Unveiling Determinants of Successful Dairy Farm Performance from Dairy Exporting EU Countries
Abstract
:1. Introduction
2. Literature Review
3. Materials and Methods
4. Results and Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- OECD|Food and Agriculture Organization of the United Nations. OECD-FAO. Agricultural Outlook 2023–2032. Available online: https://chooser.crossref.org/?doi=10.1787%2F08801ab7-en(accessed on 26 March 2024).
- Augere-Granier, M.-L. The EU Dairy Sector. Main Features, Challenges and Prospects; EPRS: Luxembourg, 2018. [Google Scholar]
- European Commission. Agridata/Dairy Production. Available online: https://agridata.ec.europa.eu/extensions/DashboardDairy/DairyProduction.html (accessed on 27 March 2024).
- European Commission. Agridata/Dairy Trade. Available online: https://agridata.ec.europa.eu/extensions/DashboardDairy/DairyTrade.html (accessed on 27 March 2024).
- FAO. Dairy Market Review. Emerging Trends and Outlook in 2023. Available online: https://openknowledge.fao.org/handle/20.500.14283/cc9105en (accessed on 26 March 2024).
- European Commission. Agridata/EU Milk Specialised Farms. Available online: https://agridata.ec.europa.eu/extensions/DairyReport/DairyReport.html (accessed on 26 March 2024).
- Bełdycka-Bórawska, A.; Bórawski, P.; Guth, M.; Parzonko, A.; Rokicki, T.; Klepacki, B.; Wysokiński, M.; Maciąg, A.; Dunn, J.W. Price changes of dairy products in the European Union. Agric. Econ. 2021, 67, 373–381. [Google Scholar] [CrossRef]
- Olipra, J. Cycles in the global milk market. J. Agribus. Rural Dev. 2019, 52, 165–172. [Google Scholar] [CrossRef]
- Borychowski, M.; Grzelak, A.; Stępień, S. Economic and environmental determinants of farm succession. The empirical evidence from Wielkopolska region (Poland). J. Rural Stud. 2023, 101, 103063. [Google Scholar] [CrossRef]
- Jongeneel, R.; Gonzalez-martinez, A.; Donnellan, T.; Thorne, F.; Dillon, E.; Loughrey, J. Research for AGRI Committee—Development of Milk Production in the EU after the End of Milk Quotas. Available online: https://www.europarl.europa.eu/Reg-Data/etudes/STUD/2023/747268/IPOL_STU(2023)747268_EN.pdf (accessed on 20 February 2024).
- Buckwell, A.; Nordang Uhre, A.; Williams, A.; Poláková, J.; H Blum, W.E.; Schiefer, J.; Lair, G.J.; Heissenhuber, A.; Schieβl, P.; Krämer, C.; et al. Sustainable Intensification of European Agriculture. A review sponsored by the RISE Foundation. Available online: https://risefoundation.eu/wp-content/uploads/2020/07/2014_-SI_RISE_FULL_EN.pdf (accessed on 20 February 2024).
- Gerber, P.J.; Steinfeld, H.; Henderson, B.; Mottet, A.; Opio, C.; Dijkman, J.; Falcucci, A.; Tempio, G. Tackling Climate Change through Livestock—A Global Assessment of Emissions and Mitigation Opportunities. Available online: https://www.fao.org/4/i3437e/i3437e.pdf (accessed on 12 February 2024).
- Statistcs Lithuania. State Data Agency. Žemės Ūkio Statistika. Available online: https://osp.stat.gov.lt/zemes-ukis (accessed on 10 April 2024).
- Agricultural Data Center. Pieno Rinka. Available online: https://zudc.lt/leidiniai-ir-statistika/ (accessed on 10 April 2024).
- Van Der Meulen, H.A.B.; Dolman, M.A.; Jager, J.H.; Venema, G.S. The impact of farm size on sustainability of Dutch dairy farms. Int. J. Agric. Manag. 2014, 3, 119–123. [Google Scholar] [CrossRef]
- Malak-Rawlikowska, A.; Gębska, M.; Hoste, R.; Leeb, C.; Montanari, C.; Wallace, M.; de Roest, K. Developing a methodology for aggregated assessment of the economic sustainability of pig farms. Energies 2021, 14, 1760. [Google Scholar] [CrossRef]
- Latruffe, L.; Diazabakana, A.; Bockstaller, C.; Desjeux, Y.; Finn, J.; Kelly, E.; Ryan, M.; Uthes, S. Measurement of sustainability in agriculture: A review of indicators. Stud. Agric. Econ. 2016, 118, 123–130. [Google Scholar] [CrossRef]
- Segerkvist, K.A.; Hansson, H.; Sonesson, U.; Gunnarsson, S. Research on environmental, economic, and social sustainability in dairy farming: A systematic mapping of current literature. Sustainability 2020, 12, 5502. [Google Scholar] [CrossRef]
- Schader, C.; Grenz, J.; Meier, M.S.; Stolze, M. Scope and precision of sustainability assessment approaches to food systems. Ecol. Soc. 2014, 19, 42. [Google Scholar] [CrossRef]
- FAO. SAFA Guidelines: Sustainability Assessment of Food and Agriculture Systems. Available online: https://www.fao.org/fileadmin/templates/nr/sustainability_pathways/docs/SAFA_Guidelines_Final_122013.pdf (accessed on 19 February 2024).
