Achieving sustainability requires major changes in several areas in which society makes use of technology to meet human needs and while doing so influences the environment, such as agriculture, mobility, power production and water management. The awareness of a need for radical changes is accompanied by an increasing recognition of the interconnectedness of technological, socio-cultural and environmental elements and
processes. This has led to an increasing amount of research on system innovations.
System innovations refer to changes to a "structurally different" system involving radical changes in the technological and socio-cultural domains and are often contrasted to incremental (technological) change. System innovations involve many actors and many factors, and developments at multiple levels interact. Control over such processes is distributed, they are laden with uncertainty and they exhibit sometimes surprising and unexpected behaviour due to non-linear dynamics and emergent properties involved.
Our current understanding of system innovations is limited and the need for an enhanced understanding has clearly been recognized. Computer simulation models seem a
promising tool to that end as they already proved to be useful to enhance the
understanding of complex systems in many fields like complex chemistry, ecosystems
and physics. However, system innovations are mostly processes in social systems. In the
social sciences, the application of formal simulation models has a far shorter history and the availability of formalized (and widely accepted) theories and generalizations is low compared to the natural sciences. It is thus not clear-cut which role computer simulation models can play with respect to system innovations. This thesis fathoms the potential of
computer simulation models for enhancing our understanding of system innovations and
takes some first steps towards fruitful application of models.
A theoretical and methodological discussion outlines how models can in principle
contribute to an understanding of social macro-processes through facilitating a causal
reconstruction of processes that account for the respective observed phenomenon. The
view adopted regarding the representation of the social world thereby is that of reciprocity of agency and structure. Compared to the sociological literature the perspective is extended beyond comprising actors and institutions but encompasses also other entities, especially technological artefacts.
The thesis then relates the current state of empirical and conceptual work in the field of
transition research (the terms "transition" and "system innovation" are used interchangeably) to insights from modelling of complex systems. The intrinsic
characteristics of system innovations and the knowledge base available to study them are explicated and implicated challenges and opportunities for model application are
discussed. This is complemented by a review of the few existing models of system
innovations.
The thesis further develops a specification of the regime concept. A regime refers to a
dominant structure which originates incremental change but resists system innovations.
The concept of "regime" is at the heart of the multi-level perspective, the most widely
used framework of transition research, but it is yet only loosely defined. The absence of shared definitions, concept specifications and operationalizations of key concepts of transition research is a major obstacle for defining (and especially for comparing) models.
In this thesis, five defining characteristics of regimes are developed and a method to structure and graphically represent knowledge about a regime is introduced.
Furthermore, theoretical and conceptual work has been complemented by hands-on
experience to make methodological and theoretical deliberations tangible. An agent-based model has been developed which addresses the transition from rainfed to irrigated agriculture in the Upper Guadiana, Spain. The purpose of the model is to bridge a gap in the explanation for the observed process. Case specific literature provides information on driving forces (technological development, changes in regulations) and consequences (amount of irrigation). The model focuses on the farmers which "translate" driving forces
into practices of irrigation and water use. It studies the effect of weights farmers attach to a list of priorities. The main findings are that interactions of factors have to be considered and that it is important to acknowledge heterogeneity of farm types to understand empirically observed land-use changes.
Based on the outlined work, different possibilities to model system innovations have been abstracted and discussed with respect to their advantages and limitations: a) functional subsystems, b) interacting structures (niches, regimes and landscape) as suggested by the multi-level perspective and c) micro-level entities (actors, technological artefacts, institutions, etc.). None of these representations is superior to the other ones per se but
each features certain advantages and drawbacks. The model purpose is a necessary
guideline to choose an appropriate representation and to distinguish those parts and aspects of a system which need to be captured from negligible ones.
The main findings of this thesis can be summarized as follows: System innovations
feature several characteristics which put model-based approaches to this topic on the most challenging edge of the broader endeavour of understanding and modelling social systems. Those are the significance of emergent decay and re-creation of structure during system innovations; the vast scope of system innovations involving several types of subsystems (consumption, production, governance, and nature); the intertwinement of system innovations with their governance – a field which is hardly accessible to modelling; the complexity of the topic; and the unpredictability of innovations.
Still, it is concluded that models can be useful as thinking tools. In any case, given the complexity of the topic and the underdeveloped knowledge base, adhering to transparency is essential. In a field as vast and complex as system innovations this requires either very strong simplifications or restricting a model's scope to some parts or aspects of an overall process. This thesis proposes to make use of existing building blocks of understanding of
an intermediate level of complexity – e.g. timing and kind of multi-level interactions - to define abstractions and model scope. The challenge to identify, specify, understand and relate conceptual building blocks, to identify the contexts and situations in which each of them becomes relevant and to explicate their role in the overall system innovation could be an agenda for transition modelling for the coming years.
Modelling system innovations will remain a huge challenge in the near future. However,
this thesis fathoms that models can be valuable tools contributing to the enhancement of the knowledge base of the field; little by little adding to answers of the "big questions".
The specific role(s) models of system innovations can play in this endeavour needs to be further explored and discussed.
| Identifer | oai:union.ndltd.org:uni-osnabrueck.de/oai:repositorium.ub.uni-osnabrueck.de:urn:nbn:de:gbv:700-201006116333 |
| Date | 11 June 2010 |
| Creators | Holtz, Georg |
| Contributors | Prof. Dr. Claudia Pahl-Wostl, PD Dr. Bernhard Truffer |
| Source Sets | Universität Osnabrück |
| Language | English |
| Detected Language | English |
| Type | doc-type:doctoralThesis |
| Format | application/zip, application/pdf |
| Rights | Namensnennung 3.0 Unported, http://creativecommons.org/licenses/by/3.0/ |
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