The Experience of European Countries in Managing the Expenditures
of Enterprises in the Agricultural Sector
ANDRII REZNIK
Economics and International Economic Relations Chair,
Poltava State Agrarian University,
Poltava,
UKRAINE
SVITLANA LAVRYNENKO
Management of Organizations and Administration,
after M. P. Polishchuk, Polissya National University,
Zhytomyr,
UKRAINE
ANTONINA ZELISKA
Department of Organizational Management and Administration,
Polissya National University,
Zhytomyr,
UKRAINE
NATALIIA MARDUS
Accounting and Hotel Restaurant Business,
National Technical University «Kharkiv Polytechnic Institute»,
Kharkiv,
UKRAINE
OKSANA SAMBORSKA
Department of Administrative Management and Alternative Energy Sources,
Vinnytsia National Agrarian University,
Vinnytsia,
UKRAINE
Abstract: Ensuring the efficient development and functioning of agricultural enterprises depends on the
rationally formed optimal level of costs for the implementation of economic activities, particularly for the
production of agricultural products. This article aims to describe methodological principles of cost management
of agricultural enterprises based on the European Union countries using determination of interconnection
between total costs of agricultural enterprises and indicators of the value of agricultural products manufactured
by them. Methods: theoretical analysis, abstraction, induction, deduction, tabular and graphical presentation,
description, comparison, comparison, and generalization. Results: It was found that the disclosure of
methodological principles of cost management of agricultural enterprises should be carried out by identifying
the relationship between the total costs of agrarian enterprises and indicators of the cost of agricultural products
produced by them using correlation analysis. As a result of correlation analysis, we established direct and
reversed very high, high, medium, moderate, and weak correlations between the indicator of total costs of
agricultural enterprises and the indicator of the cost of grain growing, index of production cost of industrial
crops and the index of the cost of forage crops production according to the surveyed countries of the European
Union. It was found that with very high and high intensity of interconnection between the analyzed variables.
The increase in the indicator of total costs directly affects the growth of the cost of growing crops by
agricultural enterprises in Austria, Belgium, Bulgaria, Croatia, Cyprus, Estonia, Latvia, the Netherlands, and
Romania. The growth in the indicator of total costs directly affects the growth of the production cost of
industrial crops by agricultural enterprises of Denmark, Estonia, Greece, Latvia, and Portugal and the increase
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.109
Andrii Reznik, Svitlana Lavrynenko,
Antonina Zeliska, Nataliia Mardus,
Oksana Samborska
E-ISSN: 2224-3496
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in the indicator of total costs directly affects the increase in the cost of growing forage crops by agricultural
enterprises of Belgium, Croatia, Cyprus, Estonia, Ireland, the Netherlands, Romania, Slovenia, Spain, and
Sweden. The prospect of the following research is to disclose the methodological principles of cost
management of agricultural enterprises on the application of the United States of America.
Key-Words: agricultural business, production of agricultural products, gross value added, correlation analysis.
Received: November 16, 2021. Revised: August 16, 2022. Accepted: September 19, 2022. Published: October 12, 2022.
1 Introduction
The effective development and functioning of
agricultural enterprises depend on many factors, a
special place among which is the optimal level of
costs for economic activity, formed by the cost
management system. The basis of such a system is
several business processes, including business
processes of strategic cost management of
agricultural enterprises, business processes of
planning, forecasting, and control of costs of
agricultural enterprises, and more. Operating the
necessary information about the available and
possible costs allows you to rationally plan the
economic activities of agricultural enterprises,
primarily related to the production of agricultural
products.
The practice gives grounds to note that during
the formation and implementation of an effective
cost management system for agricultural enterprises
it is necessary to take into account both
methodological recommendations and rely on the
experience of enterprises that already operate
effectively in the field of agribusiness. Emphasizing
the importance of forming and implementing a cost
management system in the economic activities of
agricultural enterprises, the research will focus on
methodological and practical principles of cost
management of agricultural enterprises.
2 Literature Review
Markina et al. [1] and Zinina et al. [2] note that an
important principle of sustainable development of
agricultural enterprises is to ensure the effective cost
management of such enterprises. Sharifi et al. [3] in
the context of the study of the peculiarities of the
formation of costs of agricultural enterprises note
that an important role in reducing them, in particular
in reducing transaction costs, play agricultural
cooperatives that form agricultural enterprises.
Kocaköse et al. [4] also emphasize that an important
role in the context of reducing costs, particular
production costs, agricultural enterprises play the
relevant factors of influence, namely: 1) the level of
mechanization; 2) availability of irrigation facilities;
3) the level of supply of resources; 4) features of
sales; 5) product prices; 6) prices for raw materials;
7) labor resources. Agizan et al. [5] emphasize the
importance of mechanization as one of the key
factors in the development of agricultural
production. Panagos et al. [6] argue that agricultural
enterprises often face the problem of loss of
productivity of agricultural production due to soil
erosion, which affects the growth of direct costs of
these enterprises.
