Designing a Model of Startups Management Based on System Dynamics

Subject Areas : Technology and information management

Hamid Adldoost ¹ ( Ph.D. Candidate, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran )
Mahmood Alborzi ² ( Associate Prof, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran )
Seyed Abdollah Amin Mousavi ³ ( Assistant Prof, Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran )

Received: 2023-01-05 Accepted : 2023-04-04 Published : 2024-09-23

Keywords: Business Dynamics, Startup, Success and Failure Factors, System Dynamics,

Abstract :

The purpose of this research is to create a system dynamics model to manage the life cycle of start-up businesses based on the identified factors that are effective in the failure and success of these businesses and to examine the effects of these factors in different circles. The method of this research is grounded theory in the identification of factors and in the modeling part it is based on system dynamics. According to the studies, the success rate of startups around the world is very low, less than 10%. Therefore, identifying the factors affecting the success and failure of start-ups and designing a dynamic model based on these factors can lead to the management of start-ups and increase the probability of success. In order to extract failure and success factors in this research, 25 interviews were conducted with the activists of start-up businesses in Tehran, within the framework of the constructionist grounded theory method. The identified factors included 87 concepts, 32 categories and 7 general categories. To design the model, first, causal loops diagrams were drawn in different areas and then a model, based on system dynamics, was designed which included 13 stocks of effective factors. The resulting model was checked with numerous tests, the results of which revealed the possibility of predicting the growth or failure of startups through modeling and determining the relevant coefficients.

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