Busy lines are a persistent and persuasive problem common to all telephone systems, whether it counts with the most advanced digital technology and network management or no, there will always be a period during the day on the week where telephone calls cannot be completed due to busy line with the resultant loss of revenue. If expansion programs for telephone lines were not in accordance to actual demand growth telephone calls, this problemwill grow to the point where retrials would seriously impairthe telephone system operation. This paper describes the use of a system dynamics model for designing and evaluating expansion policies that respond to actual demand and ameliorate problem.
In a world of increasing complexity and turbulence organizations run the risk to loose effectiveness as well as efficiency when managed on the base of linear thinking and shortsighted decision making. System thinking and organizational learning instead will become a prerequisite for competitiveness and survival.
Population is an element in the social system. There are a number of elements in the social systems which will influence the population growth rate. On the other hand, population growth will, in turn, exert influence on other social elements. We can, therefore, apply the system dynamics (SD) model to dealing with the problems of population control. This paper, based on the investigation carried out in Anhui Province of China, conducts a study of the policies concerning population control in China by use of the system dynamics model.
The coordination in industrial systems should be one of the major challenges for future competitive advantages. The issues of industrial system’s coordination have been studied in system dynamics at the very beginning of the field. However, system dynamicists had not put enough efforts to study the industrial “systems”. This paper attempts to use system dynamics approach to study the “dynamics complexity” issues in industrial systems. The Center-Satellite System simulation game (CSS game), which based on Taiwan’s center-satellite industrial system (a huge industrial system with over 120 Center-factories, each with up to 400 networked Satellite-factories) was developed. Future research directions are discussed.
Recent research in the field of System Dynamics has been concerned with defining archetypal structures by which toclassify insights in dynamical systems. For example, Richmond has proposed both infrastructure and activity archetypes, whereas Senge has defined eight relevsnt generic structures. Additionall,Wolstenholme has defined a number of management situations as being made up of actual outcomes which are opposed to those intended.
What is the relative importance of internal versus contextual forces in the birth and death of scientific theories? Elaborating on the analysis of a model of multiple paradigm competition and scientific development already developed by Wittenberg and Sterman, we find that situational factors present when a paradigm is launched largely determine a paradigm’s probability of rising to dominance. Stronger paradigms that survive the emergence phase live longer than their weaker counterparts, but this too is contingent upon factors present during the emergence period.
This article concerns the problems that junior college students encounter when trying to understand and utilize the concept and insights traditionally provided by the teaching of mathematics. In this context, the concept “change” is significant because it is closely associated with the ‘derivative” and the "integral” defined in mathematical analysis.
The author explores a comprehensive methods of system analysis, inference and synthesis and model sets for studying complex system. These methodologies and model sets can be used in studying the development strategy and planning of socio-economic-ecosystem. It has been successful in the study of Pudong Economic Zone of Shanghai.
Based on system dynamics, this paper creates an approach of combining qualitative and quantitative analyses, systems thinking, system analysis, synthesis and deduction with a set of models. First, We build up a generic model set with various economic indexes. About several dozen modern management methods have been applied to the different subsystems implied by their parameters and feedback structures.
In recent years many system dynamics modelers have pointed out that for effective implementation of model results it is that the client participates in the model-building process. This has lead to various more or less successful approaches in group model-building. However, up to now little systematic research has been conducted in the area of effectiveness of group model-building. Systematic evaluation of group model-building is important in order to a) understand how clients and organizations are effected by group model-building; and b) improve the effectiveness of the group model-building proces. In this paper evaluation results are presented of four model-building projects based on clients' opinions of the successfulness of these projects.
This paper presents one middle term simulations model and its main results. We chose the production systems which produce complex capital goods, for example electrical equipement or household goods. The objective of this type of system is to build up stocks of finished goods which are put at the disposal of the customers. The corresponding macro model was designed by a systemic vision and split into three components which represent the operating, decision and information production sub-systems. The simulation of the generic model has permitted the improvement of system dynamics knowledge. We detected prominent decision loops and some unnecessary loops in production control.
Fuzzy numbers is presented as an alternative to probabilistic methods for the management of uncertainty in system dynamic model. Fuzzy numbers are particularly suitable to represent vagueness and qualitative values. Fuzzy numbers are used during simulation, but due to interactiveness among variables there is a need for global optimization methods. Some examples that illustrate the use of fuzzy numbers, both directly and as a means to represent qualitative values, are shown.
This paper explores the behavior of the gross investment considerig the linear versions and two non-linear versions from Kalecki’s model. This model assumes that there is an average gestation lag of investment and it is formuled by means of a mixed differential-difference equations.
