A UBCO study on the popularity of electric scooter rentals in Kelowna found that the service is very well-liked among younger community members.
The study, spearheaded by doctoral student Muntahith Mehadil Orvin, looked at data from July 2019 to October 2019. They developed a forecasting model by exploring key predictors such as time of day, week, season and weather. They also examined transportation, infrastructure, land use and neighbourhood features.
The results are unsurprising: usage was likely to be higher during nicer weather and demand is more likely in places with higher density and a higher ratio of cycle lanes.
Out of the 22,700 shared trips logged into these services, Orvin and his team found that e-scooter services were most utilized on the weekends in July and August. More than 90 per cent of the trips took place near the Okanagan Lake and downtown area, and most trips were in the afternoon and evenings. The majority of the users also tended to be younger, the study found.
“Despite the ongoing popularity of shared e-scooter services globally, there hasn’t been a lot of research into their actual demand—specifically how the demand varies over different times of the day and week across a city,” said Orvin.
Assistant professor Mahmudur Fatmi is not surprised that e-scooters are popular in the city. Smaller cities like Kelowna attracts many visitors each year and is ideal location for micro-mobility solutions.
“Kelowna’s bike infrastructure—combined with its parks and lake access in the flatter portion of the city—are critical elements to attract e-scooter users,” he said. “Such innovative micro-mobility options could be the affordable, equitable and sustainable way to go for short-distance travel.
While the study did not look at the safety of e-scooters, Orvin said his findings will provide important insights for effective policy-making to support e-scooter use in the future.
“Our data clearly illustrates that there is a call for micro-mobility solutions like e-scooters in Kelowna,” said Orvin. “Other similar-sized municipalities considering these type of transportation solutions could benefit by transferring the developed model to their settings to help predict demand over time and space.”