Dynamic Modeling of a New Product Supply Chain using System Dynamics Approach

Document Type : Original Article

Authors

1 Professor, University of Tehran.

2 Ph.D Student, University of Tehran.

Abstract

Supply chains are network of organizations and individuals involved in fulfilling customer needs. Increasing research and interests of researchers and industrial managers in the supply chain, make it necessary to investigate the behavior of the supply chain network. At this research, researchers tried to analyze the impact of variables of demand uncertainties, as well as uncertainties related to supply chain partners' performance on the supply chain performance in a two-echelon supply chain of medical equipments. Customer demand fill rate (CDFR), and the bullwhip effect (BE) were analyzed as two indicators of supply chain performance. In order to analysis of system behavior regarding uncertainties, system dynamics (SD) is employed, which is a powerful tool to analyze and understand the behavior of the supply chain operations. The results showed that increase in demand, the uncertainty of demand, uncertainty of production systems, and uncertainties related to the ability to supply, has a significant effect on intensifying the effect of BE, and reducing CDFR across the supply chain.

Keywords


1. Altiok, T., & Melamed, B. (2007). Simulation modeling and analysis with Arena. Academic Press.
2. Azar, A., Gholamrezayi, D., Danayifard, H., & Khodadad-Hosseini, H. (1392). Dynamic analysis of relationships between industry and university with considering higher education policies in fifth development plan by using system dynamics. Journal of Industrial Management Perspective3(9), 79–115.
3. Barlas, Y. (1996). Formal aspects of model validity and validation in system dynamics. System Dynamics Review12(3), 183–210.
4. Chan, S. L., & Ip, W. H. (2011). A dynamic decision support system to predict the value of customer for new product development. Decision Support Systems52(1), 178–188.
5. Chopra, S. & Meindl, P. (2013). Supply Chain Management: Strategy, Planning and Operation (5th Editio). Upper Saddle River, NJ: Prentice Hall.
6. CSCMP. (2010). Glosario de te´rminos del ‘Council of Supply Chain Management Professionals.
7. Faghih, N., Kordshooli, H. R., Mohammadi, A., Samadi, A. H., Musavi-Haghighi, M. H., & Ghafurnian, M. (1393). Mathematical modeling of service supply chain of Iran’s landline by using systems dynamics. Jouranl of Industrial Management Perspective4(13), 31–50.
8. Forrester, J. W. (1961). Industrial Dynamics. Waltham, MA: M.I.T. Press.
9. Jean, R., Kim, D., & Sinkovics, R. R. (2012). Drivers and Performance Outcomes of Supplier Innovation Generation in Customer–Supplier Relationships: The Role of Power‚ÄźDependence. Decision Sciences43(6), 1003–1038.
10. Johnsen, T. E. (2009). Supplier involvement in new product development and innovation: Taking stock and looking to the future. Journal of Purchasing and Supply Management15(3), 187–197.
11. Özbayrak, M., Papadopoulou, T. C., & Akgun, M. (2007). Systems dynamics modelling of a manufacturing supply chain system. Simulation Modelling Practice and Theory15(10), 1338–1355. http://doi.org/http://dx.doi.org/10.1016/j.simpat.2007.09.007
12. Piewthongngam, K., Vijitnopparat, P., Pathumnakul, S., Chumpatong, S., & Duangjinda, M. (2014). System dynamics modelling of an integrated pig production supply chain. Biosystems Engineering127, 24–40.
13. Schumpeter, J. A. (1934). The theory of economic development. Cambridge: MA: Harvard University Press.
14. Sterman, J. D. (2000). Business dynamics: systems thinking and modeling for a complex world (Vol. 19). Irwin/McGraw-Hill Boston.
15. Towill, D. R. (1996). Industrial dynamics modelling of supply chains. Logistics Information Management9, 43–56.