Assessment of the Lithuanian Pig Farming Sector via Prospective Farm Size

Abstract

Scientists, politicians, and practitioners are debating the current structure of pig farms in Lithuania, as medium and small farms have almost disappeared over the past decade. The debated problem is whether the revitalization of medium and small pig farms would sustainably contribute to self-sufficiency in pork production. Therefore, this research aims to determine which farms in terms of size could offer the best prospect for Lithuania. In order to achieve this aim, the multicriteria evaluation method TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) was used. The production and economic indicators of the Lithuanian pig farming sector in Lithuania and in the context of the selected EU countries of Belgium, Denmark, Germany, Estonia, Spain, France, Latvia, Netherlands, Austria, and Poland were analyzed. The main research period was 2004–2022. The multicriteria evaluation led to the conclusion that Danish pig farms were the best-managed. Large industrial farms were found to dominate in that country. Large pig farms (approximately two thousand sows) appeared as the best prospect in Lithuania: they took first place in the years examined (2016–2021). The criterion estimate of their assessed indicators was much higher than that of the medium (100 sows) and small (20 sows) farms. The main reasons are significantly higher labor productivity, lower cost, lower price, and better production indicators. Large pig farms generate relatively higher incomes and can meet the increasing environmental requirements and devote a larger part of the income to wages. Further research should consider the European Green Deal and the Farm to Fork Strategy, which are of great importance to farms and policymakers.

1. Introduction

The pig farming sector is one of the most economically important sectors of Lithuanian agriculture. From 2004 to 2017, pig production occupied the second place in animal production after milk. Later, in the 2018–2021 period, pig production fell to the third position after milk and poultry production [1]. However, pig production has been on a downward trend since Lithuania’s accession to the EU, with a negative annual growth rate of −1.3% between 2004 and 2021. It can be stated that pork production in Lithuania has undergone many changes over the last decades. According to the data published by the Lithuanian Agricultural Data Centre [1], the number of pigs at the beginning of 2022 was 1.8 times lower than in 2004, with an annual negative growth rate of −3.4%. The number of pig farms in Lithuania has fallen more than 20 times between 2003 and 2020, from 169.2 to 8.4 thousand units. The structure of farms has changed from family operations with a herd size of three–nine pigs, which accounted for about one-third of pig farms in 2003, to large-scale pig farms with a herd size of more than five thousand pigs, which accounted for 87.6% in 2020.

Summing up, during the last decade, the Lithuanian pig sector developed the same tendency as the European pig sector, which increased in average farm size and decreased in the total number of farms [2,3].

Full self-sufficiency in pork production is one of Lithuania’s strategic goals [4]. This is important for the development of the pig farming sector. This is confirmed by the literature [5,6,7], which states that it is important for the state due to higher income for the sector, job creation, and ensuring food security.

It is worth noting that, traditionally, the consumption of pork occupies an important place in the meat consumption of Lithuania. An increasing tendency of meat consumption per capita during 2004–2021 has been observed. Per capita, the consumption of pork has also increased steadily over the last decade, reaching 59 kg in 2021, accounting for 58.4% of total meat consumption. While per capita production has remained stable, the self-sufficiency rate has gradually decreased from 78% in 2004 to 47% in 2021 (Figure 1). To meet the rest of the demand, pork was imported into the country, and in 2021, pork imports accounted for around two-thirds of the production level [1].

Additional problems related to pig farming were exacerbated by outbreaks of African swine fever. According to the State Food and Veterinary Service, since 2014, when African swine fever was first reported in Lithuania, the country’s farms have lost almost 78.0 thousand pigs [8].

The resilience of farms in the pig farming sector was put to the test during the COVID-19 outbreak. The restrictions imposed by the closure of catering establishments during the pandemic and the decrease in export prices caused additional difficulties for pig farms. During the COVID-19 outbreak, Lithuanian agricultural entities received product/service-oriented support in the form of loans to ensure the liquidity of the entities, compensation of interest and guarantee premiums for the agricultural and fisheries sectors, and compensation of interest paid on loans and leasing services without guarantee. The support was also provided for specific agricultural subsectors such as poultry and eggs, milk, cattle, pigs, vegetables, and fur-bearing animals. Lithuanian agricultural entities could apply for support under the measure “Exceptional temporary support for farmers and small and medium-sized enterprises (SMEs) particularly affected by the COVID-19 crisis” under the Lithuanian Rural Development Programme 2014–2020 [9].

The war in Ukraine after Russia invaded Ukraine (on 24 February 2022) reinforced the effect of COVID-19, as these two crises happened so close together [10]. In the case of Lithuania, the prices for energy according to the Economic Accounts for Agriculture increased 2.2 times in 2022 compared with 2019, and consequently, the compound feeding stuff for pigs rose by 57% in 2022 (2015 = 100%) [11]. The feed is the main component of costs for granivore farms as it comprises approximately two-thirds of the total cost [12]. The differences between sales revenue and costs per 1 kg of pig production are presented in Figure 2 based on the data from the statistical reports on production–financial indicators of agricultural companies and other agricultural enterprises [13].

During the period of 2010–2021, pig farms operated profitably, with the exception of the years 2010 and 2011, in which the average profit reached—0.08 EUR/kg [13] (Figure 2). Such profits could only satisfy large farms, and consequently, small farms had to withdraw from the pig farming business.

