The emergence of self-organisation in social systems: the case of the geographic industrial clusters

The objective of this work is to use complexity theory to propose a new interpretation of industrial clusters. Industrial clusters constitute a specific type of econosphere, whose driving principles are self-organisation, economies of diversity and a configuration that optimises the exploration of diversity starting from the configuration of connectivity of the system. This work shows the centrality of diversity by linking complexity theory (intended as "a method for understanding diversity"') to different concepts such as power law distributions, self-organisation, autocatalytic cycles and connectivity.I propose a method to distinguish self-organising from non self-organising agglomerations, based on the correlation between self-organising dynamics and power law network theories. Self-organised criticality, rank-size rule and scale-free networks theories become three aspects indicating a common underlying pattern, i.e. the edge of chaos dynamic. I propose a general model of development of industrial clusters, based on the mutual interaction between social and economic autocatalytic cycle. Starting from Kauffman's idea(^2) on the autocatalytic properties of diversity, I illustrate how the loops of the economies of diversity are based on the expansion of systemic diversity (product of diversity and connectivity). My thesis provides a way to measure systemic diversity. In particular I introduce the distinction between modular innovation at the agent level and architectural innovation at the network level and show that the cluster constitutes an appropriate organisational form to manage the tension and dynamics of simultaneous modular and architectural innovation. The thesis is structured around two propositions: 1. Self-organising systems are closer to a power law than hierarchical systems or aggregates (collection of parts). For industrial agglomerations (SLLs), the closeness to a power law is related to the degree of self-organisation present in the agglomeration, and emerges in the agglomeration’s structural and/or behavioural properties subject to self-organising dynamic.2. Self-organising systems maximise the product of diversity times connectivity at a rate higher than hierarchical systems

Beyond Gaussian averages : redirecting management research toward extreme events and power laws

Practicing managers live in a world of ‘extremes’ but management research is based on Gaussian statistics that rule out those extremes. On occasion, deviation amplifying mutual causal processes among interdependent data points cause extreme events characterized by power laws. They seem ubiquitous; we lis t80 kinds of them – half each among natural and social phenomena. We draw a ‘line in the sand’ between Gaussian (based on independent data points, finite variance and emphasizing averages) and Paretian statistics(based on interdependence, positive feedback, infinite variance, and emphasizing extremes). Quantitative journal publication depends almost entirely on Gaussian statistics. We draw on complexity and earthquake sciences to propose redirecting Management Studies. No statistical findings should be accepted into Management Studies if they gain significance via some assumption-device by which extreme events and infinite variance are ignored. The cost is inaccurate science and irrelevance to practitioners

NEKS final report

The NEKS project in the North East of England resulted in a number of outcomes, the following being the most important: 1. Identification and mapping of the subsea technologies cluster [STC] for the first time 2. Creating basis for collaboration and networking within the sector 3. Establishing links between the subsea sector and: academia, local authorities and other organisations 4. Helped to raise awareness and identity of subsea sector in the North East 5. Helped to identify and address main issues the sector faces 6. Creation of a committee for Subsea North East as an administrative body to provide a platform for collaboration, networking and addressing a number of issues identified in the course of the project 7. Development of a new framework for identification and supporting embryonic clusters in the context of industrial demis

Constraints and sources of nonequilibrium: a case of radical market transformation in Brazil

Illycaffé entered Brazil in 1991 with the simple goal of finding high quality coffee and with a simple but revolutionary procurement strategy based on a) direct interaction with farmers and b) on an Award for the best coffee quality beans. The entry of Illycaffé unleashed a series of long-lasting consequences and unintended effects that revolutionised the Brazilian coffee industry and enabled the emergence of the quality coffee sector from the undifferentiated segment of commodity production. This paper analyses the ‘butterfly effect’ of the emergence of the quality coffee in Brazil in terms of complexity theory; and more specifically in terms of constraints and sources on nonequilibrium. I show how the entry of Illycaffé worked as an attractor (pull-strategy) that caused the decommoditisation of the coffee sector, enabled the emergence of a network of quality producers, and caused the rise of a ‘long tail’ of diversity

Measuring exaptation and its impact on innovation, search, and problem solving

Exaptation, the emergence of latent functionality in existing artifacts, is an underexplored mechanism of novelty generation in innovation. In this paper, we measure the frequency of exaptation in the pharmaceutical industry. We find that about 42% of new functions derived from existing drugs have an exaptive nature. We think that this constitutes the first measure of exaptation in any industry. We also link exaptation with radical innovation and find that most radical innovations in our sample are exaptive. Also, nearly all radical innovations occur in market areas very distant from the drug’s original market. We propose that exaptive innovation constitutes a different search mechanism and problem-solving approach from deliberate innovation and discuss the role of context and serendipity in innovation

Beyond Gaussian Averages: Redirecting Management . . .

international business and management research toward extreme events and power law

Managing in a Pareto world calls for new thinking

ABSTRACT Increasingly, complexity science focuses on power laws, long tails, extreme events, fractals and other Pareto-related effects. New fields such as econophysics and sociophysics have arisen. These recognize the nonlinear interdependences among agents, where power laws are often signify scale-free dynamics. Findings showing the ubiquity of power laws in the social and organizational worlds underlie increasing calls for more applications of Pareto-driven ideas to organizational and management research. Given that the world of practicing managers is, then, quite likely Paretian rather than Gaussian, what to tell managers? Basic ideas highlighting key differences between Gaussian and Paretian approaches are first reviewed. Then, four specific cases highlighting the managerial tails of Pareto distributions are discussed. These illustrate how overall managerial effectiveness improves by managing the Pareto tails rather than relying on conventional wisdom to manage 'average' behaviour. Insights and effective strategies better tuned to Pareto-distributed managerial practice follow