Insights From Systems Thinking

2021 ◽  
pp. 146-166
Author(s):  
Rifat Atun
Keyword(s):  
Health Systems ◽  
Systems Thinking ◽  
Double Loop ◽  
Double Loop Learning ◽  
Values And Beliefs ◽  
Human Perceptions ◽  
Second Order Change ◽  
Collective Benefit ◽  
High Level ◽  
The Cost

Chapter 7 presents three high-level insights that can be drawn from this book’s look at a health system from a systems thinking perspective. First, all health systems suffer from one of systems theory’s classic descriptive models called The Tragedy of the Commons, in which a scarce resource is consumed when a collective benefit (e.g., health insurance) is subsidized and its price to the user is less than the cost to produce it. Second, when viewed from a systems perspective of value-for-money, most health systems face competing objectives—satisfying individual’s demands for maximizing their own medical care and providing healthcare as a fundamental right of all citizens regardless of ability to pay. Third, to integrate these goals requires re-framing the way societies think about each. The authors describe double-loop learning, which is required when confronting second-order change. The latter term describes problems where it is necessary to redesign human perceptions for change to lead to improvement. Complex changes require double-loop learning, in which underlying interpretive conflicts and differing values and beliefs are surfaced and managed.

Organizational Learning and the Learning Organization

2015 ◽  
pp. 286-312 ◽  
Keyword(s):  
Organizational Learning ◽  
Competitive Advantage ◽  
Systems Thinking ◽  
Learning Organization ◽  
Double Loop ◽  
Peter Senge ◽  
Generative Process ◽  
Double Loop Learning ◽  
Five Disciplines ◽  
A Company

Organizational learning and learning organization are two constructs based on conceptual metaphors. Organizational learning is a process that occurs across individual, group, and organizational levels through intuiting, interpreting, integrating, and institutionalizing. It is a purposeful process designed and sustained by inspired leadership. It may be an adaptive process based on the single-loop learning or a generative process based on the double-loop learning. The organization that is capable of transforming organizational learning into the engine of knowledge creation aiming at building up a competitive advantage may become a learning organization. Peter Senge developed the theory of the five disciplines that may transform a company into a learning organization, focusing on systems thinking. The purpose of this chapter is to present different views concerning organizational learning and its main characteristics.

scholarly journals Wisdom from Experience Paradox: Organizational Learning, Mistakes, Hierarchy and Maturity Issues

2021 ◽  
Vol 19 (2) ◽  
pp. pp105-117
Author(s):  
Wioleta Kucharska
Keyword(s):  
Knowledge Workers ◽  
Organisational Change ◽  
Double Loop ◽  
Positive Outcomes ◽  
Learning Resource ◽  
Double Loop Learning ◽  
Organizational Maturity ◽  
Low Performance ◽  
High Level ◽  
The Relationship

Organisations often perceive mistakes as indicators of negligence and low performance, yet they can be a precious learning resource. However, organisations cannot learn from mistakes if they have not accepted them. This study aimed to explore how organisational hierarchy and maturity levels influence the relationship between mistakes acceptance and the ability to change. A sample composed of 380 Polish employees working in knowledge-driven organisations across various industries was used to examine this phenomenon. Data collection occurred from November to December 2019. Data were analysed through OLS regression, using PROCESS software. The findings revealed that the acceptance of mistakes positively influences adaptability to change. Moreover, because of mistakes acceptance, knowledge workers in organisations with a low-level hierarchy adapt to changes more effectively than those who work in strongly (or high-level) hierarchical companies. Additionally, higher levels of hierarchy result in lower adaptability to change, which is particularly visible in mature organisations. The study's essence is the empirical proof that a high level of organizational maturity and hierarchy can be a blocker of the adaptability to change if the organisation stays on the single-loop of learning (does perfectly what it used to do). Mistakes acceptance and thanks to this, also learning from mistakes, supports organisational change adaptability. Change adaptability is vital for double-loop learning (organizational actions re-framing). Moreover, this study has exposed the paradox of ‘wisdom from experience’ empirically. Namely, it is expected that experience and maturity result in positive outcomes and increased organisational leverage. Whereas more prominent, experienced, and mature organisations face serious difficulties when changing their routines and behaviours.