The other challenges for Lithuanian pig farms are related to the changing animal welfare requirements. In the current unfavorable economic situation of Lithuanian pig farms, the introduction of animal welfare measures, considering European Food Safety Authority (EFSA) [14] recommendations and implementing the EU’s Green Deal strategy [15], is becoming a major financial problem. These EU-wide requirements demand a clear implementation of measures and financial support to pig production farms to sustain an already weakening sector.

Large pig farming operations have formed under the Lithuanian conditions due to external and internal factors of the sector, and its contraction in the current period has made Lithuania a net importer of pork: in 2022, the import of pigmeat in Lithuania exceeded production by 56.5% [1]. However, the sector still has the potential to evolve: it has qualified employees and it has buildings and infrastructure, but it needs to receive more attention in transforming it into farming that is more environmentally friendly and meets society’s expectations. There must be a prompt response to the crises in the sector, such as the sudden increases in the price of feed components, price drops caused by pig or human diseases (African swine fever, COVID-19, etc.), energy price increases due to the war or other disasters, etc.

According to the State Food and Veterinary Office’s pig farm surveillance data for 2019, many pig farms in the country do not have adequate housing facilities, manure and slurry collection, or disposal systems for the use of natural environmental enhancers, and they recommend promoting the modernization of pig farming technologies on farms.

It should be noted that the pig farming sector received the least amount of support. According to the Farm Accountancy Data Network (FADN) [12], total subsidies (excluding on investment), based on the available data for the period 2014–2021, amounted to an average of EUR 33 per thousand euro of total output, compared with a farm average of EUR 261. The other indicator, the investment-to-depreciation ratio, shows the growth of a business/agricultural entity (farm). A higher ratio indicates that the farm is investing significantly in fixed assets, which is an indication of expected future growth or development. In the case of Lithuanian pig farms (based on available data for 2014–2021), the average indicator was 0.77, while the average for all Lithuanian farms was 1.57 [12].

If there was income support and priority investment support for the pig farming sector, by distinguishing support for animal welfare and reducing the density of pigs and adding additional materials to enable proper investigation and manipulation activities, it would be possible to have more favorable health conditions for pigs, use less medication for treatment, have exceptional production quality, and promote it to Lithuanian consumers. Greater attention could be devoted to the modernization and innovation of pig farms. Given this unfavorable economic situation, farms are challenged to retain employees and attract new ones, as they do not see prospects, which exacerbates the problems in the sector.

All of the above challenges facing the Lithuanian pig sector call for solutions. Therefore, the aim of this research is to determine which farms in terms of size could offer the best prospect in Lithuania. In order to achieve this aim, the following work structure was envisaged. The literature review provides a picture of the domestic and foreign scientific research and allows for a comparison of the obtained results on the issues of pig farming in Section 2. Then, in Section 3, the materials and methods used in this research are presented. The research results related to the assessment of pig farming in Lithuania and selected EU countries are provided and discussed in Section 4. The main conclusions are summarized in Section 5.

2. Literature Review

A bibliometric analysis of the research topic was used to conduct the literature review. The greatest value of a bibliometric analysis is its power to reveal trends in scientific knowledge in a given field of research by studying published research papers using mathematical and statistical methods [16] and handling large volumes of scientific data [17] and, in this way, the analysis allows to map the evolution of the research field in a more objective and quantitative way [18].

The bibliometric analysis is a sufficiently novel tool for analyzing scientific literature, but it has been applied to analyzing agricultural research, for example, to assess the trajectories of efficiency measurement [19], agricultural co-operatives in Western countries [20], to investigate farmers’ market actors, dynamics, and attributes [21], to map innovative business models for vertical farm entrepreneurs [22], and to provide knowledge on alternative sustainable agricultural systems [23]. Research trends related to the pig sector in relation to environmental and economic issues have scarcely been investigated, so a bibliometric survey of journals, authors, institutions, and countries was carried out to fill this gap.

The literature review provides a picture of the trend in research and the development of the number of publications by country, and the most influential articles on the Web of Science disclosing the major past research streams are discussed. Furthermore, to enrich the analysis, a keyword co-occurrence analysis and a keyword cluster analysis were carried out to show research hotspots in the research field to enrich the understanding of the thematic clusters, as keyword analysis is one of the key elements of bibliometric analysis used in studies [17,21,22,24,25,26,27].

The literature review was based on a search of the Web of Science (WoS) Core Collection. On the WoS website (https://www.webofscience.com/ (accessed on 28 March 2023), the following query string search was processed in the search engine: TOPIC (searches title, abstract, author keywords, Keywords plus) = “pig farm*” OR “swine farm*”. The WoS offers the classification of papers by research areas. In order to find publications focusing on pig farming and pig production in economic, environmental, and agricultural policy research, we refined the search by Agricultural Policy, Economics, Climate Change, and Environmental Sciences themes. The bibliometric mapping of the keywords found in the publications was performed using the bibliometric software Visualisation of Similarities (VOS) viewer version 1.6.18 (VOSviewer) developed by van Eck and Waltman [28].

A total of 207 publications were retrieved from the database. Figure 3 shows the increase in the number of publications focusing on pig farming each year in relation to aspects of agricultural policy (economic, environmental, and social) as a research topic. The entire research period (1991–2023) could be divided into three stages based on the change and increase in the number of publications. The first stage was from 1991 to 2003, when an average of 1.3 articles were published per year. The second stage, from 2004 to 2013, reveals a greater interest of researchers in this field, with an upward trend in the number of publications. The third stage, which can be described as a phase of slow growth of publications, accounted for 68% of all publications during the period analyzed (Figure 3).