This paper examines the use of a system dynamics modelling technique to enhance the contribution made by cash flow forecasts to decision makers' mental models. It is argued that by making explicit and accessible the dynamic complexity in cash flow relationships, systems dynamics can provide valuable insights for decision making puposes. By permitting the exploration of behavioural responses to perceptions about the financial position of thee business, a richer picture of the decision outcome is developed leading to changes in decision makers perceptions about the riskiness of a proposed course of action. A case study of a commercial organisation is used to illustrate these insights.
Service quality cannot be measured and tested in as straight forward a manner as in manufacturing. This biases serve businesses to focusing on keeping measurable variables-typically, expenses and work flows-in control, while underinvesting in the intangibles of service capacity and service quality. In the long-term, results can be mediocre levels of service quality, poor customers satisfaction, high turnover of service personnel, and ultimately, higher total costs. In this paper we will present an emerging theory of interactions between Service Quality and Service Capacity, relate this theory to past research in both the System Dynamics and Total Quality Management traditions and outline ongoing empirical testing of the theory.
What should every professional dynamicist know? What are the core works defining our field? This survey of the English-language system dynamics literature identifies and summarizes one view of the essential papers, book, games and software programs that have influenced the development of the field. Such a list serves as a means of reflecting on the foundation of current research and practice, thus providing a catalyst for a continuing discussion among system dynamicists on the major themes of the field and the contributions that define them. In presenting this bibliography, the authors encourage other researchers., practitioners and student to add their views to the present effort.
This Paper develops a conceptual model of a collegial system working without external adjudication or an institutional charter governing the conduct of its operations. The model is applicable to many of the academic and research organizations established in the developing countries, which have attempted to emulate the equivalent professional organization in the advanced industrial countries but have achieved low efficacy. The analysis suggests that an unadjudicated collegial system is not sustainable, for it will tend to create an authoritarian administration which will impair the collegial norms and misallocate scarce resources to the activities fueling bureaucratization and expansion of administrative scope, while professional autonomy, innovativeness and self-actualized behavior are suppressed. Professional conduct tends to be more-value rational than the bureaucracy since it is subject to reviews by external peers. Thus, legitimation of referent power is essential to creating value-rational decisions which assure a balanced resource allocation that sustains a collegial system. Limiting scope of the administration through an external scrutiny of its conduct or a charter appears to facilitate this process.
The purpose of this paper is to show that a well-known group of economists known as “Post Keynesians” or “Post Keynesian Institutionalists”, engage in macroeconomic modeling in a way that is strikingly similar to the system dynamics method. It will be argued, therefore, that system dynamics can be used to improve Post Keynesian macroeconomic analysis. In addition, this paper will present an original system dynamics model of macroeconomic growth, instability, and income distribution, that can clearly be classified as Post Keynesian. Of interest is that the model generates, among other behaviors, an economic long wave.
This paper is a case study on the introduction of systems thinking tools into a research group within a large information service company. The central dynamics involved in this learning process was a continuous goal shift. We address the realities of trying to develop a shared dynamic problem definition, and show how would-be practitioners internalize the material in unexpected and often paradoxical ways.
The paper proposes a methodology, of building system dynamics models for queuing systems. The methodology is applied to a variety of queuing systems and it is observed that, the models so developed are more transparent than conventional state-transition diagram and incorporation of real life complexities are easier. In effect working out the transient and steady state behaviour of a wide variety of queuing system becomes easy without going into much mathematical tedium.
The paper review the experience of a consultancy in the company called BETA. Two goals are pursued: cognitive and methodological. Cognitive goal refers to the System Dynamics methodology applied to a concrete case of the company growth and strategy making within a traditionally dominated accounting framework. Based on symbolic (though keeping similarity to real) data, the article presents the ithink™ model construction and simulation within 3 strategic scenarios: optimistic, realistic, and pessimistic. The methodological objective contains the use of the Partitioning and Tearing Method in the problem conceptualization and model preparation. Although the scope of the paper excluded a possibility of its detailed description, it is argued that this method has proved to be very useful in working with complex problems containing many variables.
