An Evaluation Method for Bicycle Sharing Satisfaction Based on a Bivariate Ordered Probit Model
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摘要: 城市共享单车是城市绿色交通系统的组成部分,是服务公众短距离出行和公共交通接驳换乘的重要方式,在解决城市交通出行“最后一公里”问题等方面发挥了积极作用。为科学评估城市共享单车服务的满意度,采用问卷调查法和实地踏勘法采集了宁波市1 212个共享单车用户有效样本,利用统计学方法构建二元有序概率(bivariate ordered probit, BOP)模型,分析共享单车满意度影响因素,计算显著影响因素的边际效应,量化分析共享单车满意度和使用率的影响因素效用。结果表明:BOP模型可以量化分析影响共享单车使用频率和满意度的各类因素。结果表明,性别、年龄、教育程度、家庭拥有车辆情况、平时出行方式和出行距离等具有统计显著性,是影响城市共享单车服务满意度的显著因素。从用户需求和服务感知出发,了解现有服务所存在的主要问题以及迫切需要优化的方面,提升共享单车服务质量和用户出行体验。Abstract: As an integral part of the urban green transportation system, bicycle sharing is an important way to serve the public for short-distance travel and public transport interchange, playing an active role in solving the"last mile"of urban transportation.A valid sample of 1 212 bicycle-sharing users in Ningbo is collected using questionnaires and field surveys to assess the satisfaction of bicycle-sharing services.Also, a bivariate-ordered-probit(BOP)model is constructed using statistical methods to analyze the factors influencing bicycle sharing satisfaction and calculate the marginal effects of significant influencing factors.The BOP model is used to quantify the utility of the factors influencing bicycle sharing satisfaction and usage.The results show that it can quantify the factors influencing the frequency and satisfaction of bicycle sharing.Gender, age, education, household ownership, usual travel mode, and trip distance are statistically significant factors influencing satisfaction with bicycle sharing services in the city.From user needs and service perceptions, the main problems of the existing service and the aspects that need to be optimized are understood to improve the quality of bike-sharing service and users'travel experience.
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Key words:
- traffic engineering /
- satisfaction /
- usage /
- bivariate ordered probit /
- bicycle sharing
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表 1 信度分析Cronbach'sα系数
Table 1. Cronbach'sαcoefficients for reliability analysis
指标 项数 Cronbach's a 使用率 50 0.984 满意度 50 0.984 表 2 KMO和Bartlett的检验
Table 2. Flow of the model
取样足够度的 Kaiser-Meyer-Olkin度量 0.986 近似卡方 91896.431 Bartlett的球形度检验 df 1 225 Sig. 0.000 表 3 BOP模型估计结果
Table 3. Estimated results of the BOP model
变量 使用率 满意度 β S.E. ρ -value β S.E. ρ -value 性别(男/女) 0.386 0.072 0.05 0.094 0.070 0.176 年龄(青少年/老年) -0.152 0.099 0.125 0.204 0.114 0.074 教育程度(高/低) 0.117 0.072 0.104 0.100 0.070 0.156 月收人(高/低) 0.097 0.054 0.075 0.016 0.056 0.779 职业 -0.057 0.029 0.052 -0.071 0.035 0.042 家庭拥有车辆情况(1辆小汽车) -0.013 0.100 0.897 -0.042 0.100 0.677 家庭拥有车辆情况(2辆小汽车) 0.090 0.134 0.501 -0.192 0.144 0.183 家庭拥有车辆情况(> 3辆小汽车) -0.131 0.251 0.600 -0.201 0.232 0.387 家庭拥有车辆情况(电瓶车) 0.171 0.090 0.059 -0.046 0.091 0.610 家庭拥有车辆情况(自行车) 0.026 0.092 0.775 -0.165 0.085 0.052 家庭拥有车辆情况(无) 0.001 0.151 0.996 -0.078 0.136 0.568 平时出行方式(共享单车) -0.795 0.079 0.052 -0.095 0.077 0.213 平时出行方式(电瓶车) -0.055 0.107 0.610 0.149 0.113 0.187 平时出行方式(公共自行车) -0.055 0.115 0.634 -0.024 0.111 0.827 平时出行方式(公交或地铁) -0.003 0.078 0.966 0.111 0.080 0.169 平时出行距离 0.049 0.039 0.204 -0.050 0.038 0.185 主要用途(上下班/上下学) -0.290 0.077 0.000 0.061 0.075 0.413 主要用途(购物旅游) 0.049 0.083 0.367 -0.164 0.087 0.061 使用理由(租还车方便) -0.038 0.080 0.635 -0.293 0.082 0.000 使用理由(经济实惠) -0.150 0.079 0.059 -0.324 0.073 0.000 使用理由(环保) -0.037 0.081 0.648 -0.300 0.077 0.000 存在问题(乱停乱放) 0.234 0.094 0.012 0.329 0.096 0.001 存在问题(故障车太多) -0.113 0.086 0.191 0.239 0.088 0.007 交通事故 -0.210 0.146 0.151 -0.405 0.177 0.022 改进之处(违停现象) 0.021 0.083 0.803 -0.068 0.072 0.343 改进之处(单车破损) -0.001 0.096 0.995 0.053 0.094 0.572 改进之处(单车广告) -0.014 0.097 0.885 0.039 0.085 0.642 改进之处(定位系统) -0.146 0.085 0.084 -0.017 0.079 0.826 改进之处(乘客服务) 0.049 0.094 0.603 0.184 0.092 0.047 电子围栏 -0.034 0.073 0.064 0.060 0.067 0.372 -
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