System Dynamics: Systems Thinking and Modeling for a Complex World
01 May 2002-
TL;DR: The field of system dynamics, created at MIT in the 1950s by Jay Forrester, is designed to help us learn about the structure and dynamics of complex systems in which we are embedded, design high-leverage policies for sustained improvement, and catalyze successful implementation and change as discussed by the authors.
Abstract: Todays problems often arise as unintended consequences of yesterdays solutions. Social systems often suffer from policy resistance, the tendency for well-intentioned interventions to be defeated by the response of the system to the intervention itself. The field of system dynamics, created at MIT in the 1950s by Jay Forrester, is designed to help us learn about the structure and dynamics of the complex systems in which we are embedded, design high-leverage policies for sustained improvement, and catalyze successful implementation and change. Drawing on engineering control theory and the modern theory of nonlinear dynamical systems, system dynamics often involves the development of formal models andmanagement flight simulators� to capture complex dynamics, and to create an environment for learning and policy design. Unlikepureengineering problemsif any existhuman systems present unique challenges, including long time horizons, issues that cross disciplinary boundaries, the need to develop reliable models of human behavior, and the great difficulty of experimental testing. Successful change in social systems also requires the active participation of a wide range of people in the modeling and policy design process, people who often lack technical training. In this paper I discuss requirements for the effective use of system dynamics and illustrate with a successful application to a difficult business issue.
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TL;DR: Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems, and its four areas of application are discussed by using real- world applications.
Abstract: Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed.
3,969 citations
01 Jan 2004
TL;DR: The goal of this dissertation is to find and provide the basis for a managerial tool that allows a firm to easily express its business logic and provide a software prototype to capture a company's business model in an information system.
Abstract: The goal of this dissertation is to find and provide the basis for a managerial tool that allows a firm to easily express its business logic. The methodological basis for this work is design science, where the researcher builds an artifact to solve a specific problem. In this case the aim is to provide an ontology that makes it possible to explicit a firm's business model. In other words, the proposed artifact helps a firm to formally describe its value proposition, its customers, the relationship with them, the necessary intra- and inter-firm infrastructure and its profit model. Such an ontology is relevant because until now there is no model that expresses a company's global business logic from a pure business point of view. Previous models essentially take an organizational or process perspective or cover only parts of a firm's business logic. The four main pillars of the ontology, which are inspired by management science and enterprise- and processmodeling, are product, customer interface, infrastructure and finance. The ontology is validated by case studies, a panel of experts and managers. The dissertation also provides a software prototype to capture a company's business model in an information system. The last part of the thesis consists of a demonstration of the value of the ontology in business strategy and Information Systems (IS) alignment.
Structure of this thesis:
The dissertation is structured in nine parts:
Chapter 1 presents the motivations of this research, the research methodology with which the goals shall be achieved and why this dissertation present a contribution to research.
Chapter 2 investigates the origins, the term and the concept of business models. It defines what is meant by business models in this dissertation and how they are situated in the context of the firm. In addition this chapter outlines the possible uses of the business model concept.
Chapter 3 gives an overview of the research done in the field of business models and enterprise ontologies.
Chapter 4 introduces the major contribution of this dissertation: the business model ontology. In this part of the thesis the elements, attributes and relationships of the ontology are explained and described in detail.
Chapter 5 presents a case study of the Montreux Jazz Festival which's business model was captured by applying the structure and concepts of the ontology. In fact, it gives an impression of how a business model description based on the ontology looks like.
Chapter 6 shows an instantiation of the ontology into a prototype tool: the Business Model Modelling Language BM2L. This is an XML-based description language that allows to capture and describe the business model of a firm and has a large potential for further applications.
Chapter 7 is about the evaluation of the business model ontology. The evaluation builds on literature review, a set of interviews with practitioners and case studies.
Chapter 8 gives an outlook on possible future research and applications of the business model ontology. The main areas of interest are alignment of business and information technology IT/information systems IS and business model comparison. Finally, chapter 9 presents some conclusions.
1,913 citations
TL;DR: A ‘Global Systems Science’ might create the required knowledge and paradigm shift in thinking to make man-made systems manageable.
