The case for taking action to tackle climate change is persuasive. Housing is a focal sector for climate change policies, but we know that housing and energy-efficiency policies may cause unintended consequences in the built-environment and beyond (Shrubsole et al. 2014). Allocating funds to address energy efficiency, the community and industry is a complex task.
Improve your systems thinking capabilities and test the outcome of different policy options with an interactive simulation environment. Through work with our large group of interdisciplinary stakeholders, we identified relationships in the socio-technical realm of the built environment. The resulting model represents a working hypothesis of these interactions and provides decision-makers with a tool to test their assumptions and for discussion. The model is built in Systo, a toolkit for incorporating live System Dynamics modelling into web pages.
You may allocate investments in different policy areas and view the impacts on a variety of indicators elated to energy efficiency, communal spaces and quality control and their effect on efficiency, performance and wellbeing indicators. These indicators were developed during previous Housing, Energy and Wellbeing project work. You will receive feedback instantaneously regarding the effects of you investments. Invariably, your actions can result in a multitude of both intended and unintended effects.
As your familiarity with the model grows, you can test your assumptions by viewing the model diagram and can even change its assumptions by modifying its parameters. The high level of transparency of the model motivates improvement in group process. Be forewarned, your individual viewpoints may be challenged. However, the model is intended to aid in constructive group discussions. Don't hesitate to tell us about your experience by email.
We hope you come away with a better understanding of the complexity that characterizes the built environment by observing the dynamics of the system, and that it helps you to make 'wise' decisions in the future.
You are governmental policy-maker with experience in the built environment and are asked for a strategy for the allocation of the long-term built environment budget. In particular, you are asked about how certain investments can improve the performance of London's mixed housing area. Your task is to determine the long-term allocation of an investment fund (10,000 monetary units per year) that will support policies in three different domains. The three different policy areas are: energy efficiency, communal spaces and monitoring.
|Investment in energy efficiency
By investing in energy efficiency you are supporting measures intended to reduce energy usage in buildings. This may take the form of subsidizing new technologies, promoting the benefits of retrofitting to encourage residents to invest and much more.
|Investment in communal spaces
Investments in communal spaces are directed towards adding or improving communal areas that can be accessed by residents. Examples of communal spaces are green spaces, pubs, cafes, recreational facilities, community hubs and more.
|Investment in monitoring
Investments in monitoring are supportive of policies aimed towards collecting information about the performance of the built environment and implementing a spirit of accountability among architects, builders and developers.
Under the simulate heading you will see five graphs. Each graph contains an indicator representing several of the important policy criteria that have developed from previous HEW project work. (For more on this see the menu at the top of this page).
All indicators are highly aggregated in order to deliver a holistic point-of-view. The concepts associated with each of the indicators are given below.
Average Energy Efficiency Performance: This relates to the energy efficiency coming from the housing stock, including old, retrofitted and newly built homes.
Average HEW (Housing, Energy and Wellbeing) Performance of Buildings: How well the built environment meets multiple demands as a comfortable space to live that is affordable to heat/cool and that integrates with the surrounding environment. It covers the concepts of, for instance, thermal comfort, indoor air quality, layout, etc.
Community Connection: The social life and connection at the community level relating to engagement and interest in the local area as well as familiarity and friendliness of residents.
Communal Spaces: These are shared areas where community members can gather. Examples are parks (or green space), recreational areas, pubs, cafes and more.
Wellbeing of Residents: Refers to the mental, physical and emotional health of people in the community.
Use the sliders to select your investment. Remember, the total cannot be more than 10,000 monetary units!!!
Each simulation run is shown with a different colour. Runs can be stored using the buttons below.
Units for communal spaces are given in acres. All other indicators use a scale from zero to one (corresponding to 0% - 100%).
Causal loop diagrams are a simplified representation of the main cause-and-effect relationships defined inside the model. This creates feedback loops that can be used to explain model behaviour. There are two kinds of feedback: balancing and reinforcing.
Reinforcing feedback, on its own, often leads to rapid growth of the affected variables. Keep in mind that growth is not always a good thing!
Balancing feedback loops are oriented towards a goal and can limit growth. The interaction between these two types of feedback generates model behaviour over time.
Let's start on the top right of the causal loop diagram (see below).
The model you see below is the 'engine' that computes all the simulations you have tested so far. Its relationships as well as their strength are based on many interviews and three workshops with stakeholders. The model should be regarded as a simplified representation of reality to be used as a platform for discussion. It is composed of three main elements:
To explore the model diagram, you can click and drag in the window to reposition. Buttons on the right side of the diagram allow you to zoom in and out, reset the diagram to the original view or toggle the amount of detail shown. Double clicking on an element opens a window where you can view, and even change the equations numerically.
These scroll-down panels allow you to dig deeper into the model assumptions and perform more detailed scenario testing. As you get comfortable with the model and its elements, test your thinking by adjusting the initial levels of stocks or changing the value of parameters. It is a good idea to consider what you expect to happen before you make a change. Question the result, does it make sense?
Start with Wellbeing of Residents – See that the net change to this stock is influenced by communal spaces, HEW performance and community connection. The strength of each effect is determined by a weight that our stakeholders collectively attributed to it at a workshop.
Modify the weights, ensuring that they sum to 1, and view the behaviour in the graphs above!
What is the purpose of this simulation environment?
This model and simulation environment were developed through a series of three workshops with industry, community and policy stakeholders that focused on building consensus among these stakeholders. The model and its behaviour serve as a focal point for discussion and, as participants critically evaluate the assumptions and simulation results produced by the model, they are simultaneously forced to evaluate their own "mental model" of how the system works. As a result, individual views can be better understood and discussed by the group, which can lead to more integrated planning among stakeholders in the built environment.
This model does not include all the details I expected, how can I be confident in the simulation results?
All models are representations of reality. For example, a paper airplane does not contain any of the detailed controls of 747, nor can it carry passengers across the Atlantic. However it is a useful tool to teach us about the physics governing flight.
WISE is similar to this example. As it is a simplified representation of our stakeholder's understanding regarding the complex built environment, it cannot provide precise forecasting for housing demand or household energy use. However, it is a useful tool to improve our understanding about the interactions between social and technical aspects of housing.
The model behind this interactive simulation environment is derived from a larger model that captures more detailed links between housing, energy and wellbeing. This larger model is based on the information collected from stakeholders in the three group model building workshops. Therefore, the causal mechanisms behind the model represent the expert knowledge in these areas. Furthermore, the model is quantified by using the data provided in extensive governmental databases such as the English Housing Survey. Yet, even the larger model is meant to be far from complete and also a tool to test our assumptions and learn about the complex interactions rather than to make point predictions.
To learn more about this large model, look at the Workshop 4 area on the HEW website. You can check back as publications will be made available under Output.
How is the model implemented?
The model is implemented using the Systo toolkit. Systo makes it easy to incorporate interactive System Dynamics models into a web page, so that visitors to the page can view and edit the model diagram, its parameters and equations, and see how the simulation results respond as they change input values.
This model was actually built using Vensim then converted into Systo format, but it is possible (and more common) to build the model directly in Systo itself, using for example SystoLite.