Kubala [7] examines the features of the
relationship between the activities of agricultural
enterprises and the costs borne by agricultural
enterprises in the context of such activities.
Bayramoglu et al. [8] consider the features of
achieving economic stability of agricultural
enterprises, one of the important components of
which is to ensure effective cost management of
such enterprises. Dudin et al. [9] note that renewable
energy sources play an important role in reducing
costs as a direction of cost management of
agricultural enterprises. According to scientists,
renewable energy sources are one of the main tools
to increase the competitiveness of agricultural
enterprises.
Kucera et al. [10] argue that the cost
management system of the enterprise is one of the
main components of the management system.
Govdya et al. [11] emphasize the importance of the
accounting and analytical system for cost
management of agricultural enterprises, which
should be formed based on the decomposition
approach to such a process. Stašová [12] argues that
in the context of managing the costs of agricultural
enterprises, it is necessary to perform a statistical
analysis of the suitability of such enterprises, using
the method of calculation. Borodina et al. [13]
consider models of cost management of agricultural
enterprises. In particular, scientists focus on adapted
management models, the effective introduction of
which into economic activity by agricultural
enterprises will allow increasing the volume of
agricultural production and improving the quality of
agricultural production. Lizot et al. [14] investigate
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Andrii Reznik, Svitlana Lavrynenko,
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the features of cost management in the agrarian
family business. Researchers emphasize the
effectiveness of using an instrumental model of cost
management for agricultural enterprises of this type,
which will allow more effective management
decisions with a focus on the core business of such
enterprises. Byshov [15] argues that in the context
of cost management of agricultural enterprises
should be laid systematic analysis, the effective use
of which will increase the overall efficiency of
production by agricultural enterprises. Zakić et al.
[16] emphasize that
Shaimardanovich et al. [17] argue that a special
role in the effective cost management of agricultural
enterprises is played by the optimization of
production of these enterprises. Savic et al. [18] note
that the optimization of costs of agricultural
enterprises should be carried out based on the life
cycle of agricultural products produced by
agricultural enterprises. Beznosov et al. [19]
emphasize that in the course of cost optimization of
agricultural enterprises it is impossible to reduce all
production costs, at the same time it is possible to
reduce only those costs that directly affect the main
indicators of production efficiency. Mohamed et al.
[20] note that the optimization of costs of
agricultural enterprises will contribute to the
greatest savings in the direction of costs for
depreciation, maintenance, and repair of equipment,
as well as fuel costs. Paidipati et al. [21] argue that
in the context of cost optimization, which provides
for cost reduction and profit maximization of
agricultural enterprises, it is necessary to ensure the
effective management of resources of agricultural
enterprises. Kaldiyarov et al. [22] argue that the
optimization of production costs of agricultural
enterprises is a factor in the development of
cooperative forms of business in the agricultural
sector.
Emphasizing the information obtained in the
context of the literature review on the researched
issues, it was found that the issues of
methodological and practical approaches to cost
management of agricultural enterprises are
insufficiently disclosed.
The article aims to reveal the methodological
principles of cost management of agricultural
enterprises in the example of the European Union by
determining the relationship between the total costs
of agricultural enterprises and indicators of the
value of their agricultural products.
To achieve the aim of the article it is necessary to
solve the following tasks:
determine the total costs of agricultural
enterprises in the European Union;
to present indicators of the cost of the made
agricultural production by the agricultural
enterprises of the countries of the European Union;
to conduct a correlation analysis to determine the
relationship between the total costs of agricultural
enterprises in the European Union and indicators of
the value of their agricultural products.
3. Materials and Methods of Research
To achieve the aim and to solve the problems
identified in the article, were used: 1) methods of
theoretical analysis, abstraction, induction, and
deduction - to present the theoretical foundations of
cost management of agricultural enterprises; 2)
methods of tabular and graphical presentation,
description, observation, comparison, and
generalization - to reveal the methodological
principles of cost management of agricultural
enterprises on the example of the European Union
by determining the relationship between total costs
of agricultural enterprises and indicators of the
value of agricultural products.
The information base of the study consists of the
following indicators:
1) Gross value added of the agricultural industry
- basic and producer prices, Million euro [23];
2) Output of the agricultural industry - basic and
producer prices, Million euro [24];
3) Economic accounts for agriculture - values at
current prices [25].
4 Results of the Research
To reveal the methodological principles of cost
management of agricultural enterprises, we will
conduct a correlation analysis between the total
costs of agricultural enterprises and indicators of the
value of their agricultural products, in particular:
1) an indicator of the cost of growing cereals at
current prices;
2) an indicator of the cost of growing industrial
crops at current prices;
3) an indicator of the cost of growing fodder
plants at current prices.
