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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Tarbiat Modares University</PublisherName>
				<JournalTitle>Journal of Agricultural Science and Technology</JournalTitle>
				<Issn>1680-7073</Issn>
				<Volume>28</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2026</Year>
					<Month>07</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Sheep Farmers’ Types and Efficiency in Konya</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>843</FirstPage>
			<LastPage>856</LastPage>
			<ELocationID EIdType="pii">24096</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Cennet</FirstName>
					<LastName>Oguz</LastName>
<Affiliation>Department of Agricultural Economics, Faculty of Agriculture, University of Selcuk, Türkiye.</Affiliation>

</Author>
<Author>
					<FirstName>Aysun</FirstName>
					<LastName>Yener Ögur</LastName>
<Affiliation>Department of Agricultural Economics, Faculty of Agriculture, University of Selcuk, Türkiye.</Affiliation>

</Author>
<Author>
					<FirstName>Aykut</FirstName>
					<LastName>ORS</LastName>
<Affiliation>Agriculture and Rural Development Support Institution, Konya Provincial Coordination Unit, Türkiye.</Affiliation>

</Author>
<Author>
					<FirstName>Yusuf</FirstName>
					<LastName>Celik</LastName>
<Affiliation>Department of Agricultural Economics, Faculty of Agriculture, University of Selcuk, Türkiye.</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2025</Year>
					<Month>09</Month>
					<Day>16</Day>
				</PubDate>
			</History>
		<Abstract>This study aimed to identify farm typologies and evaluate resource use efficiency based on sheep farmers&#039; perceptions of and adaptations to climate change in Konya Province, Türkiye. The sample size was determined as 151 using Neyman’s stratified random sampling method. Data were collected through face-to-face surveys with sheep rising enterprises. Farmers’ perceptions and adaptive behaviors related to climate change were analyzed using SPSS. The Principal Component Analysis (PCA) and cluster analysis were applied to classify farmer typologies, which were categorized as “climate-friendly smart innovators&lt;em&gt;, &lt;/em&gt;disengaged&lt;em&gt;, &lt;/em&gt;concerned&lt;em&gt;, &lt;/em&gt;and&lt;em&gt; &lt;/em&gt;unconcerned”. The farms’ resource use efficiency, economic efficiency, and pure technical efficiency were determined using Data Envelopment Analysis (DEA). The average Technical Efficiency (TE) of the farms was found to be 39.80%, indicating that farms could reduce input usage by 60.20% without compromising agricultural output. Resource use efficiency differed significantly across farm typologies. Specifically, allocative efficiency—closely linked to the identified farmer types—was found to be only 16.20%, indicating widespread inefficiencies in resource allocation and poor farm management. The findings also revealed that the majority of farmers demonstrated limited awareness and adaptation capacity concerning climate change.&lt;br&gt;&lt;br&gt;&lt;br&gt;</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Data Envelopment Analysis (DEA), Farmer typology, Konya, Sheep farming, T&amp;uuml</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">rkiye</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jast.modares.ac.ir/article_24096_aadeccf20333fe8cb7946318389d4555.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