Periodically, at different times of its history, the Argentine economy has been dominated by a vicious circle, well known among developing countries. The Central Bank pays interest on money and such interest is financed through emission of more money thus, causing inflation. In one of these periods: the corresponding to February 1981-July 1982, the accumulated inflation increased to 250 per cent. In 1982, the government decided to reduce the interest rate abruptly, in order to achieve a quick reduction of the inflation rate. However, the year 1982 witnessed the failure of the application of this financial reform. Although the growth rate of liquid assets declined, the inflation rate of July 1982 duplicated the precious month rate. This article reformulates a small economic model, in the Cagan tradition, due to Rodriguez (1986). It was conceived to explain the historic dynamics of the financial indicators, after the reform. Hopefully, the readability of the model should improve, when compared with the original version. And, instead of attributing the dynamics globally to the complex behavior of the system, the paper identifies the cause of this dynamics throughout the causal structure that produced it.
The purpose of this paper is fourfold: 1) to survey the literature on evolutionary economics in general; 2) to survey the literature on evolutionary economics modeling in particular; 3) to outline the contribution that system dynamics can make to evolutionary economic modeling; and 4) to present two original, evolutionary, system dynamics models.
Innovation is a topic that has received much attention in the literature in recent years. For the most part, these articles have not solved an important problem facing the managers in today’s large organizations -- how to manage a portfolio of interactive product- and process- innovations, addressing the interrelated forces, including monetary constraints, manpower planning & technology capability, to a dynamic environment. By systems thinking of these problems, the author first set up a generic S.D. model as a Microcosm for portfolio analysis of technological innovations. Based on this Microcosm, an experiment aimed at pattern selection of product-& process- innovations was conducted, drawing the conclusion different from the famous Abernathy/Utterback’s. Finally, the mechanism of group decision on project selection of innovation portfolio using the Microcosm was explained, and the group decision support system was constructed.
By the thought of coordinative development between Science & Technology, economy, education and finance, this paper first concerns the problems facing China on the resource allocation of Scientific Research. A comparative study on both developed and developing countries is made. In the meantime, the mechanism of the coordinative development between Science & Technology, economy, education and finance, the coordinative development between Scientific Research (Basic Research), Applied Research & Development as well as the priority of Scientific Research in different stages of social & economic development, a system dynamic model is constructed, focusing the analysis of scale & speed of resource allocation for Scientific Research in China.
This paper describes what is meant by modelling at Sunderland and how System Dynamics fits into this ethos. The teaching and the examples covered in this System dynamics module are different the usual course and the paper deals with our experience in these areas. The reaction of Eastern European ( Bulgarian ) students to this type of teaching is discussed. Students must complete a project in a work placement to obtain a masters qualification. The reaction of companies to the use of System Dynamics ( a new experience for most ) is discussed and examples of the type of projects that have been completed are given. The paper concludes with a description of a Hypercard project which extends the use of System dynamics to Engineering students.
The development and diffusion of innovations is a highly dynamic phenomenon. It is influenced by various factors like price, product quality, and market entry time. The paper discusses the impact of pricing strategies on R&D performance and the diffusion of innovations. It is based on a comprehensive decision support model in the field of innovation management. The model consists of two components: (1) an evolution algorithm modeling the processes of corporate R&D, and (2) a DYNAMO-based modul mapping corporate policy making and the structural fundamentals of market dynamics. The integrated model is used to analyze the dynamic consequences of different pricing strategies on research and development, the readiness for market entry and the resulting competitive advantages.
This paper presents a system developed to design strategies for organizational expansion based on system dynamics and expert system methodologies. The tool was especially built to plan the expansion of a computing system network.
The main objective of the MISTELA model is to integrate the different aspects of strategic planning of TELEFONICA DE ESPAÑA into one signal unit. By so doing one is obviously forced to give up many of the small details in order to be able to look at the larger picture. MISTELA uses a systemic approach to construct the model described in, this paper, Systems Dynamics was chosen, since this technique permits straightforward combination of different modelling procedures such as statistical inference, calibration by trail and error, linear and/or quadratic programming, etc. To give an idea of the size of the model, it handles about 1,500 equations, definition and identities. There are some 700 conceptual variables, and because many of these are vectors, in effect there about 4,000 scalar variables.
In almost all urban areas, existing infrastructure (transportation, water, sewer, social services) lags behind desired infrastructure. Planning new infrastructure depends on future land use forecasts. The distribution of future land use is also dependent of on available infrastructure. Due to this feedback, the infrastructure shortfall problem is resistant to solution through infrastructure improvement and local land use regulations. We have developed regional land use/infrastructure planning models that combine fairly simple system dynamics structures with spatially disaggregated databases. The models provide insights about the effectiveness of alternative policies, using detail of the local area that planners need.
