The Knowledge-Based Economy by Loet Leydesdorff

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.

Andrew Webster
Science & Technology Studies, University of York, UK

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.

Mike Thelwall
Information Science, University of Wolverhampton, UK

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.

Dirk Baecker
Sociology, Universität Witten/Herdecke, Germany

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 volatile as knowledge be sustained? The urgency of improving our understanding of a knowledge-based economy provides the 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 specified knowledge-based systems from a sociological perspective. In this book, I take this theory one step further and demonstrate how the knowledge base of an economic system can be operationalized, both in terms of measurement and by providing simulation models.

In the first chapters, I make two theoretical steps. First, I submit that the knowledge base of an economy can be considered as an effect of the interactions between three social coordination mechanisms: economic exchange relations, political power relations, and the socially organized generation of novelty in the science system. In other words, this generalized Triple Helix model can be used as an explanans for the knowledge-based economy as the explanandum. Because the three (differently coded) communication systems can also interact, my approach takes elements from Luhmann’s (1984) social systems theory, but also deviates from it. This is extensively explained in Chapter Two, where I specify meaning-processing as an operation on underlying (Shannon-type) information processing.

Meaning is provided from the perspective of hindsight, and thus the time axis is locally inverted. Knowledge can then be considered as a meaning that makes a difference from the perspective of hindsight, and thus discursive knowledge as a social coordination mechanism can be expected to reinforce this inversion of the time axis. These two levels of codifying the events along the time axis from the perspective of hindsight can be modeled using concepts like weakly and strongly anticipatory systems, respectively (Rosen, 1985; Dubois, 1998).

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.