The topic of pig farming in the context of the selected research areas covers 25 countries (Figure 4). The analysis of country contributions shows that The Netherlands and China have the highest number of publications (33 publications each), followed by France (23 articles) and Germany (20 articles). The European region contributes 68% of all publications. Lithuanian researchers contributed only three publications—Jurkėnaitė and Paparas [29], Jurkėnaitė and Syp [30], and Venslauskas et al. [31].

Jurkėnaitė and Paparas’s [29] and Jurkėnaitė and Syp’s [30] articles investigate pigmeat price transmissions via supply chain. Venslauskas et al. [31] provided three nutrient flow scenarios on a farm to evaluate the environmental impacts of conventional and sustainable pig slurry management practices. However, the functional unit of the presented farm in the method was taken to be a 1000-pig-rearing farm having 867 hectares. According to the State Data Agency [1], in 2020, there were only six farms in the size group of 1000 and 2000 pigs, and the latest data (2023) from the Farm Accountancy Data Network [32] shows that specialist granivore farms had on average 19.76 hectares of utilized agricultural area in 2021.

Considering the distinct stages of the publications trend, twelve publications were published in the first stage, of which eight articles (two-thirds) concerned research carried out in Europe: five in The Netherlands and others in Belgium, Denmark, and France. The most cited stage-one article was an analysis of the strategic planning of Dutch pig farmers by Lansink et al. [33], with a total of 31 citations (up to October 2023 in WoS core). The authors conducted a study prompted by the situation in the pig sector, in which the Dutch pig sector was facing extreme changes due to new and stricter government legislation on animal welfare and environmental protection. Based on a farmer questionnaire and using a multivariate probit model, the authors investigated how pig farmers would react to these changes. The research findings disclosed that having a successor and/or being a young farmer reduces the likelihood of stagnation and increases the likelihood of having plans to increase the size of the farm/rebuild the barn and enhance quality.

In stage two, The Netherlands and France were the leading countries in terms of publications (eight articles each). On the other hand, four-fifths of the total number of articles were attributed to European research. During this period, research in the EU countries was boosted by the introduction of the Council Directive 2008/120/EC of 18 December 2008, laying down minimum standards for the protection of pigs [34]. The top-cited article from the second-stage period received 108 citations. The authors Meul et al. [35] address the issue of the energy use efficiency of milk, arable, and pig farms. The results of the study in relation to the pig sector showed that the most energy-efficient pig farms were intensive farms where high production was combined with low energy consumption.

Out of 142 publications conducted during stage three, 86% were from Europe. The Netherlands held the first place with 20 publications produced. England (with 13 publications), Germany, Spain, and France (12 publications each) followed just behind in quantity. The most-cited article (79 citations) is a study on the environmental impact of pig farming in Denmark, The Netherlands, Spain, France, and Germany by Dourmad et al. [36]. The main finding of the study shows an inverse relationship between the degree of intensification and the environmental impact per kilogram of pig production.

An all-keywords analysis (with fractional counting method) was carried out to identify the main research ideas and directions within pig farming related to the selected themes of the publications in the identified stages of publications and over a given period of time. A minimum of five (5) occurrences of a keyword was applied as a threshold factor. Thus, out of 1098 keywords from 207 publications, only 61 keywords met the threshold. The overlay visualization of keywords discloses the main topics from 2014 (marked in yellow) to 2020 (marked in blue) (Figure 5). The keywords were formed into five clusters and uncovered the following research topics: cluster 1 (covering environmental issues such as ammonia emissions, manure management, biogas); cluster 2 (related to the assessment of the system and covering life cycle analysis and carbon footprint); cluster 3 (dealing with productivity and efficiency measures); cluster 4 (concerning meat, food, market), and cluster 5 (involving food safety and production systems).

In co-occurrence with the keywords analysis from the stage-one publications, two clusters of keywords were constructed by VOSviewer: the first cluster, related to methods used in the publications, comprises “asymptotic least squares”, “cointegration”, “forecasting models”, and “prediction”, while the second cluster, which focuses on the environmental issues, covers “nature quality”,” nutrient surplus”, “environmental accounting”, and “energy use”.

Based on the co-occurrence of the second-stage keywords, three clusters were found: The first cluster is mainly concerned with the environmental assessment of the pig sector, including keywords such as “emissions”, “environmental impact”, and “life cycle assessment”. The second cluster is linked mainly to the efficiency of the pig sector, including keywords such as “data envelopment analysis”, “environmental efficiency”, and “technical efficiency”. The third cluster included only three keywords: “model”, “nitrogen”, and “pig production”.

The keywords from the third-stage publications cover a broader range of issues than in the first two stages of the analysis and are classified into three clusters. The first cluster is mainly about “environmental impacts” and “emissions”, although a new keyword, “animal welfare”, was introduced. The second cluster consists of keywords such as “carbon”, “footprint”, “life cycle analysis”, and “sustainability”. The third cluster reveals the assessment of the pig sector in terms of such measures as “productivity”, “profitability”, and “technical efficiency”.

To summarize the studies mentioned earlier by Lithuanian researchers, it can be stated that the research of Venslauskas et al. [31] is connected with the cluster 1 topics, while the research of Jurkėnaitė and Paparas [29] and Jurkėnaitė and Syp [30] is linked with cluster 4 topics.

