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Synthesis

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Co-Evolution of Standards in Innovation Systems

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

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Abstract

The main contributions of the book are developed in Chaps. 5, 6, 7, and 8. The integration of the results of these chapters helps in arriving at the quantitative feedback model and policy analysis of Chap. 6. Chapter 5 has created the qualitative-conceptual base. Chapter 7 contributed frameworks and a heuristic to the available validation methodology of system dynamics. These means of validation have supported the model development and increased its level of validity. Chapter 8 has created a measure of dynamic complexity to ensure that the model in Chap. 6 indeed captures that dimension. Besides the individual contributions of the previous chapters, Chap. 9 now relates selected contributions of the book to existing fields of research. In addition, it abstracts from the case study and develops a generic model about the co-evolution of norms. Chapter 9 thereby provides hypotheses as a means to advance existing research. From a methodological perspective, this chapter also conceptualizes a modular and generic piece of simulation structure (molecule) which can be reused in modeling nonlinear behavioral-decision rules.

The goal of any science is to discover hypotheses and laws that may ultimately be organized into a deductive system or theory. This is the essence of cumulative knowledge in science. From this vantage point, cumulative knowledge is not simply the accumulation of facts and laws; rather it is the construction of more complex theoretical systems or theories which explain empirical laws and facts in the deductive sense. Nagasawa von Bretzel (1977, p. 222)

All truths are easy to understand once they are discovered; the point is to discover them. Galileo Galilei

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Notes

  1. 1.

    The development of methods, concepts, measures, and other means for undertaking the intended research is normal in other fields of science. My personal experiences refer to the fields of electrical engineering and molecular biology.

  2. 2.

    I want to thank Georg Richardson, Henry Weil, and John Lyneis for stimulating discussions during the process of developing the measure in Chap. 8.

  3. 3.

    The term “synthesis”, as understood here, has three functions. The first is that sythesizing relates the book’s contributions to the existing research addressed at the outset of the research. The second function is that synthesizing also connects the research to fields of study which have not been addressed at the outset of the book. This latter function situates, the book in a larger context, a process which can include the abstraction or generalization of results. And the third meaning of synthesis, as used here, also contains the creation of hypotheses that bring together the insights of the book. These hypotheses also relate to a broader area then the original scope of research.

  4. 4.

    The index i can assume values from {1,2} since there are two norms in Fig. 9.1.

  5. 5.

    Simulation has been used for the purpose to develop broader hypotheses based on single case studies. Others have used simulation modeling in this mode before (e.g., Abrahamson & Rosenkopf, 1993; Perlow & Repenning, 2009; Yücel & van Daalen, 2011).

  6. 6.

    I do not introduce the possible combinations of the different types of controls.

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  1. Institute of Management (IfB-HSG) HSG System Dynamic Group, University of St. Gallen, St.Gallen, Switzerland

    Stefan N. Grösser

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  1. Stefan N. Grösser
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Grösser, S.N. (2013). Synthesis. In: Co-Evolution of Standards in Innovation Systems. Contributions to Management Science. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2858-0_9

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