Socio-Economic Structure of Sheep Enterprises in Türkiye: A Micro-Level Analysis

Simple Summary

This study explores the structure of sheep farming enterprises in Türkiye. Surveys were conducted with 201 farmers during the 2023 production period to collect data on farm size, production goals, marketing methods, and economic performance. The results show that most sheep farmers are middle-aged or older and have low education levels. They usually use traditional (extensive) production systems and sell their products directly to consumers. To make sheep farming more sustainable, it is important to attract younger farmers, offer better training, and support the use of modern farming methods.

Abstract

This study aims to analyze the technical and economic infrastructure of sheep farming enterprises operating in Türkiye. It assesses the demographic characteristics of enterprise owners, enterprise scales, production objectives, marketing strategies, and economic performance. Primary data were collected through face-to-face surveys conducted with 201 sheep farming enterprises during the 2023 production period. The sample was selected based on information provided by the Provincial Directorates of Agriculture and Forestry and the Breeding Sheep and Goat Breeders’ Associations. Data analysis was performed using SPSS 27. Categorical data related to enterprise characteristics and the demographic profiles of enterprise owners were examined. The findings indicate that the majority of enterprise owners are middle-aged or older individuals, have a low level of education, and operate predominantly within an extensive production system. The producers’ marketing methods rely mainly on direct sales. In conclusion, ensuring the sustainability of the sheep farming sector requires encouraging young producers to enter the industry, expanding educational programs, and adopting modern production techniques.

1. Introduction

The sheep husbandry sector represents a significant sub-branch of the livestock industry in Türkiye. This economic activity enables the production of various products, including meat, milk, wool, and leather [1,2]. Owing to their high adaptability, sheep can be raised across a wide range of regions by adapting to diverse geographical conditions. The fact that sheep farming requires lower maintenance/feeding conditions and operating costs than cattle farming makes sheep farming an attractive economic activity, especially for small-scale enterprises [3]. In addition, sheep husbandry contributes to economic development by providing employment in rural areas [4]. In addition, the sheep husbandry sector is strategically important in meeting the demand for red meat because of the very limited production and consumption of pork in Türkiye. Sheep husbandry contributes to an increase in red meat consumption per capita [5,6].

Sheep husbandry is a prominent livestock activity in Türkiye, and is particularly prevalent in inland regions and areas with low precipitation. Despite its economic contributions, the sector’s development is constrained by the low yield capacity of domestic sheep breeds and suboptimal management practices [3]. Following the establishment of the Republic in 1923, scientific research and policy support emphasized the development of the sector, initially prioritizing wool and meat production. However, with the global proliferation of synthetic fibers—particularly from the mid-20th century onward—competition in wool production diminished. Consequently, efforts have increasingly focused on enhancing meat and milk productivity [5].

At present, the state of sheep and goat husbandry in Türkiye remains below targeted levels, as indicated by expert reports on animal husbandry [7]. As of 2024, per capita red meat consumption (including beef, sheep, and goat meat) in Türkiye is about 16.6 kg, whereas the average for the European Union (EU-28), including pork, is 54 kg—39 kg of which is accounted for by pork alone [8]. In this context, strengthening the ovine livestock sector is essential for raising red meat consumption levels. Furthermore, the continued reliance on red meat imports underscores the sector’s underutilized potential and its ongoing relevance to national food security and economic sustainability [5].

When the last 10-year period, independent of the past, is examined, a general increase in the number of sheep can be seen. The farming data for Ankara, Balıkesir, Erzurum, Eskişehir, and Konya Provinces, representing Türkiye and Türkiye in general for the years 2014–2023, are presented in

Table 1. Total sheep (2014–2023) in provinces and in Türkiye and changes within the scope of the study, x1000 (2014 = 100).

