Online Content
Number of results to display per page
Search Results
-
- Type:
- Document
- Date Created:
- 1994
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, c060552994c1527f70693734935660f1, and fe35db792b573af835d96e6eba4759cd
- Description:
- This software life cycle model encompasses initial development, software upgrades, and error maintenance. The dynamic S**4 model is used to calculate several different development and maintenance strategies. The impact of Intergrated Computer Assisted Software Engineering (ICASE) tools on development and maintenance cost, schedule, and error rate is quantitatively evaluated. Alternative techniques for grouping error rate is quantitatively evaluated. Alternative techniques for grouping errors and functions into releases are evaluated.
-
- Type:
- Document
- Date Created:
- 1994
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, c060552994c1527f70693734935660f1, and fe35db792b573af835d96e6eba4759cd
- Description:
- The analytic uncertainty modeling techniques is useful whenever sensitivity analysis is important. It provides the entire resulting probability distribution instead of a single uncertain point estimate of the mean. Both analytic development costs, and computer execution cost are far less than in discrete event simulation. The price paid is some lack in modeling flexibility. Discrete simulation requires multiple long simulation runs to obtain a statistically significant point estimate. The different result values from multiple runs with identical parameter values but different random number seeds, are average to obtain the point estimate of the mean results value. Conversely, the analytic solution gives the entire resulting probability distribution with minimal calculation. The analytic solution also considerably simplifies sensitivity analysis. A single analytic run is done for each input parameter setting. Discrete event simulation requires multiple runs for each input parameter, to obtain a statistically significant mean result. In functional economic analysis we are interested in the relative future cost of alternative systems. There are uncertainties in process performance, resource requirements, cost estimate, investments required, workload, interest and inflation rates. There is also uncertainty in the future projection of these elements. Analytic uncertainty modeling provides a simple way of calculating output measure uncertainty from model input parameter uncertainties.
-
- Type:
- Document
- Date Created:
- 1994
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, c060552994c1527f70693734935660f1, and fe35db792b573af835d96e6eba4759cd
- Description:
- A new simulation is proposed to overcome several of the limitation of discrete event simulation. It is based on the combination of analytic queuing networks and analytic uncertainty modeling. The analytic queue techniques gives an approximate transient solution to the general inter arrival time and general service time single server queue. Analytic uncertainty analysis is based on the beta distribution. It provides the entire uncertainty probability distribution can be fit based on the minimum, mean, maximum, and estimate of the mean and standard deviation statistics. In a complex results calculation, all that is required is to keep track of these statistics as the calculation proceeds. At any point in a calculation, the probability distribution of the result can be derived by fitting a beta distribution based on the four statistics. When analytic queuing is combined with analytic uncertainty, modelling dynamics uncertainty analysis becomes feasible. The time varying uncertainty distribution in resulting measures of effectiveness can be calculated at any specified time or over nay user specified time interval. The new capability is not available in discrete event simulation.
-
- Type:
- Document
- Date Created:
- 1994
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, c060552994c1527f70693734935660f1, and fe35db792b573af835d96e6eba4759cd
- Description:
- Both strategic planning by senior management in the private sector and industry policy analysis by analysist in the public sector have the need for a systematic approach to develop an understanding the dynamics of their industry. Currently a systematic attempt at industry-level analysis requires the simultaneous use of a plethora of techniques such as Porter's five forces for competitive analysis, network approaches to examine inter-organizational transactions, as well as competitive population ecology to examine population dynamics. Building scenarios of possible consequences of significant strategic moves involves modeling the industry or strategic analysis. The underlying theory is developed from general system theory, strategic policy analysis. The aim of the approach is to allow a comprehensive qualitative model of the industry or strategic group to be developed based on graphically representing three subsystems: The social Subsystem, Information Subsystem, and the Physical Subsystem. The approach has been applied to an examination of the rapidly developing textile industry in Indonesia.
-
- Type:
- Document
- Date Created:
- 1994
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, c060552994c1527f70693734935660f1, and fe35db792b573af835d96e6eba4759cd
- Description:
- Learning curves are met in a wide variety of industrial situations. They have become particularly important in modern business strategy because product life cycles are constantly reducing as companies seek to gain competitive advantage via a rapid response to customer demands. The paper describes a family of System Dynamics models that have been found particularly appropriate in modeling and forecasting the performance of business organisations including the performance of manufacturing systems and the penetration of new product into the market place. The system dynamics learning curve model have a servomechanism analogue that yields valuable insights into the parameter estimation problem. The models are required under two quite different circumstances. The first is based on historical information where the model is to be added to a company or consultancy data base. The second is for on-line forecasting and control of a business activity. An enhanced stability least squared error predictor is described which covers both requirements. The paper concludes with industrial applications of the system dynamics models.
