A Simulation Model to explore Community Dynamics based on Resources and Quality of Space
Jeffery Jonathan Joshua (ישוע) Davis and Florian Schübeler
The Embassy of Peace, Whitianga, New Zealand
joshua_888@yahoo.com, florian@theembassyofpeace.com
In this paper we present a model that explores the dynamics of a small community where soft variables like quality of space, understood as the spirit and the atmosphere of the community, become very relevant, even more than resource availability. We aim at providing new tools and mental models in order to study and analyse more complex community dynamics. For this study we developed a simulation model based on a larger system dynamics model that we previously designed to describe the dynamics of an economy based on actions of kindness (Schübeler et al., 2018). Here we explore different scenarios in a horizon of four (4) years. We conclude that there is a close relationship between the quality of space and the attractiveness of the community for new entries or resignations that will affect the number of people in the community, at different times with different delays. These results reflect the personal and subjective experience of the active participants of The Embassy of Peace, which share the views of the authors. We conjecture that the model will be a useful tool to support the design of desired futures for types of communities, such as, the one at The Embassy of Peace.
INTRODUCTION
It is well known that people learn by experience. However, learning by experience can sometimes be too costly and painful, particularly when one only has one chance to make it happen in life. Many people start communities, such as ashrams or learning centres, which often collapse because, when their visionaries or leaders left, they did so without sharing the legacy and the proper understanding of the complexities about community dynamics. Apart from the leaders' spiritual wisdom and skills, a proper storytelling based on causal feedback loops and simulation models may serve the purpose of passing on to the next generation a certain level of understanding that together with expertise may contribute to the long-term successful existence of the community. One of the motivations for creating the model presented here is to assist communities with more robust systems knowledge and understanding to enable them to survive existential challenges such as, for example, the departure of key and wise members.
The Embassy of Peace in Whitianga, New Zealand is a learning organisation comprised by a small community of people committed to upholding inner peace and living in harmony with the land and its environment, and whose experience also served the purpose of building the simulation model, also taking into consideration other previous and relevant studies (Schübeler et al., 2018) (Zhuang et al., 2016) (Davis & Schübeler, 2018a) (Davis & Schübeler, 2018). The process of building this community started around the year 1996 with a small number of visionaries who shared inspirations and visions towards a peaceful world that allowed and still allows them to inspire others in sharing this vision with commitment to action. This initial serendipitous set of events brought together, at different times, small groups of people from different nations, cultures and beliefs, who found a gathering place provided by two (2) of the visionaries in 1999. Over a period of about twelve (12) years, the number of people who participated in this endeavour and experience fluctuated between zero (0) and ten (10) per week on average during the year, with numbers fluctuating between fifteen (15) and forty (40) per week in peak season (summer), totalling 3000 visitors during this twelve (12) year period. Since 2011 the core group has stabilised to around ten (10) committed individuals who have pioneered and spent significant amounts of time at The Embassy of Peace in Whitianga in subsequent years. It is important to note that other committed individuals who were part of the community building process and have supported the development of The Embassy of Peace in Whitianga are living in other regions of the planet and are giving continuity to this seminal ideal.
We draw experience and anecdotal evidence from the different dynamics of the community observed over time, such as periods of rapid growth followed by an exodus to return to social life, such as schooling, work and household upkeep. Other equally present modulators of these dynamics included worries about survival needs, other personal dreams and family commitments. Basically, the overshoot and collapse dynamics could be avoided or at least significantly attenuated by more committed people to the vision together with a strong foundation of shared values. However, the community learned that this had to be built and sustained and that this required people with a genuine desire and commitment to participate. Avoiding unwanted dynamics can be achieved by various means and a thorough exploration of some of these community dynamics and how to avoid them can be found in previous work (Schübeler et al., 2018) (Zhuang et al., 2016) (Davis & Schübeler, 2018a). What we have unequivocally concluded is that quality of space is paramount to sustain a healthy community, such as an Embassy of Peace, over and above other factors, such as the availability or scarcity of resources at times.
This phenomenon will be explained with the aid of a simulation model that was programmed with Insight Maker, an online, open source simulation tool.