- Jongeneel, R.; Slangen, L. Sustainability and resilience of the dairy sector in a changing world: A farm economic and EU perspective. Sustain. Dairy Prod. 2013, 53, 55–86. [Google Scholar]
- Meul, M.; Passel, S.V.; Nevens, F.; Dessein, J.; Rogge, E.; Mulier, A.; Hauwermeiren, A.V. MOTIFS: A monitoring tool for integrated farm sustainability. Agron. Sustain. Dev. 2008, 28, 321–332. [Google Scholar] [CrossRef]
- Zahm, F.d.r.; Girard, S. La méthode IDEA 4: Indicateurs de Durabilité des Exploitations Agricoles: Principes & Guide D’utilisation: Évaluer la Durabilité des Exploitations Agricoles. Available online: https://www.edued.fr/BAS/AG02107LE.pdf (accessed on 21 February 2024).
- Zorn, A.; Esteves, M.; Baur, I.; Lips, M. Financial ratios as indicators of economic sustainability: A quantitative analysis for Swiss dairy farms. Sustainability 2018, 10, 2942. [Google Scholar] [CrossRef]
- Spicka, J.; Hlavsa, T.; Soukupova, K.; Stolbova, M. Approaches to estimation the farm-level economic viability and sustainability in agriculture: A literature review. Agric. Econ. 2019, 65, 289–297. [Google Scholar] [CrossRef]
- Buckley, C.; Donnellan, T. Teagasc National Farm Survey 2022 Sustainability Report; Athenry, Co.: Galway, Ireland, 2023. [Google Scholar]
- Kołoszycz, E. Economic viability of dairy farms in selected European Union countries. Ann. Pol. Assoc. Agric. Agribus. Econ. 2020, XXII, 129–139. [Google Scholar] [CrossRef]
- O’Donoghue, C.; Devisme, S.; Ryan, M.; Conneely, R.; Gillespie, P.; Vrolijk, H. Farm economic sustainability in the European Union: A pilot study. Stud. Agric. Econ. 2016, 118, 163–171. [Google Scholar] [CrossRef]
- Ryan, M.; Hennessy, T.; Buckley, C.; Dillon, E.J.; Donnellan, T.; Hanrahan, K.; Moran, B. Developing farm-level sustainability indicators for Ireland using the Teagasc National Farm Survey. Ir. J. Agric. Food Res. 2016, 55, 112–125. [Google Scholar] [CrossRef]
- Savickienė, J. Šeimos Ūkių Ekonominio Gyvybingumo Vertinimas. Available online: https://talpykla.elaba.lt/elaba-fedora/objects/elaba:19818737/datastreams/MAIN/content (accessed on 14 March 2024).
- Wilczyński, A.; Kołoszycz, E. Economic resilience of EU dairy farms: An evaluation of economic viability. Agriculture 2021, 11, 510. [Google Scholar] [CrossRef]
- Latruffe, L. Competitiveness, Productivity and Efficiency in the Agricultural and Agri-Food Sectors. Available online: https://www.oecd-ilibrary.org/agriculture-and-food/competitiveness-productivity-and-efficiency-in-the-agricultural-and-agri-food-sectors_5km91nkdt6d6-en (accessed on 12 February 2024).
- Parzonko, A.; Bórawski, P. Competitiveness of Polish dairy farms in the European Union. Agric. Econ. 2020, 66, 168–174. [Google Scholar] [CrossRef]
- Irz, X.; Jansik, C. Competitiveness of Dairy Farms in Northern Europe: A Cross-Country Analysis. Available online: https://journal.fi/afs/article/view/50881 (accessed on 12 February 2024).
