Design and Simulation of Beef Value Chain in Mashhad City Using: System Dynamic Approach

Document Type : Research Paper

Authors

1 Assistant Professor of Agricultural Economics at University of Kurdistan

2 Associate professor of Agricultural Economics at Ferdowsi University of Mashhad

3 Professor of Agricultural Economics at Ferdowsi Univrtsity of Mashhad

4 Professor of Agricultural Economics at University of Kentucky

10.22034/iaes.2024.2007173.2007

Abstract

Introduction
The price of red meat has grown significantly in recent years, which has reduced the welfare of the consumers of this product, and its consumption has decreased greatly in the low-income groups of the society. The presence of many challenges in the beef value chain and the presence of many activists with different goals in this chain have made it complicated and difficult to analyze this chain. One of the best methods for designing complex systems, determining policies and solving their problems is system dynamics modeling.
Material and Methods
In this study, after identifying the actors in the value chain, the relationships among the elements of this system were expressed in the form of causal loop diagram. Then, the types of the variables in the system were determined including stock, rate, auxiliary and parameters and the stock-flow diagram of this value chain was drawn and then was formulated. After validating the designed model using the behavior reproduction test, the current state of this value chain has been simulated.
Results and Discussion
In this basic model, by creating scenarios on key variables such as the exchange rate and the import tariff rate of inputs and red meat, it is possible to examine the impact of various government support policies on the price of beef and other important variables of this chain.
Suggestions
Therefore, such a model that shows the dynamics of the relationships between the factors involved in the red meat value chain can be used as an operational dashboard for decision making for policy makers and planners of the country's agricultural sector.