The total costs of agricultural enterprises are
calculated as the difference between the output of
the agricultural industry and the Gross value added
of the agricultural industry, presented in Table 1.
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Table 1. Initial data for determining the total costs of agricultural enterprises
â„–
Countries
2016
2018
2019
2020
X1
Y1
X2
Y2
X3
Y3
X4
Y4
X5
Y5
1
Austria
6945.34
2861,8
1
7302.4
5
3226,4
6
7364.0
8
3123,3
3
7471.3
9
3070,1
3
7712.5
3
3241,3
7
2
Belgium
7981.09
2155,2
7
8384.9
8
2384,5
2
8203.3
5
2124,1
8
8719.2
3
2479,2
4
8661.4
1
2275,1
3
3
Bulgaria
4003,63
1776,5
7
4213,0
5
1922,6
8
4324,3
6
1873,0
8
4321,4
7
1878,7
9
3964,6
1
1663,1
5
4
Croatia
2183,63
967,97
2203,8
5
974,98
2333,1
5
1083,0
8
2423,4
6
1135,3
0
2552,7
1
1254,6
0
5
Cyprus
678,66
318,83
723,42
321,17
714,24
308.38
756.04
328,72
760.69
340,25
6
Czech Republic
4918,63
1690,2
9
5085.0
3
1675,1
0
5304.3
3
1700,2
9
5497.7
2
1759,0
1
5494.8
3
1845,2
8
7
Denmark
10042.52
2102,9
7
11200.
32
3113,3
5
10546.
84
2562,4
8
11067.
37
2921,0
9
11089.
75
2961,0
8
8
Estonia
749,73
151.10
885,85
277.51
859,23
205,91
997,64
281.81
974,30
242.03
9
Finland
4318,73
1151,0
8
4273,3
7
1164,9
5
4466,7
4
1120,0
6
4745,4
2
1400,8
0
4463,0
9
1430,8
8
10
France
70485.70
26284.
14
73152.
38
29823.
33
78295,
39
33735.
01
77023.
61
31920,
18
75428.
14
30182,
49
11
Germany
52515.44
16415.
62
57553.
64
21821.
69
53537.
29
16846.
55
58527.
78
22088.
17
56804.
21
20257.
33
12
Greece
10942,28
5416.7
3
11722.
73
6082.3
6
11475.
73
5803.8
3
11880.
09
6140.9
6
11813.
99
6144.4
2
13
Hungary
8308.99
3437,6
3
8394,1
9
3564,9
5
8443.6
4
3465,2
6
8721.5
5
3584,0
4
8464.5
8
3647,1
4
14
Ireland
7444.21
2359,0
7
8476.4
1
3158,4
9
8686.0
0
2647,8
5
8521.6
8
2873,9
9
8763.2
6
3086,8
7
15
Italy
54402.90
31350,
36
56084.
92
32436.
70
58515.
19
33867.
36
57828.
71
32928.
15
56320,
40
31448,
59
16
Latvia
1315,90
333.31
1407,3
2
426,81
1345,3
8
346,49
1628,6
8
549,59
1681,7
3
591,98
17
Lithuania
2834,78
997,50
3141,6
4
1241,1
6
2907,6
8
990,06
3209,3
9
1232,1
2
3461,2
8
1503,7
2
18
Luxembourg
406.33
100.51
429,08
120.70
435,16
125.55
442,43
125.59
438,84
124.60
19
Malta
126.53
63.61
121.78
59.36
121.17
56.37
126.40
60.90
127.29
62.04
20
Netherlands
27246,19
10653.
13
28936.
81
11743.
67
28162.
24
10725.
06
29138.
34
11269.
31
28235.
54
10574.
15
21
Poland
22412.32
8589.4
2
25655,
20
10625.
44
25608.
02
9404.9
9
26357.
72
10189.
19
27177.
73
11045.
32
22
Portugal
7094.87
2671,8
4
7639.0
7
2983,8
4
7833.5
3
3008,2
3
8084.4
6
3192,7
6
7829.1
5
2912,2
3
23
Romania
15443.75
6537.9
5
17180,
46
7714.0
7
18553.
78
8328.4
5
18963.
83
8786.3
0
16847.
02
7921.7
1
24
Slovakia
2391,10
625,86
2390,1
9
651,68
2317,7
5
541,09
2261,1
2
521.05
2329,4
5
577.12
25
Slovenia
1206,89
469,58
1153,0
1
430,26
1369,9
5
619,62
1325,1
7
561,03
1353,3
2
603,27
26
Spain
48411.62
27328.
