This paper presents a system dynamics model of human factors in the implementation of office automation in the Job Service. The model includes sectors representing model acceptance by managers, supervisors, professionals, and clerks with the various factors impacting on such acceptance. Since the perceived usefulness of the automated system for office performance is quite important (especially for managers), sectors representing workflow and efficiency are also included.
Proper data management is an essential component of system dynamic modeling. The authors have developed an approach to data management, as set forth in this article. The article first describes the modeling and data management activities from a critical path point of view. The approach to handling the data associated activities is then developed. This approach asserts the following: 1. it is appropriate to address data relates activities at each stage of the model development process, and 2. when properly linked, a synergism exists between each model development stage and its associated data handling activity. It is claimed that this approach, including sequenced data handling and synergism between data and modeling activities, can produce a more comprehensive and timely model.
The most basic problem of sociology as an empirical science is the difficulty of replicating studies within reasonable time limits and in genuinely comparable conditions. Sociologists aspire to make correct predictions based on verifiable statements about causal relationships, but cannot, the nature of macro-social phenomena precluding experimental designs with adequate controls. System Dynamics promises a way out of this dilemma. Four things need to be done. (1) Formulate the sociological theory as a causal loop diagram, making all causal reasoning explicit. (2) State what variables are involved in the functioning of the system. Calibrate the model until it is internally consistent. (3) Refine and adjust the constants until the model can reproduce a known time-series of relevant data. Repeat this on number of data-sets. (4) Systematically vary each constant in turn while controlling for the others. This is, in fact, the quasi-experimental procedure for testing the conditions under which the theory will stand or fall, and why. An illustrative example of the proposed strategy is presented, with encouraging results.
This paper discusses an approach to model refinement which involves testing the behavior of individual pieces of a model in response to empirical input data for comparison with empirical output data. Partial-model tests should be used for selecting formulations or estimating parameters only when appropriate case-specific or logical information is not available for this purpose. The smaller the model components used for partial-model testing, the more likely it is that the model will prove useful for anticipating events outside the historical experience and the less likely it is that observed behavior will be incorrectly attributed to certain relationships or parameters. Thus, from the standpoint of structural validity, partial-model testing is an improvement over whole-model testing for the purpose of structural adjustment. The paper presents a detailed example of partial-model testing in the context of a generic model of the evolving use of a new medical technology. Specifically, the technique is used for adjusting and validating a model subsystem that can explain why the reporting of clinical information on cardiac pacemakers has been marked by regular oscillations over time.
It is envisaged that although the rabies system is a special case whereby there is no recovery from the disease, the principles generated by the analysis may be applicable to epidemiology in general. Such applications providing a definition of a disease system such that effective control policies may be elucidated. The work presented here is complete in itself forming a qualitative analysis of the system. It also provides the basis for a quantitative analysis using a derived computer simulation model.
The paper is concerned with describing an investigation of information usage in the control of colliery operations. The premise of the work is that to make the most of new information retrieval technology currently being installed in collieries research is needed to provide compatible advances in the methods of information usage. The approach adopted was to construct a continuous simulation model using system dynamics capable of providing a laboratory assessment of alternative managerial control policies based on alternative sources and levels of aggregation of information. The model developed represents a typical colliery situation composed of three working coalfaces and incorporating planning production, development and manpower sectors. The face sectors transform coal reserves to mined coal output, under manpower constraints and geological shocks, and these are all interlinked by means of allocation policies for manpower and shifts. A range of policies for for the exercise of control through these allocations are considered subject to a range of shocks. It is concluded that, although there are difficulties in designing single policies which are universally best, there are clear advantages associated with fully integrated colliery policies based on information inputs from all aspects of the operations.
Among the most stable phase relationships between economic variables is that between money, the change in money, and general economic activity. Both the change in money and money itself lead production over the business cycle. This relationship buttressed with results of the Granger/Sims test for causality, has been used to support the notion that money causes real activity. This notion, in turn, is used to argue both that monetary policy causes the business cycle and that monetary policy can ameliorate the business cycle. This paper examines a hypothesis for the phase relationships which assume that money does not cause real activity, but, rather, real activity causes money. According to the hypothesis inventory assessment, which leads business activity, induces corporate borrowing, which in turn causes a money expansion with a lead similar to that observed. This has been a working hypothesis for the phasing in money of the System Dynamics National Model project. It is concluded that the hypothesis, by itself, is insufficient to account for the observed timing relationships. However, the inventory investment hypothesis combined with additional hypotheses such as a mechanism for household portfolio adjustment, can account for the phasing. These results do not depend on a causal flow from money to real activity. As a consequence, business cycle phase relationships should not be taken to imply money causes the business cycle nor that monetary policy can influence the business cycle.
A process-theoretic approach, seldom used but not without promise for organizational behavior research, is employed to postulate a process model of the natural logic evident in organizational policy making. The model is used to explain how the policies of a sample firm (for which twenty years of data are available) became adopted and how, together with critical events, this caused the firm to evolve in particular directions rather than others. Implications of the study are put forward in terms of identifying the pathologies of the policy making process. Some prescriptions are put forward for the proper control of organizations by supervisory bodies, such as boards of directors. It is suggested that Management Science, in the form of systematic procedures for adaptive organizational design and updatable cause maps, may have an important future role to play in senior management affairs. Questions are raised for government and society concerning sustaining and regulating firms in both the public and private sectors in the light of the study.
A steel demand model consisting of 15 sub-sectors was formulated by the authors to dynamically estimate the steel demand from GNP per capita. Attempt is now being made to develop a more general consumer demand model specific to India, which, among other things, takes into consideration inflation as caused by increase in money supply to finance development plans of the country, remittances from expatriate workers, foreign loans, and wage increase to increase in production ratio. Existing model has been further modified by giving due weightage to the effect of income distribution among low, middle and high income groups of population on the dynamics of demand. Attempt has also been made to study the sensitivity of the economy, and hence the consumer demand, to changes in the saving to consumption ratio. The positive effect of increase in saving on capital formation on the one side, and negative effect of decrease in demand on the other side, has been discussed.
For four years, the authers have been studying agricultural products markets with this year a development on lumber market. Search goals are not only to understand market working processes but also to define for each of then the M.I.S. necessary to permit some control by interprofessional organisations specially on price levels. The paper presents in a first step two building model approaches: One is a pragmatic approach, formalised by Buffa, Cuzo, Bonini, Boulden, Cetenick, Rosenzweig, on San Diego meeting, A.M.A., in 1970, the other is a theoretical approach by Bross, Schoderbeck, New -York in 1971, and Kaplan, Scranton in 1964. In a second type, the use of System Dynamics approach is confronted with these two first methods specially on noted research area, In conclusion, results of our models are discussed.