Andrew Ford
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Andrew Ford has a total of 8 co-authors. Here are the top co-authors by number of shared publications:
Hilary Flynn
Prometheus Institute for Sustainable Development, 1280 Massachusetts Avenue, Cambridge, MA 02138, U.S.A.
1 shared publicationJoanne M. Earnhardt
1 shared publicationJohn McLeod
1 shared publicationLisa J. Faust
1 shared publication- Robert Y. Cavana
School of Management Victoria University of Wellington Wellington New Zealand
1 shared publication Rosemary Jackson
1 shared publication
Latest Publications
- 31 January 2020
- Published by Springer Nature
- p. 375-399
System Dynamics Models of Environment, Energy, and Climate Change
- 31 January 2020
- Published by Springer Nature
- p. 375-399
System Dynamics Models of Environment, Energy, and Climate Change
- 11 September 2018
- Published by Springer Nature
- p. 1-25
System Dynamics Models of Environment, Energy, and Climate Change
- 11 September 2018
- Published by Springer Nature
- p. 1-25
System Dynamics Models of Environment, Energy, and Climate Change
- Open Access
- 1 December 2005
- Published by Wiley in System Dynamics Review
- Vol. 21 (4) , 273-303
Statistical screening of system dynamics models
This paper describes a pragmatic method of searching for the key inputs to a system dynamics model. This analysis is known as screening. The goal is to learn which of the many uncertain inputs stand out as most influential. The method is implemented with readily available software and relies on the simple correlation coefficient to indicate the relative importance of model inputs at different times in the simulation. The screening is demonstrated with two examples with step‐by‐step instructions. The paper recommends that screening analysis be used in an iterative process of screening and model expansion to arrive at tolerance intervals on model results. The appendices compare screening analysis with analytical methods to identify the key inputs to system dynamics models. Copyright © 2005 John Wiley & Sons, Ltd.
- 1 December 2005
- Published by Wiley in System Dynamics Review
- Vol. 21 (4) , 273-303
Open AccessStatistical screening of system dynamics models
This paper describes a pragmatic method of searching for the key inputs to a system dynamics model. This analysis is known as screening. The goal is to learn which of the many uncertain inputs stand out as most influential. The method is implemented with readily available software and relies on the simple correlation coefficient to indicate the relative importance of model inputs at different times in the simulation. The screening is demonstrated with two examples with step‐by‐step instructions. The paper recommends that screening analysis be used in an iterative process of screening and model expansion to arrive at tolerance intervals on model results. The appendices compare screening analysis with analytical methods to identify the key inputs to system dynamics models. Copyright © 2005 John Wiley & Sons, Ltd.
- 1 June 2004
- Published by Wiley in System Dynamics Review
- Vol. 20 (2) , 89-98
Environmental and resource systems: Editors' introduction
This paper provides an introduction to the special issue on environmental and resource systems. The quantity and quality of previous system dynamics publications related to environmental and resource systems are briefly outlined. The background to the special issue is provided, together with a summary and comparison of the five papers and models in the issue. The papers relate to forestry in Indonesia, irrigated lands in Spain, renewable resource management in Norway, wildlife management in USA and blue‐green algae bloom in the coastal waters of Australia. Copyright © 2004 John Wiley & Sons, Ltd.
- 1 June 2004
- Published by Wiley in System Dynamics Review
- Vol. 20 (2) , 89-98
Environmental and resource systems: Editors' introduction
This paper provides an introduction to the special issue on environmental and resource systems. The quantity and quality of previous system dynamics publications related to environmental and resource systems are briefly outlined. The background to the special issue is provided, together with a summary and comparison of the five papers and models in the issue. The papers relate to forestry in Indonesia, irrigated lands in Spain, renewable resource management in Norway, wildlife management in USA and blue‐green algae bloom in the coastal waters of Australia. Copyright © 2004 John Wiley & Sons, Ltd.
- 1 June 2004
- Published by Wiley in System Dynamics Review
- Vol. 20 (2) , 163-178
Models for management of wildlife populations: lessons from spectacled bears in zoos and grizzly bears in Yellowstone
Models of population dynamics are frequently used in the management and conservation of wildlife populations. They provide a powerful method of quantitatively assessing a population's risk of decline and determining the potential to reverse the decline. Models from recent studies of managed populations are presented. The first model simulates the spectacled bear populations maintained in American Zoo and Aquarium Association (AZA) zoos. The second model simulates the grizzly bear population in the Greater Yellowstone Ecosystem (GYE). The article concludes with a discussion of system dynamics modeling in the larger context of population dynamics modeling. Copyright © 2004 John Wiley & Sons, Ltd.
- 1 June 2004
- Published by Wiley in System Dynamics Review
- Vol. 20 (2) , 163-178
Models for management of wildlife populations: lessons from spectacled bears in zoos and grizzly bears in Yellowstone
Models of population dynamics are frequently used in the management and conservation of wildlife populations. They provide a powerful method of quantitatively assessing a population's risk of decline and determining the potential to reverse the decline. Models from recent studies of managed populations are presented. The first model simulates the spectacled bear populations maintained in American Zoo and Aquarium Association (AZA) zoos. The second model simulates the grizzly bear population in the Greater Yellowstone Ecosystem (GYE). The article concludes with a discussion of system dynamics modeling in the larger context of population dynamics modeling. Copyright © 2004 John Wiley & Sons, Ltd.
- 1 July 1996
- Published by SAGE Publications in SIMULATION
- Vol. 67 (1) , 66-72
Simulation in the Service of Society
This month, in line with our policy of sometimes publishing information on work planned, or in progress, rather than "carved in stone," we present the first part of QUEST, an article which we received from Dave Biggs of SDRI, University of British Columbia. Note that this project is one that is still in the development stage, and the authors invite suggestions and comments from readers. It is believed that such feedback can be more helpful now than later.
- 1 July 1996
- Published by SAGE Publications in SIMULATION
- Vol. 67 (1) , 66-72
Simulation in the Service of Society
This month, in line with our policy of sometimes publishing information on work planned, or in progress, rather than "carved in stone," we present the first part of QUEST, an article which we received from Dave Biggs of SDRI, University of British Columbia. Note that this project is one that is still in the development stage, and the authors invite suggestions and comments from readers. It is believed that such feedback can be more helpful now than later.