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Research Note ---How Semantics and Pragmatics Interact in Understanding Conceptual Models

Author

Listed:
  • Palash Bera

    (John Cook School of Business, Saint Louis University, St. Louis, Missouri 63108)

  • Andrew Burton-Jones

    (University of Queensland, UQ Business School, Brisbane, QLD 4072, Australia)

  • Yair Wand

    (Sauder School of Business, University of British Columbia, Vancouver, British Columbia, V6T 1Z2, Canada)

Abstract

Underlying the design of any information system is an explicit or implicit conceptual model of the domain that the system supports. Because of the importance of such models, researchers and practitioners have long focused on how best to construct them. Past research on constructing conceptual models has generally focused on their semantics (their meaning), to discover how to convey meaning more clearly and completely, or their pragmatics (the importance of context in model creation and use), to discover how best to create or use a model in a given situation. We join these literatures by showing how semantics and pragmatics interact. Specifically, we carried out an experiment to examine how the importance of clear semantics in conceptual models---operationalized in terms of ontological clarity---varies depending on the pragmatics of readers' knowledge of the domain shown in the model. Our results show that the benefit of ontological clarity on understanding is concave downward (follows an inverted- U ) as a function of readers' prior domain knowledge. The benefit is greatest when readers have moderate knowledge of the domain shown in the model. When readers have high or low domain knowledge, ontological clarity has no apparent benefit. Our study extends the theory of ontological clarity and emphasizes the need to construct conceptual models with readers' knowledge in mind.

Suggested Citation

  • Palash Bera & Andrew Burton-Jones & Yair Wand, 2014. "Research Note ---How Semantics and Pragmatics Interact in Understanding Conceptual Models," Information Systems Research, INFORMS, vol. 25(2), pages 401-419, June.
    • Handle: RePEc:inm:orisre:v:25:y:2014:i:2:p:401-419
    DOI: 10.1287/isre.2014.0515
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    References listed on IDEAS

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    Cited by:

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    2. Lawrence Bunnell & Kweku-Muata Osei-Bryson & Victoria Y. Yoon, 2020. "RecSys Issues Ontology: A Knowledge Classification of Issues for Recommender Systems Researchers," Information Systems Frontiers, Springer, vol. 22(6), pages 1377-1418, December.
    3. Palash Bera, 2021. "Interactions between Analysts in Developing Collaborative Conceptual Models," Information Systems Frontiers, Springer, vol. 23(3), pages 561-573, June.
    4. Roger Clarke & Andrew Burton-Jones & Ron Weber, 2016. "On the Ontological Quality and Logical Quality of Conceptual-Modeling Grammars: The Need for a Dual Perspective," Information Systems Research, INFORMS, vol. 27(2), pages 365-382, June.
    5. Pedro Antunes & Nguyen Hoang Thuan & David Johnstone, 2022. "Nature and purpose of visual artifacts in design science research," Information Systems and e-Business Management, Springer, vol. 20(3), pages 515-550, September.
    6. Jan Mendling & Jan Recker & Hajo A. Reijers & Henrik Leopold, 2019. "An Empirical Review of the Connection Between Model Viewer Characteristics and the Comprehension of Conceptual Process Models," Information Systems Frontiers, Springer, vol. 21(5), pages 1111-1135, October.

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