system dynamics models: mcqs iv

Small System Dynamics Models

forBig Issues

Triple Jump towards Real-World Dynamic Complexity

Erik Pruyt

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Chapter 15

MCQs Part IV

‘Cessante causa cessat effectus.’ Sallustius

Which of the following statements are right and which are wrong?

1. The result of a sensitivity analysis includes information on the response of the model to alarge number of small changes to uncertain parameters.

2. The only real goal of sensitivity analysis is to find parameters with high leverage.

3. The most valid SD model is the one which produces better point predictions.

4. The choice of integration method and step size always needs to be checked.

5. Any SD model that accurately replicates historical data is always valid.

6. A system that is not sensitive to perturbations by exogenous variables, is in equilibrium.

7. A model that is not sensitive to small parameter changes is better than a model that issensitive to small parameter changes.

8. SD models are almost always numerically sensitive to parameter changes, but that is notsurprising and is not of much interest to system dynamicists.

9. One should also test the sensitivity of SD models to changes in equations of soft variables,table functions, structures and boundaries.

10. If a variable cannot be influenced by the decision-maker (that is, if it is not a policy lever),then behavior mode sensitivity to changes in that variable is desirable.

11. Sensitivity analysis could be used to study whether changes in parameters and structureslead to changes in modes of behavior and/or (relative) performance of policies.

12. SD validation is really all about checking whether SD models provide the right outputbehaviors for the right reasons.

13. Direct structure and structure-oriented behavior tests are used to find erroneous behavior.

14. If your software shows no errors regarding units, this means your dimensional analysis iscompleted and the model is good.

15. SD model testing should be designed to prove models are right, which makes falsificationpossible and, hence, adds to the credibility of models and modeler.

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c⃝ 2013 by Erik Pruyt STEP: MCQs Part IV

Multiple Choice Question 1

Consider the model about the exodus of a social housing district due to the social cohesion (exercise14.14 on page 182) displayed above. Simulation of the SD model leads –even for very differentvalues of the parameters in orange (see 100 very different runs in the graph)– to inverse S-shapedbehavior of the original population. Which of the following aggregated CLDs is the best diagramto communicate the essential link between structure and behavior of this model?

(a) (b)

(c) (d)

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STEP: MCQs Part IV c⃝ 2013 by Erik Pruyt


Given are two technology transition models. Suppose that all parameters and initial values > 0.Which of the following behaviors fit the variable ‘sustainable technology ’ of models (a) & (b)?

(a) (b)

a. (1) fits model (a);(2) fits model (b).

b. (2) fits model (a);(1) fits model (b).

c. (3) fits model (a);(4) fits model (b).

d. (4) fits model (a);(3) fits model (b).


Consider the symbolic representation of asubmodel of a larger bluefin tuna fisheriesmodel. Which of the following equationscould describe its behavior over time?

a. dTdt =

(r+ g − eS− T

O/l)∗T

b. dT =(r+ g − eS− T

O/l)∗T

c. T =(r+ g − eS− T

O/l)∗T ∗ t

d. −dTdt = −

(r ∗ g + eS− T

O/l)∗T

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(a) tons of tuna (b) tuna ships

The trajectories in the graphs are obtained by testing the sensitivity of the bluefin tuna model withthe existing policy to changes in parameters and uncertain functions. What could be concluded?

a. The model is both numerically sensitive and policy sensitive

b. The model is behavior mode sensitive, but not numerically sensitive

c. The model is numerically sensitive, but not behavior mode sensitive

d. The model is numerically sensitive, but not policy sensitive


Suppose that you are hired by the RIVM (the Dutch environmental agency) to model the epidemicoutbreak of a new flu strand (actually just discovered). The RIVM estimates it will take about6 to 9 months to develop and mass-produce a new vaccine. The simulation runs of the infectedfraction give an indication of the sensitivity of the model to small changes in the variable averagecontact rate. Which of the following statements is not correct?

a. The rather different behaviors of the infected fraction for slightly different contact ratesindicate that the contact rate may be exploited as a policy until a vaccine has been developed.

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b. The model is numerically and policy sensitive to changes in the average contact rate.

c. The model is not behavior mode sensitive to changes in the average contact rate becausethere are always two flu peaks and the epidemic is always over after 21 months.

d. None of the statements above is correct.


Consider the simulation model below concerning a manufacturing company you may have made.Each final product assembled in the assembly line requires 2 components from the component line.

