System Dynamics Integrative Modeling and Simulation for Mobile Telephony Innovation Diffusion

2012 ◽  
Vol 1 (3) ◽  
pp. 84-121 ◽  
Author(s):  
Sanjay Bhushan
Keyword(s):  
System Dynamics ◽  
Modeling And Simulation ◽  
Innovation Diffusion ◽  
Technology Development ◽  
Effective Diffusion ◽  
Mobile Telephony ◽  
Adoption Process ◽  
Dynamics Modeling ◽  
Telecommunication Sector ◽  
Holistic Understanding

In the recent times, India has emerged as one of the fastest growing telecom markets in the world and witnessed a telecommunication revolution brought about by a collaboration of government, industry, and the scientific community. It has truly been a success story of indigenous technology development and effective diffusion management of mobile telephony services. In the present paper, a system dynamics integrated model of Indian telecommunication sector (Mobile Telephony) has been calibrated to demonstrate the nature of interactions among system variables and the resultant outcome which assume degrees of importance at different stages of the diffusion/adoption process in the Indian telecom sector. The work done here proves how the application of system dynamics modeling and simulation coupled with soft computational neural networking can improve the holistic understanding of the dynamic structural complexities and forces of telecom diffusion. Simulation results show the potential of system dynamics as a promising tool to capture and predict the structural behavior of innovation diffusion process.

Capturing Structural Complexity of Innovation Diffusion through System Dynamics

2013 ◽  
Vol 2 (1) ◽  
pp. 59-96 ◽  
Author(s):  
Sanjay Bhushan
Keyword(s):  
System Dynamics ◽  
Diffusion Process ◽  
Innovation Diffusion ◽  
Systems Approach ◽  
General Rule ◽  
Dynamics Modeling ◽  
Holistic Understanding ◽  
Structural Variables ◽  
Innovation And Diffusion ◽  
Innovation Diffusion Process

This paper shows the utility of systems approach by extending the traditional innovation models and incorporating and integrating into them selective critical structural variables to map their interaction and explain the inherent dynamism. Conventionally, the approaches in explaining the innovation diffusion process assume that the process takes place in a stable and homogeneous system in which the innovation diffuses or spreads without being affected by the system’s structural variables even under external influences. However, many studies have established that the presence of symmetry is not the general rule in innovation diffusion process. This work examines these models and recognizes that they need further modification to improve the holistic understanding of the dynamic structural complexities and forces driving the processes of innovation and diffusion. This paper shows the general but extended frameworks of innovation diffusion mainly propounded by Frank M. Bass, E. M. Roger, E. Muller, P. Milling, and Frank H. Maier and proves how the application of system dynamics modeling can contribute in a meaningful way to the area of innovation diffusion research. A proof-of-the-concept analysis has been done by calibrating a diffusion model of Indian foundry sector followed by discussion on simulation results and future direction.

System dynamics modeling and simulation with Kotlin

2021 ◽  
Author(s):  
Siniša Sovilj ◽  
Darko Etinger ◽  
Zlatko Sirotić ◽  
Krešimir Pripužić
Keyword(s):  
System Dynamics ◽  
Modeling And Simulation ◽  
System Dynamics Modeling ◽  
Dynamics Modeling
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