- Engelberts, L.; van Rheede, A.; Kievit, H.; Nijhof, A. Appreciating multiple realities in the transformation towards a sustainable dairy sector: An explorative study from the inside-out perspective. Agronomy 2021, 11, 2116. [Google Scholar] [CrossRef]
- Hoes, A.C.; Aramyan, L. Blind Spot for Pioneering Farmers? Reflections on Dutch Dairy Sustainability Transition. Sustainability 2022, 14, 10959. [Google Scholar] [CrossRef]
- Runhaar, H.; Fünfschilling, L.; van den Pol-Van Dasselaar, A.; Moors, E.H.M.; Temmink, R.; Hekkert, M. Endogenous regime change: Lessons from transition pathways in Dutch dairy farming. Environ. Innov. Soc. Transit. 2020, 36, 137–150. [Google Scholar] [CrossRef]
- Alem, H. The role of technical efficiency achieving sustainable development: A dynamic analysis of Norwegian dairy farms. Sustainability 2021, 13, 1841. [Google Scholar] [CrossRef]
- Cele, L.P.; Hennessy, T.; Thorne, F. Regional technical efficiency rankings and their determinants in the Irish dairy industry: A stochastic meta-frontier analysis. Agribusiness 2022, 39, 727–743. [Google Scholar] [CrossRef]
- Latruffe, L.; Desjeux, Y. Common Agricultural Policy support, technical efficiency and productivity change in French agriculture. Rev. Agric. Food Environ. Stud. 2016, 97, 15–28. [Google Scholar] [CrossRef]
- Poczta-Wajda, A. Economic viability of family farms in Europe—A literature review. Ann. Pol. Assoc. Agric. Agribus. Econ. 2020, XXII, 161–172. [Google Scholar] [CrossRef]
- Stoychev, V.; Ivanov, B. Comparison of competitiveness between Bulgaria, EU, USA, and New Zealand dairy sectors. Econ. Sci. Agribus. Rural. Econ. 2022, 5, 70–75. [Google Scholar] [CrossRef]
- Viira, A.-H.; Omel, R.; Värnik, R.; Luik, H.; Maasing, B.; Põldaru, R. Competitiveness of the Estonian dairy sector, 1994–2014. J. Agric. Sci. 2014, 26, 84–105. [Google Scholar]
- Ziętara, W.; Mirkowska, Z. Concentration of dairy cow breeding and competitiveness of Polish farms specialized in milk production. Ann. Pol. Assoc. Agric. Agribus. Econ. 2023, XXV, 168–181. [Google Scholar] [CrossRef]
- Średzińska, J.; Siemiński, P.; Godek, M. Income Situation of Dairy Farms in European Union Countries: A Synthetic Approach. Eur. Res. Stud. J. 2021, 24, 993–1011. [Google Scholar] [CrossRef]
- Syrůček, J.; Bartoň, L.; Burdych, J. Break-even point analysis for milk production—Selected EU countries. Agric. Econ. 2022, 68, 199–206. [Google Scholar] [CrossRef]
- Poczta, W.; Średzińska, J.; Chenczke, M. Economic situation of dairy farms in identified clusters of European Union countries. Agriculture 2020, 10, 92. [Google Scholar] [CrossRef]
- Balezentis, T.; Chen, X.; Galnaityte, A.; Namiotko, V. Optimizing crop mix with respect to economic and environmental constraints: An integrated MCDM approach. Sci. Total Environ. 2020, 705, 135896. [Google Scholar] [CrossRef]
- Morkunas, M.; Volkov, A. The Progress of the Development of a Climate-smart Agriculture in Europe: Is there Cohesion in the European Union? Environ. Manag. 2023, 71, 1111–1127. [Google Scholar] [CrossRef]
- Namiotko, V.; Galnaityte, A.; Krisciukaitiene, I.; Balezentis, T. Assessment of agri-environmental situation in selected EU countries: A multi-criteria decision-making approach for sustainable agricultural development. Environ. Sci. Pollut. Res. 2022, 29, 25556–25567. [Google Scholar] [CrossRef]
- Dace, E.; Blumberga, D. How do 28 European Union Member States perform in agricultural greenhouse gas emissions? It depends on what we look at: Application of the multi-criteria analysis. Ecol. Indic. 2016, 71, 352–358. [Google Scholar] [CrossRef]
- Matysik-Pejas, R.; Bogusz, M.; Daniek, K.; Szafrańska, M.; Satoła, Ł.; Krasnodębski, A.; Dziekański, P. An Assessment of the Spatial Diversification of Agriculture in the Conditions of the Circular Economy in European Union Countries. Agriculture 2023, 13, 2235. [Google Scholar] [CrossRef]
- Nowak, A.; Krukowski, A.; Różańska-Boczula, M. Assessment of sustainability in agriculture of the European Union countries. Agronomy 2019, 9, 890. [Google Scholar] [CrossRef]