Years	Ankara	Index	Balıkesir	Index	Erzurum	Index	Eskişehir	Index	Konya	Index	Türkiye	Index
2014	817	100.00	816	100.00	633	100.00	602	100.00	1896	100.00	31,140	100.00
2015	879	107.59	793	97.18	698	110.27	693	115.12	1862	98.21	31,508	101.18
2016	984	120.44	797	97.67	617	97.47	651	108.14	1827	96.36	30,984	99.50
2017	1233	150.92	984	120.59	615	97.16	644	106.98	1895	99.95	33,678	108.15
2018	1319	161.44	1006	123.28	650	102.69	706	117.28	2001	105.54	35,195	113.02
2019	1455	178.09	1112	136.27	689	108.85	927	153.99	2191	115.56	37,276	119.70
2020	1718	210.28	1300	159.31	799	126.22	1071	177.91	2557	134.86	42,127	135.28
2021	1940	237.45	1495	183.21	810	127.96	1153	191.53	2769	146.04	45,178	145.08
2022	1680	205.63	1272	155.88	912	144.08	1154	191.69	2771	146.15	44,688	143.51
2023	1620	198.29	1183	144.98	800	126.38	995	165.28	2793	147.31	42,060	135.07

[9].

Table 1 reveals that there is a general upward trend in the number of sheep throughout Türkiye and in the provinces where the study was conducted between 2014 and 2023. The number of sheep in Türkiye has increased by about 35%, and differences in these rates are noteworthy on the basis of individual provinces. Konya stands out as the province with the highest number of sheep, while Ankara has recorded the largest increase in its sheep population. This growth is primarily attributed to imports rather than structural improvements or transformation, with most imports driven by investments from capitalists outside the sector [5]. Furthermore, there is evidence of a transition from extensive to intensive production methods in ovine farming, spurred by capital inflows [10]. In order to ensure the sustainability of this transformation, it is essential to conduct accurate and comprehensive analyses of sheep husbandry activities.

In recent years, various structural problems have been addressed [11,12,13,14,15], and socio-economic conditions have been examined [16,17,18,19] in studies on sheep husbandry in different districts and provinces of Türkiye. However, these studies are largely limited to the provincial or district level.

The main purpose of this study is to reveal the socio-economic, technical, and economic infrastructure of sheep husbandry enterprises operating in Ankara, Balıkesir, Erzurum, Eskişehir, and Konya Provinces in different geographical regions of Türkiye and the sectoral profile of the enterprises. The analysis is conducted at the micro level, based on enterprise-level characteristics such as demographics, production scale, and income structure.

2. Materials and Methods

The primary data of the study were obtained from field visits, and the survey method was applied to the enterprises carrying out sheep husbandry activities in Ankara, Balıkesir, Erzurum, Eskişehir, and Konya Provinces during the production cycle of 2023, which represented Türkiye. These provinces were selected because they are among the most active sheep production regions in the country, covering diverse geographical and climatic conditions and accounting for a significant share of the national sheep population. The questionnaire development process was based on the form designed by Gambelli et al. (2021) [20], with adaptations made to align with local conditions and the specific objectives of this study. In this context, the validity of the survey questions was first evaluated through a review of the relevant literature. Subsequently, the scope of the content was expanded based on feedback from industry experts and academics. In the final stage, a draft version of the survey was pilot-tested on a small sample group, and necessary revisions were made in light of the feedback received. The content of the questionnaires prepared for sheep husbandry enterprises included questions tailored to the statistical analysis methods employed. These questions aim to determine the current status and structural characteristics of sheep husbandry enterprises in the selected provinces. Face-to-face interviews were conducted with enterprise owners engaged in sheep husbandry using the questionnaires developed during the research process. Additionally, data were drawn from the five-year development plans of the Turkish Statistical Institute (TSI), the United Nations Food and Agriculture Organization (FAO), and the Ministry of Development, alongside secondary data compiled from relevant national and international literature.

