公交移动支付定价最优化方案

Bus Mobile Payment Pricing Optimization Plan

随着智能手机的普及和移动技术提高,移动支付日益普及,也弥补了现金支付的不便和普通刷卡的弊端,本文主要是关于移动公交支付问题的评估方案,建立适当的模型并给出可行性建议。首先,选择了一个城市的公交支付数据为样本,先对数据进行预处理,进行统计分析。得知城市乘车人出行支付特征,支付特征与季节、时段、乘车次数有关,与是否为工作日无关的结论。其次,根据公司常见盈利模式,建立第三方平台的利润函数。考虑了公司可能的运营成本,从而得出该公司的商业盈利模型,再对所得模型进行定量分析其收支盈利情况。接着,利用MATLAB实现BP神经网络算法,对样本数据进行归一化及反归一化等处理,预测出该城市一年内的客流量总额。代入商业盈利模型,进而估计出该城市全部公交实现第三方支付后的盈利情况,可知利润与手续费和存款协议率成正相关,求得最大利润点。最后,为移动支付公司制定商业计划可行性报告。本文贴合时代背景,应用性较强。

With the popularization of smart phones and the improvement of mobile technology,mobile payment has become more and more popular,which also makes up for the inconvenience of cash payment and the drawbacks of ordinary credit card.This paper is mainly about the evaluation plan of mobile bus payment problem,establishing appropriate model and giving feasible suggestion.First,the city's bus payment data are selected as a sample,and the data are preprocessed for statistical analysis.Knowing the characteristics of the city passenger travel payment,the payment characteristics are related to the season,time period,and number of rides,and are not related to whether it is a workday.Secondly,based on the company's common profit model,establish a profit function for the third-party platform.Taking into account the company's possible operating costs,the company's business profit model is derived,and the resulting model is quantitatively analyzed for its revenue and expenditure.Then,using MATLAB to implement BP neural network algorithm,the sample data are normalized and denormalized,and the total traffic volume of the city in one year is predicted.Substituting into the business profit model,and estimating the profitability of all the public transportation in the city after third-party payment,it is known that the profit is positively correlated with the handling fee and the deposit agreement rate,and the maximum profit point is obtained.Finally,a business plan feasibility report is prepared for the mobile payment company;this article fits the background of the times and is more applicable.