The Competitiveness of Agriculture in EU Member States According to the Competitiveness Pyramid Model
Abstract
:1. Introduction
2. Materials and Methods
- (1)
- developing a theoretical model for the analyzed problem,
- (2)
- selecting normalized and standardized variables,
- (3)
- grouping and assigning weights to indicators,
- (4)
- calculating the values of the competitiveness index
3. Results and Discussion
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Group of Factors | Variable | |
---|---|---|
Sources of competitiveness (SC) | Human resources (HR) | X1–the percentage of agricultural workers [%] |
X2–workers per 100 ha of agricultural land [AWU/100 ha] | ||
X3–the percentage of farms where the manager has full agricultural training [%] | ||
X4–share of farm managers aged under 44 (%) | ||
Farming conditions (FC) | X5–share of UAA in the total area of the country (%) | |
X6–share of ecological UAA in total UAA (total fully converted and under conversion to organic farming) (%) | ||
X7–average farm area [ha] | ||
X8–the average economic size of a farm (FADN) | ||
Capital outlays (CO) | X9–intermediate consumption per 1 ha UAA [EUR/ha] | |
X10-gross investment per 1 ha UAA [EUR/ha] (FADN) | ||
X11–fixed assets per 1 ha UAA [EUR/ha] (FADN) | ||
X12–the percentage of UAA after land improvement [%] | ||
Competitiveness effects (CE) | X13–land productivity (total production value per 1 ha UAA) [EUR/ha] | |
X14–labor productivity (gross value added per 1 AWU) [EUR/AWU] | ||
X15–share in GVA of EU’s agriculture (%) | ||
X16–capital productivity (production/total costs) [EUR] | ||
X17–share in EU food exports (Food, drinks and tobacco) [%] | ||
X18–farm income per 1 AWU [EUR/AWU] (FADN) |
Variable | Average | Min. | Min. (Country) | Max. | Max. (Country) | Standard Deviation | V (Variation Coefficient) [%] |
---|---|---|---|---|---|---|---|
X1 | 5.99 | 0.92 | Luxembourg | 27.09 | Romania | 5.72 | 96% |
X2 | 7.61 | 1.70 | United Kingdom | 43.08 | Malta | 8.23 | 108% |
X3 | 14.95 | 0.44 | Romania | 51.40 | Luxembourg | 12.88 | 86% |
X4 | 21.95 | 10.24 | Portugal | 37.56 | Poland | 6.30 | 29% |
X5 | 48.69 | 8.31 | Finland | 74.36 | Denmark | 15.11 | 31% |
X6 | 7.30 | 0.28 | Malta | 20.98 | Austria | 5.13 | 70% |
X7 | 33.77 | 1.05 | Malta | 142.70 | Czechia | 32.13 | 95% |
X8 | 144.09 | 14.97 | Romania | 506.83 | Netherlands | 137.73 | 96% |
X9 | 1666.95 | 456.90 | Latvia | 8709.02 | Netherlands | 1677.71 | 101% |
X10 | 435.27 | 61.02 | Romania | 2054.53 | Netherlands | 422.91 | 97% |
X11 | 12,147.13 | 1280.42 | Slovakia | 65,689.90 | Malta | 15,023.79 | 124% |
X12 | 5.87 | 0.00 | Ireland, Luxembourg | 31.38 | Malta | 8.44 | 144% |
X13 | 2779.68 | 585.04 | Latvia | 13,730.98 | Netherlands | 2845.46 | 102% |
X14 | 23,550.82 | 4493.67 | Latvia | 124,709.91 | Belgium | 25,860.03 | 110% |