Abstract: Today's strongly connected, global networks have produced highly interdependent systems that we do not understand and cannot control well. These systems are vulnerable to failure at all scales, posing serious threats to society, even when external shocks are absent. As the complexity and interaction strengths in our networked world increase, man-made systems can become unstable, creating uncontrollable situations even when decision-makers are well-skilled, have all data and technology at their disposal, and do their best. To make these systems manageable, a fundamental redesign is needed. A 'Global Systems Science' might create the required knowledge and paradigm shift in thinking.
929 citations
TL;DR: This paper proposes a definition of computational thinking for mathematics and science in the form of a taxonomy consisting of four main categories: data practices, modeling and simulation practices, computational problem solving practices, and systems thinking practices.
Abstract: Science and mathematics are becoming computational endeavors. This fact is reflected in the recently released Next Generation Science Standards and the decision to include “computational thinking” as a core scientific practice. With this addition, and the increased presence of computation in mathematics and scientific contexts, a new urgency has come to the challenge of defining computational thinking and providing a theoretical grounding for what form it should take in school science and mathematics classrooms. This paper presents a response to this challenge by proposing a definition of computational thinking for mathematics and science in the form of a taxonomy consisting of four main categories: data practices, modeling and simulation practices, computational problem solving practices, and systems thinking practices. In formulating this taxonomy, we draw on the existing computational thinking literature, interviews with mathematicians and scientists, and exemplary computational thinking instructional materials. This work was undertaken as part of a larger effort to infuse computational thinking into high school science and mathematics curricular materials. In this paper, we argue for the approach of embedding computational thinking in mathematics and science contexts, present the taxonomy, and discuss how we envision the taxonomy being used to bring current educational efforts in line with the increasingly computational nature of modern science and mathematics.
860 citations
TL;DR: The utility and applicability of the construct in the context of NRM is explored and includes a review of elicitation techniques used within the field and the major theoretical and practical challenges that arise in drawing on the construct to provide a cognitive dimension to NRM are addressed.
Abstract: Mental models are personal, internal representations of external reality that people use to interact with the world around them. They are constructed by individuals based on their unique life experiences, perceptions, and understandings of the world. Mental models are used to reason and make decisions and can be the basis of individual behaviors. They provide the mechanism through which new information is filtered and stored. Recognizing and dealing with the plurality of stakeholder's perceptions, values, and goals is currently considered a key aspect of effective natural resource management (NRM) practice. Therefore, gaining a better understanding of how mental models internally represent complex, dynamic systems and how these representations change over time will allow us to develop mechanisms to enhance effective management and use of natural resources. Realizing this potential, however, relies on developing and testing adequate tools and techniques to elicit these internal representations of the world effectively. This paper provides an interdisciplinary synthesis of the literature that has contributed to the theoretical development and practical application of the mental model construct. It explores the utility and applicability of the construct in the context of NRM and includes a review of elicitation techniques used within the field. The major theoretical and practical challenges that arise in drawing on the construct to provide a cognitive dimension to NRM are also addressed.
726 citations
References
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TL;DR: Senge's Fifth Discipline is a set of principles for building a "learning organization" as discussed by the authors, where people expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nutured, where collective aspiration is set free, and where people are contually learning together.
Abstract: Peter Senge, founder and director of the Society for Organisational Learning and senior lecturer at MIT, has found the means of creating a 'learning organisation'. In The Fifth Discipline, he draws the blueprints for an organisation where people expand their capacity to create the results they truly desire, where new and expansive patterns of thinking are nutured, where collective aspiration is set free, and where people are contually learning together. The Fifth Discipline fuses these features together into a coherent body of theory and practice, making the whole of an organisation more effective than the sum of its parts. Mastering the disciplines will: *Reignite the spark of learning, driven by people focused on what truly matters to them. *Bridge teamwork into macro-creativity. *Free you from confining assumptions and mind-sets. *Teach you to see the forest and the trees. *End the struggle between work and family time. The Fifth Discipline is a remarkable book that draws on science, spiritual values, psychology, the cutting edge of management thought and Senge's work with leading companies which employ Fifth Discipline methods. Reading it provides a searching personal experience and a dramatic professional shift of mind. This edition contains more than 100 pages of new material about how companies are actually using and benefiting from Fifth Discipline practices, as well as a new foreword from Peter Senge about his work with the Fifth Discipline over the last 15 years.
16,386 citations
Book•
01 Jan 1969TL;DR: A new edition of Simon's classic work on artificial intelligence as mentioned in this paper adds a chapter that sorts out the current themes and tools for analyzing complexity and complex systems, taking into account important advances in cognitive psychology and the science of design while confirming and extending Simon's basic thesis that a physical symbol system has the necessary and sufficient means for intelligent action.