In five provinces where the primary data of the study were obtained, a sample with high representation power was selected via a stratified random sampling method among the enterprises that are members of the Brood Sheep and Goat Breeders Association. The sample size was determined as a 95% confidence interval and 5% margin of error in line with the method reported by Güneş & Arıkan (1985) [21]. The calculation for this is presented below:

$${\mathrm{n}}_0={\displaystyle \frac{\mathrm{N}{\mathrm{t}}^2\mathrm{P}\mathrm{Q}}{{\mathrm{d}}^2\left(\mathrm{N}-1\right)+{\mathrm{t}}^2\mathrm{P}\mathrm{Q}}}={\displaystyle \frac{65265{\left(1.96\right)}^{2}0.9\times 0.1}{{\left(0.05\right)}^2\left(65265-1\right)+{\left(1.96\right)}^{2}0.9\times 0.1}}\cong 195$$

[Table value t corresponding to confidence level (95%) = 1.96; probability of selecting an enterprise: P = 0.9; Q = 0.1].

N: Number of units in the population

P: Frequency of occurrence of the event to be examined

Q: Frequency of non-occurrence of the event to be examined

t: Theoretical value found in the t-table

d: Frequency of occurrence of the event

$Strata weight={\displaystyle \frac{195}{65265}}=0.003 (whole sample$) [22,23].

It is important to clarify that the value “195/65,265 = 0.003” refers to the overall sampling fraction, which indicates the proportion of the selected sample to the total population. This value is distinct from the t-value used in the sample size determination formula. In this context, the t-value (1.96) represents the critical value from the t-distribution corresponding to a 95% confidence level, whereas the sampling fraction is used solely for proportional allocation in the stratified sampling design.

Table 2. The number of samples determined according to stratified provinces.

Provinces	Number of Enterprises	Wh *	nh **
Ankara	10,121	0.16	30
Balıkesir	20,821	0.32	62
Eskişehir	8670	0.13	26
Erzurum	7045	0.11	21
Konya	18,608	0.29	56
Total	65,265	1	195

* Wh: strata weight; ** nh: number of individuals per strata.

shows the distribution of enterprises by province and stratum.

In

Table 3. Distribution of enterprises by scale in selected provinces.

Provinces	Enterprises			Number of Enterprises								Example Total
	Small *	Medium *	Large *		Wh ** (Small)	Wh ** (Medium)	Wh ** (Large)		nh *** (Small)	nh *** (Medium)	nh *** (Large)
Ankara	2600	3703	3818	10,121	0.26	0.37	0.38	1	8	11	11	30
Balıkesir	10,121	9189	1511	20,821	0.49	0.44	0.07	1	30	27	5	62
Eskişehir	3257	3370	2043	8670	0.38	0.39	0.24	1	10	10	6	26
Erzurum	2722	2615	1708	7045	0.39	0.37	0.24	1	8	8	5	21
Konya	5238	7531	5839	18,608	0.28	40	0.31	1	16	23	17	56
Total	23,938	26,408	14,919	65,265					72	79	45	195

* Enterprises are classified based on flock size: Small (1–50 animals), Medium (51–200 animals), and Large (201 and more animals). ** Wh: strata weight; *** nh: number of individuals per strata.

, information on the number of enterprises determined according to the scale after each province is presented.

Of the 195 enterprises included in the study, 72 were categorized as small, 79 as medium, and 45 as large based on their flock size, as shown in Table 3.

Within the scope of the study, about 10% of the total sample size, that is, 20 enterprises, were determined as reserves. In this context, 215 enterprises were visited. After removing those enterprises that refused to participate in the questionnaires or whose data were not reliable, the number of valid enterprises surveyed was determined to be 201. This process was carried out carefully to ensure the accuracy of the data. Consequently, the actual number of enterprises visited in each province (as presented in Figure 1) may slightly differ from the planned sample sizes (‘n_h’) shown in Table 2.

Sheep husbandry enterprises were identified through consultations with the Brood Sheep and Goat Breeders’ Associations, as well as the District Directorates of Agriculture and Forestry in the relevant provinces and districts. Time and budget constraints were taken into consideration to ensure the collection of accurate and reliable data.