05
50640.
76
28846.
30
52144.
46
28742.
91
51668.
68
28065.
69
52919.
36
29287.
97
27
Sweden
5971.69
1641,9
9
6456.9
8
1933,5
6
5901.3
7
1441,2
8
5998.6
3
1553,2
7
6103.0
0
1742,2
2
Legend:
Х1, Х2,…, Х5 - Output of the agricultural industry - basic and producer prices, Million euro
Y1, Y2,…, Y5 - Gross value added of the agricultural industry - basic and producer prices, Million euro
Source: [23; 24]
After performing the calculation, we obtain the
corresponding values of the total costs of
agricultural enterprises (V1, V2,… V5) for each of
the countries of the European Union and present
them in the Table 2.
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Andrii Reznik, Svitlana Lavrynenko,
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Table 2. Total costs of agricultural enterprises, Million €
â„–
Countries
2016
2018
2019
2020
1
Austria
4083,53
4240,75
4401,26
4471,16
2
Belgium
5825.82
6079.17
6239.99
6386.28
3
Bulgaria
2227,06
2451,28
2442,68
2301,46
4
Croatia
1215,66
1250,07
1288,16
1298,11
5
Cyprus
359,83
405,86
427,32
420,44
6
Czech
Republic
3228,34
3604,04
3738,71
3649,55
7
Denmark
7939.55
7984.36
8146.28
8128.67
8
Estonia
598,63
653,32
715,83
732,27
9
Finland
3167,65
3346,68
3344,62
3032,21
10
France
44201,56
44560.38
45103,43
45245,65
11
Germany
36099.82
36690,74
36439.61
36546.88
12
Greece
5525.55
5671.9
5739.13
5669.57
13
Hungary
4871,36
4978.38
5137.51
4817,44
14
Ireland
5085.14
6038.15
5647.69
5676.39
15
Italy
23052,54
24647.83
24900,56
24871.81
16
Latvia
982,59
998,89
1079,09
1089,75
17
Lithuania
1837,28
1917,62
1977,27
1957,56
18
Luxembourg
305.82
309.61
316.84
314,24
19
Malta
62.92
64.8
65.5
65.25
20
Netherlands
16593.06
17437.18
17869.03
17661,39
21
Poland
13822.9
16203.03
16168.53
16132,41
22
Portugal
4423,03
4825.3
4891.7
4916.92
23
Romania
8905.8
10225.33
10177.53
8925.31
24
Slovakia
1765,24
1776,66
1740,07
1752,33
25
Slovenia
737,31
750,33
764,14
750.05
26
Spain
21083.57
23401.55
23602.99
23631.39
27
Sweden
4329.7
4460.09
4445,36
4360,78
Source: calculated by the authors according to [23; 24].
Indicators of the cost of growing cereals at
current prices, the cost of growing industrial crops
at current prices, and the cost of growing fodder
plants at current prices, which will be variable in the
correlation analysis, are presented in Table 3
(Annex 1).
As a result of our calculation, we obtained the
value of the correlation coefficient. We assessed the
degree of relationship between variables on the
Chaddock scale (Appendix 2, Table 4).
Analyzing the data of correlation analysis, a very
high and sometimes direct correlation between the
indicator of total costs and the indicator of the cost
of growing crops was established, which indicates
that an increase in the indicator of total costs
directly affects the increase in the indicator of the
cost of growing crops in Belgium, Bulgaria, Latvia,
and Rumania. The high correlation, which indicates
that the increase in the indicator of total costs
directly affects the increase in the indicator of the
cost of growing crops in Austria, Croatia, Cyprus,
Estonia, and the Netherlands, the correlation
between the analyzed variables was 89.90%,
72.70%, 87.26%, 87.51%, and 82.60%. The
presence of a high inverse relationship between the
analyzed variables, according to which an increase
in the indicator of total costs influences the decrease
in the indicator of the cost of growing crops, is
found in Greece. In Portugal, the intensity of the
relationship between the analyzed variables is
average and the relationship is negative, but in
Germany, Italy, and Sweden the intensity of the
relationship is weak, while the relationship is
average. The data received for Portugal indicate that
the variation of growth in the indicator of total costs
leads to a decrease in the indicator of the cost of
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growing crops by 63.73%. At the same time, the
variation of growth of the total costs index in
Germany, Italy, and Switzerland leads to a decrease
in the indicator of the cost of crop production by
5.07%, 23.84%, and 15.54% respectively.