The model comprises three (3) levels: People, Resources and Quality of Space with associated carrying capacities, which are descriptive of the community dynamics. Other variables such as rates and parameters are included to represent the relationship between resources and people and a comfort quality factor associated with the availability of resources, as well as quantities describing the kind of synergy that influences a new influx of people in the community. It is important to note that this model has been referred to as the "left side" of a larger model in (Schübeler et al., 2018). This paper is the first in a sequence of three (3), where (a) the first paper gives an overview of how to model inner peace, social harmony, community development and actions of kindness and presents the reader with the problem and complexities associated to it, as well as a subsystem simulation model; (b) the second paper in this sequence develops another subsystem simulation model and (c) paper three provides an integrative simulation model of subsystems one (1) and two (2) together with general findings and conclusions. It must be emphasized that the reader should read all three (3) papers in sequence in order to fully understand the theoretical framework and paradigm presented here.
Using this model five (5) different scenarios were simulated, all starting with ten (10) people. In Scenario 1 a simulation of an ideal situation beginning with a high level of resources, a high synergy level and high resource efficiency factor is presented. In Scenario 2 the initial resources and resource efficiency factor were reduced, while maintaining a high quality of synergy. In Scenario 3 the effect of dropping the quality synergy level with a high level of resources and high resource efficiency factor was simulated. In Scenario 4 all initial levels are low and in Scenario 5 all initial levels are very low.
It can be observed that the scenarios match our previous observations and anecdotal evidence based on years of experience and therefore it can be said that the model reflects our experience of reality relatively well. However, these require more simulations, more investigation and the building of a future database with some relevant indicators of the dynamics of the community.
We conclude that models like this can help us, to a large extent, to prevent undesired circumstances and promote desired futures. It is for this purpose, as a learning environment, that the model can be used in the future for prevention and graceful corrections and remedies concerning the design and functioning of intentional communities of this kind.
DESCRIPTION OF THE MODEL
In Figure 1 a system dynamics diagram is introduced that provides the foundation for the simulation model. It describes the dynamics between People, Resources and Quality of Space and how these are modulated by their relationships. In Figure 1 the reader can identify two (2) possible relationships between elements of the system, either a relationship that behaves in the same direction (signed '+'), where if one (1) element increases (or decreases), the other element will also increase (or decrease). The other type of relationship (signed '-') behaves in an opposite direction, where when one (1) element increases (or decreases), the other will decrease (or increase). While Resources and People build a positive (or reinforcing) feedback loop, the relationship between People and Quality of Space describes a negative (or balancing) feedback loop (Meadows, 2008) (Roberts et al., 1996).
The model shown in Figure 1 further identifies other key elements that modulate the behaviour of the system. For example, the Consumption of Resources increases as People and Resources increase and thereby contributes to the increase in Comfort while at the same time the Consumption of Resources contributes to the decrease of Resources. However, it is important to note that the increase in Comfort together with Quality of Space, also contributes to the increase of the Net Quality Factor, which in turn also contributes to the increase of People, and this will in parallel lead to the increase of Resources. The reader must note that on one hand, via one feedback loop, Resources may decrease (or increase) while, via another loop, Resources may increase (or decrease). There are several such positive and negative feedback loops that modulate the system here introduced in our model of the system and for a more in depth description and analysis of the system the reader is referred to our previous work (Schübeler et al., 2018). It is also important to note that any parameter, level or rate in the model when written in italics should be taken to mean a variable of the system, as for example, Comfort, would mean the ‘variable Comfort’.
The focus of this paper is on simulating the behaviour of such a system and therefore the systems diagram in Figure 1 has been translated into the simulation model presented in Figure 2.
Both the systems diagram (Figure 1) and the simulation model (Figure 2) were built with Insight Maker, a free, open source, web-browser based, modelling and simulation tool (Insight Maker, 2017). The software allows for system dynamics and agent based simulation modelling, featuring sensitivity analysis and built-in optimization amongst others. The user can choose between the Euler Method and the 4th Order Runge-Kutte Method as simulation algorithms, where the latter was chosen for our simulations with the appropriate dt=0.02 to guarantee accuracy in the solution of the equations (Roberts et al., 1996).