The survey data collected from sheep husbandry enterprises were entered into the computer using Microsoft Office 365 programs and subsequently processed using the Statistical Package for the Social Sciences (SPSS) version 27 (IBM Corp., Armonk, NY, USA), making them ready for analysis.

Within the scope of the study, enterprise characteristics such as enterprise type, enterprise scale, and questions such as the age, education level, and experience period of the enterprise owners were designed as categorical data. The number (n) and percentage (%) values were determined for the categorical data obtained through the questions. The arithmetic mean, standard deviation, median, minimum, and maximum values were used to evaluate the income of enterprise owners from activities such as milk sales, livestock sales, brood sales, and fleece sales. Findings on the market type of sheep husbandry enterprises were evaluated via “Multiple Response” analysis since enterprise owners can mark more than one option.

3. Results

The number (n) values of the provinces where sheep husbandry enterprise owners, who contributed to the survey questions in the study with their answers, carried out sheep husbandry activities are presented in Figure 1.

Figure 1 shows that the majority of the participants carried out sheep husbandry activities in Balıkesir and Konya Provinces, with rates of 30.8% and 28.4%, respectively.

In the present study, 200 (99.5%) of the 201 participants were men, and only 1 (0.5%) was a woman.

The number (n) and percentage (%) value findings regarding the age and educational status of sheep husbandry enterprise owners are given in

Table 4. Demographic characteristics of the study participants.

	Statistics
Characteristics	Number (n)	Percentage (%)
Breeder’s Age
18–25	2	1.0
26–40	37	18.4
41–50	57	28.4
51 and above	105	52.2
Total	201	100.0
Education level
Literate	7	3.5
Primary Education	123	61.2
High School	50	24.9
University	19	9.4
Postgraduate	2	1.0
Total	201	100.0
Course/training status on sheep husbandry
Those who have not taken a course/training on sheep husbandry	114	56.7
Those who took courses/trainings on sheep husbandry	87	43.3
Total	201	100.0

.

An examination of Table 4 reveals that the majority of sheep husbandry enterprise owners are aged 51 and above, accounting for 52.2% of the sample. In terms of educational attainment, primary school graduates constitute the largest group at 61.2%, followed by high school graduates at 24.9% and university graduates at 9.4%. The proportion of enterprise owners with postgraduate education is notably low, at just 1%. Additionally, 43.3% of the participants reported having received courses or training related to sheep husbandry, while 56.7% indicated that they had not received any such training.

The number (n) and percentage (%) values concerning the agricultural and livestock sector experience of sheep owners, as well as their specific experience in ovine livestock, are presented in

Table 5. Experience-related characteristics of the study participants.

	Statistics
	Number (n)	Percentage (%)
Years of experience in agriculture and livestock sector
1 to 5	6	3.0
6 to 10	15	7.5
11 to 20	46	22.9
21 and above	134	66.7
Total	201	100.0
Duration of experience in the ovine livestock sector (Years)
1 to 5	22	10.9
6 to 10	35	17.4
11 to 20	44	21.9
21 and above	100	49.8
Total	201	100.0

.

According to Table 5, when the duration of experience in the agriculture and livestock sector is examined, the majority of the participants (66.7%) have 21 years or more of experience. This rate is 49.8% in ovine livestock. Those with 11–20 years of experience are 22.9% and 21.9%, those with 6–10 years of experience are 7.5% and 17.4%, and those with 1–5 years of experience are 3.0% and 10.9%, respectively.

The number (n) and percentage (%) findings regarding the type of enterprise, scale of the enterprise, production purpose of the enterprise, and lambing per litter status of sheep husbandry enterprises, in which the characteristics of the enterprise are examined, are given in

Table 6. Enterprise characteristics of the study participants.

