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Using Big Data to Solve the Supply and Demand Problem of Sharing Bike

2018-01-08 17:31:36
Under the global wave of sharing,sharing bike has also become the means of transport to solve the last mile of people traveling.Now many city appeared in a variety of colors sharing bike,but how to improve the use of sharing bike to achieve the real sharing model.For the user,it is mainly necessary to solve the problem that is a sharing bike available in anytime or anywhere if they need.The main demand for operators is to increase the daily average frequency of each bicycle.

Contradiction between the two reflected as follows: users want to use the bike,but no bike nearby available or a bike can not be use.For operators,on the one hand,users have a need for a bike but can not respond promptly,on the other hand,a large number of sharing bikes are temporarily idle in other regions.In fact,this demand is for supply and demand in time and space to match the problem.The higher the matching degree,the problem is solved better.The lower the matching cost,the benefit will be better.

Big data based on Internet technology has massive information, so long as the information can be interconnected and shared,the number of sharing bike putting on the market can be easily locked,In terms of quantity,the operations department is perfectly fine-tuned for sharing bikes that are put on the market.This precise regulation of big data,in addition to allowing the number of sharing bicycles in the market has always been to meet the objective needs of the dynamic balance,but also it can reduce excessive put on shared bicycles to brought governance problems to achieve a win-win governance.

Omni sharing bike system, through Built-in smart bike lock with GPS positioning module can accurately obtain the physical location,operators can monitor the location and usage of sharing bike through real-time monitoring in the background.Through big data,it helps operators improve the operation of sharing bike and maximize improve the benefits and customer experience.