with the collaboration of Iranian Society of Mechanical Engineers (ISME)

Strategic Assessment and Prioritisation of Agricultural Mechanisation Development in East Azerbaijan Province, Iran Using an Integrated SWOT–TOPSIS Approach

Document Type : Research Article- En

Authors

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

10.22067/jam.2026.99379.1498
Abstract
Sustainable agricultural development in Iran increasingly depends on context-specific mechanisation strategies that account for regional capacities and constraints. This study aims to identify and prioritise strategic pathways for agricultural mechanisation development in East Azerbaijan Province, Iran using an integrated SWOT–TOPSIS framework. The study adopted a descriptive-analytical, mixed-method design in which internal and external factors affecting mechanisation were first identified and structured through SWOT analysis based on expert knowledge. The statistical population consisted of experts and specialists, mechanisation companies and cooperatives, and experts affiliated with the Agricultural Jihad Organization of East Azerbaijan Province, Iran. Because the study required specialised judgments, a purposive, judgmental, non-probability sampling method was used, and the participants were selected based on their relevant expertise, practical experience, and familiarity with mechanisation issues in the province. Data were collected from 102 agricultural mechanisation experts using a structured questionnaire. Subsequently, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was applied to prioritise the identified factors. The results indicate that internal strengths currently provide a relatively favourable basis for mechanisation development (weighted internal factor score = 2.53), mainly due to the presence of agricultural machinery industries and access to spare parts. However, external threats outweigh existing opportunities (weighted external factor score = 2.37), with the Urmia Lake environmental crisis and rising machinery prices identified as the most critical constraints. Among the internal factors, based on their derived weights, local manufacturing capacity and spare part availability ranked as the most influential strengths, while outdated machinery and fragmented farm structures represented the most significant weaknesses. Based on the SWOT strategic position, the agricultural mechanisation sector in East Azerbaijan Province is placed in the Strength–Threats (ST) quadrant; therefore, the most appropriate strategies are those that use internal strengths to reduce or offset external threats. Accordingly, strategies that leverage internal strengths to mitigate external threats should be prioritised, particularly those aimed at strengthening domestic manufacturing capacity, improving repair and maintenance services, and enhancing resilience to environmental and market-related pressures. The proposed analytical framework offers evidence-based insights crucial for policymakers and agricultural planners. It supports the design of more effective, region-specific mechanisation policies to foster sustainable agricultural development in East Azerbaijan Province.

Keywords

Subjects

Authors retain the copyright. This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)

