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Capturing Structural Complexity of Innovation Diffusion through System Dynamics: A Discussion on Model Development, Calibration and Simulation Results

Capturing Structural Complexity of Innovation Diffusion through System Dynamics: A Discussion on Model Development, Calibration and Simulation Results

Sanjay Bhushan
Copyright: © 2013 |Volume: 2 |Issue: 1 |Pages: 38
ISSN: 2160-9772|EISSN: 2160-9799|EISBN13: 9781466631540|DOI: 10.4018/ijsda.2013010104
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MLA

Bhushan, Sanjay. "Capturing Structural Complexity of Innovation Diffusion through System Dynamics: A Discussion on Model Development, Calibration and Simulation Results." IJSDA vol.2, no.1 2013: pp.59-96. http://doi.org/10.4018/ijsda.2013010104

APA

Bhushan, S. (2013). Capturing Structural Complexity of Innovation Diffusion through System Dynamics: A Discussion on Model Development, Calibration and Simulation Results. International Journal of System Dynamics Applications (IJSDA), 2(1), 59-96. http://doi.org/10.4018/ijsda.2013010104

Chicago

Bhushan, Sanjay. "Capturing Structural Complexity of Innovation Diffusion through System Dynamics: A Discussion on Model Development, Calibration and Simulation Results," International Journal of System Dynamics Applications (IJSDA) 2, no.1: 59-96. http://doi.org/10.4018/ijsda.2013010104

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Abstract

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.

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