Introduction This issue of E:CO is devoted to the absolutely vital issue of how our new acceptance and understanding of complexity affects the knowledge we have, and the basis that this provides for any policy or intervention that is aimed at ‘improving’ the future. Since there is already an excellent editorial written by the guest […]
Introduction The advent of the new sciences of complexity has produced a subtle but important change in policy analysis illustrated by the papers in this volume. In brief, policy analysis is no longer strictly concerned with simplifying a complex environment by reducing alternatives for problem solving and resource allocation to a few optimal scenarios that […]
Real institutions are ‘open’, which can result in unpredictable changes in both their internal resources and external environment. This implies that a broadly useful approach to decision support must not rely on either prediction or on gathering all relevant information before useful calculations can be made. This paper describes an approach to highly interactive decision support based upon using ensembles of alternative models, robust option analysis, and adaptive strategies.
Concept mapping is a participatory mixed methodology that enables diverse participant groups to develop shared conceptual frameworks that can be used in a variety of policy contexts to identify or encourage complexity, and the adaptive emergent properties associated with it. The method is consistent with an evolving paradigm of complex adaptive systems thinking and helps groups address complexity in several ways: it is inductive, allowing shared meaning to emerge; it is based on a simple set of rules (operations) that generate complex patterns and results; it engages diverse agents throughout the process through a range of participation channels (synchronous or asynchronous web, face-to-face, etc.); the visual products – the concept maps, pattern matches, action plots – provide high-level representations of evolving thinking; the results are generative, encouraging shared meaning and organizational learning while preserving individuality and diversity; the maps themselves provide a framework that enables autonomous agents to align action with broader organizational or systems vision. The concept mapping process involves free listing, unstructured sorting and rating of ideas, and a sequence of statistical analyses (multidimensional scaling, hierarchical cluster analysis) that produce maps and other results that the participants then interpret. An example is provided of a web-based project that mapped the practical challenges that need to be addressed to encourage and support effective systems thinking and modeling in public health work. It is suggested that using concept mapping especially in combination with other types of human simulation provides a valuable addition to our methodological tools for studying complex human systems.
The aim of this paper is to explore how complexity insights can be used to facilitate resource decision making in public systems. The focus is on health care and in particular the UK National Health System. Attempts at rational resource decision making in public systems have identified that there are no explicit frameworks that are acceptable both publicly and politically and that rational decision frameworks are invariably unworkable. This paper explores insights from the UK National Health Service and suggests how complexity insights might be developed to facilitate resource decision making, particularly at grass roots level. The focus moves from the current development of an increasingly methodological competence to creating the conditions for a conversational competence amongst decision makers from which solutions will emerge that may not be optimal but which will satisfy the constraints placed on the system.
One of the celebrated features of the emergence of ‘complexity thinking’ on the research scene is its acclaimed ability to cut across disciplinary boundaries, offering potential explanations to pertinent issues that have haunted ‘experts’ and bureaucrats for a long time. In the field of urban studies, such vexing questions revolve around the notoriety and reluctance of the urban system to be harnessed into our-own-made, control-oriented predictive models. Despite the prevalence of copious volumes of literature on the subject, there are still more questions than answers in the understanding of the urban system. This paper attempts to view urban regeneration through the lenses of complexity theory. The task involves a historical narrative that weighs the evolution of the regeneration processes of a once highly deprived inner city area of Hulme in Manchester against the characteristic features of complex adaptive systems. A premium is placed on the analysis of the design platform and processes that saw Hulme emerge from worst slum in Manchester to one of the exemplars of regeneration in England. The analysis goes beyond mere explanation by making a commitment to securing potential areas for better-informed intervention. The fundamental argument that is championed is that even prior to central intervention, there is usually a resilient prior reality that characterizes that particular setting and that successful intervention is a function of how well a programme conforms to these natural tendencies.
We raise the question of how Ireland can become an innovative knowledge economy. Questioning received orthodoxy we show that Irish culture should put more value on scientific skills, promote a scientifically literate culture, and reform institutional and structural support systems to develop an innovative knowledge-based economy. Developing the idea of knowledge as essentially a complex emergent phenomenon we illustrate the importance of system supports for the development of knowledge and learning through the idea of a national system of innovation. Using the Priority Pointing Procedure, derived from Nomology, we explore the key priorities for Ireland.
Some authors claim that attempts to apply complexity science to organization can only be successful if loyalty is paid to original meanings: only when students of organization accept complexity science as indivisible and operationalize complexity concepts rigorously can faddism be forestalled. In this article it is argued that loose application of complexity theory is not only inevitable, but that meaningful use of complexity theory in the field of organization and management actually depends on flexible application and translation of complexity concepts. The example of the ‘career’ of the anthropological concept of culture in the field of organization is used to support the argument that fitting complexity concepts into their new habitat does not leave them meaningless, but is instead the conditio sine qua non of successful application.
Introduction It is the curse of those who try to create new ideas to be forever stumbling over the same ideas in long forgotten papers. As a defence mechanism we periodically change the language and the boundaries of our disciplines so that we can confidently discount ‘out of date’ ideas as belonging to a previous […]
Just when you thought you had it all figured out, just when everything was starting to make sense and your choices and decisions were beginning to r off, something unexpected pops up that forces a whole new set of consequences, forcing you to operate in a fashion you had never intended. This isn’t theory. This […]
Introduction For those who believe, as I do, that people behave very much as if they were the adaptive agents of complexity theory, few topics are more fascinating than unconscious cognition. After all, if people do behave this way, they are constantly modeling their social environments, continually taking in information of which they are consciously […]
Introduction For the last three or four years, I have looked for a good textbook to introduce theoretical and practical applications of complexity theory to graduate courses in business, public, and nonprofit administration. It should be basic enough to use with students who have never heard of complexity theory, minimize technical or ‘hard science’ terminology, […]