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Exploring the Synergy Between Industrial Ecology and System of Systems to Understand Complexity
Author(s) -
DeLaurentis Daniel A.,
Ayyalasomayajula Sricharan
Publication year - 2009
Publication title -
journal of industrial ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.377
H-Index - 102
eISSN - 1530-9290
pISSN - 1088-1980
DOI - 10.1111/j.1530-9290.2009.00121.x
Subject(s) - sociotechnical system , industrial ecology , computer science , complex adaptive system , context (archaeology) , management science , complex system , ecology , systems ecology , adaptation (eye) , systems thinking , perspective (graphical) , system of systems , ecological systems theory , systems theory , data science , knowledge management , engineering , systems design , applied ecology , artificial intelligence , software engineering , biology , paleontology , neuroscience , sustainability , biodiversity
Summary Two objectives are pursued in this article. First, from a methodological perspective, we explore the relationships among the constructs of complex adaptive systems, systems of systems, and industrial ecology. Through examination of central traits of each, we find that industrial ecology and system of systems present complementary frameworks for posing systemic problems in the context of sociotechnical applications. Furthermore, we contend that complexity science (the basis for the study of complex adaptive systems) provides a natural and necessary foundation and set of tools to analyze mechanisms such as evolution, emergence, and regulation in these applications. The second objective of the article is to illustrate the use of two tools from complexity sciences to address a network transition problem in air transportation framed from the system‐of‐systems viewpoint and shaped by an industrial ecology perspective. A stochastic simulation consisting of network theory analysis combined with agent‐based modeling to study the evolution of an air transport network is presented. Patterns in agent behavior that lead to preferred outcomes across two scenarios are observed, and the implications of these results for decision makers are described. Furthermore, we highlight the necessity for future efforts to combine the merits of both system of systems and industrial ecology in tackling the issues of complexity in such large‐scale, sociotechnical problems.