Challenging, theoretically rich yet anchored in detailed empirical analysis, Loet Leydesdorff’s exploration of the dynamics of the knowledge-economy is a major contribution to the field. Drawing on his expertise in science and technology studies, systems theory, and his internationally respected work on the ‘triple helix’, the book provides a radically new modelling and simulation of knowledge systems, capturing the articulation of structure, communication, and agency therein. This work will be of immense interest to both theorists of the knowledge-economy and practitioners in science policy.
This book is a ground-breaking collection of theory and techniques to help understand the internal dynamics of the modern knowledge-based economy, including issues such as stability, anticipation, and interactions amongst components. The combination of theory, measurement, and modelling gives the necessary power with which to address the complexity of modern networked social systems. Each on its own would partly illuminate an innovation system, but the combination sheds a far brighter light.
The sociologist Niklas Luhmann is considered one of the few social scientists possibly able to explain a decisive event once it has happened. In this book, Loet Leydesdorff answers the challenge to take Luhmann’s analysis one step further by introducing anticipation into the theory. This book provides a fascinating exploration of the use of recursion and incursion to model social processes.
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Newsletter 20 of Research Committee 51 (Sociocybernetics) of the International Sociological Association, December 2006, pp. 12-13:
How can an economy based on something as
knowledge be sustained? The urgency of improving our understanding of a
knowledge-based economy provides
context and necessity of this study. In a previous study entitled A Sociological Theory of Communications: The
Self-Organization of the Knowledge-based Society (2001), I
knowledge-based systems from a sociological perspective. In this book,
this theory one step further and demonstrate how the knowledge base of
economic system can be operationalized, both in terms of measurement
providing simulation models.
Weakly and strongly anticipatory systems can be operationalized by using incursive and hyper-incursive equations. In the case of hyper-incursivity, the future states of the system are considered as the independent variable. Thus, the system co-constructs its own future. I show in Chapter Four that the incursive and hyper-incursive formulations of the logistic equation enable us to model the knowledge-based economy as a regime which continuously produces sets of differently codified expectations (Leydesdorff & Dubois, 2004). These different sets have to be interfaced by organizing decisions. The decisions are shaped along historical trajectories and can thus become locked-in into suboptima (Arthur, 1994; Luhmann, 2000).
The mutual information in three (or more) dimensions enables us to measure the generation of negative (probabilistic) entropy within a knowledge-based system. The negative value of the probabilistic entropy indicates the inversion of the time axis quantitatively. In the empirical chapters (8, 9, and 10), this is first elaborated from the perspective of the Triple-Helix model, and then applied to the measurement of the knowledge bases in the Dutch and German economies (Leydesdorff, Dolfsma, & Van der Panne, 2006; Leydesdorff & Fritsch, 2006). Among the conclusions: high-tech manufacturing and knowledge-intensive services tend to uncouple the knowledge-based economy from its geographical dimension as a consequence of potential globalization. Regional development efforts should focus on medium-tech manufacturing.
In the final chapter, I turn to the philosophical reflection on how the knowledge base of an economy can be conceptualized as an order of expectations. Following Luhmann (1995), I use Husserl’s (1929) notion of the substantivity of the cogitatum, that is, the subject of uncertainty of Descartes’s cogito. In principle, uncertainties can nowadays be measured using information theory (Shannon, 1948; Theil, 1972; Leydesdorff, 1995). Luhmann, following Parsons, added that under the condition of modernity the uncertainty in communication systems is functionally differentiated in terms of the codes of the communication. Hitherto, the Shannon-formulas have only been elaborated with the axis of time. This study adds the non-linear dynamics of meaning-processing against the axis of time, provides the relevant formulas, and shows how one could begin with the operationalization. The focus is on the knowledge-based economy, but the socio-cybernetics can also be applied to other knowledge-based (sub)systems.
The Knowledge-Based Economy: Modeled, Measured, Simulated
Table of Contents
1. The Knowledge-Based Economy
1.1 What is the knowledge base of an economy?2. Knowledge, Information, and Globalization
2.1 Information, uncertainty, and meaning3. The Processing of Meaning in Anticipatory Systems
3.1 Simulation and the second-order perspective4. Codification and Differentiation of Meaning in Social Systems
4.1 The sociological perspective in systems theory5. The Transformation of Organization and Agency
5.1 Hyper-incursion and the requirement of decisions6. Reflexive Globalization and the Emergence of a Knowledge-Based Order
6.1 The emergence of a global level7. The Historical Evolution of the Triple Helix
7.1 Science and technology policies8. The Measurement of the Knowledge Base
8.1 The Triple Helix dynamics9. The Knowledge Base of the Dutch Economy
9.1 The measurement problem in evolutionary economics10. The Knowledge Base of the German Economy
10.1 Methods and materials11. Summary and Conclusions:
The foundation of the knowledge base in Husserl’s CogitatumBibliography
List of Figures
List of Tables