Our society's scientific paradigm prevents us from benefiting from the processes of invention and innovation. This book analyzes the topic in depth, positing that a 'complex systems' approach is better suited than our traditional approach to the phenomenon.

Innovation is nowadays a question of life and death for many of the economies of the western world. Yet, due to our generally reductionist scientific paradigm, invention and innovation are rarely studied scientifically. Most work prefers to study its context and its consequences. As a result, we are as a society, lacking the scientific tools to understand, improve or otherwise impact on the processes of invention and innovation. This book delves deeply into that topic, taking the position that the complex systems approach, with its emphasis on 'emergence', is better suited than our traditional approach to the phenomenon. In a collection of very coherent papers, which are the result of an EU-funded four year international research team's effort, it addresses various aspect of the topic from different disciplinary angles. One of the main emphases is the need, in the social sciences, to move away from neo-darwinist 'population thinking' to 'organization thinking' if we want to understand social evolution. Another main emphasis is on developing a generative approach to invention and innovation, looking in detail at the contexts within which invention and innovation occur, and how these contexts impact on the chances for success or failure. Throughout, the book is infused with interesting new insights, but also presents several well-elaborated case studies that connect the ideas with a substantive body of 'real world' information.

Focus on invention and innovation as socio-technical processes Applied complex system perspective Innovative social science theory Includes supplementary material: sn.pub/extras

Inhalt
From Biology to Society.- From Population to Organization Thinking.- The Innovation Innovation.- The Long-Term Evolution of Social Organization.- Biological Metaphors in Economics: Natural Selection and Competition.- Innovation in the Context of Networks, Hierarchies, and Cohesion.- Innovation and Urban Systems.- The Organization of Urban Systems.- The Self Similarity of Human Social Organization and Dynamics in Cities.- Innovation Cycles and Urban Dynamics.- Innovation and Market Systems.- Building a New Market System: Effective Action, Redirection and Generative Relationships.- Incorporating a New Technology into Agent-Artifact Space: The Case of Control System Automation in Europe.- Innovation Policy: Levels and Levers.- Modeling Innovation and Social Change.- The Future of Urban Systems: Exploratory Models.- Modeling Innovation.- An Agent-Based Model of Information Flows in Social Dynamics.- Exaptive Processes: An Agent Based Model.- Power Laws in Urban Supply Networks, Social Systems, and Dense Pedestrian Crowds.- Using Statistical Physics to Understand Relational Space: A Case Study from Mediterranean Prehistory.