The Goldilocks Effect in parking was theorized by Donald Shoup in 2005. The Goldilocks principle of paid parking states that the optimal parking occupancy is 15%, and this can be achieved using dynamic pricing strategies.
Most cities can’t provide something basic that every motorist longs for – curb parking spaces, available on-demand. The main reason for this is that the demand for curb parking differs by area and the time of the day.
For instance, it is harder to find an empty curb parking spot around supermarkets or offices. At the same time, it’s much easier to find one in residential areas. It’s always harder to find vacant parking spots around peak hours on weekdays. These are predictable patterns of parking occupancy.
What if we could improve parking availability using dynamic prices for peak hours? Can cities ensure curb parking supply is in sync with demand by vehicle owners?
It’s possible using the Goldilocks Principle, according to UCLA professor, Donald Shoup
What is the Goldilocks Effect?
Professor Don Shoup coined the term ‘the Goldilocks Principle’ in 2005 while researching parking pricing.
He concluded that if 15% of spots remained vacant in a parking space, motorists could easily park without cruising. To achieve this optimal parking occupancy, he suggested implementing dynamic pricing.
If there is a high demand for curb spaces, parking operators should raise fees to tackle demand. Similarly, if there is a low demand for curb spaces, operators should reduce fees to increase demand.
Professor Shoup suggested that optimal parking pricing would bring occupancy to 85%, leaving enough space for motorists looking to park. He also recommended that cities return the excess parking fare collected to their respective districts.
Cities can use these earnings to upgrade infrastructure, improve security, implement street lighting, etc. These are additional benefits in a bid to encourage efficient curbside parking.
Using dynamic pricing to achieve the Goldilocks effect in parking
Many cities have been deploying dynamic pricing to optimize both occupancy and revenue. Parking operators also implement smart parking tools like sensors to understand occupancy trends and make fee adjustments accordingly.
While some cities experiment with parking fees periodically, others use time-of-the day-pricing or surge fees depending on the time of the day.
For instance, here’s how dynamic parking works in Auckland city.
Dynamic parking in Auckland, New Zealand
Auckland implemented a dynamic pricing model citywide in 2012. This is how parking prices change based on occupancy:
- If the average parking occupancy is below 50%, the parking fees are lowered by $1 per hour.
- If occupancy levels are between 50-70%, parking fees are reduced by $0.5 per hour.
- If occupancy levels are between 70-90%, parking fees remain unchanged.
- If occupancy is over 90%, parking fees increase by $0.5 per hour.
For the most part, fee adjustments also depend on several other factors such as the time of operation, peak and off-peak hours, the location, and quarterly or yearly revisions based on data from occupancy surveys.
Optimizing occupancy with smart parking systems
Smart parking systems, equipped with sensors and IoT capabilities can measure lot occupancy and offer insights on parking trends. This also gives authorities access to real-time parking information and helps them strategically implement pricing models. Additionally, automated parking management systems can process and implement complex parking fee configurations easily without any human intervention.
In conclusion, Goldilocks-based parking and dynamic pricing models allow motorists to find available parking spots and help authorities tide over slow parking periods by regulating fees. It’s no surprise that many cities have already implemented the Goldilocks Principle. Many more are planning to join the bandwagon by implementing smart parking systems.
