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Organizational Response: The Cost Performance Tradeoff

Author

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  • Zhiang Lin

    (The Hong Kong University of Science & Technology, Department of Management and Organizations, Clear Water Bay, Kowloon, Hong Kong)

  • Kathleen M. Carley

    (Carnegie Mellon University, Department of Social and Decision Sciences, Pittsburgh, Pennsylvania 15213)

Abstract

Organizations constantly face a dynamic environment where they must respond both quickly and accurately in order to survive. In this paper, we examine the issue: do organizations need to employ costly designs in order to exhibit high performance in a dynamic situation. In the context of a computational framework we derive a set of logically consistent propositions about the interrelationship among task, opportunities for review, training, and cost and their relative impact on organizational performance. Our analyses indicate that complex organizational designs have drawbacks and design is often not the dominant factor affecting performance. The relationship between organizational complexity (hence cost) and performance is complex and depends on the level of time pressure, training, and the task environment. Within the context of the computational framework, we find that the benefits of re-thinking decisions and of matching the organizational design to the task environment are questionable. Further, these results suggest that applying scarce resources to mitigate the adverse impact of time pressure may have more impact on performance than using those resources to support a more complex organizational design.

Suggested Citation

  • Zhiang Lin & Kathleen M. Carley, 1997. "Organizational Response: The Cost Performance Tradeoff," Management Science, INFORMS, vol. 43(2), pages 217-234, February.
    • Handle: RePEc:inm:ormnsc:v:43:y:1997:i:2:p:217-234
    DOI: 10.1287/mnsc.43.2.217
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    Citations

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    Cited by:

    1. Stevo Pavićević & Thomas Keil, 2021. "The role of procedural rationality in debiasing acquisition decisions of overconfident CEOs," Strategic Management Journal, Wiley Blackwell, vol. 42(9), pages 1696-1715, September.
    2. Yitzhak Samuel & Chanoch Jacobsen, 1997. "A System Dynamics Model of Planned Organizational Change," Computational and Mathematical Organization Theory, Springer, vol. 3(3), pages 151-171, September.
    3. Giampio Bracchi & Chiara Francalanci, 1997. "A Model for Information Processing Capacity: Formalizing the Impact of Structural and Information System Choices on Organizational Performance," Computational and Mathematical Organization Theory, Springer, vol. 3(3), pages 173-198, September.
    4. Nicolaj Siggelkow & Jan W. Rivkin, 2005. "Speed and Search: Designing Organizations for Turbulence and Complexity," Organization Science, INFORMS, vol. 16(2), pages 101-122, April.
    5. Thorbjørn Knudsen & Daniel A. Levinthal, 2007. "Two Faces of Search: Alternative Generation and Alternative Evaluation," Organization Science, INFORMS, vol. 18(1), pages 39-54, February.
    6. Zhiang (John) Lin & Xia Zhao & Kiran M. Ismail & Kathleen M. Carley, 2006. "Organizational Design and Restructuring in Response to Crises: Lessons from Computational Modeling and Real-World Cases," Organization Science, INFORMS, vol. 17(5), pages 598-618, October.
    7. Olan, Femi & Ogiemwonyi Arakpogun, Emmanuel & Suklan, Jana & Nakpodia, Franklin & Damij, Nadja & Jayawickrama, Uchitha, 2022. "Artificial intelligence and knowledge sharing: Contributing factors to organizational performance," Journal of Business Research, Elsevier, vol. 145(C), pages 605-615.
    8. Edoardo Mollona & Andrea Marcozzi, 2009. "FirmNet: the scope of firms and the allocation of task in a knowledge-based economy," Computational and Mathematical Organization Theory, Springer, vol. 15(2), pages 109-126, June.
    9. Edoardo Mollona & Andrea Marcozzi, 2009. "Self-emerging coordination mechanisms for knowledge integration processes," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 8(2), pages 223-241, December.
    10. Jerker. Denrell & Christina. Fang & Daniel A. Levinthal, 2004. "From T-Mazes to Labyrinths: Learning from Model-Based Feedback," Management Science, INFORMS, vol. 50(10), pages 1366-1378, October.
    11. Zhiang Lin & Chun Hui, 1997. "Adapting to the Changing Environment: A Theoretical Comparison of Decision Making Proficiency of Lean and Mass Organization Systems," Computational and Mathematical Organization Theory, Springer, vol. 3(2), pages 113-142, June.

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