Decision Support System (DSS) are commonly used in the manufacturing industry to assist management in decision making processes. There are several major types of DSS systems and each is useful for solving specific manufacturing problems. The development of intelligent DSS systems that can carry out high level reasoning is itself a challenge and a requirement by modern management. This paper illustrates the formulation of a DSS system (called Performance Decision System) that can be used for solving complex manufacturing problems. The DSS system is based on two major types of DSS; System Dynamics and Experts Systems.
This paper describes the work and experience gained by a team using a system thinking approach to developing a microworld to support the strategic planning of Athabasca University (AU), a fast growing opening university in western Canada. The opportunity for this experience arose from an invitation by the university President to teach an introductory course in Systems Thinking to a group of 30 senior management representing the faculty, administration, and the governing council. This work is intended to aid in understanding the dynamic forces which have allowed AU to double the number of courses registration in the past five years while lowering cost to government of providing access to AU from $1,179 to $635 per course registration (in constant dollars) since 1985. This work reports the experience of AU in building a Microworlds® system in order to accelerate organizational learning. The system is based on the system dynamics methodology and was developed using STELLA®. The system has been used to test different scenarios of strategic options which are almost impossible to evaluate otherwise. The system was validated against actual data and was used as management flight simulator to the system till year 2000. Repeated runs of the simulations have proved that quick fixes to one part of the system do not necessarily help its overall performance. It has been found that the process of constructing a simulation model is as valuable for problem solving as the final model itself.
The Beer Game is still today, one of the tools with the greatest impact in demonstrating that the behaviour of a system is generated by its structure. However, we believe that in its original form too much time is needed to play it and carry out a proper debriefing. In addition, it is not always easy to guarantee the hypothesis of isolation for the different positions within the game. Finally, we feel that participants often have difficulty in picking up quickly and clearly the process characterizing the game. To deal with these and other problems we have introduced certain modifications which, in our view, totally or partially resolve these difficulties.
A great number of System Dynamicists coincide in our belief that the methods and tools presently used in virtually all management education centres insufficient to cope with an ever more complex reality. For some years now there has been a significant movement within our field which aims to provide alternative ways and tools which will serve to fill the existing gap. Working along these lines we created a work group and started, within the EC Comett framework in 1990, a project termed “Learning laboratories in computer-aided Systemic Business Management”, sponsored by numerous European firms and institutions. The aims of the project are multiple and interrelated: production of learning tools based on System Dynamics, facilitating reflection on causes, design of learning laboratories in business management following a systemic approach, trying out the tools created and checking learning processes for different circumstances, development of training courses, promoting training of trainers.
The function of a competitive intelligence system is to generate a manufacturing strategy which is superior than the competition. A competitive intelligence system consists of a set of tools that capture and synthesize the competitors manufacturing strategies in order to generate the desired strategy. A competitive intelligence system that uses reference models is presented here and its use illustrated with a case study. A reference model is a generic system dynamics model which includes the cause-effect relationships that explain the current quality of the competitors products.
The savings and loan industry has been the primary source of home mortgages for American families since 1932. Since 1984, however, 25 percent of the savings and loans, approximately 700 out of 2800, have failed. Although the total costs associated with these failed savings and loans have yet to be determined, estimates range from $300 billion to $1 trillion. This paper discusses a system dynamics model of the effects of interest rate risk and default risk focusing on the savings and loan industry. Using the model to test the effects of policy initiatives specific to the prime interest rate and the default risk on loans, the authors demonstrate that the savings and loan crisis might have been lessened or even avoided if the regulators had a better understanding of the system’s structure and the effect of that structure on system behavior.
The diffusion of new technologies into the market is a critical factor in the success of any technology based company. This paper describes a system dynamics model which integrates a number of key concepts presently used to understand the diffusion process (e.g. technical progress functions, cost-experience curves). It shows how these concepts, together with management decisions regarding R&D investment, marketing, and pricing, drive the evolution of diffusion between technologies. It then illustrates how simulation can be used to understand the critical success factors in technology diffusion, and what this means for the management of technology-based companies.
In this paper we describe a modification of the Beer Distribution Game which we have used with MBA students and executives. In this version, we introduce a change in communication rules at the end of week 24. Our game debriefing addresses all of Senge’s five learning disciplines and stresses the basic question: how do we deal more effectively with underlying structure? This variation on the usual rules shows a way for designing experiments with the Beer Game to improve our understanding of how organizations learn.