	Statistics
	Number (n)	Percentage (%)
Enterprise Scale
Small (1–50)	72	35.8
Medium (51–200)	79	39.3
Large (201 and above)	50	24.9
Total	201	100.0
Enterprise type
Extensive	125	62.2
Semi-intensive	70	34.8
Intensive	6	3.0
Total	201	100.0
Purpose of enterprise owners for raising animals
For fatlings	134	66.7
For both fatling and milk production (combined)	51	25.3
For breeding purposes	10	5.0
For milk production	6	3.0
Total	201	100.0
Lambing/litter status
Once a year	116	57.7
Three times in two years	65	32.3
Twice a year	20	10.0
Total	201	100.0

.

When the findings related to Table 6 are evaluated, the scale distributions of enterprises are 35.8%, 39.3%, and 24.9%, respectively, from small to large. When the type of enterprise is examined, the percentage of enterprises that produce extensively is 62.2%, and the percentage of semi-intensive enterprises is 34.8%. The rate of intensive enterprises is quite low, at only 3%. For the purpose of raising livestock, 66.7% of the enterprise owners prefer to breed fatlings, while the percentage of enterprises aiming at both fatling and milk production is 25.3%, and the percentage of enterprises operating for breeding purposes constitute 5% of the sample, while those focused on milk production account for just 3%. Regarding lambing frequency, 57.7% of enterprises reported lambing once per year. Additionally, 32.3% of enterprises lamb three times every two years, and 10% report lambing twice a year.

Findings related to the dairy and livestock marketing practices of sheep farm owners, as well as their marketing methods, are presented in

Table 7. Milk and livestock marketing status and marketing methods used in sheep husbandry enterprises *.

	Statistics
	Frequency (n)	Percentage (%)
Milk marketing status (processed or unprocessed)
Marketed	96	47.8
Not marketed	105	52.2
Total	201	100.0
Milk marketing methods * (processed or unprocessed)
Direct sale by hand	89	70.1
Small shops	27	21.2
Contract with a retail company	8	6.3
Online sales	3	2.4
Total	127	100.0
Live animal marketing status
Marketed	198	98.5
Not marketed	3	1.5
Total	201	100.0
Livestock marketing methods *
Direct sale by hand	188	70.7
Animal Market	57	21.4
Contract with a retail company	8	3.0
Online sales	13	4.9
Total	266	100.0

* Participants selected more than one option.

.

As shown in Table 7, various aspects of the technical infrastructure of sheep husbandry enterprises are presented. It is observed that the majority of enterprises (52.2%) do not engage in milk marketing, while a very high proportion (98.5%) are involved in the sale of live animals. In both product categories, direct hand-to-hand sales emerge as the most commonly used marketing method.

The findings regarding the arithmetic mean ($\overline{X}$), standard deviation (SD), median (M), minimum (min), and maximum (max) values of the enterprise owners to evaluate their income from activities such as annual milk sales, live animal sales (butchery/sacrifice), brood sales, and fleece sales are shown in

Table 8. Distribution of sales revenues of the participants (total Turkish Lira (TRY) per year).

		Statistics
Sales Income Elements	$\overline{X}$	SD	Median	Min–Max
Milk sales (TRY Thousand)	27.3	106.9	0	0–1000
Livestock sales—sacrifice (TRY Thousand)	155.8	241.3	75	0–2000
Livestock sales—butchery (TRY Thousand)	327.3	499.3	125	0–3000
Brood sales (TRY Thousand)	94.8	269.5	0	0–1700
Fleece sales (TRY Thousand)	0.4	1.5	0	0–10
Total sales (TRY Thousand)	605.6	700.8	362	30–4309

. In Figure 2, the average income levels of enterprise owners according to sales income elements are presented as percentages.

An examination of the data in Table 8 reveals that different sales income items in the livestock sector vary widely. Fleece sales are the lowest source of income, with an annual average of TRY 0.41 thousand (0.07%), whereas butchery animal sales have the highest average, with an annual average of TRY 327.32 thousand (54.05%). Sacrificial animal sales represent a significant income component, with an average annual revenue of TRY 155.77 thousand (25.77%), followed by brood animal sales at TRY 94.79 thousand (15.65%) (Figure 2). Total sales revenues exhibit considerable variation, with an annual average of TRY 605.61 thousand (100.00%) (SD: 700.81; Min–Max: 30–4309), indicating substantial income disparities among livestock enterprises.