The results of the correlation analysis between
the indicator of total inputs and the indicator of the
cost of growing fodder crops allowed us to note the
existence of a direct and very high correlation
between the analyzed variables in Belgium, Croatia,
Cyprus, Italy, Romania, and Sweden. Thus, the
variation of growth of the index of total costs in
these countries of the European Union leads to
growth of the cost of producing feed crops by
94.65%, 92.26%, 99.19%, 92.22%, 92.40%, and
98.66% accordingly. The presence of a high
correlation between increasing total inputs directly
affects the growth of the cost of producing fodder
crops in Estonia, Ireland, the Netherlands, Slovenia,
and Spain. The high correlation between the
analyzed variables is observed only in Luxembourg,
as the variation of growth in total inputs leads to a
decrease in the indicator of the value of feed crops
by 73.13%. The presence of a reversed and weak
relationship between the indicator of total inputs and
the indicator of the cost of growing fodder plants in
Bulgaria, Denmark, Germany, and Portugal. Thus,
in these countries of the European Union, the
variation of growth of the total costs index leads to a
decrease in the cost of producing forage crops by
24,10%, 23,95%, 27,14%, and 21,84% accordingly.
5 Discussion
The carried out research gives grounds to state that
the problem of cost management of agricultural
enterprises is very relevant since it is widely
represented in the studies of many scientists. In
particular, it has been established that efficient cost
management of agricultural enterprises is one of the
key prerequisites for ensuring the sustainable
development of these enterprises (Markina et al. [1];
Zinina et al. [2]. Kocaköse et al. [4] and Agizan et
al. [5] stressed the importance of an appropriate
level of mechanization, availability of agrarian
capacities, the appropriate level of supply of
resources, etc., which reduces the costs of agrarian
enterprises and Agizan et al. [5]. The research of
Bayramoglu et al. [8] has stated that ensuring
efficient cost management of agricultural enterprises
is one of the important components of achieving the
economic sustainability of these enterprises. Govdya
et al. [11] argue that the accounting and analytical
system should be introduced into the cost
management system of agrarian enterprises, but
Stašová [12] notes that the cost management system
of agricultural enterprises should include a business
process of statistical analysis and assessment of
such enterprises' ability to carry out efficient
economic activities. Byshov [15] argues for the use
of system analysis in the cost management system
of agricultural enterprises, and Zakić et al. [16]
focus on the use of classical (traditional) approaches
to cost accounting. Borodina et al. [13] focus on the
use of adapted models in the cost management of
agricultural enterprises. The importance of
implementation of the cost management system of
agricultural enterprises in the agricultural family
business is the subject of research by Lizot et al.
[14]. Optimization of production of agricultural
enterprises, due to which it is possible to effectively
manage the costs of these enterprises, is the subject
of research Shaimardanovich et al. [17]. The
optimization of costs of agricultural enterprises,
which will allow for effectively managing them, is
the subject of research by Savić et al. [18],
Beznosov et al. [19], Mohamed et al. [20], Paidipati
et al. [21] and Kaldiyarov et al. [22].
We fully agree with the results of the research of
the above-mentioned scientists and researchers, but
note that the cost management of agricultural
enterprises should be based on the relationship
between the total costs of agricultural enterprises
and the cost of agricultural products. Therefore, in
the study, we conducted a correlation analysis to
determine the relationship between the cost of
agricultural enterprises and the cost of agricultural
products of each type, respectively. Correlation
analysis was performed on the example of
agricultural enterprises in the European Union.
The results of the correlation analysis will allow
us to establish both direct and inverse relationships
between the total cost of agricultural enterprises and
the cost of growing cereals, the cost of growing
industrial crops, and the cost of growing fodder
plants, respectively, for the studied countries of the
European Union.
It was found that efficient cost management of
agricultural enterprises specializing in growing
crops is generally present in agricultural enterprises
of such European Union countries as Austria,
Belgium, Bulgaria, Croatia, Cyprus, Estonia, Latvia,
the Netherlands, and Romania, as evidenced by the
very high direct and indirect correlation between the
total costs of agricultural enterprises and the cost of
grain production. Efficient cost management of
agricultural enterprises specializing in industrial
crop production is generally present in agricultural
enterprises of such countries of the European Union
as Denmark, Estonia, Greece, Latvia, and Portugal,
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as evidenced by the very high direct and indirect
correlation between the total costs of agricultural
enterprises and the cost of industrial crops. The
efficient cost management of agricultural enterprises
specializing in forage crops is generally present in
agricultural enterprises of such countries of the
European Union as Belgium, Croatia, Cyprus,
Estonia, Ireland, Italy, Netherlands, Rumania,
Slovenia, Spain, and Sweden, as evidenced by the
presence of direct very high and high correlation
between the indicator of total costs of agricultural
enterprises and the indicator of the cost of producing
forage crops.