The Management Flight Simulator is now being established as a tool to facilitate experiential learning with both undergraduate and postgraduate management students, and managers within learning organisations. Existing MFS provide user-friendly reports and graphical representations of historical data, designed to the limits of human computer interface (HCI) good practice. Although, existing MFS make use of sophisticated quantitative databases and models, but lack the softer data: managers’ in-trays, meeting notes, employee feedback, interviews with customers, press and television news reports, industry observers, financial analysts, and so on. Managers in real life rarely make decisions without going to look at a problem for themselves. Using multimedia MFS, users will be able to do the same, by interrogating and making observations using electronic-based media.
Management Flight Simulators (MFS) are now being used together with model-supported case studies in learning laboratories as part of undergraduate, graduate and executive courses, and also with managers in learning organisations. This paper reports results with three groups of undergraduate and postgraduate students, in a business school environment. With one group, a multi-stage experimental design is used to collect a variety of process data, including:
At its inception, the paradigm of SD was deliberately made distant from that of OR. Yet developments in 'soft' OR and systems theory now have much in common with current SD modelling practice. This paper briefly traces the parallel development of SD and soft OR and argues that a dialogue between the two would be mutually rewarding. To support this claim, example of soft OR tools are described along with some of the field's philosophical grounding and current issues. Potential benefits resulting from a dialogue are proposed, with particular emphasis on the methodological framework of SD. The paper closes with some suggestion on how to begin learning from the links between the two fields.
Managers involved in the production and trading of a commodity had adopted conflicting positions regarding the macro-dynamic behaviour of output and revenues in their market. The tools of system dynamics were used to articulate the assumptions of the participants and, in so doing, support a dialogue in which the understanding that the managers had of the key variables could be altered. The eventual use of a small STELLA model allowed the managers to isolate two specific, micro effects from which the conflict emanated. Further idea sharing allowed a consensus to be achieved on those two and, furnished with this new understanding, the participants aligned behind a single view of the market’s behaviour.
The form of the management flight simulator should follow from the functions it serves for the user. Interfaces designed to facilitate educational interventions should differ in functional form from interfaces designed to provide support systems for executives making real time decisions or conducting scenario planning exercises. Designers should consider the purpose of the interface, the nature of the interaction, the characteristics of the users, the context of use, and the style of presentation before developing the software application. This paper provides examples of how radically different design criteria lead a design team to choose different forms for several management flight simulators and executive-information systems.
A system dynamics model was develop for a company looking to reduce delivery times in projects involving the engineering, procurement and construction of complex equipment systems for pulp and paper mills. The model has some original features, particularly its portrayal of a critical path determined the ‘gates’ connecting sequential activities, which should be of general interest to project modelers. The model has helped the company identify practical ways to reduce delivery times by at least 30% and do so without driving up costs.
Advocates of the "Modelling as Learning" philosophy would not endorse a policy of handling over a ready-made model to a new client. In commercial environments, however, consultants and clients move on and there is pressure to maximise return on investment. This often means that existing System Dynamics models must be transferred between consultants and clients. Within the Business Consultancy department at Shell both the consultants and clients change jobs every three years or so and model handover is an issue that must be managed.
This paper investigates how mode-locking and other highly nonlinear dynamic phenomena arise through the interaction of two capital-producing sectors in a disaggregated economic long-wave model. One sector might represent the construction of building and infrastructure capital with long lifetimes while the other represents production of machinery, computers, etc. with much shorter lifetimes. Due to the positive feedback associated with capital self-ordering, each sector in isolation produces a self-sustained oscillation with a period and amplitude determine by the characteristics of that sector. However, the sectors interact through their mutual dependence on each other’s output for their own production. When this coupling is accounted for, the two sectors tend to synchronize or lock together with a rational ratio between the periods. While keeping the aggregate equilibrium characteristics of the system constant, we study how this locking occurs as a function of the difference in capital lifetimes and as a function of strength of the coupling between sectors. Besides mode-locking and quasi-periodic behavior, the observed phenomena includes cascades of period-doubling bifurcations, chaos, and intermittency. When the difference in capital lifetimes is very large, the system behaves like a one-sector model with a reduced capital content of production: Only one oscillatory mode remains, and it is much less pronounced than in the original one-sector model.
The Beer Distribution Game is one of the most popular ways of introducing managers and students to system dynamics. One of the reasons for this popularity is its success at teaching, on an experiential level, one of the fundamental principles of System Dynamics--that structure causes behavior. It does this in an entertaining and engaging manner. Some players have become so engaged in the experience that they want to explore the dynamics of game further. Because of this interest computer versions of the game have been developed to accelerate the opportunities to explore the game’s dynamics and make it easier to use and facilitate. This paper will highlight some of the features of these games which facilitate learning by individuals or teams.