4. Discussion

In this study, it was determined that the majority of the producers in the sheep husbandry sector were 41 years old or older (Table 4). Similarly, studies conducted in Konya, Siirt, and Çanakkale have shown that enterprise owners are generally concentrated in middle-aged and older groups [14,24,25]. Other studies across Türkiye have revealed similar results that are consistent with these findings. This shows that the sector is based on more traditional production methods and that the demand for ovine breeding by young populations is insufficient. In studies conducted in Greece, South Wales, and South Australia, the sheep breeding sector has been carried out mainly by middle-aged and older groups [26,27,28]. However, there are supportive policies in developed countries that encourage the participation of young people in the sector. The implementation of similar practices in Türkiye may be critical for the modernization and sustainability of the sector.

The study found that the majority of sheep husbandry enterprise owners (61.2%) were primary school graduates (Table 4). Similar findings have been reported in studies conducted in Konya, Selçuklu, and Aksaray [14,19,29]. In contrast, the majority of enterprise owners in countries such as Greece, Norway, and Chile possess at least a secondary level of education [26,30,31]. The relatively lower education levels observed among enterprise owners in Türkiye may pose limitations in areas such as financial planning, adoption of modern technologies, and effective enterprise management.

In this study, 43.3% of the enterprise owners received courses or training on sheep husbandry (Table 4). This rate is higher in Muş, Konya, and Ardahan Provinces than in previous studies [16,19,32,33]. This finding, which is higher than the rates reported in Greece (15.1%) and Brazil (30.6%), shows that participation in vocational training in Türkiye is similar to that reported in European countries in some regions [26,34]. However, considering the regional differences throughout the country, it is important to disseminate educational activities at the national level in the sheep husbandry sector.

The study determined that most sheep husbandry enterprise owners had 21 years or more of experience in the sector (Table 5). Similar findings have been reported in studies conducted in the provinces of Konya, Siirt, and Çanakkale [14,24,25]. In Greece and Chile, the average experience ranges around 24 years, while in Norway it falls between 21 and 25 years [25,30,31], aligning closely with the findings from Türkiye. These results highlight that sheep husbandry is a sector that is globally grounded in long-term knowledge and experience. However, a high level of experience does not always correspond with parallel development in modernization. In many countries, including Türkiye, it is observed that business owners who have been engaged in the profession for many years tend to adhere to traditional methods. This tendency may hinder the adoption of modern technologies and the integration of younger generations into the sector. Therefore, alongside experience, it is essential to provide continuous professional development opportunities and to expand training programs focused on digital technologies and innovative production methods. Such efforts would not only enhance the capacities of experienced producers but also support the overall modernization of the sector.

In this study, it was determined that enterprise owners conducted substantially extensive production (62.2%), followed by semi-intensive production (34.8%) (Table 6). In a study conducted in Aksaray, 94.2% of enterprises preferred semi-intensive production, and 96% preferred semi-intensive production in Mersin [29,35]. This difference may be due to differences in breeding habits, enterprise structure, pasture facilities, and regional conditions. In this study, which was conducted in five provinces, the wide range of pasture opportunities in some regions may have caused enterprises to turn to extensive production. It has been reported that 78% of enterprises in northeastern Brazil operate under semi-intensive systems, while 14% utilize extensive systems [34]. A study conducted in Europe found that 37.8% of enterprises employed extensive systems, and 34.4% adopted semi-intensive methods [36]. In Greece, the rate of semi-intensive production is 38.06% [26]. Findings from Türkiye indicate that production systems vary across regions due to differing local conditions; however, semi-intensive production appears to be a widely adopted approach on a global scale. Structural factors such as the regional distribution of agricultural support policies, the level of infrastructure investment, and the effectiveness of producer organizations play a decisive role in shaping producers’ preferences for production systems in Türkiye. In particular, the inadequacy of support mechanisms and the limited marketing channels in the Eastern and Southeastern Anatolia regions may lead to a preference for extensive production systems. Conversely, in more developed regions such as Central Anatolia and the Aegean, the tendency toward semi-intensive systems can provide producers with higher added value. This situation highlights the need for a comprehensive approach to address the structural and policy factors underlying regional differences in production systems.

