Gerard P J Dijkema
Biographic Data
| ID | 6273914 |
|---|---|
| NAME | Gerard P J Dijkema |
| GIVEN NAMES | Gerard P J |
| FAMILY NAME | Dijkema |
| SIGNATURE | DIJKEMA G P J |
| AFFILIATIONS | Delft University of Technology |
| VERIFIED | No |
| TOTAL WORKS | 14 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 14 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1998 |
| LATEST PUBLICATION YEAR | 2016 |
| H-INDEX | 1 |
An Energy Systems Modelling Tool for the Social Simulation Community
The growing importance of links between the social and technical dimensions of the electricity infrastructure mean that many research problems cannot be effectively addressed without joint consideration of social and technical dynamics. This paper motivates the need for and introduces a tool to facilitate the development of linked social and technical models of electric power systems. The tool, called MatpowerConnect, enables the runtime linkage …
Complexity in Industrial Ecology
What Makes Eco‐Transformation of Industrial Parks Take Off in China
This article focuses on the effects of policy instruments for developing viable eco‐industrial parks (EIPs) in China. We analyzed the root of China's national EIP program and inventoried the general instruments available to local authorities to shape and promote eco‐industrial development. Empirical research conducted in Tianjin Economic‐technological Development Area and Dalian Development Area led to the activities and actions conducted by loca…
Multimodel Ecologies
Many industrial ecology models may be classified as single‐use products ‐constructed to address a specific problem and of little use beyond their original context. But a knowledge ecosystem based around single‐use representations of reality wastes effort and resources and limits the impact of industrial ecology as a field. In recent years, tangible progress has been made in areas such as integrated modeling and multisimulation. However, this work…
Structuring Qualitative Data for Agent-Based Modelling
Using ethnography to build agent-based models may result in more empirically grounded simulations. Our study on innovation practice and culture in the Westland horticulture sector served to explore what information and data from ethnographic analysis could be used in models and how. MAIA, a framework for agent-based model development of social systems, is our starting point for structuring and translating said knowledge into a model. The data tha…
Understanding the Evolution of Industrial Symbiosis Research
This study analyzes the evolution of the research field of industrial symbiosis (IS). We elucidate its embedding in industrial ecology (IE), trace the development of research themes, and reveal the evolution of the research network through analysis of the core literature and journals that appeared from 1997 to 2012 by citation analysis, cocitation analysis, and network analysis. In the first period (1997–2005), IS research held a minority share i…
Evolving Greenhouses
To explore the space between the theories of the Diffusion of Innovations and Universal Darwinism, we first examine a case study of the history of the greenhouse horticulture sector of the Netherlands, comparing and contrasting the narrow focus of Diffusion of Innovations and the wider focus of Universal Darwinism. We then build an agent-based model using elements of both in order to test how well the Diffusion of Innovations theory holds up when…
Maia
In this paper we introduce and motivate a conceptualization framework for agent-based social simulation, MAIA: Modelling Agent systems based on Institutional Analysis. The MAIA framework is based on Ostrom's Institutional Analysis and Development framework, and provides an extensive set of modelling concepts that is rich enough to capture a large range of complex social phenomena. Developing advanced agent-based models requires substantial experi…
Modeling Metal Flow Systems
Substance flow analysis (SFA) is a frequently used industrial ecology technique for studying societal metal flows, but it is limited in its ability to inform us about future developments in metal flow patterns and how we can affect them. Equation‐based simulation modeling techniques, such as dynamic SFA and system dynamics, can usefully complement static SFA studies in this respect, but they are also restricted in several ways. The objective of t…
Industrial Ecology 2.0
Industrial ecology (IE) is an ambitious field of study where we seek to understand systems using a wide perspective ranging from the scale of molecules to that of the planet. Achieving such a holistic view is challenging and requires collecting, processing, curating, and sharing immense amounts of data and knowledge. We are not capable of fully achieving this due to the current state of tools used in IE and current community practices. Although w…
Complexity and Industrial Ecology
Integration of Life Cycle Assessment Into Agent‐Based Modeling
A method is presented that allows for a life cycle assessment (LCA) to provide environmental information on an energy infrastructure system while it evolves. Energy conversion facilities are represented in an agent‐based model (ABM) as distinct instances of technologies with owners capable of making decisions based on economic and environmental information. This simulation setup allows us to explore the dynamics of assembly, disassembly, and use …
Process Knowledge, System Dynamics, and Metal Ecology
A key principle in industrial ecology is the cyclic use of materials, a characteristic of natural ecosystems but a challenge in economic systems. Indeed, in society, metal retention, that is, the ongoing use or ready availability of metal in the economy between the life‐cycle stages of resource extraction and final disposal back into the lithosphere, is finite because of the limited grade of secondary (recycled) metals. Currently, the utility of …