It was found that the agrarian enterprises of
Germany, Greece, and Portugal, which specialize in
the cultivation of crops, the agrarian enterprises of
Cyprus, Czech Republic, France, Germany,
Ukraine, and Luxembourg specializing in growing
industrial crops and agricultural enterprises of
Luxembourg, which specialize in the cultivation of
fodder crops, in general, should be based on the
experience of agrarian enterprises of other countries
of the European Union, which in a particular area of
agricultural production show very high and a high
degree of generality of the relationship between
costs and production costs of the appropriate type of
agrarian products.
6 Conclusions
It is stated that methodological principles of
agrarian enterprise costs management based on
European Union countries should be explained
through the determination of interrelation between
total costs of agrarian enterprises and indicators of
costs of agrarian products produced by them, using
correlation analysis.
According to the results of correlation analysis
carried out between the indicator of total costs of
agricultural enterprises and the indicator of the cost
of growing crops, The indicator of industrial crop
production costs and the indicator of forage crops
production costs for the surveyed countries of the
European Union found a very high, high, medium,
moderate and low correlation between the analyzed
variables.
It was found that an increase in the indicator of
total costs directly affects (with a very high and high
intensity of interconnection between the analyzed
variables) the increase in the indicator of the cost of
growing crops by agricultural enterprises in such
countries of the European Union, Austria, Belgium,
Bulgaria, Croatia, Cyprus, Estonia, Latvia, the
Netherlands, and Romania. An increase in the
indicator of total costs directly affects (with a very
high and high intensity of interconnection between
the analyzed variables) the increase in the indicator
of the cost of production of industrial crops by
agricultural enterprises in such countries of the
European Union, such as Denmark, Estonia, Greece,
Latvia, and Portugal. An increase in the indicator of
total costs directly affects (with a very high and high
intensity of interconnection between the analyzed
variables) the increase in the indicator of the cost of
growing forage plants by agricultural enterprises in
such countries of the European Union, such as
Belgium, Croatia, Cyprus, Estonia, Ireland, Italy,
the Netherlands, Romania, Slovenia, Spain, and
Sweden.
The practical importance of the results of the
research shows that this approach to the disclosure
of methodological principles of cost management of
agricultural enterprises by identifying the
relationship between total costs of agricultural
enterprises and indicators of the cost of agricultural
products produced by them, using thus correlation
analysis is universal and can be used for revealing
the methodological principles of cost management
of enterprises of other types of economic activities.
In the future, it is planned to disclose
methodological principles of cost management of
agricultural enterprises based on the application of
the United States of America.
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Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the Creative
Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en_US
Appendix 1
Table 3. Indicators of the cost of growing cereals at current prices, growing industrial crops at current prices, and the cost of growing fodder plants at current prices,
Million euro
â„–
Countries
2016
2017
2018
2019
2020
A1
B1
C1
A2
B2
C2
A3
B3
C3
A4
B4
C4
A5
B5
C5
1
Austria
749,33
357,48
569,79
754,07
281.15
483.05
776,49
246.42
479,75
801,11
273.67
499,66
884,19
299,29
542,24
2
Belgium
305.91
198.64
600.77
376,77
228,37
659,38
417,79
222.89
639,51
435.90
229.57
681,40
484,64
195.93
747,33
3
Bulgaria
1199,37
987,69
81.61
1246,43
1006,85
114.47
1443,72
935,16
90.38
1499,80
899,13
73.29
1253,52
812,09
80.17
4
Croatia
365.05
216.88
207.31
323.85
252.15
182.65
399.05
240,53
219.80
393.12
224.60
253.13
406,38
265.43
281.24
5
Cyprus
3.20
0.95
16.13
7.18
0.72
31.33
5.84
0.55
36.20
11.94
0.58
44.48
13.43
0.64
39.83
6
Czech Republic
1158,70
812,43
506.93
1085,51
733,01
476,21
1180.00
782,11
448,55
1219,29
701.63
591,55
1225,99
752,64
596,41
7
Denmark
1129,68
269.13
751,58
1358,64
357,49
799,85
1327,51
254.83
788,56
1301,14
340,96
th most
commo
n
772,80
1182,25
300.83
689,56
8
Estonia
111.69
70.59
59.29
175.90
76.45
62.82
149.05
58.50
64.14
222.01
92.36
76.09
229.72
99.67
69.83
9
Finland
446,44
73.86
213.27
447,14
67.63
200.55
443,33
55.63
234.61
652,18
54.61
319,22
468,14
55.16
244.46
10
France
8003,17
3864,21
5480.83
9846.95
4373,51
5213.13
10763.1
5
4056,23
5195.24
10793.1
2
3506,88
5463.81
9484.14
3553,00
5565.57
11
Germany
5659.29
4739,79
5218.58
6664.60
4646,24
4662,29
5567.63
4436,27
3327,76
7167.32
3926,01
5503.44
7050.78
4045,31
5266.45
12
Greece
785,56
892,09
591,06
724,96
965,59
562,46
668.01
1013,16
621,43
704,13
1047,57
642,38
731,26
974,85
668.90
13
Hungary
2223,54
1218,86
222.22
1998,53
1257,35
208.54
2238,24
1086,18
224.63
2300,71
1053,21
219.06
2272,99
1082,49
203.69
14
Ireland
304.81
8.64
975,43
325.07
9.90
1017,91
361.72
9.87
1266,97
365.24
10.33
1013,44
306.04
10.33
1011,84
15
Italy
4034,01
786,07
1382,53
3500,59
849,80
1469,24
3680,16
820,02
1880,24
3679,35
808,52
1787,48
3904,71
825,28
1716,48
16
Latvia
359,77
127.73
81.79
376,76
153.89
73.21
353,48
110.63
67.39
504.43
177.64
82.08
587,29
200.49
86.71
17
Lithuania
811,08
363.64
235,49
881,40
410,58
249.42
813,06
310,37
th most
commo
n
252.05
966,86
397,49
248.81
1198,05
504.80
241.36
18
Luxembourg
18.27
4.06
115.50
21.31
4.38
98.98
26.18
4.31
95.58
24.01
3.92
96.15
22.85
3.57
89.13
19
Malta
n.d.