- Stecy, A. The AHP-TOPSIS model in the analysis of the counties sustainable development in the West Pomeranian Province in 2010 and 2017. J. Ecol. Eng. 2019, 20, 233–244. [Google Scholar] [CrossRef]
- Validi, S.; Bhattacharya, A.; Byrne, P.J. A case analysis of a sustainable food supply chain distribution system—A multi-objective approach. Int. J. Prod. Econ. 2014, 152, 71–87. [Google Scholar] [CrossRef]
- Galnaitytė, A.; Kriščiukaitienė, I.; Baležentis, T.; Namiotko, V. Evaluation of technological, economic and social indicators of different farming practices in Lithuania. Econ. Sociol. 2017, 10, 189–202. [Google Scholar] [CrossRef]
- Galnaitytė, A.; Kriščiukaitienė, I.; Namiotko, V.; Dabkienė, V. Assessment of the Lithuanian Pig Farming Sector via Prospective Farm Size. Agriculture 2024, 14, 32. [Google Scholar] [CrossRef]
- Nowak, A.; Kaminska, A. Agricultural competitiveness: The case of the European Union countries. Agric. Econ. 2016, 62, 507–516. [Google Scholar] [CrossRef]
- Rouyendegh, B.D.; Savalan, Ş. An Integrated Fuzzy MCDM Hybrid Methodology to Analyze Agricultural Production. Sustainability 2022, 14, 4835. [Google Scholar] [CrossRef]
- Vistarte, L.; Pubule, J.; Balode, L.; Kaleja, D.; Bumbiere, K. An Assessment of the Impact of Latvian New Common Agriculture Policy: Transition to Climate Neutrality. Environ. Clim. Technol. 2023, 27, 683–695. [Google Scholar] [CrossRef]
- Volkov, A.; Balezentis, T.; Morkunas, M.; Streimikiene, D. Who Benefits from CAP? The way the direct payments system impacts socioeconomic sustainability of small farms. Sustainability 2019, 11, 2112. [Google Scholar] [CrossRef]
- Hwang, C.L.; Yoon, K. Methods for multiple attribute decision making. In Multiple Attribute Decision Making; Springer: Berlin/Heidelberg, Germany, 1981; pp. 58–191. [Google Scholar]
- Torkayesh, A.E.; Deveci, M.; Karagoz, S.; Antucheviciene, J. A state-of-the-art survey of evaluation based on distance from average solution (EDAS): Developments and applications. Expert Syst. Appl. 2023, 221, 119724. [Google Scholar] [CrossRef]
- Keshavarz Ghorabaee, M.; Zavadskas, E.K.; Olfat, L.; Turskis, Z. Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica 2015, 26, 435–451. [Google Scholar] [CrossRef]
- Gonzalez-Mejia, A.; Styles, D.; Wilson, P.; Gibbons, J. Metrics and methods for characterizing dairy farm intensification using farm survey data. PLoS ONE 2018, 13, e0195286. [Google Scholar] [CrossRef]
- Kołoszycz, E.; Świtłyk, M. The production and economic results of dairy farms belonging to the European dairy farmers in 2016. Probl. Agric. Econ. 2019, 1, 88–105. [Google Scholar] [CrossRef]
- Syrůček, J.; Bartoň, L.; Řehák, D.; Kvapilík, J.; Burdych, J. Evaluation of economic indicators for Czech dairy farms. Agric. Econ. 2019, 65, 499–508. [Google Scholar] [CrossRef]
- Cele, L.P.; Hennessy, T.; Thorne, F. Evaluating farm and export competitiveness of the Irish dairy industry: Post-quota analysis. Compet. Rev. 2022, 32, 1–20. [Google Scholar] [CrossRef]
- Entrena-Barbero, E.; Tarpani, R.R.Z.; Fernández, M.; Moreira, M.T.; Gallego-Schmid, A. Integrating circularity as an essential pillar of dairy farm sustainability. J. Clean. Prod. 2024, 458, 142508. [Google Scholar] [CrossRef]
- European Commission. EU Dairy Farms Report Based on 2018 FADN Data. Available online: https://agriculture.ec.europa.eu/system/files/2022-08/fadn-dairy-report-2021_en.pdf (accessed on 21 March 2024).
- Hanrahan, L.; McHugh, N.; Hennessy, T.; Moran, B.; Kearney, R.; Wallace, M.; Shalloo, L. Factors associated with profitability in pasture-based systems of milk production. J. Dairy Sci. 2018, 101, 5474–5485. [Google Scholar] [CrossRef]
- Key, N.; Prager, D.L.; Burns, C.B. The Income Volatility of U.S. Commercial Farm Households. Appl. Econ. Perspect. Policy 2018, 40, 215–239. [Google Scholar] [CrossRef]
- Madau, F.A.; Furesi, R.; Pulina, P. Technical efficiency and total factor productivity changes in European dairy farm sectors. Agric. Food Econ. 2017, 5, 17. [Google Scholar] [CrossRef]
- Clal.it. Per Capita Consumption Across Selected Countries in Milk Equivalent in 2023. Available online: https://www.clal.it/en/?section=tabs_consumi_procapite (accessed on 10 April 2024).
