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Model Name: payments, penalties, and environmental ethic
Citation: Dudley, R. 2007. Payments, penalties, payouts, and environmental ethics: a system dynamics examination Sustainability: Science, Practice, & Policy 3(2):24-35. http://ejournal.nbii.org/archives/vol3iss2/0706-013.dudley.html.
Source: Richard G. Dudley
Copyright: Richard G. Dudley (2007)
License: Gnu GPL
Peer reviewed: Yes (probably when submitted for publication?)
Units balance: Yes
Target audience: People interested in the concept of payments for environmental services as a means of improving land use and conservation of natural resources.
Questions answered: How might land users’ environmental ethic be influenced by, and influence, payments for environmental services.
Models in the Special Issue of the System Dynamics Review on Environmental and Resource Systems, Andrew Ford & Robert Cavana, Editors. System Dynamics Review, Volume 20, Number 2, Summer of 2004.
- Modeling the Effects of a Log Export Ban in Indonesia by Richard G. Dudley
- The Dynamics of Water Scarcity in Irrigated Landscapes: Mazarron and Aguilas in South-eastern Spain by Julia Martinez Fernandez & Angel Esteve Selma
- Misperceptions of Basic Dynamics: The Case of Renewable Resource Management by Erling Moxnes
- Models for Management of Wildlife Populations: Lessons from Spectacle Bears in Zoos and Gizzly Bears in Yellowstone by Lisa Faust, Rosemary Jackson, Andrew Ford, Joanne Earnhardt and Steven Thompson
- Modeling a Blue-Green Algae Bloom by Steven Arquitt & Ron Johnstone
See the following web site for article summaries and downloadable models described in this special issue: http://www.wsu.edu/~forda/SIOpen.html
Submitted by Richard Dudley, 23 April 2008
This is a little experimental model that I developed to investigate stochastic allocation of rental cars, in response to a Vensim forum question.
There’s a single fleet of rental cars distributed around 50 cities, connected by a random distance matrix (probably not physically realizable on a 2D manifold, but good enough for test purposes). In each city, customers arrive at random, rent a car if available, and return it locally or in another city. Along the way, the dawdle a bit, so returns are essentially a 2nd order delay of rentals: a combination of transit time and idle time.
The two interesting features here are:
- Proper use of Poisson arrivals within each time step, so that car flows are dimensionally consistent and preserve the integer constraint (no fractional cars)
- Use of Vensim’s ALLOC_P/MARKETP functions to constrain rentals when car availability is low. The usual approach, setting actual = MIN(desired, available/TIME STEP), doesn’t work because available is subscripted by 50 cities, while desired has 50 x 50 origin-destination pairs. Therefore the constrained allocation could result in fractional cars. The alternative approach is to set up a randomized first-come, first-served queue, so that any shortfall preserves the integer constraint.
The interesting experiment with this model is to lower the fleet until it becomes a constraint (at around 10,000 cars).
Documentation is sparse, but units balance.
Requires an advanced Vensim version (for arrays) or the free Model Reader.
Update, with improved distribution choice and smaller array dimensions for convenience:
The first major model (Chapter 15) from Forrester’s classic Industrial Dynamics (1961), an SD must-read. Replicated by Tom Fiddaman.
IDch15 (Vensim .vmf & auxiliary files)
IDch15 (Vensim .vpm)
This is an implementation of the logistic model – a very simple example of discrete time chaotic behavior. It’s sometimes used to illustrate chaotic dynamics of insect populations.
There’s a nice description here, and the other top links on google tend to be good.
Note that this version corrects an equation error in previous versions.
Logistic (Vensim .vpm)
Logistic (Vensim .vmf)
Replicated by: Tom Fiddaman
Citation: Hatlebakk, Magnus, & Moxnes, Erling (1992). Misperceptions and Mismanagement of the Greenhouse Effect? The Simulation Model . Report # CMR-92-A30009, December). Christian Michelsen Research.
