Acta Scientiarum Naturalium Universitatis Pekinensis ›› 2017, Vol. 53 ›› Issue (3): 429-435.DOI: 10.13209/j.0479-8023.2017.007
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Yongsheng ZHU, Jisong ZHU, Shengwen YU, Guoyu QIU()
Received:
2015-12-20
Revised:
2016-04-01
Online:
2017-05-20
Published:
2017-05-20
基金资助:
Yongsheng ZHU, Jisong ZHU, Shengwen YU, Guoyu QIU. Research of Customer’s Choice Preference for New Energy Vehicles:Based on the Analysis of a Consumer Survey in Shenzhen[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2017, 53(3): 429-435.
朱勇胜, 朱继松, 余升文, 邱国玉. 新能源汽车的消费者特征研究—— 基于深圳市消费者调查的分析[J]. 北京大学学报自然科学版, 2017, 53(3): 429-435.
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URL: https://xbna.pku.edu.cn/EN/10.13209/j.0479-8023.2017.007
变量 | 变量属性 | 样本数量 | 比例/% |
---|---|---|---|
性别 (Gender) | 男 | 420 | 77.1 |
女 | 125 | 22.9 | |
年龄 (Age) | 18~30岁 | 374 | 68.6 |
31~45岁 | 171 | 31.4 | |
家庭月收入 (Income) | 10000元以下 | 300 | 55.0 |
10000~15000元 | 124 | 22.8 | |
15000元以上 | 121 | 22.2 | |
受教育程度 (Edu) | 高中及以下 | 139 | 25.5 |
大专及以上 | 406 | 74.5 | |
每日出行里程 (Range) | 40 km以下 | 340 | 62.4 |
40~60 km | 133 | 24.4 | |
60 km以上 | 72 | 13.2 |
Table 1 Statistical information of consumer sample for consumer attributes
变量 | 变量属性 | 样本数量 | 比例/% |
---|---|---|---|
性别 (Gender) | 男 | 420 | 77.1 |
女 | 125 | 22.9 | |
年龄 (Age) | 18~30岁 | 374 | 68.6 |
31~45岁 | 171 | 31.4 | |
家庭月收入 (Income) | 10000元以下 | 300 | 55.0 |
10000~15000元 | 124 | 22.8 | |
15000元以上 | 121 | 22.2 | |
受教育程度 (Edu) | 高中及以下 | 139 | 25.5 |
大专及以上 | 406 | 74.5 | |
每日出行里程 (Range) | 40 km以下 | 340 | 62.4 |
40~60 km | 133 | 24.4 | |
60 km以上 | 72 | 13.2 |
购车类型 | 样本数量 | 比例% |
---|---|---|
传统型内燃机汽车(ICEVs) | 259 | 47.5 |
混合动力汽车(HEV) | 110 | 20.2 |
插电式混合动力汽车(PHEV) | 138 | 25.3 |
纯电动汽车(BEV) | 38 | 7.0 |
Table 2 Car types’ statistical information of consumer preference
购车类型 | 样本数量 | 比例% |
---|---|---|
传统型内燃机汽车(ICEVs) | 259 | 47.5 |
混合动力汽车(HEV) | 110 | 20.2 |
插电式混合动力汽车(PHEV) | 138 | 25.3 |
纯电动汽车(BEV) | 38 | 7.0 |
观测数 | 案例数 | 对数似然 | 对数似然Null (logL(0)) | 最大绝对梯度 | 迭代数 | 优化方法 | AIC | Schwarz准则 |
---|---|---|---|---|---|---|---|---|
545 | 2180 | -629 | -756 | 3.09×10-8 | 31 | Newton-Raphson | 1298 | 1384 |
Table 3 Model fitting information for consumer attributes
观测数 | 案例数 | 对数似然 | 对数似然Null (logL(0)) | 最大绝对梯度 | 迭代数 | 优化方法 | AIC | Schwarz准则 |
---|---|---|---|---|---|---|---|---|
545 | 2180 | -629 | -756 | 3.09×10-8 | 31 | Newton-Raphson | 1298 | 1384 |
测度 | 值 | 公式 |
---|---|---|
似然比(R) | 253 | 2(logL - logL0) |
R的上限(U) | 1511 | - 2 log L0 |
Aldrich-Nelson | 0.32 | R/(R+N) |
Cragg-Uhler 1 | 0.37 | 1- exp(-R/N) |
Cragg-Uhler 2 | 0.40 | (1- exp(-R/N)) / (1- exp(-U/N)) |
Estrella | 0.40 | 1- (1-R/U)(U/N) |
调整Estrella | 0.35 | |
McFadden LRI | 0.17 | R/U |
Veall-Zimmermann | 0.43 | (R(U+N))/(U(R+N)) |
Table 4 Goodness-of-fit for consumer attributes
测度 | 值 | 公式 |
---|---|---|
似然比(R) | 253 | 2(logL - logL0) |
R的上限(U) | 1511 | - 2 log L0 |
Aldrich-Nelson | 0.32 | R/(R+N) |
Cragg-Uhler 1 | 0.37 | 1- exp(-R/N) |
Cragg-Uhler 2 | 0.40 | (1- exp(-R/N)) / (1- exp(-U/N)) |
Estrella | 0.40 | 1- (1-R/U)(U/N) |
调整Estrella | 0.35 | |
McFadden LRI | 0.17 | R/U |
Veall-Zimmermann | 0.43 | (R(U+N))/(U(R+N)) |
消费者属性变量 | 混合动力汽车与 传统型内燃机汽车相比 | 插电式混合动力汽车与 传统型内燃机汽车相比 | 纯电动汽车与 传统型内燃机汽车相比 |
---|---|---|---|
常数 | -0.9590 | -0.0326 | -1.4512* |
性别(Gender) | 0.1351 | -0.5750* | 0.3553 |
年龄(Age) | -0.5127** | -0.1361 | 0.7499* |
收入(Income) | 0.0996 | -0.2698 | -0.4761* |
受教育程度(Edu) | -0.0060 | 0.3397* | -0.8637*** |
每日出行里程(Range) | 0.2896 | -0.1474 | 0.2114 |
Table 5 Parameter estimates for consumer attributes
消费者属性变量 | 混合动力汽车与 传统型内燃机汽车相比 | 插电式混合动力汽车与 传统型内燃机汽车相比 | 纯电动汽车与 传统型内燃机汽车相比 |
---|---|---|---|
常数 | -0.9590 | -0.0326 | -1.4512* |
性别(Gender) | 0.1351 | -0.5750* | 0.3553 |
年龄(Age) | -0.5127** | -0.1361 | 0.7499* |
收入(Income) | 0.0996 | -0.2698 | -0.4761* |
受教育程度(Edu) | -0.0060 | 0.3397* | -0.8637*** |
每日出行里程(Range) | 0.2896 | -0.1474 | 0.2114 |
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