Changing Role of Agriculture in Income and Employment, and Trends of Agricultural Worker Productivity in Indian States

2020 ◽  
pp. 183-189
Keyword(s):  
Green Revolution ◽  
Positive Trend ◽  
Worker Productivity ◽  
Indian States ◽  
Agricultural Worker ◽  
The Sixties ◽  
High Level ◽  
The Cost ◽  
Changing Role

The productivity of land has been often discussed and deliberated by the academia and policymakers to understand agriculture, however, very few studies have focused on the agriculture worker productivity to analyze this sector. This study concentrates on the productivity of agricultural workers from across the states taking two-time points into consideration. The agriculture worker productivity needs to be dealt with seriously and on a time series basis so that the marginal productivity of worker can be ascertained but also the dependency of worker on agriculture gets revealed. There is still disguised unemployment in all the states and high level of labour migration, yet most of the states showed the dependency has gone down. Although a state like Madhya Pradesh is doing very well in terms of income earned but that is at the cost of increased worker power in agriculture as a result of which, the productivity of worker has gone down. States like Mizoram, Meghalaya, Nagaland and Tripura, though small in size showed remarkable growth in productivity and all these states showed a positive trend in terms of worker shifting away from agriculture. The traditional states which gained the most from Green Revolution of the sixties are performing decently well, but they need to have the next major policy push so that they move to the next orbit of growth.

scholarly journals Determining the critical period for weed control in high-yielding cotton using common sunflower as a mimic weed

2019 ◽  
Vol 33 (6) ◽  
pp. 800-807 ◽  
Author(s):  
Graham W. Charles ◽  
Brian M. Sindel ◽  
Annette L. Cowie ◽  
Oliver G. G. Knox
Keyword(s):  
Weed Control ◽  
Critical Period ◽  
Yield Loss ◽  
Field Studies ◽  
Growing Degree Days ◽  
Degree Days ◽  
Weed Density ◽  
High Level ◽  
The Cost ◽  
Planting Season

AbstractField studies were conducted over six seasons to determine the critical period for weed control (CPWC) in high-yielding cotton, using common sunflower as a mimic weed. Common sunflower was planted with or after cotton emergence at densities of 1, 2, 5, 10, 20, and 50 plants m−2. Common sunflower was added and removed at approximately 0, 150, 300, 450, 600, 750, and 900 growing degree days (GDD) after planting. Season-long interference resulted in no harvestable cotton at densities of five or more common sunflower plants m−2. High levels of intraspecific and interspecific competition occurred at the highest weed densities, with increases in weed biomass and reductions in crop yield not proportional to the changes in weed density. Using a 5% yield-loss threshold, the CPWC extended from 43 to 615 GDD, and 20 to 1,512 GDD for one and 50 common sunflower plants m−2, respectively. These results highlight the high level of weed control required in high-yielding cotton to ensure crop losses do not exceed the cost of control.

scholarly journals Computing the Exact Number of Similarity Classes in the Longest Edge Bisection of Tetrahedra

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1447
Author(s):  
Jose P. Suárez ◽  
Agustín Trujillo ◽  
Tania Moreno
Keyword(s):  
Data Structure ◽  
Stability Condition ◽  
Open Problem ◽  
Integer Arithmetic ◽  
Exact Number ◽  
Similarity Class ◽  
The Stability ◽  
High Level ◽  
The Cost

Showing whether the longest-edge (LE) bisection of tetrahedra meshes degenerates the stability condition or not is still an open problem. Some reasons, in part, are due to the cost for achieving the computation of similarity classes of millions of tetrahedra. We prove the existence of tetrahedra where the LE bisection introduces, at most, 37 similarity classes. This family of new tetrahedra was roughly pointed out by Adler in 1983. However, as far as we know, there has been no evidence confirming its existence. We also introduce a new data structure and algorithm for computing the number of similarity tetrahedral classes based on integer arithmetic, storing only the square of edges. The algorithm lets us perform compact and efficient high-level similarity class computations with a cost that is only dependent on the number of similarity classes.

