Abstract
We propose a generic theory of the diffusion of eco-technologies that integrates properties of the market, technology, policy change, and public policy interventions. Eco-technologies are technologies that lead to reduced environmental stress compared to an incumbent, mainstream technology. Because our theory is generic, it can be applied to a wide set of different technologies. Methodologically, we rely on System Dynamics modeling and simulation to arrive at a dynamic, causally explicit, and endogenous explanation of the key feedback loops driving (or inhibiting) such diffusion processes. In addition to a description of our theory, we provide an extensive discussion of how the System Dynamics methodology can be used to conduct research and support policymaking in the context of eco-technologies.
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Notes
- 1.
In this conceptualization it does not matter whether the eco-technology is a completely new technology or improvement of an existing technology. What is important is that there is a “better” configuration that has to overcome a “worse” configuration (also see “Model Sectors and General Setup”; in particular Table 1).
- 2.
In line with Knoepfel et al. (2007, p. 24), we define public policy as “a series of intentionally coherent decisions or activities taken or carried out by different public and sometimes private actors whose resources, institutional links and interest vary, with a view to resolving in a targeted manner a problem defined politically as collective in nature.” Relying on this abstract term allows us to ignore the question which specific institutions are involved.
- 3.
System Dynamics is an interdisciplinary, scientific methodology that is used to describe the structure of causality driving change processes and to elicit the resulting behavior produced by that structure. Specifically, change processes are represented mathematically by differential equations. In order to obtain behavior, these equations are solved, by way of computer simulation. Any kind of change process can be represented as a simulation model, regardless whether it stems from the physical, ecological, or social domain. The methodology was developed by Jay W. Forrester in the late 1950s and early 1960s by applying principles of control (from electric engineering) to the management of real-world problems (Lane and Oliva, 1998, p. 219; Sterman 2000).
- 4.
The concept of middle-range theory was introduced by Merton (1957). It refers to theories that are located between universal theories (“grand theories”) and micro theories. They integrate theoretical and empirical research. They consolidate different hypotheses or findings. Instead of all-inclusive efforts to develop a unified theory, they are limited to specific types of contexts, which allow for the formulation and testing of specific hypotheses. A middle-range theory is generic in that it holds for a whole class of systems. In contrast, a micro theory is less abstract, deals with relatively small slices of time, and covers small numbers of objects, e.g., individuals, interactions, or families.
- 5.
The model is electronically available in the Vensim model format from Matthias Müller.
- 6.
See Ventana Systems (2012) for a discussion of strengths and limitations of various formulations of allocation.
- 7.
This description of the advocacy coalition framework substantially draws on previously published work reported in Müller (2012, Chap. 5.4.4.1;2013).
- 8.
Also see Müller (2012, Sect. 2.2.3 and 9.5.1) for further reflections on designing System Dynamics research that includes variables that are hard to measure.
- 9.
A pertinent example for the case of municipal waste management is documented in Ulli-Beer (2006).
- 10.
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Acknowledgments
The authors thank Susanne Bruppacher, Franz Schultheis, Heidi Hoffmann, and Stephan Walther for contributing valuable discussions and comments toward improving this article. The research underlying this chapter was supported by the Swiss National Science Foundation within the context of the National Research Program 54 (Sustainable Development of the Built Environment), Novatlantis—Sustainability at the ETH Domain, the Swiss Federal Office of Energy, the City of Zürich, the Interdisciplinary Centre for General Ecology at the University of Bern, the University of St. Gallen, and Paul Scherer Institut.
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Müller, M., Kaufmann-Hayoz, R., Schwaninger, M., Ulli-Beer, S. (2013). The Diffusion of Eco-Technologies: A Model-Based Theory. In: Qudrat-Ullah, H. (eds) Energy Policy Modeling in the 21st Century. Understanding Complex Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8606-0_4
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