There are limited studies on determining prospective farm size. The most recent studies include research on the U-shaped relationship between farm productivity and farm scale based on Indian data [37], the relationship between farm size and efficiency in wheat farms in the European Union [38], and the relationship between farm size and agricultural production efficiency in Chinese agriculture [39].

Huong et al. [40] analyzed the technical efficiency of pig production in Vietnam. Their findings in relation to herd size disclose that increasing herd size reduces the technical efficiency of large-scale industrial farms but increases the technical efficiency of smaller traditional farms.

Petrovska [41] analyzed the efficiency of large, medium, and small farms and revealed that all farms have similar efficiency that varies between 70–90%; however, they noticed that small farms are more vulnerable to various external factors compared with large farms.

Sato et al. [42] investigated what the ideal pig farm is and why and concluded that in some countries, especially emerging economies, the preference of pork consumers for large farms is associated with the perception that sanitary conditions and food safety standards are higher on these types of farms [42,43,44].

Kuncová et al. [45], using multicriteria evaluation, assessed the effect of pig farm size on economic performance and showed that larger farms reached higher economic performance compared with smaller ones. This study showed that economies of scale are an important factor in ensuring good economic performance in the pig farming sector.

Among the factors affecting pig farms, Wang et al. [46] examined farm size and found that larger farms were able to invest more in biosecurity.

Kovács et al. [47] assessed and compared the efficiency of the livestock sector, including the pig sector, by farm size class in Hungary and Croatia. The authors found that in the pig sector, the efficiency of small farms is better than that of medium-sized farms. This is particularly evident in the results obtained in Hungary.

Ziętara [48] studied Poland, Denmark, Germany, The Netherlands, and Spain to determine what size pig farms would be competitive. It turned out that small farms did not have opportunities to compete and develop. Only large Polish and Spanish (100–500 thousand EUR standard production) pig farms could compete. Very large (more than 500 thousand EUR standard production) pig farms in the above-mentioned countries were completely competitive.

Ábel et al. [49] showed the competitive advantage of large pig farms due to their better technological development compared with small ones. The authors suggest that the solution to the problems can be found in horizontal and vertical integration.

The literature review revealed that the topic of pig production is gaining increasing attention from researchers in the context of publications on topics such as agricultural policy, economics, climate change, and the environment. Increasingly stringent policies and requirements for pig farms require solutions to help them survive on the market, to continue to operate, and to ensure that the meat is available to the population. In the literature related to pig farm size, it was observed that farms tend to get larger because economies of scale allow them to better adapt to changing economic and environmental requirements.

3. Materials and Methods

In order to achieve the aim of this research—to determine which pig farms in terms of size could offer the best prospects—a comparative analysis of the pig farming sector in Lithuania and the selected neighboring countries Latvia and Estonia, which have similar conditions and experience, as well as Poland with low pork prices, Belgium, Denmark, Germany, Spain, France, The Netherlands, and Austria as dominant actors in the EU pig farming sector, was carried out in order to better understand the structural situation in the selected countries.

Labor productivity (thousand EUR/AWU), self-sufficiency, (pct), feed price index, pork price (EUR/t), and average number of pigs in the farm (ln), which describe the competitiveness of the pig farming sector, were used in order to determine in which country pig farms were managed better (

Table 1. Selected pig farming indicators for the multicriteria evaluation.

Indicator	Description	Source of Literature
Labor productivity, thousand EUR/AWU	Output of pigs per annual work unit	Bachev, 2021 [50]; Ait-Sidhoum et al., 2021 [51]; Malak-Rawlikowska et al., 2021 [52]
Self-sufficiency, pct	Percentage of domestic pork consumption to domestic pork production	Palat and Palatova, 2020 [53]; Shi et al., 2023 [5]
Feed price change index	Change in the price of pig feed over time	Palat and Palatova, 2020 [53]; Bachev, 2021 [50]; Ait-Sidhoum et al., 2021 [51]; Malak-Rawlikowska et al., 2021 [52]
Price, EUR/t	Farm gate, live weight, pig price	Palat and Palatova, 2020 [53]; Pokorna et al., 2020 [54]; Bachev, 2021 [50]; Ait-Sidhoum et al., 2021 [51]; Malak-Rawlikowska et al., 2021 [52]
Average number of pigs on the farm, ln	Total number of pigs divided by the number of farms, which determines average farm size. Due to large differences in the values of the indicator, they are expressed in logarithms	Ait-Sidhoum et al., 2021 [51]; Malak-Rawlikowska et al., 2021 [52]
Cost, EUR/t	All the expenses incurred in pig farming divided by production volume	Pokorna et al., 2020 [54]; Bachev, 2021 [50]; Malak-Rawlikowska et al., 2021 [52]
Number of piglets (per sow per year)	An indicator affecting the volume and profit of pig meat production	Pokorna et al., 2020 [54]; Malak-Rawlikowska et al., 2021 [52]
Production (kg per pig per year)	Pig weight gain per year and the effectiveness of feeding and management practices	Secco et al., 2020 [55]; Gómez et al., 2021 [56]

).

Five important physical and economic indicators reflecting the essence of the prospective farm were chosen for this research, namely price (EUR/t), cost (EUR/t), labor productivity (EUR/AWU), number of piglets (per sow per year), production (kg per pig per year), were used to determine a prospective pig farm in Lithuania. In line with the situation observed in Lithuania, it was assumed that large farms have 2 thousand sows, medium farms—100 sows, and small farms—20 sows.

