signal instability of the passenger transportation industry.
• The proposed service encourages resiliency in the passenger transportation industry.
  • A consistently close-to-full fleet utilization rate may indicate that the industry is at its supply capacity, and unable to meet further demand growth. A consistently low fleet utilization can indicate a lack of growth of the industry.
• The proposed service minimizes significant market disruption.
  • A significant change in the fleet utilization rate can signal market disruption.
• The proposed service protects the taxi sector from rapid disruption to ensure its long-term stability as an essential service.
  • Frequent spikes to close-to-full fleet utilization indicates the supply of the industry is unable to adapt to market disruptions.
• The proposed service promotes overall profitability and economic sustainability of the industry.
  • Close-to-full fleet utilization rates can indicate licensees are unable meet demand to maintain and grow their profit margin.
  • A consistent reduction in the fleet utilization rate can indicate deteriorating profit margins.