In order to simulate the dynamics of a community similar to the one introduced in the introduction, a simulation model was developed that evolves around three (3) key levels: (1) People, (2) Resource and (3) Quality of Space (QOS). People accounts for the number of people in the community, Resource for the amount of resources available to the people in the community and QOS for the quality of space that is shared and experienced by the community members, all of them at any given moment in time, t. The two (2) levels People and Resource are both limited by carrying capacities (Meadows et al., 1992) which are set to values of 40 and 100 respectively. The level QOS can vary between zero (0) and a maximum value, where any value above one (1) is considered a very high quality value. Perhaps the reader could imagine that a community of people with the quality of being peace like in the case of John Lennon for example, could set a reasonably high standard of quality of space with value ≈ 1, while a community of people like Sri Aurobindo and Mother Theresa for example, would be represented by a value of ≈ 1.7, a higher quality of space. For values higher than that a community comprised of people like Siddhartha (Buddha) or Yeshua (Jesus) can be imagined, in a maximum high for QOS, living in the peaceful presence of other spiritual and sentient beings like angels and animals, for example.
The system can initially produce higher values than 1 for QOS, which can be interpreted as a catalyst that sets the system dynamics in motion and ignites the growth of the community, as for example with a blessing for the land and the community in an opening ceremony. All three (3) levels have an inflow and an outflow. The level People increases by a rate of people per month, in our model this rate (or flow) is called In. The level People also has a rate connected by which people are leaving the community per month, in our model this flow is called Out. Similarly, the levels Resource and QOS also have inflows determining the rate at which resources and quality enter their respective level per month and outflows, quantifying the rate at which resources are consumed and quality dissipates per month. These flows are called R_In and R_Out connected to Resource and QIn and QOut connected to QOS.
In Figure 2 the connections between those levels and flows and what variables and parameters influence their behaviour can be appreciated. In the following section these variables and parameters will be introduced to the reader.
Here the Quality Rate is introduced, a variable which is directly influenced by the level of People and modulates the in and out flows of the QOS level, where more people result to a lower output of quality (Q) via an s-shaped or sigmoid transfer function (converter) (von Bertalanffy, 2013) (Kyurkchiev & Markov, 2015).
While the inflow to QOS is directly influenced by Quality Rate, the outflow is further modulated by a delay (Delay 1), which is calculated by the conversion of the range of small values of Quality Rate into lower delay values, which in turn contribute to higher values for QOut, meaning a greater outflow of quality from QOS. Basically, this means that for higher values of Quality Rate the delay at which quality flows out from QOS is longer. We propose that more people will tend to contribute to less quality of the community space and hence the transformation via another s-shaped transfer function in the Delay 1. The parameter Q SW 1 acts as a switch to turn QIn on or off, and is equal to zero (0, off) when People reaches zero (0). This configuration ensures that as soon as People reaches a level of zero (0), QOS will start to decrease towards zero (0). The inflow of quality per month (Q/month) is also influenced by the Synergy Quality Rate parameter, which can take values between 0 and 0.66.
Following, the People Factor is introduced that predominantly governs the in and out flows of people per month from the level People. This People Factor is modulated by an inverse s-shape transfer function (converter), where an increase in QOS results in an increase in People. The outflow of people per month (Out) is further modulated by the parameter Max 1. Finally, the Resource Comfort Dropping Rate is introduced, a variable that influences the amount of people leaving per month depending on the values that the Resource Comfort Quality Factor takes. This Resource Comfort Dropping Rate is described again by an inverse s-shape transfer function (converter) that takes higher values for small values of the Resource Comfort Quality Factor and approaches zero (0) as the Resource Comfort Quality Factor rises towards a maximum, meaning that a higher level of comfort results in less people leaving the community.
Now let us have a look at Resource/People that is governed in its behaviour by an s-shaped transfer function that causes an increase in resource output as the number of people rises, and together with the Resource Efficiency Factor and the carrying capacity (R_Carrying Capacity) determines the inflow of resources per month into the level Resource. The outflow from Resource is dependent on the amount of resources in the level and the Resource Dissipation Delay, a parameter by which Resource is divided to calculate the rate by which resources are being consumed per month.
