Classification of determinant factors of irrigated vegetable problems using exploratory factor analysis in Swaida governorate, Syria



The objective of this research was to classify the determinant factors of irrigated vegetable problems and the amount of variance that is explained by each factor in Swaida Governorate/ Syria by using the Exploratory Factor Analysis. The research is based on the data which were collected through questionnaires that were obtained according to the opinions of farmers. It included questions about some of the social and economic characteristics of farmers, and the concerning problems related to irrigated agriculture by using multiple-choice questions (on a 3-point scale) during the 2019-2020 Based on a sample size of 92 farmers, representing 54.9 % of the studied statistical community, and distributed randomly within the areas of spread of irrigated vegetable cultivation.. The results showed the success of using the exploratory factor analysis technique, using the Principal components methodology and Varimax in classifying six factors with an initial eigenvalues greater than one for each, and these factors are: agricultural technological progress, agricultural employment, sale outlets, natural conditions, prices, production requirements. These factors explained (13.21 %, 12.65 %, 12.55 %, 11.12 %, 10.94 %, and 9.85 %) of the total variance respectively, and together explained 70.33 %.


exploratory factor analysis; principal component; factors; Varimax; irrigated vegetables

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Ahmadi, H., Rezaei, R., & Kheiri, S. (2013). Factor analysis of barriers and problems affecting the development of nanotechnol-ogy in agriculture. Annals of Biological Research, 4(1), 131-134.

Anderson, T. W. (2003). An Introduction to Multivariate Statistical Analysis. Third Edition. John Wiley & Suns, Inc. Huboken, New Jersey. p.747.

Cattell, R. B. (1966). The scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245-276.

Chandrashekar, S., Bahal, R., & V.P.H.D. (2012). Factors influencing the entrepreneurial behavior of agricultural graduates. SAARC Journal of Agriculture. 10(2), 31‐39.

Field, A. (2009). Discovering Statistics using Spss. 3th edition. London: SAGE publications Ltd. Singapore. p. 854.

Glenn, D. I. (1992). Determining Sample Size. Florida cooperative extension service. University of Florida. Fact sheet peod-6.

Harman, H. H. (1976). Modern Factor Analysis. Third edition. Revised. Chicago, University of Chicago Press. P. 508.

Hair, J. F. Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate Data Analysis. Seventh edition. Published by Pearson.

Mcdonald, R. P. (1985). Factor Analysis and Related Methods. Hillside, NJ: Lawrence Erlbaum associates, inc.

Ledesma, D. R., Mora, P. M. V., & Macbeth, G. (2015). The scree test and the number of factors: a dynamic graphics approach. Spanish Journal of Psychology, 18(11), 1–10.

Pavel, A. & Octavian, M. (2019). Determining local economic development in the rural areas of Romania. Exploring the role of exogenous factor. Sustainability, 11, 282;

Pituch, K. A. & Stevens, J. P. (2016). Applied Multivariate Statistics For The Social Sciences Analyses With SAS and SPSS. Sixth edition. Routledge (Taylor & Francis group). New York and London.

Rezai, G., Shamsudin, M. N., & Mohamed, Z. (2016). Urban agriculture: a way forward to food and nutrition security in Malay-sia, Procedia - Social and Behavioral Sciences, 216, 39 – 45.

Ministry of Agriculture and Agrarian Reform. Directorate of planning and international cooperation. Annual agricultural statisti-cal abstracts (2016-2018). Damascus, Syria.

Ministry of Agriculture and Agrarian Reform. Directorate of agricultural extension unpublished data 2020. Swaida, Syria.

Tabachnik, B. G. & Fidell, L. S. (2013). Using Multivariate Statistics. Sixth edition, Pearson education, Inc. New Jersey. USA. P.1018.

Tighza, M. B. (2012). Exploratory Factor Analysis and Confirmatory, Concepts and Methods Using Spss and LIREl. First edition. Dar Almasera. Aman, Jordan. P. 399.

Thompson, B. (2004). Exploratory and Confirmatory Factor Analysis Understanding Concepts and Applications. American Psycho-logical Association. P.185.

Yamane, T. (1967). An Introductory Analysis. Second edition. New York: Harper and Row.

Zeina, M. (2015). The important of exploratory factor analysis to achieve the factorial structure of psychological tests. Geel Journal of Social and Human Sciences, 14, 40-31.



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