- Bórawski, P.; Pawlewicz, A.; Parzonko, A.; Harper, J.K.; Holden, L. Factors shaping cow’s milk production in the EU. Sustainability 2020, 12, 420. [Google Scholar] [CrossRef]
- Náglová, Z.; Rudinskaya, T. Factors influencing technical efficiency in the EU dairy farms. Agriculture 2021, 11, 1114. [Google Scholar] [CrossRef]
- Vrolijk, H.; Reijs, J.; Dijkshoorn-Dekker, M. Lessons from the Socio-Economic Perspective. Towards Sustainable and Circular Farming in The Netherlands. Available online: https://edepot.wur.nl/533842 (accessed on 8 April 2024).
- Jongeneel, R.; Gonzalez-Martinez, A.R. The role of market drivers in explaining the EU milk supply after the milk quota abolition. Econ. Anal. Policy 2022, 73, 194–209. [Google Scholar] [CrossRef]
- Olagunju, K.O.; Sherry, E.; Samuel, A.; Caskie, P. Unpacking Total Factor Productivity on Dairy Farms Using Empirical Evidence. Agriculture 2022, 12, 225. [Google Scholar] [CrossRef]
- Requena-i-Mora, M.; Barbeta-Viñas, M. The agrarian question in dairy farms: An analysis of dairy farms in the European Union countries. Agric. Hum. Values 2023, 41, 459–474. [Google Scholar] [CrossRef]
- Karlsson, J.O.; Robling, H.; Cederberg, C.; Spörndly, R.; Lindberg, M.; Martiin, C.; Ardfors, E.; Tidåker, P. What can we learn from the past? Tracking sustainability indicators for the Swedish dairy sector over 30 years. Agric. Syst. 2023, 212, 103779. [Google Scholar] [CrossRef]
- Latruffe, L.; Niedermayr, A.; Desjeux, Y.; Dakpo, K.H.; Ayouba, K.; Schaller, L.; Kantelhardt, J.; Jin, Y.; Kilcline, K.; Ryan, M.; et al. Identifying and assessing intensive and extensive technologies in European dairy farming. Eur. Rev. Agric. Econ. 2023, 50, 1482–1519. [Google Scholar] [CrossRef]
- Kellermann, M.; Salhofer, K. Dairy farming on permanent grassland: Can it keep up? J. Dairy Sci. 2014, 97, 6196–6210. [Google Scholar] [CrossRef] [PubMed]
- Hemme, T.; Uddin, M.M.; Ndambi, O.A. Benchmarking Cost of Milk Production in 46 Countries. J. Rev. Glob. Econ. 2014, 3, 254–270. [Google Scholar] [CrossRef]
- European Commission. Milk Market Observatory. Available online: https://agriculture.ec.europa.eu/data-and-analysis/markets/overviews/market-observatories/milk_en (accessed on 21 March 2024).
- Eurostat. Agricultural Holdings with Livestock. Available online: https://ec.europa.eu/eurostat/databrowser/view/tag00124/default/table?lang=en&category=t_agr.t_ef (accessed on 21 March 2024).
- Läpple, D.; Sirr, G. Dairy Intensification and Quota Abolition: A Comparative Study of Production in Ireland and the Netherlands. EuroChoices 2019, 18, 26–32. [Google Scholar] [CrossRef]
- Gołaś, Z. Determinants of milk production profitability of dairy farms in the EU member states. Zagadnienia Ekon. Rolnej 2017, 3, 19–40. [Google Scholar] [CrossRef]
- Jongeneel, R.; Gonzalez-Martinez, A. EU Dairy after the Quota Abolition: Inelastic Asymmetric Price Responsiveness and Adverse Milk Supply during Crisis Time. Agriculture 2022, 12, 1985. [Google Scholar] [CrossRef]
- Revoredo-Giha, C.; Clayton, P.; Costa-Font, M.; Agra-Lorenzo, F.; Akaichi, F. The Impact of Mandatory Written Dairy Contracts in European Countries and Their Potential Application in Scotland. (Social Research series). Scottish Government Social Research. 2019. Available online: https://pure.sruc.ac.uk/ws/files/34055599/impact_mandatory_written_dairy_contracts_european_countries_potential_application_scotland.pdf (accessed on 21 February 2024).
