Modeling and Evaluation of Information Systems

  • Oscar Barros


A general graphical model for organizational information Systems (IS) is proposed. This model is based on systems theory and general patterns of organizational processes regulation derived from empirical observation and experience. It includes generalized decision making and data manipulation functions to regulate generalized organizational processes through flows of information. The general IS model is shown to serve as a basic pattern to approach the design of any IS. In particular, it is shown that alternative IS structures or designs can be derived from it. Structures not only include information that will be computerized, but also the prescription of the decision making behavior of the information users. This problem of jointly studying alternative behavior-sets of information or structures can be related to and supported by organizational design theory. The existence of alternatives leads to a problem of evaluation for which a quantitative modeling approach is proposed. Connection with organization theory allows base modeling on the measuring of organizational effectiveness of each alternative.


Information System Material Requirement Average Inventory Slack Resource Reorder Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Albrecht, A. J., and Gaffney, J. E., 1983, Software Functions, Source Lines of Code, and Development Effort Prediction: A Software Science Validation, IEEE Trans. Software Eng., Vol. SE-9, pp. 639–648.Google Scholar
  2. Alford, M., 1985, SREM at the Age Eight: The Distributed Computing Design System, Computer, Vol. 18, pp. 36–46.CrossRefGoogle Scholar
  3. Ashby, R. W., 1970, An Introduction to Cybernetics, Chapman & Hall Ltd, London.Google Scholar
  4. Barros, O., 1975, Some Ideas on a Methodology for the Logical Design of Information Systems, Management Datamatics, Vol. 4, pp. 49–56.Google Scholar
  5. Barros, O., 1984, Alternative Architectures in Information System Design in Beyond Productivity: Information Systems for Organizational Effectiveness, Th.M.A., Bemelmans, ed., North Holland, Amsterdam.Google Scholar
  6. Barros, O., 1987, Information Requirements and Alternatives in Information System Design, Information Systems, Vol. 12, pp. 125–136.CrossRefGoogle Scholar
  7. Beer, S., 1972, Brain of the Firm, Allen Lane, The Penguin Press, London.Google Scholar
  8. Berzins, V., and Gray, M., 1985, Analysis and Design “MSG.84: Formalizing Functional Specifications”, IEEE Trans. Software Eng., Vol. SE-11, pp. 657–670.Google Scholar
  9. Cameron, J. R., 1986, An Overview of JSD, IEEE Trans. Software Eng., Vol. SE-12, pp. 222–240.Google Scholar
  10. Carlson, W. M., 1979, Business Information Analysis and Integration Technique (BIAIT)–The New Horizon, Data Base, Vol. 10, pp. 3–9.Google Scholar
  11. Chen, P. P., 1976, The Entity-Relationship Model–Toward a Unified View of Data, ACM Transactions on Data Base Systems, Vol. 1, pp. 9–36.CrossRefGoogle Scholar
  12. Davis, G. B., 1982, Strategies for Information Requirements Determination, IBM Syst. J., Vol. 21, pp. 4–30.CrossRefGoogle Scholar
  13. De Marco, T., 1978, Structured Analysis and System Specification, Yourdon Press, New York (1978).Google Scholar
  14. Emery, F. E., 1979, Systems Thinking, Penguin Books, Baltimore.Google Scholar
  15. Emery, J. C., 1969, Organizational Planning and Control Systems, MacMillan, New York.Google Scholar
  16. Execucom Systems Corp., 1983, IFPS/Optimum User’s Manual, Rel. 3.0, Austin, Texas. Execucom Systems Corp., 1987, IFPS User’s Manual, Rel. 11. 0, Austin, Texas.Google Scholar
  17. Forrester, J., 1961, Industrial Dynamics, The MIT Press, Cambridge, Mass.Google Scholar
  18. Forrester, J., 1970, Principles of Systems, Wright Allen Press, New York.Google Scholar
