Lecture F1 (2022-03-31): Chapter 8, Industry Dynamics – Oil Price and the Global Oil Producers (Morecroft, 2015)

In this lecture, we discuss highlights of Chapter 8 from Morecroft (2015) on the industry dynamics linking oil price to global oil producers, with a particular focus on the effect of OPEC (Organization of Petroleum Exporting Countries) and independent producers. The goal is to explain patterns of subtle oscillations, relative stability, and massive fluctuations in the market over time. The model starts with a basic negative feedback model of a free-market economy and then adds a component related to OPEC's cartel influence (the effect of a swing producer in a cartel) and even the eventual addition of Russian oil reserves after the breakdown of the Soviet Union/USSR. System dynamics models help provide insight into the less observable latent variables that are necessary to explain otherwise puzzling patterns in behavior over time.

Lecture E5 (2022-03-24): SOS 212 Assignment E5 – Creating Limited, Coupled Population Models

This lecture provides assistance and introduction to the final two homework assignments in SOS 212. We start with some tips about Assignment E2 (a Vensim PLE/Insight Maker assignment that makes use of sliders, units, and delays). We then discuss Assignment E5 (which is a two-sector model of a coupled population/water dynamics system). The class ends early for students to do work on the assignments during the class period.

Lecture E4 (2022-03-22): Chapter 6, The Dynamics of Growth and Diffusion (Morecroft, 2015)

In this lecture, we cover highlights of Chapter 6 (Dynamics of Growth and Diffusion) from Morecroft (2015). This chapter focuses on S-shaped growth in consumer markets (and innovation diffusion in general), and it uses the Bass diffusion model (with advertising) as a central dynamical hypothesis. We draw connections between the contagion in the Bass model to limiting processes in simple logistic growth models as well as the infection part of the SIR model. After showing variants of the Bass model for the cases of repeat purchases and durable goods, we move on to a scenario planning/strategic thinking example for the case of easyJet (a low-cost air carrier).

Lecture E3 (2022-03-17): Epidemic Dynamics

In this lecture, we introduce the use of System Dynamics Modeling (particularly, stock-and-flow simulation models) to the analysis of the spread of infectious disease. We focus our investigation around the SIR   (Susceptible–Infectious–Recovered) model from epidemiology. We build up the SIR model from scratch (using a stock-and-flow model) and derive the basic reproduction number (R0) and discuss how quarantines are most practical for "flattening the curve" (the infection peak) and not totally stopping the spread of disease. We close with an introduction to other compartmental infectious disease models, such as SIS, SIRS, SEIR, SEIRS, MSEIR, and MSEIRS.

Lecture E2 (2022-03-15): Making Simulations More Realistic, Part 2 – Delays, Fixed and Smoothing

In this lecture, we discuss how to implement two types of delays (fixed delays and smoothing delays) in stock-and-flow diagram dynamical systems models using two System Dynamics Modeling tools – Vensim PLE (by Ventana Systems) and Insight Maker. Along with covering fixed delays and smoothing delays, we also introduce higher-order smoothing delays (which are a type of delay in between the two other purer forms of delays) and some functions for perturbing systems (pulses and steps).

Lecture E1 (2022-03-03): Making Simulations More Realistic, Part 1 – Units, Sliders, and Lookup-Table Converters

In this lecture, we introduce Units, Sliders, and Lookup-Table Converters in both Vensim PLE (by Ventana Systems) and Insight Maker. This also allows us to introduce shadow variables in Vensim (and access "Time" in both Vensim and Insight Maker). These constructs help us make more realistic simulations or help make interacting with simulations more convenient.