X15 | 96.99 | 0.22 | Malta | 1696.20 | Netherlands | 314.13 | 324% |
X16 | 1.08 | 0.76 | Finland | 1.52 | Italy | 0.17 | 16% |
X17 | 3.57 | 0.05 | Malta | 15.80 | Netherlands | 4.55 | 128% |
X18 | 13,111.35 | 1366.98 | Slovakia | 29,063.87 | Belgium | 7743.60 | 59% |
Factor | Extraction Sum of Squared Loadings | |
---|---|---|
Own Value | Accounting for Variance (%) | |
HR | 2.12 | 53.1 |
FC | 1.64 | 81.9 |
CO | 2.75 | 91.5 |
SC | 1.49 | 49.7 |
CE | 3.24 | 64.9 |
HR Factor | FC Factor | CO Factor | SC Factor | CE Factor | |||||
---|---|---|---|---|---|---|---|---|---|
X1 | 0.022 | X7 | 0.941 | X9 | −0.974 | ZL | 0.912 | X13 | 0.405 |
X2 | 0.399 | X8 | 0.340 | X10 | −0.937 | WG | 0.655 | X14 | 0.882 |
X3 | 0.771 | X11 | −0.958 | NK | 0.006 | X15 | 0.103 | ||
X4 | 0.930 | X17 | 0.601 | ||||||
X18 | 0.898 |
No. | Country | SC | CE | CI |
---|---|---|---|---|
1 | Austria | 1.292 | 0.362 | 2.339 |
2 | Belgium | −0.149 | 3.183 | 4.291 |
3 | Bulgaria | −0.392 | −0.976 | −1.934 |
4 | Croatia | −1.181 | −0.932 | −2.987 |
5 | Cyprus | −1.968 | −0.698 | −3.770 |
6 | Czechia | 2.325 | −0.594 | 2.448 |
7 | Denmark | −0.181 | 1.330 | 1.626 |
8 | Estonia | 0.637 | −0.643 | −0.008 |
9 | Finland | 0.564 | 0.036 | 0.849 |
10 | France | 1.157 | 1.110 | 3.206 |
11 | Germany | 0.717 | 1.017 | 2.453 |
12 | Greece | −0.685 | −0.460 | −1.619 |
13 | Hungary | −0.875 | −0.604 | −2.093 |
14 | Ireland | 0.518 | 0.292 | 1.145 |
15 | Italy | −1.152 | 0.639 | −0.726 |
16 | Latvia | 0.173 | −0.854 | −0.963 |
17 | Lithuania | −0.303 | −0.731 | −1.463 |
18 | Luxembourg | 1.590 | 1.023 | 3.695 |
19 | Netherlands | −0.171 | 0.468 | 0.419 |
20 | Poland | 1.322 | −0.732 | 0.834 |
21 | Portugal | −1.500 | −0.518 | −2.855 |
22 | Romania | −0.345 | −0.966 | −1.854 |
23 | Slovakia | 0.065 | −1.137 | −1.516 |
24 | Slovenia | −0.617 | −1.006 | −2.296 |
25 | Spain | −0.888 | 0.701 | −0.264 |
26 | Sweden | −0.168 | −0.010 | −0.252 |
27 | United Kingdom | 0.216 | 0.699 | 1.294 |
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Nowak, A.; Różańska-Boczula, M. The Competitiveness of Agriculture in EU Member States According to the Competitiveness Pyramid Model. Agriculture 2022, 12, 28. https://doi.org/10.3390/agriculture12010028
Nowak A, Różańska-Boczula M. The Competitiveness of Agriculture in EU Member States According to the Competitiveness Pyramid Model. Agriculture. 2022; 12(1):28. https://doi.org/10.3390/agriculture12010028
Chicago/Turabian StyleNowak, Anna, and Monika Różańska-Boczula. 2022. "The Competitiveness of Agriculture in EU Member States According to the Competitiveness Pyramid Model" Agriculture 12, no. 1: 28. https://doi.org/10.3390/agriculture12010028
APA StyleNowak, A., & Różańska-Boczula, M. (2022). The Competitiveness of Agriculture in EU Member States According to the Competitiveness Pyramid Model. Agriculture, 12(1), 28. https://doi.org/10.3390/agriculture12010028