GHG emissions in pig farming are mainly related to manure management and enteric fermentation. Since 2000, the procedures for compliance with high EU standards related to environmental protection requirements in the pig farming sector have been applied in Lithuania. Large amounts of support are allocated to manure management, and the problem related to water pollution in Lithuania has largely been solved.

As for environmental indicators, and in particular comparable indicators between countries and by farm size, they are still in the early stages of development and collection, so we could not include them in this study, and they should be considered in the future.

The method of multicriteria evaluation was used to evaluate in which country pig farms are managed better and to determine the prospective pig farm size in Lithuania, considering the above-mentioned performance indicators.

An analysis of the scientific literature shows that different authors provide different classifications of multicriteria methods, but in general, according to Velasquez and Hester [57], all methods can be classified according to the type of information. When solving tasks, certain information is used that differs in its structure and level of reliability. According to its type, a multicriteria method is chosen for solving the task. In the study conducted by Velasquez and Hester [57], the following multi-criteria evaluation methods used in various fields were distinguished: MultiAttribute Utility Theory (MAUT), Analytic Hierarchy Process (AHP), Case-Based Reasoning (CBR), Data Envelopment Anal ELECTRE ysis (DEA), Fuzzy Set Theory, Simple MultiAttribute Rating Technique (SMART), Goal Programming (GP), PROMETHEE, Simple Additive Weighting (SAW), and Technique for Order Preferences by Similarity to Ideal Solutions (TOPSIS). Each of these methods has advantages and disadvantages.

In this article, we applied the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) multicriteria evaluation method, because its use is not complicated, it does not change the stages of the processing process due to the selected amount of indicators used. The TOPSIS was developed by Hwang and Yoon in 1981 [58], further developed by Yoon in 1987 [59], and by Hwang, Lai, and Liu in 1993 [60]. It is used in various fields to study phenomena characterized by different criteria. Nowak and Kaminska, in 2016, used the TOPSIS to assess the competitiveness of EU countries’ agricultural sectors [61], and in 2020, Jarosz-Angowska et al. used the TOPSIS to assess the competitive potential of the agricultural and food sectors of EU member states [62]. Luo et al., in 2021, used the TOPSIS to assess the growth performance of Chinese agricultural companies and analyze the factors influencing them [20,63].

Using the TOPSIS, the criterion estimate was calculated, which was obtained from different indicators. This method was used to estimate the prospective farm size in the pig farming sector. The TOPSIS method vector normalization used is as follows:

$$\widetilde{r_{ij}}=\frac{r_{ij}}{\sqrt{\sum _{j=1}^n{r}_{ij}^2}}.$$

(1)

($i=1,\dots ,m;j=1,\dots ,n$).

The main criterion of the TOPSIS method was calculated according to the distances to the best and worst options (solutions):

$$C_j^{\mathrm{*}}=\frac{D_j^{-}}{D_j^{\mathrm{*}}+D_j^{-}}$$

(2)

where $D_j^{\mathrm{*}}$ and $D_j^{-}$ are the total distance of the $j$th alternative to the best and worst options (solutions), respectively.

$D_j^{\mathrm{*}}$ and $D_j^{-}$ were calculated according to the following formulae:

$$D_j^{\mathrm{*}}=\sqrt{{\sum }_{i=1}^m{({\omega }_i{\tilde{r}}_{ij}-V_i^{\mathrm{*}})}^2};D_j^{-}=\sqrt{{\sum }_{i=1}^m{({\omega }_i{\tilde{r}}_{ij}-V_i^{-})}^2}$$

(3)

where $V_i^{\mathrm{*}}$ and $V_i^{-}$ are the best and worst option (solution) for each criterion $i$, respectively:

$$V^{\mathrm{*}}=\left\{V_1^{\mathrm{*}},V_2^{\mathrm{*}},\dots ,V_m^{\mathrm{*}}\right\}=\left\{\left(\underset{j}{\max }{\omega }_i{\tilde{r}}_{ij}/i\in I_1\right),\left(\underset{j}{\min }{\omega }_i{\tilde{r}}_{ij}/i\in I_2\right)\right\},$$

(4)

$$V^{-}=\left\{V_1^{-},V_2^{-},\dots ,V_m^{-}\right\}=\left\{\left(\underset{j}{\min }{\omega }_i{\tilde{r}}_{ij}/i\in I_1\right),\left(\underset{j}{\max }{\omega }_i{\tilde{r}}_{ij}/i\in I_2\right)\right\}.$$

(5)

where $I_1$ is a set of indices of maximizing indicators, and $I_2$ is a set of indices of minimizing indicators.

The maximum value of the TOPSIS criterion corresponds to the best alternative.

The main research period for the analysis of indicators was 2004–2022, and for the multicriteria evaluation, it was 2016–2022. The period for this research was chosen in order to eliminate the influence of the cyclicity of pigs on the results. Data from the European Commission, Eurostat, State Data Agency, Agricultural Data Centre, Agricultural companies, and farms were used in this research. The total number of pig farms analyzed in Lithuania fluctuated from 169.2 (2003) to 8.4 thousand units (2020). Pig farms are mostly located in the northern part of Lithuania.

