As pollution and population continue to increase, new concepts of ecofriendly commutating evolve. One of the emerging concepts is the bicycle sharing system; it is a bike rental service on a short-term basis at a moderate price. It provides people the flexibility to rent a bike from one location and return it to another location. This business is quickly gaining popularity all over the globe.
In May 2011, there were only 375 bike rental schemes comprised of nearly 236,000 bikes in the USA. However, this number jumped to 535 bike sharing programs with approximately 517,000 bikes in just a couple of years. It is expected that this trend will continue to grow at a similar pace in the future.
Most of the businesses involved in this system of bike rental are faced with the challenge of balancing between supply and inconsistent demand. The number of bikes needed on a particular day can vary on several factors such as season, time, temperature, wind speed, humidity, holiday and the day of the week. In this paper we have illustrated an application of SAS® Forecast Studio to attempt to solve the forecasting problem. Incorporating the effect of all the above factors and analyzing the demand trends of the last two years, we have been able to precisely forecast the number of bikes needed on any day in the future. From a managerial perspective, we are also able to illustrate the scenario analysis to observe the effect of particular variables on demand.
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