- Dabkienė, V. The comparative analysis of Lithuanian farms economic performance in the context of selected EU countries. Bulg. J. Agric. Sci. 2021, 27, 1074–1083. [Google Scholar]
Indicator | Description | Source of Literature |
---|---|---|
Productivity indicators: | ||
Farm size | Average number of dairy cows (livestock unit (LU)) per holding. Allows to estimate herd size and production scale. | Gonzalez-Mejia et al., 2018 [65]; Kołoszycz and Świtłyk, 2019 [66]; Syrůček et al., 2019 [67]; Wilczyński and Kołoszycz, 2021 [31] |
Milk yield per cow | Average milk production per cow per year (kg). Measure of production efficiency. | Syrůček et al., 2019 [67]; Wilczyński and Kołoszycz, 2021 [31] |
Number of cows per AWU | Number of dairy cows per AWU 1 Indirect measure of technology. Useful for comparing farm productivity, and for socio-economic characterisation. | Gonzalez-Mejia et al., 2018 [65]; Van Der Meulen et al., 2014 [15] |
Milk production per fodder area | Milk volume produced per ha fodder area (milk in tons/ ha fodder area). Measure of land use intensity for dairy cows. Useful for characterising farms and comparing management practices. | Cele et al., 2022 [68]; Kołoszycz and Świtłyk, 2019 [66]; Spicka et al., 2019 [25] |
Feed autonomy | Share of own-produced feed in total feed used in farm (%). Measure of self-sufficiency in feed. | Entrena-Barbero et al., 2024 [69] |
Economic indicators: | ||
Milk price | Annual milk price (Eur/t). | Entrena-Barbero et al., 2024 [69]; Galnaitytė et al., 2017 [56] |
Total operating costs | Total operating costs include specific costs for milk production (purchased concentrates, purchased coarse fodder, farm use of non-fodder crops, specific forage costs, milk herd renewal costs, and the milk levy and other specific livestock costs (veterinary, etc.))+ non-specific costs: upkeep of machinery and buildings, power (fuel and electricity), contract work, taxes and other dues, taxes on land and buildings, insurance for farm buildings, and other direct costs (Eur/t) [70]. | Galnaitytė et al., 2017 [56]; Hanrahan et al., 2018 [71] |
Depreciation | Annual depreciation of buildings, equipment (Eur/t milk). | Key et al., 2018 [72] |
Farm net value added/AWU | Farm net value added (FNVA) = total output − intermediate consumptions + balance subsidies and taxes − depreciation divided by AWU (FNVA/AWU, Eur). | Madau et al., 2017 [73] |
External economic environment indicators: | ||
Milk production per capita | Indicates the level of self-sufficiency in milk and the export orientation of the country’s dairy sector, calculated as the amount of milk produced in the country divided by the country’s population (due to the different methodologies for calculating the self-sufficiency indicator and the varying values of the indicator reported in different sources, we did not use the self-sufficiency indicator in the study to assess the sector’s dependence on exports) (kg milk per capita). In EU countries, the average consumption of milk and dairy products per capita was 251 kg per year [74], suggesting that in countries where per capita production is well above this level of consumption, the self-sufficiency in milk and dairy products is high. | Stoychev and Ivanov, 2022 [42] |
Gross domestic product (GDP) at market prices | GDP at current prices, Eur per capita. | Bórawski et al., 2020 [75]; Nowak and Kaminska, 2016 [58] |