Abstract: Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial intelligence adds a chapter that sorts out the current themes and tools -- chaos, adaptive systems, genetic algorithms -- for analyzing complexity and complex systems. There are updates throughout the book as well. These take into account important advances in cognitive psychology and the science of design while confirming and extending the book's basic thesis: that a physical symbol system has the necessary and sufficient means for intelligent action. The chapter "Economic Reality" has also been revised to reflect a change in emphasis in Simon's thinking about the respective roles of organizations and markets in economic systems.
11,845 citations
Book•
01 Jan 2000
TL;DR: Requirements for the effective use of system dynamics are discussed and a successful application to a difficult business issue is illustrated.
Abstract: Introduction Part I. Perspective and Process 1. Learning In and About Complex Systems 2. System Dynamics In Action 3. The Modeling Process 4. Structure and Behavior of Dynamic Systems Part II. Tools for Systems Thinking 5. Causal Loop Diagrams 6. Stocks and Flows 7. Dynamics of Stocks and Flows 8. Closing the Loop: Dynamics of Simple Structures Part III. The Dynamics of Growth 9. S-Shaped Growth: Epidemics, Innovation Diffusion, and the Growth of New Products 10. Path Dependence and Positive Feedback Part IV. Tools for Modeling Dynamic Systems 11. Delays 12. Coflows and Aging Chains 13. Modeling Decision Making 14. Forming Non-linear Relationships Part V. Instability and Oscillation 15. Modeling Human Behavior: Bounded Rationality or Rational Expectations? 16. Forecasts and Fudge Factors: Modeling Expectation Formation 17. Supply Chains and the Origin of Oscillations 18. Managing Supply Chains in Manufacturing 19. The Labor Supply Chain and the Origin of Business Cycles 20. The Invisible Hand Sometimes Shakes: Commodity Cycles Part VI. Validation and Model Testing 21. Truth and Beauty Part VII. Commencement 22. Challenges for the Future Appendix A: Numerical Integration Appendix B: Noise References Index
6,808 citations
TL;DR: In this paper, the authors explored the shortcomings of intuitive psychologists and the sources of bias in their attempts at understanding, predicting, and controlling the events that unfold around them, and explored the logical or rational schemata employed by intuitive psychologists.
Abstract: Publisher Summary Attribution theory is concerned with the attempts of ordinary people to understand the causes and implications of the events they witness. It deals with the “naive psychology” of the “man in the street” as he interprets his own behaviors and the actions of others. For man—in the perspective of attribution theory—is an intuitive psychologist who seeks to explain behavior and draw inferences about actors and their environments. To better understand the perceptions and actions of this intuitive scientist, his methods must be explored. The sources of oversight, error, or bias in his assumptions and procedures may have serious consequences, both for the lay psychologist himself and for the society that he builds and perpetuates. These shortcomings, explored from the vantage point of contemporary attribution theory, are the focus of the chapter. The logical or rational schemata employed by intuitive psychologists and the sources of bias in their attempts at understanding, predicting, and controlling the events that unfold around them are considered. Attributional biases in the psychology of prediction, perseverance of social inferences and social theories, and the intuitive psychologist's illusions and insights are described.
3,733 citations
TL;DR: In this paper, the authors report an experiment on the generation of macrodynamics from microstructure in a common managerial context, where subjects manage a simulated inventory distribution system which contains multiple actors, feedbacks, nonlinearities, and time delays.
Abstract: Studies in the psychology of individual choice have identified numerous cognitive and other bounds on human rationality, often producing systematic errors and biases. Yet for the most part models of aggregate phenomena in management science and economics are not consistent with such micro-empirical knowledge of individual decision-making. One explanation has been the difficulty of extending the experimental methods used to study individual decisions to aggregate, dynamic settings. This paper reports an experiment on the generation of macrodynamics from microstructure in a common managerial context. Subjects manage a simulated inventory distribution system which contains multiple actors, feedbacks, nonlinearities, and time delays. The interaction of individual decisions with the structure of the simulated firm produces aggregate dynamics which systematically diverge from optimal behavior. An anchoring and adjustment heuristic for stock management is proposed as a model of the subjects' decision processes. ...
2,209 citations