Using Systems Thinking to Understand and Enlarge Mental Models: Helping the Transition to a Sustainable World

Garrity, Edward J.

doi:10.3390/systems6020015

Cited by 25 publications

(15 citation statements)

References 25 publications

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“…Kahneman [27], (pp. [20][21] explains that there are two systems of thinking, called generically System 1 and System 2: "System 1 operates automatically and quickly, with little or no effort and no sense of voluntary control. System 2 allocates attention to the effortful mental activities that demand it, including complex computations".…”

Section: Knowledge As Energy: a Mental Challengementioning

confidence: 99%

“…System 1 processes emotional information received by the sensory system and transforms it into emotional knowledge which creates impressions, intuitions, and feelings. System 2 processes rational information and transforms it into rational knowledge which creates concepts, ideas, theories, and mental models [20,28,29]. These two thinking systems interact continuously across the invisible interface between the cognitive unconscious and our consciousness [30,31].…”

Section: Knowledge As Energy: a Mental Challengementioning

confidence: 99%

“…This is what the author defines as an 'accountingisation' of IC". Overcoming those limitations can be done by creating new metaphors and new mental models [20,21].…”

Section: Introductionmentioning

confidence: 99%

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The Theory of Knowledge Fields: A Thermodynamics Approach

Brătianu

Bejinaru

2019

Systems

115

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The emergence of knowledge economy and knowledge management revealed the need for reconsidering the concept of knowledge in a larger framework than that created by philosophers from ancient times. While the epistemology as a theory of knowledge and justification considers knowledge as a justified true belief, experts in knowledge management consider knowledge as a strategic resource. The new economic interpretation of knowledge as a strategic resource and a key contributor to achieving a competitive advantage generated a search of new metaphors to supply the attributes needed in constructing the new framework of understanding and operating with a working concept of knowledge in management. The most widespread knowledge metaphors are based on analogies with stocks, flows, and stock-and-flows. These metaphors induce, beyond some useful attributes, the Newtonian mechanics paradigm which is limited by the properties of linear spaces and reversible processes. The purpose of this paper is to show how we can enrich the theory of knowledge by introducing the concepts of knowledge fields and knowledge dynamics based on metaphorical thinking and the thermodynamics principles. The focus of our research is the energy metaphor which considers energy as a source semantic field. The main outcome of the present research is that knowledge can be considered as a field, which is manifesting in different forms like energy. This thermodynamics framework opens new directions for research in knowledge management, decision-making and leadership.Furthermore, tacit knowledge is deeply rooted in an individual's action and experience, as well as in 52 the ideals, values, or emotions he or she embraces" [8, p. 8]. Since tacit knowledge is processed in the 53 cognitive unconscious zone of our brain we hardly are aware of how much we know. As Polanyi [14, 54 p. 4] reveals, "we can know more than we can tell". 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 Figure 1. The structure of a conceptual metaphor 71 72 73 The second generation of knowledge metaphors introduced in the source domain the concept of 74 flows or stocks-and-flows [15-17]. Knowledge is compared with a flow of fluid from one part of the 75 organization to another one, or with a flow in time. That is a very simple and intuitive metaphor, 76 which was used also in the beginning for understanding heat and electricity. However, applying 77 fluid mechanics to knowledge dynamics yields a mechanical thinking model with its tangibility and 78 linearity limitations. The flows and stocks-and-flows metaphors cannot explain organizational 79 learning processes which are based on knowledge transformations. Also, these metaphors cannot 80 explain managerial decision-making processes and organizational changes.81 The linearity induced attribute by these metaphors created real difficulties in evaluating 82 intellectual capital (IC) which is based on knowledge and other intangible organizational resources.83 Even the definition of the intellectual capital has been influenced by this linearity ...

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Section: Knowledge As Energy: a Mental Challengementioning

confidence: 99%

Section: Knowledge As Energy: a Mental Challengementioning

confidence: 99%

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The Theory of Knowledge Fields: A Thermodynamics Approach

Brătianu

Bejinaru

2019

Systems

115

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“…This was explored via the development of a preliminary causal loop diagram (CLD) to identify important feedback loops. In the systems thinking field, CLD is a powerful tool for dealing with complex problems which has the ability to uncover the underlying feedback structures and leverage points in a system [9][10][11]. Moreover, causal loop modelling has been widely applied in health systems research [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Developing a Preliminary Causal Loop Diagram for Understanding the Wicked Complexity of the COVID-19 Pandemic

Sahin

Salim

Suprun

et al. 2020

Systems

103

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COVID-19 is a wicked problem for policy makers internationally as the complexity of the pandemic transcends health, environment, social and economic boundaries. Many countries are focusing on two key responses, namely virus containment and financial measures, but fail to recognise other aspects. The systems approach, however, enables policy makers to design the most effective strategies and reduce the unintended consequences. To achieve fundamental change, it is imperative to firstly identify the “right” interventions (leverage points) and implement additional measures to reduce negative consequences. To do so, a preliminary causal loop diagram of the COVID-19 pandemic was designed to explore its influence on socio-economic systems. In order to transcend the “wait and see” approach, and create an adaptive and resilient system, governments need to consider “deep” leverage points that can be realistically maintained over the long-term and cause a fundamental change, rather than focusing on “shallow” leverage points that are relatively easy to implement but do not result in significant systemic change.

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“…It is a powerful tool for identifying the non-linear feedback loops that operate in the system to amplify or balance outcomes. It can help stakeholders to converge on a shared mental model of a system, a set of beliefs, values, and assumptions that underly why things work as they do [ 27 ]. This shared understanding about how something works and what is important can be used to enhance policy setting and decision-making.…”

Section: Introductionmentioning

confidence: 99%

Applications of Systems Science to Understand and Manage Multiple Influences within Children’s Environmental Health in Least Developed Countries: A Causal Loop Diagram Approach

Brereton

Jagals

2021

IJERPH

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Least developed countries (LDCs) are home to over a billion people throughout Africa, Asia-Pacific, and the Caribbean. The people who live in LDCs represent just 13% of the global population but 40% of its growth rate. Characterised by low incomes and low education levels, high proportions of the population practising subsistence living, inadequate infrastructure, and lack of economic diversity and resilience, LDCs face serious health, environmental, social, and economic challenges. Many communities in LDCs have very limited access to adequate sanitation, safe water, and clean cooking fuel. LDCs are environmentally vulnerable; facing depletion of natural resources, the effects of unsustainable urbanization, and the impacts of climate change, leaving them unable to safeguard their children’s lifetime health and wellbeing. This paper reviews and describes the complexity of the causal relationships between children’s health and its environmental, social, and economic influences in LDCs using a causal loop diagram (CLD). The results identify some critical feedbacks between poverty, family size, population growth, children’s and adults’ health, inadequate water, sanitation and hygiene (WASH), air pollution, and education levels in LDCs and suggest leverage points for potential interventions. A CLD can also be a starting point for quantitative systems science approaches in the field, which can predict and compare the effects of interventions.

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Using Systems Thinking to Understand and Enlarge Mental Models: Helping the Transition to a Sustainable World

Cited by 25 publications

References 25 publications

The Theory of Knowledge Fields: A Thermodynamics Approach

The Theory of Knowledge Fields: A Thermodynamics Approach

Developing a Preliminary Causal Loop Diagram for Understanding the Wicked Complexity of the COVID-19 Pandemic

Applications of Systems Science to Understand and Manage Multiple Influences within Children’s Environmental Health in Least Developed Countries: A Causal Loop Diagram Approach

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