| dc.description.abstract | The impact of COVID-19 on Oslo bicycle sharing system was analyzed in this thesis. Weather data in
the form of temperature, precipitation and wind speed, and calendar event factor (whether the day,
when the ride was taken, was workday or weekend) were used as explanatory variables to assess
shared bikes usage. Independent variables were chosen using LASSO shrinkage method. Response
variables were daily rides and average trip duration. Predictions of sharing system usage, if no
COVID happened, were made using generalized additive model. Afterwards, predictions and actual
values were compared to estimate the effect of COVID-19 on Oslo system and suggestions for
improvements of Oslo City Bike were given.
Weather data and bicycle usage data were obtained from the open sources managed by the official
providers of this information such as Norwegian Meteorological Institute and Oslo City Bike
respectively. R was used to analyze this pool of data. Data were divided for train (pre pandemic
period) and test (pandemic period).
Based on conducted analysis, it was concluded that overall daily rides on shared bikes in Oslo
decreased and average trip duration increased due to COVID-19. Number of rides also could have been
affected by the appearance of massive amount of electric scooters on the streets of Oslo in
2019-2021.
Oslo bicycle sharing system was able to satisfy the decreased aggregate demand for rides, but in
terms of satisfying the demand for longer trips the supply side was limited to Ring 3 (road #150)
of Oslo. This could be improved by rearranging placements of existing stations at a lower total
cost or by expanding the bicycle sharing system’s coverage area with new bikes and new stations at
a higher total cost. | en_US |