Finally, let us take a closer look at the already briefly introduced Resource Comfort Quality Factor. This variable mainly dictates the rate at which people are entering and leaving the community and is modulated via the level People. This Resource Comfort Quality Factor is in turn modulated by the level QOS, where higher values of QOS cause a greater Resource Comfort Quality Factor. Another variable, the People per Resource Comfort Factor, which is described by an s-shaped transfer function, where an increase in R_Out (meaning more resources are being consumed) causes an increase of comfort and therefore higher values for People per Resource Comfort Factor. It is important to note that CF 1 simply is a unit conversion parameter and is set to the value of one (1) resulting in units of people/month for the rate In.
The following section will introduce a set of simulation scenarios and will provide some insights into the behaviour of the system.
SIMULATION SCENARIOS AND RESULTS
In Scenario 1 the initial condition of Resource (10) and the values of Synergy Quality Rate (0.02) and Resource Efficiency Factor (0.1) are significantly low. The level Resource decreases rapidly from ten (10) to zero (0) over a period of seven (7) months, and the number of people (People) decreases from ten (10) to reach zero (0) by month seven (7). A combination of few people in the community, a low synergy rate and a very low efficiency in the use of resources, results in a rapid drop in Resource and People. In this scenario, the system collapses and displays a community, which is unsustainable. Note that the quality of space declines in response to the drop in resources and number of people in the community with a delay of up to 32 months before it also reaches zero (0). Initially, a burst of QOS is injected into the system as often takes place with the establishment of a new community or even a new nation, such as the inspiration that comes from a shared ideal and the synergy to manifest such an ideal, like the writing of the Declaration of Independence of the United States of America, for example (Senge et al., 2005) (Senge, 1990). It is also important to note that the following four (4) scenarios will also reflect an initial rise in QOS, however, with different behaviours along time depending on the scenario modelled.
Scenario 2 displays initial oscillating behaviour of number of people (People) and the quality of space (QOS). This oscillating behaviour is due to the counterbalancing feedback loop between People and QOS, which is influenced by the input of Synergy Quality Rate that is low in this case, resulting in a negative impact on QOS.
Thus, as QOS increases, the number of people also increases with a delay and as more people arrive into the community, QOS starts to drop which causes an increase in the outflow of people from the community and subsequently QOS starts to rise again. In this scenario the number of people oscillates for the first twenty (20) months and then stabilises at around twenty (20) people. The level of QOS stabilises also at around twenty (20) months at a value of 0.7. This scenario reflects how even when there are enough resources, People and QOS never reach a higher maximum since Synergy Quality Rate is low. An explanation for this low Synergy Quality Rate could be that the members of the community are neither working together towards a shared vision nor contributing to QOS through actions of kindness, which constrains the growth and vibrancy of the community.
In Scenario 3 the graph displays the same oscillating behaviour as in Scenario 2 for People and QOS. The number of people increases also with a delay as QOS increases, showing strong oscillations for up to around twenty (20) months and then stabilises at around twenty (20) people. The level QOS stabilises also at around twenty (20) months at a value of 0.7, an above medium value. It is important to note that the system oscillates as in Scenario 2 for People and QOS, however, different amplitudes are observed, due to a change in scale of the primary y-axis. This scenario shows a significant decrease in the value at which Resource stabilises due to the effect of initial low resources. However, the net initial growth in Resource, until it stabilises, is greater (~ 30) in this scenario than the previous one (~ 7). The highlight of this scenario is that even with fewer resources, QOS and People display the same behaviour and reach the same final values. Far from being a surprise this result was expected since, in our experience in community building, quality of space is more relevant than availability of resources to inspire cohesiveness, growth and the production and management of resources, something that is reflected both in the system and simulation models.
In Scenario 4 the simulation starts with ten (10) people, a significant amount of resources, a high synergy level for quality and high efficiency for the use of resources with an initial burst of quality of space injected into the system as in the other scenarios. The high initial conditions, in particular the high synergy level, contribute to the rapid growth in the number of community members. Once the number of people approaches carrying capacity (Meadows, 2008), the community population stabilises. In this scenario it can be observed that with this configuration of values for the variables, the number of people in the community grows rapidly to a significantly high value (~ 35), almost reaching carrying capacity by fourteen (14) months. It is important to note that after this period it will take more than thirty (30) months to reach carrying capacity (40 people), a period that could be used to properly plan the next cycle of growth. The reader must also note that a high level of quality is maintained (~ 1) while reaching the carrying capacity of People, hand in hand with a significant amount of resources.
