Barry Newell, The Australian National University, Canberra, Australia


Presentation Title: Collaborative conceptual modelling: UNRAVELING the complexity of urban systems

Slides

 

Summary

Collaborative Conceptual Modelling (CCM) is a practical meta-method designed to guide the integrated use of the concepts and tools of applied history, system dynamics and scenario planning with its use in search for dominant feedback structures. CCM consists of six ‘co-evolving activities’ that are labelled with key questions: What is the challenge? What is the story? Can I see how you think? What drives system behavior? Where are the leverage points? Can we have new eyes? Embedded in each activity are well-defined protocols that can help a cross-discipline, cross-sector group to develop a shared understanding of urban dynamics and so develop more-sustainable policies and practices.

Key Lessons Learned

Cities are complex adaptive systems. When managers take action in such a system a spectrum of unexpected outcomes emerges, driven by interactions between the parts of the system. Overwhelmingly, these outcomes are unwanted and cannot be anticipated on the basis of studies of the parts taken separately. A comprehensive view is needed. As soon as one tries to look at the whole city, however, it s overwhelming in its complexity. This research  focuses on ways to escape from this ‘complexity dilemma’ (for a summary see Newell and Proust 2012 Introduction to Collaborative Conceptual Modelling). This work has led to the following views:

  • A new science of cities needs to have a mutually agreed theoretical and methodological framework. System Dynamics, as developed initially at the Massachusetts Institute of Technology (Forrester 1961), can provide a significant component of the required theory. Nevertheless, like any theory, the framework must capture essential invariances if it is to provide useful guidance, and suggest ways to escape from the complexity dilemma. Research has led to the conclusion that these essential invariances include relatively simple, generic feedback structures, such as the ‘system archetypes’ popularised by Senge (1990). These feedback structures can be thought of as ‘invariances of organisation’ (Laszlo 1996).
     
  • A science of cities, if it is to support efforts to respond to global change, must have an urban dynamics core. ‘Urban dynamics’ is defined to be the study of the way that the state of a city changes over time in response to both endogenous and exogenous forces. Of particular importance is the interplay between the accumulations (or stocks) that represent the time-dependent state variables of the urban complex and the state-change processes (or flows) that change those accumulations.
     
  • There are two sets of critical interactions that must be taken into account in any science of cities: (a) cross-sector feedback interactions that can dominate the dynamics of urban systems, and (b) knowledge-generating discussions between people from many different disciplines, sectors, and walks of life. Because no one person can see the whole system, effective integrative discussions are absolutely necessary if cross-sector feedback structures are to be identified and understood. Nevertheless, the effort required is rarely deemed worthwhile. Focused dialogue of the required openness and depth is rare. A key lesson is that, while truly effective communication is difficult and time consuming, it is a critical enabler of any effort to unravel the complexity of urban systems (Newell 2012).

Policy/Practice Implications of Research

The single most important implication for policy/practice is the need to develop a more integrative, cross-sector approach to policy design and management. The persistence of the major problems facing urban communities is due largely to the highly fragmented, silo-based approach taken at all levels of governance. Cross-sector feedback effects are generally overlooked, greatly increasing the prevalence of policy resistance and failure. The possibility that an action taken in one sector can feed back, through other sectors to undercut the initial management initiative, is rarely considered. The fact that these unwanted outcomes are usually delayed by years hides the feedback effects, and so exacerbates the situation. Such outcomes can be minimized only by focused dialogue between people from different sectors, carried out by individuals who understand the basics of feedback dynamics.

Knowledge Gaps and Needs

  • To what extent can significant aspects of the dynamics of an urban complex be captured by low-order system-dynamics (LOSD) models? There is a need for more theoretical research into the number of variables that an urban system can ‘see’. Existing research suggests that this is a small number.
     
  • How can policymakers and managers be helped to understand the critical role of cross-sector feedback? There is a need for case studies (both modern and historical) that demonstrate the impact of cross-sector feedback in urban systems.
     
  • How can system dynamics concepts and tools be used to craft a shared cause-effect language that can support effective communication across discipline and sector boundaries? There is a need for much more work on the difficulties of effective communication between people with different backgrounds, and on the development of ways to improve communication.

 

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