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 (Department of Management, Faculty of Social Sciences, Dayalbagh Educational Institute, Deemed University, Dayalbagh, Agra, India)
Copyright: © 2013 |Pages: 38
DOI: 10.4018/ijsda.2013010104
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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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1. Introduction

Innovation is an important topic of high intellectual and research visibility in the study of economics, business, entrepreneurship, design, technology and engineering. Colloquially, the word “innovation” is often referred synonymous with the output of the process. However, business practitioners and economists tend to focus on the process of innovation itself, from the origination of an idea to its transformation into something meaningful, to its implementation; and on the system within which the process of innovation unfolds.

Joseph Schumpeter defined economic innovation in “Theorie der Wirtschaftlichen Entwicklung”-The Theory of Economic Development (Schumpeter, 1934). Traditionally, innovation management deals with all stages of the innovation process (Schumpeter, 1961):

  • Invention, i.e., the phase where new products are developed;

  • Innovation, i.e., the phase of introducing new products in the market;

  • Imitation or diffusion, i.e., the spread of new products in the market.


2. System Perspective

System engineers define a system as a set of interrelated components working toward a common objective. Systems are made up of components, relationships, and attributes (Carlsson et al., 2002). Checkland defines a system as: a set of elements connected together which form a whole, thus showing properties which are properties of the whole, rather than properties of its component parts (Checkland, 1990). In recent years “systems thinking” has developed as an alternative to mechanistic thinking (Flood & Jackson, 1993).

In this light, Innovation can also be attributed as a systemic and interactive process which is developed in a specific social, economic and institutional context (Lundvall, 1992; Morgan, 1997). A distinction can be made between a narrow and a broad definition of an innovation process respectively: The narrow definition includes organisations and institutions involved in searching and exploring novelties, whereas, the broad definition includes all parts and aspects of the economic structure and the institutional set-up affecting innovation process—the production system, the marketing system and the system of diffusion itself present themselves as subsystems in which learning and diffusion takes place (Lundvall, 1992; Freeman, 1988; Nelson, 1993; Rosenberg, 1976).

This systemic view is in a striking contrast to the reductionist approach of analyzing innovation problems in a micro sense. The innovation systems perspective emphasizes the importance of the trinity of the “supply push”, the process itself and the “demand pull” of the users of new knowledge. At its simplest, the development of innovation studies as a field rests on a rejection of the linear model of innovation. It fundamentally highlights the context in which a number of variant actors of innovation system interact in order to innovate and subsequently adopt and are affected by social, economic, physical and technological environment. Such a system is complex and evolves through time (Arnold et al., 2001; Rosenberg, 1976).

From a practitioner’s perspective too, in a traditional business set up, innovation used to be a linear trajectory from new knowledge to new product and historically, the conventional approaches to innovation diffusion have tended to regard innovation as the product of research, and view its dissemination as a largely linear process confined to researchers, producers and target users. Contrary to this, systems approach places greater emphasis on the rapidly changing internal and external structural dynamics and on the importance of a diversity of key actors and the surrounding operating environment.

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