Scenario 5 gives similar results to the previous scenario in relation to rapid growth in the number of people together with a high quality of space. Even though the system begins with few resources and low resource efficiency, the high synergy quality rate contributes to the growth in QOS, which in turn contributes to an increase in the number of people with a consequent increase in resources. The number of people in this scenario also grows to reach its carrying capacity as in the previous scenario. A synergy for the quality of space is of great importance for a healthy, harmonious community and is closely connected to the amount of actions of kindness inputted into the system. The lesson here to be confirmed is that a continuous injection of quality and synergy is the main mitigating factor for the growth of the community, similar to what has been written: seek quality of space first and the rest will follow.
To summarise from the above scenarios:
1. Three (3) different outcomes can be identified as follows: (1) the community can collapse and dissipate without sufficient resources and/or a very low quality of space; (2) the community can oscillate until it reaches an equilibrium and (3) the community can grow exponentially until it reaches a limiting capacity.
2. Based on our experience, vision and values, we prefer the third outcome, viz. we believe it is more desirable to design a community, which can grow exponentially until it reaches a plateau at a manageable level.
3. Oscillations are undesirable due to the tension and elements of chaos which can occur in such scenarios; which, in our experience and observations, are usually caused by a lack of resources or low quality of space with the latter being much more significant and reliant on individual responsibility for inner peace. In other words, the quality of space has a larger impact than the availability and amount of resources on the development of the community when aiming at a sustained growth towards a limiting capacity.
4. A temporary plateau after a significant growth period, allows the wise members of the community a time to re-evaluate the vision and make wise decisions to plan for the future. At this point in time, the decision makers can explore questions such as: "Do we stay at that number of people (the plateau) with the existing high quality of space with commensurate resources, or do we plan for the next cycle of growth?" It is of paramount importance that, at this point, the decision makers need to know whether the community has the ability to maintain the high level of quality of space during the next cycle of growth and that there is the capability to contribute with more individual inner peace and actions of kindness when needed.
5. In our view, the quality of space is created via meditation together with the embodiment of spiritual values expressed in actions of kindness, hand in hand with the cultivation of inner peace (Zhuang et al., 2016). This is, we conjecture, a formula to successfully breathe life and vibrancy into a community, even when resources are limited. Furthermore, such quality will stimulate constructive creativity and intelligence to support the generation, acquisition and management of resources to wisely stimulate the growth and development of the community. Moreover, a community based on an economy of actions of kindness fuelled by spiritual values, will more likely have a greater capacity to regenerate itself and build resilience to grow towards health, wellbeing and social harmony.
CONCLUSION AND FUTURE PERSPECTIVE
Here we set out to use our system dynamics model depicted in Figure 1 in order to build a simulation model to describe the dynamics of a small pilot community known and experienced by the authors. This process has aided the exploration of key elements of the system, like resources, people and quality of space and how they impact on the growth or decline of such a community. In this way we purpose to guide humanity towards more peaceful and harmonious ways of living with each other and with their environment. Matching the conclusions of our previous paper that, through modelling and simulating such a pilot community, insight can be derived into how to aid other communities in their planning and developmental phases and this could potentially support the transition process from existing social and economic paradigms and structures towards alternative paradigms, like the one of an economy based on actions of kindness.
This work is also intended to support people to avoid the hard lessons that may arise through blind trial and error, therefore minimising the risk and pain of failure while maximising the probability to achieve a path of harmonious and sustainable growth, both for small and large communities, and with such a local learning process, aspire to contribute and support the development of larger regions and ideally the planetary community.
