Changing Stocks, Flows and Behaviors in Industrial Ecosystems

Changing Stocks, Flows and Behaviors in Industrial Ecosystems

Edited by Matthias Ruth and Brynhildur Davidsdottir

Industrial ecology provides a consistent material and energetic description of human production and consumption processes in the larger context of environmental and socioeconomic change. The contributors to this book offer methodologies for such descriptions, focusing on the dynamics associated with stocks of materials and capital, flows of raw materials, intermediate products, desired outputs and wastes, as well as the associated changes in behaviors of producers, consumers and institutions.

Chapter 6: Agent-Based Analysis of Dynamic Industrial Ecosystems: An Introduction

Marco A. Janssen

Subjects: business and management, management and sustainability, organisation studies, economics and finance, industrial organisation, environment, environmental management, environmental sociology


Marco A. Janssen INTRODUCTION The agent-based approach, which is used in the chapters of this part, explicitly studies the emergent macro-level phenomena from interactions at the microlevel between autonomous agents. Individual attributes and strategies of the agents can influence the emergent patterns, the information derived by the agents, and the structure of the network of agents. Agent-based analysis can be performed by conceptual (Chapter 9) as well as computational approaches (Chapters 7 and 8). The computational approach is referred to as agent-based modeling. Agent-based modeling within social science has its roots in the early 1970s. Initially developed during the 1940s, the technical methodology of computational models of multiple interacting agents arose when John von Neumann started to work on cellular automata (von Neumann 1966). A cellular automata is a set of cells where each cell can be in one of multiple predefined states, such as forest land or farm land. Changes in the state of a cell occur based on the prior states of the cell’s own history and the history of neighboring cells. Cellular automata became more popular in light of a creative application by John Conway, named the Game of Life (Gardner 1970). The Game of Life illustrated how the following simple rules of local interaction could lead to the emergence of complex global patterns. In contrast to cellular automata, agent-based models enable a researcher to examine the heterogeneity of agents beyond their specific location and history. A pioneering contribution is the work of economist...

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