n.d.
2.74
n.d.
n.d.
3.98
n.d.
n.d.
4.25
n.d.
n.d.
4.20
n.d.
n.d.
3.85
20
Netherlands
267.55
205,73
th most
628,57
277.58
270.08
643,86
338,56
184.68
682,94
323,23
197.07
707,13
335,92
188,56
th most
738,66
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commo
n
commo
n
21
Poland
3530,89
1639,82
851,43
4031,34
1765,46
879,32
3660,41
1585,27
793,57
3959,36
1659,64
735,46
4430,
.61
1931,00
1092,72
22
Portugal
247.65
54.82
271.07
235.65
62.21
231.62
241.69
62.60
263.74
240.92
72.30
240.03
233.86
78.74
263.72
23
Romania
3448,48
1339,06
1245,46
4054,52
1800,64
1312,82
4877.45
1686,25
1446,85
4764,68
1568,64
1520,36
3207,44
1125,04
1310,04
24
Slovakia
618,38
328,18
126.89
450.25
327.13
211.98
575.64
313.72
168.89
583.05
281.14
138.25
613,86
313,78
160.35
25
Slovenia
82.79
39.70
199,39
75.83
29.78
156.94
85.79
37.24
201.95
84.76
36.63
202,35
95.74
39.13
197.93
26
Spain
3841,08
968,39
1733,46
2966,52
986,81
1539,23
4342,57
1053,15
1850,45
3643,10
834,07
1831,98
4696,37
889,37
1945,23
27
Sweden
695,80
189.59
966,84
755,35
219.84
1098,56
577,17
146.43
1056,52
775.69
219.30
1033,99
821,63
202,11
1001,64
Legend:
A1, A2,…, A5 - the cost of growing cereals, Million euro
B1, B2,…, B5 - the cost of growing industrial crops, Million euro
C1, C2,…, C5 - the cost of growing fodder plants, Million euro
Source: built by the authors according to Eurostat, 2021p.
Annex 2
Table 3. The results of the correlation analysis
Countries
Correlation between V and A
Correlation between V and B
Correlation between V and C
Austria
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.899037
1
inverted and moderate
Column 1
Column 2
Column 1
1
Column 2
-0.32626
1
straight and weak
Column 1
Column 2
Column 1
1
Column 2
0.016555
1
Belgium
straight and very high
Column 1
Column 2
Column 1
1
Column 2
0.978443
1
inverted and weak
Column 1
Column 2
Column 1
1
Column 2
-0.03033
1
straight and very high
Column 1
Column 2
Column 1
1
Column 2
0,946536
1
Bulgaria
straight and very high
Column 1
Column 2
Column 1
1
Column 2
0.975431
1
inverted and weak
Column 1
Column 2
Column 1
1
Column 2
-0.27054
1
inverted and weak
Column 1
Column 2
Column 1
1
Column 2
-0.24106
1
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Croatia
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.727042
1
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.411685
1
straight and very high
Column 1
Column 2
Column 1
1
Column 2
0.922686
1
Cyprus
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.872668
1
inverted and high
Column 1
Column 2
Column 1
1
Column 2
-0.9012
1
straight and very high
Column 1
Column 2
Column 1
1
Column 2
0.991963
1
Czech
Republic
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.673272
1
inverted and middle
Column 1
Column 2
Column 1
1
Column 2
-0.68312
1
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.508105
1
Denmark
direct and moderate
Column 1
Column 2
Column 1
1
Column 2
0.319017
1
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.765038
1
inverted and weak
Column 1
Column 2
Column 1
1
Column 2
-0.23952
1
Estonia
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.875151
1
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.747742
1
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.887476
1
Finland
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0,500831
1
inverted and moderate
Column 1
Column 2
Column 1
1
Column 2
-0.35101
1
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0,549881
1
France
straight and weak
Column 1
Column 2
Column 1
1
Column 2
0.255157
1
inverted and very high
Column 1
Column 2
Column 1
1
Column 2
-0.92656
1
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.659987
1
Germany
inverted and middle
Column 1
Column 2
Column 1
1
inverted and middle
Column 1
Column 2
Column 1
1
inverted and weak
Column 1
Column 2
Column 1
1
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Column 2
