中国汽车产业集群战略暨汽车零部件成长性企业25页PPT

3.771 37.711 37.711 3.347 33.465 33.465
2.110 21.100 58.811 2.114 21.143 54.608
Βιβλιοθήκη Baidu
1.063 10.627 69.437 1.149 11.486 66.094
1.013 10.131 79.569 1.010 10.100 76.194
Rotated Component Matrix(a)
Component
1
g_yszk
.025
g_ldzc
.773
g_zc
.969
g_sales .968
g_profit -.919
g_num
.123
g_prod .078
g_newp rod
.002
g_spre
.080
g_expor t
.582
-.095
.682
6 -.501 .145 .019 -.162 .114 .654 -.171
.036
-.120
.105
7 -.015 .240 .071 .021 .274 -.132 -.057
.000
-.038
.008
8 .011 -.200 .137 .168 .150 .056 -.028
Descriptive Statistics
g_yszk g_ldzc g_zc g_sales g_profit g_num g_prod g_newprod g_spre g_export
Mean 1.4059 .5100 .4617 1.1130 -1.3199 .4840 .6204 -.8859 .6679 .7249
.004
.005
.009
9 -.001 .023 -.125 .115 .009 .019 -.004
.000
-.024
.002
10 .001 -.001 .008 -.002 .005 .003 .060
.000
-.061
.001
Extraction Method: Principal Component Analysis. a 10 components extracted.
1
3.771 37.711 37.711
2
2.110 21.100 58.811
3
1.063 10.627 69.437
4
1.013 10.131 79.569
5
.936
9.358 88.927
6
.795
7.955 96.882
7
.161
1.607 98.489
8
.113
1.133 99.622
9
.030
.013
.821
.072
3 .349 .078 .007 -.064 .055 .253 -.130
.572
-.113
-.712
4 .647 .093 .005 -.122 .049 .351 -.248
-.577
-.210
.082
5 .323 .016 -.012 -.054 -.022 .046 -.112
.304 99.926
10
.007
.074 100.000
Extraction Sums of Squared Loadings
Rotation Sums of Squared Loadings
% of Cumulati
% of Cumulati
Total Variance ve % Total Variance ve %
23
585
417
585
23
585
368
a For each variable, missing values are replaced with the variable mean.
Total Variance Explained
Initial Eigenvalues
Compon
ent
Total
% of Cumulati Variance ve %
Component
g_yszk g_ldzc g_zc g_sales
1 .177 .931 .916 .909
g_profit
g_num
g_prod
g_newp rod
g_spre
g_expor t
-.729 .457 .472 .009 .490 .066
2 .269 -.001 -.346 -.289 .594 .391 .806
测评单位
《中国汽车界》
2019中国汽车零部件百家最具成长 性企业测评模型介绍
为了真实客观的反映中国最具成长性的零部 件生产企业，此次评选采用近三年企业的总 资产增速、产品销售收入增速、工业总产值 增速、利润总额增速、新产品产值增速、工 业销售产值增速、出口交货值增速、从业人 员增速、应收账款净额、流动资产平均余额 十项数值来进行分析、评选。
.320 99.924
.007
.074 100.000 .008
.076 100.000
Extraction Method: Principal Component Analysis.
Scree Plot
4
3
Eigenvalue
2
1
0
1
2
3
4
5
6
7
8
9
10
Component Number
Component Matrix(a)
.936
9.358 88.927 1.001 10.006 86.200
.795
7.955 96.882 1.000 10.001 96.201
.161
1.607 98.489 .189
1.889 98.090
.113
1.133 99.622 .151
1.514 99.604
.030
.304 99.926 .032
具体评选办法
1、搜集反映企业发展特征的指标数据：（2019－2019年度） 出口交货值 应收账款净额 流动资产平均余额 资产总计 产品销售收入 利润总额 全部从业人员平均人数 工业总产值(现价) 新产品产值 工业销售产值(现价)
计算方法：
利用搜集到的若干企业的指标数据，计算 出2019－2019年度各项指标的平均增速， 采用因子分析的方法，按不同因子在体系 中载荷的大小赋以权重，计算各企业的因 子得分，按得分大小进行排序，即可选出 前N家企业。
Std. Deviation(a)
13.56258 1.92975 2.73123 9.95487 97.71438 6.73409 1.99463
.07612 2.12124 1.16171
Analysis N(a) Missing N
585
34
585
24
585
24
585
25
585
26
585
24
585