Developing a decision-making support model to investigate the drivers affecting the optimization of agricultural crop production (The Case of South of Sistan and Baluchestan province)

Authors

• fahime Rigi ¹
• Ayatollah Karami ²

¹ PhD Graduate in Agricultural Development, Faculty of Agriculture, Yasouj University, Yasouj, Iran.

² Associate Prof., Faculty of Agriculture, Yasouj University, Yasouj, Iran.

10.30495/jzpm.2021.27854.3882

Abstract

Stakeholders in the agricultural sector (managers and farm operators) do not understand the products of these interactions due to the wide range of issues related to the "planning", "production" and even "consumer market". Lack of understanding the interactions between social, economic and environmental parameters leads to manifold challenges in the field of cropping production. Price fluctuation is a multifaceted problem attributed by various factors which, when combined, culminate in dangerous consequences for the most farmers .Challenges that have caused crop prices to fluctuate over a period of time, a sharp decline in area under crop, and a long-term decline in farmers' livelihoods. To obviate' this challenge, this study provided a dynamic model for assisting agricultural stakeholders' decisions in the agricultural planning process. The model mentioned in this study, referred to as the "decision-making model", seeks to understand the complexity of the agricultural planning space in the southern region of Sistan and Baluchestan. This model includes a set of dependent factors and drivers in the agricultural plan of the region that aims to understand the feedback of stakeholders' decisions in the agricultural sector and modeling and ultimately simulating their behavior. The DPSIR framework and then VENSIM software were used to evaluate the decision feedback in a decision model. So that first with the help of DPSIR framework the drives affecting on crop program planning of the region are classified and then with the help of VENSIM software modeling and various scenarios are simulated. The results of this study showed that policy makers can provide the conditions for creating good agriculture in the study area by focusing on the components of stress (derived from the DPSIR framework), which are mainly subsistence components. The results of this study in the study area show that many of the components used in crop planning will not lead to improvement or serious damage to the production stability of the study area (onions and tomatoes). In other words, it is possible to help improve and stabilize production in the region by controlling key factors such as reducing the vulnerability of farmers' livelihoods to price fluctuations.

Keywords

• برنامه‌ریزی زراعی
• پیشرانه‌های تصمیم‌گیری
• پویایی سیستم
• جنوب بلوچستان

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References

1. Aisyah, I., Hamdan, D., Tuty, A., Abdul, K., & Adzhar, K. (2021). Potential data collections methods for system dynamics modeling: A brief overview. International Journal of Advanced Computer Science and Applications (IJACSA). 12(3), 256-268.
2. Alizadeh M., & Keikha Z. (2010). The effect of land integration on the yield of agricultural products in Lootak rural district of Zabol. Journal of Zagros Geographical Vision, 2(3), 139 -152. (In Persian)
3. Azizalahi, M., Amiri, Z., Kakalvand, A., & Khalili Arjomandi, M. (2007). Increasing the productivity of production resources through land consolidation and using new irrigation methods (Case study of Selseleh County), 9th national seminar on irrigation and evaporation reduction, Kerman. (In Persian)
4. Barzel, B., Liu, Y., & Barabási, A. (2015). Constructing minimal models for complex system dynamics. National Communication, 6(1), 7186-801.
5. Dabirian, S., Abbaspour, S., Khanzadi, M., & Ahmadi, M. (2019). Dynamic modeling of human resource allocation in construction projects. International Journal of Construction Management, 35(2), 69-79. (In Persian).
6. Hoomani Farahani, M., Shahbazi, K., & Faalju, H. (2018). The effects of financial development on value added of agriculture in d8 countries. Journal of agricultural economics research, 10(2 (38), 135-154.
7. Kalantari, K., Hosseini, S. M., & Abdollahzadeh, G. H. (2005). Organizing and integrating agricultural lands using the experiences of Eastern European countries. Journal of Village and Development. 8 (3), 67-104. (In Persian)
8. Khatibi, A., Daneh Kar, A., & Poorabrahim, Sh., Vahid, M. (2017). Introduction of DPSIR model and its applicability in environmental decision making. Journal of Human and Environment Quarterly, 13(4), 65-79. (In Persian)
9. Liani, Q., Bakhshodeh, M., & Zibaii, M. (2019). Application of dynamic system method in evaluating the effects of water demand management policies in Khairabad river basin. Iranian Journal of Agricultural Economics and Development Research (Iranian Journal of Agricultural Sciences). 51(2), 216-195. (In Persian).
10. Mirkarimi, Sh., Joolaie, R., Eshraghi, F., & Shirani Bid Abad, F. (2016). Cropping pattern management of crops with emphasis on environmental, considerations (case study: Amol Township). Journal of Environmental Science and Technology. 18(3), 253-263. (In Persian).
11. Nathan, N. (2020). An assessment of stakeholders’ participation in land use planning process of Luapula Province Planning Authority. Journal of Land Use Policy, 97, 10-35.
12. Norozi , H., Hoseini, S., & Ansari, V. (2019). Investigating the effects of macroeconomic variables and support policy on the growth of the agricultural sector in Iran. Iranian Journal of Agricultural Economics and Development. 49(4), 587-60. (In Persian)
13. Pruyt, E. (2013). Small System Dynamics Models for Big Issues: Triple Jump towards Real-World Dynamic Complexity. TU Delft Library, Delft, the Netherlands Version 1.0.
14. Richardson, G.P. (2011). Reflections on the foundations of system dynamics. Journal of System Dynamic Reviw.27 (3), 219–243.
15. Rigi, F., & Ahmadvand, M. (2021). Analyzing the mental schemas of agricultural actors in choosing the types of crops: Applying grey relational approach. Journal of Agricultural Extension and Education Sciences. 16(1), 23-40. (In Persian).
16. Sassenrath, F., Hanson, J. D., Hendrickson, J. R., Archer, D. W., Halloran, J. M., & Steiner, J. J. (2009). Principles of dynamic integrated agricultural systems: lessons learned from an examination of southeast production systems. Taylor and Francis/CRC Press. Chapter: 15 (pp.259-269).
17. Sharifi, M., Sardar Shahraki, A., Dadashi, M., & Asgari, M. (2019). Review the integration process of agricultural lands and its economic impact, case study: rice farmers in Guilan province. Journal of agricultural economics research, 11(1 (41)), 217-236. (In Persian).
18. Shuhao, T., Nico H., & Futian, Q. (2006). Land fragmentation and its driving forces in China. Journal of Land Use Policy, 23 (3), 272-285.
19. Spicar, R. (2013). System Dynamics Archetypes in Capacity Planning. 24th DAAAM International Symposium on Intelligent Manufacturing and Automation, 2013.
20. Sterman, J. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill/Irwin.
21. Walters, J. P., & Javernick-Will, A. N. (2015). Long-term functionality of rural water services in developing countries: a system dynamics approach to understanding the dynamic interaction of factors. Journal of Environmental Science Technology, 49 (8), 5035–5043.
22. Zaheri, M., Karimzadeh, H., & Alipour, KH. (2019). Participatory planning of rural development with emphasis on border markets (Case study: Sardasht city). Journal of Quarterly Scientific, 9(35), 105-120. (In Persian).