4. Results and Discussion

4.1. Assessment of Pig Farming in the Context of Selected EU Countries

Different situations are observed in the analysis of the selected EU countries. After the 2013, 2016, and 2020 (the latest available Agricultural Structure Survey data provided by Eurostat) [11] analyses of the countries neighboring the EU and dominating the EU pig farming sector, it can be seen that in these countries, during the research period, pig farms had a clear tendency to increase in size. Lithuania stood out as one of the countries where these farms grew the most after Estonia. The same tendency was observed in Poland and Latvia. Poland has a fairly rational structure of farms (i.e., an even distribution of pigs is observed in all groups of farms), and although it grew the fastest, in the final result in 2020, pig farms with more than 500 livestock units reached only 37%, while this indicator reached 92% in Lithuania. It is worth noting that in Estonia and Denmark, the farms of the mentioned group had even more pigs—93%. In Germany, a somewhat different structure of farms is observed in terms of the number of pigs, but a tendency to get larger is also visible. Only in Austria did the average size of pig farms remain almost unchanged, and in this country, medium-sized farms predominate.

The largest pig farms, making up a very small proportion of all farms, raise a large proportion of all pigs. This share is particularly large in Lithuania and Latvia: 0.4% of farms grow 92% of pigs and 0.8% of farms grow 91%, respectively. The balance is much better in the other analyzed countries.

The analysis of the pig farming sector of the selected countries revealed that the farms of the countries are very different according to the indicators chosen for analysis, which described the competitiveness (

Table 2. Pig farming indicators in the selected countries in 2022.

Country	Labor Productivity, Thousand EUR/AWU	Self-Sufficiency, pct	Feed Price Change Index	Price (Live Weight), EUR/t	Average Number of Pigs on the Farm, pcs *	Average Number of Pigs on the Farm, ln *
Belgium	49	224	170	1156	1470	7.29
Denmark	49	326	142	1095	4432	8.40
Germany	61	139	159	1034	826	6.72
Estonia	55	76	157	1190	4410	8.39
Spain	50	192	154	1518	875	6.77
France	54	101	146	1260	933	6.84
Latvia	43	49	196	1338	90	4.50
Lithuania	50	50	196	1324	65	4.17
The Netherlands	46	212	158	1334	3357	8.12
Austria	57	114	146	1613	112	4.72
Poland	53	92	153	1018	131	4.88

* 2020; ln-logarithm.

). Comparable country-level data were collected from the Eurostat database [11] and balance sheets provided by the European Commission [64].

Labor productivity in Lithuania is one-fifth lower than in Germany but higher than in Belgium, Denmark, The Netherlands, and Latvia. Germany, Austria, Estonia, and France are leaders in this indicator. Lithuania’s self-sufficiency in self-produced pork is one of the smallest ones: in 2022, self-sufficiency in pork amounted to 50%, and it was 28 p.p. less than in 2004. The leading countries in pork supply are Spain, Germany, Denmark, The Netherlands, and Belgium. It should also be noted that only in Latvia, Lithuania, Estonia, and Poland, did self-sufficiency not reach 100%. The feed price change index (when 2015 = 100) illustrates the difference in feed prices in Lithuania and other EU countries. In Lithuania, a large increase in prices is observed, while in other analyzed countries, the price of fodder also increased but not as fast as in Lithuania. The increase in feed purchase prices in Lithuania in 2022 compared with 2015 was almost two times higher. As for prices, the purchase price of pigs in The Netherlands and Latvia was similar to the price in Lithuania, and the corresponding price in Poland and Germany was lower by 30 and 28%, respectively. The difference in pork price was constantly decreasing during the 2003–2022 period. The purchase price of Lithuanian pork was similar to The Netherlands and Latvia. Despite the common EU market, pork prices in Lithuania still remain about one-fifth higher than in Germany, Denmark, Belgium, and Poland and lower at the same amount than in Austria and Spain. This shows that the price convergence process is taking place in Lithuania’s favor: the competitiveness of the Lithuanian pig farming sector is increasing, considering the most important indicator—prices. The average farm size indicator was chosen to evaluate the production concept. In order to eliminate particularly large differences between the selected countries, logarithms were applied to the values.

Table A1. Index matrix for ranking results of the countries according to selected indicators.