Eia’s contribution to environmental decision-making on large chemical plants
Eia’s contribution to environmental decision-making on large chemical plants
Process Knowledge, System Dynamics, and Metal Ecology
A key principle in industrial ecology is the cyclic use of materials, a characteristic of natural ecosystems but a challenge in economic systems. Indeed, in society, metal retention, that is, the ongoing use or ready availability of metal in the economy between the life‐cycle stages of resource extraction and final disposal back into the lithosphere, is finite because of the limited grade of secondary (recycled) metals. Currently, the utility of …
Complexity and Industrial Ecology
Integration of Life Cycle Assessment Into Agent‐Based Modeling
A method is presented that allows for a life cycle assessment (LCA) to provide environmental information on an energy infrastructure system while it evolves. Energy conversion facilities are represented in an agent‐based model (ABM) as distinct instances of technologies with owners capable of making decisions based on economic and environmental information. This simulation setup allows us to explore the dynamics of assembly, disassembly, and use …
Industrial Ecology 2.0
Industrial ecology (IE) is an ambitious field of study where we seek to understand systems using a wide perspective ranging from the scale of molecules to that of the planet. Achieving such a holistic view is challenging and requires collecting, processing, curating, and sharing immense amounts of data and knowledge. We are not capable of fully achieving this due to the current state of tools used in IE and current community practices. Although w…
Modeling Metal Flow Systems
Substance flow analysis (SFA) is a frequently used industrial ecology technique for studying societal metal flows, but it is limited in its ability to inform us about future developments in metal flow patterns and how we can affect them. Equation‐based simulation modeling techniques, such as dynamic SFA and system dynamics, can usefully complement static SFA studies in this respect, but they are also restricted in several ways. The objective of t…
Evolving Greenhouses
To explore the space between the theories of the Diffusion of Innovations and Universal Darwinism, we first examine a case study of the history of the greenhouse horticulture sector of the Netherlands, comparing and contrasting the narrow focus of Diffusion of Innovations and the wider focus of Universal Darwinism. We then build an agent-based model using elements of both in order to test how well the Diffusion of Innovations theory holds up when…
Maia
In this paper we introduce and motivate a conceptualization framework for agent-based social simulation, MAIA: Modelling Agent systems based on Institutional Analysis. The MAIA framework is based on Ostrom's Institutional Analysis and Development framework, and provides an extensive set of modelling concepts that is rich enough to capture a large range of complex social phenomena. Developing advanced agent-based models requires substantial experi…
Understanding the Evolution of Industrial Symbiosis Research
This study analyzes the evolution of the research field of industrial symbiosis (IS). We elucidate its embedding in industrial ecology (IE), trace the development of research themes, and reveal the evolution of the research network through analysis of the core literature and journals that appeared from 1997 to 2012 by citation analysis, cocitation analysis, and network analysis. In the first period (1997–2005), IS research held a minority share i…
Complexity in Industrial Ecology
What Makes Eco‐Transformation of Industrial Parks Take Off in China
This article focuses on the effects of policy instruments for developing viable eco‐industrial parks (EIPs) in China. We analyzed the root of China's national EIP program and inventoried the general instruments available to local authorities to shape and promote eco‐industrial development. Empirical research conducted in Tianjin Economic‐technological Development Area and Dalian Development Area led to the activities and actions conducted by loca…
Multimodel Ecologies
Many industrial ecology models may be classified as single‐use products ‐constructed to address a specific problem and of little use beyond their original context. But a knowledge ecosystem based around single‐use representations of reality wastes effort and resources and limits the impact of industrial ecology as a field. In recent years, tangible progress has been made in areas such as integrated modeling and multisimulation. However, this work…
Structuring Qualitative Data for Agent-Based Modelling
Using ethnography to build agent-based models may result in more empirically grounded simulations. Our study on innovation practice and culture in the Westland horticulture sector served to explore what information and data from ethnographic analysis could be used in models and how. MAIA, a framework for agent-based model development of social systems, is our starting point for structuring and translating said knowledge into a model. The data tha…
An Energy Systems Modelling Tool for the Social Simulation Community
The growing importance of links between the social and technical dimensions of the electricity infrastructure mean that many research problems cannot be effectively addressed without joint consideration of social and technical dynamics. This paper motivates the need for and introduces a tool to facilitate the development of linked social and technical models of electric power systems. The tool, called MatpowerConnect, enables the runtime linkage …
Computer Science (11 works) · Industrial ecology (9 works) · Sustainability (8 works) · Sustainable Industrial Ecology (8 works) · Ecology (7 works) · Biology (6 works) · Engineering (6 works) · Environmental Science (6 works) · Business (5 works) · Environmental resource management (4 works)