Simulation of this model generates the behavior displayed above. Which of the statementsbelow concerning the model and the corresponding behavior is correct?

a. Although the structure and specification of the model are wrong, the behavior generatedwith it are plausible and realistic.

b. This behavior is impossible. It must be caused by a numeric integration error, i.e. aninadequate combination of integration method and time step.

c. The model was modeled in a non-protective manner in view of learning from it and designingpolicies to prevent undesirable (and impossible) dynamics from happening.

d. None of the statements above is correct

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Small variations in two parameters –the ‘immigration time’ (the time necessary to attract newimmigrants) and the ‘construction time’ (the time necessary to develop new real estate)– in aSD simulation model concerning the possible real estate bust in Dubai gives the graphs above.The (relatively small) shock in month 10 corresponds to the announcement of the suspension ofpayments by Dubai World. Both the ‘immigration time’ and the ‘construction time’ are to someextent policy variables. The number of ‘immigrants’ for immigration times of 1, 2, and 3 monthsare displayed in the left hand side graph. The number of ‘immigrants’ for construction times of1, 2, 3, 4, and 5 months is displayed in the right hand side graph (note the detailed graph in theframe). The immigration time could be influenced by policy makers. What could be concludedfrom this sensitivity analysis?

a. For the changes above, the number of ‘immigrants’ in the model is numerically sensitive,but not behaviorally nor policy sensitive.

b. For the changes above, the number of ‘immigrants’ in the model is numerically and behav-iorally sensitive, but not policy sensitive.

c. For the changes above, the number of ‘immigrants’ in the model is numerically and behav-iorally and policy sensitive.

d. None of the previous answers is correct.


Which of the following statements about validation is wrong?

a. System Dynamics validation is about checking whether a System Dynamics model providesthe right output behavior for the right reasons.

b. Direct structure tests are used to find erroneous structures, not erroneous behaviors. Andstructure-oriented behavior tests are used to find erroneous behaviors, not structures.

c. Sensitivity analysis could be used to study whether small changes in parameters and struc-tures lead to changes in modes of behavior and/or policies.

d. A System Dynamics model that replicates historical data is not necessarily valid.

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The graph displayed above shows the behavior of a model about the sudden illegalization of thesupply of prostitution (Demand for prostitution (green), supply of prostitution (red), and the price(blue)). Which of the following statements regarding the formulation of this policy is correct? Thestock of prostitutes can be emptied overnight in this model with:

a. a pulse function b. a pulse train function c. a step function d. a reset function


Consider the flu model comprising a seasonal form of immunity (the green part in the figure dis-played above). The ‘normal immune population fraction’ fluctuates over the course of the year.Suppose that you need to write an equation for the flow variable ‘susceptible to immune popu-lation flow ’. Which of the following formulations is most appropriate for this SD simulation model?

a. IF THEN ELSE(

normal immune population−immune populationsusceptible to immune population time delay < 0,

MIN(normal immune population−immune populationsusceptible to immune population time delay , susceptible population

susceptible to immune population time delay ),

MIN(normal immune population−immune populationsusceptible to immune population time delay , immune population

susceptible to immune population time delay ))

b. MAX(MIN(normal immune population−immune population

susceptible to immune population time delay ,

susceptible populationsusceptible to immune population time delay ),

−immune populationsusceptible to immune population time delay

)

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c. MIN(MIN(normal immune population−immune population




)d. MIN

(MAX(normal immune population−immune population




)Multiple Choice Question 11

The runs displayed below were generated with the SD simulation model next to it: what is wrong?

a. The parameter values: such wrong behaviors are often caused by wrong parameter values.

b. The model equations: the flows should have been specified as non-negative flows.

c. The combination of integration method and time step: this is a numeric integration error.

d. Nothing is wrong. If that is the model that generated this output, then it simply is the rightmodel behavior.


Consider the (slightly aggregated and simplified) stock-flow diagram concerning the cholera epi-demic in Zimbabwe (2008-2009) which you may have modeled and simulated (ex.14.9 on p171).

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How many feedback loops do you need in an extremely aggregated CLD in order to respect thestructure and the dynamics of the simulation model above?

a. 1 feedback loop b. 2 feedback loops c. 7 feedback loops d. None of the previous answers


What is the minimum number of independent feedback loops in the following simulation modelon overfishing of bluefin tuna?

a. 1 feedback loop b. 5 feedback loops c. 6 feedback loops d. 7 feedback loops


Suppose you are a professor at a faculty that depends on a fixed monthly teaching fee and a fixedamount of money earned per publication and has a policy to hire as many professors as possibleas long as the (roll-over) cash reserves remain positive and stable. Your dean asks you to make aSD simulation model about the dynamics of a faculty to explore plausible futures of the system.

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Your model, of which the incomplete CLD is displayed on the left, generates growth, overshoot,damped oscillations and, after a while, convergence to an equilibrium, both in terms of the numberof professors (blue) and the cash reserves (red). The ambitious dean finds the limits to growthunacceptable and asks you to identify policy levers that will change the developmental path of thefaculty in line with his expansionary desires. Based on this CLD (and possibly your experiencewith a simulation model like this), what would you advise the dean?

a. Reduce the average salary per professor!

b. Increase the average salary per professor!

c. Create the conditions for professors to publish more.

d. In the long term, nothing will help: this system will always converge to the same equilibrium.


