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Information Acquisition and Mental Models: An Investigation into the Relationship Between Behaviour and Learning

Author

Listed:
  • Betty Vandenbosch

    (Weatherhead School of Management, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, Ohio 44106-7235)

  • Chris Higgins

    (Western Business School, University of Western Ontario, London, Ontario, Canada N5Y 3H6)

Abstract

A cognitive learning perspective is used to develop and test a model of the relationship between information acquisition and learning in the executive support systems (ESS) context. The model proposes two types of learning: mental model maintenance in which new information fits into existing mental models and confirms them; and mental model building in which mental models are changed to accommodate new information. It also proposes that information acquisition objectives determine the type of learning that is possible. When ESS are used to answer specific questions or solve well-defined problems, they help to fine-tune operations and verify assumptions---in other words, they help to maintain current mental models. However, ESS may be able to challenge fundamental assumptions and help to build new mental models if executives scan through them to help formulate problems and foster creativity.Thirty-six interviews with executive ESS users at seven organizations and a survey of 361 users at 18 additional organizations are used to develop scales to measure the model's constructs and provide support for its relationships. These results support the model's prediction that mental model building is more likely with scanning than with focused search. ESS also appear to contribute to mental model maintenance much more often than they do to mental model building. Without a clear focus on mental model building, it seems that business as usual is the more likely outcome.

Suggested Citation

  • Betty Vandenbosch & Chris Higgins, 1996. "Information Acquisition and Mental Models: An Investigation into the Relationship Between Behaviour and Learning," Information Systems Research, INFORMS, vol. 7(2), pages 198-214, June.
    • Handle: RePEc:inm:orisre:v:7:y:1996:i:2:p:198-214
    DOI: 10.1287/isre.7.2.198
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    Cited by:

    1. Chong Lau & Brigitte Oger, 2019. "The effects of comprehensive performance measurement systems on information overload, job-relevant information, role clarity and procedural fairness," Working Papers halshs-02300746, HAL.
    2. Maryam Alavi & Dorothy E. Leidner, 2001. "Research Commentary: Technology-Mediated Learning—A Call for Greater Depth and Breadth of Research," Information Systems Research, INFORMS, vol. 12(1), pages 1-10, March.
    3. Ghiyoung Im & Arun Rai, 2014. "IT-Enabled Coordination for Ambidextrous Interorganizational Relationships," Information Systems Research, INFORMS, vol. 25(1), pages 72-92, March.
    4. Miles M Yang & Feifei Yang & Tingru Cui & Ying-Chu Cheng, 2019. "Analysing the dynamics of mental models using causal loop diagrams," Australian Journal of Management, Australian School of Business, vol. 44(3), pages 495-512, August.
    5. Manis, K.T. & Madhavaram, Sreedhar, 2023. "AI-Enabled marketing capabilities and the hierarchy of capabilities: Conceptualization, proposition development, and research avenues," Journal of Business Research, Elsevier, vol. 157(C).
    6. Dong-Gil Ko & Alan R. Dennis, 2011. "Profiting from Knowledge Management: The Impact of Time and Experience," Information Systems Research, INFORMS, vol. 22(1), pages 134-152, March.
    7. Henri Barki & Ryad Titah & Céline Boffo, 2007. "Information System Use--Related Activity: An Expanded Behavioral Conceptualization of Individual-Level Information System Use," Information Systems Research, INFORMS, vol. 18(2), pages 173-192, June.
    8. Kevin Bauer & Moritz von Zahn & Oliver Hinz, 2023. "Expl(AI)ned: The Impact of Explainable Artificial Intelligence on Users’ Information Processing," Information Systems Research, INFORMS, vol. 34(4), pages 1582-1602, December.
    9. Lau, Chong M. & Roopnarain, Ketvi, 2014. "The effects of nonfinancial and financial measures on employee motivation to participate in target setting," The British Accounting Review, Elsevier, vol. 46(3), pages 228-247.
    10. Lauri Wessel & Martin Gersch & Erik Harloff, 2017. "Talking Past Each Other," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 59(1), pages 23-40, February.
    11. Lau, Chong M. & Scully, Glennda & Lee, Alina, 2018. "The effects of organizational politics on employee motivations to participate in target setting and employee budgetary participation," Journal of Business Research, Elsevier, vol. 90(C), pages 247-259.
    12. O’Neil, Glenn & Bauer, Martin W., 2018. "Pathways to use of communication campaigns’ evaluation findings within international organizations," Evaluation and Program Planning, Elsevier, vol. 69(C), pages 82-91.
    13. Alex Osei‐Kojo & Paul Lawer Kenney & Clement Mensah Damoah & Albert Ahenkan, 2022. "Collective learning and COVID‐19 mitigation in Ghana," Review of Policy Research, Policy Studies Organization, vol. 39(3), pages 255-281, May.
    14. Jim Nelson, 2021. "Hunch Mining," International Journal of Knowledge Management (IJKM), IGI Global, vol. 17(3), pages 1-14, July.
    15. Kevin Bauer & Andrej Gill, 2024. "Mirror, Mirror on the Wall: Algorithmic Assessments, Transparency, and Self-Fulfilling Prophecies," Information Systems Research, INFORMS, vol. 35(1), pages 226-248, March.

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