Investigating and analyzing methods of selecting agricultural machines in East Azarbaijan province using SWOT matrix

Authors

1 Department of Biosystem Engineering, Faculty of Agriculture, University of Tabriz, Iran.

2 School of Biosystem Engineering, University of Tabriz, Tabriz, Iran

3 Department of Biosystem Engineering, Faculty of Agriculture, University of Tabriz, Tabriz, Iran

Abstract

SWOT matrix (SWOT) is a management method in better advancing strategies in all sciences and industries. Therefore, it can be very effective in the management of agricultural mechanization. The current research was conducted with the aim of investigating and analyzing the methods of selecting agricultural machines using the SWOT matrix. The basis of this matrix is to identify weaknesses, strengths, threats and opportunities. A questionnaire was used to collect the research data, and the statistical population related to the research questionnaires is all the experts of the agricultural department of East Azarbaijan province, 126 of whom were selected as a statistical sample using Morgan's table. The result of Cronbach's alpha test for strengths, weaknesses, threats and opportunities was 0.82, 0.86, 0.83 and 0.71 respectively. Based on the results, the quality of the farmer's knowledge and skill in using agricultural machines as the best point, the lack of ability to know the type of soil by farmers as the most significant weakness, changes in weather conditions are the worst threat and determining the definitive price for the machine. agriculture and announcing it as the best opportunity. The findings of the research showed that the method based on quality and technology factors is preferred over the other two methods, economic and environmental, for selecting agricultural machines, and the method based on economic factors is in the second place and the method based on environmental factors is in the first place. The third priority was placed.

Keywords

Main Subjects

Agricultural Mechanization
Volume 8, Issue 3
September 2023

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History

  • Receive Date: 26 March 2023
  • Revise Date: 13 November 2023
  • Accept Date: 13 January 2024

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