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A complex adaptive systems approach for productive efficiency analysis: building blocks and associative inferences

Author

Listed:
  • Francis L. Dougherty

    (Virginia Polytechnic Institute and State University)

  • Nathaniel P. Ambler

    (Virginia Polytechnic Institute and State University)

  • Konstantinos P. Triantis

    (Virginia Polytechnic Institute and State University)

Abstract

Linkages between complex adaptive systems (CAS) thinking and efficiency analysis are in their infancy. This paper associates the basic building blocks of the CAS “flocking” metaphor with the essential building blocks of the data envelopment analysis (DEA) form of productive efficiency analysis. The linkage between these paradigms is made within an agent-based modeling framework we have named the complex adaptive productive efficiency model. Within this framework DEA “decision-making units” (DMUs) representing business units within a management system, are modeled as agents and are therefore known as agent DMU’s (ADMUs). Guided by the three fundamental rules inherent in the flocking metaphor, ADMUs “align” with other ADMUs to achieve mutual protection and reduce risks. They “cohere” with the most efficient ADMUs among them to achieve the greatest possible efficiency in the least possible time. And they “separate” themselves for one another just enough to maintain diversity of operations and avoid unnecessary competition among business units of the management system. Analysis of the resulting patterns of ADMU behavior over time enable policy insights measured against benchmarks of productive efficiency that are both intuitive and evidence-based.

Suggested Citation

  • Francis L. Dougherty & Nathaniel P. Ambler & Konstantinos P. Triantis, 2017. "A complex adaptive systems approach for productive efficiency analysis: building blocks and associative inferences," Annals of Operations Research, Springer, vol. 250(1), pages 45-63, March.
    • Handle: RePEc:spr:annopr:v:250:y:2017:i:1:d:10.1007_s10479-016-2134-3
    DOI: 10.1007/s10479-016-2134-3
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    References listed on IDEAS

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    1. Cecilio Mar-Molinero & Diego Prior & Maria-Manuela Segovia & Fabiola Portillo, 2014. "On centralized resource utilization and its reallocation by using DEA," Annals of Operations Research, Springer, vol. 221(1), pages 273-283, October.
    2. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    3. Warren Vaneman & Konstantinos Triantis, 2003. "The Dynamic Production Axioms and System Dynamics Behaviors: The Foundation for Future Integration," Journal of Productivity Analysis, Springer, vol. 19(1), pages 93-113, January.
    4. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, December.
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    Cited by:

    1. Victor Dragotă & Camelia Delcea, 2019. "How Long Does It Last to Systematically Make Bad Decisions? An Agent-Based Application for Dividend Policy," JRFM, MDPI, vol. 12(4), pages 1-34, November.
    2. Herrera-Restrepo, Oscar & Triantis, Konstantinos, 2019. "Enterprise design through complex adaptive systems and efficiency measurement," European Journal of Operational Research, Elsevier, vol. 278(2), pages 481-497.

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