-
- Type:
- Document
- Date Created:
- 1994
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, c060552994c1527f70693734935660f1, and fe35db792b573af835d96e6eba4759cd
- Description:
- As the field of system dynamics modeling is expanding, there is a continuos need for improvements of the available tools for developing simulation model. Lack of features like array variables often lead to modelers to choose third generation languages like C when developing large, realistic models. This paper describes the array variables of the POWERSIM language. Comparisons are made to other notation, including mathematics and DYNAMO. Index variables, array dimensions, subscripts, and functions operating arrays are described. An important feature of POWERSIM is that the array notation goes well together with standard accumulator-flow diagram (AFD) and casual loop diagram used by system dynamicists. This makes the use of array variables almost as easy and intuitive as using scalars. The transition from single scalar values to multi-element array variables is visualized through examples. Examples include capital stock with machines and building, work force with inexperienced and experienced workers, delay structures programmed as arrays, etc. The array features of POWERSIM has been used with success in several large-scale projects. Many modeling problems are not practically solvable without using arrays. Even models that can be developed using only scalars, sometimes become much easier to develop, explain and maintain when using array's. In conclusion, the family of simulation problems that are best solved using a system dynamics tool, has been extended significantly through POWERSIM's array mechanism.
-
- Type:
- Document
- Date Created:
- 1994
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, c060552994c1527f70693734935660f1, and fe35db792b573af835d96e6eba4759cd
- Description:
- There has been an increased interest in teams and empowerment of working groups in management literature yet some researchers note that little has been done to define and analyse the critical factors that explain the variations of their performances as well as the participation progamme itself. This paper presents an initial investigation of the interfacing factors in participation, and its construct, motivation. The system archetypes in the participation system are first developed using recognized relationships in social science literature. Their corresponding balancing loops are later inferred largely from conflicting accounts and observations of the participating process. Some of the basic loops that are presented include the Organizational Improvement Loop, the Worker Environment Loop, the Tug-o-War Control Loop and the contribution sharing Loop. A simulation model of the Organizational Improvement Loop is then presented with its results.
-
- Type:
- Document
- Date Created:
- 1994
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, c060552994c1527f70693734935660f1, and fe35db792b573af835d96e6eba4759cd
- Description:
- The bulk of the literature on manpower planning models deals with long term planning and strategy evaluation. The most common approach is to use a Markov type model. This can readily model wastage and promotion rates, together with training policies and can be used to evaluate the longer term impact of personal policies. However many manpower planning problems span a much shorter time period and precise modeling of training and promotion strategies is inappropriate. This paper presents such problem. Staff planning procedures were required to reduce a large but temporary backlog of work. Two modeling approaches are contrasted: a time base simulation (a decision support system approach) and a system dynamics approach. The simulation model was encoded in a spreadsheet this enabled management to easily make alternatives, to the model data. The systems dynamics model presented a graphical representation of the problem which made all the modeling assumptions explicit. Both models could assess management alternatives, the spreadsheet model was able to provide very detailed information, whilst the main strength of the system dynamics model was its ability to provide more general results for the longer term. With both approaches the cooperation of management was essential for suggesting practical solutions.
-
- Type:
- Document
- Date Created:
- 1994
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, c060552994c1527f70693734935660f1, and fe35db792b573af835d96e6eba4759cd
- Description:
- The concept of "organizational learning" offers a rich opportunity for not only rethinking theories of organizational behavior (OB) but also reexamining the relationship between OB and financial performance. This paper examines an attempt to operationalise organizational learning by conducting a field study in the Australian hotel industry. The research process is described. Four models from the literature and out own feedback model provided the basis for initial analysis. Preliminary results suggest that the methodology is not only useful in differentiating hotels but in promoting new questions that need to be addressed. However the models provided little more than a check list. As a consequence, we have constructed a composite model that proved for a more useful testing of the triggers and dynamics of organizational learning.
-
- Type:
- Document
- Date Created:
- 1994
- Collection:
- System Dynamic Society Records
- Collecting Area:
- University Archives
- Collection ID:
- ua435
- Parent Record(s):
- 23d738ba88f8333bc39725f9cb5bd0b8, c060552994c1527f70693734935660f1, and fe35db792b573af835d96e6eba4759cd
- Description:
- Financial modeling is generally founded on the premise that financial managers and fiscal policy makers operate 'by the numbers'. Indeed the assumption is so deeply ingrained as to shape much of spreadsheet software to conform with accounting practices. It is the thesis of this paper that there is a qualitative side to financial decision making which translate the mathematical expressions of accounting into the commonsense language of mangers. The research reported in this paper examines the relationship between conventional financial models and the linguistic representations given them by financial managers. The research takes form of a STELLA model of corporate finance with a HYPERCARD interface. In the interface, the authors employ the propositions of fuzzy set theory to incorporate such linguistic hedges as "too high", "way out of line", and others found in common management speech. The resulting model assists financial managers in linking their qualitative judgments to the numerical parameters of a typical corporate financial model. As the model runs, it allows managers to adjust their financial policies on a quarterly time scale - while recording each person's decisions as related to model performance. The authors report the decision making practices of a sample of corporate executives as a set of qualitative propositions. There take the form of statements like, "If market share is falling rapidly, and leverage is fairly high, product line expansion is required." Such propositions take on a dual role; they can be translated into average numerical values to control a Stella simulation - or they can be simulated as a purely qualitative model. The significance of the qualitative thesis lies in the new perspectives it offers to those who study and practice financial management. The thesis offers a clear connection between the arcane world of the analyst or accountant and the complex environment of the working manager. It fosters a dialog across professional boundaries that may well result in more accurate models and more effective practitioners.