Exploring Balancing Loops and Leverage Points in System Dynamics for Ride Sharing Services
Creating or evaluating systems is a difficult and a tedious task. This is the case because the behaviours and the impacts of a system depend on how carefully the variables were chosen and framed to be analyzed. Thoughtful decisions for the variables are important because one variable can possess multiple dimensions, dependencies, behaviours, and unanticipated impacts in reflection to its network. The variables can also suggest hidden biases and surface unpredictability.
In order to define a system correctly, Rivera shares an approach for tackling certain technological systems: To exploit the sustainability potential of ICT and not become worse off, long-term and far reaching systemic effects, which might be unintended and unforeseen, need to be addressed. Interactions between ICT and economic, ecological and social systems may be complex, but must be considered and assessed to a larger extent and environmental assessment methods need to encompass such complexity. (Rivera, 105, 106).
To simplify this concept, two cause and loop methodologies can be used to analyze the relationships of the variables. One is called the “Reinforcing Loop”, where it illustrates growth, amplify deviations, and reinforce change (Sterman, 109). Another is called the “Balancing Loop” where it seeks balance, equilibrium and stasis. They act to bring the state of the system in line with a goal or desired state. (Sterman, 111).
In the previous assignment, I defined two reinforcing loops from exploring how services like Uber and Lyft are affecting Toronto’s public transportation usage leading to higher traffic congestions. Through research: as ride sharing services and usages increase, it is likely that users will receive ride discounts from the services, which will enable users to continue using the applications. This will cause a decrease in public transportation usage, yielding the transportation fare to increase to fill the gap to support any expense discrepancies. To reinforce this cycle, more users will turn to Uber and Lyft because in the end, they’re looking to save time and money.
Next Steps
“After identifying positive (reinforcing) loops potentially responsible for observed growth, you should ask what negative (balancing) loops might stop the growth” (Sterman, 117)
In order to mitigate the negative impacts of the reinforcing loop, which variables or leveraging points [places within a complex system (a corporation, an economy, a living body, a city, an ecosystem) where a small shift in one thing can produce big changes in everything - Meadows] can be identified to help balance? Furthermore, what rebound effects are present to uncover the consequences?
Notes on Rebound Effects:
In economics, the rebound effect most commonly refers to behavioural or other systemic responses to the introduction of new technologies that increase the efficiency of resource use. These responses tend to offset the beneficial effects of the new technologies/measures (Rivera, 107).
First order effects are a direct consequence of a particular activity (Rivera, 107).
Direct economic rebound effects occur when improved resource efficiency for a particular service/product using this resource decreases the effective price of the service/product and therefore leads to an increase in its consumption (Rivera, 108).
Indirect economic rebound effects occur when savings accrued due to the introduction of a more efficient technology decrease the price of a specific product (service), which in turn increases demand and/ or expenditure for other goods and services that also require re- sources to provide (Maxwell et al., 2011).
New findings will be shared through Assignment 2.
References
Börjesson Rivera, M., Håkansson, C., Svenfelt, Å., & Finnveden, G. “Including second order effects in environmental assessments of ICT. Environmental Modelling & Software”, 2014, pp 105,106, https://doi.org/10.1016/j.envsoft.2014.02.005
Sterman, John D. “Business Dynamics: Systems Thinking and Modeling for a Complex World”, Irwin McGraw-Hill, 2000, pp 109, 111.
Meadows, Donella H. “Leverage Points: Places to Intervene in a System”, http://donellameadows.org/archives/leverage-points-places-to-intervene-in-a-system/
