A Comparative Study of System Dynamics and Intuitive Scenario forecasting about Military Conflict Scenarios between I.R.Iran and K.Saudi Arabia

Document Type : Original Article

Authors

1 Ms.c Student in Management, Faculty of Economic, Management and Political Sciences, Semnan University

2 Associate Prof., Faculty of Economic, Management and Political Sciences, Semnan University

3 Professor, Faculty of Economic, Management and Political Sciences, Semnan University

Abstract

Recent developments in decades of defensive technologies, as well as defensive thinking, such as the spread of a quick war on the planet, the network of warfare, and the emergence of free and open access to the virtual media have transformed the face of the wars. This transformation has led to new features for wars. War is one of the most challenging arenas of decision making for mankind. The advancement of technology and the evolution of war have forced commanders to make important decisions in short periods. Due to the complex nature of war and difficaulty of the fast analysis of its environment for human mind, its nessecary for commanders to use computer modeling methods to making better decisions. One of these methods is System Dynamics. Its important ability is calculating simultaneous effect of many variables on each other. In this Research the researcher tried to use system dynamics for executing the causal models of experts on the I.R.I and K.S.A Military conflict issue. Along with that, with a qualitative approach, the researcher reports the difficaulties of applying SD for strategic security and defensive issues and at the end, makes some suggestions for better modeling of these issues.

Keywords


  • Bafandeh Zendeh, A., & Sababi Pour Asl, G. (2014). Strategic plan compilation using system dynamics modelling: case study of a university. Education, Business and Society: Contemporary Middle Eastern Issues, 7 (4): 257-276.
  • Bonabeau, E. (2002) Agent-based modeling: Methods and techniques for simulating human systems, PNAS, 99: 7280–7287.
  •  Ceric, A. (2016). Analysis of interactions between IT and organizational resources in a manufacturing organization using cross-impact analysis. Journal of Enterprise Information Management, 29 (4): 589-611
  • Cooper, D. F., & Klein, J. (1980). Board wargames for decision making research: European. Journal of Operational Research, 5: 36-41.
  • Elsawah, S., Pierce, S. A., Hamilton, S. H., van Delden, H., & et al. (2017). An overview of the system dynamics process for integrated modelling of socio-ecological systems: Lessons on good modelling practice from five case studies. Environmental Modelling & Software, 93: 127-145.
  • Forrester, J. W. (1997). Industrial dynamics. Journal of the Operational Research Society, 48 (10): 1037-1041.
  • Harris, G. (2014). Four blind alleys of scenario analysis. Strategy & Leadership, 42 (6): 37-41
  • Jawan, Q. (2016). Causes of Inflation across Main Oil Exporting Countries, Kuwait Program at Science Po.
  • Kennedy, P. J., & Avila, R. J. (2013). Decision making under extreme uncertainty: blending quantitative modeling and scenario planning. Strategy & Leadership, 41(4): 30-36.‏
  • Kurtz, J. (2003). Business wargaming: simulations guide crucial strategy decisions. Strategy & Leadership, 31 (6): 12-21
  • Levite, A. E., & Tertrais, B. (2008). What Might the Middle East Look by2025? Sciences Po.
  • Moffat, J. (1995). The system dynamics of future warfare. European journal of Operational Research, 90: 609-618
  • Ojha, R., & Vart, P. (2017). Integrated impact of highway infrastructure, labour productivity and circular material consumption on Indian manufacturing growth: A system dynamics perspective. Journal of Advances in Management Research, 14 (4): 527-542
  • Oliver Schwarz, J. (2013). Business wargaming for teaching strategy making. Futures, 51: 59-66
  • Schwartz, S. (2013). Value priorities and behavior: Applying. In The psychology of values: The Ontario symposium, 8: 12-19.‏

Von Bertalanffy, L (1968). General system theory. New York.