1.      Abbasi, K. (2018). Mechanization and the use of machinery in the production process to reduce production costs of agricultural products. (In Persian).
2.      Almasi, M., Kiani, S., & Loveimi, N. (2008). Principles of agricultural mechanization. Jungle Publication, Tehran. (In Persian).
3.      Amjadi, A., & Chizari, A. (2006). Agricultural mechanization in Iran. Agricultural Economics and Development. (In Persian).
4.      Asakereh, A. (2021). A study of the challenges and opportunities of Ahvaz County in the development of agricultural mechanization using the SWOT matrix. Journal of Geography and Environmental Planning, Ferdowsi University of Mashhad. (In Persian).
5.      Asghari, M., Taheri Hajivand, A., & Gholipour Ganjgah, M. (2022). Evaluation and analysis of the development of peach cultivation in Shabestar County, East Azerbaijan Province. Proceedings of the 14th National Congress of Mechanical Engineering of Biosystems and Mechanization of Iran (ISC), Shabestar, Iran. (In Persian).
6.      Ataei, P., Sadighi, H., Aenis, T., Chizari, M., & Abbasi, E. (2021). Challenges of applying conservation agriculture in Iran: An overview of experts’ and farmers’ perspectives. Air, Soil and Water Research, 14, 1–11. https://doi.org/10.1177/11786221211043356
7.      Banaeian, N., & Zangeneh, M. (2011). Mechanization and economic analysis of wheat production in Iran. AMA, Agricultural Mechanization in Asia, Africa and Latin America, 42(4), 15–27.
8.      Davarpanah, S., & Hashemi, S. (2017). Evaluation of agricultural sustainability in Ardabil Province using a hybrid approach of analytic hierarchy process and TOPSIS. Urmia University. (In Persian).
9.      FAO. (2021). The State of Food and Agriculture 2021: Making agrifood systems more resilient to shocks and stresses. Food and Agriculture Organization of the United Nations, Rome.
10.  Farhadi, H. (2001). Evaluation of the status of agricultural mechanization and suitable strategies in Marvdasht region (MSc Thesis). Science and Research Branch, Islamic Azad University, Tehran. (In Persian).
11.  Habibzadeh, H., Taheri Hajivand, A., & Irankhah, H. (2022). Evaluation and analysis of the development of apple cultivation in Bostanabad County using the SWOT method. Proceedings of the 7th National Congress of New Findings in Agricultural and Natural Resources, Environment and Tourism (ISC), Tabriz, Iran. (In Persian).
12.  Jellali, A., Hachicha, W., & Aljuaid, A. M. (2021). Sustainable configuration of the Tunisian olive oil supply chain using a fuzzy TOPSIS-based approach. Sustainability, 13(5), 2700. https://doi.org/10.3390/su13052700
13.  Mikaeili, M., Taheri Hajivand, A., & Salehi, M. (2023). Evaluation and analysis of apple cultivation development in Ahar County, East Azerbaijan Province. Proceedings of the 5th National Conference on Sustainable Development in Agricultural Natural Resources and Environment of Iran. (In Persian).
14.  Rahimi, M., & Hajivand, A. T. (2023). Analysis of machinery selection methods in East Azerbaijan using SWOT. Agricultural Mechanization Journal, 8(3), 57–68. (In Persian).
15.  Ramazani, M., Sadeghian, S., & Sadeghi, H. (2015). Strategic planning for rural development using SWOT. (In Persian).
16.  Salehi, M., Taheri Hajivand, A., & Mikaeili, M. (2022). Evaluation and analysis of the development of walnut cultivation in Osku County. Proceedings of the 12th National Conference on Sustainable Agriculture and Natural Resources. (In Persian).
17.  Sarbazi, H., Sheikholeslami, M., & Omid, M. (2015). Evaluation of the status of agricultural mechanization in Kaleybar County. (In Persian).
18.  Sheikholeslami Borghani, M., Rezvani, M., & Shabiri, S. M. (2016). Application of SWOT in analyzing agricultural water promotion programs (case study: Markazi Province). Proceedings of the 6th National Conference on Optimal Water Use, Arak, Iran. (In Persian).
19.  Statistical Yearbook of East Azerbaijan. (2019). East Azerbaijan Agricultural Organization. (In Persian).
20.  Zangeneh, M., & Banaeian, N. (2014). Investigation of agricultural mechanization status in corn production of Iran. Agricultural Engineering International: CIGR Journal, 16(1), 191–197.
21.  Zangeneh, M., & Hassanpour, K. (2023). Evaluation of the developmental status of Iran’s hatchery industries using the TOPSIS method. Strategic Research Journal of Agricultural Sciences and Natural Resources, 8(2), 141–156. https://doi.org/10.22047/srjasnr.2023.181000
22.  Zangeneh, M., Omid, M., & Akram, A. (2010). Assessment of agricultural mechanization status of potato production by means of Artificial Neural Network model. Australian Journal of Crop Sciences, 8(5), 372–377.
23.  Zangeneh, M., Omid, M., & Akram, A. (2015). Integrated assessment and modeling of agricultural mechanization in potato production of Iran by Artificial Neural Networks. Agricultural Research, 4(3), 283–302. https://doi.org/10.1007/s40003-015-0160-z
24.  Zangeneh, M., Akram, A., Nielsen, P., Keyhani, A., & Banaeian, N. (2015). A solution approach for agricultural service center location problem using TOPSIS, DEA and SAW techniques. In P. Golińska & A. Kawa (Eds.), Technology management for sustainable production and logistics (pp. 21–42). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33935-6_2
25.  Zarifneshat, S., Mozaffari, M., & Saeedirad, M. (2015). Improvement strategies for agricultural mechanization in saffron farms using SWOT. National Conference on Agricultural Engineering and Mechanization of Iran, Mashhad, Iran. (In Persian).
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Articles in Press, Accepted Manuscript
Available Online from 07 November 2026

  • Receive Date 16 June 2026
  • Revise Date 31 August 2026
  • Accept Date 09 September 2026
  • First Publish Date 07 November 2026