ANLY482 AY2017-18T2 Group08 : Project Overview / Methodology
| Description | Data | Methodology |
Methodology
Limitations
oBike is a relatively new company and as such, they do not yet have extensive data collection measures in place. Consequently, we are only provided LTA ticket issuance data for the period of November to December 2017 and often, data from the last quarter of the year tends to differ from the rest as it clashes with the holiday season. This hinders our analysis as it becomes difficult to analyse and forecast annual trends. To help overcome this, our team will put forth a request to obtain data from May 2017 onwards, as well as upcoming months i.e. January/February 2018.
Nevertheless, given that the bike-sharing industry is relatively new in Singapore, it is highly volatile in nature. Ergo, older data might not be very representative of existing trends. Thus, the use of the most recent data for analysis, forecasting and prescriptive measures might be more suitable for such an industry.
Further, upon reviewing the data, we observe that ‘# of Bikes’ column has a significant amount of missing values. oBike has explained that this occurs because LTA does not always inform them of the exact number of bicycles included in each parking ticket. Given that LTA has only just begun stepping up their enforcements efforts, it is of no surprise that there are still variances in their reporting formats. As such, we cannot analyse the exact number of bikes that are illegally parked. However, since one ticket is issued for one or more bikes in the same location at the same time, useful insights can still be obtained with regards to the geographical locations where illegal bike parking problems are the most prevalent.
