1st ICAI 2020

International Conference on Automotive Industry 2020

Mladá Boleslav, Czech Republic

• X6 – amount of depreciation charges (thousand CZK); • X7 – labor productivity index (thousand CZK / month). The calculation of Pearson’s Mutual Coefficient Matrix is shown in Table 2.

Table 2: Pairs of Pearson’s Mutual Coherence Matrix. X1 X2 X3 X4 X5

X6

X7

X1

1

0,448**

0,025 0,281**

0,023 0,286**

-0,032

X2 0,448**

1

0,663** 0,756** 0,414** 0,732** 0,246**

X3 0,025 0,663**

1

0,347** 0,646** 0,248** 0,418**

X4 0,281** 0,756** 0,347**

1

0,499** 0,982** 0,559**

X5 0,023 0,414** 0,646** 0,499**

1

0,338** 0,637**

X6 0,286** 0,732** 0,248** 0,982** 0,338** X7 -0,032 0,246** 0,418** 0,559** 0,637** 0,476** 1

0,476**

1

** The correlation is significant at 0.01 (2-sided). Source: own calculations

It should be noted that the variables used in the cluster analysis almost coincided with those used in similar studies in other sectors of the Czech economy. The cluster analysis was done using the Ward method. Due to the different units of measurement, preliminary standardization of the data was carried out. The analysis excluded objects with data omissions as well as objects with abnormally high values of value added and total assets against the background of other organizations. Accordingly, the cluster analysis was conducted on a sample of 326 motor vehicle manufacturing enterprises. The hypothesis of equality of dispersions within and between clusters is rejected for all variables at 5 and 1689 degrees of freedom. Value p is the probability of error when accepting the hypothesis of inequality of dispersions is extremely low, not exceeding 0.001 (F-criterion is significant for all variables at the level of not less than 0.01). This allows us to say that the hypothesis of inequality of dispersions is accepted and, accordingly, the clusters are formed correctly. The results of the cluster analysis of motor vehicle production enterprises are presented in Table 3.

Table 3: Average values of variables in clusters, sorted by total assets (X4)

Symbol of the variable

Cluster 1N=270

Cluster 4N=10

Cluster 2N=25

Cluster 3N=20

Cluster 5N=1

Name of the variable

Number of units

X1

1.6

1.5

1.2

5.1

1.0

Average number of employees total (persons)

X2

186

330

1 030 2 113 2 750

23