One-IPC high-level simulation of microthreaded many-core architectures

2016 ◽  
Vol 31 (2) ◽  
pp. 152-162 ◽  
Author(s):  
Irfan Uddin
Keyword(s):  
Design Space Exploration ◽  
Instruction Set ◽  
Efficient Design ◽  
Simulation Framework ◽  
Fine Grained ◽  
Detailed Simulation ◽  
High Level ◽  
Many Core ◽  
The Cost ◽  
Multiple Clusters

The microthreaded many-core architecture is comprised of multiple clusters of fine-grained multi-threaded cores. The management of concurrency is supported in the instruction set architecture of the cores and the computational work in application is asynchronously delegated to different clusters of cores, where the cluster is allocated dynamically. Computer architects are always interested in analyzing the complex interaction amongst the dynamically allocated resources. Generally a detailed simulation with a cycle-accurate simulation of the execution time is used. However, the cycle-accurate simulator for the microthreaded architecture executes at the rate of 100,000 instructions per second, divided over the number of simulated cores. This means that the evaluation of a complex application executing on a contemporary multi-core machine can be very slow. To perform efficient design space exploration we present a co-simulation environment, where the detailed execution of instructions in the pipeline of microthreaded cores and the interactions amongst the hardware components are abstracted. We present the evaluation of the high-level simulation framework against the cycle-accurate simulation framework. The results show that the high-level simulator is faster and less complicated than the cycle-accurate simulator but with the cost of losing accuracy.

Reflection and Double Loop Learning

2013 ◽  
Vol 31 (1) ◽  
pp. 124-134 ◽  
Author(s):  
Michael Synnott
Keyword(s):  
Double Loop ◽  
Double Loop Learning

scholarly journals Evolution of coordination in pairwise and multi-player interactions via prior commitments

2021 ◽  
pp. 105971232199316
Author(s):  
Ndidi Bianca Ogbo ◽  
Aiman Elragig ◽  
The Anh Han
Keyword(s):  
Autonomous Agents ◽  
Evolutionary Game ◽  
Multi Agent Systems ◽  
Coordination Problem ◽  
Mutual Cooperation ◽  
Payoff Structure ◽  
Optimal Coordination ◽  
Selection Intensities ◽  
Collective Benefit ◽  
High Level

Upon starting a collective endeavour, it is important to understand your partners’ preferences and how strongly they commit to a common goal. Establishing a prior commitment or agreement in terms of posterior benefits and consequences from those engaging in it provides an important mechanism for securing cooperation. Resorting to methods from Evolutionary Game Theory (EGT), here we analyse how prior commitments can also be adopted as a tool for enhancing coordination when its outcomes exhibit an asymmetric payoff structure, in both pairwise and multi-party interactions. Arguably, coordination is more complex to achieve than cooperation since there might be several desirable collective outcomes in a coordination problem (compared to mutual cooperation, the only desirable collective outcome in cooperation dilemmas). Our analysis, both analytically and via numerical simulations, shows that whether prior commitment would be a viable evolutionary mechanism for enhancing coordination and the overall population social welfare strongly depends on the collective benefit and severity of competition, and more importantly, how asymmetric benefits are resolved in a commitment deal. Moreover, in multi-party interactions, prior commitments prove to be crucial when a high level of group diversity is required for optimal coordination. The results are robust for different selection intensities. Overall, our analysis provides new insights into the complexity and beauty of behavioural evolution driven by humans’ capacity for commitment, as well as for the design of self-organised and distributed multi-agent systems for ensuring coordination among autonomous agents.

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