Country	Labor Productivity, Thousand EUR/AWU	Self-Sufficiency, pct	Feed Price Change Index	Price (Live Weight), EUR/t	Average Number of Pigs on the Farm, ln *
Data
Belgium	49	224	170	1156	7.29
Denmark	49	326	142	1095	8.40
Germany	61	139	159	1034	6.72
Estonia	55	76	157	1190	8.39
Spain	50	192	154	1518	6.77
France	54	101	146	1260	6.84
Latvia	43	49	196	1338	4.50
Lithuania	50	50	196	1324	4.17
The Netherlands	46	212	158	1334	8.12
Austria	57	114	146	1613	4.72
Poland	53	92	153	1018	4.88
Weight	0.2	0.2	0.2	0.2	0.2
Direction	Max.	Max.	Min.	Min.	Max.
Transformation of data
Belgium	2389	50,176	28,791	1,335,765	53
Denmark	2370	106,276	20,158	1,199,682	71
Germany	3668	19,321	25,154	1,068,799	45
Estonia	3017	5776	24,706	1,416,100	70
Spain	2480	36,864	23,688	2,302,806	46
France	2936	10,201	21,372	1,587,600	47
Latvia	1819	2401	38,416	1,791,315	20
Lithuania	2521	2500	38,463	1,753,770	17
The Netherlands	2107	44,944	25,091	1,779,022	66
Austria	3301	12,996	21,316	2,602,092	22
Poland	2770	8464	23,473	1,036,433	24
Data normalization
Belgium	0.057	0.082	0.063	0.055	0.066
Denmark	0.057	0.119	0.053	0.052	0.077
Germany	0.071	0.051	0.059	0.049	0.061
Estonia	0.064	0.028	0.058	0.056	0.076
Spain	0.058	0.070	0.057	0.072	0.062
France	0.063	0.037	0.054	0.060	0.062
Latvia	0.050	0.018	0.073	0.063	0.041
Lithuania	0.059	0.018	0.073	0.063	0.038
The Netherlands	0.054	0.077	0.059	0.063	0.074
Austria	0.067	0.042	0.054	0.076	0.043
Poland	0.061	0.034	0.057	0.048	0.044
Distance to the best option						Total distance to the best option	$D_j^{\mathrm{*}}$
Belgium	0.0001859	0.0013876	0.0001056	0.0000424	0.0001012	0.0018227	0.0426932
Denmark	0.0001922	0.0000000	0.0000000	0.0000134	0.0000000	0.0002056	0.0143386
Germany	0.0000000	0.0046638	0.0000380	0.0000006	0.0002346	0.0049369	0.0702634
Estonia	0.0000432	0.0083356	0.0000318	0.0000662	0.0000000	0.0084768	0.0920695
Spain	0.0001578	0.0023948	0.0000196	0.0005583	0.0002185	0.0033490	0.0578703
France	0.0000554	0.0067518	0.0000024	0.0001310	0.0002018	0.0071424	0.0845128
Latvia	0.0004370	0.0102333	0.0004016	0.0002297	0.0012644	0.0125661	0.1120985
Lithuania	0.0001460	0.0101595	0.0004034	0.0002099	0.0014864	0.0124053	0.1113789
The Netherlands	0.0002926	0.0017333	0.0000371	0.0002231	0.0000064	0.0022925	0.0478801
Austria	0.0000132	0.0059942	0.0000022	0.0007924	0.0011213	0.0079233	0.0890128
Poland	0.0000857	0.0073028	0.0000174	0.0000000	0.0010295	0.0084353	0.0918439
Distance to the worst option						Total distance to the worst option	$D_j^{-}$	Criterion estimate
Belgium	0.0000529	0.0040844	0.0000962	0.0004681	0.0008120	0.0055136	0.0742537	0.6349
Denmark	0.0000496	0.0102333	0.0004034	0.0006000	0.0014864	0.0127728	0.1130166	0.8874
Germany	0.0004370	0.0010803	0.0001938	0.0007510	0.0005400	0.0030021	0.0547912	0.4381
Estonia	0.0002053	0.0000972	0.0002087	0.0004006	0.0014829	0.0023948	0.0489363	0.3471
Spain	0.0000696	0.0027273	0.0002452	0.0000205	0.0005651	0.0036276	0.0602298	0.5100
France	0.0001813	0.0003606	0.0003431	0.0002790	0.0005929	0.0017570	0.0419162	0.3315
Latvia	0.0000000	0.0000000	0.0000000	0.0001689	0.0000090	0.0001779	0.0133361	0.1063
Lithuania	0.0000779	0.0000001	0.0000000	0.0001867	0.0000000	0.0002647	0.0162681	0.1274
The Netherlands	0.0000144	0.0035435	0.0001958	0.0001746	0.0012976	0.0052259	0.0722903	0.6016
Austria	0.0002985	0.0005635	0.0003457	0.0000000	0.0000257	0.0012334	0.0351201	0.2829
Poland	0.0001357	0.0002466	0.0002534	0.0007924	0.0000418	0.0014700	0.0383405	0.2945

* 2020; ln-logarithm.

in Appendix A and

Table 3. Ranking results of the countries according to selected indicators.

Country	Criterion Estimate	Rank
Denmark	0.8874	1
Belgium	0.6349	2
The Netherlands	0.6016	3
Spain	0.5100	4
Germany	0.4381	5
Estonia	0.3471	6
France	0.3315	7
Poland	0.2945	8
Austria	0.2829	9
Lithuania	0.1274	10
Latvia	0.1063	11

present the cumulative evaluation estimates of the pig farming sector in the selected countries and the places determined by them.

The multicriteria evaluation method draws the conclusion that Danish pig farms are the best-managed. Belgium occupies second place, followed by The Netherlands, Spain, and Germany. Some fragments of these countries’ management could be applied as good practices in Lithuania. Wojciech Ziętara [48] assessed the efficiency and competitiveness of pig farms in Poland and compared them with similar farms in Germany, Denmark, The Netherlands, and Spain. He found that only large pig farms were able to compete, and very large farms were fully competitive. The results show that the major factor determining the production efficiency and competitiveness of Polish pig farms was the production scale stemming from a very low level of breeding concentration, in comparison with farms in Denmark, The Netherlands, and Germany. The pig sector is also intensive and highly concentrated in Spain [2,65]. According to Wojciech Ziętara [48], the primary prerequisite for restocking the pig population in Poland is to effectively remove existing barriers to investing in livestock buildings adapted to a larger production scale, which enables the professional production of live pigs.

4.2. Evaluation of the Lithuanian Pig Farms According to Size

In order to answer the question of what a prospective pig farm in Lithuania is according to the number of sows based on the three existing groups of farms, the five most important physical and economic indicators reflecting the essence of a prospective farm were chosen for this research: price (EUR/t), cost (EUR/t), labor productivity (EUR/AWU), number of piglets (per sow per year), and production (kg per pig per year). Farm-level data were collected from FADN [12] for small- and medium-sized farms, as well as from statistical reports on production–financial indicators of agricultural companies and other agricultural enterprises [13] for large pig farms.