What is wrong with the SD model about the police fight against burglaries (HB) displayed above?

a. One of the loop does not have at least one stock variable, hence, there are simultaneousequations.

b. The police response seems to be reactive instead of proactive.

c. The simulation model is not endogenous enough: the seasonality of the percentage of houseswith opportunities for burglary should have been modeled endogenously.

d. Nothing seems to be wrong with this simulation model nor with the situation it represents.


A quick sensitivity analysis on a model about de/radicalization generates only two types of be-havior (see left figure below): either radicalization or deradicalization. A ‘brute force’ uncertaintyanalysis confirms this conclusion: this model only generates these two modes of behavior evenwith 10000 runs and enormous uncertainty bands. Further analysis shows that a particular set of

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counter-intuitive policies with regard to radicalization has –in contrast to other sets of policies– arobust influence on the modes of behavior: this appropriate set of proactive policies should allowto nip undesirable radicalization in the bud, that is to say, it does in the model. What do youconclude with regards to the sensitivity?

(a) deradicalization (red) versus radicalization (blue)

1940 1960 1980 2000 2020 2040 2060 2080 21000.0

0.2

0.4

0.6

0.8

1.0

(b) radical action level (uncertainty analysis with10000 runs)

a. Real-world de/radicalization is behaviorally –not policy– sensitive for these policies.

b. Real-world de/radicalization is behaviorally and policy sensitive for these policies.

c. This de/radicalization model is behaviorally –not policy– sensitive for these policies.

d. This de/radicalization model is behaviorally and policy sensitive for these policies.


Which of the following graphs cannot be generated with the modelon the right. (Note that equations and parameters are unknown andthat it is not known whether X or Y are displayed in these graphs.)

a. Only i b. Only ii c. Only iii d. Either none or all

(a) i (b) ii (c) iii

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(d) Debt (e) Production Plants

The graphs above display 20 simulations of the amount of debt over time and the number ofproduction plants over time with the Debt Crisis model for variations of their initial conditions(initial production plants between 0 and 200, initial debt between 0 and 2000, latin hypercubesampling). Which of the following state space diagrams developed with the structure and modelsdeveloped by Hartmut Bossel (2007a, Z115) corresponds to the above behaviors over time graphs?

(a) (b)

(c) (d)


The unfinished and overly detailed CLD concerning the potential long term effects of choleraoutbreaks displayed below is hardly communicable. Which of the aggregated CLDs correspondsbest with the underlying simulation model and allows to communicate about potential short termas well as long term effects?

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(a) (b)

(c) (d)

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Which statement regarding the simulation model about the consequences of the growing demandfor lithium from the ICT and electrical vehicles sectors fully displayed above is most correct?

a. The submodel in blue is an inherently limited diffusion structure. Due to these inherentlimits, lithium will never be overexploited by electrical vehicle diffusion.

b. Although for a constant positive growth rate of lithium demand from the ICT sector, thesubmodel in green will first generate exponential growth of the annual ICT lithium demand,although, in the end, growth of the annual ICT lithium demand is likely to be constrainedin this model by the limits to lithium exploitation.

c. Loop-wise this model is incomplete: important loops, such as the ones connecting lithiumavailability to the electrification of the vehicle fleet and growth of the lithium-based ICTsector, are missing.

d. Unexploited lithium reserves and resources should not be modeled as a limited non-renewablestock: the different reserves and resources should be modeled in detail.

Link to the answers to the 15 right/wrong questions & 20 multiple choice questions in this chapter.

Links to web based quizzes: | | | |

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Flexible E-Book for Blended Learning with Online Materials

Although this e-book is first and foremost an electronic case book, it is much more than justa set of case descriptions: it is the backbone of an online blended-learning approach. It consistsof 6 concise theory chapters, short theory videos, 6 chapters with about 90 modeling exercisesand cases, many demo and feedback videos, feedback sheets for each case, 5 overall chapters withfeedback, 5 chapters with multiple choice questions (with graphs or figures), hundreds of onlinemultiple choice questions, links to on-site lectures, past exams, models, online simulators, 126slots for new exercises and cases, and additional materials for lecturers (slides, exams, new cases).The fully hyperlinked e-version allows students (or anybody else for that matter) to learn –in arelatively short time– how to build SD models of dynamically complex issues, simulate and analyzethem, and use them to design adaptive policies and test their robustness.

ISBN paperback version:

ISBN e-book version:

system dynamics models: mcqs iv

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