Farm Size (Dairy Cows/Farm) | Cows/AWU | Milk Yield per Cow (kg/cow) | Milk/Fodder Area (t/ha) | Feed Autonomy (Share of Own Produced Feed %) | Milk Price (Eur/t) | Total Operating Costs (Eur/t) | Depreciation (Eur/t) | FNVA/AWU (Eur/AWU) | Milk Production per Capita (kg/capita) | GDP at Market Prices (Eur/capita) | |
---|---|---|---|---|---|---|---|---|---|---|---|
Weight | 0.1 | 0.1 | 0.1 | 0.05 | 0.05 | 0.15 | 0.15 | 0.05 | 0.15 | 0.05 | 0.05 |
Direction | max | max | max | max | max | max | min | min | max | max | max |
Countries 2 | Sample Farms | Farm Size (LU) 1 | Forage Area (ha) | Milk Production (t) | Milk Yield per Cow (kg/cow) 1 | Livestock Density (LU/ha) | Milk per ha Fodder Area (t/ha) 1 | Feed Autonomy (%) 1 | Cows/AWU 1 | AWU | Share of Family Work Unit (%) |
---|---|---|---|---|---|---|---|---|---|---|---|
Ireland | 317 | 80 | 65 | 467 | 5865 | 1.23 | 7.2 | 31% | 47.3 | 1.7 | 84% |
Denmark | 407 | 188 | 126 | 1854 | 9841 | 1.49 | 14.3 | 33% | 54.0 | 3.5 | 35% |
Netherlands | 367 | 102 | 57 | 901 | 8815 | 1.80 | 15.8 | 22% | 55.1 | 1.9 | 88% |
Luxembourg | 248 | 77 | 88 | 601 | 7809 | 0.87 | 6.8 | 27% | 42.6 | 1.8 | 87% |
Estonia | 120 | 114 | 199 | 1085 | 9554 | 0.57 | 5.3 | 38% | 18.9 | 6.0 | 15% |
Lithuania | 324 | 13 | 25 | 76 | 5980 | 0.51 | 3.0 | 55% | 7.2 | 1.8 | 80% |
Latvia | 341 | 20 | 43 | 134 | 6786 | 0.46 | 3.1 | 44% | 9.1 | 2.2 | 60% |
Austria | 660 | 22 | 25 | 156 | 7228 | 0.86 | 6.2 | 31% | 12.8 | 1.7 | 99% |
Finland | 239 | 41 | 54 | 381 | 9233 | 0.77 | 7.1 | 29% | 19.5 | 2.1 | 81% |
Germany | 2887 | 73 | 62 | 590 | 8047 | 1.18 | 9.5 | 28% | 31.9 | 2.3 | 64% |
France | 1350 | 64 | 80 | 456 | 7086 | 0.81 | 5.7 | 30% | 32.1 | 2.0 | 86% |
Belgium | 305 | 75 | 54 | 593 | 7875 | 1.40 | 11.0 | 24% | 38.6 | 2.0 | 96% |
Poland | 2562 | 19 | 15 | 117 | 6169 | 1.27 | 7.8 | 47% | 10.2 | 1.9 | 94% |
Slovenia | 138 | 19 | 17 | 110 | 5709 | 1.15 | 6.6 | 47% | 11.2 | 1.7 | 100% |
Czech Republic | 220 | 178 | 305 | 1471 | 8259 | 0.58 | 4.8 | 56% | 9.9 | 17.9 | 7% |
Sweden | 364 | 88 | 128 | 805 | 9103 | 0.69 | 6.3 | 26% | 32.1 | 2.8 | 63% |
Hungary | 108 | 56 | 44 | 448 | 7955 | 1.28 | 11.6 | 38% | 13.3 | 4.2 | 22% |
Slovakia | 63 | 232 | 670 | 1701 | 7326 | 0.35 | 2.5 | 69% | 8.4 | 27.6 | 2% |
Mean | x | 81 | 114 | 664 | 7702 | 0.96 | 7.5 | 38% | 25 | 4.7 | 65% |
Minimum | x | 13 | 15 | 76 | 5709 | 0.35 | 2.5 | 22% | 7.25 | 1.7 | 2% |
Maximum | x | 232 | 670 | 1854 | 9841 | 1.80 | 15.8 | 69% | 55.1 | 27.6 | 100% |
Std. deviation | x | 61 | 152 | 533 | 1255 | 0.39 | 3.6 | 13% | 16.2 | 6.7 | 33% |
Median | x | 74 | 60 | 529 | 7842 | 0.87 | 6.7 | 32% | 19.2 | 2.1 | 80% |
Coefficient of variation | x | 75% | 133% | 80% | 16% | 41% | 48% | 33% | 64% | 141% | 50% |
Countries 2 | Milk Price (Eur/t) 1 | Coupled Payment (Eur/t) | Total Operating Costs (Eur/t) 1 | Gross Margin (Eur/t) | Depreciation Eur/t milk 1 | FNVA/AWU Eur 1 | Balance Subsidies and Taxes/AWU | Share of Subsidies in FNVA | Milk Production per Capita kg 1 | GDP at Market Prices (Eur/capita) 1 |
---|---|---|---|---|---|---|---|---|---|---|
Ireland | 335 | 0.0 | 201 | 134 | 24.3 | 50,776 | 12,670 | 25% | 1624 | 67,283 |
Denmark | 390 | 0.0 | 274 | 116 | 37.4 | 94,312 | 21,153 | 22% | 965 | 52,177 |
Netherlands | 394 | 0.0 | 261 | 133 | 48.7 | 72,573 | 10,404 | 14% | 837 | 44,963 |
Luxembourg | 341 | 0.0 | 235 | 106 | 92.4 | 55,157 | 47,430 | 86% | 673 | 98,880 |