Table 4. Comparison of Lithuanian pig farms according to average farm size using physical and economic indicators in 2016–2021.

Farm Group	Price, EUR/t	Cost, EUR/t	Labor Productivity, EUR/AWU	Number of Piglets (per Sow)	Production, kg (per Pig)
Large farms	1113	1000	122,930	30	221
Medium farms	1586	1308	32,981	21	203
Small farms	1202	1049	43,599	20	200

presents the average values of the period from 2016 to 2021, but it is worth mentioning that similar trends are observed when analyzing the individual years of the period. With higher results of physical and economic indicators, large farms (two thousand sows) were also able to better adapt to changing animal welfare requirements. It was noticed by Wang et al. [46] that the size of the farm had a significant positive impact on the level of biosecurity implemented by farmers. The results of their study reveal that farmers with larger farms and a higher proportion of income from farming were more likely to take proactive measures to improve biosecurity when faced with the risk of diseases.

Large-scale industrial farms have been heavily criticized in Europe [42,66]. In contrast to the Europeans, Chinese urban citizens seem to prefer industrial farms. In most countries, pork consumers prefer large industrial pig farms due to the higher sanitary conditions and food safety standards of these types of farms [42,43,44].

As mentioned in the methodological section, the period of 2016–2021 was chosen for this research in order to eliminate the influence of the cyclicity of pigs on the results.

Table 5. Ranking results of the Lithuanian farms according to size using selected indicators.

Farm Group	2016		2021		2016–2021
	Criterion Estimate	Rank	Criterion Estimate	Rank	Criterion Estimate	Rank
Large farms	1.00	1	0.97	1	1.00	1
Medium farms	0.00	3	0.09	3	0.03	3
Small farms	0.28	2	0.37	2	0.26	2

presents the results of the multicriteria evaluation based on the data for 2016, 2021, and the average of 2016–2021.

Large pig farms (two thousand sows) currently appear to be the best prospect: they took first place in all the years examined. The cumulative estimate of their assessed indicators was much higher than the cumulative estimates of the medium (100 sows) and small (20 sows) farms analyzed. The main reasons are as follows: significantly higher work productivity, lower cost, lower price, and better structural indicators. These indicators also assume the advantage of large pig farms. They can produce pork more efficiently and at a lower cost per unit of production. They also have more resources to invest in research and development, and they are better able to implement new technologies. Some of the smaller farms, according to the authors, better adapt to the prevailing market conditions, supplying niche products in the market to consumers who want pork raised by a local farmer, thus creating short supply chains.

The results we obtained are consistent with the results obtained by Kuncová et al. [45]. They evaluated the effect of farm size on the economic performance of the pig sector in the Czech Republic and concluded that larger firms reached higher economic performance compared with smaller ones. The analysis of Agatha Popescu [67] carried out in Romania also confirmed that the largest pig farm showed the highest efficiency. Kovács et al. [47] examined and compared the efficiency of livestock sectors, including the pig sector in Croatia and Hungary, by comparing farms of different size classes based on their standard production value. Kovács et al. [47] could not compare large farms, as there were not any in Croatia, but they concluded that the technical efficiency of small pig farms was better than that of medium pig farms, both in Hungary and Croatia. The same tendency was found in Lithuania.

Ábel et al. [49] studied the pig farming sector in Hungary and revealed that it needs technology development. Huge differences were detected regarding pig farm size. According to Ábel et al. [49], large pig farms have an advantage in financing development, so it is assumed that the existing number of small farms that are already falling behind in technology will increase. It was concluded that to reach the same level of technological development, small farms need a significantly higher per-unit investment value.

In the literature, the results of studies that are different from those of our study were also found. The results of the study carried out in the Republic of Macedonia showed that all sizes of pig farms had similar efficiencies [41].

5. Conclusions

This research, using the multicriteria evaluation method TOPSIS, has revealed that in Lithuania, according to the main activity indicators, large farms developed the most successfully. The same dynamics were observed in the countries chosen for this research: Belgium, Denmark, Germany, Estonia, Spain, France, Latvia, The Netherlands, Austria, and Poland. Small farms faced difficulties and withdrew from the market due to existing economic conditions and stricter environmental requirements.

Lithuania’s self-sufficiency in pork production was one of the smallest: in 2022, the self-sufficiency of pork amounted to 50%, and it was 28 percentage points less than in 2004. In Latvia, Estonia, and Poland, self-sufficiency did not reach 100%, either. The leading countries concerning the self-sufficiency of this product are Denmark, Belgium, The Netherlands, and Spain.

This study contributes to research in the field of pig farming both theoretically and practically. The theoretical contribution consists of the systematization of scientific knowledge and the preparation of a system of indicators and a methodology. Practical empirical evidence provides knowledge about pig farming and helps to consider policy changes. This study also reveals that further research should cover environmental and food safety issues.

A limitation of the study is that the indicator system does not include environmental indicators. The absence of these indicators, due to the lack of available data, led to this limitation of the study. In the future, this limitation will no longer be relevant, because the Farm Accountancy Data Network has already included, and is starting to collect, data on environmental protection.

In Lithuania, there is a demand for long-term scientific research that would disclose challenges and problems and would suggest appropriate measures to support the sustainable development of the pig farming sector. So, further research should consider the European Green Deal and the Farm to Fork Strategy, which are of great importance to farms and policymakers.