Complexity in Industrial Ecology: Models, Analysis, and Actions

Abstract

“ . . . beyond methods and tools, the articles in this special issue are proof that complexity science has provided IE an overarching knowledge paradigm that matches the continuously evolving resource, production, and consumption systems that are the object of study in the field.” co-authorship networks, and offer application of complex systems models and analyses. The articles demonstrate the links, relevance, and implications of many (often emerging) fields of study to IE, including network analysis, participatory modeling, nonequilibrium thermodynamics, and agent-based modeling. Together, these articles show that IE itself is a complex adaptive system, where knowledge, frameworks, methods, and tools evolve with and by their applications and use in small and large case studies— multidisciplinary knowledge ecology. In the special issue “Complexity and Industrial Ecology” (Volume 13, Number 2, 2009), Dijkema and Basson (2009, 157) propose that “ . . . complexity theory and its tools has potential to shift the frontier of Industrial Ecology, by enhancing the quality of systems analysis and by underpinning recommendations for redirecting industrial development towards sustainability.” Indeed, in action-oriented IE (Nikolic et al. 2009), we arguably study “complex, layered and dynamic systems that interact with their environment and thereby perpetually affect one another” (Dijkema and Basson 2009, 157). Indeed, we study sociotechnical systems, where the social evolves the technical and vice versa (de Bruijn and Herder 2009). Both their evolution and impact occur at multiple spatial, temporal, and systems scales. Where it has been argued that “sustainability” is an anthropocentric, normative concept (Allenby 2009; Ehrenfeld 2007), from complexity science we may learn that sustainability is an emerging characteristic of the complex adaptive system of our planet earth and any subsystem or part thereof (Nikolic et al. 2009). Taking a complex systems approach and applying complex systems methods can thus deepen and broaden our understanding of resource, production, and consumption systems. In fact,