Estonia | 312 | 6.4 | 230 | 88 | 41.5 | 27,079 | 13,413 | 50% | 608 | 19,627 |
Lithuania | 288 | 17.2 | 186 | 119 | 74.6 | 8,067 | 5,359 | 66% | 554 | 16,240 |
Latvia | 292 | 23.7 | 217 | 99 | 45.1 | 10,622 | 7,192 | 68% | 509 | 15,003 |
Austria | 378 | 0.6 | 235 | 143 | 94.2 | 22,002 | 13,968 | 63% | 428 | 43,443 |
Finland | 375 | 83.5 | 357 | 101 | 91.8 | 26,800 | 38,566 | 144% | 428 | 42,280 |
Germany | 363 | 0.0 | 244 | 119 | 47.7 | 46,764 | 18,177 | 39% | 398 | 40,643 |
France | 360 | 5.2 | 245 | 119 | 64.5 | 35,488 | 18,395 | 52% | 374 | 35,083 |
Belgium | 349 | 0.9 | 205 | 145 | 41.9 | 51,916 | 12,451 | 24% | 367 | 40,350 |
Poland | 307 | 11.2 | 166 | 152 | 40.7 | 12,896 | 4,747 | 37% | 314 | 12,993 |
Slovenia | 318 | 11.5 | 234 | 95 | 98.8 | 9,088 | 6,643 | 73% | 298 | 22,073 |
Czech Republic | 334 | 16.9 | 284 | 67 | 45.1 | 24,980 | 17,786 | 71% | 295 | 19,777 |
Sweden | 376 | 11.4 | 303 | 85 | 54.0 | 51,599 | 36,012 | 70% | 273 | 46,793 |
Hungary | 307 | 37.4 | 270 | 74 | 26.5 | 24,199 | 13,809 | 57% | 200 | 13,967 |
Slovakia | 334 | 37.6 | 329 | 43 | 51.9 | 17,799 | 14,013 | 79% | 167 | 16,463 |
Mean | 342 | 15 | 249 | 108 | 56.7 | 35,673 | 17,344 | 58% | 517 | 36,002 |
Minimum | 288 | 0 | 166 | 43 | 24.3 | 8,067 | 4,747 | 14% | 167 | 12,993 |
Maximum | 394 | 83 | 357 | 152 | 98.8 | 94,312 | 47,430 | 144% | 1624 | 98,880 |
Std. deviation | 32 | 20 | 47 | 28 | 23.0 | 23,056 | 11,510 | 30% | 338 | 21,705 |
Median | 338 | 9 | 239 | 111 | 48.2 | 26,940 | 13,888 | 60% | 413 | 37,717 |
Coefficient of variation | 9% | 140% | 19% | 26% | 41% | 65% | 66% | 51% | 65% | 60% |
Country | Rank 1 | TOPSIS | EDAS | SAW | |||
---|---|---|---|---|---|---|---|
Criterion Estimate | Rank | Criterion Estimate | Rank | Criterion Estimate | Rank | ||
Denmark | 1 | 0.7758 | 1 | 0.9713 | 1 | 0.8268 | 1 |
Netherlands | 2 | 0.6254 | 2 | 0.7942 | 2 | 0.7343 | 2 |
Ireland | 3 | 0.5372 | 3 | 0.6897 | 3 | 0.6918 | 3 |
Luxemburg | 4 | 0.5065 | 4 | 0.5600 | 5 | 0.6392 | 4 |
Belgium | 5 | 0.4683 | 5 | 0.5922 | 4 | 0.6330 | 5 |
Germany | 6 | 0.4146 | 7 | 0.5380 | 6 | 0.5945 | 6 |
Sweden | 7 | 0.4291 | 6 | 0.4974 | 7 | 0.5900 | 7 |
Estonia | 8–9 | 0.3375 | 10 | 0.4529 | 8 | 0.5529 | 8 |
France | 8–9 | 0.3373 | 11 | 0.4296 | 9 | 0.5412 | 9 |
Czech Republic | 10 | 0.3620 | 9 | 0.3919 | 10 | 0.5359 | 10 |
Slovakia | 11 | 0.3838 | 8 | 0.3139 | 11 | 0.5161 | 11 |
Hungary | 12 | 0.2503 | 12 | 0.2893 | 12 | 0.4999 | 12 |
Finland | 13 | 0.2316 | 14 | 0.2129 | 13 | 0.4937 | 13 |
Poland | 14 | 0.2399 | 13 | 0.1664 | 15 | 0.4822 | 14 |
Austria | 15 | 0.2212 | 15 | 0.1812 | 14 | 0.4813 | 15 |
Latvia | 16 | 0.1943 | 17 | 0.1045 | 16 | 0.4292 | 16 |
Lithuania | 17 | 0.2076 | 16 | 0.0498 | 17 | 0.4270 | 17 |
Slovenia | 18 | 0.1662 | 18 | 0.0430 | 18 | 0.4166 | 18 |
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Savickienė, R.; Galnaitytė, A. Unveiling Determinants of Successful Dairy Farm Performance from Dairy Exporting EU Countries. Agriculture 2024, 14, 1117. https://doi.org/10.3390/agriculture14071117
Savickienė R, Galnaitytė A. Unveiling Determinants of Successful Dairy Farm Performance from Dairy Exporting EU Countries. Agriculture. 2024; 14(7):1117. https://doi.org/10.3390/agriculture14071117
Chicago/Turabian StyleSavickienė, Rūta, and Aistė Galnaitytė. 2024. "Unveiling Determinants of Successful Dairy Farm Performance from Dairy Exporting EU Countries" Agriculture 14, no. 7: 1117. https://doi.org/10.3390/agriculture14071117