This study found that the vast majority of sheep husbandry enterprises raise animals primarily for fatling purposes (Table 6). In a study conducted in Aksaray, 47.8% of enterprises engaged in the production of meat, milk, and wool, while in Mersin, 72% of enterprises preferred the combined production of meat and milk [29,35]. The dominance of fatling cultivation is thought to be due to factors such as regional differences, producer preferences, pasture use, and market conditions. In a study conducted in Muğla, 46% of the enterprises were engaged in meat production only, while 34% were involved in combined production of both meat and milk [37]. In Brazil, 49% of enterprises produce milk, 37% produce meat, and 14% have combined production; in Europe, 67.8% produce milk and 32.2% produce meat [34,36]. The observed variations in results may be attributed to factors such as climatic conditions, pasture facilities, consumer demands, support policies, and regional production traditions.

In this study, it was seen that lambing occurs once a year in 67.7% of the enterprises and twice in 10% (Table 6). In a study conducted in Konya, it was determined that 83.2% of the enterprises had a single lambing per year, while 8.4% had lambing twice a year, and in Bursa, these rates were 68.1% and 6.4%, respectively [14,38]. A single lambing per year is common throughout Türkiye, and farmers are hesitant due to maintenance and feeding difficulties associated with more than one lamb. In contrast, the frequency of lambing is higher in Spain and Egypt, with an average of 1.5 in Spain and 8–10 months in Egypt [39,40]. This shows that the range of lambing in Türkiye is longer than that in international samples.

In this study, 47.8% of the enterprises marketed milk and dairy products, and 70.1% made these sales directly to consumers (Table 7). In a similar study conducted in Aksaray, located in the Central Anatolia Region of Türkiye, the milk marketing rate was reported as 71.6% [29], while in Ardahan, from the Eastern Anatolia Region, it was 45.5% [33]. Direct sales are common throughout Türkiye, although regional and sectoral differences significantly influence marketing methods. To provide an international perspective and contextualize the findings, comparable trends can be observed in other countries as well. For example, in Greece, 33.1% of milk producers sell to local milk processing plants, and 24.8% to national milk companies [41]. Similarly, in Italy, 73.68% of traditional cheese producers prefer direct sales to companies [42]. In Sicily, 70% of dairy products are sold in wholesale and 30% are sold in retail [43]. These international examples help to highlight that while direct sales are prevalent across different contexts, the structure of marketing channels may vary depending on regional production dynamics, policy environments, and market organization—parallels that can also be observed in Türkiye.

It was observed that 98.5% of the enterprise owners marketed live animals, and 70.7% of them used the direct sale method (Table 7). Similarly, in studies conducted in Aksaray and Niğde, which are located in the Central Anatolia Region of Türkiye, direct sales were also commonly practiced. These provinces are frequently used for comparison in the literature due to their similar regional, structural, and socio-economic characteristics to the study area [13,29]. While marketing methods among enterprises in Türkiye exhibit similar trends, data from Brazil show that 74.4% of producers market their animals for economic purposes, with 38.5% selling directly by hand and 33.3% marketing through unions [44]. In Greece, 56.7% of enterprises sell directly to wholesalers, while 21.7% sell to retailers [41]. Although the prevalence of direct sales in Türkiye is comparable to that in Brazil and Greece, notable differences exist in the use of sales channels. This suggests that the livestock sector in Türkiye remains heavily reliant on traditional marketing practices and that modern cooperative structures have yet to be fully developed.

