Simulation with AnyLogic/System Dynamics/Step 7. Adding auxiliaries

Step 7. Adding Auxiliaries We need to add two auxiliaries representing adoptions resulting from word of mouth and from advertising. File:Step_1._Creating_a_new_model1.gif‎ Create the AdoptionFromAd auxiliary Drag the Flow Aux Variable File:Step 7. Adding auxiliaries 1.gif element from the System Dynamics page of the Palette view onto the diagram of active object class (right to the place where you want to locate a variable). In the Properties view, change the Name to AdoptionFromAd. Define the formula expression. In the AdoptionFromAd = edit box, type: AdEffectiveness*PotentialAdoptersFile:Step 7. Adding auxiliaries 2.png File:Step_1._Creating_a_new_model1.gif‎ Create the AdoptionFromWOM auxiliary Do it in the same way except name the auxiliary AdoptionFromWOM and specify the following formula: ContactRate*AdoptionFraction*PotentialAdopters*Adopters/TotalPopulation File:Step 7. Adding auxiliaries 3.png Now we can formulate the adoption flow using just defined auxiliares. The two sources of adoption are assumed to be independent. Thus, the total adoption rate is the sum of adoptions resulting from word of mouth driven by the population of adopters and adoptions resulting from advertising. File:Step_1._Creating_a_new_model1.gif‎ Define the formula for the adoption rate Click the just created flow variable on the diagram. Go to the General page of the Properties view. Specify the formula expression in the AdoptionRate = field: AdoptionFromAd+AdoptionFromWOM File:Step 7. Adding auxiliaries 4.png Now we have completely defined our model. The stock and flow diagram of the model should look like as on the figure below. File:Step 7. Adding auxiliaries 5.png You may examine the causal dependencies between stocks, flows and auxiliaries in your model. They are denoted with arrows as in standard SD notation. A thick arrow going from flow to stock means that this flow acts as inflow for this stock. A thick arrow going from stock to flow means that this flow acts as outflow. A thin arrow going from A variable to B means that A causes to change B. You can see that our model has one balancing and one reinforcing feedback loop. A balancing feedback loop affects the adoption rate due to advertising. The adoption rate reduces the pool of the potential adopters, which in turn decreases the adoption rate. A reinforcing loop affects the adoption rate due to word of mouth. The adoption rate increases the adopter population, resulting in an increase of word of mouth, and thus the increase of the adoption rate.