Keywords

Main Subjects


Abbasi, I. A., Ashari, H., Ariffin, A. S., & Yusuf, I. (2023). Farm to Fork: Indigenous Chicken Value Chain Modelling Using System Dynamics Approach. Sustainability, 15(2), 1402.
Abdulla, I., Arshad, F. M., Bala, B. K., Bach, N. L., and Mohammadi, S. (2016). Management of beef cattle production in Malaysia: a step forward to sustainability. American Journal of Applied Sciences, 13(9): 976-983.
Alizadeh, P. (2019). Dynamic modeling of the effects of supportive government policies on value chain of red meat in Mashhad. PhD Thesis, Ferdowsi University of Mashhad.
Alizadeh, P., Mohammadi, H., Shahnoushi, N., Saghaian, S., & Pooya, A. (2019a). Evaluating Cost Structure and Economies of Scale of Beef Cattle Fattening Farms in Mashhad City. Journal of Agricultural Science and Technology, 21(7), 1753-1766.
Alizadeh, P., Mohammadi, H., Shahnoushi, N., Saghaian, S., & Pooya, A. (2019b). Investigating factors affecting import demand of meat and livestock inputs in Iran. Iranian Journal of Agricultural Economics, 13 (3): 1-28.
Alizadeh, P., Mohammadi, H., Shahnoushi, N., Saghaian, S., & Pooya, A. (2020). Application of system thinking approach in identifying the challenges of beef value chain. AGRIS on-line Papers in Economics and Informatics, 12(665-2020-1230), 3-16.
Conrad, S. H.  (2004). The dynamics of agricultural commodities and their responses to disruptions of considerable magnitude. In Proceedings of the International Conference of the System Dynamics Society.
Cox, A. (1999). Power, value and supply chain management. Supply Chain Management: An International Journal, 4: 167-175.
Fartookzadeh, H. and Rajabi, M. (2011). “Dynamic modeling of traffic in cities in order to transport improvement policies”. Journal of transportation research, 30(1), pp. 82-63.
Forrester, J.W. (1961). Industrial Dynamics. Cambridge: MIT Press. Currently available from Pegasus Communications: Waltham, MA.
Forrester, J.W. (1997). System dynamics and K-12 teachers. Massachusetts Institute of Technology. Cambridge, MA, USA.
Hamza, K., Rich, K.M., Baker, D. and Hendrickx. (2014). Commercializing smallholder value chains for goats in Mozambique: a system dynamics approach. Proceedings in System Dynamics and Innovation in Food Networks.
Heydari, J., Zareayan, M.K., Heydari, E., Hezarkhani, B., and Karimi, R. (2019). Modeling the price fluctuations in the supply chain of poultry meat: a system dynamics approach. Journal of Agricultural Economics Research, 11 (42), 237- 262.
Iran Ministry of Agriculture Jihad. (2017). Available at: https://www.maj.ir/Dorsapax/userfiles/Sub65/sava-1395.pdf
Iran Ministry of Agriculture Jihad. (2022). Information and Communication Technology Center. Available online at: https://maj.ir/page-amar/FA/65/form/pId3353#
Iran Statistical Center. (2016). Summary of slaughtering statistics. Available online at: https://www.amar.org.ir/Portals/0/News/1396/chkdams-95.pdf
Jalali, H., Kamaei, ZH., and Azizi A. (2019). Investigation of changes in production, consumption and prices of red meat in the country. Statistical Research and Training Center
Jamshidifar, M., Salarpour, M., Sabouhi, M., Mehrabi, H., and Ahmadpour Borazjani, M. (2017).Simulation of chicken meat supply chain facing bird Flu crisis: case study: Khorasan Razavi province. Journal of Agricultural Economics and Development, 31 (4): 321-331.
Jie, F., Jenkins, R. J., and Parton, K. (2007). A systems dynamics approach to modelling in the Australian beef supply chain. In Australian and New Zealand Academy of Management Conference. ANZAM Operations Management Symposium.
Kleijnen, J. and Smits, M. (2003). Performance metrics in supp1y chain man Lie, H., and Rich, K. 2016. Improving value chains for dairy farmers in matiguás, Nicaragua: a System Dynamics Approach. Proceedings in Food System Dynamics, 229-244.agement. Journal of the Operational Research Society, 54(5): 507-514.
Laibuni, N., and Kirui, L. (2018). Transforming livestock production through systems thinking approach: the case of west Pokot and Narok counties. In 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia, No. 276020. International Association of Agricultural Economists.
Mahmoodi, E., Naim Sadeghi, A., Chaharsooghi, K., and Eskandari, H. (2010). Impact of information system flow on make-to-order manufacturer supply chain network: systems dynamics approach. Journal of Modeling in Engineering, 8 (22): 21-35.
Management and Planning Organization of Khorasn Razavi. (2016). Statistical yearbook of Khorasn Razavi province. Available online at: http://stat.roostanet.com/details.php?id=1182
Meadows, D. L. (1970). Dynamics of Commodity Production Cycles. The MIT Press.
Safaei, B., Mosleh Shirazi, A., Mohamadi, A., and Alimohammadlou, M. (2019). A Systematic model for the diffusion of commercial Soft  technology in Iran’s oil industry. Journal of Technology Development Management, 6 (3): 41-70.
Setianto, N. (2015). Systems thinking approach to develop smallholder beef farming in rural Java, Indonesia. PhD Thesis, University of Queensland.
Shank, J. K. (1989). Strategic cost management: new wine, or just new bottles. Journal of Management Accounting Research, 1: 47–65.
Shapiro, J. F. 2007. Modeling the Supply Chain. 2nd edition, Belmont.
Sterman, J. (2000). Business Dynamics: Systems Thinking and Modeling for a Complex World. McGraw-Hill, Boston.
Suryani, E., Hendrawan, R. A., Muhandhis, I., and Dewi, L. P. (2016). Dynamic simulation model of beef supply chain to fulfill national demand. Jrnal Teknologi, 78(9): 169-177.
Tedeschi, L. O., Nicholson, C. F., and Rich, E. (2011). Using system dynamics modelling approach to develop management tools for animal production with emphasis on small ruminants. Small Ruminant Research, 98(1-3): 102-110.
Towill, D. R. (1996). Industrial dynamics modeling of supply chains. International Journal of Physical distribution and logistics management, 26(2): 23-42.
Volker,G., and Steven, F. (2005). Individual-based Modeling and Ecology. Princeton University Press.
Wessely, P. (2010). Value Determination of Supply Chain Initiatives: A Quantification Approach Based on Fuzzy Logic and System Dynamics. Springer Science and Business Media.