Most annual sales revenues in sheep husbandry enterprises in Türkiye are derived from the sale of butchery and sacrificial animals, while the share of revenue from brood animal and milk sales remains relatively low (Table 8). Studies based on provincial-level data from Konya Province (Selçuklu district) in Türkiye’s Central Anatolia Region and Muş Province (Korkut district) in the Eastern Anatolia Region reported that the share of lamb and red meat sales in total household income were 72.2% and 63.5%, respectively. These findings are consistent with the present study [16,19]. In contrast, the high productive asset increase (PDKA) rate of 56.4% observed in Yozgat indicates that enterprises there tend to adopt a herd growth strategy [17]. In general, butchery and sacrificial animal sales are the main sources of income in Türkiye. In studies conducted in other countries, milk sales in Spain constitute 78.6% of revenues, whereas the income distribution of sheep husbandry enterprises in France, Spain, and the United Kingdom varies according to the production system [45,46]. The dominance of meat sales in Türkiye can largely be attributed to the economic impact of Eid al-Adha, whereas the prominence of milk revenues in some other countries reflects variations in enterprise structures and consumer preferences. This indicates that sheep husbandry in Türkiye is predominantly shaped by periodic and traditional demand patterns. To ensure long-term sustainability, it is essential to develop a more balanced income model within the sector.

In addition to the academic and sectoral implications of the findings, it is crucial to consider how these results can be effectively communicated to the wider public. Given the growing prevalence of misinformation, particularly in animal science, social media platforms such as Twitter (X), Facebook, and Instagram offer valuable opportunities to share accurate, research-based knowledge with a broad audience. Transparent and accessible dissemination of information can enhance public understanding of the socio-economic dynamics of sheep husbandry and combat misconceptions. In a parallel vein, a study focused on utilizing Instagram illustrates how social media can serve as an effective tool for agricultural outreach [47]. This study underscores the power of digital platforms in conveying complex topics, such as the socio-economic structure of sheep enterprises, to a diverse audience. Promoting engagement through modern communication channels not only increases the visibility of research but also fosters trust and awareness among consumers, producers, and policymakers alike.

5. Conclusions

As a result, this research makes an important contribution to the literature by addressing the sheep husbandry sector in Türkiye not only with economic indicators but also with a multidimensional perspective in the context of producer profiles and structural practices. This study presents the structural profile of the sheep farming sector in Türkiye based on a sample drawn from five key provinces that are among the most active sheep production regions across different geographical areas of the country. These provinces not only represent diverse regional conditions but also account for a significant share of national sheep production, thereby enhancing the relevance of the findings for understanding sectoral dynamics at the national level. The selected regions provide a robust basis for gaining a broader perspective on the structural characteristics of sheep farming in Türkiye. In this respect, it not only captures the on-the-ground realities of the field but also reinforces the link between scientific knowledge and sectoral policymaking.

The dominance of traditional production and marketing methods in the sheep husbandry sector reveals that the development potential of the sector cannot be adequately evaluated. This clearly underscores the need for structural transformations aimed at enhancing efficiency, sustainability, and profitability in the sector. The inclusion of the young population in the sector, strengthening producers’ access to educational opportunities, and comprehensive policies that encourage the adoption of modern production techniques are expected to form the basis of this transformation.

Limitations and Future Research

This study focuses on five key provinces where sheep husbandry is prevalent in Turkey, which, while not entirely limiting, may somewhat constrain the generalizability of the findings to the national level. Moreover, due to time and budgetary constraints, the analysis primarily relied on descriptive statistics. Consequently, the study’s ability to uncover causal relationships and deeply explore socio-economic interactions remains limited. Another limitation is the lack of an integrated theoretical framework, which future studies should address to strengthen academic contributions.

Future research is recommended to expand the geographical scope to include additional regions and to employ more advanced quantitative methods, such as regression and econometric modeling, alongside qualitative approaches. Such comprehensive analyses would facilitate a more nuanced understanding of the interrelations between economic performance and social factors—such as gender roles and knowledge transfer—within the sector. This, in turn, would contribute to better-informed policy-making aimed at supporting the sustainable development of sheep husbandry.