This is a climate-economy model, of about the same scale and vintage as Nordhaus’ original DICE model. It’s more interesting in some respects, because it includes path-dependent reversible and irreversible emissions reductions. As I recall, the original also had some stochastic elements, not active here. This version has no units; hopefully I can get an improved version online at some point.
Heat trap (Vensim .vmf)
Population sector extracted from the World3 model.
Documented in Dynamics of Growth in a Finite World, by Dennis L. Meadows, William W. Behrens III, Donella H. Meadows, Roger F. Naill, Jorgen Randers, and Erich K.O. Zahn. 1974 ISBN 0-9600294-4-3 . See also Limits to Growth, The 30-Year Update, by Dennis Meadows and Eric Tapley. ISBN 1-931498-85-7 .
See my article at The other bathtubs – population
World3-Population (Vensim .vpm)
World3-Population (Vensim .mdl)
World3-Population (Vensim .vmf)
Citation: Jeppe Sturis, Kenneth S. Polonsky, Erik Mokilde, and Eve van Cauter. Computer Model for Mechanisms Underlying Ultradian Oscillations of Insulin and Glucose. Am. J. Physiol. 260 (Endocrinol. Metab. 23): E801-E809, 1991.
Source: Replicated by Hank Taylor
Ultradian Oscillations of Insulin and Glucose (Vensim .vpm)
Refreshed, with units defined (mathematically the same as before): ultradia2.vpm ultradia2.mdl
Further refined, for initialization in equilibrium (insulin by analytic expression; glucose by parameter). Glucose infusion turned on by default. Graphs added.
Model Name: A Behavioral Analysis of Learning Curve Strategy
Citation: A Behavioral Analysis of Learning Curve Strategy, John D. Sterman and Rebecca Henderson, Sloan School of Management, MIT and Eric D. Beinhocker and Lee I. Newman, McKinsey and Company.
Neoclassical models of strategic behavior have yielded many insights into competitive behavior, despite the fact that they often rely on a number of assumptions-including instantaneous market clearing and perfect foresight-that have been called into question by a broad range of research. Researchers generally argue that these assumptions are “good enough” to predict an industry’s probable equilibria, and that disequilibrium adjustments and bounded rationality have limited competitive implications. Here we focus on the case of strategy in the presence of increasing returns to highlight how relaxing these two assumptions can lead to outcomes quite different from those predicted by standard neoclassical models. Prior research suggests that in the presence of increasing returns, tight appropriability and accommodating rivals, in some circumstances early entrants can achieve sustained competitive advantage by pursuing Get Big Fast (GBF) strategies: rapidly expanding capacity and cutting prices to gain market share advantage and exploit positive feedbacks faster than their rivals. Using a simulation of the duopoly case we show that when the industry moves slowly compared to capacity adjustment delays, boundedly rational firms find their way to the equilibria predicted by conventional models. However, when market dynamics are rapid relative to capacity adjustment, forecasting errors lead to excess capacity, overwhelming the advantage conferred by increasing returns. Our results highlight the risks of ignoring the role of disequilibrium dynamics and bounded rationality in shaping competitive outcomes, and demonstrate how both can be incorporated into strategic analysis to form a dynamic, behavioral game theory amenable to rigorous analysis.
The original paper is on Archive.org ; it was eventually published in Management Science. You can get the MS version from John Sterman’s page here.
Source: Replicated by Tom Fiddaman
Units balance: Yes
Format: Vensim (the model uses subscripts, so it requires Pro, DSS, or Model Reader)
Behavioral Analysis of Learning Curve Strategy (Vensim .vmf)
Model Name: World Dynamics
Citation: Jay W. Forrester (1971) World Dynamics. Cambridge, MA: Wright-Allen Press
Source: Standard Vensim distribution
Units balance: Yes
World Dynamics (Vensim .vmf)