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Model Integration and Modeling Languages: A Process Perspective

Author

Listed:
  • Jeffrey E. Kottemann

    (School of Business Administration, The University of Michigan, Ann Arbor, Michigan 48109-1234)

  • Daniel R. Dolk

    (Department of Administrative Sciences, Naval Postgraduate School, Monterey, California 93943)

Abstract

Development of large-scale models often involves—or, certainly could benefit from—linking existing models. This process is termed model integration and involves two related aspects: (1) the coupling of model representations, and (2) the coupling of the processes for evaluating, or executing, instances of these representations. Given this distinction, we overview model integration capabilities in existing executable modeling languages, discuss current theoretical approaches to model integration, and identify the limiting assumptions implicitly made in both cases. In particular, current approaches assume away issues of dynamic variable correspondence and synchronization in composite model execution. We then propose a process-oriented conceptualization and associated constructs that overcome these limiting assumptions. The constructs allow model components to be used as building blocks for more elaborate composite models in ways unforeseen when the components were originally developed. While we do not prove the sufficiency of the constructs over the set of all model types and integration configurations, we present several examples of model integration from various domains to demonstrate the utility of the approach.

Suggested Citation

  • Jeffrey E. Kottemann & Daniel R. Dolk, 1992. "Model Integration and Modeling Languages: A Process Perspective," Information Systems Research, INFORMS, vol. 3(1), pages 1-16, March.
    • Handle: RePEc:inm:orisre:v:3:y:1992:i:1:p:1-16
    DOI: 10.1287/isre.3.1.1
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    Citations

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    Cited by:

    1. Kaushal Chari, 2002. "Model Composition Using Filter Spaces," Information Systems Research, INFORMS, vol. 13(1), pages 15-35, March.
    2. Amit V. Deokar & Omar F. El-Gayar, 2011. "Decision-enabled dynamic process management for networked enterprises," Information Systems Frontiers, Springer, vol. 13(5), pages 655-668, November.
    3. Srinivasan, Ananth & Sundaram, David, 2000. "An object relational approach for the design of decision support systems," European Journal of Operational Research, Elsevier, vol. 127(3), pages 594-610, December.
    4. David Schuff & Karen Corral & Robert D. St. Louis & Greg Schymik, 0. "Enabling self-service BI: A methodology and a case study for a model management warehouse," Information Systems Frontiers, Springer, vol. 0, pages 1-14.
    5. Makowski, Marek, 2005. "A structured modeling technology," European Journal of Operational Research, Elsevier, vol. 166(3), pages 615-648, November.
    6. Gordon P. Wright & Alok R. Chaturvedi & Radha V. Mookerjee & Susan Garrod, 1998. "Integrated Modeling Environments in Organizations: An Empirical Study," Information Systems Research, INFORMS, vol. 9(1), pages 64-84, March.
    7. Therani Madhusudan, 2007. "A web services framework for distributed model management," Information Systems Frontiers, Springer, vol. 9(1), pages 9-27, March.
    8. David Schuff & Karen Corral & Robert D. St. Louis & Greg Schymik, 2018. "Enabling self-service BI: A methodology and a case study for a model management warehouse," Information Systems Frontiers, Springer, vol. 20(2), pages 275-288, April.

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