Through looking at the analysis of the five (5) different scenarios that were simulated, it can be concluded that for such a community to evolve harmoniously, the quality of space is a more significant factor than the availability or efficient use of resources. This means that people who place their attention on embodying spiritual values and maintaining inner peace will contribute towards achieving a high quality of space thus creating resilience within the community and hence the ability to direct and commit their energy for actions of kindness and the creative work that allows the vision of the community to unfold (Senge et al., 2005) (Senge, 1990).
So far the model reflects our observation through the years and our conclusion that the quality of space should be the main focus and valued accordingly, hand in hand with a wise management of resources, and in so doing, the model and more importantly the modelling process, become fundamental to our learning together with the planning and management of the limits to growth (Meadows et al., 1972) (Meadows et al., 1992).
In this paper only one subsystem of a larger model of an economy based on actions of kindness and altruistic work has been explored (Schübeler et al., 2018). In future work we will model and simulate the other subsystems and the larger model that includes inner peace, perceived kindness and perceived kindness dissipation, together with actions of kindness. It is important to note that we see these models as a very powerful and robust tool, potentially useful for future education and policy-making. They can also serve as seminal models to support communities towards achieving social harmony, initially at a microscopic level and ideally replicable at a macroscopic and planetary level, which will require the creation of an integrated simulation model.
Generally speaking, as stated in the introduction, the scenarios explored and analysed in this paper match our previous observations of the pilot community based on years of experience and anecdotal evidence. However, for greater reliability more investigation and the building of a future database with some relevant indicators of the dynamics of the community will be required, in order to validate the model presented with further refined simulations.
A further moral to this story is that mental and simulation models are just an efficient and effective conceptual framework to guide us, through a learning process, to the ultimate aim of improving the quality of our subjective~objective experience of community.
GLOSSARY
Actions of Kindness (AoK):
An Action of Kindness is an event that entails an interaction between a giver and a recipient or receiver, be it an individual or a group. Such an action stands as an opportunity to do good and have a positive impact primarily for the recipient, however, also with a spiritual or emotional benefit for the giver. The giver enjoys the act of giving or doing good. The reader must note that there are indirect benefits from such actions of kindness, which also have positive consequences in other people's lives and communities at large.
In folk wisdom this may have been described as 'what goes around comes around.' At a deeper level the laws of cause and effect may create social feedback loops of happiness and inner peace based on interactions between people that are intended to manifest kindness towards the other.
Actions of kindness differ from actions based only on good intentions in a way that considers more deeply the real needs of the receiver above only the good intention and the different biases, for example cultural or religious biases, of the giver (Ackoff, 1978). Actions of kindness have no strings attached to the recipient and can be regarded as genuine acts of unconditional love. In a sense, for the knower of God, actions of kindness are inspired by The Creator and fuelled by spiritual values.
Quality of Space (QOS):
A level or state variable that quantifies the subjective experience of the quality of environment and relationships that the community provides. When normalised, QOS takes values between zero (0) and one (1).
People per Resource Comfort Factor:
A quantity that describes to which degree the basic survival needs and comforts are met for the members of the community. Zero (0) means a total lack of basic needs and comforts and one (1) represents a total satisfaction when the basic survival needs and comforts of the community are met.
Soft Variables:
A type of variable in a system dynamics model that includes qualitative factors, such as intangibles like love and peace or social variables like morale for example, that are closely related to spiritual and behavioural values. Because of their qualitative nature, soft variables can be difficult or impossible to measure or estimate, however, they can be quantified by providing an appropriate scale. These variables are in all certainty, just as necessary a part of the system as hard-quantitative variables are in order to model, explain or predict the overall dynamics.
ACKNOWLEDGEMENTS
The team at The Embassy of Peace in Whitianga, New Zealand, would like to acknowledge The Creator for being a continuous source of inspiration, inner peace and harmony to our currently small societal community.We would also like to acknowledge the dedication and support of Enya, Sarah, Keryn, Matthew, Colin, Carey, Shiloh and Kali for the completion of this work. We also want to express our gratitude to the team of Insight Maker, whom we have never had the privilege to know in person and who, with their hard work, have provided a free and open source online simulation platform of high quality.
ABOUT EMBASSY OF PEACE
The Embassy of Peace in Whitianga, New Zealand is a learning organization comprised by a small community of people committed to upholding inner peace and living in harmony with the land and its environment.
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