-0.05074
1
Column 2
-0.62394
1
Column 2
-0.27149
1
Greece
inverted and high
Column 1
Column 2
Column 1
1
Column 2
-0.7857
1
straight and very high
Column 1
Column 2
Column 1
1
Column 2
0,972517
1
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0,545488
1
Hungary
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0,521461
1
inverted and middle
Column 1
Column 2
Column 1
1
Column 2
-0.62256
1
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0,580768
1
Ireland
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.669352
1
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.6604
1
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.80556
1
Italy
inverted and weak
Column 1
Column 2
Column 1
1
Column 2
-0.23842
1
straight and weak
Column 1
Column 2
Column 1
1
Column 2
0.235409
1
straight and very high
Column 1
Column 2
Column 1
1
Column 2
0.922278
1
Latvia
straight and very high
Column 1
Column 2
Column 1
1
Column 2
0.956927
1
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.835799
1
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.64775
1
Lithuania
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.664037
1
direct and moderate
Column 1
Column 2
Column 1
1
Column 2
0.434986
1
direct and moderate
Column 1
Column 2
Column 1
1
Column 2
0.516302
1
Luxembourg
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.561652
1
inverted and middle
Column 1
Column 2
Column 1
1
Column 2
-0.61602
1
inverted and high
Column 1
Column 2
Column 1
1
Column 2
-0.73135
1
Malta
n.d.
n.d.
direct and medium
Column 1
Column 2
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.109
Andrii Reznik, Svitlana Lavrynenko,
Antonina Zeliska, Nataliia Mardus,
Oksana Samborska
E-ISSN: 2224-3496
1155
Volume 18, 2022
Column 1
1
Column 2
0,540233
1
Netherlands
straight and high
Column 1
Column 2
Column 1
1
Column 2
0,826051
1
inverted and weak
Column 1
Column 2
Column 1
1
Column 2
-0.31596
1
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.868318
1
Poland
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0,522489
1
straight and weak
Column 1
Column 2
Column 1
1
Column 2
0,194066
1
straight and weak
Column 1
Column 2
Column 1
1
Column 2
0.042218
1
Portugal
inverted and middle
Column 1
Column 2
Column 1
1
Column 2
-0.63735
1
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.877856
1
inverted and weak
Column 1
Column 2
Column 1
1
Column 2
-0.21846
1
Romania
straight and very high
Column 1
Column 2
Column 1
1
Column 2
0.990592
1
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.686799
1
straight and very high
Column 1
Column 2
Column 1
1
Column 2
0.924002
1
Slovakia
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.506497
1
direct and moderate
Column 1
Column 2
Column 1
1
Column 2
0.329773
1
inverted and moderate
Column 1
Column 2
Column 1
1
Column 2
-0.31337
1
Slovenia
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.615013
1
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.58427
1
straight and high
Column 1
Column 2
Column 1
1
Column 2
0,823879
1
Spain
direct and medium
Column 1
Column 2
Column 1
1
Column 2
0.558748
1
inverted and moderate
Column 1
Column 2
Column 1
1
Column 2
-0.37396
1
straight and high
Column 1
Column 2
Column 1
1
Column 2
0.744241
1
Sweden
inverted and weak
straight and weak
straight and very high
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.109
Andrii Reznik, Svitlana Lavrynenko,
Antonina Zeliska, Nataliia Mardus,
Oksana Samborska
E-ISSN: 2224-3496
1156
Volume 18, 2022
Column 1
Column 2
Column 1
1
Column 2
-0.15547
1
Column 1
Column 2
Column 1
1
Column 2
0.137122
1
Column 1
Column 2
Column 1
1
Column 2
0.986628
1
Source: calculated by the authors
WSEAS TRANSACTIONS on ENVIRONMENT and DEVELOPMENT
DOI: 10.37394/232015.2022.18.109
Andrii Reznik, Svitlana Lavrynenko,
Antonina Zeliska, Nataliia Mardus,
Oksana Samborska
E-ISSN: 2224-3496
1157
Volume 18, 2022