  19. Gailbraith, J. R., 1977, Organization Design, Addison-Wesley, Reading, Mass.Google Scholar
  20. Hamilton, M., and Zelding, S., 1976, Higher Order Software–A Methodology for Defining Software, IEEE Trans. of Software Eng., Vol. SE-2, pp. 9–32.Google Scholar
  21. Horning, J J, and Randell, B., 1973, Process Structuring, Computer Surveys, Vol. 5, pp. 5–30.MATHCrossRefGoogle Scholar
  22. Ives, B., and Dearmonth, G. P., 1984, The Information System as a CompetitiveGoogle Scholar
  23. Weapon, Comm. ACM,Vol. 27, pp. 1193–1201.Google Scholar
  24. Johnson, L. A., and Montgomery, D. C., 1974, Operations Research in Production Planning Scheduling and Control, Wiley, New York.Google Scholar
  25. Kerner, D. V., 1979, Business Information Characterization Study, Data Base, Vol. 10, pp. 10–17.Google Scholar
  26. Lorsch, J. W., and Lawrence, P. R., 1972, Organization Planning, Richard Irwin and The Dorsey Press, Homewood, Illinois.Google Scholar
  27. Malone, T. W., 1987, Modeling Coordination in Organizations and Markets, Management Science, Vol. 33, pp. 1317–1332.CrossRefGoogle Scholar
  28. Marschack, J., 1954, Towards an Economic Theory of Organization and Information, Decision Processes, Thrall, R. M., Commbs, G. H., and Davis, R. L., eds., Wiley, New York.Google Scholar
  29. Marschack, J., 1968, Economics of Inquiring, Communicating and Deciding, American Economic Review, Vol. 58, pp. 1–8.Google Scholar
  30. Martin, J., and Finkelstein, C., 1981, Information Engineering, Savant Institute, London. Melcher, A. J., 1976, Structure and Process of Organizations, Prentice Hall, Englewood Cliffs, N.J.Google Scholar
  31. Minsky, M., 1967, Computation: Finite and Infinite Machines, Prentice Hall, Englewood Cliffs, N.J. Peterson, J. L., 1977, Petri Nets, Computing Surveys, Vol. 9, pp. 224–252.Google Scholar
  32. Pugh, A. L., III, 1961, Dynamo User’s Manual, The MIT Press, Cambridge, Mass.Google Scholar
  33. Reiman, B. C., and Waren, A. D., 1985, User-oriented Criteria for the Selection of DSS Software, Comm. ACM, Vol. 28, pp. 1966–1980.CrossRefGoogle Scholar
  34. Ross, D. T., 1977, Structured Analysis (SA.): A Language for Communicating Ideas, IEEE Trans. Software Eng., Vol. SE-3, pp. 16–34.Google Scholar
  35. Roy, A., De Falomir, E. E., and Lasdon, L., 1982, An Optimization-Based Decision Support System for a product Mix Problem, Interfaces, Vol. 12, pp. 26–33.CrossRefGoogle Scholar
  36. Roy, A., Lasdon, L. S., and Lordeman, I., 1986, Extending Planning Languages to include Optimization Capabilities, Management Science, Vol. 32, pp. 360–373.CrossRefGoogle Scholar
  37. Silver, E., and Meal, H,. 1970, A Simple Modification of the EOQ for the Case of Varying Demand Rate and Discrete Opportunities for Replenishment, Production and Inventory Management, Vol. 14, pp. 64–73.Google Scholar
  38. Simon, H., 1970, The Sciences of the Artificial, MIT Press, Cambridge, Mass.Google Scholar
  39. Verrijn-Stuart, A. A., 1986, Themes and Trends in Information Systems, Trens in Information Systems, Langefors, B., Verrijn-Stuart, A. A., and Bracchi, G., eds., North Holland, Amsterdam.Google Scholar
  40. Yourdon, E., and Constantine, L. L., 1979, Structured Design, Prentice Hall, Englewood Cliffs, N.J.MATHGoogle Scholar
  41. Zachman, J. A., 1979, Business Systems Planning and Business Information Control Study: A Comparison, IBM Syst. J., Vol. 21, pp. 31–53.CrossRefGoogle Scholar
  42. Zave, P., 1982, An Operational Approach to Requirements Specification for Embedded Systems, IEEE Trans. Software Eng., Vol. SE-8, pp. 250–269.Google Scholar

Copyright information

© Plenum Press, New York 1990

Authors and Affiliations

  • Oscar Barros
    • 1
  1. 1.Departamento de Ingenieria IndustrialUniversidad de ChileSantiagoChile

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