International Journal of Advance Agricultural Research
ISSN: 2053-1265
Vol. 9(2), pp. 22-34, April 2021

Viability and competitiveness of goat farms under the influence of socio-economic environment

Maria Tsiouni1*, Alexandra Pavloudi1, Stamatis Aggelopoulos1 and Christos Konstantinidis2

1Department of Agriculture, International Hellenic University, Thessaloniki, Greece.
2School of Business Administration, International Hellenic University, Serres, Greece.

*To whom correspondence should be addressed. E-mail:,

Received 19 March, 2021; Received in revised form 14 April, 2021; Accepted 16 April, 2021.


Goat farming, Principal component analysis, Economic indicators, Social indicators.

Goat farming in Greece is an important sector, since Greece is one of the largest European producer of goat milk among European Union countries and the first country in goat head. Greece is among the leading European Union countries in milk market, because of the high demand for feta cheese, but also because of a large variety of other cheeses made from goat milk. The goat sector in Greece is not so competitive compared to other countries, due to the high operational costs and that makes the sector unprofitable with a high risk for further marginalization. The objective of the current study was to identify the socio-economic structures of the farms in order to identify some improvement strategies and policies. Another objective of the study was to provide target information to the farmers in order to improve goat farm management. For this purpose, in the paper it was analyzed the technical, economic and social aspects of goat farms with the use of multivariate statistical techniques. The variables responsible for the difference were identified using principal component analysis (PCA). The application of PCA highlighted two components that explain 79.87% of the total variance. The first component, explaining 63.26%, is associated with all parameters related to the cost and can be described as component of the general cost. The amount of loans and labour cost had the greatest influence in determining this general cost. The second component, explaining 16.61% of the total variance, can be described as a component of social characteristics of the farmers that contribute to the production cost (PC). In the second PC, the highest contribution is attributed to the farmers’ age and their education level.

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